[User] Please transcribe this text

[Assistant] Project brush there. Reason why is because the sphere brush will only grab the, for example, this part and then in a sphere radius from it, it will move the hairs with it. But with projected, it will move everything from front to back pretty much. Right? So let's just do it with that. So make this a little bit longer. Just like that. Beautiful.


[User] Please transcribe this text

[Assistant] Beautiful, beautiful, beautiful, beautiful. Alright, something like that. Looks quite nice. And let's crank this up a little bit too. Make it nice and intersect. And let's go back to the comb brush and move some of these hairs out a bit more. Something like that.


[User] Please transcribe this text

[Assistant] So it's more random and more beautiful. You write something like that, that looks like quite a nice intersection.


[User] Please transcribe this text

[Assistant] Quite a nice transition, a nice flow. I'm gonna go back to object mode, and now we're gonna start working on some of those geometry nodes. Right, so I'm gonna drag this to the left, and set the right window to geometry nodes editor.


[User] Please transcribe this text

[Assistant] And now, we have our Deformed Curves on Surface node, and that is usually what comes with adding the curves onto your surface, right? Because it is deforming curves on the surface, the surface being this little sphere, right? If we move the sphere, everything will move with it as well.


[User] Please transcribe this text

[Assistant] So, that is something all of these systems have, and let's rename the long hairs. Let's call it the mains. Here we go.


[User] Please transcribe this text

[Assistant] Alright, so we can even order these by sending a little one point in front of it. So they are nicely in order. Beautiful.


[User] Please transcribe this text

[Assistant] And now we can start tweaking this, right? And I'm going to swipe this little window to the bottom and set this to the asset browser. And we're going to set this to the essentials and then hair.


[User] Please transcribe this text

[Assistant] Right, so this is all the hair that comes with Blender. They included it in, I think, 3.5, and it works incredible. So we're gonna be using a lot of these to actually tweak our system. Right, so let's see. I'm gonna move that up.


[User] Please transcribe this text

[Assistant] And move this a bit to the right. There we go. So we have a bit more space to work with. There we go.


[User] Please transcribe this text

[Assistant] Right, so we don't really need geometry nodes themselves. We're not gonna be tweaking them all that much, but we will be tweaking them just a little bit at some point.


[User] Please transcribe this text

[Assistant] Alright, so first things first, let's add a little bit of a curve radius. Let's go to the rendered view, and I prefer starting off with a clean plate, which means that the best way to see what your system looks like is by already having the correct radius of your hairs. Alright, so what I'm gonna do is I'm going to go to my


[User] Please transcribe this text

[Assistant] Note there that says set hair curve profile, right? So that is nice. So that's already gives us a new radius of the hair is a little bit already a little bit thinner.


[User] Please transcribe this text

[Assistant] So we can now set this to a value we like, for example 0.003.


[User] Please transcribe this text

[Assistant] Right, so that is nice and thin hair. That is something we can work with for sure. Now for the face hairs, we wanna do the same thing. And I'm not gonna use the same geometry node system, so I'm not just gonna use this one. I'm gonna drag in a new one. Reason why?


[User] Please transcribe this text

[Assistant] Beautiful, so now I want these hairs to be a little bit thicker already. Uhm, so the reason why is because even though they may be the same thickness in real life, I'm gonna add a little bit of thickness to those hairs because


[User] Please transcribe this text

[Assistant] It will look a bit more natural. And that way we won't have to fill up the entire face with more and more hairs. We can just crank the thickness up a little bit and it will still look quite natural. Right, so I'm gonna set this radius to about .005.


[User] Please transcribe this text

[Assistant] Right? And it should still look quite decent, right? You can see maybe they are a little bit thick, but we can take a look at that later. Okay?


[User] Please transcribe this text

[Assistant] So, make sure that, well, you have the render engine set that you want to use. I use Cycles. I have it set on CPU, that's not the right way. GPU is much quicker. And now we only have the beards, the neck, the mains left, so drag your curve profile on there as well. And...


[User] Please transcribe this text

[Assistant] Let's set this to 0.003 as well. Right, because those are long hairs and this looks fine. Right, we can even crank that down later, maybe we should already. 0.002. Just a little bit, because they are long hairs.


[User] Please transcribe this text

[Assistant] Alright, something like this. So now we can start working with all of these assets and see how we can achieve the best result that we can.


[User] Please transcribe this text

[Assistant] Alright, so first things first, for the face hairs, we still see some skin through it, so we need some extra hairs. So I'm just gonna add a duplicate hairs there, let's see where it is. Duplicate, duplicate.


[User] Please transcribe this text

[Assistant] I always struggle to find the right ones. Uhm, and there it is. Just drag that one on.


[User] Please transcribe this text

[Assistant] And you can see initially we get 10 hairs for each hair we already have in there. Alright, so this already is going to depend a little bit on what your system can handle.


[User] Please transcribe this text

[Assistant] Right, uhm, my system is quite powerful, uhm, it has no issues with 10 whatsoever. But you can also set this to 3, it should still be quite filling up the face. But I'm gonna leave this at 10 for now.


[User] Please transcribe this text

[Assistant] And we can even crank it up later if we really want that.


[User] Please transcribe this text

[Assistant] Okay, so what I see initially is that at those side parts we don't really have a smooth transition. So I'm gonna go back to solid view. I'm gonna select my face hairs, go to skilled mode and I'm gonna just sneak hook out some of those hairs on the sides and set that to sphere as well. Let's disable the duplicate hairs for a sec.


[User] Please transcribe this text

[Assistant] And let's just drag this out a little bit, and make sure that your mouse is nice and on the side, so you don't drag all of it out. Just some of these endpoints. Alright, just like this.


[User] Please transcribe this text

[Assistant] Same for the other sides. Drag it all out a little bit. Here we go. Rate those nice transitions that you're looking for.


[User] Please transcribe this text

[Assistant] Beautiful, beautiful, beautiful. And remember that every hair you now drag out is going to have 10 children hairs in that geomaterno system that we just added. Right, so don't add too many there. Something like this is already quite decent. Decent in my opinion. Here we go.


[User] Please transcribe this text

[Assistant] There as well a little bit, because there we also have quite a hard transition. Here we go. Alright, that looks quite, quite nice. There as well a little bit. Here too, and there too.


[User] Please transcribe this text

[Assistant] Right, I think that should be fine. So let's go back to front view, and object mode, and let's see it with the Duplicate Harrison.


[User] Please transcribe this text

[Assistant] Alright, so already we have much more of an actual kind of transition between those hairs and we can still sculpt them later, don't worry.


[User] Please transcribe this text

[Assistant] Right, so now I just wanna take a look at those.


[User] Please transcribe this text

[Assistant] The face, or sorry, the top hairs and the side hairs.


[User] Please transcribe this text

[Assistant] Because there's not a lot that we really need to change there in the center, because the hair doesn't really have much room and much length to really do something. It can't really clump together. It can't really curl. All it can do is pretty much stick out, just like you can't really shape a busket, right? You can...


[User] Please transcribe this text

[Assistant] What do we want to add there? Well, for starters, I usually want to add some kind of a noise profile, right? So I will start with adding some hair curve noise. Drag that on top of the hair there.


[User] Please transcribe this text

[Assistant] And I think I added it to the base hairs, yes I did. Let's drag it to the outer hairs. There we go. Right, so now we can control the actual noise there. And there is some different values that we can actually work with.


[User] Please transcribe this text

[Assistant] So what we usually try to do is work with a factor, so how strongly this affects our hair, and you can see, uhm, zero is basically straight, one is gonna be noisy, and the distance from how much they move away from the center as well. Right, so I still want some kind of, uh,


[User] Please transcribe this text

[Assistant] So I'm not gonna crank up the distance too much. So something like this works fine. And then for the shape, this is pretty much where it starts to add the noise on the hair. 0.5 is half way, 0.7 is going to be 0.7 of the way of the hair.


[User] Please transcribe this text

[Assistant] And, well, you can pretty much define where it starts having the noise. So the starting points of the hair, I don't want to add too much noise to, that's where the hair is the thickest.


[User] Please transcribe this text

[Assistant] Right? The hair is the thickest as where it comes right out of your skin. That is why some people think if you shave, your hairs become thicker, while actually you just cut your hairs off at a thicker point and they will feel thicker.


[User] Please transcribe this text

[Assistant] Right? At least I think that's where it comes from. And then we can simply just crank up the skill if we want this to be stronger.


[User] Please transcribe this text

[Assistant] Right, for example, like this. And there we go. So we can also change the seat if you have a specific kind of part that you wanna have more noise in. Sometimes this will change that and will perform that for you.


[User] Please transcribe this text

[Assistant] Okay, so for the skill, let's see, maybe we want a little bit more. Here we go.


[User] Please transcribe this text

[Assistant] And I think we can leave it at that for now. Right, so we have a little bit of noise going on which looks quite beautiful. Right, so we still want some more hairs there at the side as well. You can see that those parts on the sides are also quite dense and first you can look right through them.


[User] Please transcribe this text

[Assistant] So I'm gonna add another duplicate node on there. So duplicate hair curves. Here we go. And right away you can see we add a lot of new hair. So let's set this on 6 instead.


