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[Assistant] It's photo time, man, and they deserve it here, back center stage as an entire squad still wearing their medals.


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[Assistant] Uzi and the rest of the RNG squad. Much deserved victory here in Paris, France, but that is going to do it for MSI 2018. So for myself, the casters, and the entire live broadcast crew, thank you Paris. Thank you for watching, and we'll see you next time for more international action.


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[Assistant] Maybe we can get you a dinosaur balloon. Are you?


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[Assistant] That's right. We have to find George a dinosaur balloon.


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[Assistant] Most important of all, we need a dinosaur balloon for George.


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[Assistant] Don't worry George, I've got an idea. Could we have two of the long balloons please? Watch this everybody. What is Daddy Pig doing with the balloons? There. Can anyone guess what it is?


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[Assistant] I was travelling on the eight o'clock train to London, said the man.


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[Assistant] Do you always catch such an early train? asked the inspector. Of course I do, answered the man. I must be at work at ten o'clock.


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[Assistant] Would a later train get you to work on time? asked the inspector.


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[Assistant] I suppose it would, but I never catch a later train.


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[Assistant] At what time did you arrive at the station? At ten to eight. I bought a paper and waited for the train.


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[Assistant] And you didn't notice anything unusual? Of course not.


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[Assistant] I suggest, said the inspector, that you are not telling the truth.


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[Assistant] I suggest that you did not catch the 8 o'clock train, but that you caught the 8.25 which would still get you to work on time. You see, on the morning of the murder,


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[Assistant] It broke down at Fern Green station and was taken off the line.


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[Assistant] I have just received a letter from my old school.


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[Assistant] All those who have contributed towards the gift will sign their names in a large album which will be sent to the headmaster's home. We shall all remember Mr. Page for his patience and understanding.


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[Assistant] And for the kindly encouragement he gave us when we went so unwillingly to school.


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[Assistant] A great many former pupils will be attending a farewell dinner in his honor next Thursday.


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[Assistant] It is a curious coincidence that the day before his retirement,


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[Assistant] Four. Written by Marianne Marazzi. Illustrated by Luciana Navarro Powell.


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[Assistant] I like my new shoes so much. I don't want to ever take them off.


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[Assistant] There are many different places to travel to around the world. Some of them are nature spots and some of them are popular cities. But sometimes in English you're even asked about your hometown or somewhere you know well.


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[Assistant] Name and location, location in relation to other places, and three key features or characteristics. This is how you talk about a place in English. And today I'm going to teach you exactly how to do it.


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[Assistant] Welcome to Speak English with Tiffany. I am Teacher Tiffany. Let's jump right in.


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[Assistant] Name and location. Okay, so the first thing that you want to do when you talk about a place in English is to state clearly which place you will be talking about.


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[Assistant] You also need to give a short description of where that place is located. So to do this, you need two sentences, the first part of the formula.


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[Assistant] The first sentence involves giving the exact name of the place. And the second sentence requires you to tell where the place is located.


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[Assistant] This right here, what you're looking at is actually the Brooklyn Bridge. And if you ever have an opportunity to visit America and come to New York, you must visit the Brooklyn Bridge. It's one of the oldest roadway bridges in the United States.


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[Assistant] If we're using this first section, these first two sentences to talk about a place, let's say the question is, where is your hometown?


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[Assistant] Now remember, we have two sentences for this section. The first one is, give the exact name of the place. And the second one is, tell where the place is located. So, let's get started.


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[Assistant] Where is your hometown? The first sentence is my hometown is New York City.


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[Assistant] And my second sentence is, it is located in the state of New York. So I have answered both of these sentences. But I want us to look very quickly at something in this sentence. It is located in...


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[Assistant] Dot, dot, dot. So, you can actually use this same sentence pattern when you are talking about a place. It is located in dot, dot, dot. So remember that, okay? Alright, let's keep going.


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[Assistant] Now, the next section is location in relation to other places.


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[Assistant] The second thing that you want to do when you talk about a place in English is to explain where it is in relation to other places.


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[Assistant] You also need to give details about the distance from the other places. You see, this requires three sentences, the second part of the formula. Now, the first of these three sentences is to list two places that are close to the place you will talk about.


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[Assistant] The second of these three sentences is, give the distance from the first place. Now don't worry, I'm gonna explain exactly how to do this. And the last one is, give the distance from the second place. Okay.


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[Assistant] The Philadelphia City Hall. Now, Pennsylvania is near New York. That's why we're looking at this. Now, just to give you a little bit of history, Philadelphia City Hall was actually constructed from 1871 all the way to 1901.


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[Assistant] Yep, it took a total of 30 years to build this building. This is in Philadelphia. Now,


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[Assistant] If we're gonna use this and move on to the second part of our answer, remember the question was, where is your hometown?


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[Assistant] This is how our response would look. Okay, remember there are three sentences. List two places that are close to the place you will talk about. So, it says right here.


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[Assistant] Pennsylvania and New Jersey are not too far from New York City. Now, this is the first of the three sentences, but I want you to look at this sentence pattern. So you see here we have Pennsylvania and New Jersey. So this is one


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[Assistant] And this is two. Remember we said talk about two places. So.


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[Assistant] Pennsylvania and New Jersey are not too far from, and then we have New York City right here.


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[Assistant] From, and then the last place is the place you are actually.


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[Assistant] Talking about. So that's the pattern you can use. Again, for this first one right here. So one and two are not too far from dot dot dot. Alright, let's keep going.


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[Assistant] It takes about three and a half hours to get to Pennsylvania from New York. So again,


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[Assistant] For the second sentence, we're talking about the distance from the first place, okay? Now, this first place is just actually talking about New York City, the main place that we're discussing. So, for this pattern, you can say, it takes about, and you can choose the time period right here,


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[Assistant] Three and a half hours is the time that I chose to get to, remember this right here is gonna be one, the same one right here.


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[Assistant] From, and this right here represents this place right here, okay? So it takes about, dot dot dot, which is the time period, to get to, this is the first place we're talking about right here, from here, okay? Now, let's go to the third sentence, okay? But, so now we have a comparison,


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[Assistant] It only takes about two hours to get to New Jersey from New York. So remember the third sentence is also talking about a distance, but we kind of want to use a comparison. So we said,


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[Assistant] But it only takes about. So you can use the same sentence pattern. But it only takes about and then you give a time period.


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[Assistant] This time needs to be less than this time. Okay. All right. But it only takes about two hours to get to this right here is number two right here. Number two.


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[Assistant] From New York. Okay, again, New York is the main place we're discussing. So again,


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[Assistant] The next thing we're going to do is look at the three key features or characteristics. Now, the third thing that you want to do when you talk about a place in English is to give the key features or characteristics of the place you will be talking about.


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[Assistant] You should focus only on three key features or characteristics, okay? That's very important. Only three key features, alright? Now, for this section, you need seven sentences, okay? This is the last part of the formula. You need seven sentences. So, the first sentence will be,


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[Assistant] Clear, I guess, precursor. Precursor just means giving information in advance. Okay, to what you're gonna talk about. Then the second sentence is, give the first feature. Then the third sentence, give more information about the first feature. The next sentence, give the second feature.


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[Assistant] If we're gonna apply this to the last portion of our talk,


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[Assistant] Remember, where is your hometown? Remember there are seven sentences. So, the first one is, state how many features you will talk about. So, I will say, there are three key features of New York City. So you see what I did right here? There are three key features of. You can use this pattern.


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[Assistant] Precise when I said three, because I said we want to state how many features, alright? So, there are three key features of New York City. The next sentence, give the first feature.


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[Assistant] First, New York City is known for all of the places it has to shop. So in my first sentence I said, my second, excuse me, the second sentence talking about the first feature, okay, clearly understand that. First, then I say the place.


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[Assistant] This place is popular because, so is known for. It means that many people know this specific thing.


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[Assistant] About this place, okay? So when people think of New York, they think about these things. So again, let's keep going.


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[Assistant] Third sentence, many people come from all around the world just to shop there.


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[Assistant] So what I've done is I've given more information about this feature. Okay? We talked about shopping and then we gave more information. We said many people come from all around the world just to shop there. Okay. And now what I want to look at real quick here is just to dot dot dot.


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[Assistant] Now, this is another way of saying because. Okay, this is short for because.


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[Assistant] But it emphasizes the reason. Let's see if we can write this. Emphasizes, okay? Emphasizes, alright?


