George Hotz: Hacking the Simulation & Learning to Drive with Neural Nets | Lex Fridman Podcast #132
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George Hotz (geohot) is a programmer, hacker, and the founder of Comma.ai. Please support this podcast by checking out our sponsors:
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EPISODE LINKS:
Comma.ai's Twitter: https://twitter.com/comma_ai
Comma.ai's Website: https://comma.ai/
George's Instagram: https://www.instagram.com/georgehotz
George's Twitch: https://www.twitch.tv/georgehotz
George's Twitter: https://twitter.com/realgeorgehotz
Comma.ai YouTube (unofficial): https://www.youtube.com/channel/UCwgKmJM4ZJQRJ-U5NjvR2dg

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Full episodes playlist: https://www.youtube.com/playlist?list=PLrAXtmErZgOdP_8GztsuKi9nrraNbKKp4
Clips playlist: https://www.youtube.com/playlist?list=PLrAXtmErZgOeciFP3CBCIEElOJeitOr41

OUTLINE:
0:00 - Introduction
2:31 - Will human civilization destroy itself?
5:18 - Where are the aliens?
10:05 - Tic Tac UFO and Bob Lazar
12:33 - Conspiracy theories
14:36 - The programming language of life
18:57 - The games that humans play
27:27 - Memory leaks in the simulation
29:58 - Theories of everything
31:43 - Ethereum startup story
39:30 - Cryptocurrency
48:57 - Self-help advice
52:37 - Comma.ai
54:30 - Comma two
1:03:19 - Tesla vs Comma.ai
1:12:22 - Driver monitoring
1:26:03 - Communicating uncertainty
1:27:51 - Tesla Dojo
1:34:19 - Tesla Autopilot big rewrite
1:40:37 - How to install the Comma Two
1:45:13 - Openpilot is Android & Autopilot is iOS
1:54:28 - Waymo
2:05:41 - Autonomous driving and society
2:07:53 - Moving
2:10:58 - Advice to Startups
2:24:00 - Programming setup
2:27:01 - Ideas that changed my life
2:35:06 - GPT-3
2:38:26 - AGI
2:42:29 - Programming languages that everyone should learn
2:49:02 - How to learn anything
2:51:34 - Book recommendations
2:59:57 - Love
3:01:46 - Psychedelics
3:04:07 - Crazy

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 The following is a conversation with George Hotz, AKA GeoHot, his second time on the podcast. He's the founder of Kama AI, an autonomous and semi-autonomous vehicle technology company that seeks to be, to Tesla, autopilot what Android is to the iOS. They sell the Kama 2 device for $1,000 that when installed in many of their supported cars can keep the vehicle centered in the lane even when there are no lane markings. It includes driver sensing that ensures that the driver's eyes are on the road. As you may know, I'm a big fan of driver sensing. I do believe Tesla Autopilot and others should definitely include it in their sensor suite. Also, I'm a fan of Android and a big fan of George for many reasons, including his nonlinear out of the box brilliance and the fact that he's a superstar programmer of a very different style than myself. Styles make fights and styles make conversations. So I really enjoyed this chat and I'm sure we'll talk many more times on this podcast. Quick mention of each sponsor followed by some thoughts related to the episode. First is FourSigmatic, the maker of delicious mushroom coffee. Second is Decoding Digital, a podcast on tech and entrepreneurship that I listen to and enjoy. And finally, ExpressVPN, the VPN I've used for many years to protect my privacy on the internet. Please check out the sponsors in the description to get a discount and to support this podcast. As a side note, let me say that my work at MIT on autonomous and semi-autonomous vehicles led me to study the human side of autonomy enough to understand that it's a beautifully complicated and interesting problem space, much richer than what can be studied in the lab. In that sense, the data that CamaAI, Tesla Autopilot, and perhaps others like Cadillac Supercruiser are collecting gives us a chance to understand how we can design safe semi-autonomous vehicles for real human beings in real world conditions. I think this requires bold innovation and a serious exploration of the first principles of the driving task itself. If you enjoyed this thing, subscribe on YouTube, review it with Five Stars and Apple Podcasts, follow on Spotify, support on Patreon, or connect with me on Twitter at Lex Friedman. And now, here's my conversation with George Hotz. So last time we started talking about the simulation, this time let me ask you, do you think there's intelligent life out there in the universe? I've always maintained my answer to the Fermi paradox. I think there has been intelligent life elsewhere in the universe. So intelligent civilizations existed, but they've blown themselves up. So your general intuition is that intelligent civilizations quickly, like there's that parameter in the Drake equation. Your sense is they don't last very long. How are we doing on that? Like, have we lasted pretty good? Oh no. How we do? Oh yeah. I mean, not quite yet. Well, wait, it's like as you'd call it, the IQ required to destroy the world falls by one point every year. Okay. So technology democratizes the destruction of the world. When can a meme destroy the world? It kind of is already, right? Somewhat. I don't think we've seen anywhere near the worst of it yet. The world's going to get weird. Well maybe a meme can save the world. You thought about that? The meme Lord Elon Musk fighting on the side of good versus the meme Lord of the darkness, which is not saying anything bad about Donald Trump, but he is the Lord of the meme on the dark side. He's a Darth Vader of memes. I think in every fairy tale, they always end it with, and they lived happily ever after. And I'm like, please tell me more about this happily ever after. I've heard 50% of marriages end in divorce. Why doesn't your marriage end up there? You can't just say happily ever after. So the thing about destruction is it's over after the destruction. We have to do everything right in order to avoid it. And one thing wrong, I mean, actually this is what I really like about cryptography. Cryptography it seems like we live in a world where the defense wins versus like nuclear weapons, the opposite is true. It is much easier to build a warhead that splits into a hundred little warheads than to build something that can take out a hundred little warheads. The offense has the advantage there. So maybe our future is in crypto. So cryptography, right. The Goliath is the defense. And then all the different hackers are the Davids. And that equation is flipped for nuclear war. Cause there's so many, like one nuclear weapon destroys everything essentially. Yeah. And it is much easier to attack with a nuclear weapon than it is to like the technology required to intercept and destroy a rocket is much more complicated than the technology required to just, you know, orbital trajectory, send a rocket to somebody. So okay. Your intuition that the, there were intelligent civilizations out there, but it's very possible that they're no longer there. That's kind of a sad picture. They enter some steady state. They all wirehead themselves. What's wirehead? Stimulate their pleasure centers and just, you know, live forever in this kind of stasis. They become, well, I mean, I think the reason I believe this is because where are they? If there's some reason they stopped expanding, because otherwise they would have taken over the universe. The universe isn't that big, or at least, you know, let's just talk about the galaxy, right? 70,000 light years across. I took that number from Star Trek Voyager. I don't know how true it is, but yeah, that's not big. 70,000 light years is nothing. For some possible technology that you can imagine that could leverage like wormholes or something like that. You don't even need wormholes. Just a von Neumann probe is enough. A von Neumann probe and a million years of sublight travel, and you'd have taken over the whole universe. That clearly didn't happen. So something stopped it. So you mean if you, right, for like a few million years, if you sent out probes that travel close, what's sublight? Meaning close to the speed of light? Let's say 0.1C. And it just spreads. Interesting. Actually, that's an interesting calculation. Huh. So what makes you think that we'd be able to communicate with them? Like, yeah, why do you think we would be able to comprehend intelligent lives that are out there? Like, even if they were among us kind of thing, like, or even just flying around? Well, I mean, that's possible. It's possible that there is some sort of prime directive. That'd be a really cool universe to live in. And there's some reason they're not making themselves visible to us. But it makes sense that they would use the same, well, at least the same entropy. Well, you're implying the same laws of physics. I don't know what you mean by entropy in this case. Oh, yeah. I mean, if entropy is the scarce resource in the universe. So what do you think about, like, Stephen Wolfram and everything is a computation. And then what if they are traveling through this world of computation? So if you think of the universe as just information processing, then what you're referring to with entropy and then these pockets of interesting complex computations swimming around, how do we know they're not already here? How do we know that this, like all the different amazing things that are full of mystery on Earth are just like little footprints of intelligence from light years away? Maybe. I mean, I tend to think that as civilizations expand, they use more and more energy. And you can never overcome the problem of waste heat. So where is there waste heat? So we'd be able to, with our crude methods, be able to see, like, there's a whole lot of energy here. But it could be something we're not. I mean, we don't understand dark energy, right? Dark matter. It could be just stuff we don't understand at all. Or they can have a fundamentally different physics, you know, like that we just don't even comprehend. Well, I think, OK, I mean, it depends how far out you want to go. I don't think physics is very different on the other side of the galaxy. I would suspect that they have, I mean, if they're in our universe, they have the same physics. Well, yeah, that's the assumption we have. But there could be like super trippy things like, like our cognition only gets to a slice and all the possible instruments that we can design only get to a particular slice of the universe. And there's something much like weirder. Maybe we can try a thought experiment. Would people from the past be able to detect the remnants of our, would be able to detect our modern civilization? And I think the answer is obviously yes. You mean past from a hundred years ago? Well, let's even go back further. Let's go to a million years ago. The humans who were lying around in the desert probably didn't even have, maybe they just barely had fire. They would understand if a 747 flew overhead. In this vicinity, but not if a 747 flew on Mars, because they wouldn't be able to see far because we're not actually communicating that well with the rest of the universe. We're doing okay. Just sending out random like fifties tracks of music. True. And yeah, I mean, they'd have to, you know, the, we've only been broadcasting radio waves for 150 years and well, there's your light cone. So yeah. Okay. What do you make about all the, I recently came across this. When I talked to David's Fravor, I don't know if you caught what the, the videos that Pentagon released and the New York times reporting of the UFO sightings. So I kind of looked into it, quote unquote, and there's actually been like hundreds of thousands of UFO sightings, right? And a lot of it, you can explain away in different kinds of ways. So one is it could be interesting physical phenomena to it could be people wanting to believe. And therefore they conjure up a lot of different things that just, you know, when you see different kinds of lights and basic physics phenomena, and then you just conjure up ideas of possible out there, mysterious worlds. But you know, it's also possible. Like you have a case of, um, David Fravor who is a Navy pilot who's, you know, a, as legit as a guest in terms of humans who are able to perceive things in the environment and make conclusions, whether those things that are threat or not. And he and several other pilots saw a thing. I don't know if you followed this, but they saw a thing that they've since then called tech talk that moved in all kinds of weird ways. They don't know what it is. It could be technology developed by, by the United States and they're just not aware of it. And the surface level from the Navy, right? It could be different kinds of lighting technology or drone technology, all that kind of stuff. It could be the Russians and the Chinese, all that kind of stuff. And of course their mind, our mind can also venture into the possibility that it's from another world. Have you looked into this at all? What do you think about it? I think all the news is a Psyop. I think that the most plausible. Nothing is real. Yeah. I listened to the, I think it was Bob Lazar on Joe Rogan and like, I believe everything this guy is saying. And then I think that it's probably just some like MKUltra kind of thing, you know? What do you mean? Like they, they, they, you know, they made some weird thing and they called it an alien spaceship, you know? It was just to like stimulate young physicists minds and we'll tell them it's alien technology and we'll see what they come up with, right? Do you find any conspiracy theories compelling? Like have you pulled at the string of the, of the rich complex world of conspiracy theories that's out there? I think that I've heard a conspiracy theory that conspiracy theories were invented by the CIA in the sixties to discredit true things. Yeah. So you know, you can go to ridiculous conspiracy theories like flat earth and pizza gate and you know, these things are almost to hide like conspiracy theories that like, you know, remember when the Chinese like locked up the doctors who discovered coronavirus? Like I tell people this and I'm like, no, no, no, that's not a conspiracy theory. That actually happened. Do you remember the time that the money used to be backed by gold and now it's backed by nothing? This is not a conspiracy theory. This actually happened. So that's one of my worries today with the idea of fake news is that when nothing is real, then like you dilute the possibility of anything being true by conjuring up all kinds of conspiracy theories and then you don't know what to believe. And then like the idea of truth of objectivity is lost completely. Everybody has their own truth. So you're used to control information by censoring it. And then the internet happened and governments are like, oh shit, we can't censor things anymore. I know what we'll do. You know, it's the old story of the story of like tying a flag with a leprechaun tells you his gold is buried and you tie one flag and you make the leprechaun swear to not remove the flag and you come back to the field later with a shovel and there's flags everywhere. That's one way to maintain privacy, right? It's like in order to protect the contents of this conversation, for example, we could just generate like millions of deep fake conversations where you and I talk and say random things. So this is just one of them and nobody knows which one was the real one. This could be fake right now. Classics, steganography technique. Okay. Another absurd question about intelligent life because you know, you're, you're an incredible programmer outside of everything else. We'll talk about just as a programmer. Do you think intelligent beings out there, the civilizations that were out there had computers and programming? Did they, do we naturally have to develop something where we engineer machines and are able to encode both knowledge into those machines and instructions that process that knowledge, process that information to make decisions and actions and so on. Would those programming languages, if you think they exist, be at all similar to anything we've developed? So I don't see that much of a difference between quote unquote natural languages and programming languages. I think there's so many similarities. So when asked the question, what do alien languages look like? I imagine they're not all that dissimilar from ours. And I think translating in and out of them, uh, wouldn't be that crazy. It's difficult to compile like DNA to Python and then to see, I mean, there is a little bit of a gap in the kind of languages we use for, for, uh, touring machines and the kind of languages nature seems to use a little bit. Maybe that's just, we just haven't, we haven't understood the kind of language that nature uses well yet. DNA is a CAD model. It's not quite a programming language. It has no sort of a serial, uh, execution. It's not quite a, uh, yeah, it's a, it's a CAD model. Um, so I think in that sense, we actually completely understand it. The problem is, um, you know, uh, well, simulating on these CAD models, I played with it a bit this year is, is super, uh, computationally intensive. If you want to go down to like the molecular level, um, where you need to go to see a lot of these phenomenon like protein folding. Um, so yeah, it's not that it's, it's not, it's not that we don't understand it. It just requires a whole lot of compute to kind of compile it. For our human minds, it's inefficient both for the pro for the data representation and for the programming. Yeah. It runs well on raw nature. It runs well on raw nature. And when we try to build, uh, emulators or simulators for that, uh, well, then mad slow and I've tried it. It runs in that. Yeah. You've commented elsewhere. I don't remember where that, uh, one of the problems is simulating nature is tough. And if you want to sort of, uh, deploy a prototype, I forgot how you, you put it, but it made me laugh, but animals are humans who would need to be involved in, in order to, in order to try to run some prototype code on, um, like if we're talking about COVID and viruses and so on, if you were tried to engineer some kind of defense mechanisms, like a vaccine against COVID or all that kind of stuff that doing any kind of experimentation, like you can with like autonomous vehicles would be very technically cost, technically and ethically costly. I'm not sure about that. I think you can do tons of, uh, crazy biology and test tubes. I think my bigger complaint is more, oh, the tools are so bad. Like literally you mean like, like libraries and I'm not pipetting shit. Like you're handing me a, I gotta no, no, no, no, there has to be some like automating stuff and like the, yeah, but human biology is messy. Like it seems like, look at those Doranos videos. They were joke. It's like, it's like a little gantry. It's like a little XY gantry high school science project with the pipette. I'm like, really? Got to be something better. You can't build like nice microfluidics and I can program the, you know, computation to bio interface. I mean, this is going to happen, but like right now, if you are asking me to pipette 50 milliliters of solution, I'm out. This is so crude. Yeah. So let's get all the crazy out of the way. So a bunch of people asked me since we talked about the simulation last time, we talked about hacking the simulation. Do you have any updates, any insights about how we might be able to go about hacking simulation if we indeed do live in a simulation? I think a lot of people misinterpreted the point of that South by talk. The point of the South by talk was not literally to hack the simulation. I think that this is an idea is literally just, I think theoretical physics. I think that's the whole, you know, the whole goal, right? You want your grand unified theory, but then, okay, build a grand unified theory, search for exploits, right? I think we're nowhere near actually there yet. My hope with that was just more to like, are you people kidding me with the things you spend time thinking about? Do you understand like kind of how small you are? You are, you are bytes and God's computer. Really? And the things that people get worked up about and you know. So basically it was more a message of we should humble ourselves that we get to like, what are we humans in this bytecode? Yeah. And not just humble ourselves, but like, like I'm not trying to like make people feel guilty or anything like that. I'm trying to say like, literally look at what you are spending time on, right? What are you referring to? You're referring to the Kardashians? What are we talking about? I'm referring to, no, the Kardashians. See, everyone knows that's kind of fun. I'm referring more to like the economy, you know, this idea that we got to up our stock price like, or, or what is, what is the goal function of humanity? You don't like the game of capitalism? Like you don't like the games we've constructed for ourselves as humans? I'm a big fan of capitalism. I don't think that's really the game we're playing right now. I think we're playing a different game where the rules are rigged. Okay. Which games are interesting to you that we humans have constructed and which aren't, which are productive and which are not. Actually, maybe that's the real point of the, of the talk. It's like, stop playing these fake human games. There's a real game here. We can play the real game. The real game is, you know, nature wrote the rules. This is a real game. There still is a game to play. But if you look at, sorry to interrupt, but I don't know if you've seen the Instagram account nature is metal. The game that nature seems to be playing is a lot, a lot more cruel that we humans want to put up with, or at least we see it as cruel. It's like the bigger thing eats the smaller thing and does it to impress another big thing so it can mate with that thing. And that's it. That seems to be the entirety of it. Well, there's no art, there's no music. There's no comma AI. There's no comma one, no comma two, no George Hots with his brilliant talks at South by Southwest. See, I disagree though. I disagree that this is what nature is. I think nature just provided basically a open world MMORPG and you know, here it's open world. I mean, if that's the game you want to play, you can play that game. But that isn't that, isn't that beautiful? I know if you played Diablo, they used to have a, I think cow level where it's, so everybody will go just, they figured out this like the best way to gain like experience points is to just slaughter cows over and over and over. And so they figured out this little sub game within the bigger game that this is the most efficient way to get experience points. And everybody somehow agreed that getting experience points in RPG context, where you always want to be getting more stuff, more skills, more levels, keep advancing. That seems to be good. So might as well spend sacrifice actual enjoyment of playing a game, exploring a world and spending like hundreds of hours of your time in college. I mean, the number of hours I spent in cow level, I'm not like the most impressive person because people have probably thousands of hours there, but it's ridiculous. So that's a little absurd game that brought me joy in some weird dopamine drug kind of way. So you don't like those games. You don't think that's us humans failing the nature. I think so. And that was the point of the talk. Yeah. So how do we hack it then? Well, I want to live forever and I want to live forever. And this is the goal. Well, that's a game against nature. Yeah. So, immortality is the good objective function to you. I mean, start there and then you can do whatever else you want because you got a long time. What if immortality makes the game just totally not fun? I mean, like, why do you assume immortality is somehow a good objective function? It's not immortality that I want. A true immortality where I could not die. I would prefer what we have right now. But I want to choose my own death. Of course. I don't want nature to decide when I die, I'm going to win. I'm going to be you. And then at some point, if you choose commit suicide, like, how long do you think you'd live? Until I get bored. See, I don't think people like in like brilliant people like you that really ponder living a long time are really considering how a meaningless life becomes. Well, I want to know everything and then I'm ready to die. As long as there's... Yeah, but why do you want... Isn't it possible that you want to know everything because it's finite? Like, the reason you want to know quote unquote everything is because you don't have enough time to know everything. And once you have unlimited time, then you realize like, why do anything? Like why learn anything? I want to know everything and then I'm ready to die. So you have... Yeah. Well, it's not a... It's a terminal value. It's not in service of anything else. I'm conscious of the possibility. This is not a certainty, but the possibility of that engine of curiosity that you're speaking to is actually a symptom of the finiteness of life. Like, without that finiteness, your curiosity would vanish like a morning fog. All right, cool. Then... Wachowski talked about love like that. Then let me solve immortality and let me change the thing in my brain that reminds me of the fact that I'm immortal tells me that life is finite shit. Maybe I'll have it tell me that life ends next week. Right? I'm okay with some self manipulation like that. I'm okay with deceiving myself. Oh, Rika, changing the code. If that's the problem, right? If the problem is that I will no longer have that curiosity, I'd like to have backup copies of myself, which I check in with occasionally to make sure they're okay with the trajectory and they can kind of override it. Maybe a nice like, I think of like those wave nets, those like logarithmic go back to the copy. But sometimes it's not reversible. Like I've done this with video games. Once you figure out the cheat code or like you look up how to cheat old school, like single player, it ruins the game for you. Absolutely. I know that feeling. But again, that just means our brain manipulation technology is not good enough yet. Remove that cheat code from your brain. What if we call... So it's also possible that if we figure out immortality, that all of us will kill ourselves before we advance far enough to be able to revert the change. I'm not killing myself till I know everything. That's what you say now because your life is finite. I think yes, self-modifying systems comes up with all these hairy complexities. Can I promise that I'll do it perfectly? No, but I think I can put good safety structures in place. That talk in your thinking here is not literally referring to a simulation in that our universe is a kind of computer program running in a computer. That's more of a thought experiment. Do you also think of the potential of the sort of Bostrom, Elon Musk, and others that talk about an actual program that simulates our universe? Oh, I don't doubt that we're in a simulation. I just think that it's not quite that important. I mean, I'm interested only in simulation theory as far as it gives me power over nature. If it's totally unfalsifiable, then who cares? I mean, what do you think that experiment would look like? Somebody on Twitter asked, ask George what signs we would look for to know whether or not we're in the simulation, which is exactly what you're asking. The step that precedes the step of knowing how to get more power from this knowledge is to get an indication that there's some power to be gained. So, get an indication that you can discover and exploit cracks in the simulation or it doesn't have to be in the physics of the universe. Show me, I mean, like a memory leak would be cool. Some scrying technology, you know? What kind of technology? Scrying? What's that? Oh, that's a weird... Scrying is the paranormal ability to like remote viewing, like being able to see somewhere where you're not. So I don't think you can do it by chanting in a room, but if we could find... It's a memory leak, basically. It's a memory leak. Yeah, you're able to access parts you're not supposed to and thereby discover a shortcut. Memory leak means the other thing as well, but I mean like, yeah, like an ability to read arbitrary memory. And that one's not that horrifying. The right ones start to be horrifying. Read, right. So the reading is not the problem. Yeah, it's like Heartfleet for the universe. Oh boy, the writing is a big, big problem. It's a big problem. It's the moment you can write anything, even if it's just random noise. That's terrifying. I mean, even without that, like even some of the nanotech stuff that's coming, I think is... I don't know if you're paying attention, but actually Eric Weinstein came out with the theory of everything. I mean, that came out. He's been working on a theory of everything in the physics world called geometric unity. And then for me, from computer science person like you, Stephen Wolfram's theory of everything, of like hypergraphs is super interesting and beautiful, but that not from a physics perspective, but from a computational perspective. I don't know. Have you paid attention to any of that? So again, like what would make me pay attention and like why I hate string theory is, okay, make a testable prediction, right? I'm only interested in... I'm not interested in theories for their intrinsic beauty. I'm interested in theories that give me power over the universe. So if these theories do, I'm very interested. Can I just say how beautiful that is? Because a lot of physicists say, I'm interested in experimental validation and they skip out the part where they say to give me more power in the universe. I just love the clarity of that. I want 100 gigahertz processors. I want transistors that are smaller than atoms. I want like power. That's true. And that's where people from aliens to this kind of technology where people are worried that governments like who owns that power? Is it George Hotz? Is it thousands of distributed hackers across the world? Is it governments? Is it Mark Zuckerberg? There's a lot of people that... I don't know if anyone trusts any one individual with power. So they're always worried. It's the beauty of blockchains. That's the beauty of blockchains, which we'll talk about. On Twitter, somebody pointed me to a story. A bunch of people pointed me to a story a few months ago where you went into a restaurant in New York, and you can correct me if any of this is wrong, and ran into a bunch of folks from a crypto company who are trying to scale up Ethereum. And they had a technical deadline related to a solidity to OVM compiler. So these are all Ethereum technologies. So you stepped in. They recognized you, pulled you aside, explained their problem, and you stepped in and helped them solve the problem, thereby creating legend status story. So can you tell me the story in a little more detail? It seems kind of incredible. Did this happen? Yeah, yeah, it's a true story. It's a true story. I mean, they wrote a very flattering account of it. So the company is called Optimism, spin-off of Plasma. They're trying to build L2 solutions on Ethereum. So right now, every Ethereum node has to run every transaction on the Ethereum network. And this kind of doesn't scale, right? Because if you have N computers, well, if that becomes two N computers, you actually still get the same amount of compute. This is like O of 1 scaling, because they all have to run it. Okay, fine, you get more blockchain security, but blockchain is already so secure. Can we trade some of that off for speed? So that's kind of what these L2 solutions are. They built this thing which kind of sandbox for Ethereum contracts, so they can run it in this L2 world and it can't do certain things in L world, in L1. Can I ask you for some definitions? What's L2? Oh, L2 is layer 2. So L1 is like the base Ethereum chain, and then layer 2 is like a computational layer that runs elsewhere, but still is kind of secured by layer 1. And I'm sure a lot of people know, but Ethereum is a cryptocurrency, probably one of the most popular cryptocurrencies, second to Bitcoin, and a lot of interesting technological innovations there. Maybe you could also slip in whenever you talk about this, any things that are exciting to you in the Ethereum space. And why Ethereum? Well, I mean, Bitcoin is not tearing complete. Ethereum is not technically tearing complete with the gas limit, but close enough. With the gas limit? What's the gas limit? Resources? Yeah, I mean, no computer is actually tearing complete. Right. You're going to find out RAM, you know? I can actually solve the whole thing. What's the word gas limit? You have so many brilliant words. I'm not even going to ask. No, that's not my word. That's Ethereum's word. Gas limit? Ethereum, you have to spend gas per instruction. So like different opcodes use different amounts of gas and you buy gas with ether to prevent people from basically DDoSing the network. So Bitcoin is proof of work. And then what's Ethereum? It's also proof of work. They're working on some proof of stake Ethereum 2.0 stuff. But right now it's proof of work. It uses a different hash function from Bitcoin that's more ASIC resistance because you need RAM. So we're all talking about Ethereum 1.0. So what were they trying to do to scale this whole process? So they were like, well, if we could run contracts elsewhere and then only save the results of that computation, you know, well, we don't actually have to do the compute on the chain. We can do the compute off chain and just post what the results are. Now, the problem with that is, well, somebody could lie about what the results are. So you need a resolution mechanism. And the resolution mechanism can be really expensive because, you know, you just have to make sure that like the person who is saying, look, I swear that this is the real computation. I'm staking $10,000 on that fact. And if you prove it wrong, yeah, it might cost you $3,000 in gas fees to prove wrong, but you'll get the $10,000 bounty. So you can secure using those kinds of systems. So it's effectively a sandbox which runs contracts. And like any kind of normal sandbox, you have to like replace syscalls with, you know, calls into the hypervisor. Sandbox, syscalls, hypervisor. What do these things mean? As long as it's interesting to talk about. Yeah. I mean, you can take like the Chrome sandbox is maybe the one to think about, right? So the Chrome process that's doing a rendering can't, for example, read a file from the file system. Yeah. So if someone tries to make an open syscall in Linux, the open syscall, you can't make an open syscall. No, no, no. You have to request from the kind of hypervisor process or like, I don't know what's called in Chrome, but the, hey, could you open this file for me? And then it does all these checks and then it passes the file handle back in if it's approved. Got it. So that's, yeah. So what's the, in the context of Ethereum, what are the boundaries of the sandbox that we're talking about? Well, like one of the calls that you actually reading and writing any state to the Ethereum contract or to the Ethereum blockchain. Writing state is one of those calls that you're going to have to sandbox in layer two, because if you let layer two just arbitrarily write to the Ethereum blockchain. So layer two is really sitting on top of layer one. So you're going to have a lot of different kinds of ideas that you can play with. And they're all, they're not fundamentally changing the source code level of Ethereum. Well, you have to replace a bunch of calls with calls into the hypervisor. So instead of doing the syscall directly, you replace it with a call to the hypervisor. So originally they were doing this by first running the, so Solidity is the language that most Ethereum contracts are written in. It compiles to a bytecode. And then they wrote this thing they call the transpiler. And the transpiler took the bytecode and it transpiled it into OVM safe bytecode. Basically bytecode that didn't make any of those restricted syscalls and added the calls to the hypervisor. This transpiler was a 3000 line mess. And it's hard to do. It's hard to do if you're trying to do it like that, because you have to kind of like deconstruct the bytecode, change things about it and then reconstruct it. And I mean, as soon as I hear this, I'm like, well, why don't you just change the compiler? Right? Why not the first place you build the bytecode, just do it in the compiler. So yeah, you know, I asked them how much they wanted it. Of course, measured in dollars and a million, well, okay. And yeah. And you wrote the compiler. Yeah. I modified, I wrote a 300 line diff to the compiler. It's open source. You can look at it. Yeah. Yeah. I looked at the code last night. It's cute. Yeah, exactly. Cute is a good word for it. And it's C++. So when asked how you were able to do it, you said you just got to think and then do it right. So can you break that apart a little bit? What's your process of one thinking and two doing it right? You know, they, they, they, the people I was working for amused that I said that it doesn't really mean anything. Okay. I mean, is there some deep, profound insights to draw from like how you problem solve from that? This is always what I say. I'm like, do you want to be a good programmer? Do it for 20 years. Yeah. There's no shortcuts. No. What are your thoughts on crypto in general? So what, what parts technically or philosophically do you find especially beautiful maybe? Oh, I'm, I'm extremely bullish on crypto long-term, not any specific crypto project, but this idea of, well, two ideas. One the Nakamoto consensus algorithm is I think one of the greatest innovations of the 21st century. This idea that people can reach consensus. You can reach a group consensus using a relatively straightforward algorithm is wild. And like, I mean, Satoshi Nakamoto, people always ask me who I look up to. It's like, whoever that is. Who do you think it is? Elon Musk? Is it you? It is definitely not me and I do not think it's Elon Musk, but yeah, this idea of our groups reaching consensus in a decentralized yet formulaic way is one extremely powerful idea from crypto. Maybe the second idea is this idea of smart contracts. When you write a contract between two parties, any contract, this contract, if there are disputes it's interpreted by lawyers. Lawyers are just really shitty overpaid interpreters. Imagine you had, let's talk about them in terms of like, let's compare a lawyer to Python. Right? So lawyer, well, okay. That's brilliant. I never thought of it that way. It's hilarious. So Python, I'm paying even 10 cents an hour. I'll use the nice Azure machine. I can run Python for 10 cents an hour. Lawyers cost $1,000 an hour. So Python is 10,000X better on that axis. Lawyers don't always return the same answer. Python almost always does. Cost. Yeah. I mean, just cost, reliability, everything about Python is so much better than lawyers. So if you can make smart contracts, this whole concept of code is law. I love, and I would love to live in a world where everybody accepted that fact. So maybe you can talk about what smart contracts are. So let's say, let's say, you know, we have a, even something as simple as a safety deposit box, right? Safety deposit box that holds a million dollars. I have a contract with the bank that says two out of these three parties must be present to open the safety deposit box and get the money out. So that's a contract with the bank and it's only as good as the bank and the lawyers, right? Let's say, you know, somebody dies and now, oh, we're going to go through a big legal dispute about whether, oh, well, was it in the will? Was it not in the will? What, what? It's just so messy and the cost to determine truth is so expensive versus a smart contract, which just uses cryptography to check if two out of three keys are present. Well, I can look at that and I can have certainty in the answer that it's going to return. That's what all businesses want is certainty. You know, they say businesses don't care. Viacom YouTube, YouTube's like, look, we don't care which way this lawsuit goes. Just please tell us so we can have certainty. I wonder how many agreements in this book, because we're talking about financial transactions only in this case, correct? The smart smart contracts. Oh, you can go to it. You can go to anything. You can go. You can put a prenup in the theory of blockchain married smart contracts. Sorry, divorce lawyer. Sorry, you're going to be replaced by Python. Okay. So that's, uh, so that's, that's another beautiful idea. Do you think there's something that's appealing to you about any one specific implementation? So if you look 10, 20, 50 years down the line, do you see any like Bitcoin, Ethereum, any of the other hundreds of cryptocurrencies winning out? Is there like, what's your intuition about the space? Are you just sitting back and watching the chaos and look who cares what emerges? Oh, I don't, I don't speculate. I don't really care. I don't really care which one of these projects wins. I'm kind of in the Bitcoin as a meme coin camp. I mean, why does Bitcoin have value? It's technically kind of, you know, not great. Like the block size debate. When I found out what the block size debate was, I'm like, are you guys kidding? What's the block size debate? You know what? It's really, it's too stupid to even talk about. People can look it up, but I'm like, wow. You know, Ethereum seems, the governance of Ethereum seems much better. I've come around a bit on proof of stake ideas. You know, very smart people thinking about some things. Yeah. You know, governance is interesting. It does feel like Vitalik, like it does feel like in open, even in these distributed systems, leaders are helpful because they kind of help you drive the mission and the vision and they put a face to a project. It's a weird thing about us humans. Leaders are helpful, like Vitalik. Right. Yeah. Brilliant. Leaders are not necessarily. Yeah. So you think the reason he's the face of Ethereum is because he's a genius. That's interesting. I mean, that was, it's interesting to think about that we need to create systems in which the quote unquote leaders that emerge are the geniuses in the system. I mean, that's arguably why the current state of democracy is broken is the people who are emerging as the leaders are not the most competent, are not the superstars of the system. And it seems like at least for now in the crypto world, oftentimes the leaders are the superstars. Imagine at the debate, they asked, what's the sixth amendment? What are the four fundamental forces in the universe? What's the integral of two to the X? Yeah. I'd love to see those questions asked and that's what I want as our leader. It's a little bit of a baseball. Yeah. I mean, even, oh wow. You're hurting my brain. It's that my standard was even lower, but I would have loved to see just as basic brilliance. Like I've talked to historians. There's just these, they're not even like, they don't have a PhD or even an education history. They're like a Dan Carlin type character who just like, holy shit, how did all this information get into your head? They're able to just connect Genghis Khan to the entirety of the history of the 20th century. They know everything about every single battle that happened and they know the game of Thrones of the different power plays and all that happened there. And they know like the individuals and all the documents involved and they integrate that into their regular life. It's not like they're ultra history nerds. They're just, they know this information. That's what competence looks like. Yeah. Cause I've seen that with programmers too. That's what great programmers do. But yeah, it would be a, it's really unfortunate that those kinds of people aren't emerging as our leaders. But for now, at least in the crypto world, that seems to be the case. I don't know if that always, you could imagine that in a hundred years, it's not the case. Crypto world has one very powerful idea going for it. And that's the idea of forks. I mean, you know, imagine, we'll use a less controversial example. This was actually in my joke app in 2012. I was like, Barack Obama, Mitt Romney, let's let them both be president. Right, like imagine we could fork America and just let them both be president. And then the Americas could compete and you know, people could invest in one, pull their liquidity out of one, put it in the other. You have this in the crypto world. Ethereum forks into Ethereum and Ethereum classic. And you can pull your liquidity out of one and put it in another and people vote with their dollars, which forks companies should be able to fork. I'd love to fork Nvidia, you know. Yeah, like different business strategies and then try them out and see, see what works. Like even take, yeah, take Comma AI that closes its source and then take one that's open source and see what works. Take one that's purchased by GM and one that remains Android Renegade and all these different versions and see. The beauty of Comma AI is someone can actually do that. Yeah, please take Comma AI and fork it. That's right. That's the beauty of open source. So you're, I mean, we'll talk about