[User] Please transcribe this text

[Assistant] And that looks quite good actually. Alright, quite nice. And I think the top hair is actually a little bit, maybe too short. So how do we change that? Well, just select the hair and go back to Sculpt Mode. And just drag that out a little bit more.


[User] Please transcribe this text

[Assistant] Like this for example. If you want this to be longer, I'm gonna disable Y and just make this a bit more.


[User] Please transcribe this text

[Assistant] Pointy, I guess. And maybe have some more randomness there. Beautiful.


[User] Please transcribe this text

[Assistant] Alright, that should do the trick a bit more already. Okay, so next up, I wanna look at what else we can do with this hair. It is still maybe a little bit static.


[User] Please transcribe this text

[Assistant] So we can add another noise level right after the duplicate hair curves, right? So because right now the hairs that were there initially are just duplicated with the same kind of noise offset. But if we add another layer of noise, or let's do frizz actually.


[User] Please transcribe this text

[Assistant] Then all of those individual duplicated hairs are going to be phrased. Right, so if we drag this on top.


[User] Please transcribe this text

[Assistant] You can see that now each of those endpoints hairs are going to be frizzed a little bit, right? So you can see it happening. And we can even crank up the distance so they become more random there at the endpoints. Which may look just like you want.


[User] Please transcribe this text

[Assistant] Same thing like I told you with the, the noise profile, right? Something like this.


[User] Please transcribe this text

[Assistant] Looks quite nice, if you ask me. Uhm, so let's start working on this bottom layer. The mains of the cat. Because right now it looks, well, off. Right? So let's initially drag and duplicate hair curves on there. Beautiful. And let's start off with some noise as well. So drag your noise on there.


[User] Please transcribe this text

[Assistant] Something like that. And I think the shape should be 0.5 around that and the skill can be much stronger. Maybe something like that.


[User] Please transcribe this text

[Assistant] Right? I think that looks much better already. So one thing we forgot to add at the top hat, what we definitely need at this bigger area, is


[User] Please transcribe this text

[Assistant] The clumping, right? Clumping is very important in animals. Usually the hairs follow a bit more in the same direction for clumps, right? You can see that they actually clump together quite


[User] Please transcribe this text

[Assistant] It doesn't get dirty, it doesn't get wet, and if you have animals outside, hairs tend to clump even more together because you have dirt that makes it stick together, hair becomes wet, dries up, it becomes sticky, and it will just stick together more.


[User] Please transcribe this text

[Assistant] And so that is how you, well, what you have to figure out. So there is a clump note, so clump hair curve, just drag that on top.


[User] Please transcribe this text

[Assistant] And right away you can see that we get some clumping going on in those beard hairs. Now I think this clumping is too small. So how do we fix that? Uhm, well there's a very easy way. And we need to look at the structure of the geometry nodes here.


[User] Please transcribe this text

[Assistant] So we have a duplicate hair curves. If we disable that, we pretty much have the clumping that we want to have, right? There are quite big chunks, but if we enable this, then it's going to be clumping the duplicate hair curves instead.


[User] Please transcribe this text

[Assistant] So I'm just going to move this in front of our duplicate hair profile. And then we have much more of an actual clumping of the initial hair.


[User] Please transcribe this text

[Assistant] And then I'm going to add another clump hair curves right after, right? So now we get quite some strong looking clumping profiles, right? So if we disable that initial one, it still clumps, but it doesn't clump as hard as I would love it to be.


[User] Please transcribe this text

[Assistant] All right, so that is pretty much how that works. So let's disable the last one and work with the first one first because there is a lot of failures that we can tweak. And so the tip spread being one of them.


[User] Please transcribe this text

[Assistant] If you want your tips to be a bit more spread apart, it literally just does what it says. Alright, you can open it up a little bit. And you can also change the shape, right? So I want this to clump maybe a little bit earlier even. So point four.


[User] Please transcribe this text

[Assistant] And uhm, I think the rest of this is pretty much fine. We can try to change the plump offset a little bit. Maybe so the hair goes slightly outwards. Let's see.


[User] Please transcribe this text

[Assistant] Maybe just a little bit. There we go. And the distance falloff, we can even increase that if we want there to be less clumping the longer the hair gets. But let's look at our kitty. It doesn't really work that way. So right, let's just keep it at zero. And the dishing threshold, I think we can keep it at zero too.


[User] Please transcribe this text

[Assistant] So, that is the first one, let's re-enable the second one, right, because that is really where the clumping gets crazy.


[User] Please transcribe this text

[Assistant] And we want this to be quite strong like this, right? Keep a look at your reference image. You can see that the endpoints split a lot more than we have right now. So we can split those endpoints up a bit more. So tip spread, crank that a little bit up. There we go. And maybe the distance fall off a little bit as well. Note the clump offset, I guess.


[User] Please transcribe this text

[Assistant] Just to make this a bit more randomized. So something like that.


[User] Please transcribe this text

[Assistant] Uhm, that looks quite nice. And actually I'm going to go to my Duplicate Hairs and maybe set this to a bit higher values. Maybe 12. There we go. And that looks quite decent. So let's just hide our first clumping for a second. See how it looks.


[User] Please transcribe this text

[Assistant] Okay, that looks fine. And now for the final part, I'm gonna add at least some phrase in the end because, well, it still looks a little bit static.


[User] Please transcribe this text

[Assistant] For some, ehm, some of the points, so what I'm gonna do is just add a bit of frizz. And frizz usually just makes your endpoints of the hairs go a little bit crazy. Right, so let's just throw that on there. And let's see how it looks. Let's add a little bit of a distance, or not so much, but just a little bit. Just like that.


[User] Please transcribe this text

[Assistant] Right, it's beautiful. And the shape, I guess we can set it at like 0.75.


[User] Please transcribe this text

[Assistant] Nice, nice, nice. Right, so let's start actually adding an HDRI real quick because the shadow here is throwing me off a little bit. So let's go to the world settings, environment texture, open.


[User] Please transcribe this text

[Assistant] Go to where you store all of your HDRIs, which is going to be in my download folder. And you can find it by typing in HDR.


[User] Please transcribe this text

[Assistant] I'm guessing you can't see this screen, so that's why I'm telling what I'm doing. And then I'm gonna drag in this one.


[User] Please transcribe this text

[Assistant] That looks nice and I'm gonna delete the initial light point. Let's set this to shader and world for a second. Go to home. If you can't find your notes, you can press the home key and it will take you to your notes. And I'm gonna select this, hit control T and I'm gonna rotate this so we get some nice light values.


[User] Please transcribe this text

[Assistant] Alright, something like this looks quite cool to me.


[User] Please transcribe this text

[Assistant] Alright, so let's hide that background, so let's go to Film, in the Render Properties, and let's just select Transparent, so we don't get distracted by that background when we rotate our screen. Right? Beautiful, and you can see that the back of our head, the back of our kitty is bald. Alright, so that's fine.


[User] Please transcribe this text

[Assistant] And yeah, let's try working more with this. So now we actually get a more.


[User] Please transcribe this text

[Assistant] Accurate representation of what this looks like, right? So something that I feel like is missing is a little bit of that


[User] Please transcribe this text

[Assistant] High frequency, kind of twisting, curling there. It doesn't curl a lot, but you can see there's a slight kind of bending going on there. So how do we do that? Well, we just drag and drop, uh, let's say...


[User] Please transcribe this text

[Assistant] Curl hair curves. There we go. So from the start it's going to curl way too much. So let's go to the...


[User] Please transcribe this text

[Assistant] Actual node tree there, and let's just tweak that to be very, very subtle, right? So that means that we have to crank down the factor, of course, right? So we want this to be quite low.


[User] Please transcribe this text

[Assistant] Something that looks right to us. Something like this maybe. Let's see. Let's see how it looks.


[User] Please transcribe this text

[Assistant] Looks a little bit better, but I think now it is a bit too chaotic. It looks nice though, but the kitty is quite groomed. So let's just start with the factor to be a little bit less even. So it's just a little bit of that hint of bending.


[User] Please transcribe this text

[Assistant] Something like this maybe. Right, so it is very low, but you can still see it happening right there.


[User] Please transcribe this text

[Assistant] Right, so that looks quite alright, so let's say we wanna add some color or we wanna tweak some of these values and the one thing that I really do wanna add, by the way,


[User] Please transcribe this text

[Assistant] Is those pointy hairs that are sticking out of the head, right? So this is still, I'm guessing it's because it's a young cat, I'm not sure. But the hairs will still grow on the head, so these will grow as well. So maybe there are some hairs that's already a bit longer, I guess.


[User] Please transcribe this text

[Assistant] Uhm, but that's what I wanna recreate here too, because I kinda like it. So let's do that. It already has it a little bit, but not really those long ones. So how do we do that?


[User] Please transcribe this text

[Assistant] Well, you may think that the trim curves is not the way to go, but I'm gonna use that anyway because the trim hairs is also going to allow us to make hairs longer. Right? Quite nice. So let's drag and drop that on there, and right away you can see that it


[User] Please transcribe this text

[Assistant] Which is not what we want. So what we can do is just go to that geometry nodes tab. Let's select it. And let's just set the replace length to no.


[User] Please transcribe this text

[Assistant] There we go. So now you can see that if we change the length factor, you can see that we can actually trim our hairs down so they become shorter. But we want them to become longer.