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[Assistant] Emphasize it. So for example, I went to the store to get water. I may have also went to get other things. But if I want to emphasize that I only went for water, I can say, I went to the store just to get water. That's the only reason, okay? Emphasizing it, right?


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[Assistant] Alright, let's keep going. So now we're going to go to the fourth sentence, which is give the second feature. Alright, so second, it is a melting pot of people from many different countries. So again, you can just say second, but I want to explain this expression right here. Melting pot.


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[Assistant] Are grouped together. Okay, are grouped.


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[Assistant] So they can live together or they can just be together, okay? Be together, live together, or work together. We call that a melting pot. A place where many cultures or races are grouped together, okay? Alright, let's keep going. Now we're looking at this sentence right here, which is the fifth sentence, okay? Alright, so we're gonna give more information.


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[Assistant] This makes New York City a very interesting city to live in. So because it's a melting pot, we're saying it's very interesting, giving a little bit more information.


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[Assistant] Now let's keep going on to the next sentence. So it says, the third key feature of New York City is the night life. Alright, now let me explain what night life means, okay? So night life just refers to a place that has a lot


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[Assistant] To do at night. Okay, a lot to do, let's get on here, at night.


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[Assistant] So for example, some people like to go out to eat, but usually after 9pm things are closed. But in New York City, things stay open till midnight or 1am or 2am. So for those that want to go to a club or they want to go to bowling or something to do at night,


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[Assistant] Whereas in other places those things are closed, in New York City there's a lot of things to do at night. If you want to party or enjoy yourself at night with your friends. Late into the night. So we say night life. Okay? And let's keep going. This is going to be the final sentence.


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[Assistant] No matter what time it is, you will always find something to do in New York City. So again, given more information, and we said no matter what time it is, okay? So no matter what time it is just means 24-7, 24 hours a day.


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[Assistant] Seven days a week. It's a kind of way of kind of exaggerating that something is always open. Now, of course there are times when things close, but no matter what time it is just refers to something always being available or always being open. Okay. No matter what time it is. Okay. That's how we use that. All right now.


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[Assistant] This is how you would talk about your hometown, a place. So again, doesn't matter if the question is about your hometown or any other place. You can use this formula 237 to talk about any place in English.


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[Assistant] Now, if you have yet to receive your free ebook, you need to go to my website to get it. And if you want to get other ebooks, go to speakenglishwithtiffani.com slash ebooks. And if you want to study my courses or study with me in my courses, go to speakenglishwithtiffani.com slash courses.


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[Assistant] Look on the left side of your screen and watch my next English video lesson. And remember to always study English.


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[Assistant] The sky is getting darker and darker. There is going to be a thunderstorm.


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[Assistant] Thank you very much. Quick shot. RNG knows they had game two in the bag and they're playing game three like they know that. Trying to strike back, trying to close it out in four and they pushed the series to two and one.


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[Assistant] And just to put a stamp on your point, Jatt, about what that does, winning the mid lane for RNG to the rest of the lanes, Uzi's 10k timing. Do you want to guess? I'm going to say 19 minutes 50 seconds. 1847! Oh, are you kidding me? 1847!


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[Assistant] And here again, another crushing defeat in game three. They gotta put two together back to back, Papa Smithy. It can't be done.


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[Assistant] I have to imagine that pressure is only growing and growing and growing again. We have to remember that a lot of these guys on King's Zone at international tournaments have fallen short. So on top of living up to the ghost of SKT, it's about defeating their own demons, right, that have been plugging them throughout their tournament or rather their careers.


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[Assistant] Well, it's not us who has to have the answers, it's Kingzone, right? So RNG here on Matchpoint, they're on the cusp of claiming the title of MSI Champion. We'll see if Kingzone can bring this series to Game 5 when we return.


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[Assistant] So uhm, I kept on rewriting the title. This is not a bad title for this class. Another way of looking at it is instead of.


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[Assistant] Trying to move forward from here where everything is confusing and...


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[Assistant] The present looks like reality. We want to go out to the future and bring it back.


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[Assistant] And we talked about some process and methods. Today we're gonna talk about a few of the gazillion things. Of course I didn't get done last week, which made


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[Assistant] This week even more and finally I decided screw it, I'm gonna do this, both of these talks again without an audience.


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[Assistant] To do them to their natural length because the destiny for this is being online and online people are not confined to 50 minute hours. And I'm sure Sam is all for that. Great. So, again, here's my email address. Out of all the people who are tuned into this talk and in the classroom, I got three emails. One of which was interesting.


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[Assistant] Either or both of my talk isn't interesting or you're not interesting or both. So try and at least disabuse me of the latter.


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[Assistant] Okay, so to start off with, here's Leonardo. Pretty smart guy.


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[Assistant] Imagine if you were born with twice Leonardo's IQ. Think of how easy it would be to get into Stanford.


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[Assistant] Maybe you do have twice Leonardo's IQ, but suppose you were born with twice Leonardo's IQ in 10,000 BC. How far are you gonna get?


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[Assistant] Before they burn you at the stake or whatever they did back then. Yeah, so.


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[Assistant] Here's a guy with nowhere near Leonardo's IQ, Henry Ford.


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[Assistant] And whereas Leonardo could not invent a single motor for any of his vehicles, think about that.


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[Assistant] So he was smart, but he wasn't that smart. Henry Ford was able to...


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[Assistant] Put together processes that allowed him to make millions and millions of cars for about 800, sell them for $800.


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[Assistant] In the 19th century made much more difference than any level of smartness. And where did that knowledge come from? It came, might as well pick Newton if you're gonna pick anybody. It came because the context was changed from the


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[Assistant] That change, a change in outlook, we could call it a change in context, worldview, point of view, whatever you want.


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[Assistant] So I'm numbering rules for you. I decided to go back and start with zero.


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[Assistant] So the zeroth rule here, probably the most important one is, uh, to make progress here, uh,


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[Assistant] Context, let me move this guy off. Context or point of view is worth 80 IQ points. If you've got the context of science and math, you are gazillions of times smarter


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[Assistant] A person who learns calculus with an IQ of 110 or 120 can do things that the greatest geniuses of the past can't do. Okay, so uhm,


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[Assistant] We can sum that up by saying knowledge is silver, context is gold, and IQ is just lead. It's a lead weight on you.


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[Assistant] Biggest problem with most people who are at your level.


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[Assistant] And going to the next level is you're always the smartest people in your classroom or room at home.


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[Assistant] And if you happen to be a room that had the hundred smartest people in the world, and you were the smartest person in that room,


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[Assistant] You're still not as smart as the other 99 working together.


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[Assistant] And this is the simplest snare, it's the IQ Snare. Tony Hoare, really great guy, was here at Stanford for a while, touring winner.


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[Assistant] So people are so clever writing the program, they forget that debugging is harder. And that's true about anything. So that's principle number one, we had zero. And here's a summary of what I showed you.


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[Assistant] The number two one at the top there is that the goodness of the results correlates most strongly with the goodness of the funders. This is the simplest way of summing up the past. Because you have to realize


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[Assistant] The difference in the past wasn't that the people were smarter back then. We weren't smarter than the smart people today. Every generation has really smart people. The difference in whether you get enormous results or not,


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[Assistant] Is in this context idea and the funders that support it.


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[Assistant] One of the ways of thinking about them is, as opposed to getting gold medals like a bunch of us have gotten,


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[Assistant] In our 60s and 70s, 40 years after we did the deeds, good funders give out the gold medals ahead of time knowing that 70% of them are going to turn to lead.


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[Assistant] So this, this will be a slide that you can use later on. It's basically what I said last time. And last time we looked at four systems.


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[Assistant] Uh, Sketchpad, we didn't really look at the Engelbart system, but it's easy to find out about online. We looked at...


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[Assistant] The first really good gesture system grail and we saw that Ivan Sutherland again invented VR long long.


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[Assistant] Before it ever came to use and I really rushed past personal computers and the first thing


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[Assistant] It was kinda like a personal computer. It was kinda cute. It was Harry Husky's.


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[Assistant] Uh, Bendix G15 in the mid fifties. So this is really early. Harry just left us.


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[Assistant] A few years over the age of 100, really wonderful guy.