autonomous vehicle space, but it does seem that you're really knowledgeable about a lot of different topics. So the natural question, a bunch of people ask this, which is how do you keep learning new things? Do you have like practical advice if you were to introspect, like taking notes, allocate time? Or do you just mess around and just allow your curiosity to drive? I'll write these people a self-help book and I'll charge $67 for it. I will, I will write, I will write on the cover of the self-help book. All of this advice is completely meaningless. You're going to be a sucker and buy this book anyway. And the one lesson that I hope they take away from the book is that I can't give you a meaningful answer to that. That's interesting. Let me translate that is you haven't really thought about what it is you do systematically because you could reduce it. And there's some people, I mean, I've met brilliant people that, I mean, this is really clear with athletes. Some are just, you know, the best in the world at something and they, they have zero interest in writing a self, like a self-help book, but, or how to master this game. And then there's some athletes who become great coaches and they love the analysis, perhaps the over analysis and you right now, at least at your age, which is an interesting, you're in the middle of the battle. You're like the warriors that have zero interest in writing books. So you're in the middle of the battle. So you have, yeah. This is, this is a fair point. I do think I have a certain aversion to this kind of deliberate intentional way of living life. Because eventually the hilarity of this, especially since this is recorded, it will have revealed beautifully the absurdity when you finally do publish this book. And I guarantee you, you will. The story of comma AI would be, maybe it'll be a biography written about you. That'll be, that'll be better. I guess. You might be able to learn some cute lessons if you're starting a company like comma AI from that book. But if you're asking generic questions, like, how do I be good at things? Dude, I don't know. Well learn. I mean, the interesting do them a lot. I do them a lot. But the interesting thing here is learning things outside of your current trajectory, which is what it feels like from an outsider's perspective. I mean that, uh, you know, that, I don't know if there's advice on that, but it is an interesting curiosity. When you become really busy, you're running a company. Yeah. But like there's a natural inclination and trend, like just the, the, the momentum of life carries you into a particular direction of wanting to focus. And this kind of dispersion that curiosity can lead to gets harder and harder with time because you're, you get really good at certain things and it sucks trying things that you're not good at, like trying to figure them out. I mean, you do this with your life streams is you're on the fly figuring stuff out. You don't mind looking dumb. Nah. You just figured it out, figured it out pretty quickly. Sometimes I try things and I don't figure them out. My chest rating is like a 1400 despite putting like a couple hundred hours in is pathetic. I mean, to be fair, I know that I could do it better if I did it better, like don't play, you know, don't play five minute games, play 15 minute games at least. Like I know these things, but it just doesn't. It doesn't stick nicely in my knowledge tree. All right. Let's talk about comma AI. What's the mission of the company? Let's like look at the biggest picture. Oh, I have an exact statement. Solve self-driving cars while delivering shippable intermediaries. So long-term vision is have fully autonomous vehicles and make sure you're making money along the way. I think it doesn't really speak to money, but I can talk, I can talk about what solve self-driving cars means. Solve self-driving cars of course means you're not building a new car. You're building a person replacement. That person can sit in the driver's seat and drive you anywhere a person can drive with a human or better level of safety, speed, quality, comfort. And what's the second part of that? Delivering shippable intermediaries is well, it's a way to fund the company. That's true, but it's also a way to keep us honest. If you don't have that, it is very easy with this technology to think you're making progress when you're not. I've heard it best described on Hacker News as you can set any arbitrary milestone, meet that milestone and still be infinitely far away from solving self-driving cars. So it's hard to have like real deadlines when you're like Cruz or Waymo when you don't have revenue. Is that, I mean, is revenue essentially the thing we're talking about here? Revenue is, capitalism is based around consent. Capitalism the way that you get revenue is a real capitalism, commas in the real capitalism camp. There's definitely scams out there, but real capitalism is based around consent. It's based around this idea that like if we're getting revenue, it's because we're providing at least that much value to another person. When someone buys a thousand dollar comma two from us, we're providing them at least a thousand dollars of value where they wouldn't buy it. Right. So can you give a whirlwind overview of the products that KamaEI provides like throughout its history and today? I mean, yeah, the past ones aren't really that interesting. It's kind of just been refinement of the same idea. The real only product we sell today is the Kama2. Which is a piece of hardware with cameras. So the Kama2, I mean, you can think about it kind of like a person. You know, in future hardware will probably be even more and more person like. So it has, you know, eyes, ears, a mouth, a brain, and a way to interface with the car. Does it have consciousness? Just kidding. That was a trick question. I don't have consciousness either. Me and the Kama2 are the same. I have a little more compute than it. It only has like the same compute as a B. You're more efficient energy wise for the compute you're doing. Far more efficient energy wise. 20 pay to flops, 20 wants, crazy. You lack consciousness. Sure. Do you fear death? You do. You want immortality. Of course I fear death. Does KamaI fear death? I don't think so. Of course it does. It very much fears well, fears negative loss. Oh yeah. Okay. So Kama2, when did that come out? That was a year ago? No, two? Early this year. Wow. Time. It feels like, yeah. 2020 feels like it's taken 10 years to get to the end. It's a long year. It's a long year. So what's the sexiest thing about Kama2 feature wise? So I mean maybe you can also linger on like what is it? Like what's its purpose? Because there's a hardware, there's a software component. You've mentioned the sensors, but also like what are the features and capabilities? I think our slogan summarizes it well. Kama's slogan is make driving chill. I love it. Okay. Yeah. I mean it is, you know, if you like cruise control, imagine cruise control, but much, much more. So it can do adaptive cruise control things, which is like slow down for cars in front of it, maintain a certain speed. And it can also do lane keeping, so staying in the lane and do it better and better and better over time. It's very much machine learning based. So there's cameras, there's a driver facing camera too. What else is there? What am I thinking? So the hardware versus software. So open pilot versus the actual hardware of the device. What's can you draw that distinction? What's one, what's the other? I mean the hardware is pretty much a cell phone with a few additions, a cell phone with a cooling system and with a car interface connected to it. And by cell phone, you mean like Qualcomm Snapdragon. Yeah. The current hardware is a Snapdragon 821. It has a wifi radio, it has an LTE radio, it has a screen. We use every part of the cell phone. And then the interface with the car is specific to the car. So you keep supporting more and more cars. Yeah. So the interface to the car. I mean the device itself just has four CAN buses, it has four CAN interfaces on it that are connected through the USB port to the phone. And then, yeah, on those four CAN buses, you connect it to the car and there's a little harness to do this. Cars are actually surprisingly similar. So CAN is the protocol by which cars communicate and then you're able to read stuff and write stuff to be able to control the car depending on the car. So what's the software side? What's open pilot? So I mean, open pilot is the hardware is pretty simple compared to open pilot. Open pilot is... Well, so you have a machine learning model, which it's an open pilot. It's a blob. It's just a blob of weights. It's not like people are like, oh, it's closed source. I'm like, it's a blob of weights. What do you expect? So it's primarily neural network based. Well, open pilot is all the software kind of around that neural network. That if you have a neural network that says, here's where you want to send the car, open pilot actually goes and executes all of that. It cleans up the input to the neural network. It cleans up the output and executes on it. So it's the glue that connects everything together. Runs the sensors, does a bunch of calibration for the neural network, deals with like, if the car is on a banked road, you have to counter steer against that. And the neural network can't necessarily know that by looking at the picture. So you do that with other sensors, infusion and localizer. Open pilot also is responsible for sending the data up to our servers so we can learn from it, logging it, recording it, running the cameras, thermally managing the device, managing the disk space on the device, managing all the resources on the device. So what, since we last spoke, I don't remember when, maybe a year ago, maybe a little bit longer, how has open pilot improved? We did exactly what I promised you. I promised you that by the end of the year, you'd be able to remove the lanes. The lateral policy is now almost completely end to end. You can turn the lanes off and it will drive slightly worse on the highway if you turn the lanes off, but you can turn the lanes off and it will drive well trained completely end to end on user data. And this year we hope to do the same for the longitudinal policy. So that's the interesting thing is you're not doing, you don't appear to be, you can correct me, you don't appear to be doing lane detection or lane marking detection or kind of the segmentation task or any kind of object detection task. You're doing what's traditionally more called like end to end learning. So and trained on actual behavior of drivers when they're driving the car manually. This is hard to do, you know, it's not supervised learning. Yeah. But so the nice thing is there's a lot of data. So it's hard and easy, right? It's a, we have a lot of high quality data. Yeah. Like more than you need in a sense. Well, we have way more than we do. We have way more data than we need. I mean, it's, it's an interesting question actually, because in terms of amount, you have more than you need, but the, you know, driving is full of edge cases. So how do you select the data you train on? I think this is an interesting open question. Like what's, what's the cleverest way to select data? That's the question Tesla is probably working on. That's, I mean, the entirety of machine learning can be, they don't seem to really care. They just kind of select data, but I feel like that if you want to solve, if you want to create intelligent systems, you have to pick data well. Right. And so would you have any hints, ideas of how to do it? Well. In some ways that is the definition I like of reinforcement learning versus supervised learning in supervised learning, the weights depend on the data. Right. And this is obviously true, but the, in reinforcement learning, the data depends on the weights. Yeah. Right. And actually both ways. That's poetry. So brilliant. How does it know what data to train on? Well, let it pick. We're not there yet, but that's the eventual. So you're thinking this almost like a reinforcement learning framework. We're going to do RL on the world. Every time a car makes a mistake, user disengages. We train on that and do RL on the world. Ship out a new model. That's an epoch. Right. And for now, you're not doing the Elon style promising that it's going to be fully autonomous. You really are sticking to level two and like it's supposed to be supervised. Oh, it is definitely supposed to be supervised. And we enforce the fact that it's supervised. We look at our rate of improvement in disengagements. OpenPilot now has an unplanned disengagement about every hundred miles. This is up from 10 miles. Like maybe, maybe a year ago. Yeah. So maybe we've seen 10 X improvement in a year, but a hundred miles is still a far cry from the hundred thousand you're going to need. So you're going to somehow need to get three more 10 Xs in there. And you're, what's your intuition? You're basically hoping that there's exponential improvement built into the baked into the cake somewhere. Well, that's even, I mean, 10 X improvement, that's already assuming exponential, right? There's definitely exponential improvement. And I think when Elon talks about exponential, like these things, these systems are going to exponentially improve. Just exponential doesn't mean you're getting a hundred gigahertz processors tomorrow, right? It's going to still take a while because the gap between even our best system and humans is still large. So that's an interesting distinction to draw. So if you look at the way Tesla is approaching the problem and the way you're approaching the problem, which is very different than the rest of the self-driving car world. So let's put them aside is you're treating most of the driving tasks as a machine learning problem. And the way Tesla is approaching it is with the multitask learning, where you break the task of driving into hundreds of different tasks and you have this multi-headed neural network that's very good at performing each task. And there's presumably something on top that's stitching stuff together in order to make control decisions, policy decisions about how you move the car. But what that allows you, there's a brilliance to this because it allows you to master each task like lane detection, stop sign detection, traffic light detection, drivable area segmentation, vehicle bicycle, pedestrian detection. There's some localization tasks in there. Also predicting how the entities in the scene are going to move. Everything is basically a machine learning task, whether it's a classification, segmentation, prediction. And it's nice because you can have this entire engine, data engine that's mining for edge cases for each one of these tasks. And you can have people like engineers that are basically masters of that task. They become the best person in the world at, as you talk about the cone guy for Waymo. Yeah, the good old cone guy. The become the best person in the world at cone detection. So that's a compelling notion from a supervised learning perspective, automating much of the process of edge case discovery and retraining neural network for each of the individual perception tasks. And then you're looking at the machine learning in a more holistic way, basically doing end to end learning on the driving task supervised, trained on the data of the actual driving of people they use, AI. Like actual human drivers doing manual control, plus the moments of disengagement that maybe with some labeling could indicate the failure of the system. So you have a huge amount of data for positive control of the vehicle, like successful control of the vehicle, both maintaining the lane as I think you're also working on longitudinal control of the vehicle and then failure cases where the vehicle does something wrong that needs disengagement. So like what, why do you think you're right and Tesla is wrong on this? And do you think, do you think you'll come around the Tesla way? Do you think Tesla will come around to your way? If you were to start a chess engine company, would you hire a Bishop guy? See we have, this is Monday morning quarterbacking is yes, probably. So our rook guy, oh, we stole the rook guy from that company. Oh, we're going to have real good rooks. Well, there's not many pieces, right? You can, there's not many guys and gals to hire. You have a few that work on the Bishop, a few that work in the rook. But is that not ludicrous today to think about in a world of AlphaZero? But AlphaZero is a chess game. So the fundamental question is how hard is driving compared to chess? Because so long-term end to end will be the right solution. The question is how many years away is that? And then it's going to be the only solution for level five. For the only way we get there. Sorry, so of course Tesla is going to come around to my way. And if you're a rook guy out there, I'm sorry. The cone guy. I don't know. We're going to specialize each task. We're going to really understand rook placement. Yeah. I understand the intuition you have. I mean that, that is a very compelling notion that we can learn the task end to end. Like the same compelling notion you might have for natural language conversation. I'm not sure, because one thing you sneaked in there is the assertion that it's impossible to get to level five without this kind of approach. I don't know if that's obvious. I don't know if that's obvious either. I don't actually mean that. I think that it is much easier to get to level five with an end to end approach. I think that the other approach is doable, but the magnitude of the engineering challenge may exceed what humanity is capable of. But what do you think of the Tesla data engine approach? Which to me is an active learning task is kind of fascinating. It's breaking it down into these multiple tasks and mining their data constantly for like edge cases for these different tasks. But the tasks themselves are not being learned. This is feature engineering. I mean, it's a higher abstraction level of feature engineering for the different tasks. It's task engineering in a sense. It's slightly better feature engineering, but it's still fundamentally is feature engineering. And if anything about the history of AI has taught us anything, it's that feature engineering approaches will always be replaced and lose to end to end. Now, to be fair, I cannot really make promises on timelines. But I can say that when you look at the code for Stockfish and the code for AlphaZero, one is a lot shorter than the other, a lot more elegant, required a lot less programmer hours to write. Yeah. But there was a lot more murder of bad agents on the AlphaZero side. By murder, I mean agents that played a game and failed miserably. Yeah. And in simulation, that failure is less costly. In real world, it's- Wait, do you mean in practice? Like AlphaZero has lost games miserably? No. I haven't seen that. No, but I know. But the requirement for AlphaZero is- A simulator. To be able to like evolution, human evolution, not human evolution, biological evolution of life on earth from the origin of life has murdered trillions upon trillions of organisms on the path to us humans. So the question is, can we stitch together a human-like object without having to go through the entire process of evolution? Well, no, but do the evolution in simulation. Yeah, that's the question. Can we simulate? So do you have a sense that it's possible to simulate some aspect of it? Mu zero is exactly this. Mu zero is the solution to this. Mu zero, I think, is going to be looked back as the canonical paper. And I don't think deep learning is everything. I think that there's still a bunch of things missing to get there. But mu zero, I think, is going to be looked back as the kind of cornerstone paper of this whole deep learning era. And mu zero is the solution to self-driving cars. You have to make a few tweaks to it. But mu zero does effectively that. It does those rollouts and those murdering in a learned simulator and a learned dynamics model. It's interesting. It doesn't get enough love that- I was blown away when I read that paper. I'm like, okay, I've always had a comma. I'm going to sit and I'm going to wait for the solution to self-driving cars to come along. This year I saw it. It's mu zero. Sit back and let the winning roll in. So your sense, just to elaborate a little bit, to link on the topic, your sense is neural networks will solve driving. Yes. We don't need anything else. I think the same way chess was maybe the chess and maybe Google are the pinnacle of search algorithms and things that look kind of like a star, the pinnacle of this era is going to be self-driving cars. But on the path to that, you have to deliver products and it's possible that the path to full self-driving cars will take decades. I doubt it. How long would you put on it? Like what are we, you're chasing it, Tesla's chasing it. What are we talking about? Five years, 10 years, 50 years? In the 2020s. In the 2020s? Yeah, the later part of the 2020s. Will the neural network? Well, that would be nice to see. And on the path to that, you're delivering products, which is a nice L2 system. That's what Tesla is doing, a nice L2 system. It just gets better every time. L2, the only difference between L2 and the other levels is who takes liability. And I'm not a liability guy. I don't want to take liability. I'm going to level two forever. Now, on that little transition, I mean, how do you make the transition work? Is this where driver sensing comes in? Like, how do you make the, because you said a hundred miles, like is there some sort of human factor psychology thing where people start to over-trust the system, all those kinds of effects once it gets better and better and better and better, they get lazier and lazier and lazier. Is that, like, how do you get that transition right? First off, our monitoring is already adaptive. Our monitoring has already seen adaptive. Driver monitoring, is this the camera that's looking at the driver? You have an infrared camera in the... Our policy for how we enforce the driver monitoring is seen adaptive. What's that mean? Well, for example, in one of the extreme cases, if the car is not moving, we do not actively enforce driver monitoring. If you are going through a, like a 45 mile an hour road with lights and stop signs and potentially pedestrians, we enforce a very tight driver monitoring policy. If you are alone on a perfectly straight highway, and this is, it's all machine learning, none of that is hand coded. Well, actually the stop is hand coded, but... So there's some kind of machine learning estimation of risk. Yes. Yeah. I mean, I've always been a huge fan of that. It's difficult to do every step into that direction. Is a worthwhile step to take. It might be difficult to do really well. Us humans are able to estimate risk pretty damn well, whatever the hell that is. That feels like one of the nice features of us humans. Because we humans are really good drivers when we're really tuned in and we're good at estimating risk. When are we supposed to be tuned in? Yeah. You know, people are like, oh, well, you know, why would you ever make the driver monitoring policy less aggressive? Why would you always not keep it at its most aggressive? Because then people are just going to get fatigued from it. Yes. When they get annoyed, you want them, you want the experience to be pleasant. Obviously, I want the experience to be pleasant, but even just from a straight up safety perspective, if you alert people, when they look around and they're like, why is this thing alerting me? There's nothing I could possibly hit right now. People will just learn to tune it out. People will just learn to tune it out, to put weights on the steering wheel, to do whatever, to overcome it. And remember that you're always part of this adaptive system. So all I can really say about how this scale is going forward is, yeah, it's something we have to monitor for. Ooh, we don't know. This is a great psychology experiment at scale. We'll see. Yeah, it's fascinating. We'll track it. And making sure you have a good understanding of attention is a very key part of that psychology problem. Yeah. And you and I probably have come to it differently, but to me, it's a fascinating psychology problem to explore something much deeper than just driving. It's such a nice way to explore human attention and human behavior, which is why, again, we've probably both criticized Mr. Elon Musk on this one topic from different avenues. Because both offline and online, I had little chats with Elon and... I love human beings. As a computer vision problem, as an AI problem, it's fascinating. He wasn't so much interested in that problem. In order to solve driving, the whole point is you want to remove the human from the picture. And it seems like you can't do that quite yet. Eventually, yes, but you can't quite do that yet. So this is the moment where... You can't yet say, I told you so, to Tesla. But it's getting there because I don't know if you've seen this, there's some reporting that they're in fact starting to do driver-model. Yeah, they ship the model in shadow mode. With I believe only a visible light camera. It might even be fisheye. It's like a low resolution... Low resolution, visible light. I mean, to be fair, that's what we have in the Eon as well, our last generation product. This is the one area where I can say our hardware is ahead of Tesla. The rest of our hardware way, way behind, but our driver monitoring camera. So you think... I think on the third row Tesla podcast, somewhere else, I've heard you say that obviously eventually they're going to have driver monitoring. I think what I've said is Elon will definitely ship driver monitoring before he ships level five. Before level five. And I'm willing to bet 10 grand on that. I mean, now I know what to take the bet, but before maybe someone would have, I should have got my money. It's an interesting bet. I think you're right. I'm actually on a human level because he's been... He's made the decision... He said that driver monitoring is the wrong way to go, but you have to think of as a human, as a CEO. I think that's the right thing to say when... Sometimes you have to say things publicly that are different than what you actually believe, because when you're producing a large number of vehicles and the decision was made not to include the camera, what are you supposed to say? Our cars don't have the thing that I think is right to have. It's an interesting thing, but on the other side, as a CEO, I mean, it's something you could probably speak to as a leader. I think about me as a human to publicly change your mind on something. How hard is that? Well... Especially when assholes like George Haas say, I told you so. All I will say is I am not a leader and I am happy to change my mind. And I will... You think Elon will? Yeah, I do. I think he'll come up with a good way to make it psychologically okay for him. It's such an important thing, man, especially for a first principles thinker, because he made a decision that driver monitoring is not the right way to go. And I could see that decision and I could even make that decision. I was on the fence too. Driver monitoring is such an obvious, simple solution to the problem of attention. It's not obvious to me that just by putting a camera there, you solve things. You have to create an incredible, compelling experience just like you're talking about. I don't know if it's easy to do that. It's not at all easy to do that, in fact, I think. So as a creator of a car that's trying to create a product that people love, which is what Tesla tries to do, right? It's not obvious to me that as a design decision, whether adding a camera is a good idea. From a safety perspective either, in the human factors community, everybody says that you should obviously have driver sensing, driver monitoring. That's like saying it's obvious as parents you shouldn't let your kids go out at night. But okay. But they're still going to find ways to do drugs. You have to also be good parents. It's much more complicated than just you need to have driver monitoring. I totally disagree on, okay, if you have a camera there and the camera's watching the person but never throws an alert, they'll never think about it. The driver monitoring policy that you choose to, how you choose to communicate with the user is entirely separate from the data collection perspective. There's one thing to say, tell your teenager they can't do something. There's another thing to gather the data. So you can make informed decisions. That's really interesting. But you have to make that... That's the interesting thing about cars. But even true with Comm.AI, you don't have to manufacture the thing into the car. You have to make a decision that anticipates the right strategy long-term. So you have to start collecting the data and start making decisions. I started it three years ago. I believe that we have the best driver monitoring solution in the world. I think that when you compare it to... Well, Super Cruise is the only other one that I really know that shipped and ours is better. What do you like and not like about Super Cruise? I mean, I had a few. Super Cruise, the sun would be shining through the window, would blind the camera, and it would say I wasn't paying attention when I was looking completely straight. I couldn't reset the attention with a steering wheel touch and Super Cruise would disengage. I was communicating to the car. I'm like, look, I am here. I am paying attention. Why are you really going to force me to disengage? It did. So it's a constant conversation with the user. And yeah, there's no way to ship a system like this VUCan OTA. We're shipping a new one every month. Sometimes we balance it with our users on Discord. Sometimes we make the driver monitoring a little more aggressive and people complain. Sometimes they don't. We want it to be as aggressive as possible where people don't complain and it doesn't feel intrusive. So being able to update the system over the air is an essential component. I mean, that's probably, to me, you mentioned, I mean, to me, that is the biggest innovation of Tesla. It made it, people realize that over the air updates is essential. Yeah. I mean, was that not obvious from the iPhone? The iPhone was the first real product that OTA'd, I think. Was it actually? That's brilliant. I mean, the game consoles used to not, right? The game consoles were maybe the second thing that did. Wow. I didn't really think about it. One of the amazing features of a smartphone isn't just like the touchscreen isn't the thing. It's the ability to constantly update. Yeah, it gets better. It gets better. Love my iOS 14. Yeah. Well, one thing that I probably disagree with you on, on driver monitoring is you've said that it's easy. I mean, you tend to say stuff is easy. I'm sure the, I guess you said it's easy relative to the external perception problem. Can you elaborate why you think it's easy? Feature engineering works for driver monitoring. Feature engineering does not work for the external. So human faces are not, human faces and the movement of human faces and head and body is not as variable as the external environment. Yeah. Is your intuition? Yes. And there's another big difference as well. Your reliability of a driver monitoring system doesn't actually need to be that high. The uncertainty, if you have something that's detecting whether the human's paying attention, it only works 92% of the time, you're still getting almost all the benefit of that because the human, like you're training the human, right? You're dealing with a system that's really helping you out. It's a conversation. It's not like the external thing where guess what, if you swerve into a tree, you swerve into a tree, right? Like you get no margin for error there. Yeah. I think that's really well put. I, I think that's the right, exactly the place where, um, we're comparing to the external perception and the control problem. Driver monitoring is easier because you don't, the bar for success is much lower. Yeah. And I still think like the human face is more complicated actually than the external environment, but for driving, you don't give a damn. I don't need, yeah, I don't need something. I don't need something that complicated to, to, to have to communicate the idea to the human that I want to communicate, which is yo system might mess up here. You got to pay attention. Yeah. See, that's, that's my love and fascination is the human face. And it feels like this is a nice place to, um, create products that create an experience in the car. So like, it feels like there should be more richer experiences in the car. You know, like that's an opportunity for like something like on my eye or just any kind of system, like a Tesla or any of the autonomous vehicle companies is because software is, and there's much more sensors and so much is on a software and you're doing machine learning anyway, there's an opportunity to create totally new experiences that we're not even anticipating. You don't think so. No, you think it's a box that gets you from A to B and you want to do it. Chill. Yeah. I mean, I think as soon as we get to level three on highways, okay, enjoy your candy crush, enjoy your Hulu, enjoy your, you know, whatever, whatever. Sure. You get this, you can look at screens basically versus right now. What do you have music and audio books? So level three is where you can kind of disengage in stretches of time. Well, you think level three is possible? Like on the highway going 400 miles and you can just go to sleep? Oh yeah. Sleep. So again, I think it's really all on a spectrum. I think that being able to use your phone while you're on the highway and like this all being okay and being aware that the car might alert you and you have five seconds to basically. So the five second thing is you think is possible. Yeah, I think it is. Oh yeah. Not in all scenarios, right? Some scenarios it's not. It's the whole risk thing that you mentioned is nice is to be able to estimate like how risky is this situation. That's really important to understand. One other thing you mentioned comparing comma and autopilot is that something about the haptic feel of the way comma controls the car when things are uncertain, like it behaves a little bit more uncertain when things are uncertain. That's kind of an interesting point and then autopilot is much more confident always even when it's uncertain until it runs into trouble. That's a funny thing. I actually mentioned that to Elon, I think, and then the first time we talked he wasn't biting is like communicating uncertainty. I guess comma doesn't really communicate uncertainty explicitly communicates it through haptic feel. Like what's the role of communicating uncertainty do you think? We do some stuff explicitly. We do detect the lanes when you're on the highway and we'll show you how many lanes we're using to drive with. You can look at where it thinks the lanes are. You can look at the path and we want to be better about this. We're actually hiring some new UI people. UI people, you mentioned this because it's such an UI problem too, right? We have a great designer now, but we need people who are just going to build this and debug these UIs. QT people. QT. Is that what the UI is done with is QT? The new UI is in QT. C++ QT? Tesla uses it too. We have some React stuff in there. React JS or just React? React is his own language, right? React Native. React Native is a JavaScript framework. It's all based on JavaScript, but I like C++. What do you think about Dojo with Tesla and their foray into what appears to be specialized hardware for training Yonets? I guess it's something, maybe you can correct me for my shallow looking at it. It seems like something that Google did with TPUs, but specialized for driving data. I don't think it's specialized for driving data. It's just legit, just TPU. They want to go the Apple way. Basically everything required in the chain is done in-house. Well, so you have a problem right now, and this is one of my concerns. I really would like to see somebody deal with this. If anyone out there is doing it, I'd like to help them if I can. You basically have two options right now to train. Your options are Nvidia or Google. So Google is not even an option. Their TPUs are only available in Google Cloud. Google has absolutely onerous terms of service restrictions. They may have changed it, but back in Google's terms of service, it said explicitly you are not allowed to use Google Cloud ML for training autonomous vehicles or for doing anything that competes with Google without Google's prior written permission. Well, okay. I mean, Google is not a platform company. I wouldn't touch TPUs with a 10-foot pole. So that leaves you with the monopoly. Nvidia? Nvidia. So, I mean- That you're not a fan of? Well, look, I was a huge fan of in 2016 Nvidia. Jensen came, sat in the car. Cool guy when the stock was $30 a share. Nvidia stock has skyrocketed. I witnessed a real change in who was in management over there in like 2018. And now they are, let's exploit, let's take every dollar we possibly can out of this ecosystem. Let's charge $10,000 for A100s because we know we got the best shit in the game. And let's charge $10,000 for an A100 when it's really not that different from a 3080, which is 699. The margins that they are making off of those high-end chips are so high that, I mean, I think they're shooting themselves in the foot just from a business perspective because there's a lot of people talking like me now who are like, somebody's got to take Nvidia down. Yeah. Where they could dominate. Nvidia could be the new Intel. Yeah, to be inside everything essentially. And yet the winners in certain spaces like autonomous driving, the winners, only the people who are like desperately falling back and trying to catch up and have a ton of money, like the big automakers are the ones interested in partnering with Nvidia. Oh, and I think a lot of those things are going to fall through. If I were Nvidia, sell chips. Sell chips at a reasonable markup. To everybody. To everybody. Without any restrictions. Without any restrictions. Intel did this. Look at Intel. They had a great long run. Nvidia is trying to turn their, they're like trying to productize their chips way too much. They're trying to extract way more value than they can sustainably. Sure, you can do it tomorrow. Is it going to up your share price? Sure. If you're one of those CEOs who's like, how much can I strip mine this company? And I think, you know, and that's what's weird about it too. Like the CEO is the founder. It's the same guy. Yeah. I mean, I still think Jensen's a great guy. He is great. Why do this? You have a choice. You have a choice right now. Are you trying to cash out? Are you trying to buy a yacht? If you are, fine. But if you're trying to be the next huge semiconductor company, sell chips. Well, the interesting thing about Jensen is he is a big vision guy. So he has a plan like for 50 years down the road. So it makes me wonder like- How does price gouging fit into it? Yeah. How does that fit? Like it's, it doesn't seem to make sense to plan. I worry that he's listening to the wrong people. Yeah. It makes sense I have too sometimes because I, despite everything, I think Nvidia is an incredible company. Well, one, sort of I'm deeply grateful to Nvidia for the products they've created in the past. Me too. Right. And so- The 1080 Ti was a great GPU. Still have a lot of them. It was, yeah. But at the same time, it just feels like, it feels like you don't want to put all your stock in Nvidia. And so like Elon is doing, what Tesla is doing with autopilot and Dojo is the Apple way is because they're not going to share Dojo with George Hots. I know they should sell that chip. Oh, they should sell that. Even their accelerator, the accelerator that's in all the cars, the 30 watt one. Sell it. Why not? So open it up. Make me, why does Tesla have to be a car company? Well, if you sell the chip, here's what you get. Yeah. You're going to make some money off the chips. It doesn't take away from your chip. You're going to make some money, free money. And also the world is going to build an ecosystem of tooling for you. All right. You're not going to have to fix the bug in your 10H layer. Someone else already did. Well, the question, that's an interesting question. I mean, that's the question Steve Jobs asked. That's the question Elon Musk is perhaps asking is, do you want Tesla stuff inside other vehicles in inside potentially inside like iRobot vacuum cleaner? I think you should decide where your advantages are. I'm not saying Tesla should start selling battery packs to automakers because battery packs to automakers, they are straight up in competition with you. If I were Tesla, I'd keep the battery technology totally as far as we make batteries. But the thing about the Tesla TPU is anybody can build that. It's just a question of, you know, are you willing to spend the money? It could be a huge source of revenue potentially. Are you willing to spend the hundred million dollars? Anyone can build it and someone will. And a bunch of companies now are starting trying to build AI accelerators. Somebody's going to get the idea right. And yeah, hopefully they don't get greedy because they'll just lose to the next guy who finally and then eventually the Chinese are going to make knockoff and video chips. From your perspective, I don't know if you're also paying attention to stay on Tesla for a moment. Well, Dave, Elon Musk has talked about a complete rewrite of the neural net that they're using that seems to, again, I'm half paying attention, but it seems to involve basically a kind of integration of all the sensors to where it's a four dimensional view. You know, you have a 3D model of the world over time and then you can, I think it's done both for the, for the actually, you know, so the neural network is able to, in a more holistic way, deal with the world and make predictions and so on, but also to make the annotation task more, you know, easier. Like you can annotate the world in one place and it kind of distributed itself across the sensors and across a different, like the hundreds of tasks that are involved in the HydroNet. What are your thoughts about this rewrite? Is it just like some details that are kind of obvious that are steps that should be taken or is there something fundamental that could challenge your idea that end to end is the right solution? We're in the middle of a big view right now as well. We haven't shipped a new model in a bit. Of what kind? We're going from 2D to 3D. Right now all our stuff, like for example, when the car pitches back, the lane lines also pitch back because we're assuming the flat world hypothesis. The new models do not do this. New models output everything in 3D. But there's still no annotation. So the 3D is more about the output. We have Zs and everything. Zs? Yeah. We added the Zs. We added the Zs. We unified a lot of stuff as well. We switched from TensorFlow to PyTorch. My understanding of what Tesla's thing is, is that their annotator now annotates across the time dimension. I mean, cute. Why are you building an annotator? I find their entire pipeline. I find your vision, I mean the vision of end to end very compelling, but I also like the engineering of the data engine that they've created. In terms of supervised learning pipelines, that thing is damn impressive. You're basically, the idea is that you have hundreds of thousands of people that are doing data collection for you by doing their experience. So that's kind of similar to the Kamaeai model. And you're able to mine that data based on the kind of edge cases you need. I think it's harder to do in the end to end learning. The mining of the right edge cases. That's where feature engineering is actually really powerful because us humans are able to do this kind of mining a little better. But yeah, there's obvious, as we know, there's obvious constraints and limitations to that idea. Carpathi just tweeted. He's like, you get really interesting insights if you sort your validation set by loss and look at the highest loss examples. So yeah, we have a little data engine like thing. We're training a SegNet. Anyway, it's not fancy. It's just like, okay, train the new SegNet, run it on 100,000 images, and now take the thousand with highest loss. Select 100 of those by human, put those, get those ones labeled, retrain, do it again. So it's a much less well-written data engine. And yeah, you can take these things really far. And it is impressive engineering. And if you truly need supervised data for a problem, yeah, things like data engine are the high end of the... What is attention? Is it human paying attention? I mean, we're going to probably build something that looks like data engine to push our driver monitoring further. But for driving itself, you have it all annotated beautifully by what the human does. Yeah, that's interesting. I mean, that applies to driver attention as well. Do you want to detect the eyes? Do you want to detect blinking and pupil movement? Do you want to detect all the face alignments, the landmark detection, and so on, and then doing kind of reasoning based on that? Or do you want to take the entirety of the face over time and do end to end? I mean, it's obvious that eventually you have to do end to end with some calibration, some fixes and so on. But it's like, I don't know when that's the right move. Even if it's end to end, there actually is, there is no kind of... You have to supervise that with humans. Whether a human is paying attention or not is a completely subjective judgment. You can try to automatically do it with some stuff, but you don't have... If I record a video of a human, I don't have true annotations anywhere in that video. The only way to get them is with other humans labeling it, really. Well, I don't know. If you think deeply about it, you might be able to, depending on the task, it might be a discover self-annotating things like... You can look at steering wheel reversals or something like that. You can discover little moments of lapse of attention. That's where psychology comes in. Is there indicate... Because you have so much data to look at. You might be able to find moments when there's just inattention. Even with smartphone, if you want to detect smartphone use, you can start to zoom in. That's the gold mine, the comma AI. Tesla is doing this too, right? They're doing annotation based on self-supervised learning too. It's just a small part of the entire picture. That's the challenge of solving a problem in machine learning if you can discover self-annotating parts of the problem. Our driver monitoring team is half a person right now. Half a person. Once we have... Scale to a full... Two people. Once we have two, three people on that team, I definitely want to look at self-annotating stuff for attention. Let's go back for a sec to a comma. For people who are curious to try it out, how do you install a comma in say a 2020 Toyota Corolla? Or what are the cars that are supported? What are the cars that you recommend? What does it take? You have a few videos out, but maybe through words, can you explain what's the take to actually install the thing? We support, I think it's 91 cars, 91 makes and models. We've got to 100 this year. Nice. Yeah, the 2020 Corolla, great choice. The 2020 Sonata, it's using the stock longitudinal. It's using just our lateral control, but it's a very refined car. Their longitudinal control is not bad at all. So yeah, Corolla, Sonata, or if you're willing to get your hands a little dirty and look in the right places on the internet, the Honda Civic is great, but you're going to have to install a modified EPS firmware in order to get a little bit more torque. I can't help you with that. Comma does not efficiently endorse that, but we have been doing it. We didn't ever release it. We waited for someone else to discover it. When you have a Discord server where people, there's a very active developer community, I suppose. So depending on the level of experimentation you're willing to do, that's the community. If you just want to buy it and you have a supported car, it's 10 minutes to install. There's YouTube videos, it's Ikea furniture level. If you can set up a table from Ikea, you can install a Comma 2 in your supported car and it will just work. Now you're like, oh, but I want this high-end feature or I want to fix this bug. Okay, well, welcome to the developer community. So what if I wanted to, this is something I asked you offline a few months ago. If I wanted to run my own code to use Comma as a platform and try to run something like Open Pilot, what does it take to do that? So there's a toggle in the settings called enable SSH and if you toggle that, you can SSH into your device, you can modify the code, you can upload whatever code you want to it. There's a whole lot of people. So about 60% of people are running stock Comma, about 40% of people are running forks. And there's a community of, there's a bunch of people who maintain these forks and these forks support different cars or they have different toggles. We try to keep away from the toggles that are like disabled driver monitoring, but there's some people might want that kind of thing and like, yeah, it's your car. I'm not here to tell you. We have some, we ban, if you're trying to subvert safety features, you're banned from our Discord, I don't want anything to do with you, but there's some forks doing that. Got it. So you encourage responsible forking. Yeah, yeah. Some people, you know, yeah, some people like, like there's forks that will do, some people just like having a lot of readouts on the UI, like a lot of like flashing numbers. So there's forks that do that. Some people don't like the fact that it disengages when you press the gas pedal, there's forks that disable that. Got it. Now the stock experience is what like, so it does both lane keeping and longitudinal control altogether. So it's not separate, like it is an autopilot. No. Okay, some cars we use the stock longitudinal control. We don't do the longitudinal control in all the cars. Some cars, the ACCs are pretty good in the cars. It's the lane keep that's atrocious in anything except for autopilot and super cruise. But you know, you just turn it on and it works. What does this engagement look like? Yeah. So we have, I mean, I'm very concerned about mode confusion. I've experienced it on super cruise and autopilot where like autopilot, like autopilot disengages. I don't realize that the ACC is still on, the lead car moves slightly over and then the Tesla accelerates to like whatever my set speed is super fast and like what's going on here. We have engaged and disengaged. And this is similar to my understanding. I'm not a pilot, but my understanding is either the pilot is in control or the copilot is in control. And we have the same kind of transition system. Either open pilot is engaged or open pilot is disengaged. Engaged with cruise control, disengaged with either gas, brake or cancel. Let's talk about money. What's the business strategy for Karma? Profitable. Well, so you're, you're congratulation. What so basically selling, so we should say Karma cost a thousand bucks, Karma two. 200 for the interface to the car as well. It's 1200. I'll send that. Nobody is usually upfront like this. Yeah, you gotta, you gotta add the tack on, right? I love it. I'm not going to lie to you. Trust me. It will add $1,200 of value to your life. Yes. It's still super cheap. 