[User] Please transcribe this text

[Assistant] So we can, we should be able to set this higher to 1.2 for example, but we don't want this to happen with every single hair.


[User] Please transcribe this text

[Assistant] But just with a selected bunch of them. And we can't really set that up in here, which is annoying. So the easiest way that I know how to do that is by going to the Geometry Notes editor of this Geo Notes. And all that we have to do now is find the, uhm, let's say,


[User] Please transcribe this text

[Assistant] Curves that are being used. Alright, so I'm going to go to the start. Usually when I can't figure out a geometry node right away, I will start from the start. We have a curve here that goes to the capture attribute, and it goes two ways here.


[User] Please transcribe this text

[Assistant] So this is the scaling part, we don't really need to touch that. And the top part, this is for repositioning the points for trimmed curves. Right, so this is the actual set position that controls our...


[User] Please transcribe this text

[Assistant] Right, so I think we should just be able to select some of the curves that are being transformed by this trim hair curves instead of all of them. Right, so if we drag this out and we set this to a random value.


[User] Please transcribe this text

[Assistant] Means that's, well, how much probability there is of a hair being selected. So if I set this all the way to one, all of the hairs are going to be.


[User] Please transcribe this text

[Assistant] We are even going to have more of those sticky hairs, just like I want it to be. Beautiful. And we can even control the random offset a little bit, right? So just to make none of them the exact same length. Make this point three.


[User] Please transcribe this text

[Assistant] 0.2 maybe, maybe 0.2. And we can set the probability, wow, probability to be just a little bit higher, and the length factor a little bit higher as well maybe.


[User] Please transcribe this text

[Assistant] Here we go. So now we have some actual hairs that are sticking out nicely off those sides. We actually get that nice.


[User] Please transcribe this text

[Assistant] Little hairs, right? And I like it. Right, so I want the same kind of trim system set up for the face, because there's not a lot of interesting stuff going on in the short hairs, but I wanna have some hairs that are actually maybe sticking out a lot.


[User] Please transcribe this text

[Assistant] Alright, so to do that, I'm first going to make everything a bit shorter, I think, because it still looks maybe a bit long. So let's add our general trim hair curves on there. So let's go back to the asset browser.


[User] Please transcribe this text

[Assistant] Drag and drop that on. And disable this. And we can now just create a little bit of a random offset of like points.


[User] Please transcribe this text

[Assistant] Six, right, so some of these hairs will be a bit shorter, and we can even set the length to like 0.8 to make them all a little bit shorter. Right, so I think they do look a little bit thick right now, so let's go to that initial set her hair curve profile and set it to 0.003, just so they look a little bit thinner there as well. Right, something like that already looks pretty much like I want it to be.


[User] Please transcribe this text

[Assistant] Right, so that has been part two. We did a lot of geometry notes, setups, a lot of tweaking of values, but in the end it looks a lot more realistic and I'm happy with the results. In part three, we're going to be working on the actual texturing. Alright, so how do we...


[User] Please transcribe this text

[Assistant] Care strands, right? And believe me, it is a little bit harder than we would...


[User] Please transcribe this text

[Assistant] It's a place for old parts.


[User] Please transcribe this text

[Assistant] The following is a conversation with Elon Musk, his third time on this, the Lex Friedman podcast. Yeah, make yourself comfortable. No, wow. Okay.


[User] Please transcribe this text

[Assistant] Yeah. We'll get there. We'll get there. It's gotten soft. Allow me to say that the SpaceX launch of human beings to orbit on May 30th, 2020,


[User] Please transcribe this text

[Assistant] Was seen by many as the first step in a new era of human space exploration. These human space flight missions were a beacon of hope.


[User] Please transcribe this text

[Assistant] To me and to millions over the past two years is how our world has been going through one of the most difficult periods in recent human history.


[User] Please transcribe this text

[Assistant] We saw, we see the rise of division, fear, cynicism, and the loss of common humanity.


[User] Please transcribe this text

[Assistant] Right when it is needed most. So first, Elon, let me say thank you for giving the world hope and reason to be excited about the future.


[User] Please transcribe this text

[Assistant] Let me ask about Crew Dragon Demo 2. So that, that first flight with humans on board.


[User] Please transcribe this text

[Assistant] How did you feel leading up to that launch? Were you scared? Were you excited? What was going through your mind? So much was at stake.


[User] Please transcribe this text

[Assistant] When it was a success first when the launch was a success and when they returned back home or back to earth. There's a great relief.


[User] Please transcribe this text

[Assistant] So for people that somehow don't know, it's the all-civilian first time all-civilian out to space, out to orbit.


[User] Please transcribe this text

[Assistant] I'll ask you about some of those details, but since you're so busy with the hard engineering challenges.


[User] Please transcribe this text

[Assistant] The reason I want to ask this question of May 30th, it's, it's been some time so you can look back and think about the impact already. It's already, at the time it was an engineering problem maybe. Now it's becoming a historic moment. Like it's a moment that.


[User] Please transcribe this text

[Assistant] How many moments will be remembered about the 21st century?


[User] Please transcribe this text

[Assistant] That or something like that maybe inspiration for one of those would be remembered as the early steps of a new age of space exploration.


[User] Please transcribe this text

[Assistant] So lemme, uh, ask you then to analyze Starship in that same way.


[User] Please transcribe this text

[Assistant] I know you have, you'll talk about, in more detail about Starship in the near future, perhaps.


[User] Please transcribe this text

[Assistant] Uhm, but just in that same way, like you said, you see when you see a


[User] Please transcribe this text

[Assistant] Uh, when you see a rocket, you see a sort of a list of risks. In that same way, you said that Starship is a really hard problem. So, there's many ways I can ask this, but...


[User] Please transcribe this text

[Assistant] If you magically could solve one problem perfectly, one engineering problem perfectly,


[User] Please transcribe this text

[Assistant] Which one would it be? On Starship? On, on, sorry, on Starship. So is it maybe related to the efficiency, the, uh, the engine, the weight of the different components, the complexity of various things, maybe the controls of the, the crazy thing has to do to land?


[User] Please transcribe this text

[Assistant] Talking about Raptor engine, what makes it amazing? What, what are the different aspects of it that?


[User] Please transcribe this text

[Assistant] Make it like, what are you the most excited about? Uh, if the whole thing works in terms of efficiency, all of those kinds of things.


[User] Please transcribe this text

[Assistant] So why is it such a hard engine to manufacture at scale? Uh, it's very complex.


[User] Please transcribe this text

[Assistant] A lot of, what does complexity mean here is a lot of components involved.


[User] Please transcribe this text

[Assistant] So you mentioned that you doubt, well, not you doubt, but there, there's days or moments when you doubt that this is even possible. It's so difficult.


[User] Please transcribe this text

[Assistant] What's your source of belief in situations like this?


[User] Please transcribe this text

[Assistant] When the engineering problem is so difficult, there's a lot of experts.


[User] Please transcribe this text

[Assistant] Many of whom you admire who have failed in the past. Yes. And uhm, a lot of people.


[User] Please transcribe this text

[Assistant] You know, a lot of experts, maybe journalists, all the kind of, you know, the public in general have a lot of doubt about whether it's possible.


[User] Please transcribe this text

[Assistant] And you yourself know that even if it's a non-null set, non-empty set of success, it's still unlikely or very difficult. Like where do you go to? Both personally.


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[Assistant] Uhm, intellectually as an engineer, as a team.


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[Assistant] Like for source of strength needed to sort of persevere through this. And to keep going with the project, take it to completion.


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[Assistant] Can you, uh, then zoom back in to specific problems with Starship or any engineering problems you work on? Can you try to introspect your particular biological neural network, your thinking process and describe how you think?


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[Assistant] Like in number of things you manufacture or something like that and then in time.


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[Assistant] Talk about resources and materials and stuff like that. Do you throw that into the calculation of trying to reason from first principles like how we're going to make the supply chain work here?


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[Assistant] Yeah, actually, if you don't mind me taking a tiny tangent, I had a, I often talked to Jim Keller, who was somebody that worked with you as a friend.


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[Assistant] So uhm, I suppose he carries the flame of the same kind of thinking that you're talking about now. Uhm, and I guess I see that same thing at Tesla and


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[Assistant] And, uh, SpaceX folks who work there, they kind of learn this way of thinking and it kind of becomes obvious almost. But anyway, I had, um, argument, not argument.


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[Assistant] He educated me about how cheap it might be to manufacture a Tesla bot. We just, we had an argument. What is, how can you reduce the cost of the scale of producing a robot? Because I've gotten the chance to interact quite a bit.


[User] Please transcribe this text

[Assistant] Obviously in the academic circles with humanoid robots and then Boston Dynamics and stuff like that. And they're very expensive to build.


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[Assistant] And then, uh, Jim kind of schooled me on saying like, okay, like this kind of first principles thinking of how can we get the cost of manufacturing down.


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[Assistant] Uhm, I suppose you do that, you have done, uh, that kind of thinking for TeslaBot and for all kinds of...


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[Assistant] All kinds of complex, systems that are traditionally seen as complex. And you say, okay, how can we simplify everything out?