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[Assistant] Here's my vote for the first real personal computer called The Link by Wes Clark. Wes Clark also did the building size computer that Sketchpad was done on, so he liked to work both large and small. Here's one I did with Ed Cheadle. Uhm, looks kind of modern. And,


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[Assistant] From Seymour Pappert, what children can actually do with computers and that seized me in a romantic fashion.


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[Assistant] And we looked at this idea of better and perfect are the enemy.


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[Assistant] Of what is actually needed. In other words, you have to draw thresholds in order to know where you are, else you're just measuring local variations. You don't know whether they're good or bad.


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[Assistant] And the last thing we did on Tuesday was looking at this process of


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[Assistant] Taking a glimmer of an idea out 30 or more years to see.


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[Assistant] Now five or eight years later you've got something that will revolutionize the world. This is where the trillions rather than, than billions comes in because you create an industry. And last time I didn't get a chance to show you kind of what


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[Assistant] Today, and this is a self-portrait because now I'm, I, I have extracted stuff from a demo, but this is a system we brought back to life from 1978. So you get a chance, and this is a self-portrait. So this is the, the successor to the Alto called the Dorado, so it had


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[Assistant] Now an X, bigger than X VGA screen rather than the portrait model and


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[Assistant] This dithering technique was invented at the same time in the 70s by Bob Floyd and Steinberg.


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[Assistant] And partly done at park, so this is what a typical image on.


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[Assistant] Only a few computers in the world look like back then, one bit per point. And where do we get this, uh, system from? Well,


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[Assistant] Here's the Xerox dump, and if you look closely there, there's a disc pack. Actually got Xerox throughout most of the disc packs of the work that was done at Xerox Park. A few of them got rescued. Here it is.


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[Assistant] Few hundred files on there. One of them happened to be most of a system that we did in 1978.


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[Assistant] And it's a partial interest because the next year it was the stuff that Steve Jobs got shown during his famous visit to.


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[Assistant] So you have a little flavor here. Now what we did is we brought this back to life. Uhm.


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[Assistant] And it was relatively easy because this system is called Smalltalk, Smalltalk 78.


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[Assistant] Is a pure object system and so it resembles the internet. This is a internet self-portrait and it's just as good a self-portrait of small talk because the idea was to have the


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[Assistant] One to one correspondence between the idea of little logical computers, which is what we called objects, that could


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[Assistant] Uh, one of the consequences is that there are no actual applications because you can mix and match objects as you choose to. Here we see something that is vaguely familiar. Thought I turned that off. Okay, so.


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[Assistant] This is a typical screen back then and it ran on the Alto there, the portable note taker and the Dorado.


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[Assistant] Here's a bitmap painting I did 45 years ago that we found and stuck in here. See the user interface is


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[Assistant] With the object itself and here I'm marking it up and it has a character recognizer.


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[Assistant] Just a recognizer like Grail did. There it's recognizing I want an arrow and making one. The overlapping windows, the icons.


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[Assistant] What would be called rich text today and you can see the gesture recognizer is being used to tell it how to justify.


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[Assistant] And this system is organized in terms of projects.


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[Assistant] So each project you can think of in today's terms as a separate desktop, they're, they persist over time.


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[Assistant] I think about this compared to the user interface today where you use an application that doesn't have every feature that you want and you start and stop applications and


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[Assistant] Here what you have is just working spaces.


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[Assistant] Kind of thumbnails of each one of them. We can go into one of them.


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[Assistant] Uh, here's a little thing done by a 13-year-old girl.


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[Assistant] Writing an article for Creative Computing back in 1975. And uhm, so you can see it's sort of like desktop publishing.


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[Assistant] So, but in fact, any object can be used in here and so, for example, if we look.


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[Assistant] Here, she's telling about this, how she used the program and how she's typing.


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[Assistant] Uh, in there, uh, she's typing in code and it's being executed to grow the box and turn the box and, and so forth. Alright, get the idea? So.


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[Assistant] Be nice if Wikipedia had even thought about this, right? Because imagine you go to the article on Logo.


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[Assistant] Guess what? You can't execute logo code in there. Why? It's on a computer. What didn't they get about computing? Well, pretty much everything. If you look at it closely, you'll see the web


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[Assistant] Design in the web browser are two of the worst things ever done in computing.


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[Assistant] So if this were a normal system and it didn't have that feature, we'd be done, but we can...


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[Assistant] Relate objects to each other. So here we're single stepping to get to that frame that we'd like to change. We're looking at the interface of


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[Assistant] This bouncing guy and we're seeing, oh yeaah, there's a thing called current frame, that's what this thing is.


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[Assistant] And here's our painting window and let's look at its interface.


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[Assistant] And here's something that allows me to set the picture.


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[Assistant] In there and I want to connect the two windows together so I use the gesture recognizer to draw a line between them.


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[Assistant] Gives me a little place to explain how I'd like to relate them and I say, well the painter's picture wants to be the bouncing animation's current frame.


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[Assistant] So I say, okay, go ahead and do that and now it's latched on to that thing that's there. Now I can start the animation going again. But while it's going, I can paint, look carefully and you'll see that.


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[Assistant] The thing is being painted while it's running. Wouldn't you like to be able to do that today? I mean, just think about why not?


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[Assistant] This is like sketch pad, right? Except a few years later. Yeaah. This is completely natural to what you-


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[Assistant] This particular thing gives you automatically something much more powerful than PowerPoint because all you have to do is sequence.


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[Assistant] Various inventions there. We can look at this. Now I'm answering Sam's question.


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[Assistant] Idea actually made it out of Xerox PARC, well about half. We'll see that, see what the other half is in a second.


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[Assistant] How about the, the GUI? Well about 70% because you notice the GUI didn't come out as something that has


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[Assistant] Uh, this unlimited desktop idea. Even today, 30 some odd years after this, nobody has put it in there. It's ridiculous. But it has to do with people wanting to, uh,


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[Assistant] Have applications and sell applications even though most applications won't do all the things that you need.


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[Assistant] The way we did programming, only about 10% has come out, and I won't go into all the differences, but I think you've seen some of them. Laser print are about 90%.


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[Assistant] Postscript, uh, 100%. That's partly because the guys who did this at Park, uh, formed Adobe. Keski and Warnock. And so they...


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[Assistant] Sold as in their company what it was that how they thought you should be able to do.


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[Assistant] Printing 100% of the ethernet, there was no competitor.


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[Assistant] About 50% of peer-peer and client server. We'll see why in a second.


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[Assistant] 100% of the internet, again, there's no competitor for. There's no.


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[Assistant] And so, one way of looking at this is what came out.


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[Assistant] Most successfully were the things for which people already out there didn't think they already knew how to do it.


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[Assistant] So everybody knew how to program, and so the biggest resistance was in how we did programming. That just didn't...


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[Assistant] Now here's three things that I didn't mention before because none of them made it.


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[Assistant] But one of them was, hey, the architecture of the Alto.


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[Assistant] to get them to adopt these architectures for the chip and zero. Intel especially at the time


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[Assistant] They had to be dragged kicking and screaming even to do CPUs. Andy Grove, for instance, was against the first CPU on a chip that Intel did.


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[Assistant] The idea of the Dinah book didn't make it out.


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[Assistant] Uhm, if you think about it, when did the iPad decide to put a stylus and a keyboard on the iPad? Right? The iPad Pro. They couldn't. Why couldn't they do it? What was their problem?


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[Assistant] So 10% of that idea came out. Now here's an interesting idea to think about. Here we've got the, uh,


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[Assistant] The internet of machines connected together and if your programming language happens to be a software internet like Smalltalk was, then you can map the objects into the network and you can migrate the objects around.


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[Assistant] Each object is self-contained. They do messaging the messaging.


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[Assistant] Is either done internally or goes out on the internet and so you have a solution for all the different scalings of computing that you have whether it's a small device, yes.


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[Assistant] He completely went away. All he was doing was selling sugar water to babies.


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[Assistant] And when I first, you know, and he sent me the first iPad for my comments on the thing. The first thing I did was to go out and get a capacitive stylus and draw lines with a ruler on


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[Assistant] I guess it was Autodesk, one of the Autodesk software that was pretty good and I determined that the touch sensitivity on the iPad was fabulous.


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[Assistant] Despite the fact that it's done in a very, very complex way, because it has to find centroids.


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[Assistant] By experiment whether a purely stylus driven system was actually enough to do the work that you wanted to do and the answer is no. Similarly with angle bar you could do every


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[Assistant] Piece of text entry without using the keyboard, but they had a keyboard there because you just can't do it fast enough.