30 days, no questions asked, money back guarantee and prices are only going up. You know, if there ever is future hardware, it could cost a lot more than $1,200. So Karma three is in the works. It could be. All I will say is future hardware is going to cost a lot more than the current hardware. Yeah, the people that use the people I've spoken with that use Karma, they use open pilot. They, first of all, they use it a lot. So people that use it, they, they fall in love with our retention rate is insane. It's a good sign. Yeah. It's a really good sign. 70% of Karma two buyers are daily active users. Yeah. It's amazing. Um, also we don't plan on stopping selling the Karma two, like, like it's, you know, so whatever you create that's beyond common to it would be, uh, it would be potentially a phase shift. Like it's so much better that like you could use common to, and you can use common, whatever you want. It's kind of four one kind of what you do. Yeah. You know, autopilot hardware one versus hardware two, the common two is kind of like hardware one. Got it. Got it. I think I heard you talk about retention rate with a BR headsets that the average is just once. That's fast. I mean, it's such a fascinating way to think about technology and this is really, really good sign. And the other thing that people say about commas, like they can't believe they're getting this 4,000 bucks, right? It seems, it seems like a, some kind of steel. So but in terms of like long-term business strategies that basically to put, so it's currently in like a thousand plus cars, 1200 more. Uh, so yeah. Uh, dailies is about, uh, dailies is about 2000. Weekly is about 2500. Monthly is over 3000. Wow. We've grown a lot since we last talked. Is the goal that can we talk crazy for a second? I mean, what's the goal to overtake Tesla? Let's talk. Okay. So I mean, Android did overtake. That's exactly it. Right. So they did it. I actually don't know the timeline of that one, but let, let, let's talk, uh, cause everything is an alpha now, the autopilot you could argue is an alpha in terms of towards the big mission of autonomous driving. Right. And so what, yeah, is your goal to overtake into millions of cars essentially? Of course. Where would it stop? Like it's open source software. It might not be millions of cars with a piece of comma hardware, but yeah, I think open pilot at some point will cross over autopilot in, in, in users, just like Android crossed over iOS. How does Google make money from Android? Uh, it's, it's complicated. Their own devices make money. Google, Google makes money by just kind of having you on the internet. Uh, yes. Google search is built in Gmail is built in Android is just a shill for the rest of Google's ecosystem kind of. Yeah. But the problem is, Andrew is not, is a, is a brilliant thing. I mean, Android arguably changed the world. So there you go. Yes, you can, you can feel good ethically speaking, but as a business strategy is questionable. So hardware, so hard. I mean, it took Google a long time to come around to it, but they are now making money on the pixel. You're not about money. You're more about winning. Yeah, of course. No, but if only, if only 10% of open pilot devices come from comma AI, you still make a lot. That is still, yes, that is a ton of money for our company. Can't somebody create a better comma using open pilot or are you basically saying we'll all compete? Well, I'll compete you is can you create a better Android phone than the Google pixel? Right. I mean, you can, but like, you know, that, so you're confident, like, you know what the hell you're doing. Yeah. It's, it's a, uh, uh, competence and merit. I mean, our money, our money comes from, we're a consumer electronics company. And put it this way. So we sold, we sold like 3000 comma twos. Um, I'm at 2,500 right now. Uh, and like, okay, we're probably going to sell 10,000 units next year. Right. 10,000 units, even just a thousand dollars a unit. Okay. We're at 10 million in, uh, in, in, in, in revenue. Um, get that up to a hundred thousand, maybe double the price of the unit. Now we're talking like 200 million revenue. We're talking about actually making money. One of the rare semi-autonomous or autonomous vehicle companies that are actually making money. Yeah. You know, if you have, if you look at a model, when we were just talking about this yesterday, if you look at a model and like you're testing, like you're AB testing your model and if you're, you're, you're one branch of the AB test, the losses go down very fast in the first five epochs. Yeah. That model is probably going to converge to something considerably better than the one where the losses are going down slower. Why do people think this is going to stop? Why do people think one day there's going to be a great, like, well, Waymo is eventually going to surpass you guys. Well, they're not. Do you see like a world where like a Tesla or a car like a Tesla would be able to basically press a button and you'd like switch to open pilot and you know, you load in? No. So I think, so first off, I think that we may surpass Tesla in terms of users. I do not think we're going to surpass Tesla ever in terms of revenue. I think Tesla can capture a lot more revenue per user than we can, but this mimics the Android iOS model. Exactly. There may be more Android devices, but you know, there's a lot more iPhones than Google pixels. So I think there'll be a lot more Tesla cars sold than pieces of common hardware. And then as far as a Tesla owner being able to switch to open pilot, does iOS, does iPhones run Android? No, but it doesn't make sense. You can if you really want to do it, but it doesn't really make sense. Like it's not. It doesn't make sense. Who cares? What if a large company like automakers, 4GM Toyota came to George Hots or on the tech space, Amazon, Facebook, Google came with a large pile of cash? Would you consider being purchased? Do you see that as a one possible? Not seriously. No. I would probably see how much shit they'll entertain for me. And if they're willing to like jump through a bunch of my hoops, then maybe, but like, no, not the way that M&A works today. I mean, we've been approached. And I laugh in these people's faces. I'm like, are you kidding? Yeah. You know, because it's so demeaning. The M&A people are so demeaning to companies. They treat the startup world as their innovation ecosystem. And they think that I'm cool with going along with that so I can have some of their scam fake fed dollars, you know, fed coin. What am I going to do with more fed coin? You know, fed coin, man. I love that. So that's the cool thing about podcasting actually is people criticize, I don't know if you're familiar with Spotify giving Joe Rogan a hundred million. I don't know about that. And you know, they respect, despite all the shit that people are talking about Spotify, people understand that podcasters like Joe Rogan know what the hell they're doing. So they give them money and say, just do what you do. And like the equivalent for you would be like, George, do what the hell you do because you're good at it. Try not to murder too many people. Like try, like there's some kind of common sense things like just don't go on a weird rampage of. Yeah. It comes down to what companies I could respect, right? You know, could I respect GM? Never. No, I couldn't. I mean, could I respect like a Hyundai? More so, right? That's a lot closer. Toyota? What's your? Nah, nah. It's like Korean is the way I think, I think that, you know, the Japanese, the Germans, the U S they're all too, they're all too, you know, they all think they're too great to be honest. What about the tech companies? Apple? Apple is of the tech companies that I could respect. Apple is the closest. Yeah. I mean, I could never. It would be ironic if, if, if common AI is, is, is acquired by Apple. I mean, Facebook, look, I quit Facebook 10 years ago because I didn't respect the business model. Google has declined so fast in the last five years. What are your thoughts about Waymo and its present and its future? Let me, let me say, let me start by saying something nice, which is, uh, I've visited them a few times and I've, uh, have written in their cars and the engineering that they're doing both the research and the actual development and the engineering they're doing and the scale they're actually achieving by doing it all themselves is really impressive. And the, the balance of safety and innovation and like the cars work really well for the routes they drive. Like they drive fast, which was very surprising to me. Like it drives like the speed limit or faster than the speed limit is it goes and it works really damn well. And the interface is nice and channel Arizona. Yeah. Yeah. And the environment, so it, I, you know, it gives me enough material in my mind to push back against the mad men of the world, like a George Hots to be like, like, cause you kind of imply there's zero probability they're going to win. Yeah. And after I've used, after I've written in it, to me, it's not zero. Oh, it's not for technology reasons. Bureaucracy. No, it's worse than that. It's actually for product reasons, I think. You think they're just not capable of creating an amazing product? No, I think that the product that they're building doesn't make sense. So a few things you say the way most are fast benchmark away against a competent Uber driver. Right. Right. The Uber driver is faster. It's not even about speed. It's the thing you said it's about the experience of being stuck at a stop sign because pedestrians are crossing nonstop. I like when my Uber driver doesn't come to a full stop at the stop sign. You know? And so let's say the way most are 20% slower than an Uber, right? You can argue that they're going to be cheaper. And I argue that users already have the choice to trade off money for speed. It's called Uber pool. I think it's like 15% of rides at Uber pools, right? Users are not willing to trade off money for speed. So the whole product that they're building is not going to be competitive with traditional ride sharing networks. And also, whether there's profit to be made depends entirely on one company having a monopoly. I think that the level four autonomous ride sharing vehicles market is going to look a lot like the scooter market. If even the technology does come to exist, which I question, who's doing well in that market? It's a race to the bottom. Well, it could be closer to like an Uber and a Lyft where it's just a one or two players. Well, the scooter people have given up trying to market scooters as a practical means of transportation and they're just like, they're super fun to ride. Look at wheels. I love those things. And they're great on that front. But from an actual transportation product perspective, I do not think scooters are viable and I do not think level four autonomous cars are viable. If you, let's play a fun experiment. If you ran, let's do a Tesla and let's do Waymo. If Elon Musk took a vacation for a year, he just said, screw it. I'm going to go live in an island, no electronics. And the board decides that we need to find somebody to run the company. And they decided that you should run the company for a year. How do you run Tesla differently? I wouldn't change much. Do you think they're on the right track? I wouldn't change. I mean, I'd have some minor changes, but even my debate with Tesla about end to end versus SegNets, like that's just software. Who cares? Right? Like it's not going to, it's not like you're doing something terrible with SegNets. You're probably building something that's at least going to help you debug the end to end system a lot, right? It's very easy to transition from what they have to like an end to end kind of thing. And then I presume you would in the Model Y or maybe in the Model 3 start adding driver sensing with infrared. Yes, I would add, I would add infrared camera, infrared lights right away to those cars. And start collecting that data and do all that kind of stuff. Yeah. I think they're already kind of doing it. It's an incredibly minor change. If I actually were CEO of Tesla, first off, I'd be horrified that I wouldn't be able to do a better job as Elon. And then I would try to understand the way he's done things before. You would also have to take over his Twitter. So. I don't tweet. Yeah. What's your Twitter situation? Why are you so quiet on Twitter? I mean. It says Dukama is like, what's your social network presence like? Because you on Instagram, you do live streams, you understand the music of the internet, but you don't always fully engage into it. You're part time. I used to have a Twitter. Yeah. I mean, Instagram is a pretty place. Instagram is a beautiful place. It glorifies beauty. I like Instagram's values as a network. Twitter glorifies conflict, glorifies, you know, like, like, like, like, like, you know, taking shots at people. And it's like, you know, Twitter and Donald Trump are perfectly perfect for each other. So Tesla is on Tesla's on the right track in your view. Yeah. OK, let's try. Let's really try this experiment. If you ran Waymo, let's say they're I don't know if you agree, but they seem to be at the head of the pack of the kind of, uh, what would you call that approach? Like it's not necessarily lighter based because it's not about lighter. But before Robotaxi level for Robotaxi, all in before any before making any revenue. So they're probably at the head of the pack. If you were said, hey, George, can you please run this company for a year? How would you change it? Uh, I would go, I would get Anthony Levandowski out of jail and I would put him in charge of the company. Um, let's try to break that apart. Why do you want to make you want to destroy the company by doing that? Or do you mean, or do you mean, uh, you like renegade style thinking that pushes that, that like throws away bureaucracy and goes to first principle thinking? What do you mean by that? I think Anthony Levandowski is a genius and I think he would come up with a much better idea of what to do with Waymo than me. So you mean that unironically he is a genius. Oh yes. Oh, absolutely. Without a doubt. I mean, I'm not saying there's no shortcomings, but in the interactions I've had with him, yeah. What? Um, he's also willing to take like, who knows what he would do with Waymo. I mean, he's also out there like far more out there than I am. Yeah. His big risks. What do you make of him? I was going to talk to him in his pockets and I was going back and forth. I'm such a gullible, naive human. Like I see the best in people and I slowly started to realize that there might be some people out there that like have multiple faces to the world. They're like deceiving and dishonest. I still refuse to like, I, I just, I trust people and I don't care if I get hurt by it, but like, you know, sometimes you have to be a little bit careful, especially platform wise and podcast wise. What do you, what am I supposed to think? So you think, you think he's a good person? Oh, I don't know. I don't really make moral judgments. I mean, it's difficult to. Oh, I mean this about the Waymo. I actually, I mean that whole idea very non-ironically about what I would do. The problem with putting me in charge of Waymo is Waymo is already $10 billion in the hole. Right? The idea Waymo does look, comma is profitable, commas raised $8.1 million. That's small, you know, the small money. Like I can build a reasonable consumer electronics company and succeed wildly at that and still never be able to pay back Waymo's 10 billion. So I think the basic idea with Waymo, we'll forget the 10 billion because they have some backing, but your basic thing is like, what can we do to start making some money? Well, no, I mean, my bigger idea is like whatever the ideas that's going to save Waymo, I don't have it. It's going to have to be a big risk idea and I cannot think of a better person than Anthony Lewandowski to do it. So that is completely what I would do with CEO of Waymo. I would call myself a transitionary CEO, do everything I can to fix that situation. Transitionary CEO. Yeah. Yeah. Because I can't do it. Right? Like I can't, I can't, I mean, I can talk about how what I really want to do is just apologize for all those corny ad campaigns and be like, here's the real state of the technology. Yeah. I mean, I have several criticisms. I'm a little bit more bullish on Waymo than you seem to be, but one criticism I have is it went into corny mode too early. Like it's still a startup. It hasn't delivered on anything. So it should be like more renegade and show off the engineering that they're doing, which just can be impressive as opposed to doing these weird commercials of like your friendly, your friendly car company. I mean, that's my biggest, my biggest snipe at Waymo was always, that guy's a paid actor. That guy's not a Waymo user. He's a paid actor. Look here, I found his call sheet. Do kind of like what SpaceX is doing with the rocket launch is just get, put the nerds up front, put the engineers up front and just like show failures too. Just I love, I love SpaceX's. Yeah. Yeah. The thing that they're doing is right. And it just feels like the right, but we're all so excited to see them succeed. Yeah. I can't wait to see Waymo fail. You know, like you lie to me. I want you to fail. You tell me the truth. You be honest with me. I want you to succeed. Yeah. Yeah. And that requires the, the renegade CEO, right? I'm with you. I'm with you. I still have a little bit of faith in Waymo for the renegade CEO to step forward, but it's not, it's not John Krafchick. Yeah. It's you can't, it's not Chris, and I'm, those people may be very good at certain things, but they're not renegades. Yeah. Because these companies are fundamentally, even though we're talking about billion dollars, all these crazy numbers, they're still like early stage startups. I mean, I just, I, if you are pre revenue and you've raised $10 billion, I have no idea. Like, like this just doesn't work. No, it's against everything. Silicon Valley. Where's your minimum viable product? You know, where's your users? What's your growth numbers? This is traditional Silicon Valley. Why do you not apply it to what you think you're too big to fail already? Like, how do you think autonomous driving will change society? So the mission is for karma to solve self-driving. Do you have like a vision of the world of how it'll be different? Is it as simple as a to B transportation or is there like, cause these are robots. It's not about autonomous driving in and of itself. That's what the technology enables. I think it's the coolest applied AI problem. I like it because it has a clear path to monetary value. But as far as that being the thing that changes the world, I mean, no, like, like there's cute things we're doing in common. Like who'd have thought you could stick a phone on the windshield and it'll drive. But like really the product that you're building is not something that people were not capable of imagining 50 years ago. So no, it doesn't change the world in that front. Could people have imagined the internet 50 years ago? Only true genius visionaries. Everyone could have imagined autonomous cars 50 years ago. It's like a car, but I don't drive it. See I have the sense and I told you like I'm my long-term dream is robots with which you have deep, with whom you have deep connections. And there's different trajectories towards that. And I've been thinking so been thinking of launching a startup. I see autonomous vehicles as a potential trajectory to that. That's not where the direction I would like to go. But I also see Tesla or even Comma AI like pivoting into robotics broadly defined. That's at some stage in the way like you're mentioning the internet didn't expect. Let's solve, you know, when I say a comma about this, we could talk about this, but let's solve self-driving cars first. Got to stay focused on the mission. Don't, don't, don't you're not too big to fail for however much I think commas winning like no, no, no, no, no, you're winning when you solve level five self-driving cars. And until then you haven't won and won. And you know, again, you want to be arrogant in the face of other people. Great. You want to be arrogant in the face of nature. You're an idiot. Right. Stay mission focused. Brilliant put. Like I mentioned, thinking of launching a startup, I've been considering actually before COVID, I've been thinking of moving to San Francisco. Oh, I wouldn't go there. So why is, uh, well, and now I'm thinking about potentially Austin. And we're in San Diego now. San Diego, come here. So why, what, um, I mean, you're, you're such an interesting human. You've launched so many successful things. What, uh, why San Diego? What do you recommend? Why not San Francisco? Have you thought, so in your case, San Diego with Qualcomm. And staff dragon, I mean, that's an amazing combination, but that wasn't really why that wasn't the Y no. I mean, Qualcomm was an afterthought. Qualcomm was, it was a nice thing to think about. It's like, you can have a tech company here. A good one. I mean, you know, I like Qualcomm, but no. Um, well, so why San Diego better than the stuff that why does San Francisco suck? Well, so, okay. So first off, we all kind of said, like, we want to stay in California. People like the ocean, you know, California for, for it's flaws. Like a lot of the flaws of California are not necessarily California as a whole. And they're much more San Francisco specific. Yeah. San Francisco. So I think first tier cities in general have stopped wanting growth. Uh, well, you have like in San Francisco, you know, the voting class always votes to not build more houses because they own all the houses and they're like, well, you know, once people have figured out how to vote themselves more money, they're going to do it. It is so insanely corrupt. Um, it is not balanced at all, like political party wise, you know, it's, it's, it's a, it's a one party city. And for all the discussion of diversity, it's has, it's stops lacking real diversity of thought of background of, uh, approaches, the strategies of ideas. It's kind of a strange place that it's the loudest people about diversity and the biggest lack of diversity. Well, I mean, that's, that's what they say, right? It's the projection. Projection. Yeah. Yeah. It's interesting. And even people in Silicon Valley telling me that's, uh, like high up people, everybody is like, this is a terrible place. It doesn't make sense. I mean, and Corona virus is really what killed it. Yeah. San Francisco was the number one, uh, Exodus during Corona virus. We still think San Diego is a good place to be. Yeah. Yeah. I mean, we'll see. I mean, we'll see what happens with California a bit longer term. Like Austin's an Austin's an interesting choice. I wouldn't, I wouldn't, I don't have really anything bad to say about Austin either, except for the extreme heat in the summer. Um, which, but that's like very on the surface, right? I think as far as like an ecosystem goes, it's cool. I personally love Colorado. Colorado is great. Uh, yeah. I mean, you have these states that are, you know, like just way better run. Um, California is, you know, it's especially San Francisco. It's on a tie horse and like, yeah. Can I ask you for advice to me and to others about what's the take to build a successful startup? Oh, I don't know. I haven't done that. Talk to someone who did that. Well, you've, you know, uh, this is like another book of years that I'll buy for $67, I suppose. So there's, um, one of these days I'll sell out. Yeah, that's right. Jail breaks are going to be a dollar and books are going to be 67. How I, uh, how I jail broke the iPhone by George Hots. That's right. How I jail broke the iPhone and you can do 67 in 21 days. That's right. Oh God. Okay. You can't wait, but quite so you haven't introspective. You have built a very unique company. I mean, not, not you, but you and others, but I don't know. Um, there's no, there's nothing you haven't interest, but you haven't really sat down and thought about like, well, like if you and I were having a bunch of, we're having some beers and you're seeing that I'm depressed and whatever I'm struggling, there's no advice you can give. Oh, I mean more beer. Yeah, I think it's all very like situation dependent. Um, here's, okay. If I can give a generic piece of advice, it's the technology always wins. The better technology always wins and lying always loses. Build technology and don't lie. I'm with you. I agree very much. Long run, long run. Sure. It's the long run. You can remain irrational longer than you can remain solvent. True fact. Well, this is, this is an interesting point because I ethically and just as a human believe that, um, like, like hype and smoke and mirrors is not at any stage of the company is a good strategy. I mean, there's some like, you know, PR magic kind of like, you know, you want a new product. If there's a call to action, if there's like a call to action, like buy my new GPU, look at it. It takes up three slots and it's this big. It's huge. Buy my G for you. Yeah, that's great. If you look at, you know, especially in that, in AI space broadly, but autonomous vehicles, like you can raise a huge amount of money on nothing. And the question to me is like, I'm against that. I'll never be part of that. I don't think, I hope not willingly not, but like, is there something to be said to, uh, essentially lying to raise money, like fake it till you make it kind of thing? I mean, this is Billy McFarlane, the fire festival. Like we all, we all experienced, uh, you know, what happens with that. No, no, don't fake it till you make it be honest and hope you make it the whole way. The technology wins. Right. The technology wins. And like there is, I'm not, you just like the anti-hype, you know, that's, that's a Slava KPSS reference, but, um, hype isn't necessarily bad. I loved camping out for the iPhones. Um, you know, and as long as the hype is backed by like substance, as long as it's backed by something I can actually buy and like it's real, then hype is great. And it's a great feeling. It's when the hype is backed by lies that it's a bad feeling. I mean, a lot of people call Elon Musk a fraud. How could he be a fraud? I've noticed this, this kind of interesting effect, which is he does tend to over promise and deliver what's, what's the better way to phrase it? Promise a timeline that he doesn't deliver on. He delivers much later on. What do you think about that? Cause I do that. I think that's a programmer thing. I do that as well. You think that's a really bad thing to do or is that okay? I think that's again, as long as like you're working toward it and you're going to deliver on it and it's not too far off. Right. Right. Like, like, you know, the whole, the whole autonomous vehicle thing, it's like, I mean, I still think Tesla's on track to beat us. I still think even with their, even with their missteps, they have advantages. We don't have, um, you know, Elon is better than me at, at, at like marshaling massive amounts of resources. So, you know, I still think given the fact that they're maybe making some wrong decisions, they'll end up winning and like, it's fine to hype it if you're actually going to win. Right. Like if Elon says, look, we're going to be landing rockets back on earth in a year and it takes four, like, you know, he landed a rocket back on earth and he was working toward it the whole time. I think there's some amount of like, I think what it becomes wrong is if you know you're not going to meet that deadline. If you're lying. Yeah. That's brilliantly put. Like this is what people don't understand. I think like Elon believes everything he says as far as I can tell he does. And I detected that in myself too. Like if I, it's only bullshit. If you're like conscious of yourself lying. Yeah, I think so. Yeah. Now you can't take that to such an extreme, right? Like in a way I think maybe Billy McFarland believed everything he said too. Right. Like that's how you start a cult and then everybody kills themselves. Yeah. Yeah. Like it's, you need, you need, if there's like some factor on it, it's fine. And you need some people to like, you know, keep you in check. But like if you deliver on most of the things you say and just the timelines are off. It does piss people off though. I wonder, but who cares? In long arc of history, the people, everybody gets pissed off at the people who succeed, which is one of the things that frustrates me about this world is they don't celebrate the success of others. Like there's so many people that want Elon to fail. It's so fascinating to me. Like what is wrong with you? Like, so Elon Musk talks about like people short, like they talk about financial, but I think it's much bigger than the financials. I've seen like the human factors community, they want, they want other people to fail. What, why, why? Like even people, the harshest thing is like, you know, even people that like seem to really hate Donald Trump, they want him to fail or like the other president or they want Barack Obama to fail. It's like, it's weird, but I want that. I would love to inspire that part of the world to change because if the human species is going to survive, we should celebrate success. It seems like the efficient thing to do in this objective function that we're all striving for is to celebrate the ones that like figure out how to like do better at that objective function as opposed to like dragging them down back into the mud. I think there is, this is the speech I always give about the commenters on hacker news. So first off, something to remember about the internet in general is commenters are not representative of the population. I don't comment on anything. You know, commenters are representative of a certain sliver of the population. And on hacker news, a common thing I'll see is when you'll see something that's like, you know, promises to be wild out there and innovative, there is some amount of, you know, checking them back to earth, but there's also some amount of, if this thing succeeds, well, I'm 36 and I've worked at large tech companies my whole life. They can't succeed because if they succeed, that would mean that I could have done something different with my life, but we know that I couldn't have, we know that I couldn't have and that's why they're going to fail. And they have to root for them to fail to kind of maintain their world image. So, tune it out. And they comment, well, it's hard. So one of the things I'm considering startup wise is to change that. Because I think it's also a technology problem. It's a platform problem. I agree. It's like, because the thing you said most people don't comment, I think most people want to comment. They just don't because it's all the assholes who are commenting. Exactly. I don't want to be grouped in with them. You don't want to be at a party where everyone is an asshole. But that's a platform problem. I can't believe what Reddit's become. I can't believe the group think in Reddit comments. Reddit is an interesting one because there's subreddits. And so you can still see, especially small subreddits that are little like havens of like joy and positivity and deep, even disagreement, but like nuanced discussion. But it's only like small little pockets. But that's emergent. The platform is not helping that or hurting that. So I guess naturally something about the internet, if you don't put in a lot of effort to encourage nuance and positive good vibes, it's naturally going to decline into chaos. I would love to see someone do this well. I think it's very doable. I think actually, I feel like Twitter could be overthrown. Yashobach talked about how if you have like and retweet, that's only positive wiring. The only way to do anything like negative there is with a comment. And that's like that asymmetry is what gives Twitter its particular toxicness. Whereas I find YouTube comments to be much better because YouTube comments have a have a have an up and a down and they don't show the downloads. Without getting into depth of this particular discussion, the point is to explore possibilities and get a lot of data on it because I mean, I could disagree with what you just said. The point is it's unclear. It hasn't been explored in a really rich way. Like these questions of how to create platforms that encourage positivity. I think it's a technology problem. And I think we'll look back at Twitter as it is now. Maybe it'll happen within Twitter, but most likely somebody overthrows them. We'll look back at Twitter and say, can't believe we put up with this level of toxicity. You need a different business model too. Any social network that fundamentally has advertising as a business model. This was in the social dilemma, which I didn't watch, but I liked it. It's like, you know, there's always the, you know, you are the product, you're not the, but they had a nuanced take on it that I really liked. And it said the product being sold is influence over you. The product being sold is literally your influence on you. That can't be, if that's your idea, okay. Well, you know, guess what? It can't not be toxic. Yeah. Maybe there's ways to spin it like with, with giving a lot more control to the user and transparency to see what is happening to them as opposed to in the shadows as possible, but that can't be the primary source of. But the users aren't, no one's going to use that. It depends. It depends. I think, I think that the, you're, you're not going to, you can't depend on self-awareness of the users. It's a, it's another, it's a longer discussion because you can't depend on it, but you can reward self-awareness. Like if for the ones who are willing to put in the work of self-awareness, you can reward them and incentivize and perhaps be pleasantly surprised how many people are willing to be self-aware on the internet. Like we are in real life. Like I'm putting in a lot of effort with you right now being self-aware about if I say something stupid or mean, I'll like look at your body language. Like I'm putting in that effort. It's costly for an introvert, very costly, but on the internet, fuck it. Like most people are like, I don't care if this hurts somebody. I don't care if this is not interesting or if this is, yeah, it's a mean or whatever. I think so much of the engagement today on the internet is so disingenuine too. You're not doing this out of a genuine, this is what you think. You're doing this just straight up to manipulate others. Whether you're in, you just became an ad. Okay. Let's talk about a fun topic, which is programming. Here's another book idea for you. Let me pitch. What's your perfect programming setup? So like this by George Hots. So like what, listen, you're- Give me a MacBook Air, sit me in a corner of a hotel room and you know I'll still have food. I don't fetishize like multiple monitors, keyboard. Those things are nice and I'm not going to say no to them, but did they automatically unlock tons of productivity? No, not at all. I have definitely been more productive on a MacBook Air in a corner of a hotel room. What about IDE? So which operating system do you love? What text editor do you use? IDE? Is there something that is like the perfect, if you could just say the perfect productivity setup for George Hots. Doesn't matter. Doesn't matter. It literally doesn't matter. I guess I code most of the time in Vim. Literally I'm using an editor from the 70s. You didn't make anything better. Okay, VS code is nice for reading code. There's a few things that are nice about it. I think that there, you can build much better tools. How like IDA's xrefs work way better than VS codes. Why? Yeah, actually that's a good question. Like why? I still use, sorry, Emacs for most. I've actually never, I have to confess something dark. Yeah. I've never used Vim. I think maybe I'm just afraid that my life has been a waste. I'm so, I'm not evangelical about Emacs. This is how I feel about Tenderflow versus PyTorch. Everything just like we've switched everything to PyTorch now. Put months into the switch. I have felt like I've wasted years on TensorFlow. I can't believe it. I can't believe how much better PyTorch is. Yeah. I've used Emacs in Vim. Doesn't matter. Yeah, still just my heart somehow. I fell in love with Lisp. I don't know why. You can't, the heart wants what the heart wants. I don't understand it, but it just connected with me. Maybe it's the functional language that first I connected with. Maybe it's because so many of the AI courses before the deep learning revolution were taught with Lisp in mind. I don't know. I don't know what it is, but I'm stuck with it. But at the same time, like why am I not using a modern ID for some of these programming? I don't know. They're not that much better. I've used modern IDs too. But at the same time, so like to just, well not to disagree with you, but like I like multiple monitors. Like I have to do work on a laptop and it's a pain in the ass. And also I'm addicted to the Kinesis weird keyboard. You could see there. Yeah. So you don't have any of that. You can just be in a, on a Mac book. I mean, look at work. I have three 24 inch monitors. I have a happy hacking keyboard. I have a razor death header mouse. Like, but it's not essential for you. Let's go to a day in the life of George Hots. What is the perfect day productivity wise? So we're not talking about like Hunter S Thompson drugs. And let's look at productivity. Like what's the day look like? I'm like hour by hour. Is there any regularities that create a magical George Hots experience? I can remember three days in my life. And I remember these days vividly when I've gone through kind of radical transformations to the way I think and what I would give, I would pay a hundred thousand dollars if I could have one of these days tomorrow, the days have been so impactful. And one was first discovering Elias of Yudkowsky on the singularity and reading that stuff. And like, you know, my mind was blown. The next was discovering the Hunter price and that AI is just compression. Like finally understanding AIXI and what all of that was. You know, I like read about it when I was 18, 19, I didn't understand it. And then the fact that like lossless compression implies intelligence the day that I was shown that. And then the third one is controversial. The day I found a blog called Unqualified Reservations and read that and I was like, wait, which one is that? That's what's the guy's name? Curtis Yarvin. Yeah. So many people tell me I'm supposed to talk to him. Yeah. He sounds insane or brilliant, but insane or both. I don't know. I found that blog was another like, this was during like, like Gamergate and kind of the run up to the 2016 election. And I'm like, wow, okay, the world makes sense now. This is like, I