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[Assistant] And it's almost like Rick and Morty absurd until you start to really think about it and you really should.


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[Assistant] Think about it in this way because everything else is kind of, uh, uh, if you, if you think, uh,


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[Assistant] You, you might fall victim to the momentum of the way things were done in the past, unless you think in this way.


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[Assistant] I should mention that the brilliant Siobhan Zilas is hanging on.


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[Assistant] Hanging out with us, uh, in case you hear a voice of wisdom from, uh, from, from outside, from up above.


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[Assistant] Uh, okay, so let me ask you about Mars. You mentioned it would be great for science to put, uhm, a base on the moon to do some research, but the truly big leap


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[Assistant] Again, in this category of seemingly impossible is to put a human being on Mars. When do you think SpaceX will land a human being on Mars?


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[Assistant] What are the determining factors would you say from an engineering perspective or is that not the bottlenecks?


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[Assistant] Yeah, the existence of nuclear weapons, pandemics, all kinds of threats should, uh, should kind of, um, give us some motivation.


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[Assistant] The most difficult aspect of building civilization on Mars, terraforming Mars, like from an engineering perspective, from a financial perspective, human perspective, to get


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[Assistant] To get a large number of folks there who will never return back to earth.


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[Assistant] I mean, do you think about the terraforming aspect, like actually building, are you so focused right now on the spaceships part that's so


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[Assistant] And also we should clarify in the solar system.


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[Assistant] There might be nice like vacation spots.


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[Assistant] Uh, to say the least. Let me push back on that. Not really a push back, but a quick curve ball of a question. So you did mention physics as the, the first starting point. So, um, general relativity allows for wormholes.


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[Assistant] Uh, they technically can exist. Do you think, uhm, those can ever be leveraged by humans to travel faster than the speed of light?


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[Assistant] So all the work you've done with propulsion, how much innovation is possible with rocket propulsion? Is this uhm,


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[Assistant] I mean you've seen it all and you're constantly innovating in every aspect.


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[Assistant] How much is possible? Like how much can you get 10x somehow? Is there something in there in physics?


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[Assistant] That you can get significant improvement in terms of efficiency of engines and all those kinds of things.


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[Assistant] So that's incredible. So you're saying like it's, uh, by far the biggest bang for the buck is to make it fully reusable versus like some kind of brilliant breakthrough in theoretical physics.


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[Assistant] Just brilliant engineering. Let me ask a slightly philosophical fun question. Gotta ask. I know you're focused on getting to Mars, but once we're there on Mars, what do you, what form of government, economic system, political system,


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[Assistant] Do you think would work best for an early civilization of humans?


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[Assistant] The interesting reason to talk about this stuff, it also helps people dream about the future. I know you're really focused about.


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[Assistant] The short-term engineering dream, but it's like, I don't know, there's something about imagining an actual civilization on Mars that gives people, so it really gives people hope.


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[Assistant] And not make it as annoying as those cookies we have to accept the cookie.


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[Assistant] Heard it from me on first, he accepts all your damn cookies.


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[Assistant] Yeah. Start asking me. It's annoying. Yeah. It's, uh, it's one example of, um, implementation of a good idea done really horribly.


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[Assistant] Yeah, so it, I mean, I guess the problem with the constitution is it's, it's kind of like C.


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[Assistant] Versus Java, cause it doesn't have any garbage collection built in. I think there should be, I, I, when you first said the, the, the metaphor of garbage collection, I loved it. From a coding standpoint. From a coding standpoint. Yeah, yeah. I, it would be interesting if the laws themselves kind of had a built in.


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[Assistant] So that's sort of, it's not like somebody has to kill them. They kind of die themselves. They disappear.


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[Assistant] Not to defend Java or anything, but you know, the C++, you know, you could also have a great garbage collection in Python and so on.


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[Assistant] So let me be the guy, you posted a meme on Twitter recently where there's like a row of urinals and guy just walks all the way across and he tells you about crypto.


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[Assistant] Do you think, technologically speaking, there's any room for ideas of smart contracts or so on? Cause you mentioned laws. Uhm, that's an interesting implement, use of things like smart contracts to implement the laws by which governments function. Like something built on Ethereum or maybe a dog coin that enables smart contracts and


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[Assistant] You mentioned that uh, Doge is the people's coin.


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[Assistant] Um, and you said that you were literally going, SpaceX may consider literally putting, uh, a doge coin on the moon.


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[Assistant] Is it, is it something you're still considering? Uh, Mars perhaps? Uh, do you think?


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[Assistant] There's some chance we've talked about political systems on Mars, that uh, Dogecoin is the, the official currency of Mars at some point in the future.


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[Assistant] So both policy in terms of with inflation and actual like technological cobalt, like cryptocurrency takes us into the 21st century in terms of the actual systems that allow you to do the transaction to store wealth, all those kinds of things.


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[Assistant] But people have proposed different technological solutions. Yeah, lightning network and the layer two technologies on top of that. I mean, it's, it's all, it seems to be all kind of a trade off, but the point is it's kind of brilliant to say that just think about information and think about what kind of database, what kind of infrastructure enables the exchange information.


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[Assistant] Like I said, uhm, around 2008, so you're not, uh,


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[Assistant] You know, some people suggested you might be Satoshi Nakamoto. You've previously said you're not. Let me ask. You're not for sure. Would you tell us if you were? Yes. Okay.


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[Assistant] Uh, do you think it's a feature of Bug that he's anonymous, or she, or they?


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[Assistant] It's an interesting kind of quirk of human history that there is a particular technology that is a completely anonymous inventor.


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[Assistant] So it's not perhaps like singular figures aren't even as important as the, the figures involved in the evolution of ideas that led to a thing. So, yeah, yeah. It's, you know, most perhaps it's sad to think about history, but maybe most names will be forgotten anyway.


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[Assistant] I got Elon to quote Shakespeare. I feel like I accomplished something today.


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[Assistant] Tesla Autopilot has been through an incredible journey over the past six years.


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[Assistant] Or perhaps even longer in the minds of, in your mind, in the minds of many involved.


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[Assistant] The whole journey was incredible to me to watch.


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[Assistant] Because I knew, well, part of it was I was at MIT and I knew the difficulty of computer vision. And I knew the whole, I had a lot of colleagues and friends about the DARPA challenge. I knew how difficult it is. And so there was a natural skepticism. When I first drove a Tesla with the initial system based on Mobileye, I thought there's no way


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[Assistant] The first one I got in, I thought, there's no way this car could maintain.


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[Assistant] Uhm, like staying in the lane and create a comfortable experience. So my intuition initially was that the lane keeping problem is way too difficult to solve.


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[Assistant] Well, like, uh, but not this, but solve in the way that we just, we talked about previous is prototype.


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[Assistant] I mean, there's part, that's part of the story of how you approach things sometimes. Sometimes you do things from scratch. Sometimes at first you kind of see what's out there and then you decide to do it from scratch. That was...


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[Assistant] One of the boldest decisions I've seen is both on the hardware and the software to decide to eventually go from scratch. I thought again, I was skeptical whether that's going to be able to work out because it's such a, such a difficult problem. And so it was an incredible journey. What I see now with everything, the hardware, the compute, the sensors, the things I


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[Assistant] Maybe care and love about most is the, the stuff that Andre Karpathy is leading with the data set selection, the whole data engine process, the neural network architectures, the way that's in the real world that network is tested, validated, all the different test sets.


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[Assistant] Uh, you know, versus the ImageNet model of computer vision, like what's in academia is like real world artificial intelligence.


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[Assistant] AI stuff. Yeah. So yeah, there's, I'm aware that there's an incredible team of just a lot going on.


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[Assistant] What are some insights you've gained over those?


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[Assistant] Five, six years of autopilot about the problem of autonomous driving. So you leaped in.


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[Assistant] Having some sort of, uh, first principles kinds of intuitions, but nobody knows how difficult the process is.


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[Assistant] But the question is what aspects of human nature do you have to encode into the machine, right? So you have to solve the perception problem like detect.


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[Assistant] And then you first of all realize what is the perception problem for driving, like all the kinds of things you have to be able to see. Like what, what do we even look at when we drive? There's a, I just recently heard Andre talked about at MIT about car doors. I think it was the world's greatest talk of all time about car doors.


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[Assistant] Uhm, you know, the fine details of car doors. Like what is even an open car door, man? So like the, the ontology of that, that's a perception problem. We humans solve that perception problem and Tesla has to solve that problem. And then there's the control and the planning coupled with the perception. You have to figure out like.


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[Assistant] What's involved in driving like, especially in all the different edge cases? Uhm, and, and then I mean, maybe you can comment on this.


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[Assistant] How much game theoretic kind of stuff needs to be involved, you know, at a four-way stop sign?


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[Assistant] You know, as humans, when we drive, our actions affect the world.


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[Assistant] Like it changes how others behave. Most of the time was driving.


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[Assistant] You're usually just responding, uh, to the scene as opposed to like really, uh, asserting yourself in the scene. Do you think?


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[Assistant] Don't give enough respect to how incredible the human perception system is. To mapping the raw.


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[Assistant] Photons to the vector space representation in our heads.


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[Assistant] So cool. The peripheral vision is so cool. Yes. You realize all the illusions for vision science is so makes you realize just how incredible the brain is.