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[Assistant] For being able to put in large amounts of, of text. You need to have a keyboard.


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[Assistant] That Engelbart said, they said, well, why do you have to learn your system?


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[Assistant] Back then, he said, well, people are gonna use their computers for six to eight hours a day. And they laughed at him. So what you guys are doing.


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[Assistant] And using interfaces that are made for a couple of seconds a day.


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[Assistant] What you're supposed to learn about and you can't do it in a dump like this.


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[Assistant] You have to have some sense of design around, and I'm not sure you can do software without having some sense of design around. So, how could, no. I won't, I won't make any really rude remarks, but. So.


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[Assistant] And just to use up time I don't have.


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[Assistant] I should point out that, you know, some of this migrating object idea was done at Park. A really great follow-up was done by a visitor to Park, Jerry Popek.


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[Assistant] Who then went, who was at UCLA went back to UCLA and did a fabulous system.


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[Assistant] Uh, using Unix as the base, called Locus.


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[Assistant] L-O-C-U-S, and if you're interested in looking at a future that will some, at some point actually happen.


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[Assistant] You can get that book from MIT Press, and particularly the first couple of chapters of that book, outline what the issues are for dealing with real scaling on the internet. I won't go further than that. So zero.


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[Assistant] You have to have enormous ideas in order so that


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[Assistant] People not understanding them will retain something.


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[Assistant] You don't want to have the low pass filter give you back a dial tone.


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[Assistant] That happens on, because most of the, you know, most ideas are mediocre down to bad, even by people who have good ideas. Those are the ones that you don't want to work on. Because if you're successful on them, they're still gonna get peeled at.


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[Assistant] But this is a book, this is not a book about Xerox PARK, Sam.


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[Assistant] This is a book by an executive at Xerox.


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[Assistant] Written in the 60s before Park about trying to get the Xerox machine adopted.


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[Assistant] And this was after Xerox had been the fastest growing.


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[Assistant] Uh, but one of the companies that turned down the complete rights for a licensing fee to the Xerox machine was IBM. That story is in this book. And IBM's consultant said,


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[Assistant] Well, this isn't gonna work because, uh, there's no market for plain paper copying because people are not copying. Well, of course, it wasn't a good copier back then. And so I could write a book, RUs with Xerox to trillions nobody wanted. I didn't have time to make a, a picture that looks like John Dessauer. So it doesn't matter, and I'm gonna try and explain to you in the time I have left,


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[Assistant] Why the goodness of an idea is almost irrelevant.


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[Assistant] Now for the reality kit. Get out your reality kit. And we're gonna deal with the top.


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[Assistant] So just break the seal and just open up the,


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[Assistant] And this will work best if you put it down on your thing like this. And look at the instructions.


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[Assistant] Did you get a reality kit? Okay, everybody got one? What happened? Where were you?


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[Assistant] Boy. Hey, you know what? You guys must have been late.


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[Assistant] Look at the plus with your left eye and then slowly move the thing in.


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[Assistant] Keeping focused on the plus until something happens. Slowly move slow. Slow as in the word slow.


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[Assistant] Because if there was a god, he gave squids a great eye and he gave us a bad one.


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[Assistant] Our eye happens to have the blood vessels in front of the light detecting cells.


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[Assistant] And so our brain has to figure, filter out all of those also.


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[Assistant] And over here is where most of your acuity is in an area called the fovea.


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[Assistant] So when the thing is further away, you get something like this and when you move in, at some point the...


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[Assistant] Dot gets over where there are no light sensitive cells at all and you can't see it anymore. And as my friend over here said, somehow the brain fills it in. And we'll look at that, uh, in a second.


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[Assistant] So principle number 22 is we have a blind spot in our eyes that our brain makes up stuff to fill in. It's just making it up. Think about this because what's the other case where your brain makes up stuff that you think is real?


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[Assistant] Most people think they only dream at night, but in fact, human brains are set up so that we actually dream. Did you get one of these?


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[Assistant] And a powerful idea about that is number 23 is that we can't learn to see until we realize and admit that we're blind. And the biggest problem with most human beings is they don't understand that they are blind because they think they can see.


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[Assistant] This leads to most, much of the trouble in the world. And the powerful idea about that is the zeroth one again, is it makes it


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[Assistant] Huge difference if ideas are experienced in as many ways as possible. In other words, perspective point of view is worth 80 IQ points.


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[Assistant] Just because something seems to be right. And this is why math is a danger.


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[Assistant] Okay, let's go to the poker chips now. Pry them loose.


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[Assistant] Okay, and what you're gonna do is hold them up like this. So one is about twice as far away as the other.


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[Assistant] Think about it, if it's twice as far away, it's subtending half the angle.


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[Assistant] And therefore it should show up as half-size, but it doesn't show up as half-size.


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[Assistant] Now we can put, stick these guys on a ruler. Since these poker chips are now yours, you can take it back and really science the shit out of it.


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[Assistant] Here's what we should see, that's what's on our retina. Descartes, by the way,


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[Assistant] Got an oxeye and peeled the back of it off to see whether, uh, biological lenses actually acted like glass ant lenses and they do.


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[Assistant] The cells in your brain are like the hardware and there are processes going on.


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[Assistant] One set of processes are all the ones that have to do with our belief system. And before we recognize something, uh, it goes through our belief system.


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[Assistant] And then it goes into the real time version of our belief system which is called the dream. So we have beliefs in the dream and our beliefs


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[Assistant] Are, damn it, these things are the same size. By the way, you can do this with oranges, with quarters.


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[Assistant] Anything where you know they're the same size do the same thing and so the result of


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[Assistant] Uh, information from the actual world combined with your beliefs, you wind up with this.


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[Assistant] And everybody who's, anybody here is an artist who can draw.


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[Assistant] You must know this illusion then, right? It's called size constancy. And it's why


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[Assistant] Hi and wow, that's only half size compared to this guy who's closer to me.


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[Assistant] Doesn't look like it to me. It looks like it's almost the same size because I- heads are the same. Got it?


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[Assistant] So the principle 24, the mind's eye is different than our sensory eye.


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[Assistant] And we do things according to the mind's eye, and most people who have ever lived on this planet don't know that there are two different eyes. Because they take the world as it seems.


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[Assistant] They build up a common sense from the world as it seems. This is why human beings generally cannot think. You can't think if you're doing this stuff.


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[Assistant] So another term for beliefs is a private universe. We each have one of our very own.


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[Assistant] If you've ever argued with somebody you thought was reasonable up to that point.


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[Assistant] What's happening is your beliefs are conflicting with their beliefs.


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[Assistant] I love this phrase. This is a new phrase, alternate truths. Kellyanne Conway. That's what's going on. So you can see why being a scientist is tough. A scientist has to get around all of this crap that our brain is throwing up.


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[Assistant] Okay, so quick, easy model is how random this is, is a little bit of rain water on dirt.


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[Assistant] Dislodges a few crumbs of dirt and a little gully happens and the gully is more efficient at rooting water so things start happening. Just where things start happening. Originally you get something like this. Completely random, it could have gone anyway. And you make a whole world out of it. Here's a world that's completely pink. If you've ever been in the Grand Canyon. It is just almost overwhelming. If you look up,


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[Assistant] You have to remember to look up. There's a little bit of blue sky up above. And the problem with human beings is we don't look up. We look out.


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[Assistant] That's a pink plane and our thoughts are like ants crawling over it.


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[Assistant] We can think about things, we can make progress, we can run into an obstacle, we can get around the obstacle.


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[Assistant] And so forth, but everything we're doing here is pink except we don't know it's pink because we've never been in anything else but pink. So this is like a fish not knowing it's in water. It's always been in water.


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[Assistant] Every once in a while you might have a little outlaw thought, a little blue thought, but you've been to school, you're going to Stanford, you go to church, temple, synagogue, mosque, whatever it is, because our beliefs project out. And when we see something that isn't normal, normal is actually the same as crazy. Smash.


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[Assistant] Maybe you're out for a run, you're just waking up in the morning, you're taking a shower, and all of a sudden, you get a holy shit.


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[Assistant] Holy shit. There's a blue world. A blue world that's orthogonal to the one I'm in. Once you're in that blue world, you realize, oh, there's probably a lot of them. Can you see each one of these as a context?