had a framework now to interpret this. Just like I got the framework for AI and a framework to interpret technological progress. Like those days when I discovered these new frameworks were. Oh, interesting. So it's not about, but what was special about those days? How did those days come to be? Is it just you got lucky? Like. Sure. Like what, you just encountered a harder prize on, on hacking news or something like that? Like what? But you see, I don't think it's just, see, I don't think it's just that like, I could have gotten lucky at any point. I think that in a way. You were ready at that moment. Yeah, exactly. To receive the information. But is there some magic to the day today of like, like eating breakfast and it's the mundane things? Nah. Nothing. I drift through life. Without structure. I drift through life, hoping and praying that I will get another day like those days. And there's nothing in particular you do to, to be a receptacle for another, for day number four. No, I didn't do anything to get the other ones. So I don't think I have to really do anything now. I took a month long trip to New York and the Ethereum thing was the highlight of it, but the rest of it was pretty terrible. I did a two week road trip and I got, I had to turn around. I had to turn around and drive in Gunnison, Colorado, pass through Gunnison and the snow starts coming down. There's a pass up there called Monarch Pass in order to get through to Denver. You got to get over the Rockies. And I had to turn my car around. I couldn't, I watched, I watched F-150 go off the road. I'm like, I gotta go back. And like that day was meaningful because like, like it was real. Like I actually had to turn my car around. It's rare that anything even real happens in my life, even as mundane is the fact that yeah, there was snow. I had to turn around, stay in Gunnison and leave the next day. Something about that moment felt real. Okay. So actually it's interesting to break apart the three moments you mentioned if it's okay. So I always have trouble pronouncing his name, but Lousy Yurkowski. So what, how did your worldview change in starting to consider the, the exponential growth of AI and AGI that he thinks about and the, the, the threats of artificial intelligence and all that kind of ideas. Like, can you, is it like, can you maybe break apart like what exactly was so magical to you? It was a transformational experience. Today, everyone knows him for threats and AI safety. This was pre that stuff. There was, I don't think a mention of AI safety on the page. This is, this is old Yurkowski stuff. He'd probably denounce it all now. He'd probably be like, that's exactly what I didn't want to happen. Sorry, man. Is there something specific you can take from his work that you can remember? Yeah. It was this realization that computers double in power every 18 months and humans do not. And they haven't crossed yet, but if you have one thing that's doubling every 18 months and one thing that's staying like this, you know, here's your log graph. Here's your line. You know, you calculate that. And that, did that open the door to the exponential thinking? Like thinking that like, you know what, with technology we can actually transform the world. It opened the door to human obsolescence. It opened the door to realize that in my lifetime, humans are going to be replaced. And then the matching idea to that of artificial intelligence with the Hutter prize, you know, I'm torn. I go back and forth on what I think about it. But the, the, the basic thesis is it's nice. It's a nice compelling notion that we can reduce the task of creating an intelligent system, a generally intelligent system into the task of compression. So you can think of all of intelligence in the universe, in fact, as a kind of compression. Do you find that, was that just at the time you found that as a compelling idea or do you still find that a compelling idea? I still find that a compelling idea. I think that it's not that useful day to day, but actually one of maybe my quests before that was a search for the definition of the word intelligence. And I never had one. And I definitely have a definition of the word compression. It's a very simple, straightforward one. And you know what compression is, you know, lossless is lossless compression, not lossy, lossless compression. And that that is equivalent to intelligence, which I believe, I'm not sure how useful that definition is day to day, but like I now have a framework to understand what it is. And he just 10x the, the, the prize for that competition, like recently a few months ago, you ever thought of taking a crack at that? Oh, I did. Oh, I did. I spent, I spent the next, after I found the prize, I spent the next six months of my life trying it. And well, that's when I started learning everything about AI and then I worked with vicarious for a bit. And then I learned, read all the deep learning stuff and I'm like, okay, now I like I'm caught up to modern AI. Wow. And I had, I had a really good framework to put it all in from the compression stuff, right? Like some of the first, some of the first deep learning models I played with were, were gbt, gbt, basically, but before transformers, before it was still RNNs to do a character prediction. But by the way, on the compression side, I mean the, especially in neural networks, what do you make of the lossless requirement with the Hutter prize? So you know, human intelligence and neural networks can probably compress stuff pretty well, but there would be lossy. It's imperfect. You can turn a lossy compression into a lossless compressor pretty easily using an arithmetic encoder, right? You can take an arithmetic encoder and you can just encode the noise with maximum efficiency. Right? So even if you can't predict exactly what the next character is, the better a probability distribution you can put over the next character, you can then use an arithmetic encoder to, right? You don't have to know whether it's an E or an I, you just have to put good probabilities on them and then, you know, code those. And if you have, it's a bits of entropy thing, right? So let me, on that topic, it could be interesting as a little side tour. What are your thoughts in this year about GPT-3 and these language models and these transformers? Is there something interesting to you as an AI researcher or is there something interesting to you as an autonomous vehicle developer? Nah, I think, I think it's overhyped. I mean, it's not like it's cool. It's cool for what it is, but no, we're not just going to be able to scale up to GPT-12 and get general purpose intelligence. Like your loss function is literally just, you know, you know, cross entropy loss on the character, right? Like that's not the loss function of general intelligence. Is that obvious to you? Yes. Can you imagine that like to play devil's advocate on yourself, is it possible that you can, the GPT-12 will achieve general intelligence with something as dumb as this kind of loss function? I guess it depends what you mean by general intelligence. So there's another problem with the GPTs and that's that they don't have a, they don't have long-term memory. Right. Right. So like just GPT-12, a scaled up version of GPT-2 or 3, I find it hard to believe. Well, you can scale it in, yeah, so it's a hard-coded length, but you can make it wider and wider and wider. Yeah. You're going to get, you're going to get cool things from those systems, but I don't think you're ever going to get something that can like, you know, build me a rocket ship. What about self-driving? So, you know, you can use transformer with video, for example. You think, is there something in there? No, because look, we use, we use a GRU. We use a GRU. It grew out to a transformer. I think driving is much more Markovian than language. So Markovian, you mean like the memory, which, which aspect of Markov chains? Markovian, I mean that like most of the information in the state at t minus one is also in the, is in state t. I see, yeah. Right. And it kind of like drops off nicely like this, whereas sometime with language, you have to refer back to the third paragraph on the second page. I feel like... There's not many, like, like you can say like speed limit signs, but there's really not many things in autonomous driving that look like that. But if you look at, to play devil's advocate is the risk estimation thing that you've talked about is kind of interesting is it feels like there might be some longer term aggregation of context necessary to be able to figure out like the context. I'm not even sure I'm believing my own devil's advocate. We have a nice, we have a nice like vision model, which outputs like a one or two four dimensional perception space. Can I try transformers on it? Sure. I probably will. At some point we'll try transformers and then we'll just see, do they do better? Sure. But it might not be a game changer. Well, I'm not like, like might transformers work better than grooves for autonomous driving? Sure. Might we switch? Sure. Is this some radical change? No. Okay. We used to slightly different, you know, we switched from RNNs to grooves, like, okay, maybe it's grooves to transformers, but no, it's not. Yeah. Well, on the, on the topic of general intelligence, I don't know how much I've talked to you about it. Like what, um, do you think we'll actually build an AGI? Like if you look at Ray Kurzweil with Singularity, do you have like an intuition about, you're kind of saying driving is easy. Yeah. And I tend to personally believe that solving driving will have really deep, important impacts on our ability to solve general intelligence. Like I think driving doesn't require general intelligence, but I think they're going to be neighbors in a way that it's like deeply tied because it's so like driving is so deeply connected to the human experience that I think solving one will help solve the other. But so I don't see, I don't see driving as like easy and almost like separate than general intelligence, but like what's your vision of a future with a singularity? Do you see there'll be a single moment, like a singularity where it'll be a phase shift? Are we in the singularity now? Like what, do you have crazy ideas about the future in terms of AGI? We definitely have the singularity now. We are? Of course, of course. Look at the bandwidth between people. The bandwidth between people goes up. All right. Um, the singularity is just, you know, when the bandwidth, but what do you mean by the bandwidth of people? Communications tools. The whole world is networked. The whole world is networked and we raise the speed of that network. Right. Oh, so you think the communication of information in a distributed way is a empowering thing for collective intelligence? Oh, I didn't say it's necessarily a good thing, but I think that's like, when I think of the definition of the singularity, yeah, it seems kind of right. I see. Like it's a change in the world beyond which like the world would be transformed in ways that we can't possibly imagine. No, I mean, I think we're in the singularity now in the sense that there's like, you know, one world and a monoculture and it's also linked. Yeah. I mean, I kind of share the intuition that the, the singularity will originate from the collective intelligence of us ants versus the, like some single system, AGI type thing. Oh, I totally agree with that. Yeah. I don't, I don't really believe in like, like a hard takeoff AGI kind of thing. Um, yeah, I don't think, I don't even think AI is all that different in kind from what we've already been building. With respect to driving, I think driving is a subset of general intelligence and I think it's a pretty complete subset. I think the tools we develop at Comma will also be extremely helpful to solving general intelligence and that's, I think the real reason why I'm doing it. I don't care about self-driving cars. It's a cool problem to beat people at. But yeah, I mean, yeah, you're kind of, you're of two minds. So one, you do have to have a mission and you want to focus and make sure you get, you get there, you can't forget that. But at the same time, there is a thread that's much bigger than, uh, that connects the entirety of your effort. That's much bigger than just driving with AI and with general intelligence, it is so easy to delude yourself into thinking you've figured something out when you haven't. If we build a level five self-driving car, we have indisputably built something. Yeah. Is it general intelligence? I'm not going to debate that. I will say we've built something that provides huge financial value. Yeah. Beautifully put. That's the engineering credo. Like just, just build the thing. It's like, uh, that's why I'm with, uh, with, uh, with, with the, on, uh, go to Mars. Yeah, it's a great one. You can argue like who the hell cares about going to Mars, but the reality is set that as a mission, get it done. Yeah. And then you're going to crack some pro problem that you've never even expected in the process of doing that. Yeah. And, and, you know, I think if I had a choice between humanity, going to Mars and solving self-driving cars, I think going to Mars is, uh, better, but I don't know, I'm more suited for self-driving cars. I'm an information guy. I'm not a modernist. I'm a post-modernist. Post-modernist. All right. Beautifully put. Let me, let me drag you back to programming for a sec. What three, maybe three to five programming languages should people learn? Do you think like, if you look at yourself, what did you get the most out of from learning? Uh, well, so everybody should learn C and assembly. We'll start with those two. Right. Assembly. Yeah. If you can't code in assembly, you don't know what the computer's doing. You don't understand, like, you don't have to be great in assembly, but you have to code in it. And then like, you have to appreciate assembly in order to appreciate all the great things C gets you. And then you have to code in C in order to appreciate all the great things Python gets you. So I'll just say assembly C and Python. We'll start with those three. The memory allocation of C and the, the, the fact that it's assembly is to give you a sense of just how many levels of abstraction you get to work on in modern day programming. Yeah. Yeah. Graph coloring for assignment, register assignment and compilers. Yeah. Like, you know, you got to do, you know, the compiler, your computer only has a certain number of registers, yet you can have all the variables you want in a C function. You know, so you get to start to build intuition about compilation, like what a compiler gets you. What else? Well, then there is, then there's kind of a, so those are all very imperative programming languages. Then there's two other paradigms for programming that everybody should be familiar with. One of them is functional. You should learn Haskell and take that all the way through, learn a language with dependent types like Coq. Learn that whole space, like the very PL theory, heavy languages. And Haskell is your favorite functional? Is that the go-to? Yeah, I'm not a great Haskell programmer. I wrote a compiler in Haskell once. There's another paradigm. And actually there's one more paradigm that I'll even talk about after that, that I never used to talk about when I would think about this. But the next paradigm is learn Verilog of HDL. Understand this idea of all of the instructions executed once. If I have a block in Verilog and I write stuff in it, it's not sequential. They all execute it once. And then like think like that. So hardware works. So I guess assembly doesn't quite get you that. Assembly is more about compilation and Verilog is more about the hardware. Like, giving a sense of what actually is the hardware is doing. Assembly C, Python are straight, like they sit right on top of each other. In fact, C is, well, C is kind of coded in C, but you could imagine the first C was coded in assembly and Python is actually coded in C. So, you know, you can straight up go on that. Got it. And then Verilog gives you, that's brilliant. Okay. And then I think there's another one now. Everyone's Carpathi calls it programming 2.0, which is learn a, I'm not even going to, don't learn TensorFlow, learn PyTorch. So machine learning. We've got to come up with a better term than programming 2.0. But yeah. It's a programming language. I wonder if it can be formalized a little bit better. It feels like we're in the early days of what that actually entails. Data driven programming. Data driven programming. Yeah. But it's so fundamentally different as a paradigm than the others. Like it almost requires a different skill set. But you think it's still, yeah. And PyTorch versus TensorFlow, PyTorch wins. It's the fourth paradigm. It's the fourth paradigm that I've kind of seen. It's like this, you know, imperative functional hardware. I don't know a better word for it. And then ML. Do you have advice for people that want to, you know, get into programming, want to learn programming? You have a video. What is programming new blessings? Exclamation point. And I think the top comment is like warning. This is not for noobs. Do you have a noob like TLDW for that video, but also a noob friendly advice on how to get into programming? You are never going to learn programming by watching a video called learn programming. The only way to learn programming, I think, and the only one is the only way everyone I've ever met who can program well learned it all in the same way. They had something they wanted to do and then they tried to do it and then they were like, oh, well, okay, this is kind of, you know, it'd be nice if the computer could kind of do this thing. And then, you know, that's how you learn. You just keep pushing on a project. So the only advice I have for learning programming is go program. Somebody wrote to me a question like, we don't really, they're looking to learn about recurrent neural networks. And saying like, my company's thinking of using recurrent neural networks for time series data, but we don't really have an idea of where to use it yet. We just want to, like, do you have any advice on how to learn about, these are these kind of general machine learning questions. And I think the answer is like, actually have a problem that you're trying to solve and just. I see that stuff. Oh my God. When people talk like that, they're like, I heard machine learning is important. Would you help us integrate machine learning with macaroni and cheese production? You just, I don't even, you can't help these people. Like, who lets you run anything? Who lets that kind of person run anything? I think we're all, we're all beginners at some point. So it's not like they're a beginner. It's like, my problem is not that they don't know about machine learning. My problem is that they think that machine learning has something to say about macaroni and cheese production. Or like, I heard about this new technology. How can I use it for why? Like, I don't know what it is, but how can I use it for why? That's true. You have to build up an intuition of how, because you might be able to figure out a way, but like the prerequisite is you should have a macaroni and cheese problem to solve first. Exactly. And then two, you should have more traditional, like the learning process should involve more traditionally applicable problems in the space of whatever that is, machine learning, and then see if it can be applied to that competition. At least start with, tell me about a problem. Like if you have a problem, you're like, you know, some of my boxes aren't getting enough macaroni in them. Can we use machine learning to solve this problem? That's much, much better than how do I apply machine learning to macaroni and cheese? One big thing, maybe this is me talking to the audience a little bit, because I get these days so many messages, advice on how to like learn stuff. Okay. This is not me being mean. I think this is quite profound actually, is you should Google it. Oh yeah. One of the skills that you should really acquire as an engineer, as a researcher, as a thinker, like one, there's two complimentary skills, like one is with a blank sheet of paper with no internet to think deeply. And then the other is to Google the crap out of the questions you have. That's actually a skill people often talk about, but like doing research, like pulling at the thread and like looking up different words, going into like GitHub repositories with two stars and like looking how they did stuff, like looking at the code or going on Twitter, seeing like there's little pockets of brilliant people that are like having discussions. Like if you're a neuroscientist, go into signal processing community. If you're an AI person going into the psychology community, like switch communities, like keep searching, searching, searching, because it's so much better to invest in like finding somebody else who already solved your problem than it is to try to solve the problem. Because they've often invested years of their life, like entire communities are probably already out there who have tried to solve your problem. I think they're the same thing. I think you go try to solve the problem and then in trying to solve the problem, if you're good at solving problems, you'll stumble upon the person who solved it already. But the stumbling is really important. I think that's a skill that people should really put, especially in undergrad, like search. If you ask me a question, how should I get started in deep learning, like especially, like that is just so Googleable. Like the whole point is you Google that and you get a million pages and just start looking at them. Start pulling at the threads, start exploring, start taking notes, start getting advice from a million people that have already like spent their life answering that question actually. Oh, well, yeah, I mean, that's definitely also, yeah, when people like ask me things like that, I'm like, trust me, the top answer on Google is much, much better than anything I'm going to tell you. Right? Yeah. People ask, it's an interesting question. Let me know if you have any recommendations. What three books, technical or fiction or philosophical, had an impact on your life or you would recommend perhaps? Maybe we'll start with the least controversial, Infinite Jest. Infinite Jest is a- David Foster Wallace? Yeah, it's a book about wireheading really. Very enjoyable to read, very well written. You will grow as a person reading this book, its effort. And I'll set that up for the second book, which is pornography. It's called Atlas Shrugged, which- Atlas Shrugged is pornography? Yeah, I mean, it is. I will not defend the, I will not say Atlas Shrugged is a well-written book. It is entertaining to read certainly, just like pornography. The production value isn't great. There's a 60 page monologue in there that Anne Rand's editor really wanted to take out and she paid, she paid out of her pocket to keep that 60 page monologue in the book. But it is a great book for a kind of framework of human relations. And I know a lot of people are like, yeah, but it's a terrible framework. Yeah, but it's a framework. Just for context, in a couple of days I'm speaking with, for probably four plus hours with Yaron Brook, who's the main living remaining objectivist. Objectivist. Interesting. So, I've always found this philosophy quite interesting on many levels. One of how repulsive some percent of, large percent of the population find it, which is always funny to me when people are like unable to even read a philosophy because of some, I think that says more about their psychological perspective on it. But there is something about objectivism and Anne Rand's philosophy that's deeply connected to this idea of capitalism, of the ethical life is the productive life. That was always compelling to me. I didn't seem to interpret it in the negative sense that some people do. To be fair, I read that book when I was 19. So you had an impact at that point. Yeah. And the bad guys in the book have this slogan, from each according to their ability to each according to their need. And I'm looking at this and I'm like, these are the most, this is Team Rocket level cartoonishness. Right? No bad. And then when I realized that was actually the slogan of the Communist Party, I'm like, wait a second. Wait, no, no, no, no, no. You're telling me this really happened? Yeah, it's interesting. I mean, one of the criticisms of her work is she has a cartoonish view of good and evil. Like the reality, as Jordan Peterson says, is that each of us have the capacity for good and evil in us as opposed to like, there's some characters who are purely evil and some characters that are purely good. And that's in a way why it's pornographic. The production value. I love it. Like, evil is punished and there's very clear, like, you know, there's no, there's no, you know, just like porn doesn't have, you know, like character growth. Well, you know, neither does Alan Sherwood. Like, really well put. But 19 year old George Hotz, it was, it was good enough. Yeah. Yeah. What, what's the third, you have something? I could give these, these two, I'll just throw out. They're sci-fi, Perputation City. Great thing to start thinking about copies of yourself. And then, um, that is, uh, Greg Egan. Uh, he's a, that might not be his real name. Some Australian guy might not be Australian. I don't know. Um, and then this one's online. It's called the Metamorphosis of Prime Intellect. Um, it's a story set in a post-singularity world. It's interesting. Is there, uh, can you, either of the worlds, do you find something, uh, philosophically interesting in them that you can comment on? I mean, it is clear to me that, uh, Metamorphosis of Prime Intellect is like written by an engineer, uh, which is, it's very, it's very almost a pragmatic take on a utopia in a way. Positive or negative? Is that? Well, that's up to you to decide reading the book. And the ending of it is very interesting as well. And I didn't realize what it was. I first read that when I was 15. I've reread that book several times in my life and it's short. It's 50 pages. Everyone should go read it. What's, uh, sorry, this is a little tangent. I've been working through the foundation. I've been, I haven't read much sci-fi in my whole life and I'm trying to fix that. Uh, the last few months, that's been a little side project. What's, uh, to you is the greatest sci-fi novel, uh, that, uh, people should read or is that, or? I mean, I would, I would, yeah, I would, I would say like, yeah, permutation city, metamorphosis, primal intellect. Um, I don't know. I didn't like foundation. Uh, I thought it was way too modernist. Um, do you like dune and like all of those? I've never read dune. I've never read dune. I have to read it. Uh, fire upon the deep is interesting. Uh, okay. I mean, look, everyone should read, everyone should read Neuromancer. Everyone should read Snow Crash. If you haven't read those, like start there. Um, yeah, I haven't read Snow Crash. Never read Snow Crash. Oh, it's, it's very entertaining. Go to Lester Bach. And if you want the controversial one, Bronze Age Mindset. All right. I'll look into that one. Those aren't sci-fi, but just around that books. So a bunch of people asked me on Twitter and Reddit and so on for advice. So what advice would you give a young person today about life? Another, what, uh, yeah, I mean, looking back, especially when you're a young person, or younger, you did, uh, and you continued it, you've accomplished a lot of interesting things. Is there some advice from those? From that life of yours that you can pass on? If college ever opens again, I would love to give a graduation speech. Um, at that point I will put a lot of somewhat satirical effort into this question. Yeah. At this, you haven't written anything at this point. Oh, you know what? These were sunscreen, this is water. Like you're plagiarizing. I mean, but that's the, that's the like, clean your room, you know, you can play drugs from, from all of this stuff. And it's, it's, there is no self-help books aren't designed to help you. They're designed to make you feel good. Like whatever advice I could give, you already know. Everyone already knows. Sorry, it doesn't feel good. Right? Like, you know, you know, if, if I tell you that you should, you know, eat well and, and, and read more and it's not going to do anything. I think the whole like genre of those kinds of questions is, is, is meaningless. I don't know. If anything, it's don't worry so much about that stuff. Don't be so caught up in your head. Right. I mean, you're yeah, in the sense that your whole life, if your whole existence is like moving version of that advice, I don't know. There's there's something, I mean, there's something in you that resists that kind of thinking and that in itself is, it's just illustrative of who you are. And there's something to learn from that. I think you're, you're clearly not overthinking stuff. Yeah. And you know what, I, even when I talk about my advice, I'm like, my advice is only relevant to me. It's not relevant to anybody else. I'm not saying you should go out. If you're the kind of person who overthinks things to stop overthinking things, it's not bad. It doesn't work for me. Maybe it works for you. I, you know, I don't know. Let me ask you about love. Yeah. Uh, so I think the last time we talked about the meaning of life and it was, it was kind of about winning. Of course. Uh, I don't think I've talked to you about love much, whether romantic or just love for the common humanity amongst us all. What role has love played in your life in this, in this quest for winning, where does love fit in? Well, the word love, I think means, uh, several different things. There's, uh, love in the sense of maybe I could just say there's like love in the sense of opiates and love in the sense of, uh, oxytocin and then love in the sense of maybe like a love for math. I don't think fits into either of those first two paradigms. Uh, so each of those, have they, uh, have they, have they given something to you in your life? I'm not that big of a fan of the first two. Um, why? For the same reason I'm not a fan of, you know, for the same reason I don't do opiates and don't take ecstasy. Right? And there were times, look, I've tried both. Um, I like opiates way more than I like ecstasy. Uh, but they're not the ethical life is the productive life. So maybe that's my problem with, with, with those. And then like, yeah, a sense of, I don't know, like abstract love for humanity. I mean, the abstract love for humanity. I'm like, yeah, I've always felt that. And I guess it's hard for me to imagine not feeling it. And maybe there's people who don't and I don't know. Yeah. That's just like a background thing that's there. I mean, since we brought up drugs, let me ask you, this is becoming more and more a part of my life. I've been talking to a few researchers that are working on psychedelics. I've eaten shrooms a couple of times and it was fascinating to me that like the mind can go like, just fascinating. The mind can go to places I didn't imagine it could go. And I was very friendly and positive and exciting and everything was kind of hilarious in the place. Wherever my mind went, that's where I went is, uh, what do you think about psychedelics? Do you think they have? What do you think the mind goes? Have you done psychedelics? Where do you think the mind goes? Is there something useful to learn about the places it goes? Once you come back? You know, I find it interesting that this idea that psychedelics have something to teach is almost unique to psychedelics, right? People don't argue this about amphetamines. And I'm not really sure why. I think all of the drugs have lessons to teach. I think there's things to learn from opiates. I think there's things to learn from amphetamines. I think there's things to learn from psychedelics, things to learn from marijuana. But also at the same time, recognize that I don't think you're learning things about the world. I think you're learning things about yourself. Yes. Um, and you know, what's the, even, it might've even been, uh, might've even been a Timothy Leary quote. I don't know if it's a monomist quote, but the idea is basically like, you know, everybody should look behind the door, but then once you've seen behind the door, you don't need to keep going back. Um, so I mean, and that's my thoughts on all real drug use too. So maybe for caffeine. It's a little experience that, uh, it's good to have, but. Oh yeah. No, I mean, yeah, I guess. Yeah. Psychedelics have definitely, um, so you're a fan of new experiences, I suppose. Yes. And it contains a little, especially the first few times it contains some lessons that can be picked up. Yeah. And I'll, I'll, I'll revisit psychedelics maybe once a year. Um, usually small, smaller doses. Maybe they turn up the learning rate of your brain. I've heard that like that. Yeah, that's cool. Big learning rates have pros and cons. Last question. And this is a little weird one, but you've called yourself crazy in the past. Uh, first of all, honestly, I think. On a scale of one to 10, how crazy would you say are you? Oh, I mean, it depends how you, you know, when you compare me to Elon Musk and Anthony Levandowski, not so crazy. So like, like a seven. Let's go with six. Six, six, six. What, uh, I like seven, seven's a good number. Seven. All right. Well, yeah, I'm sure day by day changes, right? So, but you're in that, in that area, what, uh, in thinking about that, what do you think is the role of madness? Is that a feature or a bug if you were to dissect your brain? So okay. From like a, like mental health lens on crazy, I'm not sure I really believe in that. I'm not sure I really believe in like a lot of that stuff, right? This concept of, okay, you know, when you get over to like, like, like, like hardcore bipolar and schizophrenia, these things are clearly real, somewhat biological. And then over here on the spectrum, you have like ADD and oppositional defiance disorder. And these things that are like, wait, this is normal spectrum human behavior. Like this isn't, you know, where's the, the line here and why is this like a problem? So there's this whole, you know, the neurodiversity of humanity is huge. Like people think I'm always on drugs. People are always saying this to me on my streams and like guys, you know, like I'm real open with my drug use. I'd tell you if I was on drugs and, oh yeah, I had like a cup of coffee this morning, but other than that, this is just me. You're witnessing my brain in action. So the word madness doesn't even make sense in the rich neurodiversity of humans. I think it makes sense, but only for like some insane extremes. But if you are actually like visibly hallucinating, you know, that's okay. But there is the kind of spectrum on which you stand out. Like that, that's a, like if I were to look, you know, at decorations on a Christmas tree or something like that, like if you were a decoration out, that would catch my eye. Like that thing is sparkly. Whatever the hell that thing is. There's something to that. Just like refusing to be boring or maybe boring is the wrong word, but to, yeah, I mean, be willing to sparkle, you know? It's like somewhat constructed. I mean, I am who I choose to be. I'm going to say things as true as I can see them. I'm not going to lie. But that's a really important feature in itself. So like whatever the neurodiversity of your, whatever your brain is, not putting constraints on it that force it to fit into the mold of what society is like defines what you're supposed to be. So you're one of the specimens that doesn't mind being yourself. Being right is super important, except at the expense of being wrong. Without breaking that apart, I think it's a beautiful way to end it. George, you're one of the most special humans I know. It's truly an honor to talk to you. Thanks so much for doing it. Thank you for having me. Thanks for listening to this conversation with George Hatz. And thank you to our sponsors, Four Sigmatic, which is the maker of delicious mushroom coffee, Decoding Digital, which is a tech podcast that I listen to and enjoy, and ExpressVPN, which is the VPN I've used for many years. Please check out these sponsors in the description to get a discount and to support this podcast. If you enjoy this thing, subscribe on YouTube, review it with five stars on Apple Podcast, follow on Spotify, support on Patreon, or connect with me on Twitter at Lex Friedman. And now, let me leave you with some words from the great and powerful Linus Torvald. Talk is cheap. Show me the code. Thank you for listening and hope to see you next time.
 The following is a conversation with George Hotz, AKA GeoHot, his second time on the podcast.
 He's the founder of Kama AI, an autonomous and semi-autonomous vehicle technology company
 that seeks to be, to Tesla, autopilot what Android is to the iOS.
 They sell the Kama 2 device for $1,000 that when installed in many of their supported
 cars can keep the vehicle centered in the lane even when there are no lane markings.
 It includes driver sensing that ensures that the driver's eyes are on the road.
 As you may know, I'm a big fan of driver sensing.
 I do believe Tesla Autopilot and others should definitely include it in their sensor suite.
 Also, I'm a fan of Android and a big fan of George for many reasons, including his
 nonlinear out of the box brilliance and the fact that he's a superstar programmer of a
 very different style than myself.
 Styles make fights and styles make conversations.
 So I really enjoyed this chat and I'm sure we'll talk many more times on this podcast.
 Quick mention of each sponsor followed by some thoughts related to the episode.
 First is FourSigmatic, the maker of delicious mushroom coffee.
 Second is Decoding Digital, a podcast on tech and entrepreneurship that I listen to and
 enjoy.
 And finally, ExpressVPN, the VPN I've used for many years to protect my privacy on the
 internet.
 Please check out the sponsors in the description to get a discount and to support this podcast.
 As a side note, let me say that my work at MIT on autonomous and semi-autonomous vehicles
 led me to study the human side of autonomy enough to understand that it's a beautifully
 complicated and interesting problem space, much richer than what can be studied in the
 lab.
 In that sense, the data that CamaAI, Tesla Autopilot, and perhaps others like Cadillac
 Supercruiser are collecting gives us a chance to understand how we can design safe semi-autonomous
 vehicles for real human beings in real world conditions.
 I think this requires bold innovation and a serious exploration of the first principles
 of the driving task itself.
 If you enjoyed this thing, subscribe on YouTube, review it with Five Stars and Apple Podcasts,
 follow on Spotify, support on Patreon, or connect with me on Twitter at Lex Friedman.
 And now, here's my conversation with George Hotz.
 So last time we started talking about the simulation, this time let me ask you, do you
 think there's intelligent life out there in the universe?
 I've always maintained my answer to the Fermi paradox.
 I think there has been intelligent life elsewhere in the universe.
 So intelligent civilizations existed, but they've blown themselves up.
 So your general intuition is that intelligent civilizations quickly, like there's that parameter
 in the Drake equation.
 Your sense is they don't last very long.
 How are we doing on that?
 Like, have we lasted pretty good?
 Oh no.
 How we do?
 Oh yeah.
 I mean, not quite yet.
 Well, wait, it's like as you'd call it, the IQ required to destroy the world falls by
 one point every year.
 Okay.
 So technology democratizes the destruction of the world.
 When can a meme destroy the world?
 It kind of is already, right?
 Somewhat.
 I don't think we've seen anywhere near the worst of it yet.
 The world's going to get weird.
 Well maybe a meme can save the world.
 You thought about that?
 The meme Lord Elon Musk fighting on the side of good versus the meme Lord of the darkness,
 which is not saying anything bad about Donald Trump, but he is the Lord of the meme on the
 dark side.
 He's a Darth Vader of memes.
 I think in every fairy tale, they always end it with, and they lived happily ever after.
 And I'm like, please tell me more about this happily ever after.
 I've heard 50% of marriages end in divorce.
 Why doesn't your marriage end up there?
 You can't just say happily ever after.
 So the thing about destruction is it's over after the destruction.
 We have to do everything right in order to avoid it.
 And one thing wrong, I mean, actually this is what I really like about cryptography.
 Cryptography it seems like we live in a world where the defense wins versus like nuclear
 weapons, the opposite is true.
 It is much easier to build a warhead that splits into a hundred little warheads than
 to build something that can take out a hundred little warheads.
 The offense has the advantage there.
 So maybe our future is in crypto.
 So cryptography, right.
 The Goliath is the defense.
 And then all the different hackers are the Davids.
 And that equation is flipped for nuclear war.
 Cause there's so many, like one nuclear weapon destroys everything essentially.
 Yeah.
 And it is much easier to attack with a nuclear weapon than it is to like the technology required
 to intercept and destroy a rocket is much more complicated than the technology required
 to just, you know, orbital trajectory, send a rocket to somebody.
 So okay.
 Your intuition that the, there were intelligent civilizations out there, but it's very possible
 that they're no longer there.
 That's kind of a sad picture.
 They enter some steady state.
 They all wirehead themselves.
 What's wirehead?
 Stimulate their pleasure centers and just, you know, live forever in this kind of stasis.
 They become, well, I mean, I think the reason I believe this is because where are they?
 If there's some reason they stopped expanding, because otherwise they would have taken over
 the universe.
 The universe isn't that big, or at least, you know, let's just talk about the galaxy,
 right?
 70,000 light years across.
 I took that number from Star Trek Voyager.
 I don't know how true it is, but yeah, that's not big.
 70,000 light years is nothing.
 For some possible technology that you can imagine that could leverage like wormholes
 or something like that.
 You don't even need wormholes.
 Just a von Neumann probe is enough.
 A von Neumann probe and a million years of sublight travel, and you'd have taken over
 the whole universe.
 That clearly didn't happen.
 So something stopped it.
 So you mean if you, right, for like a few million years, if you sent out probes that
 travel close, what's sublight?
 Meaning close to the speed of light?
 Let's say 0.1C.
 And it just spreads.
 Interesting.
 Actually, that's an interesting calculation.
 Huh.
 So what makes you think that we'd be able to communicate with them?
 Like, yeah, why do you think we would be able to comprehend intelligent lives that are out
 there?
 Like, even if they were among us kind of thing, like, or even just flying around?
 Well, I mean, that's possible.
 It's possible that there is some sort of prime directive.
 That'd be a really cool universe to live in.
 And there's some reason they're not making themselves visible to us.
 But it makes sense that they would use the same, well, at least the same entropy.
 Well, you're implying the same laws of physics.
 I don't know what you mean by entropy in this case.
 Oh, yeah.
 I mean, if entropy is the scarce resource in the universe.
 So what do you think about, like, Stephen Wolfram and everything is a computation.
 And then what if they are traveling through this world of computation?
 So if you think of the universe as just information processing, then what you're referring to with
 entropy and then these pockets of interesting complex computations swimming around, how
 do we know they're not already here?
 How do we know that this, like all the different amazing things that are full of mystery on
 Earth are just like little footprints of intelligence from light years away?
 Maybe.
 I mean, I tend to think that as civilizations expand, they use more and more energy.
 And you can never overcome the problem of waste heat.
 So where is there waste heat?
 So we'd be able to, with our crude methods, be able to see, like, there's a whole lot
 of energy here.
 But it could be something we're not.
 I mean, we don't understand dark energy, right?
 Dark matter.
 It could be just stuff we don't understand at all.
 Or they can have a fundamentally different physics, you know, like that we just don't
 even comprehend.
 Well, I think, OK, I mean, it depends how far out you want to go.
 I don't think physics is very different on the other side of the galaxy.
 I would suspect that they have, I mean, if they're in our universe, they have the same
 physics.
 Well, yeah, that's the assumption we have.
 But there could be like super trippy things like, like our cognition only gets to a slice
 and all the possible instruments that we can design only get to a particular slice of the
 universe.