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[Assistant] Uh, edited down or compress it even further into things like concepts. It's not, it's like, it goes beyond the human mind seems to go sometimes beyond vector space.


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[Assistant] Need to fully represent those things or maybe you get those kind of, uhm,


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[Assistant] It's a really hard problem. So with occlusions and computer vision, when you can't see an object anymore.


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[Assistant] Even when he just walks behind a tree and reappears, that's a really, really-


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[Assistant] I mean, at least in academic literature, it's tracking through occlusions. It's very difficult.


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[Assistant] And I just think the data engine side of that. So getting the data to learn all of the concepts that you're saying now is an incredible process. It's this iterative process of just, it's this, this hydra net many. We're changing the name to something else.


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[Assistant] So you want to compile the whole thing down with your own compiler.


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[Assistant] And you want to achieve as many high frame rates like a video game. You want full resolution, high frame rate. High frame rate.


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[Assistant] So you have to interpolate somehow to deal with the effects of jitter so that you can make robust control decisions.


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[Assistant] So the jitter is in the sensor information or the jitter can occur at any


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[Assistant] Well, let me ask sort of, uh, looking back the six years, looking out into the future, based on your current understanding, how hard do you think this, this full self-driving problem, when do you think Tesla will solve level four FSD?


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[Assistant] And what does the solution look like? Is it the current pool of FSD beta candidates? They start getting greater and greater as they have been.


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[Assistant] Degrees of autonomy and then there's a certain level beyond which they can, they can do their own, they can read a book.


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[Assistant] 10.6 just came out recently, 10.7 is on the way, maybe 11 is on the way so we're in the future.


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[Assistant] So ultimately it's kind of reducing the complexity of the whole thing. So, uh, reducing, reducing lines of code will actually go lower. Yeah, that's fascinating.


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[Assistant] Uhm, so you're doing fusion of all the sensors and reducing the complexity of having to deal with each sensor. Here's all the cameras. Here's all the cameras really. Right. Yes. Uhm, same with humans. Well, I guess we got ears too.


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[Assistant] I think you made it clear. I mean, at least to me, it's super exciting. Everything that's going on outside of what Andre is doing.


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[Assistant] I mean, everything is going on with data engine, uh, whatever, whatever it's called. The whole process is just work of art to me.


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[Assistant] Uh, so you've presented Tesla bot as primarily useful in the factory. First of all, I think humanoid robots are incredible from a fan of robotics, I think.


[User] Please transcribe this text

[Assistant] Uh, the elegance of movement that human, uh, the humanoid robots, the bipedal robots show are just so cool. So it's really interesting that you're working on this and also talking about applying the same kind of.


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[Assistant] All the ideas of some of which we've talked about with data engine, all the things that we're talking about with Tesla autopilot, just, uh, transferring that over to the, just yet another robotics problem.


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[Assistant] I have to ask since I care about human robot interaction, so the human side of that. So you've talked about mostly in the factory. Do you see it, uh, also, do you see as part of this problem that Tesla bot has to solve as interacting with humans and potentially having a place like in the home?


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[Assistant] So interacting, not just, not replacing labor, but also like, I dunno, being a friend or an assistant or something like that.


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[Assistant] Did you see a world when there's like hundreds of millions of Tesla bots?


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[Assistant] Doing different, performing different tasks throughout the world.


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[Assistant] Can I ask a wild question? So the number of Tesla cars has been accelerating, has been close to 2 million produced. Many of them have autopilot. I think we're over 2 million now.


[User] Please transcribe this text

[Assistant] Do you think there will ever be a time when there will be more Tesla bots than Tesla cars?


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[Assistant] Still, you do talk about love sometimes. So let me ask, this isn't like for like sex robots or something like that. Love is the answer.


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[Assistant] Yes, uh, there is something compelling to us, not compelling, but we connect with, uh, humanoid robots or even legged robots, like with the dog and she shapes with dogs. It just, it seems like.


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[Assistant] No, there's a huge amount of loneliness in this world.


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[Assistant] All of us seek companionship with other humans, friendship and all those kinds of things. We have a lot of here in Austin, a lot of people have dogs. There seems to be a huge opportunity to also have robots that decrease.


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[Assistant] The, uh, the, the amount of loneliness in the world or help us humans connect with each with each other. So in a way that dogs can, um, do you think about that with us about it all or is it really focused on the problem of.


[User] Please transcribe this text

[Assistant] Of performing specific tasks, not connecting with humans.


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[Assistant] Uh, whatever you want to call it. Uh, the other half, right? Uh, in the same way that friends do. See, I think that's a huge opportunity. I think.


[User] Please transcribe this text

[Assistant] I think the flaws being a feature is really nice. You could be quite terrible at being a robot for quite a while.


[User] Please transcribe this text

[Assistant] In the general home environment or all the in general world. And that's kind of adorable. And that's like, those are your flaws and you fall in love with those flaws. So it's, it's, it's very different than autonomous driving where it's a very high stakes environment. You can not mess up.


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[Assistant] And so yeah, it's more fun to be a robot in the home.


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[Assistant] And it's cool that it's connected to Tesla, the car.


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[Assistant] That's true. Uhm, that could be useful in all environments. Like you said, a lot of people argue in the car, so maybe we can help them out.


[User] Please transcribe this text

[Assistant] Did you, is this like, uh, you talked about all this with Dan? Yep. Awesome.


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[Assistant] Broadly looking at history, when you look at Genghis Khan, when you look at.


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[Assistant] Stalin, Hitler, the darkest moments of human history.


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[Assistant] Whether it's the wars or the individuals or just the behavior of people, any aspects of history.


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[Assistant] Does it make you sad that humans do these kinds of things to each other? You look at the 20th century, World War II, the cruelty, the abuse of power, talk about communism, Marxism and stuff.


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[Assistant] The thirties, uh, there's a lot, a lot of lessons there to me in particular that it feels like humans, like all of us have that it's the old Solzhenitsyn line.


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[Assistant] Uhm, that the line between good and evil runs through the heart of every man, that all of us are capable of evil, all of us are capable of good. It's almost like this kind of responsibility that, uhm, all of us have to, to, to tend towards the good.


[User] Please transcribe this text

[Assistant] And so like to me, looking at history is almost like an example of, look, you have some charismatic leader.


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[Assistant] Based on that story to do evil onto each other, onto your family, onto others. And so it's like our responsibility to do good. Uh, it's not like.


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[Assistant] Now it's somehow different from history. That can happen again. All of it can happen again.


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[Assistant] And yes, most of the time you're right. I mean, the optimistic view here is mostly people are just living life. And as you've often memed about, uh, the quality of life was way worse back in the day and it keeps improving over time through innovation to technology. But still it's somehow notable that these blimps of atrocities happen.


[User] Please transcribe this text

[Assistant] Well, yeah, the lesson there is to be grateful for the way things are now for, for some of us. We've spoken about this offline. I'd love to get your thought about it here.


[User] Please transcribe this text

[Assistant] If I sat down for a long form in-person conversation with the president of Russia, Vladimir Putin.


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[Assistant] Would you potentially want to call in for a few minutes, uh, to join in on a conversation with a moderated translated by me?


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[Assistant] You've shown interest in the Russian language. Is this grounded in your interest in history of linguistics, culture, general curiosity?


[User] Please transcribe this text

[Assistant] And uh, so find the words that are exactly the same and now you start to understand Cyrillic, yeaah.


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[Assistant] You, uh, you love great engineering, physics. There's a tradition of the sciences there. You look at the 20th century from rocketry. So.


[User] Please transcribe this text

[Assistant] You know, some of the greatest rockets of the space exploration has been done.


[User] Please transcribe this text

[Assistant] And the Soviet and the former Soviet Union. Yeah. So do you draw inspiration from.


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[Assistant] That history, just how this culture that in many ways, I mean, one of the sad things is because of the language, a lot of it is lost to history because it's not translated, all those kinds of, because it, it is in some ways an isolated culture. It flourishes within its, within its borders.


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[Assistant] So do you draw inspiration from those folks from the history of


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[Assistant] Yeah, I mean, I, I, you know, there's Roscosmos, the Russian agency.


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[Assistant] I look forward to a time when those countries with China are working together.


[User] Please transcribe this text

[Assistant] The United States are all working together. Maybe a little bit of friendly competition, but.


[User] Please transcribe this text

[Assistant] Uh, this is also a good place to give a shout out to a video titled The Entire Soviet Rocket Engine Family Tree by Tim Dodd, aka Everyday Astronaut. It's like an hour and a half.


[User] Please transcribe this text

[Assistant] That guy is super excited about the future, super excited about space flight. Every time I see anything by him, I just have a stupid smile on my face because he's so excited about stuff.


[User] Please transcribe this text

[Assistant] Do you mind doing a bit of a meme review in the spirit of the great, the powerful PewDiePie? Let's say one to 11. Just go over a few documents printed out. We can try. Let's try this.


[User] Please transcribe this text

[Assistant] I present to you document numero uno.


[User] Please transcribe this text

[Assistant] You get it? Because he likes impaling things? Yes, I get it. I don't know, three. Whatever. Oh, that's not very good.


[User] Please transcribe this text

[Assistant] This is uhm, grounded in some engineering, some history.