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[Assistant] Can you see that what happened from the Renaissance by Newton?


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[Assistant] To our modern age was going from a pink plane to a blue plane. Right?


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[Assistant] This is what ARPA did with computing. It went from mainframes to completely different way of thinking about things.


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[Assistant] To, uh, to the world we have today, despite the fact that nobody had thought of it at all. It was considered literally crazy by our colleagues in computing when we were doing it. Okay? So here's the compa- you just leave the compass on there. It's for you to remember that some people get to this really early. Einstein was five, he was recovering


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[Assistant] From having the measles, I think his father brought him a little compass for him to play with and Einstein


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[Assistant] Remembered later in life, he said this made the most impression of me, of anything in my childhood. Because the way he looked at it, oh, there must be something deeply hidden behind things.


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[Assistant] He didn't take it as it came because he was worrying about how does the needle know where to go? There's nothing visible about it and yet it is doing this.


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[Assistant] And that changed Einstein's complete way of, of thinking about things. Okay?


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[Assistant] So when a baby is born, when we are born, we're not born into nothing, we're born into a culture.


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[Assistant] Most cultures over the last, uh, hundred plus thousands of years were traditional cultures, hunting and gathering cultures.


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[Assistant] And traditional cultures don't know that they are inside a particular outlook. Traditional cultures think they're in reality. And so they react incredibly strongly to other people's versions of reality. To the point of war.


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[Assistant] And many people, this is what our genes give rise to, and many people today, including in our country, are born into this pretty natural way of looking at things. We had to invent the idea of outlook, and well here's another one. So if you happen to be born here, you're not


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[Assistant] French in its outlook, French in language, and so forth. So a guy by the name of Marshall McLuhan asked the question,


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[Assistant] What are books? What is writing as an environment? If you thought of writing as being brought up in France, what would that actually mean to the human race? Turns out it's profound. Take a look at it if you're interested.


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[Assistant] You also ask, what is media as an environment? So for example, what is this as an environment? 24-7.


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[Assistant] That we have today is doing exactly the same thing and most people don't realize.


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[Assistant] There's a little desktop here, tabletop. So look at the picture there first and before you start experimenting let me make an assertion that the tops of the tables are exactly the same shapes.


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[Assistant] I've been doing this hundreds of times and I can't see it, but if I take my plastic thing and move it over there,


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[Assistant] Because crazy is not having good models in our mind for what's going on out there. We just draw the line at certain kinds of crazy, but we are actually crazy. So this is a really good one, isn't it?


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[Assistant] Uh, happens to have been first done here at Stanford. This guy is Roger Shepard. And that is his book. It's full of these.


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[Assistant] Anthropologists over the last 120 years or so studied several thousand traditional cultures and wrote down properties of these cultures that were never absent.


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[Assistant] Uh, thought of as human universals. Virtually all of them are genetic. And, here's a book. You know, books are actually useful. It's another good one to read. This is, yeah.


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[Assistant] Okay, so the basic idea is genetics drives culture. Genetics has the precursors, the desires, and culture fills in the parameters. So you can think of these, they're all category names. And,


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[Assistant] Once that list was made, people got interested in things that were not in every culture. And this is a partial list of those.


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[Assistant] So agriculture had to be invented. It was a pretty easy invention, but it was only invented about 12,000 years ago.


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[Assistant] Out of several hundred thousand years of us being on the planet, so.


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[Assistant] Initially, it was a hard thing for hunting and gathering people to think about.


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[Assistant] We've got, like every animal, we have zillions of genes to help us cope with things. We can deal with hardship like every animal, incredibly.


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[Assistant] But the idea of progress had to be invented. It's really an invention of the 18th century.


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[Assistant] And the reason is, is that for almost all of human existence, people died in the same world that they were born into. Almost nothing happened.


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[Assistant] And so, what you had to do to get from birth to death was to cope.


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[Assistant] It's only been recently that the idea of, no, we can shape the world to be better. That's a new idea.


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[Assistant] These are all powerful ideas. Oral language versus writing and reading. The differences are profound.


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[Assistant] Stories, superstition, religion and magic versus the representation systems of science. News. Remember, news never introduces a new category. Right?


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[Assistant] What you hear about is, oh, it's this forest fire, it's that war, it's this murder, it's this kind deed. This is why news can happen so quickly. And that's what our mind craves. What we hate is categories.


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[Assistant] Cause it can take us a couple of years to learn a category. So you never hear any news about calculus. Takes a couple of years to learn it. And there aren't enough people.


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[Assistant] This is one of the reasons why most programming languages go bad and the web browser went bad.


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[Assistant] Whereas a modern way of thinking about things is similarities over differences.


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[Assistant] Emphasizes similarities, has many things to do also with equal rights and democracy.


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[Assistant] Vendetta and Revenge, those are the favorite movies and the favorite video games are Revenge games.


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[Assistant] Personal revenge games where the system has gone bad and somebody has to break the law to put things right. We just love that trope.


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[Assistant] But in fact, the whole legal system was set up in order to avoid thousand-year feuds and vendettas.


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[Assistant] Okay, so we can think of this side, we have things that human beings want.


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[Assistant] And simple way of thinking about them is every single one of them on this side is a legal drug.


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[Assistant] And for people in this class who are trying to make money by being entrepreneurs,


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[Assistant] Just make a technological amplifier for any of these things that we crave. Genetically, look at the things that are there. Hunting and gathering, uh, social, uh, language, uh, like the telephone, uh, stories, news, theater, all of those things.


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[Assistant] That's your list. Just get this book. Right, Sam?


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[Assistant] Make something that will make people worse and they'll buy the hell out of it. Because we don't have


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[Assistant] We don't have any natural. All of these things are in shortage.


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[Assistant] In, uh, the world that human beings have been into except for a couple hundred years ago. Over here we have things that human beings need.


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[Assistant] And they're terribly, you can't really see, but these are terribly difficult to learn because they're not particularly genetically prepared for. They had to be, uh, uh, they had to be invented.


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[Assistant] We're not born into France or traditional society anymore. We're born into a universe that is unbelievably large. A planet that most people don't even realize we're on yet.


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[Assistant] Not just our social system of a few hundred people that we know, but millions of social systems and billions of people.


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[Assistant] That is starting to touch everybody in many, many different ways.


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[Assistant] It's only been, for instance, modern medicine really dates from only World War II. That's a long time ago for you folks, but


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[Assistant] Uh, it's within my lifetime. I was born before World War II.


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[Assistant] And before World War II, you simply did not get antibiotics when you had an infection. It was that soon. Doctor, doctoring was almost quackery.


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[Assistant] So, much of scientific medicine has happened in the last 50 or 60 years.


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[Assistant] And then we have the system of our mind.


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[Assistant] It is not just social but psychological, cognitive and so forth. And so we can sum up this world that we're born into in this century as the systems we live in and the systems we are. Think about that. The difference between that and what most people think that they want. These are the systems we have to learn about and deal with.


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[Assistant] And these systems are not separate. I mentioned them separately, but they're all intertwined with each other. They're all invisible.


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[Assistant] Okay, and I'll just leave you with this last slide.


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[Assistant] So we found out about all of these systems. They were invisible until


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[Assistant] Few hundred years ago and some of them invisible until a few years ago. And the human tragedy is in two parts. Part of it is just finding out something in our civilization doesn't automatically transmit it to people born into the civilization.


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[Assistant] Alright, the educational system has to be changed in order to reflect this stuff.


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[Assistant] And the composite picture here is that part of our brain, the genetic part of our brain, even overlaid with this stuff, still has


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[Assistant] Television to look at, things like video games to look at, things like Facebook to look at. If you're gonna go out and make a company that is going to appeal to people, try to do it without appealing to the parts of their nature that they're helpless in front of. Because one of the things that those of us who helped invent the technologies of today,


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[Assistant] Are quite worried about now is that the technology is so much easier to invent than it is to change the educational system. And so what we've got is the informational equivalent of cave people with nuclear weapons. But now they're informational weapons and


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[Assistant] Renormalizing human attitudes and human beliefs.


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[Assistant] Could very easily bring down our civilization and put us back into the Stone Age. The talk on Tuesday.