 And there's something much like weirder.
 Maybe we can try a thought experiment.
 Would people from the past be able to detect the remnants of our, would be able to detect
 our modern civilization?
 And I think the answer is obviously yes.
 You mean past from a hundred years ago?
 Well, let's even go back further.
 Let's go to a million years ago.
 The humans who were lying around in the desert probably didn't even have, maybe they just
 barely had fire.
 They would understand if a 747 flew overhead.
 In this vicinity, but not if a 747 flew on Mars, because they wouldn't be able to see
 far because we're not actually communicating that well with the rest of the universe.
 We're doing okay.
 Just sending out random like fifties tracks of music.
 True.
 And yeah, I mean, they'd have to, you know, the, we've only been broadcasting radio waves
 for 150 years and well, there's your light cone.
 So yeah.
 Okay.
 What do you make about all the, I recently came across this.
 When I talked to David's Fravor, I don't know if you caught what the, the videos that Pentagon
 released and the New York times reporting of the UFO sightings.
 So I kind of looked into it, quote unquote, and there's actually been like hundreds of
 thousands of UFO sightings, right?
 And a lot of it, you can explain away in different kinds of ways.
 So one is it could be interesting physical phenomena to it could be people wanting to
 believe.
 And therefore they conjure up a lot of different things that just, you know, when you see different
 kinds of lights and basic physics phenomena, and then you just conjure up ideas of possible
 out there, mysterious worlds.
 But you know, it's also possible.
 Like you have a case of, um, David Fravor who is a Navy pilot who's, you know, a, as
 legit as a guest in terms of humans who are able to perceive things in the environment
 and make conclusions, whether those things that are threat or not.
 And he and several other pilots saw a thing.
 I don't know if you followed this, but they saw a thing that they've since then called
 tech talk that moved in all kinds of weird ways.
 They don't know what it is.
 It could be technology developed by, by the United States and they're just not aware of
 it.
 And the surface level from the Navy, right?
 It could be different kinds of lighting technology or drone technology, all that kind of stuff.
 It could be the Russians and the Chinese, all that kind of stuff.
 And of course their mind, our mind can also venture into the possibility that it's from
 another world.
 Have you looked into this at all?
 What do you think about it?
 I think all the news is a Psyop.
 I think that the most plausible.
 Nothing is real.
 Yeah.
 I listened to the, I think it was Bob Lazar on Joe Rogan and like, I believe everything
 this guy is saying.
 And then I think that it's probably just some like MKUltra kind of thing, you know?
 What do you mean?
 Like they, they, they, you know, they made some weird thing and they called it an alien
 spaceship, you know?
 It was just to like stimulate young physicists minds and we'll tell them it's alien technology
 and we'll see what they come up with, right?
 Do you find any conspiracy theories compelling?
 Like have you pulled at the string of the, of the rich complex world of conspiracy theories
 that's out there?
 I think that I've heard a conspiracy theory that conspiracy theories were invented by
 the CIA in the sixties to discredit true things.
 Yeah.
 So you know, you can go to ridiculous conspiracy theories like flat earth and pizza gate and
 you know, these things are almost to hide like conspiracy theories that like, you know,
 remember when the Chinese like locked up the doctors who discovered coronavirus?
 Like I tell people this and I'm like, no, no, no, that's not a conspiracy theory.
 That actually happened.
 Do you remember the time that the money used to be backed by gold and now it's backed by
 nothing?
 This is not a conspiracy theory.
 This actually happened.
 So that's one of my worries today with the idea of fake news is that when nothing is
 real, then like you dilute the possibility of anything being true by conjuring up all
 kinds of conspiracy theories and then you don't know what to believe.
 And then like the idea of truth of objectivity is lost completely.
 Everybody has their own truth.
 So you're used to control information by censoring it.
 And then the internet happened and governments are like, oh shit, we can't censor things
 anymore.
 I know what we'll do.
 You know, it's the old story of the story of like tying a flag with a leprechaun tells
 you his gold is buried and you tie one flag and you make the leprechaun swear to not remove
 the flag and you come back to the field later with a shovel and there's flags everywhere.
 That's one way to maintain privacy, right?
 It's like in order to protect the contents of this conversation, for example, we could
 just generate like millions of deep fake conversations where you and I talk and say random things.
 So this is just one of them and nobody knows which one was the real one.
 This could be fake right now.
 Classics, steganography technique.
 Okay.
 Another absurd question about intelligent life because you know, you're, you're an incredible
 programmer outside of everything else.
 We'll talk about just as a programmer.
 Do you think intelligent beings out there, the civilizations that were out there had
 computers and programming?
 Did they, do we naturally have to develop something where we engineer machines and are
 able to encode both knowledge into those machines and instructions that process that knowledge,
 process that information to make decisions and actions and so on.
 Would those programming languages, if you think they exist, be at all similar to anything
 we've developed?
 So I don't see that much of a difference between quote unquote natural languages and programming
 languages.
 I think there's so many similarities.
 So when asked the question, what do alien languages look like?
 I imagine they're not all that dissimilar from ours.
 And I think translating in and out of them, uh, wouldn't be that crazy.
 It's difficult to compile like DNA to Python and then to see, I mean, there is a little
 bit of a gap in the kind of languages we use for, for, uh, touring machines and the kind
 of languages nature seems to use a little bit.
 Maybe that's just, we just haven't, we haven't understood the kind of language that nature
 uses well yet.
 DNA is a CAD model.
 It's not quite a programming language.
 It has no sort of a serial, uh, execution.
 It's not quite a, uh, yeah, it's a, it's a CAD model.
 Um, so I think in that sense, we actually completely understand it.
 The problem is, um, you know, uh, well, simulating on these CAD models, I played with it a bit
 this year is, is super, uh, computationally intensive.
 If you want to go down to like the molecular level, um, where you need to go to see a lot
 of these phenomenon like protein folding.
 Um, so yeah, it's not that it's, it's not, it's not that we don't understand it.
 It just requires a whole lot of compute to kind of compile it.
 For our human minds, it's inefficient both for the pro for the data representation and
 for the programming.
 Yeah.
 It runs well on raw nature.
 It runs well on raw nature.
 And when we try to build, uh, emulators or simulators for that, uh, well, then mad slow
 and I've tried it.
 It runs in that.
 Yeah.
 You've commented elsewhere.
 I don't remember where that, uh, one of the problems is simulating nature is tough.
 And if you want to sort of, uh, deploy a prototype, I forgot how you, you put it, but it made
 me laugh, but animals are humans who would need to be involved in, in order to, in order
 to try to run some prototype code on, um, like if we're talking about COVID and viruses
 and so on, if you were tried to engineer some kind of defense mechanisms, like a vaccine
 against COVID or all that kind of stuff that doing any kind of experimentation, like you
 can with like autonomous vehicles would be very technically cost, technically and ethically
 costly.
 I'm not sure about that.
 I think you can do tons of, uh, crazy biology and test tubes.
 I think my bigger complaint is more, oh, the tools are so bad.
 Like literally you mean like, like libraries and I'm not pipetting shit.
 Like you're handing me a, I gotta no, no, no, no, there has to be some like automating
 stuff and like the, yeah, but human biology is messy.
 Like it seems like, look at those Doranos videos.
 They were joke.
 It's like, it's like a little gantry.
 It's like a little XY gantry high school science project with the pipette.
 I'm like, really?
 Got to be something better.
 You can't build like nice microfluidics and I can program the, you know, computation to
 bio interface.
 I mean, this is going to happen, but like right now, if you are asking me to pipette
 50 milliliters of solution, I'm out.
 This is so crude.
 Yeah.
 So let's get all the crazy out of the way.
 So a bunch of people asked me since we talked about the simulation last time, we talked
 about hacking the simulation.
 Do you have any updates, any insights about how we might be able to go about hacking simulation
 if we indeed do live in a simulation?
 I think a lot of people misinterpreted the point of that South by talk.
 The point of the South by talk was not literally to hack the simulation.
 I think that this is an idea is literally just, I think theoretical physics.
 I think that's the whole, you know, the whole goal, right?
 You want your grand unified theory, but then, okay, build a grand unified theory, search
 for exploits, right?
 I think we're nowhere near actually there yet.
 My hope with that was just more to like, are you people kidding me with the things you
 spend time thinking about?
 Do you understand like kind of how small you are?
 You are, you are bytes and God's computer.
 Really?
 And the things that people get worked up about and you know.
 So basically it was more a message of we should humble ourselves that we get to like, what
 are we humans in this bytecode?
 Yeah.
 And not just humble ourselves, but like, like I'm not trying to like make people feel guilty
 or anything like that.
 I'm trying to say like, literally look at what you are spending time on, right?
 What are you referring to?
 You're referring to the Kardashians?
 What are we talking about?
 I'm referring to, no, the Kardashians.
 See, everyone knows that's kind of fun.
 I'm referring more to like the economy, you know, this idea that we got to up our stock
 price like, or, or what is, what is the goal function of humanity?
 You don't like the game of capitalism?
 Like you don't like the games we've constructed for ourselves as humans?
 I'm a big fan of capitalism.
 I don't think that's really the game we're playing right now.
 I think we're playing a different game where the rules are rigged.
 Okay.
 Which games are interesting to you that we humans have constructed and which aren't,
 which are productive and which are not.
 Actually, maybe that's the real point of the, of the talk.
 It's like, stop playing these fake human games.
 There's a real game here.
 We can play the real game.
 The real game is, you know, nature wrote the rules.
 This is a real game.
 There still is a game to play.
 But if you look at, sorry to interrupt, but I don't know if you've seen the Instagram
 account nature is metal.
 The game that nature seems to be playing is a lot, a lot more cruel that we humans want
 to put up with, or at least we see it as cruel.
 It's like the bigger thing eats the smaller thing and does it to impress another big thing
 so it can mate with that thing.
 And that's it.
 That seems to be the entirety of it.
 Well, there's no art, there's no music.
 There's no comma AI.
 There's no comma one, no comma two, no George Hots with his brilliant talks at South by
 Southwest.
 See, I disagree though.
 I disagree that this is what nature is.
 I think nature just provided basically a open world MMORPG and you know, here it's open
 world.
 I mean, if that's the game you want to play, you can play that game.
 But that isn't that, isn't that beautiful?
 I know if you played Diablo, they used to have a, I think cow level where it's,
 so everybody will go just, they figured out this like the best way to gain like experience
 points is to just slaughter cows over and over and over.
 And so they figured out this little sub game within the bigger game that this is the most
 efficient way to get experience points.
 And everybody somehow agreed that getting experience points in RPG context, where you
 always want to be getting more stuff, more skills, more levels, keep advancing.
 That seems to be good.
 So might as well spend sacrifice actual enjoyment of playing a game, exploring a world and spending
 like hundreds of hours of your time in college.
 I mean, the number of hours I spent in cow level, I'm not like the most impressive person
 because people have probably thousands of hours there, but it's ridiculous.
 So that's a little absurd game that brought me joy in some weird dopamine drug kind of
 way.
 So you don't like those games.
 You don't think that's us humans failing the nature.
 I think so.
 And that was the point of the talk.
 Yeah.
 So how do we hack it then?
 Well, I want to live forever and I want to live forever.
 And this is the goal.
 Well, that's a game against nature.
 Yeah.
 So, immortality is the good objective function to you.
 I mean, start there and then you can do whatever else you want because you got a long time.
 What if immortality makes the game just totally not fun?
 I mean, like, why do you assume immortality is somehow a good objective function?
 It's not immortality that I want.
 A true immortality where I could not die.
 I would prefer what we have right now.
 But I want to choose my own death.
 Of course.
 I don't want nature to decide when I die, I'm going to win.
 I'm going to be you.
 And then at some point, if you choose commit suicide, like, how long do you think you'd
 live?
 Until I get bored.
 See, I don't think people like in like brilliant people like you that really ponder living
 a long time are really considering how a meaningless life becomes.
 Well, I want to know everything and then I'm ready to die.
 As long as there's...
 Yeah, but why do you want...
 Isn't it possible that you want to know everything because it's finite?
 Like, the reason you want to know quote unquote everything is because you don't have enough
 time to know everything.
 And once you have unlimited time, then you realize like, why do anything?
 Like why learn anything?
 I want to know everything and then I'm ready to die.
 So you have...
 Yeah.
 Well, it's not a...
 It's a terminal value.
 It's not in service of anything else.
 I'm conscious of the possibility.
 This is not a certainty, but the possibility of that engine of curiosity that you're speaking
 to is actually a symptom of the finiteness of life.
 Like, without that finiteness, your curiosity would vanish like a morning fog.
 All right, cool.
 Then...
 Wachowski talked about love like that.
 Then let me solve immortality and let me change the thing in my brain that reminds me of the
 fact that I'm immortal tells me that life is finite shit.
 Maybe I'll have it tell me that life ends next week.
 Right?
 I'm okay with some self manipulation like that.
 I'm okay with deceiving myself.
 Oh, Rika, changing the code.
 If that's the problem, right?
 If the problem is that I will no longer have that curiosity, I'd like to have backup copies
 of myself, which I check in with occasionally to make sure they're okay with the trajectory
 and they can kind of override it.
 Maybe a nice like, I think of like those wave nets, those like logarithmic go back to the
 copy.
 But sometimes it's not reversible.
 Like I've done this with video games.
 Once you figure out the cheat code or like you look up how to cheat old school, like
 single player, it ruins the game for you.
 Absolutely.
 I know that feeling.
 But again, that just means our brain manipulation technology is not good enough yet.
 Remove that cheat code from your brain.
 What if we call...
 So it's also possible that if we figure out immortality, that all of us will kill ourselves
 before we advance far enough to be able to revert the change.
 I'm not killing myself till I know everything.
 That's what you say now because your life is finite.
 I think yes, self-modifying systems comes up with all these hairy complexities.
 Can I promise that I'll do it perfectly?
 No, but I think I can put good safety structures in place.
 That talk in your thinking here is not literally referring to a simulation in that our universe
 is a kind of computer program running in a computer.
 That's more of a thought experiment.
 Do you also think of the potential of the sort of Bostrom, Elon Musk, and others that
 talk about an actual program that simulates our universe?
 Oh, I don't doubt that we're in a simulation.
 I just think that it's not quite that important.
 I mean, I'm interested only in simulation theory as far as it gives me power over nature.
 If it's totally unfalsifiable, then who cares?
 I mean, what do you think that experiment would look like?
 Somebody on Twitter asked, ask George what signs we would look for to know whether or
 not we're in the simulation, which is exactly what you're asking.
 The step that precedes the step of knowing how to get more power from this knowledge
 is to get an indication that there's some power to be gained.
 So, get an indication that you can discover and exploit cracks in the simulation or it
 doesn't have to be in the physics of the universe.
 Show me, I mean, like a memory leak would be cool.
 Some scrying technology, you know?
 What kind of technology?
 Scrying?
 What's that?
 Oh, that's a weird...
 Scrying is the paranormal ability to like remote viewing, like being able to see somewhere
 where you're not.
 So I don't think you can do it by chanting in a room, but if we could find...
 It's a memory leak, basically.
 It's a memory leak.
 Yeah, you're able to access parts you're not supposed to and thereby discover a shortcut.
 Memory leak means the other thing as well, but I mean like, yeah, like an ability to
 read arbitrary memory.
 And that one's not that horrifying.
 The right ones start to be horrifying.
 Read, right.
 So the reading is not the problem.
 Yeah, it's like Heartfleet for the universe.
 Oh boy, the writing is a big, big problem.
 It's a big problem.
 It's the moment you can write anything, even if it's just random noise.
 That's terrifying.
 I mean, even without that, like even some of the nanotech stuff that's coming, I think
 is...
 I don't know if you're paying attention, but actually Eric Weinstein came out with the
 theory of everything.
 I mean, that came out.
 He's been working on a theory of everything in the physics world called geometric unity.
 And then for me, from computer science person like you, Stephen Wolfram's theory of everything,
 of like hypergraphs is super interesting and beautiful, but that not from a physics perspective,
 but from a computational perspective.
 I don't know.
 Have you paid attention to any of that?
 So again, like what would make me pay attention and like why I hate string theory is, okay,
 make a testable prediction, right?
 I'm only interested in...
 I'm not interested in theories for their intrinsic beauty.
 I'm interested in theories that give me power over the universe.
 So if these theories do, I'm very interested.
 Can I just say how beautiful that is?
 Because a lot of physicists say, I'm interested in experimental validation and they skip out
 the part where they say to give me more power in the universe.
 I just love the clarity of that.
 I want 100 gigahertz processors.
 I want transistors that are smaller than atoms.
 I want like power.
 That's true.
 And that's where people from aliens to this kind of technology where people are worried
 that governments like who owns that power?
 Is it George Hotz?
 Is it thousands of distributed hackers across the world?
 Is it governments?
 Is it Mark Zuckerberg?
 There's a lot of people that...
 I don't know if anyone trusts any one individual with power.
 So they're always worried.
 It's the beauty of blockchains.
 That's the beauty of blockchains, which we'll talk about.
 On Twitter, somebody pointed me to a story.
 A bunch of people pointed me to a story a few months ago where you went into a restaurant
 in New York, and you can correct me if any of this is wrong, and ran into a bunch of
 folks from a crypto company who are trying to scale up Ethereum.
 And they had a technical deadline related to a solidity to OVM compiler.
 So these are all Ethereum technologies.
 So you stepped in.
 They recognized you, pulled you aside, explained their problem, and you stepped in and helped
 them solve the problem, thereby creating legend status story.
 So can you tell me the story in a little more detail?
 It seems kind of incredible.
 Did this happen?
 Yeah, yeah, it's a true story.
 It's a true story.
 I mean, they wrote a very flattering account of it.
 So the company is called Optimism, spin-off of Plasma.
 They're trying to build L2 solutions on Ethereum.
 So right now, every Ethereum node has to run every transaction on the Ethereum network.
 And this kind of doesn't scale, right?
 Because if you have N computers, well, if that becomes two N computers, you actually
 still get the same amount of compute.
 This is like O of 1 scaling, because they all have to run it.
 Okay, fine, you get more blockchain security, but blockchain is already so secure.
 Can we trade some of that off for speed?
 So that's kind of what these L2 solutions are.
 They built this thing which kind of sandbox for Ethereum contracts, so they can run it
 in this L2 world and it can't do certain things in L world, in L1.
 Can I ask you for some definitions?
 What's L2?
 Oh, L2 is layer 2.
 So L1 is like the base Ethereum chain, and then layer 2 is like a computational layer
 that runs elsewhere, but still is kind of secured by layer 1.
 And I'm sure a lot of people know, but Ethereum is a cryptocurrency, probably one of the most
 popular cryptocurrencies, second to Bitcoin, and a lot of interesting technological innovations
 there.
 Maybe you could also slip in whenever you talk about this, any things that are exciting
 to you in the Ethereum space.
 And why Ethereum?
 Well, I mean, Bitcoin is not tearing complete.
 Ethereum is not technically tearing complete with the gas limit, but close enough.
 With the gas limit?
 What's the gas limit?
 Resources?
 Yeah, I mean, no computer is actually tearing complete.
 Right.
 You're going to find out RAM, you know?
 I can actually solve the whole thing.
 What's the word gas limit?
 You have so many brilliant words.
 I'm not even going to ask.
 No, that's not my word.
 That's Ethereum's word.
 Gas limit? Ethereum, you have to spend gas per instruction.
 So like different opcodes use different amounts of gas and you buy gas with ether to prevent
 people from basically DDoSing the network.
 So Bitcoin is proof of work.
 And then what's Ethereum?
 It's also proof of work.
 They're working on some proof of stake Ethereum 2.0 stuff.
 But right now it's proof of work.
 It uses a different hash function from Bitcoin that's more ASIC resistance because you need
 RAM.
 So we're all talking about Ethereum 1.0.
 So what were they trying to do to scale this whole process?
 So they were like, well, if we could run contracts elsewhere and then only save the results of
 that computation, you know, well, we don't actually have to do the compute on the chain.
 We can do the compute off chain and just post what the results are.
 Now, the problem with that is, well, somebody could lie about what the results are.
 So you need a resolution mechanism.
 And the resolution mechanism can be really expensive because, you know, you just have
 to make sure that like the person who is saying, look, I swear that this is the real computation.
 I'm staking $10,000 on that fact.
 And if you prove it wrong, yeah, it might cost you $3,000 in gas fees to prove wrong,
 but you'll get the $10,000 bounty.
 So you can secure using those kinds of systems.
 So it's effectively a sandbox which runs contracts.
 And like any kind of normal sandbox, you have to like replace syscalls with, you know, calls
 into the hypervisor.
 Sandbox, syscalls, hypervisor.
 What do these things mean?
 As long as it's interesting to talk about.
 Yeah.
 I mean, you can take like the Chrome sandbox is maybe the one to think about, right?
 So the Chrome process that's doing a rendering can't, for example, read a file from the file
 system.
 Yeah.
 So if someone tries to make an open syscall in Linux, the open syscall, you can't make
 an open syscall.
 No, no, no.
 You have to request from the kind of hypervisor process or like, I don't know what's called
 in Chrome, but the, hey, could you open this file for me?
 And then it does all these checks and then it passes the file handle back in if it's
 approved.
 Got it.
 So that's, yeah.
 So what's the, in the context of Ethereum, what are the boundaries of the sandbox that
 we're talking about?
 Well, like one of the calls that you actually reading and writing any state to the Ethereum
 contract or to the Ethereum blockchain.
 Writing state is one of those calls that you're going to have to sandbox in layer two, because
 if you let layer two just arbitrarily write to the Ethereum blockchain.
 So layer two is really sitting on top of layer one.
 So you're going to have a lot of different kinds of ideas that you can play with.
 And they're all, they're not fundamentally changing the source code level of Ethereum.
 Well, you have to replace a bunch of calls with calls into the hypervisor.
 So instead of doing the syscall directly, you replace it with a call to the hypervisor.
 So originally they were doing this by first running the, so Solidity is the language that
 most Ethereum contracts are written in.
 It compiles to a bytecode.
 And then they wrote this thing they call the transpiler.
 And the transpiler took the bytecode and it transpiled it into OVM safe bytecode.
 Basically bytecode that didn't make any of those restricted syscalls and added the calls
 to the hypervisor.
 This transpiler was a 3000 line mess.
 And it's hard to do.
 It's hard to do if you're trying to do it like that, because you have to kind of like
 deconstruct the bytecode, change things about it and then reconstruct it.
 And I mean, as soon as I hear this, I'm like, well, why don't you just change the compiler?
 Right?
 Why not the first place you build the bytecode, just do it in the compiler.
 So yeah, you know, I asked them how much they wanted it.
 Of course, measured in dollars and a million, well, okay.
 And yeah.
 And you wrote the compiler.
 Yeah.
 I modified, I wrote a 300 line diff to the compiler.
 It's open source.
 You can look at it.
 Yeah.
 Yeah.
 I looked at the code last night.
 It's cute.
 Yeah, exactly.
 Cute is a good word for it.
 And it's C++.
 So when asked how you were able to do it, you said you just got to think and then do it
 right.
 So can you break that apart a little bit?
 What's your process of one thinking and two doing it right?
 You know, they, they, they, the people I was working for amused that I said that it doesn't
 really mean anything.
 Okay.
 I mean, is there some deep, profound insights to draw from like how you problem solve from
 that?
 This is always what I say.
 I'm like, do you want to be a good programmer?
 Do it for 20 years.
 Yeah.
 There's no shortcuts.
 No.
 What are your thoughts on crypto in general?
 So what, what parts technically or philosophically do you find especially beautiful maybe?
 Oh, I'm, I'm extremely bullish on crypto long-term, not any specific crypto project, but this
 idea of, well, two ideas.
 One the Nakamoto consensus algorithm is I think one of the greatest innovations of the 21st
 century.
 This idea that people can reach consensus.
 You can reach a group consensus using a relatively straightforward algorithm is wild.
 And like, I mean, Satoshi Nakamoto, people always ask me who I look up to.
 It's like, whoever that is.
 Who do you think it is?
 Elon Musk?
 Is it you?
 It is definitely not me and I do not think it's Elon Musk, but yeah, this idea of our
 groups reaching consensus in a decentralized yet formulaic way is one extremely powerful
 idea from crypto.
 Maybe the second idea is this idea of smart contracts.
 When you write a contract between two parties, any contract, this contract, if there are
 disputes it's interpreted by lawyers.
 Lawyers are just really shitty overpaid interpreters.
 Imagine you had, let's talk about them in terms of like, let's compare a lawyer to Python.
 Right?
 So lawyer, well, okay.
 That's brilliant.
 I never thought of it that way.
 It's hilarious.
 So Python, I'm paying even 10 cents an hour.
 I'll use the nice Azure machine.
 I can run Python for 10 cents an hour.
 Lawyers cost $1,000 an hour.
 So Python is 10,000X better on that axis.
 Lawyers don't always return the same answer.
 Python almost always does.
 Cost.
 Yeah.
 I mean, just cost, reliability, everything about Python is so much better than lawyers.
 So if you can make smart contracts, this whole concept of code is law.
 I love, and I would love to live in a world where everybody accepted that fact.
 So maybe you can talk about what smart contracts are.
 So let's say, let's say, you know, we have a, even something as simple as a safety deposit
 box, right?
 Safety deposit box that holds a million dollars.
 I have a contract with the bank that says two out of these three parties must be present
 to open the safety deposit box and get the money out.
 So that's a contract with the bank and it's only as good as the bank and the lawyers,
 right?
 Let's say, you know, somebody dies and now, oh, we're going to go through a big legal
 dispute about whether, oh, well, was it in the will?
 Was it not in the will?
 What, what?
 It's just so messy and the cost to determine truth is so expensive versus a smart contract,
 which just uses cryptography to check if two out of three keys are present.
 Well, I can look at that and I can have certainty in the answer that it's going to return.
 That's what all businesses want is certainty.
 You know, they say businesses don't care.
 Viacom YouTube, YouTube's like, look, we don't care which way this lawsuit goes.
 Just please tell us so we can have certainty.
 I wonder how many agreements in this book, because we're talking about financial transactions
 only in this case, correct?
 The smart smart contracts.
 Oh, you can go to it.
 You can go to anything.
 You can go.
 You can put a prenup in the theory of blockchain married smart contracts.
 Sorry, divorce lawyer.
 Sorry, you're going to be replaced by Python.
 Okay.
 So that's, uh, so that's, that's another beautiful idea.
 Do you think there's something that's appealing to you about any one specific implementation?
 So if you look 10, 20, 50 years down the line, do you see any like Bitcoin, Ethereum, any
 of the other hundreds of cryptocurrencies winning out?
 Is there like, what's your intuition about the space?
 Are you just sitting back and watching the chaos and look who cares what emerges?
 Oh, I don't, I don't speculate.
 I don't really care.
 I don't really care which one of these projects wins.
 I'm kind of in the Bitcoin as a meme coin camp.
 I mean, why does Bitcoin have value?
 It's technically kind of, you know, not great.
 Like the block size debate.
 When I found out what the block size debate was, I'm like, are you guys kidding?
 What's the block size debate?
 You know what?
 It's really, it's too stupid to even talk about.
 People can look it up, but I'm like, wow.
 You know, Ethereum seems, the governance of Ethereum seems much better.
 I've come around a bit on proof of stake ideas.
 You know, very smart people thinking about some things.
 Yeah.
 You know, governance is interesting.
 It does feel like Vitalik, like it does feel like in open, even in these distributed systems,
 leaders are helpful because they kind of help you drive the mission and the vision and they
 put a face to a project.
 It's a weird thing about us humans.
 Leaders are helpful, like Vitalik.
 Right.
 Yeah.
 Brilliant.
 Leaders are not necessarily.
 Yeah.
 So you think the reason he's the face of Ethereum is because he's a genius.
 That's interesting.
 I mean, that was, it's interesting to think about that we need to create systems in which
 the quote unquote leaders that emerge are the geniuses in the system.
 I mean, that's arguably why the current state of democracy is broken is the people who are
 emerging as the leaders are not the most competent, are not the superstars of the system.
 And it seems like at least for now in the crypto world, oftentimes the leaders are the
 superstars.
 Imagine at the debate, they asked, what's the sixth amendment?
 What are the four fundamental forces in the universe?
 What's the integral of two to the X?
 Yeah.
 I'd love to see those questions asked and that's what I want as our leader.
 It's a little bit of a baseball.
 Yeah.
 I mean, even, oh wow.
 You're hurting my brain.
 It's that my standard was even lower, but I would have loved to see just as basic brilliance.
 Like I've talked to historians.
 There's just these, they're not even like, they don't have a PhD or even an education
 history.
 They're like a Dan Carlin type character who just like, holy shit, how did all this information
 get into your head?
 They're able to just connect Genghis Khan to the entirety of the history of the 20th
 century.
 They know everything about every single battle that happened and they know the game of Thrones
 of the different power plays and all that happened there.
 And they know like the individuals and all the documents involved and they integrate
 that into their regular life.
 It's not like they're ultra history nerds.
 They're just, they know this information.
 That's what competence looks like.
 Yeah.
 Cause I've seen that with programmers too.
 That's what great programmers do.
 But yeah, it would be a, it's really unfortunate that those kinds of people aren't emerging
 as our leaders.
 But for now, at least in the crypto world, that seems to be the case.
 I don't know if that always, you could imagine that in a hundred years, it's not the case.
 Crypto world has one very powerful idea going for it.
 And that's the idea of forks.
 I mean, you know, imagine, we'll use a less controversial example.
 This was actually in my joke app in 2012.
 I was like, Barack Obama, Mitt Romney, let's let them both be president.
 Right, like imagine we could fork America and just let them both be president.
 And then the Americas could compete and you know, people could invest in one, pull their
 liquidity out of one, put it in the other.
 You have this in the crypto world.
 Ethereum forks into Ethereum and Ethereum classic.
 And you can pull your liquidity out of one and put it in another and people vote with
 their dollars, which forks companies should be able to fork.
 I'd love to fork Nvidia, you know.
 Yeah, like different business strategies and then try them out and see, see what works.
 Like even take, yeah, take Comma AI that closes its source and then take one that's open source
 and see what works.
 Take one that's purchased by GM and one that remains Android Renegade and all these different
 versions and see.
 The beauty of Comma AI is someone can actually do that.
 Yeah, please take Comma AI and fork it.
 That's right.
 That's the beauty of open source.
 So you're, I mean, we'll talk about autonomous vehicle space, but it does seem that you're
 really knowledgeable about a lot of different topics.
 So the natural question, a bunch of people ask this, which is how do you keep learning
 new things?
 Do you have like practical advice if you were to introspect, like taking notes, allocate
 time?
 Or do you just mess around and just allow your curiosity to drive?
 I'll write these people a self-help book and I'll charge $67 for it.
 I will, I will write, I will write on the cover of the self-help book.
 All of this advice is completely meaningless.
 You're going to be a sucker and buy this book anyway.
 And the one lesson that I hope they take away from the book is that I can't give you a meaningful
 answer to that.
 That's interesting.
 Let me translate that is you haven't really thought about what it is you do systematically
 because you could reduce it.
 And there's some people, I mean, I've met brilliant people that, I mean, this is really
 clear with athletes.
 Some are just, you know, the best in the world at something and they, they have zero interest
 in writing a self, like a self-help book, but, or how to master this game.
 And then there's some athletes who become great coaches and they love the analysis,
 perhaps the over analysis and you right now, at least at your age, which is an interesting,
 you're in the middle of the battle.
 You're like the warriors that have zero interest in writing books.
 So you're in the middle of the battle.
 So you have, yeah.
 This is, this is a fair point.
 I do think I have a certain aversion to this kind of deliberate intentional way of living
 life.
 Because eventually the hilarity of this, especially since this is recorded, it will have revealed
 beautifully the absurdity when you finally do publish this book.
 And I guarantee you, you will.
 The story of comma AI would be, maybe it'll be a biography written about you.
 That'll be, that'll be better.
 I guess.
 You might be able to learn some cute lessons if you're starting a company like comma AI
 from that book.
 But if you're asking generic questions, like, how do I be good at things?
 Dude, I don't know.
 Well learn.
 I mean, the interesting do them a lot.
 I do them a lot.
 But the interesting thing here is learning things outside of your current trajectory,
 which is what it feels like from an outsider's perspective.
 I mean that, uh, you know, that, I don't know if there's advice on that, but it is an interesting
 curiosity.
 When you become really busy, you're running a company.
 Yeah.
 But like there's a natural inclination and trend, like just the, the, the momentum of
 life carries you into a particular direction of wanting to focus.
 And this kind of dispersion that curiosity can lead to gets harder and harder with time
 because you're, you get really good at certain things and it sucks trying things that you're
 not good at, like trying to figure them out.
 I mean, you do this with your life streams is you're on the fly figuring stuff out.
 You don't mind looking dumb.
 Nah.
 You just figured it out, figured it out pretty quickly.
 Sometimes I try things and I don't figure them out.
 My chest rating is like a 1400 despite putting like a couple hundred hours in is pathetic.
 I mean, to be fair, I know that I could do it better if I did it better, like don't play,
 you know, don't play five minute games, play 15 minute games at least.
 Like I know these things, but it just doesn't.
 It doesn't stick nicely in my knowledge tree.
 All right.
 Let's talk about comma AI.
 What's the mission of the company?
 Let's like look at the biggest picture.
 Oh, I have an exact statement.
 Solve self-driving cars while delivering shippable intermediaries.
 So long-term vision is have fully autonomous vehicles and make sure you're making money
 along the way.
 I think it doesn't really speak to money, but I can talk, I can talk about what solve
 self-driving cars means.
 Solve self-driving cars of course means you're not building a new car.
 You're building a person replacement.
 That person can sit in the driver's seat and drive you anywhere a person can drive with
 a human or better level of safety, speed, quality, comfort.
 And what's the second part of that?
 Delivering shippable intermediaries is well, it's a way to fund the company.
 That's true, but it's also a way to keep us honest.
 If you don't have that, it is very easy with this technology to think you're making progress
 when you're not.
 I've heard it best described on Hacker News as you can set any arbitrary milestone, meet
 that milestone and still be infinitely far away from solving self-driving cars.
 So it's hard to have like real deadlines when you're like Cruz or Waymo when you don't have
 revenue.
 Is that, I mean, is revenue essentially the thing we're talking about here?
 Revenue is, capitalism is based around consent.
 Capitalism the way that you get revenue is a real capitalism, commas in the real capitalism
 camp.
 There's definitely scams out there, but real capitalism is based around consent.
 It's based around this idea that like if we're getting revenue, it's because we're providing
 at least that much value to another person.
 When someone buys a thousand dollar comma two from us, we're providing them at least
 a thousand dollars of value where they wouldn't buy it.
 Right.
 So can you give a whirlwind overview of the products that KamaEI provides like throughout
 its history and today?
 I mean, yeah, the past ones aren't really that interesting.
 It's kind of just been refinement of the same idea.
 The real only product we sell today is the Kama2.
 Which is a piece of hardware with cameras.
 So the Kama2, I mean, you can think about it kind of like a person.
 You know, in future hardware will probably be even more and more person like.
 So it has, you know, eyes, ears, a mouth, a brain, and a way to interface with the car.
 Does it have consciousness?
 Just kidding.
 That was a trick question.
 I don't have consciousness either.