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[Assistant] Yeah, I guess radiation is one of the words that can be used as a tool to fear monger by certain people. That's it.


[User] Please transcribe this text

[Assistant] So, uh, that, uh, 90, 180, and 360 degrees, everybody loves the math, nobody gives a shit about 270.


[User] Please transcribe this text

[Assistant] It's kind of true. Oh yeah, this is, uh, this is kind of personal for me. Next one.


[User] Please transcribe this text

[Assistant] Hello, yes, this is dog. Your wife was launched into space. And then the last one is him with his eyes closed and a bottle of vodka.


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[Assistant] They don't tell you the full story of, you know, what, what the love, the impact they had on the loved ones. True. That one gets an 11 for me. The Soviet shadow. Oh yeah. It just keeps going on the Russian theme. First man in space. Nobody cares. First man in the moon.


[User] Please transcribe this text

[Assistant] Stepping foot onto another truly foreign land.


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[Assistant] It's, it's not the journey like, uh, people that explore the oceans. It's not as important to explore the oceans as to land in a whole new continent. Yeah. Oh, this is about you.


[User] Please transcribe this text

[Assistant] Oh yeaah, I'd love to get your comment on this. Y'all musk.


[User] Please transcribe this text

[Assistant] After sending 6.6 billion dollars to the UN to end world hunger, you have three hours.


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[Assistant] So it's much more complex than something that money could solve. It's Geopolitics, it's, it's.


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[Assistant] A lot of things, it's human nature, it's governments, it's monies, monetary systems, all that kind of stuff.


[User] Please transcribe this text

[Assistant] What do you think that one gets? Just kidding. Two.


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[Assistant] He's going after Empire's world. Uh, where did you get those artifacts? The British Museum. Shout out to Monty Python. We found them.


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[Assistant] Even if there's a darker aspect to like the history of empire in general, whatever the empire is, however things were done.


[User] Please transcribe this text

[Assistant] It is the history that happened. You can't sort of erase that history, unfortunately. You could just become better in the future. That's the point.


[User] Please transcribe this text

[Assistant] We might not get a passing grade from generations that come after us. Uh, what does that one get?


[User] Please transcribe this text

[Assistant] Well, you got a new haircut. Is that, is that, is that, how does that affect your leadership?


[User] Please transcribe this text

[Assistant] Yeaah, yeaah. It must come from the eyebrows. Alright, uhm, invention. Great engineering. Look what I invented. That's the best thing since ripped up bread. Cause they invented sliced bread. Am I just explaining memes at this point? This is what my life has become.


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[Assistant] Like a scribe that like runs around with the kings and just like writes


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[Assistant] Then there's like, what is a burger? What's, what's a sandwich? And then you start getting as a pizza sandwich and what is the original? It's, it's, it gets into an ontology argument.


[User] Please transcribe this text

[Assistant] Yeah, but I'm sure they've had bread and meat separately for a long time and it was kind of a burger on the same plate, but somebody who actually combined them into the same thing.


[User] Please transcribe this text

[Assistant] Yeah. I guess this is what we're getting at. It's great. Uhm, uh, what, what about the, uh, Matthew McConaughey Austinite here? Uh, President Kennedy, do you know how to put men on the moon yet? NASA? No. President Kennedy, be a lot cooler if you did. Pretty much.


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[Assistant] Someone drew a bunch of dicks all over the walls, assisting chapel, boys bathroom.


[User] Please transcribe this text

[Assistant] Throughout human history. You tweeted that you aspire to comedy, you're friends with Joe Rogan. Might you, uh, do a short stand-up comedy set at some point in the future? Maybe, uh, open for Joe, something like that. Is that, is that- Really? Stand-up? Actual just full-on stand-up? Full-on stand-up. Is that in there or is that- I've never thought about that.


[User] Please transcribe this text

[Assistant] Uhm, it's extremely difficult if, uh, at least that's what, uh, like Joe says and the comedians say.


[User] Please transcribe this text

[Assistant] Learn something either way. Um, yeah, I kind of love, uh,


[User] Please transcribe this text

[Assistant] Both the, when you bomb and when you do great, just watching people, how they deal with it. It's so difficult. It's so, you're so fragile up there. It's just you.


[User] Please transcribe this text

[Assistant] And you think you're going to be funny and when it completely falls flat, it's just, it's beautiful to see people deal with.


[User] Please transcribe this text

[Assistant] Uhm, what's your favorite Rick and Morty concept?


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[Assistant] Somebody that's exactly like you from an alternate dimension showed up there. Elon Tusk.


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[Assistant] Easy from a, if we're talking about from the engineering perspective of super intelligence, like with Marvin the robot.


[User] Please transcribe this text

[Assistant] Like is it, it seems like it might be very easy to engineer just a depressed robot.


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[Assistant] It's not obvious to engineer a robot that's going to


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[Assistant] Find a fulfilling existence. Same as humans, I suppose. But uhm, I wonder if that's like the default.


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[Assistant] If you don't do a good job on building a robot, it's going to be sad a lot.


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[Assistant] You, uh, like I mentioned with SpaceX, you give a lot of people hope and a lot of people look up to you, millions of people look up to you. Uh, if we think about young people in high school, maybe in college, uhm, what advice would you give to them about


[User] Please transcribe this text

[Assistant] If they want to try to do something big in this world, they want to really have a big positive impact, what advice would you give them about their career, maybe about life in general?


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[Assistant] When you think about education and self-education, what do you recommend? So there's the university, there's self-study.


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[Assistant] There is a hands on sort of finding a company or a place or set of people that do the thing you're passionate about and joining them as early as possible.


[User] Please transcribe this text

[Assistant] There's, uh, taking a road trip across Europe for a few years and writing some poetry. Which, uh, which, which trajectory do you suggest?


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[Assistant] In terms of learning about how you can become useful, as you mentioned, how you can have the most positive impact.


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[Assistant] That was a super fast shortcut to, to figure out which, where are you. You both good at it. You like doing it.


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[Assistant] I mean, it's all walks of life. I've seen that. One of the, one of the reasons.


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[Assistant] Not creating a constant competition, like there's a scarcity of resources. What happens when you celebrate others and you promote others?


[User] Please transcribe this text

[Assistant] Uh, see some funding for academic research is zero sum. It is not. If you celebrate each other, if you make...


[User] Please transcribe this text

[Assistant] If you get everybody to be excited about AI, about physics, about mathematics, I think it, there'd be more and more funding and I think everybody wins. Yeah, that applies, I think broadly.


[User] Please transcribe this text

[Assistant] Exactly. So last, last question about love and meaning.


[User] Please transcribe this text

[Assistant] What is the role of love in the human condition broadly and more specific to you? How has love...


[User] Please transcribe this text

[Assistant] That's one of the great ones, yes. You've early recorded Shakespeare, but that's really up there.


[User] Please transcribe this text

[Assistant] I mean there's uhm, cause we've talked about so many inspiring things like be useful in the world, sort of like solve problems, alleviate suffering, but it seems like connection between humans is a source, you know, it's uhm,


[User] Please transcribe this text

[Assistant] It's a source of joy, it's a source of meaning, and that, that's what love is, friendship, love.


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[Assistant] I just wonder if you think about that kind of thing when you talk about


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[Assistant] Preserving the light of human consciousness and us becoming a multi-planetary, multi-planetary species. I mean, to me at least, uh,


[User] Please transcribe this text

[Assistant] That, that means like if we're just alone and conscious and intelligent, it doesn't mean nearly as much as if we're with others.


[User] Please transcribe this text

[Assistant] Right? And there's some magic created when we're together. The...


[User] Please transcribe this text

[Assistant] Uh, the, the friendship of it, and I think the highest form of it is love, which I think broadly is, is much bigger than just sort of romantic, but also yes, romantic love and, uh, family and those kinds of things.


[User] Please transcribe this text

[Assistant] So when you look at the whole of it, the human history, all the people who's ever lived, all the people alive now.


[User] Please transcribe this text

[Assistant] Pretty, we're, we're okay. On the whole, we're a pretty interesting, uh, bunch.


[User] Please transcribe this text

[Assistant] You joked about it with a 42. Uh, what do you, what do you think is the meaning of this whole thing?


[User] Please transcribe this text

[Assistant] Elon, like I said, um, I'm deeply grateful that you would spend your extremely valuable time with me today. And also that you are given millions of people hope in this difficult time, this divisive time and this, uh, cynical time. So I hope you do continue doing what you're doing. Thank you so much for talking today.


[User] Please transcribe this text

[Assistant] Thanks for listening to this conversation with Elon Musk. To support this podcast, please check out our sponsors in the description. And now, let me leave you with some words from Elon Musk himself. When something is important enough, you do it even if the odds are not in your favor. Thank you for listening and hope to see you.


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[Assistant] Who cares if you forgot the turtle's question? That turtle had no right to dump us in the water. Dumping us in the water was rude.


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[Assistant] Not like you, Poppy, said Jeb. You're funny.


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[Assistant] I guess. Said Jeb. But no one cares about digging. I do. Said Eddy.


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[Assistant] That was a text message that I received on a dark winter night in November 2016. One of them was a children's hospital.