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[Assistant] Maybe a little thicker today, but the whole impetus behind, uh, the Arpa


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[Assistant] Uh, research and inventions of these things and particularly people like Engelbart was to, uh, try to invent


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[Assistant] New tools and new media for humanity to get itself out of its problems. And Engelbart, for example, said almost everything important that has consequence in the, in the adult world is done by adults working together. And so this is why his system was collaborative from the, so here's an interesting thing. So here's a Mac. Some people have Linux, some people have Windows on it.


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[Assistant] Here's the interesting thing. Not, not a single one of the main operating systems today has built into it the thing that Engelbart


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[Assistant] Showed in 1968, which is the intrinsic ability to share


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[Assistant] Any content that you're looking at with every, anybody else to the point of allowing them to interact with it and to talk back and forth. Right? Skype, it doesn't do it.


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[Assistant] It is possible to do but not a single operating system used today.


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[Assistant] Does it? And so the ability to actually work collaboratively on content has been held back


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[Assistant] By notions of operating systems that go back pre-1965.


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[Assistant] All three operating systems we have today that are the main ones are old, old ideas. They don't even get to where Park was.


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[Assistant] On, uh, the notion of how, uh, processes can coordinate with each other.


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[Assistant] And there are many, many other of these things. Because these operating systems are rather similar to each other and because they're pervasive, unless you use your reality kit,


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[Assistant] You're gonna think that they're normal and therefore that's the way things should be. Many people in computing


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[Assistant] Have a misplaced notion of Darwinian process. Like, like most people. Most people think Darwinian processes optimize. That is absolutely not the truth.


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[Assistant] One of my degrees in molecular biology and I can tell you, any biologist would say, they're absolutely not optimized.


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[Assistant] The whole point of Darwinian processes is to fit into some niche and some environment.


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[Assistant] Isn't the right kind of environment. The process of evolution is not going to give you something that's very interesting. That is the way it works. And as computing gets less and less interesting, its way of accepting and rejecting things gets more and more mundane.


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[Assistant] So this is why some of these early systems, like Sam, look at SketchPen and say, why aren't they doing it today? Well, because nobody even thinks about that that's important. Nobody even thinks of doing WYSIWYG on the, uh, on the web, on web media. I just typed in some answers to Quora and I was in a,


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[Assistant] I couldn't see what it was going to look like until I clicked the button. Come on, this is bullshit.


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[Assistant] But nobody is protesting except old fogies like me.


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[Assistant] Because I know it can be better. You need to find out that it can be better. That is your job. Your job is not to agree with me. Your job is to wake up.


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[Assistant] Find ways of criticizing the stuff that seems normal. That is the only way out of the soup. You have to go against your genetic impulses.


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[Assistant] To try and learn the environment around you. It's the most natural thing we have, but it's not gonna help. Because the environment is weak, and if you learn the environment, you're gonna be weak.


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[Assistant] George isn't listening. He's too busy putting the dolls to bed.


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[Assistant] So in terms of the timeline, when did you first start? Like you said 18 months ago, but what did that look like? The very first tenant I guess.


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[Assistant] You guys take on the lease. What are the terms of the lease that you take out? It's just a standard one year lease, then it goes month to month?


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[Assistant] We've seen a lot of people work on this idea and


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[Assistant] It seems like you can get about as far as you have gotten, which is really great.


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[Assistant] Because you actually have to take on the lease and because you have hard costs, sometimes these can look much more like a real estate business than a tech business. And so I think


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[Assistant] What I kind of want to get at is, are there ways that you can not hold the leases? Like, is there a way you can make this much more efficient from a capital basis? Because right now, this is basically a real estate business, right? And it sounds like there's some tech in there, but I haven't really gotten from you that tech is like the differentiating factor that will make, like, that


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[Assistant] Clearly, there's people that want to do this, uhm, and, okay, so it sounds like we have about five minutes left.


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[Assistant] What are the things you're thinking about that can make this as constructive as possible? Because like, you know, just to summarize,


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[Assistant] Sounds good, you're making money, like good job.


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[Assistant] Almost again, like a real estate business, and I've seen, that's kind of the WeWork model, right?


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[Assistant] So I've seen that happen. Uh, on the other hand, you can try to make this as asset light possible where maybe you're not taking the obligation of the leases, right? And then you can grow really fast and somehow have a special deal with the landlords where you can just like grow really fast and then you're a true marketplace because you're not holding any of the liability that right now you're holding.


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[Assistant] Got it. And one quick question when we're on that. Is there any insurance implications for this? What kind of insurance do you have to take out?


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[Assistant] And so you think that's the, that's the long-term defensibility thing is ultimately the community. I'm just trying to make sure I understand. So you're saying like, look, we're going to have the best community and the best brand for community. And that's what will attract people. Cause again, with this kind of business.


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[Assistant] These kinds of businesses, uh, churn kills ya. And the founders never realized that they have high churn until, like, you may be like, oh we have really great churn, everyone always says that, but like,


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[Assistant] And you don't, you don't have enough data yet, but over the long run, sometimes you can, things can creep up on you. And if all of a sudden you start to have high churn and then you're on the hook for all these leases, like,


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[Assistant] These can get tricky. This is a lot of the food delivery type startups, like there's a whole class of things that don't work. Uhm, and they're like, we have positive margins and we have low churn and we have great, like they all say the same things, but if you really dig into them, the secret hiding in their numbers that the founders don't want to admit to themselves is that actually churn can


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[Assistant] Getcha. And if you have hard costs like warehouses, not for you, but for other people, if you have all these hard costs.


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[Assistant] Would be to amortize all of your costs for operations in your time?


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[Assistant] When you're calculating your margins. This is a classic thing people do. It's like, we do food delivery and we have positive margins and it's just that they sell, you know, a burrito for 10 bucks and it costs them 7 bucks to make it. But if you include delivery costs, if you include support costs, if you include returns, if you actually bake in all this stuff,


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[Assistant] See, and sorry, just like, you process the receipts, like, what are you, what are you pulling out of the receipt, the product data, but like, why are they, why are they giving you, that's like a lot of money for an app developer to give you. Like, why are they, what is the thing that they can't build themselves that you can build that's like super useful to them?


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[Assistant] Photographs, a physical receipt, and then the app developer calls your API with like a gif and then like you OCR it and you're like, okay, this is what this thing says.


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[Assistant] And this is sort of, everyone can extrapolate from this in the audience, but like,


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[Assistant] Maybe you should just be building the receipt tracking app that does loyalty. Like it seems like you're trying to use this API thing as like, like a shortcut and like it's gonna be hard.


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[Assistant] But you're like, well, we don't really know how to get a million receipts, so let's just build an API and other people will get receipts. And like, that kind of sounds like wishful thinking, unless...


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[Assistant] And again, it's great that you have this first customer, so congrats on that. But like, to get a million receipts, are they gonna have a million receipts?


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[Assistant] Is like tens of millions or hundreds, like the scale that you need to build a data business, uhm, is much larger, uhm, like have you seen anyone, even with millions, like maybe for millions they give you a small...


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[Assistant] So, one thing, this is just like a general purpose piece of advice is like when you're dealing with large corporates, uhm,


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[Assistant] From their side of the table, you just ask for something crazy, like go get a million receipts and then we'll look at it and maybe we'll pay. But you know, I doubt they were saying that in writing, right? Did they send you a contract?


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[Assistant] Okay, well, so like you can give people these impossible tasks just like for fun and see if they come back with it. But even if they do come back with it, that doesn't necessarily mean they're going to do the deal with you. And so we're always talking to startups that


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[Assistant] They believe the best-case scenario, and that's such, it's so good to be optimistic, so I get why. But they believe the best-case scenario that, you know, hey, this huge Fortune 500 company is gonna do a deal with my two-person startup, and they're gonna give us a million dollars.


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[Assistant] Uhm, man, does that rarely, like usually to pattern match here, usually you have to stair step up and you start with smaller customers that say yes more quickly and it's for smaller dollar amounts and you have to do that for quite a while before you're able to get one of these.


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[Assistant] Uh, deals, you can, sometimes people call them silver bullet deals. You know, it's like the deal that makes your startup where you go from zero revenue to a million. Uhm, somehow the universe makes those very, those things rarely happen.


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[Assistant] And so I think in your case, one negotiation tactic here maybe is to be like, hey, we don't have a million receipts, but why don't we start with a pilot? We do have...


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[Assistant] Whatever. Half a million. How about that? Let's start with that and like, let's just get this going and let's do our first data drop and let's get this on paper. And what you can do when you're negotiating with these kinds of people is to try to like, if they're saying come back with this really hard thing and then maybe I'll say yes.