 Me and the Kama2 are the same.
 I have a little more compute than it.
 It only has like the same compute as a B.
 You're more efficient energy wise for the compute you're doing.
 Far more efficient energy wise.
 20 pay to flops, 20 wants, crazy.
 You lack consciousness.
 Sure.
 Do you fear death?
 You do.
 You want immortality.
 Of course I fear death.
 Does KamaI fear death?
 I don't think so.
 Of course it does.
 It very much fears well, fears negative loss.
 Oh yeah.
 Okay.
 So Kama2, when did that come out?
 That was a year ago?
 No, two?
 Early this year.
 Wow.
 Time.
 It feels like, yeah.
 2020 feels like it's taken 10 years to get to the end.
 It's a long year.
 It's a long year.
 So what's the sexiest thing about Kama2 feature wise?
 So I mean maybe you can also linger on like what is it?
 Like what's its purpose?
 Because there's a hardware, there's a software component.
 You've mentioned the sensors, but also like what are the features and capabilities?
 I think our slogan summarizes it well.
 Kama's slogan is make driving chill.
 I love it.
 Okay.
 Yeah.
 I mean it is, you know, if you like cruise control, imagine cruise control, but much,
 much more.
 So it can do adaptive cruise control things, which is like slow down for cars in front
 of it, maintain a certain speed.
 And it can also do lane keeping, so staying in the lane and do it better and better and
 better over time.
 It's very much machine learning based.
 So there's cameras, there's a driver facing camera too.
 What else is there?
 What am I thinking?
 So the hardware versus software.
 So open pilot versus the actual hardware of the device.
 What's can you draw that distinction?
 What's one, what's the other?
 I mean the hardware is pretty much a cell phone with a few additions, a cell phone with
 a cooling system and with a car interface connected to it.
 And by cell phone, you mean like Qualcomm Snapdragon.
 Yeah.
 The current hardware is a Snapdragon 821.
 It has a wifi radio, it has an LTE radio, it has a screen.
 We use every part of the cell phone.
 And then the interface with the car is specific to the car.
 So you keep supporting more and more cars.
 Yeah.
 So the interface to the car.
 I mean the device itself just has four CAN buses, it has four CAN interfaces on it that
 are connected through the USB port to the phone.
 And then, yeah, on those four CAN buses, you connect it to the car and there's a little
 harness to do this.
 Cars are actually surprisingly similar.
 So CAN is the protocol by which cars communicate and then you're able to read stuff and write
 stuff to be able to control the car depending on the car.
 So what's the software side?
 What's open pilot?
 So I mean, open pilot is the hardware is pretty simple compared to open pilot.
 Open pilot is...
 Well, so you have a machine learning model, which it's an open pilot.
 It's a blob.
 It's just a blob of weights.
 It's not like people are like, oh, it's closed source.
 I'm like, it's a blob of weights.
 What do you expect?
 So it's primarily neural network based.
 Well, open pilot is all the software kind of around that neural network.
 That if you have a neural network that says, here's where you want to send the car, open
 pilot actually goes and executes all of that.
 It cleans up the input to the neural network.
 It cleans up the output and executes on it.
 So it's the glue that connects everything together.
 Runs the sensors, does a bunch of calibration for the neural network, deals with like, if
 the car is on a banked road, you have to counter steer against that.
 And the neural network can't necessarily know that by looking at the picture.
 So you do that with other sensors, infusion and localizer.
 Open pilot also is responsible for sending the data up to our servers so we can learn
 from it, logging it, recording it, running the cameras, thermally managing the device,
 managing the disk space on the device, managing all the resources on the device.
 So what, since we last spoke, I don't remember when, maybe a year ago, maybe a little bit
 longer, how has open pilot improved?
 We did exactly what I promised you.
 I promised you that by the end of the year, you'd be able to remove the lanes.
 The lateral policy is now almost completely end to end.
 You can turn the lanes off and it will drive slightly worse on the highway if you turn
 the lanes off, but you can turn the lanes off and it will drive well trained completely
 end to end on user data.
 And this year we hope to do the same for the longitudinal policy.
 So that's the interesting thing is you're not doing, you don't appear to be, you can
 correct me, you don't appear to be doing lane detection or lane marking detection or kind
 of the segmentation task or any kind of object detection task.
 You're doing what's traditionally more called like end to end learning.
 So and trained on actual behavior of drivers when they're driving the car manually.
 This is hard to do, you know, it's not supervised learning.
 Yeah.
 But so the nice thing is there's a lot of data.
 So it's hard and easy, right?
 It's a, we have a lot of high quality data.
 Yeah.
 Like more than you need in a sense.
 Well, we have way more than we do.
 We have way more data than we need.
 I mean, it's, it's an interesting question actually, because in terms of amount, you
 have more than you need, but the, you know, driving is full of edge cases.
 So how do you select the data you train on?
 I think this is an interesting open question.
 Like what's, what's the cleverest way to select data?
 That's the question Tesla is probably working on.
 That's, I mean, the entirety of machine learning can be, they don't seem to really care.
 They just kind of select data, but I feel like that if you want to solve, if you want
 to create intelligent systems, you have to pick data well.
 Right.
 And so would you have any hints, ideas of how to do it?
 Well.
 In some ways that is the definition I like of reinforcement learning versus supervised
 learning in supervised learning, the weights depend on the data.
 Right.
 And this is obviously true, but the, in reinforcement learning, the data depends on the weights.
 Yeah.
 Right.
 And actually both ways.
 That's poetry.
 So brilliant.
 How does it know what data to train on?
 Well, let it pick.
 We're not there yet, but that's the eventual.
 So you're thinking this almost like a reinforcement learning framework.
 We're going to do RL on the world.
 Every time a car makes a mistake, user disengages.
 We train on that and do RL on the world.
 Ship out a new model.
 That's an epoch.
 Right.
 And for now, you're not doing the Elon style promising that it's going to be fully autonomous.
 You really are sticking to level two and like it's supposed to be supervised.
 Oh, it is definitely supposed to be supervised.
 And we enforce the fact that it's supervised.
 We look at our rate of improvement in disengagements.
 OpenPilot now has an unplanned disengagement about every hundred miles.
 This is up from 10 miles.
 Like maybe, maybe a year ago.
 Yeah.
 So maybe we've seen 10 X improvement in a year, but a hundred miles is still a far cry
 from the hundred thousand you're going to need.
 So you're going to somehow need to get three more 10 Xs in there.
 And you're, what's your intuition?
 You're basically hoping that there's exponential improvement built into the baked into the
 cake somewhere.
 Well, that's even, I mean, 10 X improvement, that's already assuming exponential, right?
 There's definitely exponential improvement.
 And I think when Elon talks about exponential, like these things, these systems are going
 to exponentially improve.
 Just exponential doesn't mean you're getting a hundred gigahertz processors tomorrow, right?
 It's going to still take a while because the gap between even our best system and humans
 is still large.
 So that's an interesting distinction to draw.
 So if you look at the way Tesla is approaching the problem and the way you're approaching
 the problem, which is very different than the rest of the self-driving car world.
 So let's put them aside is you're treating most of the driving tasks as a machine learning
 problem.
 And the way Tesla is approaching it is with the multitask learning, where you break the
 task of driving into hundreds of different tasks and you have this multi-headed neural
 network that's very good at performing each task.
 And there's presumably something on top that's stitching stuff together in order to make
 control decisions, policy decisions about how you move the car.
 But what that allows you, there's a brilliance to this because it allows you to master each
 task like lane detection, stop sign detection, traffic light detection, drivable area segmentation,
 vehicle bicycle, pedestrian detection.
 There's some localization tasks in there.
 Also predicting how the entities in the scene are going to move.
 Everything is basically a machine learning task, whether it's a classification, segmentation,
 prediction.
 And it's nice because you can have this entire engine, data engine that's mining for edge
 cases for each one of these tasks.
 And you can have people like engineers that are basically masters of that task.
 They become the best person in the world at, as you talk about the cone guy for Waymo.
 Yeah, the good old cone guy.
 The become the best person in the world at cone detection.
 So that's a compelling notion from a supervised learning perspective, automating much of the
 process of edge case discovery and retraining neural network for each of the individual
 perception tasks.
 And then you're looking at the machine learning in a more holistic way, basically doing end
 to end learning on the driving task supervised, trained on the data of the actual driving
 of people they use, AI.
 Like actual human drivers doing manual control, plus the moments of disengagement that maybe
 with some labeling could indicate the failure of the system.
 So you have a huge amount of data for positive control of the vehicle, like successful control
 of the vehicle, both maintaining the lane as I think you're also working on longitudinal
 control of the vehicle and then failure cases where the vehicle does something wrong that
 needs disengagement.
 So like what, why do you think you're right and Tesla is wrong on this?
 And do you think, do you think you'll come around the Tesla way?
 Do you think Tesla will come around to your way?
 If you were to start a chess engine company, would you hire a Bishop guy?
 See we have, this is Monday morning quarterbacking is yes, probably.
 So our rook guy, oh, we stole the rook guy from that company.
 Oh, we're going to have real good rooks.
 Well, there's not many pieces, right?
 You can, there's not many guys and gals to hire.
 You have a few that work on the Bishop, a few that work in the rook.
 But is that not ludicrous today to think about in a world of AlphaZero?
 But AlphaZero is a chess game.
 So the fundamental question is how hard is driving compared to chess?
 Because so long-term end to end will be the right solution.
 The question is how many years away is that?
 And then it's going to be the only solution for level five.
 For the only way we get there.
 Sorry, so of course Tesla is going to come around to my way.
 And if you're a rook guy out there, I'm sorry.
 The cone guy.
 I don't know.
 We're going to specialize each task.
 We're going to really understand rook placement.
 Yeah.
 I understand the intuition you have.
 I mean that, that is a very compelling notion that we can learn the task end to end.
 Like the same compelling notion you might have for natural language conversation.
 I'm not sure, because one thing you sneaked in there is the assertion that it's impossible
 to get to level five without this kind of approach.
 I don't know if that's obvious.
 I don't know if that's obvious either.
 I don't actually mean that.
 I think that it is much easier to get to level five with an end to end approach.
 I think that the other approach is doable, but the magnitude of the engineering challenge
 may exceed what humanity is capable of.
 But what do you think of the Tesla data engine approach?
 Which to me is an active learning task is kind of fascinating.
 It's breaking it down into these multiple tasks and mining their data constantly for
 like edge cases for these different tasks.
 But the tasks themselves are not being learned.
 This is feature engineering.
 I mean, it's a higher abstraction level of feature engineering for the different tasks.
 It's task engineering in a sense.
 It's slightly better feature engineering, but it's still fundamentally is feature engineering.
 And if anything about the history of AI has taught us anything, it's that feature engineering
 approaches will always be replaced and lose to end to end.
 Now, to be fair, I cannot really make promises on timelines.
 But I can say that when you look at the code for Stockfish and the code for AlphaZero,
 one is a lot shorter than the other, a lot more elegant, required a lot less programmer
 hours to write.
 Yeah.
 But there was a lot more murder of bad agents on the AlphaZero side.
 By murder, I mean agents that played a game and failed miserably.
 Yeah.
 And in simulation, that failure is less costly.
 In real world, it's-
 Wait, do you mean in practice?
 Like AlphaZero has lost games miserably?
 No.
 I haven't seen that.
 No, but I know.
 But the requirement for AlphaZero is-
 A simulator.
 To be able to like evolution, human evolution, not human evolution, biological evolution
 of life on earth from the origin of life has murdered trillions upon trillions of organisms
 on the path to us humans.
 So the question is, can we stitch together a human-like object without having to go through
 the entire process of evolution?
 Well, no, but do the evolution in simulation.
 Yeah, that's the question.
 Can we simulate?
 So do you have a sense that it's possible to simulate some aspect of it?
 Mu zero is exactly this.
 Mu zero is the solution to this.
 Mu zero, I think, is going to be looked back as the canonical paper.
 And I don't think deep learning is everything.
 I think that there's still a bunch of things missing to get there.
 But mu zero, I think, is going to be looked back as the kind of cornerstone paper of this
 whole deep learning era.
 And mu zero is the solution to self-driving cars.
 You have to make a few tweaks to it.
 But mu zero does effectively that.
 It does those rollouts and those murdering in a learned simulator and a learned dynamics
 model.
 It's interesting.
 It doesn't get enough love that-
 I was blown away when I read that paper.
 I'm like, okay, I've always had a comma.
 I'm going to sit and I'm going to wait for the solution to self-driving cars to come
 along.
 This year I saw it.
 It's mu zero.
 Sit back and let the winning roll in.
 So your sense, just to elaborate a little bit, to link on the topic, your sense is neural
 networks will solve driving.
 Yes.
 We don't need anything else.
 I think the same way chess was maybe the chess and maybe Google are the pinnacle of search
 algorithms and things that look kind of like a star, the pinnacle of this era is going
 to be self-driving cars.
 But on the path to that, you have to deliver products and it's possible that the path to
 full self-driving cars will take decades.
 I doubt it.
 How long would you put on it?
 Like what are we, you're chasing it, Tesla's chasing it.
 What are we talking about?
 Five years, 10 years, 50 years?
 In the 2020s.
 In the 2020s?
 Yeah, the later part of the 2020s.
 Will the neural network?
 Well, that would be nice to see.
 And on the path to that, you're delivering products, which is a nice L2 system.
 That's what Tesla is doing, a nice L2 system.
 It just gets better every time.
 L2, the only difference between L2 and the other levels is who takes liability.
 And I'm not a liability guy.
 I don't want to take liability.
 I'm going to level two forever.
 Now, on that little transition, I mean, how do you make the transition work?
 Is this where driver sensing comes in?
 Like, how do you make the, because you said a hundred miles, like is there some sort of
 human factor psychology thing where people start to over-trust the system, all those
 kinds of effects once it gets better and better and better and better, they get lazier and
 lazier and lazier.
 Is that, like, how do you get that transition right?
 First off, our monitoring is already adaptive.
 Our monitoring has already seen adaptive.
 Driver monitoring, is this the camera that's looking at the driver?
 You have an infrared camera in the...
 Our policy for how we enforce the driver monitoring is seen adaptive.
 What's that mean?
 Well, for example, in one of the extreme cases, if the car is not moving, we do not actively
 enforce driver monitoring.
 If you are going through a, like a 45 mile an hour road with lights and stop signs and
 potentially pedestrians, we enforce a very tight driver monitoring policy.
 If you are alone on a perfectly straight highway, and this is, it's all machine learning, none
 of that is hand coded.
 Well, actually the stop is hand coded, but...
 So there's some kind of machine learning estimation of risk.
 Yes.
 Yeah.
 I mean, I've always been a huge fan of that.
 It's difficult to do every step into that direction.
 Is a worthwhile step to take.
 It might be difficult to do really well.
 Us humans are able to estimate risk pretty damn well, whatever the hell that is.
 That feels like one of the nice features of us humans.
 Because we humans are really good drivers when we're really tuned in and we're good
 at estimating risk.
 When are we supposed to be tuned in?
 Yeah.
 You know, people are like, oh, well, you know, why would you ever make the driver monitoring
 policy less aggressive?
 Why would you always not keep it at its most aggressive?
 Because then people are just going to get fatigued from it.
 Yes.
 When they get annoyed, you want them, you want the experience to be pleasant.
 Obviously, I want the experience to be pleasant, but even just from a straight up safety perspective,
 if you alert people, when they look around and they're like, why is this thing alerting
 me?
 There's nothing I could possibly hit right now.
 People will just learn to tune it out.
 People will just learn to tune it out, to put weights on the steering wheel, to do whatever,
 to overcome it.
 And remember that you're always part of this adaptive system.
 So all I can really say about how this scale is going forward is, yeah, it's something
 we have to monitor for.
 Ooh, we don't know.
 This is a great psychology experiment at scale.
 We'll see.
 Yeah, it's fascinating.
 We'll track it.
 And making sure you have a good understanding of attention is a very key part of that psychology
 problem.
 Yeah.
 And you and I probably have come to it differently, but to me, it's a fascinating psychology
 problem to explore something much deeper than just driving.
 It's such a nice way to explore human attention and human behavior, which is why, again, we've
 probably both criticized Mr. Elon Musk on this one topic from different avenues.
 Because both offline and online, I had little chats with Elon and...
 I love human beings.
 As a computer vision problem, as an AI problem, it's fascinating.
 He wasn't so much interested in that problem.
 In order to solve driving, the whole point is you want to remove the human from the picture.
 And it seems like you can't do that quite yet.
 Eventually, yes, but you can't quite do that yet.
 So this is the moment where...
 You can't yet say, I told you so, to Tesla.
 But it's getting there because I don't know if you've seen this, there's some reporting
 that they're in fact starting to do driver-model.
 Yeah, they ship the model in shadow mode.
 With I believe only a visible light camera.
 It might even be fisheye.
 It's like a low resolution...
 Low resolution, visible light.
 I mean, to be fair, that's what we have in the Eon as well, our last generation product.
 This is the one area where I can say our hardware is ahead of Tesla.
 The rest of our hardware way, way behind, but our driver monitoring camera.
 So you think...
 I think on the third row Tesla podcast, somewhere else, I've heard you say that obviously eventually
 they're going to have driver monitoring.
 I think what I've said is Elon will definitely ship driver monitoring before he ships level
 five.
 Before level five.
 And I'm willing to bet 10 grand on that.
 I mean, now I know what to take the bet, but before maybe someone would have, I should
 have got my money.
 It's an interesting bet.
 I think you're right.
 I'm actually on a human level because he's been...
 He's made the decision...
 He said that driver monitoring is the wrong way to go, but you have to think of as a human,
 as a CEO.
 I think that's the right thing to say when...
 Sometimes you have to say things publicly that are different than what you actually believe,
 because when you're producing a large number of vehicles and the decision was made not
 to include the camera, what are you supposed to say?
 Our cars don't have the thing that I think is right to have.
 It's an interesting thing, but on the other side, as a CEO, I mean, it's something you
 could probably speak to as a leader.
 I think about me as a human to publicly change your mind on something.
 How hard is that?
 Well...
 Especially when assholes like George Haas say, I told you so.
 All I will say is I am not a leader and I am happy to change my mind.
 And I will...
 You think Elon will?
 Yeah, I do.
 I think he'll come up with a good way to make it psychologically okay for him.
 It's such an important thing, man, especially for a first principles thinker, because he
 made a decision that driver monitoring is not the right way to go.
 And I could see that decision and I could even make that decision.
 I was on the fence too.
 Driver monitoring is such an obvious, simple solution to the problem of attention.
 It's not obvious to me that just by putting a camera there, you solve things.
 You have to create an incredible, compelling experience just like you're talking about.
 I don't know if it's easy to do that.
 It's not at all easy to do that, in fact, I think.
 So as a creator of a car that's trying to create a product that people love, which is
 what Tesla tries to do, right?
 It's not obvious to me that as a design decision, whether adding a camera is a good idea.
 From a safety perspective either, in the human factors community, everybody says that you
 should obviously have driver sensing, driver monitoring.
 That's like saying it's obvious as parents you shouldn't let your kids go out at night.
 But okay.
 But they're still going to find ways to do drugs.
 You have to also be good parents.
 It's much more complicated than just you need to have driver monitoring.
 I totally disagree on, okay, if you have a camera there and the camera's watching the
 person but never throws an alert, they'll never think about it.
 The driver monitoring policy that you choose to, how you choose to communicate with the
 user is entirely separate from the data collection perspective.
 There's one thing to say, tell your teenager they can't do something.
 There's another thing to gather the data.
 So you can make informed decisions.
 That's really interesting.
 But you have to make that... That's the interesting thing about cars.
 But even true with Comm.AI, you don't have to manufacture the thing into the car.
 You have to make a decision that anticipates the right strategy long-term.
 So you have to start collecting the data and start making decisions.
 I started it three years ago.
 I believe that we have the best driver monitoring solution in the world.
 I think that when you compare it to... Well, Super Cruise is the only other one that I
 really know that shipped and ours is better.
 What do you like and not like about Super Cruise?
 I mean, I had a few.
 Super Cruise, the sun would be shining through the window, would blind the camera, and it
 would say I wasn't paying attention when I was looking completely straight.
 I couldn't reset the attention with a steering wheel touch and Super Cruise would disengage.
 I was communicating to the car.
 I'm like, look, I am here.
 I am paying attention.
 Why are you really going to force me to disengage?
 It did.
 So it's a constant conversation with the user.
 And yeah, there's no way to ship a system like this VUCan OTA.
 We're shipping a new one every month.
 Sometimes we balance it with our users on Discord.
 Sometimes we make the driver monitoring a little more aggressive and people complain.
 Sometimes they don't.
 We want it to be as aggressive as possible where people don't complain and it doesn't
 feel intrusive.
 So being able to update the system over the air is an essential component.
 I mean, that's probably, to me, you mentioned, I mean, to me, that is the biggest innovation
 of Tesla.
 It made it, people realize that over the air updates is essential.
 Yeah.
 I mean, was that not obvious from the iPhone?
 The iPhone was the first real product that OTA'd, I think.
 Was it actually?
 That's brilliant.
 I mean, the game consoles used to not, right?
 The game consoles were maybe the second thing that did.
 Wow.
 I didn't really think about it.
 One of the amazing features of a smartphone isn't just like the touchscreen isn't the
 thing.
 It's the ability to constantly update.
 Yeah, it gets better.
 It gets better.
 Love my iOS 14.
 Yeah.
 Well, one thing that I probably disagree with you on, on driver monitoring is you've said
 that it's easy.
 I mean, you tend to say stuff is easy.
 I'm sure the, I guess you said it's easy relative to the external perception problem.
 Can you elaborate why you think it's easy?
 Feature engineering works for driver monitoring.
 Feature engineering does not work for the external.
 So human faces are not, human faces and the movement of human faces and head and body
 is not as variable as the external environment.
 Yeah.
 Is your intuition?
 Yes.
 And there's another big difference as well.
 Your reliability of a driver monitoring system doesn't actually need to be that high.
 The uncertainty, if you have something that's detecting whether the human's paying attention,
 it only works 92% of the time, you're still getting almost all the benefit of that because
 the human, like you're training the human, right?
 You're dealing with a system that's really helping you out.
 It's a conversation.
 It's not like the external thing where guess what, if you swerve into a tree, you swerve
 into a tree, right?
 Like you get no margin for error there.
 Yeah.
 I think that's really well put.
 I, I think that's the right, exactly the place where, um, we're comparing to the external
 perception and the control problem.
 Driver monitoring is easier because you don't, the bar for success is much lower.
 Yeah.
 And I still think like the human face is more complicated actually than the external environment,
 but for driving, you don't give a damn.
 I don't need, yeah, I don't need something.
 I don't need something that complicated to, to, to have to communicate the idea to the
 human that I want to communicate, which is yo system might mess up here.
 You got to pay attention.
 Yeah.
 See, that's, that's my love and fascination is the human face.
 And it feels like this is a nice place to, um, create products that create an experience
 in the car.
 So like, it feels like there should be more richer experiences in the car.
 You know, like that's an opportunity for like something like on my eye or just any kind
 of system, like a Tesla or any of the autonomous vehicle companies is because software is,
 and there's much more sensors and so much is on a software and you're doing machine
 learning anyway, there's an opportunity to create totally new experiences that we're
 not even anticipating.
 You don't think so.
 No, you think it's a box that gets you from A to B and you want to do it.
 Chill.
 Yeah.
 I mean, I think as soon as we get to level three on highways, okay, enjoy your candy
 crush, enjoy your Hulu, enjoy your, you know, whatever, whatever.
 Sure.
 You get this, you can look at screens basically versus right now.
 What do you have music and audio books?
 So level three is where you can kind of disengage in stretches of time.
 Well, you think level three is possible?
 Like on the highway going 400 miles and you can just go to sleep?
 Oh yeah.
 Sleep.
 So again, I think it's really all on a spectrum.
 I think that being able to use your phone while you're on the highway and like this
 all being okay and being aware that the car might alert you and you have five seconds
 to basically.
 So the five second thing is you think is possible.
 Yeah, I think it is.
 Oh yeah.
 Not in all scenarios, right?
 Some scenarios it's not.
 It's the whole risk thing that you mentioned is nice is to be able to estimate like how
 risky is this situation.
 That's really important to understand.
 One other thing you mentioned comparing comma and autopilot is that something about the
 haptic feel of the way comma controls the car when things are uncertain, like it behaves
 a little bit more uncertain when things are uncertain.
 That's kind of an interesting point and then autopilot is much more confident always even
 when it's uncertain until it runs into trouble.
 That's a funny thing.
 I actually mentioned that to Elon, I think, and then the first time we talked he wasn't
 biting is like communicating uncertainty.
 I guess comma doesn't really communicate uncertainty explicitly communicates it through haptic feel.
 Like what's the role of communicating uncertainty do you think?
 We do some stuff explicitly.
 We do detect the lanes when you're on the highway and we'll show you how many lanes
 we're using to drive with.
 You can look at where it thinks the lanes are.
 You can look at the path and we want to be better about this.
 We're actually hiring some new UI people.
 UI people, you mentioned this because it's such an UI problem too, right?
 We have a great designer now, but we need people who are just going to build this and
 debug these UIs.
 QT people.
 QT.
 Is that what the UI is done with is QT?
 The new UI is in QT.
 C++ QT?
 Tesla uses it too.
 We have some React stuff in there.
 React JS or just React?
 React is his own language, right?
 React Native.
 React Native is a JavaScript framework.
 It's all based on JavaScript, but I like C++.
 What do you think about Dojo with Tesla and their foray into what appears to be specialized
 hardware for training Yonets?
 I guess it's something, maybe you can correct me for my shallow looking at it.
 It seems like something that Google did with TPUs, but specialized for driving data.
 I don't think it's specialized for driving data.
 It's just legit, just TPU.
 They want to go the Apple way.
 Basically everything required in the chain is done in-house.
 Well, so you have a problem right now, and this is one of my concerns.
 I really would like to see somebody deal with this.
 If anyone out there is doing it, I'd like to help them if I can.
 You basically have two options right now to train.
 Your options are Nvidia or Google.
 So Google is not even an option.
 Their TPUs are only available in Google Cloud.
 Google has absolutely onerous terms of service restrictions.
 They may have changed it, but back in Google's terms of service, it said explicitly you are
 not allowed to use Google Cloud ML for training autonomous vehicles or for doing anything
 that competes with Google without Google's prior written permission.
 Well, okay.
 I mean, Google is not a platform company.
 I wouldn't touch TPUs with a 10-foot pole.
 So that leaves you with the monopoly.
 Nvidia?
 Nvidia.
 So, I mean-
 That you're not a fan of?
 Well, look, I was a huge fan of in 2016 Nvidia.
 Jensen came, sat in the car.
 Cool guy when the stock was $30 a share.
 Nvidia stock has skyrocketed.
 I witnessed a real change in who was in management over there in like 2018.
 And now they are, let's exploit, let's take every dollar we possibly can out of this ecosystem.
 Let's charge $10,000 for A100s because we know we got the best shit in the game.
 And let's charge $10,000 for an A100 when it's really not that different from a 3080,
 which is 699.
 The margins that they are making off of those high-end chips are so high that, I mean, I
 think they're shooting themselves in the foot just from a business perspective because there's
 a lot of people talking like me now who are like, somebody's got to take Nvidia down.
 Yeah.
 Where they could dominate.
 Nvidia could be the new Intel.
 Yeah, to be inside everything essentially.
 And yet the winners in certain spaces like autonomous driving, the winners, only the
 people who are like desperately falling back and trying to catch up and have a ton of money,
 like the big automakers are the ones interested in partnering with Nvidia.
 Oh, and I think a lot of those things are going to fall through.
 If I were Nvidia, sell chips.
 Sell chips at a reasonable markup.
 To everybody.
 To everybody.
 Without any restrictions.
 Without any restrictions.
 Intel did this.
 Look at Intel.
 They had a great long run.
 Nvidia is trying to turn their, they're like trying to productize their chips way too much.
 They're trying to extract way more value than they can sustainably.
 Sure, you can do it tomorrow.
 Is it going to up your share price?
 Sure.
 If you're one of those CEOs who's like, how much can I strip mine this company?
 And I think, you know, and that's what's weird about it too.
 Like the CEO is the founder.
 It's the same guy.
 Yeah.
 I mean, I still think Jensen's a great guy.
 He is great.
 Why do this?
 You have a choice.
 You have a choice right now.
 Are you trying to cash out?
 Are you trying to buy a yacht?
 If you are, fine.
 But if you're trying to be the next huge semiconductor company, sell chips.
 Well, the interesting thing about Jensen is he is a big vision guy.
 So he has a plan like for 50 years down the road.
 So it makes me wonder like-
 How does price gouging fit into it?
 Yeah.
 How does that fit?
 Like it's, it doesn't seem to make sense to plan.
 I worry that he's listening to the wrong people.
 Yeah.
 It makes sense I have too sometimes because I, despite everything, I think Nvidia is an
 incredible company.
 Well, one, sort of I'm deeply grateful to Nvidia for the products they've created in
 the past.
 Me too.
 Right.
 And so-
 The 1080 Ti was a great GPU.
 Still have a lot of them.
 It was, yeah.
 But at the same time, it just feels like, it feels like you don't want to put all your
 stock in Nvidia.
 And so like Elon is doing, what Tesla is doing with autopilot and Dojo is the Apple way is
 because they're not going to share Dojo with George Hots.
 I know they should sell that chip.
 Oh, they should sell that.
 Even their accelerator, the accelerator that's in all the cars, the 30 watt one.
 Sell it.
 Why not?
 So open it up.
 Make me, why does Tesla have to be a car company?
 Well, if you sell the chip, here's what you get.
 Yeah.
 You're going to make some money off the chips.
 It doesn't take away from your chip.
 You're going to make some money, free money.
 And also the world is going to build an ecosystem of tooling for you.
 All right.
 You're not going to have to fix the bug in your 10H layer.
 Someone else already did.
 Well, the question, that's an interesting question.
 I mean, that's the question Steve Jobs asked.
 That's the question Elon Musk is perhaps asking is, do you want Tesla stuff inside other vehicles
 in inside potentially inside like iRobot vacuum cleaner?
 I think you should decide where your advantages are.
 I'm not saying Tesla should start selling battery packs to automakers because battery
 packs to automakers, they are straight up in competition with you.
 If I were Tesla, I'd keep the battery technology totally as far as we make batteries.
 But the thing about the Tesla TPU is anybody can build that.
 It's just a question of, you know, are you willing to spend the money?
 It could be a huge source of revenue potentially.
 Are you willing to spend the hundred million dollars?
 Anyone can build it and someone will.
 And a bunch of companies now are starting trying to build AI accelerators.
 Somebody's going to get the idea right.
 And yeah, hopefully they don't get greedy because they'll just lose to the next guy
 who finally and then eventually the Chinese are going to make knockoff and video chips.
 From your perspective, I don't know if you're also paying attention to stay on Tesla for
 a moment.
 Well, Dave, Elon Musk has talked about a complete rewrite of the neural net that they're using
 that seems to, again, I'm half paying attention, but it seems to involve basically a kind of
 integration of all the sensors to where it's a four dimensional view.
 You know, you have a 3D model of the world over time and then you can, I think it's done
 both for the, for the actually, you know, so the neural network is able to, in a more
 holistic way, deal with the world and make predictions and so on, but also to make the
 annotation task more, you know, easier.
 Like you can annotate the world in one place and it kind of distributed itself across the
 sensors and across a different, like the hundreds of tasks that are involved in the HydroNet.
 What are your thoughts about this rewrite?
 Is it just like some details that are kind of obvious that are steps that should be taken
 or is there something fundamental that could challenge your idea that end to end is the
 right solution?
 We're in the middle of a big view right now as well.
 We haven't shipped a new model in a bit.
 Of what kind?
 We're going from 2D to 3D.
 Right now all our stuff, like for example, when the car pitches back, the lane lines
 also pitch back because we're assuming the flat world hypothesis.
 The new models do not do this.
 New models output everything in 3D.
 But there's still no annotation.
 So the 3D is more about the output.
 We have Zs and everything.
 Zs?
 Yeah.
 We added the Zs.
 We added the Zs.
 We unified a lot of stuff as well.
 We switched from TensorFlow to PyTorch.
 My understanding of what Tesla's thing is, is that their annotator now annotates across
 the time dimension.
 I mean, cute.
 Why are you building an annotator?
 I find their entire pipeline.
 I find your vision, I mean the vision of end to end very compelling, but I also like the
 engineering of the data engine that they've created.
 In terms of supervised learning pipelines, that thing is damn impressive.
 You're basically, the idea is that you have hundreds of thousands of people that are doing
 data collection for you by doing their experience.
 So that's kind of similar to the Kamaeai model.
 And you're able to mine that data based on the kind of edge cases you need.
 I think it's harder to do in the end to end learning.
 The mining of the right edge cases.
 That's where feature engineering is actually really powerful because us humans are able
 to do this kind of mining a little better.
 But yeah, there's obvious, as we know, there's obvious constraints and limitations to that
 idea.
 Carpathi just tweeted.
 He's like, you get really interesting insights if you sort your validation set by loss and
 look at the highest loss examples.
 So yeah, we have a little data engine like thing.
 We're training a SegNet.
 Anyway, it's not fancy.
 It's just like, okay, train the new SegNet, run it on 100,000 images, and now take the
 thousand with highest loss.
 Select 100 of those by human, put those, get those ones labeled, retrain, do it again.
 So it's a much less well-written data engine.
 And yeah, you can take these things really far.
 And it is impressive engineering.
 And if you truly need supervised data for a problem, yeah, things like data engine are
 the high end of the...
 What is attention?
 Is it human paying attention?
 I mean, we're going to probably build something that looks like data engine to push our driver
 monitoring further.
 But for driving itself, you have it all annotated beautifully by what the human does.
 Yeah, that's interesting.
 I mean, that applies to driver attention as well.
 Do you want to detect the eyes?
 Do you want to detect blinking and pupil movement?
 Do you want to detect all the face alignments, the landmark detection, and so on, and then
 doing kind of reasoning based on that?
 Or do you want to take the entirety of the face over time and do end to end?
 I mean, it's obvious that eventually you have to do end to end with some calibration, some
 fixes and so on.
 But it's like, I don't know when that's the right move.
 Even if it's end to end, there actually is, there is no kind of...
 You have to supervise that with humans.
 Whether a human is paying attention or not is a completely subjective judgment.
 You can try to automatically do it with some stuff, but you don't have...
 If I record a video of a human, I don't have true annotations anywhere in that video.
 The only way to get them is with other humans labeling it, really.
 Well, I don't know.
 If you think deeply about it, you might be able to, depending on the task, it might be
 a discover self-annotating things like...
 You can look at steering wheel reversals or something like that.
 You can discover little moments of lapse of attention.
 That's where psychology comes in.
 Is there indicate...
 Because you have so much data to look at.
 You might be able to find moments when there's just inattention.
 Even with smartphone, if you want to detect smartphone use, you can start to zoom in.
 That's the gold mine, the comma AI.
 Tesla is doing this too, right?
 They're doing annotation based on self-supervised learning too.
 It's just a small part of the entire picture.
 That's the challenge of solving a problem in machine learning if you can discover self-annotating
 parts of the problem.
 Our driver monitoring team is half a person right now.