[User] Please transcribe this text

[Assistant] Run by my Syrian colleagues at the Independent Doctors Association, IDA. It was the sixth time it had been bombed.


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[Assistant] I watched in horror heartbreaking footage of the head nurse Malak in the aftermath of the bombing, grabbing premature babies out of their incubators, desperate to get them to safety, before she broke down in tears. And I felt devastated.


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[Assistant] Fellow humanitarians and I have spent blood, sweat and tears rebuilding hospitals so that our patients may live, not die.


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[Assistant] The reason that people survive in crisis is because of the remarkable work of the people in crisis themselves.


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[Assistant] People survive because of people like Malak.


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[Assistant] Who despite sustaining a severe burns injury in the line of duty, the first thing she did when discharged from hospital was to go back caring for small children.


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[Assistant] From the rubble of death and devastation arise the most gallant and noble human beings. Local humanitarians are the beacons of light in the darkness of war.


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[Assistant] Now the data shows that Syrian organizations carry out 75 percent of their humanitarian work in Syria. Yet, they receive


[User] Please transcribe this text

[Assistant] And what's more, the same is happening across the crises of the world. I have witnessed this reality.


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[Assistant] It means those with the knowledge, skill and ability to respond on the front lines have little of the necessary tools, equipment and resources they need to save lives.


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[Assistant] It means groups like IDA don't have funds to rebuild their hospital.


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[Assistant] The humanitarian system is failing the most vulnerable communities in their darkest hours.


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[Assistant] A startup determined to address this imbalance and enable local responders to provide health care to their war-devastated communities. We have devised a simple model. Source trusted and impactful local groups.


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[Assistant] Support their development through an accelerator program and connect them to you via our crowdfunding platform where they can fundraise for their health needs.


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[Assistant] So when IDA asked for help, I decided to launch CanDo seven months early with very little money, and many people, including myself, thought I had finally gone mad.


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[Assistant] I wanted to do something that transformed our collective anger into something beautiful. And that's how the People's Convoy was born.


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[Assistant] It was a global crowdfunding campaign to enable IDA to rebuild a whole new children's hospital, and if successful, we, the people, would take the medical equipment all the way from London to the Syria border, and we did it.


[User] Please transcribe this text

[Assistant] Thousands of people came together from across the world to achieve a global first. We built the first ever crowdfunded hospital.


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[Assistant] The location was carefully chosen by the local experts' IDA, where they knew it would be safe and serve the greatest number of displaced children.


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[Assistant] IDA was so moved by people's response, they named it Hope Hospital.


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[Assistant] It's been open for exactly one year, and they have treated over 15,000 children.


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[Assistant] We can provide lifesaving assistance in the most volatile places on earth. The system needs to change, and change starts with us all, sharing a new humanitarian vision.


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[Assistant] One where you, global citizens with skills, expertise and resources, stand together with the local responders. One ...


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[Assistant] Where we are all humanitarians, putting the necessary resources in the hands of those who need them most and are best placed to use them effectively and efficiently.


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[Assistant] We need to support the people who are not only saving lives now, but it will also be them stitching their wounded communities back together once the conflict is over to help them heal.


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[Assistant] Local humanitarians have the courage to persist.


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[Assistant] To dust themselves off from the wreckage and to start again risking their lives to save others. And we can match their courage by not looking away or turning our backs, by helping those who are helping themselves and together save more lives. Thank you.


[User] Please transcribe this text

[Assistant] Yeah, good question. So, physicians for human rights have documented nearly 500 attacks on hospitals, and over 800 medical personnel have been killed. And they say, uhm, over 90 percent of it by the Syrian regime, and they say this is part of a systemic targeting and destruction of health care, using it as a weapon of war.


[User] Please transcribe this text

[Assistant] And the thing with this is that it's not just our problem, it's yours too, and everyone's. Because A, it exacerbates the refugee situation when you have a decimated health care system. It means the next Ebola-type epicenter of disease is going to be Syria.


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[Assistant] And unfortunately, it sets a very dangerous precedent that makes all of our hospitals anywhere in the world dangerous, and that is not how it should be.


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[Assistant] I think the answer is in that word, it's in hope. I think everyone who donated ...


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[Assistant] They had their faith in humanity renewed, knowing there were people like IDA and those doctors who were exhibiting the absolute best of humanity, and it was like an absolute reciprocation. IDA and the Syrians and many people in places of conflict feel very unheard and unseen, and I think the fact that


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[Assistant] When you read the history of the world, you are reading a saga of bloodshed and greed and folly, the import of which is impossible to ignore. An import operation.


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[Assistant] Chapter 104. The Tang Monk and the River.


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[Assistant] Wukong and his companions walked through the western paradise.


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[Assistant] The road weaved through a field of flowers and toward the Spirit Mountain.


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[Assistant] Bajie looked up at the huge mountain and shook his head.


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[Assistant] The traveler soon arrived at a river with a strong current.


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[Assistant] It wobbled and shook as the water rushed under it. The Tang Monk looked at the log.


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[Assistant] He sat on the edge of the boat as Wu Jing led the horse aboard. Ba Jie and Wu Kong followed.


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[Assistant] Wukong put his hand on the monk's shoulder and smiled. It's you, master. What? said the monk. Me?


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[Assistant] Said Wu Jing, smiling. The Tang monk looked at the body more carefully.


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[Assistant] It was wearing the same Buddhist robe that he was wearing.


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[Assistant] The boat soon reached the other riverbank and the travelers stepped out.


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[Assistant] As they walked up the slope of the Spirit Mountain, the Tang monk laughed in amazement.


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[Assistant] Everybody laughed as they continued up the mountain.


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[Assistant] Gasser drove through the water again. Splash!


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[Assistant] Just then, Miss Fender drove over. Gasser, she said, Stop that right now! Gasser frowned. Sorry, he said.


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[Assistant] Just play in the sand, Ms. Fender said. Water is not for cars!


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[Assistant] Dipper called to her friends. Come on in, she said.


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[Assistant] Tire Town School. Episode 65. Tire Town Beach.


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[Assistant] This is boring, Zippy said. I can't go fast on sand.


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[Assistant] The water looks fun, said Dipper. Miss Fender frowned.


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[Assistant] Jeb dug sand. He loaded it in Eddie's dumper.


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[Assistant] You made a wise choice to go after your dreams.


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[Assistant] You made a wise choice to go after your dreams.


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[Assistant] You made a wise choice to go after your dreams.


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[Assistant] You made a wise choice to stand up to your boss.


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[Assistant] You made a wise choice to stand up to your boss.


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[Assistant] You made a wise choice to stand up to your boss.


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[Assistant] You made a wise choice to ignore all the haters.


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[Assistant] You made a wise choice to ignore all the haters.


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[Assistant] You made a wise choice to ignore all the haters.


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[Assistant] You made a wise choice to not go out last night.


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[Assistant] You made a wise choice to not go out last night.


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[Assistant] You made a wise choice to not go out last night.


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[Assistant] You made a wise choice to stop hanging out with those people.


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[Assistant] You made a wise choice to stop hanging out with those people.


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[Assistant] You made a wise choice to stop hanging out with those people.


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[Assistant] She will be waiting for you at the park near your house.


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[Assistant] She will be waiting for you at the park near your house.


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[Assistant] She will be waiting for you at the park near your house.


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[Assistant] She will be waiting for you at your grandparents' house.


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[Assistant] She will be waiting for you at your grandparents' house.


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[Assistant] She will be waiting for you at your grandparents' house.


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[Assistant] She will be waiting for you at the entrance to your school.


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[Assistant] She will be waiting for you at the entrance to your school.


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[Assistant] She will be waiting for you at the entrance to your school.


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[Assistant] You went too far when you stole and ate my lunch.


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[Assistant] You went too far when you stole and ate my lunch.


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[Assistant] You went too far when you stole and ate my lunch.


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[Assistant] You went too far when you forwarded the email to HR.


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[Assistant] You went too far when you forwarded the email to HR.


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[Assistant] You went too far when you forwarded the email to HR.


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[Assistant] You went too far when you made fun of what she was wearing.


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[Assistant] You went too far when you made fun of what she was wearing.


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[Assistant] You went too far when you made fun of what she was wearing.


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[Assistant] You went too far when you shut off your phone for the entire week.


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[Assistant] You went too far when you shut off your phone for the entire week.


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[Assistant] You went too far when you shut off your phone for the entire week.


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[Assistant] You went too far when you stopped talking to your sister for six months.


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[Assistant] You went too far when you stopped talking to your sister for six months.


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[Assistant] You went too far when you stopped talking to your sister for six months.


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[Assistant] I had to take some time off work because I got in a car accident.


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[Assistant] I had to take some time off work because I got in a car accident.


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[Assistant] I had to take some time off work because I got in a car accident.


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[Assistant] I had to take some time off work because I was severely depressed.


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[Assistant] I had to take some time off work because I was severely depressed.


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[Assistant] I had to take some time off work because I was severely depressed.


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[Assistant] I had to take some time off work because my grandparents were sick.


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[Assistant] I had to take some time off work because my grandparents were sick.


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[Assistant] I had to take some time off work because my grandparents were sick.


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[Assistant] I had to take some time off work because I was busy renovating my house.


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[Assistant] I had to take some time off work because I was busy renovating my house.