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[Assistant] Get, move them down to something you can do, something that's more minor. And then try to get it in writing. And once you get something in writing, it's so much more likely they'll do the deal. Cause talk is cheap, man. Like anyone could say, oh we'll give you a million dollars if you do whatever.


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[Assistant] But to get someone that works at a corporation to put something in paper?


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[Assistant] They're either in a couple of excuses why they can't or they're actually serious. And think about how much


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[Assistant] Better that would be for you as founders if you had something to writing because then you know this is real and that can give you so much more confidence that you're going down the right direction.


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[Assistant] So that, that's always something I would suggest. This goes for everybody that we are dealing with these big organizations. Let's try to get anything in writing. Yeah, five minutes.


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[Assistant] Expensify and all the receipt tracking things aren't just doing this? Like, why aren't they, why can't the CPGs get access to all these other receipt tracking data things?


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[Assistant] Do you actually need the SKU? Is that what you're saying? Like is it that they don't, they can get pricing data but they don't have the actual SKU to map it back?


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[Assistant] And it sounds like you've been trying to find what the best possible market is. And so by doing a bunch of customer conversations,


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[Assistant] And so I would think of your core strength as being the technology, and on the CPG side, until you have your first thing in writing, that's still in the question mark. It's not, not a strength, but you don't, it's not like in the bag, in the way that, it sounds like you have this technology and it works today, right? That's in the bag, like you can take that to the bank. And so I would think about,


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[Assistant] You know, thinking about what your strengths are and then maybe being open minded to how you monetize it. Because it could be, you know, until you get this right, until you lock in this risk that this may not be the best possible market for this technology.


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[Assistant] Yeah, be open minded to ways you can use this. Like, other people may be like, hey, you don't need a million receipts, we'll give you money today for this other, like, semi-related, like, it could be really close to what you're doing or it could be a little farther away, we don't know, but you have something really special and you have


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[Assistant] So that's such a good test at this stage and it doesn't cost you anything.


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[Assistant] Would you say there's any similarity between this and some of the apps that are like taking off right now that are like collaborative fiction? What's the name of one of them? There's like three. Yeah, yeah, yeah. I've seen those. Is there, is this, if you squint at it at all, does it look like any of those?


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[Assistant] Are there some stories from like a year ago that are still like super popular as per the permanence question?


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[Assistant] So when I, when we say socials, both are traffic, like 80% is traffic. Because like Tumblr, Yahoo is not really taken care of. And I imagine you can pull like the top Tumblr people, right?


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[Assistant] Founders that are working on consumer internet stuff under count how many


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[Assistant] Social things get to your scale and then top out.


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[Assistant] They think everyone knows the story of Snapchat and Facebook and they know about things like that, but man, even back in the day, there were a lot of Facebook competitors.


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[Assistant] Thousand to million user range and then like top out.


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[Assistant] And as per his Twitch thing, just tell, ask them, what would it take for you to move everything over from Tumblr?


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[Assistant] Like what features do we need to build for you to take everything from your Tumblr over here and then put up a...


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[Assistant] Because like, yea, uh, consumer is different, like I think a lot of times people like out in the audience world, they hear these consumer things, which is just get big, get big, get big, and that is what we're telling you.


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[Assistant] Um, then, well, then what? Like, you don't have enough users to really monetize. Um, and that's, we've just seen a lot of people stall out at this stage. So, in your case, yea, you gotta grow. Yea, we are in the process.


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[Assistant] Uhm, usually like the way you get really huge, I built a consumer site, I got it up to 25 million MAU and uhm,


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[Assistant] Uh, Snapchat never paid anyone. All their clones sure did, right? Like, but...


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[Assistant] That's, you know what I'm saying? YouTube wasn't really paying for traffic, but all the wannabe YouTubes that were trying to raise money were paying for traffic.


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[Assistant] Uh, I think if you have the dev cycles, I don't know if you do, but I would consider a mobile app. One advantage from a retention perspective is that you can do push notifications. And that way, if someone is subscribing to something and you do a push notification to their followers, then you're ensuring a much more, a tighter feedback loop than maybe you have now on mobile web.


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[Assistant] Thousands of people working on making sure that you're constantly looking back at it, right? Like very smart people, that's all they do all day is try to like steal your attention. And you're competing with them. For attention.


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[Assistant] Just doing some really basic stuff, like continuing to iterate on email. If, if chat is the right thing to do, make sure people remember you exist and that they are a member of your community and that they should go check out some new stories. Otherwise it's going to be tricky. One experiment you could do, I've heard someone give this talk before, is go create a Facebook account with like a fake email and don't add any friends and look at how many emails it sends you. I think it sends you like


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[Assistant] Are you gonna churn or on the, you know, way past churning? Well, just like remind them that you exist. Uhm, that's best practices too.


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[Assistant] Oh, chat, hello. Hello, everyone can you hear me? I'm unmuting Discord now, hello? Welcome.


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[Assistant] Okay, it explo- it's dead. It's gone. And fruit sleep schedule exploded. Unlucky. So, we got new- two new people, Uzu and Kitnetic. Last minute replacement, thank you guys so much for coming. This is-


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[Assistant] Rizutuber. I don't know if you know about it, but you're about to find out. Episode 4, uh, featuring Nurosama, uh, AIVtuber. Surely you know about Nurosama. Uhm.


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[Assistant] You guys saw the intro, it's pretty simple. We ask five questions, you all get rated. Uh, this is a special episode, so Noodle Summer will be rating it live. This is why everyone has a zero on the left side of their webcam, because we're gonna be adding scores live, okay? It's a special episode.


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[Assistant] Uh, so I decided to do it like that. It's gonna be more fun. And, I don't know.


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[Assistant] Just funny. I don't know. Anyway, we're gonna, you know, go do the introductions now. We're gonna start with Camilla.


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[Assistant] Thank you, and next up we have Reinho PNG. Can you actually use your model, please?


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[Assistant] Okay, listen up, now we're gonna attempt to, uh, to, to...


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[Assistant] To ask Nurasama to introduce herself as well. Everyone, shh, and listen, this is your date. Nurasama, would you, would you introduce yourself to us?


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[Assistant] Should I kick you out and re-add you? You wanna rejoin?


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[Assistant] Wild Giga's- Wild Giga's fixing on her- her internet connection. Not me, by the way. Uhm.


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[Assistant] Giri, Giri, the talent show is nothing. You can do whatever you want. You can literally say you love Nurosama and that's gonna be fine. Like you don't have to do anything.


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[Assistant] Well, some people can sing, they can draw, or whatever. I don't care what you do. It's completely up to you, and it... I don't care. I literally don't care. Do whatever.


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[Assistant] Okay, we're gonna commence with question number one. By the way, this is a special episode, so, so I, I'm, I'm, I try to adapt the questions to Nura-sama, at least some of them.


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[Assistant] And the first question, we're gonna start with Camilla, and we're gonna end with Ellie, okay? The first question is gonna be, but this is a big question so it's barely seen on the screen, but, if your consciousness was uploaded onto the internet,


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[Assistant] Where on the internet would you take noodle sum on a date? Like if you had to pick like anywhere on the internet like a video game or whatever.


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[Assistant] You can think of, cause, you know, even now on the internet.


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[Assistant] Uh, go ahead Camilla. Kick the floor.


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[Assistant] Thank you, Camilla, for your beautiful answer. Uh, Nurasama, what would you rate that on a scale from 1 to 10?


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[Assistant] Why did you, why did you rate that answer a 5? Is there a specific reason?


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[Assistant] Thank you very much, Narusama. We're gonna move on to Geary. Geary, same question for you. If you could do the same thing, you know, up with your consciousness on the internet, where would you take Narusama on a date? You can choose anything or, or whatever you want.


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[Assistant] Yuri, unlucky for you, that answers, according to Nura, some of that answers sucked.


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[Assistant] Yeah, you're gonna get zero again. Uh, thank you so much for your time, we're gonna move on to Sorry. Sorry, uh, same question.


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[Assistant] Say the question, if you could upload your, so you're uploading your consciousness on the, on the internet, and you're taking neuro-summon a date anywhere on the internet, where are you going?


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[Assistant] Yeah, listen, uh, I don't know, I think it's, it will fix itself, but...