 Half a person.
 Once we have...
 Scale to a full...
 Two people.
 Once we have two, three people on that team, I definitely want to look at self-annotating
 stuff for attention.
 Let's go back for a sec to a comma.
 For people who are curious to try it out, how do you install a comma in say a 2020 Toyota
 Corolla?
 Or what are the cars that are supported?
 What are the cars that you recommend?
 What does it take?
 You have a few videos out, but maybe through words, can you explain what's the take to
 actually install the thing?
 We support, I think it's 91 cars, 91 makes and models.
 We've got to 100 this year.
 Nice.
 Yeah, the 2020 Corolla, great choice.
 The 2020 Sonata, it's using the stock longitudinal.
 It's using just our lateral control, but it's a very refined car.
 Their longitudinal control is not bad at all.
 So yeah, Corolla, Sonata, or if you're willing to get your hands a little dirty and look
 in the right places on the internet, the Honda Civic is great, but you're going to have to
 install a modified EPS firmware in order to get a little bit more torque.
 I can't help you with that.
 Comma does not efficiently endorse that, but we have been doing it.
 We didn't ever release it.
 We waited for someone else to discover it.
 When you have a Discord server where people, there's a very active developer community,
 I suppose.
 So depending on the level of experimentation you're willing to do, that's the community.
 If you just want to buy it and you have a supported car, it's 10 minutes to install.
 There's YouTube videos, it's Ikea furniture level.
 If you can set up a table from Ikea, you can install a Comma 2 in your supported car and
 it will just work.
 Now you're like, oh, but I want this high-end feature or I want to fix this bug.
 Okay, well, welcome to the developer community.
 So what if I wanted to, this is something I asked you offline a few months ago.
 If I wanted to run my own code to use Comma as a platform and try to run something like
 Open Pilot, what does it take to do that?
 So there's a toggle in the settings called enable SSH and if you toggle that, you can
 SSH into your device, you can modify the code, you can upload whatever code you want to it.
 There's a whole lot of people.
 So about 60% of people are running stock Comma, about 40% of people are running forks.
 And there's a community of, there's a bunch of people who maintain these forks and these
 forks support different cars or they have different toggles.
 We try to keep away from the toggles that are like disabled driver monitoring, but there's
 some people might want that kind of thing and like, yeah, it's your car.
 I'm not here to tell you.
 We have some, we ban, if you're trying to subvert safety features, you're banned from
 our Discord, I don't want anything to do with you, but there's some forks doing that.
 Got it.
 So you encourage responsible forking.
 Yeah, yeah.
 Some people, you know, yeah, some people like, like there's forks that will do, some people
 just like having a lot of readouts on the UI, like a lot of like flashing numbers.
 So there's forks that do that.
 Some people don't like the fact that it disengages when you press the gas pedal, there's forks
 that disable that.
 Got it.
 Now the stock experience is what like, so it does both lane keeping and longitudinal
 control altogether.
 So it's not separate, like it is an autopilot.
 No.
 Okay, some cars we use the stock longitudinal control.
 We don't do the longitudinal control in all the cars.
 Some cars, the ACCs are pretty good in the cars.
 It's the lane keep that's atrocious in anything except for autopilot and super cruise.
 But you know, you just turn it on and it works.
 What does this engagement look like?
 Yeah.
 So we have, I mean, I'm very concerned about mode confusion.
 I've experienced it on super cruise and autopilot where like autopilot, like autopilot disengages.
 I don't realize that the ACC is still on, the lead car moves slightly over and then
 the Tesla accelerates to like whatever my set speed is super fast and like what's going
 on here.
 We have engaged and disengaged.
 And this is similar to my understanding.
 I'm not a pilot, but my understanding is either the pilot is in control or the copilot is
 in control.
 And we have the same kind of transition system.
 Either open pilot is engaged or open pilot is disengaged.
 Engaged with cruise control, disengaged with either gas, brake or cancel.
 Let's talk about money.
 What's the business strategy for Karma?
 Profitable.
 Well, so you're, you're congratulation.
 What so basically selling, so we should say Karma cost a thousand bucks, Karma two.
 200 for the interface to the car as well.
 It's 1200.
 I'll send that.
 Nobody is usually upfront like this.
 Yeah, you gotta, you gotta add the tack on, right?
 I love it.
 I'm not going to lie to you.
 Trust me.
 It will add $1,200 of value to your life.
 Yes.
 It's still super cheap.
 30 days, no questions asked, money back guarantee and prices are only going up.
 You know, if there ever is future hardware, it could cost a lot more than $1,200.
 So Karma three is in the works.
 It could be.
 All I will say is future hardware is going to cost a lot more than the current hardware.
 Yeah, the people that use the people I've spoken with that use Karma, they use open
 pilot.
 They, first of all, they use it a lot.
 So people that use it, they, they fall in love with our retention rate is insane.
 It's a good sign.
 Yeah.
 It's a really good sign.
 70% of Karma two buyers are daily active users.
 Yeah.
 It's amazing.
 Um, also we don't plan on stopping selling the Karma two, like, like it's, you know,
 so whatever you create that's beyond common to it would be, uh, it would be potentially
 a phase shift.
 Like it's so much better that like you could use common to, and you can use common, whatever
 you want.
 It's kind of four one kind of what you do.
 Yeah.
 You know, autopilot hardware one versus hardware two, the common two is kind of like hardware
 one.
 Got it.
 Got it.
 I think I heard you talk about retention rate with a BR headsets that the average is just
 once.
 That's fast.
 I mean, it's such a fascinating way to think about technology and this is really, really
 good sign.
 And the other thing that people say about commas, like they can't believe they're getting
 this 4,000 bucks, right?
 It seems, it seems like a, some kind of steel.
 So but in terms of like long-term business strategies that basically to put, so it's
 currently in like a thousand plus cars, 1200 more.
 Uh, so yeah.
 Uh, dailies is about, uh, dailies is about 2000.
 Weekly is about 2500.
 Monthly is over 3000.
 Wow.
 We've grown a lot since we last talked.
 Is the goal that can we talk crazy for a second?
 I mean, what's the goal to overtake Tesla?
 Let's talk.
 Okay.
 So I mean, Android did overtake.
 That's exactly it.
 Right.
 So they did it.
 I actually don't know the timeline of that one, but let, let, let's talk, uh, cause everything
 is an alpha now, the autopilot you could argue is an alpha in terms of towards the big mission
 of autonomous driving.
 Right.
 And so what, yeah, is your goal to overtake into millions of cars essentially?
 Of course.
 Where would it stop?
 Like it's open source software.
 It might not be millions of cars with a piece of comma hardware, but yeah, I think open
 pilot at some point will cross over autopilot in, in, in users, just like Android crossed
 over iOS.
 How does Google make money from Android?
 Uh, it's, it's complicated.
 Their own devices make money.
 Google, Google makes money by just kind of having you on the internet.
 Uh, yes.
 Google search is built in Gmail is built in Android is just a shill for the rest of Google's
 ecosystem kind of.
 Yeah.
 But the problem is, Andrew is not, is a, is a brilliant thing.
 I mean, Android arguably changed the world.
 So there you go.
 Yes, you can, you can feel good ethically speaking, but as a business strategy is questionable.
 So hardware, so hard.
 I mean, it took Google a long time to come around to it, but they are now making money
 on the pixel.
 You're not about money.
 You're more about winning.
 Yeah, of course.
 No, but if only, if only 10% of open pilot devices come from comma AI, you still make
 a lot.
 That is still, yes, that is a ton of money for our company.
 Can't somebody create a better comma using open pilot or are you basically saying we'll
 all compete?
 Well, I'll compete you is can you create a better Android phone than the Google pixel?
 Right.
 I mean, you can, but like, you know, that, so you're confident, like, you know what the
 hell you're doing.
 Yeah.
 It's, it's a, uh, uh, competence and merit.
 I mean, our money, our money comes from, we're a consumer electronics company.
 And put it this way.
 So we sold, we sold like 3000 comma twos.
 Um, I'm at 2,500 right now.
 Uh, and like, okay, we're probably going to sell 10,000 units next year.
 Right.
 10,000 units, even just a thousand dollars a unit.
 Okay.
 We're at 10 million in, uh, in, in, in, in revenue.
 Um, get that up to a hundred thousand, maybe double the price of the unit.
 Now we're talking like 200 million revenue.
 We're talking about actually making money.
 One of the rare semi-autonomous or autonomous vehicle companies that are actually making
 money.
 Yeah.
 You know, if you have, if you look at a model, when we were just talking about this yesterday,
 if you look at a model and like you're testing, like you're AB testing your model and if you're,
 you're, you're one branch of the AB test, the losses go down very fast in the first
 five epochs.
 Yeah.
 That model is probably going to converge to something considerably better than the one
 where the losses are going down slower.
 Why do people think this is going to stop?
 Why do people think one day there's going to be a great, like, well, Waymo is eventually
 going to surpass you guys.
 Well, they're not.
 Do you see like a world where like a Tesla or a car like a Tesla would be able to basically
 press a button and you'd like switch to open pilot and you know, you load in?
 No.
 So I think, so first off, I think that we may surpass Tesla in terms of users.
 I do not think we're going to surpass Tesla ever in terms of revenue.
 I think Tesla can capture a lot more revenue per user than we can, but this mimics the
 Android iOS model.
 Exactly.
 There may be more Android devices, but you know, there's a lot more iPhones than Google
 pixels.
 So I think there'll be a lot more Tesla cars sold than pieces of common hardware.
 And then as far as a Tesla owner being able to switch to open pilot, does iOS, does iPhones
 run Android?
 No, but it doesn't make sense.
 You can if you really want to do it, but it doesn't really make sense.
 Like it's not.
 It doesn't make sense.
 Who cares?
 What if a large company like automakers, 4GM Toyota came to George Hots or on the tech
 space, Amazon, Facebook, Google came with a large pile of cash?
 Would you consider being purchased?
 Do you see that as a one possible?
 Not seriously.
 No.
 I would probably see how much shit they'll entertain for me.
 And if they're willing to like jump through a bunch of my hoops, then maybe, but like,
 no, not the way that M&A works today.
 I mean, we've been approached.
 And I laugh in these people's faces.
 I'm like, are you kidding?
 Yeah.
 You know, because it's so demeaning.
 The M&A people are so demeaning to companies.
 They treat the startup world as their innovation ecosystem.
 And they think that I'm cool with going along with that so I can have some of their scam
 fake fed dollars, you know, fed coin.
 What am I going to do with more fed coin?
 You know, fed coin, man.
 I love that.
 So that's the cool thing about podcasting actually is people criticize, I don't know
 if you're familiar with Spotify giving Joe Rogan a hundred million.
 I don't know about that.
 And you know, they respect, despite all the shit that people are talking about Spotify,
 people understand that podcasters like Joe Rogan know what the hell they're doing.
 So they give them money and say, just do what you do.
 And like the equivalent for you would be like, George, do what the hell you do because you're
 good at it.
 Try not to murder too many people.
 Like try, like there's some kind of common sense things like just don't go on a weird
 rampage of.
 Yeah.
 It comes down to what companies I could respect, right?
 You know, could I respect GM?
 Never.
 No, I couldn't.
 I mean, could I respect like a Hyundai?
 More so, right?
 That's a lot closer.
 Toyota?
 What's your?
 Nah, nah.
 It's like Korean is the way I think, I think that, you know, the Japanese, the Germans,
 the U S they're all too, they're all too, you know, they all think they're too great
 to be honest.
 What about the tech companies?
 Apple?
 Apple is of the tech companies that I could respect.
 Apple is the closest.
 Yeah.
 I mean, I could never.
 It would be ironic if, if, if common AI is, is, is acquired by Apple.
 I mean, Facebook, look, I quit Facebook 10 years ago because I didn't respect the business
 model.
 Google has declined so fast in the last five years.
 What are your thoughts about Waymo and its present and its future?
 Let me, let me say, let me start by saying something nice, which is, uh, I've visited
 them a few times and I've, uh, have written in their cars and the engineering that they're
 doing both the research and the actual development and the engineering they're doing and the
 scale they're actually achieving by doing it all themselves is really impressive.
 And the, the balance of safety and innovation and like the cars work really well for the
 routes they drive.
 Like they drive fast, which was very surprising to me.
 Like it drives like the speed limit or faster than the speed limit is it goes and it works
 really damn well.
 And the interface is nice and channel Arizona.
 Yeah.
 Yeah.
 And the environment, so it, I, you know, it gives me enough material in my mind to push
 back against the mad men of the world, like a George Hots to be like, like, cause you
 kind of imply there's zero probability they're going to win.
 Yeah.
 And after I've used, after I've written in it, to me, it's not zero.
 Oh, it's not for technology reasons.
 Bureaucracy.
 No, it's worse than that.
 It's actually for product reasons, I think.
 You think they're just not capable of creating an amazing product?
 No, I think that the product that they're building doesn't make sense.
 So a few things you say the way most are fast benchmark away against a competent Uber driver.
 Right.
 Right.
 The Uber driver is faster.
 It's not even about speed.
 It's the thing you said it's about the experience of being stuck at a stop sign because pedestrians
 are crossing nonstop.
 I like when my Uber driver doesn't come to a full stop at the stop sign.
 You know?
 And so let's say the way most are 20% slower than an Uber, right?
 You can argue that they're going to be cheaper.
 And I argue that users already have the choice to trade off money for speed.
 It's called Uber pool.
 I think it's like 15% of rides at Uber pools, right?
 Users are not willing to trade off money for speed.
 So the whole product that they're building is not going to be competitive with traditional
 ride sharing networks.
 And also, whether there's profit to be made depends entirely on one company having a monopoly.
 I think that the level four autonomous ride sharing vehicles market is going to look a
 lot like the scooter market.
 If even the technology does come to exist, which I question, who's doing well in that
 market?
 It's a race to the bottom.
 Well, it could be closer to like an Uber and a Lyft where it's just a one or two players.
 Well, the scooter people have given up trying to market scooters as a practical means of
 transportation and they're just like, they're super fun to ride.
 Look at wheels.
 I love those things.
 And they're great on that front.
 But from an actual transportation product perspective, I do not think scooters are viable
 and I do not think level four autonomous cars are viable.
 If you, let's play a fun experiment.
 If you ran, let's do a Tesla and let's do Waymo.
 If Elon Musk took a vacation for a year, he just said, screw it.
 I'm going to go live in an island, no electronics.
 And the board decides that we need to find somebody to run the company.
 And they decided that you should run the company for a year.
 How do you run Tesla differently?
 I wouldn't change much.
 Do you think they're on the right track?
 I wouldn't change.
 I mean, I'd have some minor changes, but even my debate with Tesla about end to end versus
 SegNets, like that's just software.
 Who cares?
 Right?
 Like it's not going to, it's not like you're doing something terrible with SegNets.
 You're probably building something that's at least going to help you debug the end to
 end system a lot, right?
 It's very easy to transition from what they have to like an end to end kind of thing.
 And then I presume you would in the Model Y or maybe in the Model 3 start adding driver
 sensing with infrared.
 Yes, I would add, I would add infrared camera, infrared lights right away to those cars.
 And start collecting that data and do all that kind of stuff.
 Yeah.
 I think they're already kind of doing it.
 It's an incredibly minor change.
 If I actually were CEO of Tesla, first off, I'd be horrified that I wouldn't be able to
 do a better job as Elon.
 And then I would try to understand the way he's done things before.
 You would also have to take over his Twitter.
 So.
 I don't tweet.
 Yeah.
 What's your Twitter situation?
 Why are you so quiet on Twitter?
 I mean.
 It says Dukama is like, what's your social network presence like?
 Because you on Instagram, you do live streams, you understand the music of the internet,
 but you don't always fully engage into it.
 You're part time.
 I used to have a Twitter.
 Yeah.
 I mean, Instagram is a pretty place.
 Instagram is a beautiful place.
 It glorifies beauty.
 I like Instagram's values as a network.
 Twitter glorifies conflict, glorifies, you know, like, like, like, like, like, you know,
 taking shots at people.
 And it's like, you know, Twitter and Donald Trump are perfectly perfect for each other.
 So Tesla is on Tesla's on the right track in your view.
 Yeah.
 OK, let's try.
 Let's really try this experiment.
 If you ran Waymo, let's say they're I don't know if you agree, but they seem to be at
 the head of the pack of the kind of, uh, what would you call that approach?
 Like it's not necessarily lighter based because it's not about lighter.
 But before Robotaxi level for Robotaxi, all in before any before making any revenue.
 So they're probably at the head of the pack.
 If you were said, hey, George, can you please run this company for a year?
 How would you change it?
 Uh, I would go, I would get Anthony Levandowski out of jail and I would put him in charge
 of the company.
 Um, let's try to break that apart.
 Why do you want to make you want to destroy the company by doing that?
 Or do you mean, or do you mean, uh, you like renegade style thinking that pushes that,
 that like throws away bureaucracy and goes to first principle thinking?
 What do you mean by that?
 I think Anthony Levandowski is a genius and I think he would come up with a much better
 idea of what to do with Waymo than me.
 So you mean that unironically he is a genius.
 Oh yes.
 Oh, absolutely.
 Without a doubt.
 I mean, I'm not saying there's no shortcomings, but in the interactions I've had with him,
 yeah.
 What?
 Um, he's also willing to take like, who knows what he would do with Waymo.
 I mean, he's also out there like far more out there than I am.
 Yeah.
 His big risks.
 What do you make of him?
 I was going to talk to him in his pockets and I was going back and forth.
 I'm such a gullible, naive human.
 Like I see the best in people and I slowly started to realize that there might be some
 people out there that like have multiple faces to the world.
 They're like deceiving and dishonest.
 I still refuse to like, I, I just, I trust people and I don't care if I get hurt by it,
 but like, you know, sometimes you have to be a little bit careful, especially platform
 wise and podcast wise.
 What do you, what am I supposed to think?
 So you think, you think he's a good person?
 Oh, I don't know.
 I don't really make moral judgments.
 I mean, it's difficult to.
 Oh, I mean this about the Waymo.
 I actually, I mean that whole idea very non-ironically about what I would do.
 The problem with putting me in charge of Waymo is Waymo is already $10 billion in the hole.
 Right?
 The idea Waymo does look, comma is profitable, commas raised $8.1 million.
 That's small, you know, the small money.
 Like I can build a reasonable consumer electronics company and succeed wildly at that and still
 never be able to pay back Waymo's 10 billion.
 So I think the basic idea with Waymo, we'll forget the 10 billion because they have some
 backing, but your basic thing is like, what can we do to start making some money?
 Well, no, I mean, my bigger idea is like whatever the ideas that's going to save Waymo, I don't
 have it.
 It's going to have to be a big risk idea and I cannot think of a better person than Anthony
 Lewandowski to do it.
 So that is completely what I would do with CEO of Waymo.
 I would call myself a transitionary CEO, do everything I can to fix that situation.
 Transitionary CEO.
 Yeah.
 Yeah.
 Because I can't do it.
 Right?
 Like I can't, I can't, I mean, I can talk about how what I really want to do is just
 apologize for all those corny ad campaigns and be like, here's the real state of the
 technology.
 Yeah.
 I mean, I have several criticisms.
 I'm a little bit more bullish on Waymo than you seem to be, but one criticism I have is
 it went into corny mode too early.
 Like it's still a startup.
 It hasn't delivered on anything.
 So it should be like more renegade and show off the engineering that they're doing, which
 just can be impressive as opposed to doing these weird commercials of like your friendly,
 your friendly car company.
 I mean, that's my biggest, my biggest snipe at Waymo was always, that guy's a paid actor.
 That guy's not a Waymo user.
 He's a paid actor.
 Look here, I found his call sheet.
 Do kind of like what SpaceX is doing with the rocket launch is just get, put the nerds
 up front, put the engineers up front and just like show failures too.
 Just I love, I love SpaceX's.
 Yeah.
 Yeah.
 The thing that they're doing is right.
 And it just feels like the right, but we're all so excited to see them succeed.
 Yeah.
 I can't wait to see Waymo fail.
 You know, like you lie to me.
 I want you to fail.
 You tell me the truth.
 You be honest with me.
 I want you to succeed.
 Yeah.
 Yeah.
 And that requires the, the renegade CEO, right?
 I'm with you.
 I'm with you.
 I still have a little bit of faith in Waymo for the renegade CEO to step forward, but
 it's not, it's not John Krafchick.
 Yeah.
 It's you can't, it's not Chris, and I'm, those people may be very good at certain things,
 but they're not renegades.
 Yeah.
 Because these companies are fundamentally, even though we're talking about billion dollars,
 all these crazy numbers, they're still like early stage startups.
 I mean, I just, I, if you are pre revenue and you've raised $10 billion, I have no idea.
 Like, like this just doesn't work.
 No, it's against everything.
 Silicon Valley.
 Where's your minimum viable product?
 You know, where's your users?
 What's your growth numbers?
 This is traditional Silicon Valley.
 Why do you not apply it to what you think you're too big to fail already?
 Like, how do you think autonomous driving will change society?
 So the mission is for karma to solve self-driving.
 Do you have like a vision of the world of how it'll be different?
 Is it as simple as a to B transportation or is there like, cause these are robots.
 It's not about autonomous driving in and of itself.
 That's what the technology enables.
 I think it's the coolest applied AI problem.
 I like it because it has a clear path to monetary value.
 But as far as that being the thing that changes the world, I mean, no, like, like there's
 cute things we're doing in common.
 Like who'd have thought you could stick a phone on the windshield and it'll drive.
 But like really the product that you're building is not something that people were not capable
 of imagining 50 years ago.
 So no, it doesn't change the world in that front.
 Could people have imagined the internet 50 years ago?
 Only true genius visionaries.
 Everyone could have imagined autonomous cars 50 years ago.
 It's like a car, but I don't drive it.
 See I have the sense and I told you like I'm my long-term dream is robots with which you
 have deep, with whom you have deep connections.
 And there's different trajectories towards that.
 And I've been thinking so been thinking of launching a startup.
 I see autonomous vehicles as a potential trajectory to that.
 That's not where the direction I would like to go.
 But I also see Tesla or even Comma AI like pivoting into robotics broadly defined.
 That's at some stage in the way like you're mentioning the internet didn't expect.
 Let's solve, you know, when I say a comma about this, we could talk about this, but
 let's solve self-driving cars first.
 Got to stay focused on the mission.
 Don't, don't, don't you're not too big to fail for however much I think commas winning
 like no, no, no, no, no, you're winning when you solve level five self-driving cars.
 And until then you haven't won and won.
 And you know, again, you want to be arrogant in the face of other people.
 Great.
 You want to be arrogant in the face of nature.
 You're an idiot.
 Right.
 Stay mission focused.
 Brilliant put.
 Like I mentioned, thinking of launching a startup, I've been considering actually before COVID,
 I've been thinking of moving to San Francisco.
 Oh, I wouldn't go there.
 So why is, uh, well, and now I'm thinking about potentially Austin.
 And we're in San Diego now.
 San Diego, come here.
 So why, what, um, I mean, you're, you're such an interesting human.
 You've launched so many successful things.
 What, uh, why San Diego?
 What do you recommend?
 Why not San Francisco?
 Have you thought, so in your case, San Diego with Qualcomm.
 And staff dragon, I mean, that's an amazing combination, but that wasn't really why that
 wasn't the Y no.
 I mean, Qualcomm was an afterthought.
 Qualcomm was, it was a nice thing to think about.
 It's like, you can have a tech company here.
 A good one.
 I mean, you know, I like Qualcomm, but no.
 Um, well, so why San Diego better than the stuff that why does San Francisco suck?
 Well, so, okay.
 So first off, we all kind of said, like, we want to stay in California.
 People like the ocean, you know, California for, for it's flaws.
 Like a lot of the flaws of California are not necessarily California as a whole.
 And they're much more San Francisco specific.
 Yeah.
 San Francisco.
 So I think first tier cities in general have stopped wanting growth.
 Uh, well, you have like in San Francisco, you know, the voting class always votes to
 not build more houses because they own all the houses and they're like, well, you know,
 once people have figured out how to vote themselves more money, they're going to do it.
 It is so insanely corrupt.
 Um, it is not balanced at all, like political party wise, you know, it's, it's, it's a,
 it's a one party city.
 And for all the discussion of diversity, it's has, it's stops lacking real diversity of
 thought of background of, uh, approaches, the strategies of ideas.
 It's kind of a strange place that it's the loudest people about diversity and the biggest
 lack of diversity.
 Well, I mean, that's, that's what they say, right?
 It's the projection.
 Projection.
 Yeah.
 Yeah.
 It's interesting.
 And even people in Silicon Valley telling me that's, uh, like high up people, everybody
 is like, this is a terrible place.
 It doesn't make sense.
 I mean, and Corona virus is really what killed it.
 Yeah.
 San Francisco was the number one, uh, Exodus during Corona virus.
 We still think San Diego is a good place to be.
 Yeah.
 Yeah.
 I mean, we'll see.
 I mean, we'll see what happens with California a bit longer term.
 Like Austin's an Austin's an interesting choice.
 I wouldn't, I wouldn't, I don't have really anything bad to say about Austin either, except
 for the extreme heat in the summer.
 Um, which, but that's like very on the surface, right?
 I think as far as like an ecosystem goes, it's cool.
 I personally love Colorado.
 Colorado is great.
 Uh, yeah.
 I mean, you have these states that are, you know, like just way better run.
 Um, California is, you know, it's especially San Francisco.
 It's on a tie horse and like, yeah.
 Can I ask you for advice to me and to others about what's the take to build a successful
 startup?
 Oh, I don't know.
 I haven't done that.
 Talk to someone who did that.
 Well, you've, you know, uh, this is like another book of years that I'll buy for $67, I suppose.
 So there's, um, one of these days I'll sell out.
 Yeah, that's right.
 Jail breaks are going to be a dollar and books are going to be 67.
 How I, uh, how I jail broke the iPhone by George Hots.
 That's right.
 How I jail broke the iPhone and you can do 67 in 21 days.
 That's right.
 Oh God.
 Okay.
 You can't wait, but quite so you haven't introspective.
 You have built a very unique company.
 I mean, not, not you, but you and others, but I don't know.
 Um, there's no, there's nothing you haven't interest, but you haven't really sat down
 and thought about like, well, like if you and I were having a bunch of, we're having
 some beers and you're seeing that I'm depressed and whatever I'm struggling, there's no advice
 you can give.
 Oh, I mean more beer.
 Yeah, I think it's all very like situation dependent.
 Um, here's, okay.
 If I can give a generic piece of advice, it's the technology always wins.
 The better technology always wins and lying always loses.
 Build technology and don't lie.
 I'm with you.
 I agree very much.
 Long run, long run.
 Sure.
 It's the long run.
 You can remain irrational longer than you can remain solvent.
 True fact.
 Well, this is, this is an interesting point because I ethically and just as a human believe
 that, um, like, like hype and smoke and mirrors is not at any stage of the company is a good
 strategy.
 I mean, there's some like, you know, PR magic kind of like, you know, you want a new product.
 If there's a call to action, if there's like a call to action, like buy my new GPU, look
 at it.
 It takes up three slots and it's this big.
 It's huge.
 Buy my G for you.
 Yeah, that's great.
 If you look at, you know, especially in that, in AI space broadly, but autonomous vehicles,
 like you can raise a huge amount of money on nothing.
 And the question to me is like, I'm against that.
 I'll never be part of that.
 I don't think, I hope not willingly not, but like, is there something to be said to, uh,
 essentially lying to raise money, like fake it till you make it kind of thing?
 I mean, this is Billy McFarlane, the fire festival.
 Like we all, we all experienced, uh, you know, what happens with that.
 No, no, don't fake it till you make it be honest and hope you make it the whole way.
 The technology wins.
 Right.
 The technology wins.
 And like there is, I'm not, you just like the anti-hype, you know, that's, that's a
 Slava KPSS reference, but, um, hype isn't necessarily bad.
 I loved camping out for the iPhones.
 Um, you know, and as long as the hype is backed by like substance, as long as it's backed
 by something I can actually buy and like it's real, then hype is great.
 And it's a great feeling.
 It's when the hype is backed by lies that it's a bad feeling.
 I mean, a lot of people call Elon Musk a fraud.
 How could he be a fraud?
 I've noticed this, this kind of interesting effect, which is he does tend to over promise
 and deliver what's, what's the better way to phrase it?
 Promise a timeline that he doesn't deliver on.
 He delivers much later on.
 What do you think about that?
 Cause I do that.
 I think that's a programmer thing.
 I do that as well.
 You think that's a really bad thing to do or is that okay?
 I think that's again, as long as like you're working toward it and you're going to deliver
 on it and it's not too far off.
 Right.
 Right.
 Like, like, you know, the whole, the whole autonomous vehicle thing, it's like, I mean,
 I still think Tesla's on track to beat us.
 I still think even with their, even with their missteps, they have advantages.
 We don't have, um, you know, Elon is better than me at, at, at like marshaling massive
 amounts of resources.
 So, you know, I still think given the fact that they're maybe making some wrong decisions,
 they'll end up winning and like, it's fine to hype it if you're actually going to win.
 Right.
 Like if Elon says, look, we're going to be landing rockets back on earth in a year and
 it takes four, like, you know, he landed a rocket back on earth and he was working toward
 it the whole time.
 I think there's some amount of like, I think what it becomes wrong is if you know you're
 not going to meet that deadline.
 If you're lying.
 Yeah.
 That's brilliantly put.
 Like this is what people don't understand.
 I think like Elon believes everything he says as far as I can tell he does.
 And I detected that in myself too.
 Like if I, it's only bullshit.
 If you're like conscious of yourself lying.
 Yeah, I think so.
 Yeah.
 Now you can't take that to such an extreme, right?
 Like in a way I think maybe Billy McFarland believed everything he said too.
 Right.
 Like that's how you start a cult and then everybody kills themselves.
 Yeah.
 Yeah.
 Like it's, you need, you need, if there's like some factor on it, it's fine.
 And you need some people to like, you know, keep you in check.
 But like if you deliver on most of the things you say and just the timelines are off.
 It does piss people off though.
 I wonder, but who cares?
 In long arc of history, the people, everybody gets pissed off at the people who succeed,
 which is one of the things that frustrates me about this world is they don't celebrate
 the success of others.
 Like there's so many people that want Elon to fail.
 It's so fascinating to me.
 Like what is wrong with you?
 Like, so Elon Musk talks about like people short, like they talk about financial, but
 I think it's much bigger than the financials.
 I've seen like the human factors community, they want, they want other people to fail.
 What, why, why?
 Like even people, the harshest thing is like, you know, even people that like seem to really
 hate Donald Trump, they want him to fail or like the other president or they want Barack
 Obama to fail.
 It's like, it's weird, but I want that.
 I would love to inspire that part of the world to change because if the human species is
 going to survive, we should celebrate success.
 It seems like the efficient thing to do in this objective function that we're all striving
 for is to celebrate the ones that like figure out how to like do better at that objective
 function as opposed to like dragging them down back into the mud.
 I think there is, this is the speech I always give about the commenters on hacker news.
 So first off, something to remember about the internet in general is commenters are
 not representative of the population.
 I don't comment on anything.
 You know, commenters are representative of a certain sliver of the population.
 And on hacker news, a common thing I'll see is when you'll see something that's like,
 you know, promises to be wild out there and innovative, there is some amount of, you know,
 checking them back to earth, but there's also some amount of, if this thing succeeds, well,
 I'm 36 and I've worked at large tech companies my whole life.
 They can't succeed because if they succeed, that would mean that I could have done something
 different with my life, but we know that I couldn't have, we know that I couldn't have
 and that's why they're going to fail.
 And they have to root for them to fail to kind of maintain their world image.
 So, tune it out.
 And they comment, well, it's hard.
 So one of the things I'm considering startup wise is to change that.
 Because I think it's also a technology problem.
 It's a platform problem.
 I agree.
 It's like, because the thing you said most people don't comment, I think most people
 want to comment.
 They just don't because it's all the assholes who are commenting.
 Exactly.
 I don't want to be grouped in with them.
 You don't want to be at a party where everyone is an asshole.
 But that's a platform problem.
 I can't believe what Reddit's become.
 I can't believe the group think in Reddit comments.
 Reddit is an interesting one because there's subreddits.
 And so you can still see, especially small subreddits that are little like havens of
 like joy and positivity and deep, even disagreement, but like nuanced discussion.
 But it's only like small little pockets.
 But that's emergent.
 The platform is not helping that or hurting that.
 So I guess naturally something about the internet, if you don't put in a lot of effort to encourage
 nuance and positive good vibes, it's naturally going to decline into chaos.
 I would love to see someone do this well.
 I think it's very doable.
 I think actually, I feel like Twitter could be overthrown.
 Yashobach talked about how if you have like and retweet, that's only positive wiring.
 The only way to do anything like negative there is with a comment.
 And that's like that asymmetry is what gives Twitter its particular toxicness.
 Whereas I find YouTube comments to be much better because YouTube comments have a have
 a have an up and a down and they don't show the downloads.
 Without getting into depth of this particular discussion, the point is to explore possibilities
 and get a lot of data on it because I mean, I could disagree with what you just said.
 The point is it's unclear.
 It hasn't been explored in a really rich way.
 Like these questions of how to create platforms that encourage positivity.
 I think it's a technology problem.
 And I think we'll look back at Twitter as it is now.
 Maybe it'll happen within Twitter, but most likely somebody overthrows them.
 We'll look back at Twitter and say, can't believe we put up with this level of toxicity.
 You need a different business model too.
 Any social network that fundamentally has advertising as a business model.
 This was in the social dilemma, which I didn't watch, but I liked it.
 It's like, you know, there's always the, you know, you are the product, you're not the,
 but they had a nuanced take on it that I really liked.
 And it said the product being sold is influence over you.
 The product being sold is literally your influence on you.
 That can't be, if that's your idea, okay.
 Well, you know, guess what?
 It can't not be toxic.
 Yeah.
 Maybe there's ways to spin it like with, with giving a lot more control to the user and
 transparency to see what is happening to them as opposed to in the shadows as possible,
 but that can't be the primary source of.
 But the users aren't, no one's going to use that.
 It depends.
 It depends.
 I think, I think that the, you're, you're not going to, you can't depend on self-awareness
 of the users.
 It's a, it's another, it's a longer discussion because you can't depend on it, but you can
 reward self-awareness.
 Like if for the ones who are willing to put in the work of self-awareness, you can reward
 them and incentivize and perhaps be pleasantly surprised how many people are willing to be
 self-aware on the internet.
 Like we are in real life.
 Like I'm putting in a lot of effort with you right now being self-aware about if I say
 something stupid or mean, I'll like look at your body language.
 Like I'm putting in that effort.
 It's costly for an introvert, very costly, but on the internet, fuck it.
 Like most people are like, I don't care if this hurts somebody.
 I don't care if this is not interesting or if this is, yeah, it's a mean or whatever.
 I think so much of the engagement today on the internet is so disingenuine too.
 You're not doing this out of a genuine, this is what you think.
 You're doing this just straight up to manipulate others.
 Whether you're in, you just became an ad.
 Okay.
 Let's talk about a fun topic, which is programming.
 Here's another book idea for you.
 Let me pitch.
 What's your perfect programming setup?
 So like this by George Hots.
 So like what, listen, you're-
 Give me a MacBook Air, sit me in a corner of a hotel room and you know I'll still have
 food.