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[Assistant] I had to take some time off work because I was busy renovating my house.


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[Assistant] I had to take some time off work because I had to deal with some personal issues.


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[Assistant] I had to take some time off work because I had to deal with some personal issues.


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[Assistant] I had to take some time off work because I had to deal with some personal issues.


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[Assistant] I had to take some time off work because I needed time to think about my next steps.


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[Assistant] I had to take some time off work because I needed time to think about my next steps.


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[Assistant] I had to take some time off work because I needed time to think about my next steps.


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[Assistant] Only a fool would buy stocks in that company.


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[Assistant] Only a fool would buy stocks in that company.


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[Assistant] Only a fool would buy stocks in that company.


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[Assistant] Only a fool would marry someone they had never met.


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[Assistant] Only a fool would marry someone they had never met.


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[Assistant] Only a fool would marry someone they had never met.


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[Assistant] Only a fool would believe the word of a perfect stranger.


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[Assistant] Only a fool would believe the word of a perfect stranger.


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[Assistant] Only a fool would believe the word of a perfect stranger.


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[Assistant] Trust me, you should ask them for a raise.


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[Assistant] Trust me, you should ask them for a raise.


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[Assistant] Trust me, you should ask them for a raise.


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[Assistant] Trust me, you should take this apartment over the other one.


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[Assistant] Trust me, you should take this apartment over the other one.


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[Assistant] Trust me, you should take this apartment over the other one.


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[Assistant] Trust me, you should buy the dress if you like it that much.


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[Assistant] Trust me, you should buy the dress if you like it that much.


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[Assistant] Trust me, you should buy the dress if you like it that much.


[User] Please transcribe this text

[Assistant] Trust me, you should eat at this restaurant for your anniversary.


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[Assistant] Trust me, you should eat at this restaurant for your anniversary.


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[Assistant] Trust me, you should eat at this restaurant for your anniversary.


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[Assistant] The last time I listened to him, I ended up...


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[Assistant] The last time I listened to him, I ended up...


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[Assistant] The last time I listened to him, I ended up in jail.


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[Assistant] The last time I listened to him, I ended up in jail.


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[Assistant] The last time I listened to him, I ended up in jail.


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[Assistant] The last time I listened to him, I ended up missing my flight.


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[Assistant] The last time I listened to him, I ended up missing my flight.


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[Assistant] The last time I listened to him, I ended up missing my flight.


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[Assistant] The last time I listened to him, I ended up sad and desperate.


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[Assistant] The last time I listened to him, I ended up sad and desperate.


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[Assistant] The last time I listened to him, I ended up sad and desperate.


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[Assistant] The last time I listened to him, I ended up lost in the jungle.


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[Assistant] The last time I listened to him, I ended up lost in the jungle.


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[Assistant] The last time I listened to him, I ended up lost in the jungle.


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[Assistant] The last time I listened to him, I ended up losing all my money.


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[Assistant] The last time I listened to him, I ended up losing all my money.


[User] Please transcribe this text

[Assistant] The last time I listened to him, I ended up losing all my money.


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[Assistant] The last time I listened to him, I ended up crashing my car into a ditch.


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[Assistant] The last time I listened to him, I ended up crashing my car into a ditch.


[User] Please transcribe this text

[Assistant] The last time I listened to him, I ended up crashing my car into a ditch.


[User] Please transcribe this text

[Assistant] The last time I listened to him, I ended up making friends with the wrong people.


[User] Please transcribe this text

[Assistant] The last time I listened to him, I ended up making friends with the wrong people.


[User] Please transcribe this text

[Assistant] The last time I listened to him, I ended up making friends with the wrong people.


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[Assistant] I'm concerned that there won't be people I know at the party.


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[Assistant] I'm concerned that there won't be people I know at the party.


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[Assistant] I'm concerned that there won't be people I know at the party.


[User] Please transcribe this text

[Assistant] I'm concerned that there won't be enough food for all the guests.


[User] Please transcribe this text

[Assistant] I'm concerned that there won't be enough food for all the guests.


[User] Please transcribe this text

[Assistant] I'm concerned that there won't be enough food for all the guests.


[User] Please transcribe this text

[Assistant] I'm concerned that there won't be free parking once we get there.


[User] Please transcribe this text

[Assistant] I'm concerned that there won't be free parking once we get there.


[User] Please transcribe this text

[Assistant] I'm concerned that there won't be free parking once we get there.


[User] Please transcribe this text

[Assistant] I'm concerned that there won't be sufficient security for the event.


[User] Please transcribe this text

[Assistant] I'm concerned that there won't be sufficient security for the event.


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[Assistant] I'm concerned that there won't be sufficient security for the event.


[User] Please transcribe this text

[Assistant] I'm concerned that there won't be any open seats next to each other.


[User] Please transcribe this text

[Assistant] I'm concerned that there won't be any open seats next to each other.


[User] Please transcribe this text

[Assistant] I'm concerned that there won't be any open seats next to each other.


[User] Please transcribe this text

[Assistant] I'm concerned that there won't be any tickets available by the time we get there.


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[Assistant] I'm concerned that there won't be any tickets available by the time we get there.


[User] Please transcribe this text

[Assistant] I'm concerned that there won't be any tickets available by the time we get there.


[User] Please transcribe this text

[Assistant] Company guidelines state employees must not disclose their salary.


[User] Please transcribe this text

[Assistant] Company guidelines state employees must not disclose their salary.


[User] Please transcribe this text

[Assistant] Company guidelines state employees must not disclose their salary.


[User] Please transcribe this text

[Assistant] Company guidelines state employees must be dressed appropriately for work.


[User] Please transcribe this text

[Assistant] Company guidelines state employees must be dressed appropriately for work.


[User] Please transcribe this text

[Assistant] Company guidelines state employees must be dressed appropriately for work.


[User] Please transcribe this text

[Assistant] Company guidelines state employees must punch in exactly at their time of work.


[User] Please transcribe this text

[Assistant] Company guidelines state employees must punch in exactly at their time of work.


[User] Please transcribe this text

[Assistant] Company guidelines state employees must punch in exactly at their time of work.


[User] Please transcribe this text

[Assistant] Company Guidelines state employees must address all customers as they enter the store.


[User] Please transcribe this text

[Assistant] Company Guidelines state employees must address all customers as they enter the store.


[User] Please transcribe this text

[Assistant] Company Guidelines state employees must address all customers as they enter the store.


[User] Please transcribe this text

[Assistant] Company guidelines state employees must not fraternize with guests during their off time.


[User] Please transcribe this text

[Assistant] Company guidelines state employees must not fraternize with guests during their off time.


[User] Please transcribe this text

[Assistant] Company guidelines state employees must not fraternize with guests during their off time.


[User] Please transcribe this text

[Assistant] Company guidelines state employees must get all vacation time pre-approved by their managers.


[User] Please transcribe this text

[Assistant] Company guidelines state employees must get all vacation time pre-approved by their managers.


[User] Please transcribe this text

[Assistant] Company guidelines state employees must get all vacation time pre-approved by their managers.


[User] Please transcribe this text

[Assistant] I'm so sorry you have to put up with somebody like me.


[User] Please transcribe this text

[Assistant] I'm so sorry you have to put up with somebody like me.


[User] Please transcribe this text

[Assistant] I'm so sorry you have to put up with somebody like me.


[User] Please transcribe this text

[Assistant] I'm so sorry you haven't gotten the respect you deserve.


[User] Please transcribe this text

[Assistant] I'm so sorry you haven't gotten the respect you deserve.


[User] Please transcribe this text

[Assistant] I'm so sorry you haven't gotten the respect you deserve.


[User] Please transcribe this text

[Assistant] I'm so sorry you were forced to make such a hard decision.


[User] Please transcribe this text

[Assistant] I'm so sorry you were forced to make such a hard decision.


[User] Please transcribe this text

[Assistant] I'm so sorry you were forced to make such a hard decision.


[User] Please transcribe this text

[Assistant] I'm so sorry that you had to go through something like that.


[User] Please transcribe this text

[Assistant] I'm so sorry that you had to go through something like that.


[User] Please transcribe this text

[Assistant] I'm so sorry that you had to go through something like that.


[User] Please transcribe this text

[Assistant] I'm so sorry you didn't win the scholarship you were hoping for.


[User] Please transcribe this text

[Assistant] I'm so sorry you didn't win the scholarship you were hoping for.


[User] Please transcribe this text

[Assistant] I'm so sorry you didn't win the scholarship you were hoping for.


[User] Please transcribe this text

[Assistant] I'm so sorry you got blamed for something that wasn't your fault.


[User] Please transcribe this text

[Assistant] I'm so sorry you got blamed for something that wasn't your fault.


[User] Please transcribe this text

[Assistant] I'm so sorry you got blamed for something that wasn't your fault.


[User] Please transcribe this text

[Assistant] We need you to make a matching blouse for this skirt.


[User] Please transcribe this text

[Assistant] We need you to make a matching blouse for this skirt.


[User] Please transcribe this text

[Assistant] We need you to make a matching blouse for the skirt.


[User] Please transcribe this text

[Assistant] We need you to make a colorful mural for our company.


[User] Please transcribe this text

[Assistant] We need you to make a colorful mural for our company.