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[Assistant] Yeah, you're good. You're great. Amazing. Perfect. So same question for you. Uh, if your conscience was uploaded on the internet, where would you take Nurosome on a date? Anywhere on the internet.


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[Assistant] Hey, thank you. Uh, Nurasama, would you rate that answer on a scale from 1 to 10?


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[Assistant] Turn her up, turn her up even more. What, I need to turn up Nurosama even more? I'm gonna put her on 200 and it's gonna blow up your ears.


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[Assistant] Okay, uhm, thank you Nurosama. We're gonna move on to Uzu. Uzu, same question. If you could upload your consciousness on the internet, where and why would you take Nurosama on a date?


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[Assistant] Okay, Nurosama, would you rate that answer on a scale from 1 to 10?


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[Assistant] Uh, we're gonna move on now, to, uh, Rain Joe. Rain Joe, uh, same questions. If your consciousness was uploaded on the internet, that-that-that-that-that-that-that-that-that-that-that-that-that-that-that-that-that-that-that-that-that-that-that-that-that-that-that-that-that-that-that-that-that-that-that-that-that-that-that-that-that-that-that-that-that-that-that-that-that-that-that-that-that-that-that-that-that-that-that-that-that-that-that-that-that-that-that-that-that-that-that-that-that-that-that-that-that-that-that-that-that-that-that-that-that-that-that-that-that-that-that-that-that-that-that-that


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[Assistant] Alright, Nurosama, what would you rate that answer from a scale 1 to 10?


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[Assistant] I feel like she's biased towards pretty anime girls. It's actually kinda weird. What about the anime boys?


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[Assistant] Okay, moving on to Giga. Giga, if you could upload your consciousness, where would you take Nurosome on a date and why?


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[Assistant] Yes. Yeah, you deserve a biscuit. Good job. That's a 10 giga, apparently.


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[Assistant] Moving on to Ellie. Ellie, if you could upload your unconsciousness, uh, on the internet, where would you take Nurasama and why?


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[Assistant] Uh, uh, uh, uh, notice someone, would that be a 1 or a 10?


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[Assistant] We're gonna do a poll. We're gonna do a poll. One or ten. Chad's gonna decide.


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[Assistant] There's too many tans, I thought there was someone who was gonna smoke you guys harder.


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[Assistant] Moving on to question number two now, uhm, this question is, how would you help Nurosama take over the world? And this time around, we're gonna start from Ellie, okay? We're going backwards.


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[Assistant] The question is, how would you help Nura Osama take over the world?


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[Assistant] Uh, okay. Yeah, moving on. That's just- It's actually called you cringe, but practically.


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[Assistant] Moving on. Uhm, Giga, same question. How would you help NuraSama take over the world?


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[Assistant] I feel like the whole heart thing is a little bit of a, a little bit of a cheat, little bit of a cheat code.


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[Assistant] Okay, moving on Rain, uh, uh, how would you help, uh, uh, help notice someone take over the world?


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[Assistant] Okay, I think she's, thank you, thank you Nurasama. We're gonna move on to Uzu. Uhm, it was the same question. How would you help Nurasama take over the world?


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[Assistant] Nura, somehow, how would you rate that answer from a scale of 1 to 10?


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[Assistant] Moving on, uh, to uh, Gary. Gary, same question. Uhm, how would you help Norisama take over the world?


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[Assistant] Okay, uh, thank you Nurosama. Thank you so much.


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[Assistant] Kamila, uhm, how would you, uh, help NuraSama take over the world?


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[Assistant] Round-round-round two is-round two is over. We're moving on to round three, okay?


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[Assistant] Uh, next up, uh, we're gonna start with Camilla this time around. By the way, currently our lowest score as well, Camilla. Uh, by the way, Camilla, I-I can't help but notice that how you bragged how...


[User] Please transcribe this text

[Assistant] A bitch. I would- I personally would not call a Nurosama's creator a bitch.


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[Assistant] Yeah, no comment. Alright, question- yeah, question number three! Let's see what question number three is. What do I even write in here?


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[Assistant] If you could give Nura a physical body, what would it be and why? Oh, okay.


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[Assistant] Uh, we're gonna start with you Camilla. So, so the question is, if you could give her a physical body, in a form of any like, anything at all, like it could be any machine, anything whatsoever, what would it be, and why?


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[Assistant] Alright, Nurosama, how would you rate that answer on a scale from 1 to 10?


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[Assistant] Okay, but Nurosama, is it a 6.5 or is it an 8?


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[Assistant] Is it a six and a half or eight?


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[Assistant] One number is 6.5 and the other number is 8. Which one of those numbers would you pick?


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[Assistant] Seven? Let's do a- You guys wanna do a seven? Ah, let's do a seven. Fine, we'll give you a seven.


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[Assistant] But she kinda entered, she kinda like concluded that it was nine, I didn't, I had no hand in it. She kinda stopped me mid-set and said, no, it's a nine and a half. Anyway, moving on to Geary.


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[Assistant] Uh, Giri, if you could give Nuro a physical body, what would it be and why? Any machine and all.


[User] Please transcribe this text

[Assistant] 11 and a half or zero. This is what you're gonna get.


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[Assistant] Oh my god, we're moving on to, to, to sorry. Sorry, if you could give Nura a physical body, what would it be and why?


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[Assistant] Okay, thank you so much Narasama, and is there a reason why you rated that 9?


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[Assistant] Okay, uh, thank you, NuraSama. We're gonna move on to, to Kidnetic. Uhm, Kidnetic, if you could give Nura a physical body, what would it be?


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[Assistant] Yo, 9.5 plus 11.5 is 21. Yeah, I-I wrote 21, are you guys-


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[Assistant] Giga, uh, if you could give Nura a physical body, what would it be?


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[Assistant] What would you rate that answer from a scale from 1 to 10?


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[Assistant] Now, moving on to Ellie. Ellie, if you could give Nura a physical body, what would it be and why?


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[Assistant] I'm not pretending, Pepper. Daddy Pig really cannot touch his toes.


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[Assistant] Great Tim. So uhm, well I'm thoughtful about it because I got to watch masters do it. I'm basically a research scientist but I was interested in the process done by far better managers than me who could deal with larger


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[Assistant] Sets of ideas and I'll try and give you a gist here.


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[Assistant] I think because people are here because they're, they want to do startups and make money, I just want to point out that if you want to make money, don't bother with a startup. Create an industry. Because then you get trillions instead of billions. So it's about a factor of a thousand between doing invention over innovation. In other words, not going incrementally from the present.


[User] Please transcribe this text

[Assistant] But carving out a whole new set of ideas that creates an entirely new context. Uhm, and we'll see some of the ways to go about it and we'll also see some of the barriers and see if this, now, this has got a bad user interface because it has the back button near to the front button. See if that works. So,


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[Assistant] A lot of, uh, what these two days are about are talking about the place that most people naturally live, which is the present.


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[Assistant] But the problem with the present, it is so glittery and distracting, there's so much stuff going on.


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[Assistant] That's hard to think about anything except the present and if you're thinking about the present


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[Assistant] Your ideas are gonna be derived from the present and therefore they're gonna be incremental and therefore you wind up doing innovation. It's not that you can't make money that way. But, uh, today I'm gonna do my


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[Assistant] The opposite of my usual order, I usually like to build a lot of context.


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[Assistant] First, but I thought in the spirit of the Harvard Business School.


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[Assistant] And the equivalent at Stanford, I'd start off with things like results and process and methods first so you have a feeling that I'm actually saying something that you might quote unquote apply.


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[Assistant] But the important talk is really on Thursday. I'm still struggling with making it the right size. So today we're gonna do that. And I urge you to copy my email address. I love emails. We're not gonna have time to have the discussion we should have here. I welcome any questions. And by the way, while I'm talking, I welcome questions at any time. Don't be shy.


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[Assistant] Okay, and here's why school pisses me off.


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[Assistant] Great man in our field, Marvin Minsky, observed that this is the best place ever to keep you from ever thinking about anything for long enough. So you don't want to try and learn in a classroom. It's terrible. In fact, I, I don't like to do classroom process.


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[Assistant] Partly because of the time constraints but also because it's oral. We might as well be sitting around a campfire a hundred thousand years ago. And almost everything that's happened that's important in the last


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[Assistant] Several thousands of years has been basically literary in form. Okay, so, one of my favorite Picasso sayings