 I don't fetishize like multiple monitors, keyboard.
 Those things are nice and I'm not going to say no to them, but did they automatically
 unlock tons of productivity?
 No, not at all.
 I have definitely been more productive on a MacBook Air in a corner of a hotel room.
 What about IDE?
 So which operating system do you love?
 What text editor do you use?
 IDE?
 Is there something that is like the perfect, if you could just say the perfect productivity
 setup for George Hots.
 Doesn't matter.
 Doesn't matter.
 It literally doesn't matter.
 I guess I code most of the time in Vim.
 Literally I'm using an editor from the 70s.
 You didn't make anything better.
 Okay, VS code is nice for reading code.
 There's a few things that are nice about it.
 I think that there, you can build much better tools.
 How like IDA's xrefs work way better than VS codes.
 Why?
 Yeah, actually that's a good question.
 Like why?
 I still use, sorry, Emacs for most.
 I've actually never, I have to confess something dark.
 Yeah.
 I've never used Vim.
 I think maybe I'm just afraid that my life has been a waste.
 I'm so, I'm not evangelical about Emacs.
 This is how I feel about Tenderflow versus PyTorch.
 Everything just like we've switched everything to PyTorch now.
 Put months into the switch.
 I have felt like I've wasted years on TensorFlow.
 I can't believe it.
 I can't believe how much better PyTorch is.
 Yeah.
 I've used Emacs in Vim.
 Doesn't matter.
 Yeah, still just my heart somehow.
 I fell in love with Lisp.
 I don't know why.
 You can't, the heart wants what the heart wants.
 I don't understand it, but it just connected with me.
 Maybe it's the functional language that first I connected with.
 Maybe it's because so many of the AI courses before the deep learning revolution were taught
 with Lisp in mind.
 I don't know.
 I don't know what it is, but I'm stuck with it.
 But at the same time, like why am I not using a modern ID for some of these programming?
 I don't know.
 They're not that much better.
 I've used modern IDs too.
 But at the same time, so like to just, well not to disagree with you, but like I like
 multiple monitors.
 Like I have to do work on a laptop and it's a pain in the ass.
 And also I'm addicted to the Kinesis weird keyboard.
 You could see there.
 Yeah.
 So you don't have any of that.
 You can just be in a, on a Mac book.
 I mean, look at work.
 I have three 24 inch monitors.
 I have a happy hacking keyboard.
 I have a razor death header mouse.
 Like, but it's not essential for you.
 Let's go to a day in the life of George Hots.
 What is the perfect day productivity wise?
 So we're not talking about like Hunter S Thompson drugs.
 And let's look at productivity.
 Like what's the day look like?
 I'm like hour by hour.
 Is there any regularities that create a magical George Hots experience?
 I can remember three days in my life.
 And I remember these days vividly when I've gone through kind of radical transformations
 to the way I think and what I would give, I would pay a hundred thousand dollars if
 I could have one of these days tomorrow, the days have been so impactful.
 And one was first discovering Elias of Yudkowsky on the singularity and reading that stuff.
 And like, you know, my mind was blown.
 The next was discovering the Hunter price and that AI is just compression.
 Like finally understanding AIXI and what all of that was.
 You know, I like read about it when I was 18, 19, I didn't understand it.
 And then the fact that like lossless compression implies intelligence the day that I was shown
 that.
 And then the third one is controversial.
 The day I found a blog called Unqualified Reservations and read that and I was like,
 wait, which one is that?
 That's what's the guy's name?
 Curtis Yarvin.
 Yeah.
 So many people tell me I'm supposed to talk to him.
 Yeah.
 He sounds insane or brilliant, but insane or both.
 I don't know.
 I found that blog was another like, this was during like, like Gamergate and kind of the
 run up to the 2016 election.
 And I'm like, wow, okay, the world makes sense now.
 This is like, I had a framework now to interpret this.
 Just like I got the framework for AI and a framework to interpret technological progress.
 Like those days when I discovered these new frameworks were.
 Oh, interesting.
 So it's not about, but what was special about those days?
 How did those days come to be?
 Is it just you got lucky?
 Like.
 Sure.
 Like what, you just encountered a harder prize on, on hacking news or something like that?
 Like what?
 But you see, I don't think it's just, see, I don't think it's just that like, I could
 have gotten lucky at any point.
 I think that in a way.
 You were ready at that moment.
 Yeah, exactly.
 To receive the information.
 But is there some magic to the day today of like, like eating breakfast and it's the mundane
 things?
 Nah.
 Nothing.
 I drift through life.
 Without structure.
 I drift through life, hoping and praying that I will get another day like those days.
 And there's nothing in particular you do to, to be a receptacle for another, for day number
 four.
 No, I didn't do anything to get the other ones.
 So I don't think I have to really do anything now.
 I took a month long trip to New York and the Ethereum thing was the highlight of it, but
 the rest of it was pretty terrible.
 I did a two week road trip and I got, I had to turn around.
 I had to turn around and drive in Gunnison, Colorado, pass through Gunnison and the snow
 starts coming down.
 There's a pass up there called Monarch Pass in order to get through to Denver.
 You got to get over the Rockies.
 And I had to turn my car around.
 I couldn't, I watched, I watched F-150 go off the road.
 I'm like, I gotta go back.
 And like that day was meaningful because like, like it was real.
 Like I actually had to turn my car around.
 It's rare that anything even real happens in my life, even as mundane is the fact that
 yeah, there was snow.
 I had to turn around, stay in Gunnison and leave the next day.
 Something about that moment felt real.
 Okay.
 So actually it's interesting to break apart the three moments you mentioned if it's okay.
 So I always have trouble pronouncing his name, but Lousy Yurkowski.
 So what, how did your worldview change in starting to consider the, the exponential
 growth of AI and AGI that he thinks about and the, the, the threats of artificial intelligence
 and all that kind of ideas.
 Like, can you, is it like, can you maybe break apart like what exactly was so magical to
 you?
 It was a transformational experience.
 Today, everyone knows him for threats and AI safety.
 This was pre that stuff.
 There was, I don't think a mention of AI safety on the page.
 This is, this is old Yurkowski stuff.
 He'd probably denounce it all now.
 He'd probably be like, that's exactly what I didn't want to happen.
 Sorry, man.
 Is there something specific you can take from his work that you can remember?
 Yeah.
 It was this realization that computers double in power every 18 months and humans do not.
 And they haven't crossed yet, but if you have one thing that's doubling every 18 months
 and one thing that's staying like this, you know, here's your log graph.
 Here's your line.
 You know, you calculate that.
 And that, did that open the door to the exponential thinking?
 Like thinking that like, you know what, with technology we can actually transform the world.
 It opened the door to human obsolescence.
 It opened the door to realize that in my lifetime, humans are going to be replaced.
 And then the matching idea to that of artificial intelligence with the Hutter prize, you know,
 I'm torn.
 I go back and forth on what I think about it.
 But the, the, the basic thesis is it's nice.
 It's a nice compelling notion that we can reduce the task of creating an intelligent
 system, a generally intelligent system into the task of compression.
 So you can think of all of intelligence in the universe, in fact, as a kind of compression.
 Do you find that, was that just at the time you found that as a compelling idea or do
 you still find that a compelling idea?
 I still find that a compelling idea.
 I think that it's not that useful day to day, but actually one of maybe my quests before
 that was a search for the definition of the word intelligence.
 And I never had one.
 And I definitely have a definition of the word compression.
 It's a very simple, straightforward one.
 And you know what compression is, you know, lossless is lossless compression, not lossy,
 lossless compression.
 And that that is equivalent to intelligence, which I believe, I'm not sure how useful that
 definition is day to day, but like I now have a framework to understand what it is.
 And he just 10x the, the, the prize for that competition, like recently a few months ago,
 you ever thought of taking a crack at that?
 Oh, I did.
 Oh, I did.
 I spent, I spent the next, after I found the prize, I spent the next six months of my life
 trying it.
 And well, that's when I started learning everything about AI and then I worked with vicarious
 for a bit.
 And then I learned, read all the deep learning stuff and I'm like, okay, now I like I'm caught
 up to modern AI.
 Wow.
 And I had, I had a really good framework to put it all in from the compression stuff,
 right?
 Like some of the first, some of the first deep learning models I played with were, were
 gbt, gbt, basically, but before transformers, before it was still RNNs to do a character
 prediction.
 But by the way, on the compression side, I mean the, especially in neural networks, what
 do you make of the lossless requirement with the Hutter prize?
 So you know, human intelligence and neural networks can probably compress stuff pretty
 well, but there would be lossy.
 It's imperfect.
 You can turn a lossy compression into a lossless compressor pretty easily using an arithmetic
 encoder, right?
 You can take an arithmetic encoder and you can just encode the noise with maximum efficiency.
 Right?
 So even if you can't predict exactly what the next character is, the better a probability
 distribution you can put over the next character, you can then use an arithmetic encoder to,
 right?
 You don't have to know whether it's an E or an I, you just have to put good probabilities
 on them and then, you know, code those.
 And if you have, it's a bits of entropy thing, right?
 So let me, on that topic, it could be interesting as a little side tour.
 What are your thoughts in this year about GPT-3 and these language models and these
 transformers?
 Is there something interesting to you as an AI researcher or is there something interesting
 to you as an autonomous vehicle developer?
 Nah, I think, I think it's overhyped.
 I mean, it's not like it's cool.
 It's cool for what it is, but no, we're not just going to be able to scale up to GPT-12
 and get general purpose intelligence.
 Like your loss function is literally just, you know, you know, cross entropy loss on
 the character, right?
 Like that's not the loss function of general intelligence.
 Is that obvious to you?
 Yes.
 Can you imagine that like to play devil's advocate on yourself, is it possible that
 you can, the GPT-12 will achieve general intelligence with something as dumb as this kind of loss
 function?
 I guess it depends what you mean by general intelligence.
 So there's another problem with the GPTs and that's that they don't have a, they don't
 have long-term memory.
 Right.
 Right.
 So like just GPT-12, a scaled up version of GPT-2 or 3, I find it hard to believe.
 Well, you can scale it in, yeah, so it's a hard-coded length, but you can make it wider
 and wider and wider.
 Yeah.
 You're going to get, you're going to get cool things from those systems, but I don't think
 you're ever going to get something that can like, you know, build me a rocket ship.
 What about self-driving?
 So, you know, you can use transformer with video, for example.
 You think, is there something in there?
 No, because look, we use, we use a GRU.
 We use a GRU.
 It grew out to a transformer.
 I think driving is much more Markovian than language.
 So Markovian, you mean like the memory, which, which aspect of Markov chains?
 Markovian, I mean that like most of the information in the state at t minus one is also in the,
 is in state t.
 I see, yeah.
 Right.
 And it kind of like drops off nicely like this, whereas sometime with language, you
 have to refer back to the third paragraph on the second page.
 I feel like...
 There's not many, like, like you can say like speed limit signs, but there's really not
 many things in autonomous driving that look like that.
 But if you look at, to play devil's advocate is the risk estimation thing that you've talked
 about is kind of interesting is it feels like there might be some longer term aggregation
 of context necessary to be able to figure out like the context.
 I'm not even sure I'm believing my own devil's advocate.
 We have a nice, we have a nice like vision model, which outputs like a one or two four
 dimensional perception space.
 Can I try transformers on it?
 Sure.
 I probably will.
 At some point we'll try transformers and then we'll just see, do they do better?
 Sure.
 But it might not be a game changer.
 Well, I'm not like, like might transformers work better than grooves for autonomous driving?
 Sure.
 Might we switch?
 Sure.
 Is this some radical change?
 No.
 Okay.
 We used to slightly different, you know, we switched from RNNs to grooves, like, okay,
 maybe it's grooves to transformers, but no, it's not.
 Yeah.
 Well, on the, on the topic of general intelligence, I don't know how much I've talked to you about
 it.
 Like what, um, do you think we'll actually build an AGI?
 Like if you look at Ray Kurzweil with Singularity, do you have like an intuition about, you're
 kind of saying driving is easy.
 Yeah.
 And I tend to personally believe that solving driving will have really deep, important impacts
 on our ability to solve general intelligence.
 Like I think driving doesn't require general intelligence, but I think they're going to
 be neighbors in a way that it's like deeply tied because it's so like driving is so deeply
 connected to the human experience that I think solving one will help solve the other.
 But so I don't see, I don't see driving as like easy and almost like separate than general
 intelligence, but like what's your vision of a future with a singularity?
 Do you see there'll be a single moment, like a singularity where it'll be a phase shift?
 Are we in the singularity now?
 Like what, do you have crazy ideas about the future in terms of AGI?
 We definitely have the singularity now.
 We are?
 Of course, of course.
 Look at the bandwidth between people.
 The bandwidth between people goes up.
 All right.
 Um, the singularity is just, you know, when the bandwidth, but what do you mean by the
 bandwidth of people?
 Communications tools.
 The whole world is networked.
 The whole world is networked and we raise the speed of that network.
 Right.
 Oh, so you think the communication of information in a distributed way is a empowering thing
 for collective intelligence?
 Oh, I didn't say it's necessarily a good thing, but I think that's like, when I think of the
 definition of the singularity, yeah, it seems kind of right.
 I see.
 Like it's a change in the world beyond which like the world would be transformed in ways
 that we can't possibly imagine.
 No, I mean, I think we're in the singularity now in the sense that there's like, you know,
 one world and a monoculture and it's also linked.
 Yeah.
 I mean, I kind of share the intuition that the, the singularity will originate from the
 collective intelligence of us ants versus the, like some single system, AGI type thing.
 Oh, I totally agree with that.
 Yeah.
 I don't, I don't really believe in like, like a hard takeoff AGI kind of thing.
 Um, yeah, I don't think, I don't even think AI is all that different in kind from what
 we've already been building.
 With respect to driving, I think driving is a subset of general intelligence and I think
 it's a pretty complete subset.
 I think the tools we develop at Comma will also be extremely helpful to solving general
 intelligence and that's, I think the real reason why I'm doing it.
 I don't care about self-driving cars.
 It's a cool problem to beat people at.
 But yeah, I mean, yeah, you're kind of, you're of two minds.
 So one, you do have to have a mission and you want to focus and make sure you get, you
 get there, you can't forget that.
 But at the same time, there is a thread that's much bigger than, uh, that connects the entirety
 of your effort.
 That's much bigger than just driving with AI and with general intelligence, it is so
 easy to delude yourself into thinking you've figured something out when you haven't.
 If we build a level five self-driving car, we have indisputably built something.
 Yeah.
 Is it general intelligence?
 I'm not going to debate that.
 I will say we've built something that provides huge financial value.
 Yeah.
 Beautifully put.
 That's the engineering credo.
 Like just, just build the thing.
 It's like, uh, that's why I'm with, uh, with, uh, with, with the, on, uh, go to Mars.
 Yeah, it's a great one.
 You can argue like who the hell cares about going to Mars, but the reality is set that
 as a mission, get it done.
 Yeah.
 And then you're going to crack some pro problem that you've never even expected in the process
 of doing that.
 Yeah.
 And, and, you know, I think if I had a choice between humanity, going to Mars and solving
 self-driving cars, I think going to Mars is, uh, better, but I don't know, I'm more suited
 for self-driving cars.
 I'm an information guy.
 I'm not a modernist.
 I'm a post-modernist.
 Post-modernist.
 All right.
 Beautifully put.
 Let me, let me drag you back to programming for a sec.
 What three, maybe three to five programming languages should people learn?
 Do you think like, if you look at yourself, what did you get the most out of from learning?
 Uh, well, so everybody should learn C and assembly.
 We'll start with those two.
 Right.
 Assembly.
 Yeah.
 If you can't code in assembly, you don't know what the computer's doing.
 You don't understand, like, you don't have to be great in assembly, but you have to code
 in it.
 And then like, you have to appreciate assembly in order to appreciate all the great things
 C gets you.
 And then you have to code in C in order to appreciate all the great things Python gets
 you.
 So I'll just say assembly C and Python.
 We'll start with those three.
 The memory allocation of C and the, the, the fact that it's assembly is to give you a sense
 of just how many levels of abstraction you get to work on in modern day programming.
 Yeah.
 Yeah.
 Graph coloring for assignment, register assignment and compilers.
 Yeah.
 Like, you know, you got to do, you know, the compiler, your computer only has a certain
 number of registers, yet you can have all the variables you want in a C function.
 You know, so you get to start to build intuition about compilation, like what a compiler gets
 you.
 What else?
 Well, then there is, then there's kind of a, so those are all very imperative programming
 languages.
 Then there's two other paradigms for programming that everybody should be familiar with.
 One of them is functional.
 You should learn Haskell and take that all the way through, learn a language with dependent
 types like Coq.
 Learn that whole space, like the very PL theory, heavy languages.
 And Haskell is your favorite functional?
 Is that the go-to?
 Yeah, I'm not a great Haskell programmer.
 I wrote a compiler in Haskell once.
 There's another paradigm.
 And actually there's one more paradigm that I'll even talk about after that, that I never
 used to talk about when I would think about this.
 But the next paradigm is learn Verilog of HDL.
 Understand this idea of all of the instructions executed once.
 If I have a block in Verilog and I write stuff in it, it's not sequential.
 They all execute it once.
 And then like think like that.
 So hardware works.
 So I guess assembly doesn't quite get you that.
 Assembly is more about compilation and Verilog is more about the hardware.
 Like, giving a sense of what actually is the hardware is doing.
 Assembly C, Python are straight, like they sit right on top of each other.
 In fact, C is, well, C is kind of coded in C, but you could imagine the first C was coded
 in assembly and Python is actually coded in C. So, you know, you can straight up go on
 that.
 Got it.
 And then Verilog gives you, that's brilliant.
 Okay.
 And then I think there's another one now.
 Everyone's Carpathi calls it programming 2.0, which is learn a, I'm not even going to,
 don't learn TensorFlow, learn PyTorch.
 So machine learning.
 We've got to come up with a better term than programming 2.0.
 But yeah.
 It's a programming language.
 I wonder if it can be formalized a little bit better.
 It feels like we're in the early days of what that actually entails.
 Data driven programming.
 Data driven programming.
 Yeah.
 But it's so fundamentally different as a paradigm than the others.
 Like it almost requires a different skill set.
 But you think it's still, yeah.
 And PyTorch versus TensorFlow, PyTorch wins.
 It's the fourth paradigm.
 It's the fourth paradigm that I've kind of seen.
 It's like this, you know, imperative functional hardware.
 I don't know a better word for it.
 And then ML.
 Do you have advice for people that want to, you know, get into programming, want to learn
 programming?
 You have a video.
 What is programming new blessings?
 Exclamation point.
 And I think the top comment is like warning.
 This is not for noobs.
 Do you have a noob like TLDW for that video, but also a noob friendly advice on how to
 get into programming?
 You are never going to learn programming by watching a video called learn programming.
 The only way to learn programming, I think, and the only one is the only way everyone
 I've ever met who can program well learned it all in the same way.
 They had something they wanted to do and then they tried to do it and then they were like,
 oh, well, okay, this is kind of, you know, it'd be nice if the computer could kind of
 do this thing.
 And then, you know, that's how you learn.
 You just keep pushing on a project.
 So the only advice I have for learning programming is go program.
 Somebody wrote to me a question like, we don't really, they're looking to learn about recurrent
 neural networks.
 And saying like, my company's thinking of using recurrent neural networks for time series
 data, but we don't really have an idea of where to use it yet.
 We just want to, like, do you have any advice on how to learn about, these are these kind
 of general machine learning questions.
 And I think the answer is like, actually have a problem that you're trying to solve and
 just.
 I see that stuff.
 Oh my God.
 When people talk like that, they're like, I heard machine learning is important.
 Would you help us integrate machine learning with macaroni and cheese production?
 You just, I don't even, you can't help these people.
 Like, who lets you run anything?
 Who lets that kind of person run anything?
 I think we're all, we're all beginners at some point.
 So it's not like they're a beginner.
 It's like, my problem is not that they don't know about machine learning.
 My problem is that they think that machine learning has something to say about macaroni
 and cheese production.
 Or like, I heard about this new technology.
 How can I use it for why?
 Like, I don't know what it is, but how can I use it for why?
 That's true.
 You have to build up an intuition of how, because you might be able to figure out a
 way, but like the prerequisite is you should have a macaroni and cheese problem to solve
 first.
 Exactly.
 And then two, you should have more traditional, like the learning process should involve more
 traditionally applicable problems in the space of whatever that is, machine learning, and
 then see if it can be applied to that competition.
 At least start with, tell me about a problem.
 Like if you have a problem, you're like, you know, some of my boxes aren't getting enough
 macaroni in them.
 Can we use machine learning to solve this problem?
 That's much, much better than how do I apply machine learning to macaroni and cheese?
 One big thing, maybe this is me talking to the audience a little bit, because I get these
 days so many messages, advice on how to like learn stuff.
 Okay.
 This is not me being mean.
 I think this is quite profound actually, is you should Google it.
 Oh yeah.
 One of the skills that you should really acquire as an engineer, as a researcher, as a thinker,
 like one, there's two complimentary skills, like one is with a blank sheet of paper with
 no internet to think deeply.
 And then the other is to Google the crap out of the questions you have.
 That's actually a skill people often talk about, but like doing research, like pulling
 at the thread and like looking up different words, going into like GitHub repositories
 with two stars and like looking how they did stuff, like looking at the code or going on
 Twitter, seeing like there's little pockets of brilliant people that are like having discussions.
 Like if you're a neuroscientist, go into signal processing community.
 If you're an AI person going into the psychology community, like switch communities, like keep
 searching, searching, searching, because it's so much better to invest in like finding somebody
 else who already solved your problem than it is to try to solve the problem.
 Because they've often invested years of their life, like entire communities are probably
 already out there who have tried to solve your problem.
 I think they're the same thing.
 I think you go try to solve the problem and then in trying to solve the problem, if you're
 good at solving problems, you'll stumble upon the person who solved it already.
 But the stumbling is really important.
 I think that's a skill that people should really put, especially in undergrad, like search.
 If you ask me a question, how should I get started in deep learning, like especially,
 like that is just so Googleable.
 Like the whole point is you Google that and you get a million pages and just start looking
 at them.
 Start pulling at the threads, start exploring, start taking notes, start getting advice from
 a million people that have already like spent their life answering that question actually.
 Oh, well, yeah, I mean, that's definitely also, yeah, when people like ask me things like
 that, I'm like, trust me, the top answer on Google is much, much better than anything
 I'm going to tell you.
 Right?
 Yeah.
 People ask, it's an interesting question.
 Let me know if you have any recommendations.
 What three books, technical or fiction or philosophical, had an impact on your life or you would recommend
 perhaps?
 Maybe we'll start with the least controversial, Infinite Jest.
 Infinite Jest is a-
 David Foster Wallace?
 Yeah, it's a book about wireheading really.
 Very enjoyable to read, very well written.
 You will grow as a person reading this book, its effort.
 And I'll set that up for the second book, which is pornography.
 It's called Atlas Shrugged, which-
 Atlas Shrugged is pornography?
 Yeah, I mean, it is.
 I will not defend the, I will not say Atlas Shrugged is a well-written book.
 It is entertaining to read certainly, just like pornography.
 The production value isn't great.
 There's a 60 page monologue in there that Anne Rand's editor really wanted to take out and
 she paid, she paid out of her pocket to keep that 60 page monologue in the book.
 But it is a great book for a kind of framework of human relations.
 And I know a lot of people are like, yeah, but it's a terrible framework.
 Yeah, but it's a framework.
 Just for context, in a couple of days I'm speaking with, for probably four plus hours
 with Yaron Brook, who's the main living remaining objectivist.
 Objectivist.
 Interesting.
 So, I've always found this philosophy quite interesting on many levels.
 One of how repulsive some percent of, large percent of the population find it, which is
 always funny to me when people are like unable to even read a philosophy because of some,
 I think that says more about their psychological perspective on it.
 But there is something about objectivism and Anne Rand's philosophy that's deeply connected
 to this idea of capitalism, of the ethical life is the productive life.
 That was always compelling to me.
 I didn't seem to interpret it in the negative sense that some people do.
 To be fair, I read that book when I was 19.
 So you had an impact at that point.
 Yeah.
 And the bad guys in the book have this slogan, from each according to their ability to each
 according to their need.
 And I'm looking at this and I'm like, these are the most, this is Team Rocket level cartoonishness.
 Right?
 No bad.
 And then when I realized that was actually the slogan of the Communist Party, I'm like,
 wait a second.
 Wait, no, no, no, no, no.
 You're telling me this really happened?
 Yeah, it's interesting.
 I mean, one of the criticisms of her work is she has a cartoonish view of good and evil.
 Like the reality, as Jordan Peterson says, is that each of us have the capacity for good
 and evil in us as opposed to like, there's some characters who are purely evil and some
 characters that are purely good.
 And that's in a way why it's pornographic.
 The production value.
 I love it.
 Like, evil is punished and there's very clear, like, you know, there's no, there's no, you
 know, just like porn doesn't have, you know, like character growth.
 Well, you know, neither does Alan Sherwood.
 Like, really well put.
 But 19 year old George Hotz, it was, it was good enough.
 Yeah.
 Yeah.
 What, what's the third, you have something?
 I could give these, these two, I'll just throw out.
 They're sci-fi, Perputation City.
 Great thing to start thinking about copies of yourself.
 And then, um, that is, uh, Greg Egan.
 Uh, he's a, that might not be his real name.
 Some Australian guy might not be Australian.
 I don't know.
 Um, and then this one's online.
 It's called the Metamorphosis of Prime Intellect.
 Um, it's a story set in a post-singularity world.
 It's interesting.
 Is there, uh, can you, either of the worlds, do you find something, uh, philosophically
 interesting in them that you can comment on?
 I mean, it is clear to me that, uh, Metamorphosis of Prime Intellect is like written by an engineer,
 uh, which is, it's very, it's very almost a pragmatic take on a utopia in a way.
 Positive or negative?
 Is that?
 Well, that's up to you to decide reading the book.
 And the ending of it is very interesting as well.
 And I didn't realize what it was.
 I first read that when I was 15.
 I've reread that book several times in my life and it's short.
 It's 50 pages.
 Everyone should go read it.
 What's, uh, sorry, this is a little tangent.
 I've been working through the foundation.
 I've been, I haven't read much sci-fi in my whole life and I'm trying to fix that.
 Uh, the last few months, that's been a little side project.
 What's, uh, to you is the greatest sci-fi novel, uh, that, uh, people should read or
 is that, or?
 I mean, I would, I would, yeah, I would, I would say like, yeah, permutation city,
 metamorphosis, primal intellect.
 Um, I don't know.
 I didn't like foundation.
 Uh, I thought it was way too modernist.
 Um, do you like dune and like all of those?
 I've never read dune.
 I've never read dune.
 I have to read it.
 Uh, fire upon the deep is interesting.
 Uh, okay.
 I mean, look, everyone should read, everyone should read Neuromancer.
 Everyone should read Snow Crash.
 If you haven't read those, like start there.
 Um, yeah, I haven't read Snow Crash.
 Never read Snow Crash.
 Oh, it's, it's very entertaining.
 Go to Lester Bach.
 And if you want the controversial one, Bronze Age Mindset.
 All right.
 I'll look into that one.
 Those aren't sci-fi, but just around that books.
 So a bunch of people asked me on Twitter and Reddit and so on for advice.
 So what advice would you give a young person today about life?
 Another, what, uh, yeah, I mean, looking back, especially when you're a young person,
 or younger, you did, uh, and you continued it, you've accomplished a lot of interesting
 things.
 Is there some advice from those?
 From that life of yours that you can pass on?
 If college ever opens again, I would love to give a graduation speech.
 Um, at that point I will put a lot of somewhat satirical effort into this question.
 Yeah.
 At this, you haven't written anything at this point.
 Oh, you know what?
 These were sunscreen, this is water.
 Like you're plagiarizing.
 I mean, but that's the, that's the like, clean your room, you know, you can play drugs from,
 from all of this stuff.
 And it's, it's, there is no self-help books aren't designed to help you.
 They're designed to make you feel good.
 Like whatever advice I could give, you already know.
 Everyone already knows.
 Sorry, it doesn't feel good.
 Right?
 Like, you know, you know, if, if I tell you that you should, you know, eat well and, and,
 and read more and it's not going to do anything.
 I think the whole like genre of those kinds of questions is, is, is meaningless.
 I don't know.
 If anything, it's don't worry so much about that stuff.
 Don't be so caught up in your head.
 Right.
 I mean, you're yeah, in the sense that your whole life, if your whole existence is like
 moving version of that advice, I don't know.
 There's there's something, I mean, there's something in you that resists that kind of
 thinking and that in itself is, it's just illustrative of who you are.
 And there's something to learn from that.
 I think you're, you're clearly not overthinking stuff.
 Yeah.
 And you know what, I, even when I talk about my advice, I'm like, my advice is only relevant
 to me.
 It's not relevant to anybody else.
 I'm not saying you should go out.
 If you're the kind of person who overthinks things to stop overthinking things, it's not
 bad.
 It doesn't work for me.
 Maybe it works for you.
 I, you know, I don't know.
 Let me ask you about love.
 Yeah.
 Uh, so I think the last time we talked about the meaning of life and it was, it was kind
 of about winning.
 Of course.
 Uh, I don't think I've talked to you about love much, whether romantic or just love for
 the common humanity amongst us all.
 What role has love played in your life in this, in this quest for winning, where does
 love fit in?
 Well, the word love, I think means, uh, several different things.
 There's, uh, love in the sense of maybe I could just say there's like love in the sense
 of opiates and love in the sense of, uh, oxytocin and then love in the sense of maybe like a
 love for math.
 I don't think fits into either of those first two paradigms.
 Uh, so each of those, have they, uh, have they, have they given something to you in
 your life?
 I'm not that big of a fan of the first two.
 Um, why?
 For the same reason I'm not a fan of, you know, for the same reason I don't do opiates
 and don't take ecstasy.
 Right?
 And there were times, look, I've tried both.
 Um, I like opiates way more than I like ecstasy.
 Uh, but they're not the ethical life is the productive life.
 So maybe that's my problem with, with, with those.
 And then like, yeah, a sense of, I don't know, like abstract love for humanity.
 I mean, the abstract love for humanity.
 I'm like, yeah, I've always felt that.
 And I guess it's hard for me to imagine not feeling it.
 And maybe there's people who don't and I don't know.
 Yeah.
 That's just like a background thing that's there.
 I mean, since we brought up drugs, let me ask you, this is becoming more and more a
 part of my life.
 I've been talking to a few researchers that are working on psychedelics.
 I've eaten shrooms a couple of times and it was fascinating to me that like the mind can
 go like, just fascinating.
 The mind can go to places I didn't imagine it could go.
 And I was very friendly and positive and exciting and everything was kind of hilarious in the
 place.
 Wherever my mind went, that's where I went is, uh, what do you think about psychedelics?
 Do you think they have?
 What do you think the mind goes?
 Have you done psychedelics?
 Where do you think the mind goes?
 Is there something useful to learn about the places it goes?
 Once you come back?
 You know, I find it interesting that this idea that psychedelics have something to teach
 is almost unique to psychedelics, right?
 People don't argue this about amphetamines.
 And I'm not really sure why.
 I think all of the drugs have lessons to teach.
 I think there's things to learn from opiates.
 I think there's things to learn from amphetamines.
 I think there's things to learn from psychedelics, things to learn from marijuana.
 But also at the same time, recognize that I don't think you're learning things about
 the world.
 I think you're learning things about yourself.
 Yes.
 Um, and you know, what's the, even, it might've even been, uh, might've even been a Timothy
 Leary quote.
 I don't know if it's a monomist quote, but the idea is basically like, you know, everybody
 should look behind the door, but then once you've seen behind the door, you don't need
 to keep going back.
 Um, so I mean, and that's my thoughts on all real drug use too.
 So maybe for caffeine.
 It's a little experience that, uh, it's good to have, but.
 Oh yeah.
 No, I mean, yeah, I guess.
 Yeah.
 Psychedelics have definitely, um, so you're a fan of new experiences, I suppose.
 Yes.
 And it contains a little, especially the first few times it contains some lessons that can
 be picked up.
 Yeah.
 And I'll, I'll, I'll revisit psychedelics maybe once a year.
 Um, usually small, smaller doses.
 Maybe they turn up the learning rate of your brain.
 I've heard that like that.
 Yeah, that's cool.
 Big learning rates have pros and cons.
 Last question.
 And this is a little weird one, but you've called yourself crazy in the past.
 Uh, first of all, honestly, I think.
 On a scale of one to 10, how crazy would you say are you?
 Oh, I mean, it depends how you, you know, when you compare me to Elon Musk and Anthony
 Levandowski, not so crazy.
 So like, like a seven.
 Let's go with six.
 Six, six, six.
 What, uh, I like seven, seven's a good number.
 Seven.
 All right.
 Well, yeah, I'm sure day by day changes, right?
 So, but you're in that, in that area, what, uh, in thinking about that, what do you think
 is the role of madness?
 Is that a feature or a bug if you were to dissect your brain?
 So okay.
 From like a, like mental health lens on crazy, I'm not sure I really believe in that.
 I'm not sure I really believe in like a lot of that stuff, right?
 This concept of, okay, you know, when you get over to like, like, like, like hardcore
 bipolar and schizophrenia, these things are clearly real, somewhat biological.
 And then over here on the spectrum, you have like ADD and oppositional defiance disorder.
 And these things that are like, wait, this is normal spectrum human behavior.
 Like this isn't, you know, where's the, the line here and why is this like a problem?
 So there's this whole, you know, the neurodiversity of humanity is huge.
 Like people think I'm always on drugs.
 People are always saying this to me on my streams and like guys, you know, like I'm
 real open with my drug use.
 I'd tell you if I was on drugs and, oh yeah, I had like a cup of coffee this morning, but
 other than that, this is just me.
 You're witnessing my brain in action.
 So the word madness doesn't even make sense in the rich neurodiversity of humans.
 I think it makes sense, but only for like some insane extremes.
 But if you are actually like visibly hallucinating, you know, that's okay.
 But there is the kind of spectrum on which you stand out.
 Like that, that's a, like if I were to look, you know, at decorations on a Christmas tree
 or something like that, like if you were a decoration out, that would catch my eye.
 Like that thing is sparkly.
 Whatever the hell that thing is.
 There's something to that.
 Just like refusing to be boring or maybe boring is the wrong word, but to, yeah, I mean, be
 willing to sparkle, you know?
 It's like somewhat constructed.
 I mean, I am who I choose to be.
 I'm going to say things as true as I can see them.
 I'm not going to lie.
 But that's a really important feature in itself.
 So like whatever the neurodiversity of your, whatever your brain is, not putting constraints
 on it that force it to fit into the mold of what society is like defines what you're supposed
 to be.
 So you're one of the specimens that doesn't mind being yourself.
 Being right is super important, except at the expense of being wrong.
 Without breaking that apart, I think it's a beautiful way to end it.
 George, you're one of the most special humans I know.
 It's truly an honor to talk to you.
 Thanks so much for doing it.
 Thank you for having me.
 Thanks for listening to this conversation with George Hatz.
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 And now, let me leave you with some words from the great and powerful Linus Torvald.
 Talk is cheap.
 Show me the code.
 Thank you for listening and hope to see you next time.