The following is a conversation with George Hots, a.k.a. Geohot, his second time in 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. I'm sure we'll

talk many more times on this podcast. Quick mention of a sponsor followed by some thoughts

related to the episode. First is ForSigmatic, the maker of delicious mushroom coffee. Second

is the coding 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 comma AI, Tesla autopilot and perhaps others like Cadillac supercruiser 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 up a podcast, follow on Spotify, support on Patreon or connect with me

on Twitter at Lex Friedman. And now here's my conversation with George Hottz. 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 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? Have we lasted pretty good? How do we do?

Yeah. I mean, not quite yet. I tell you, as Yuckowski, 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. 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. Actually, this is what I really like about

cryptography. Cryptography, it seems like we live in a world where the defense wins

versus nuclear weapons. The opposite is true. It is much easier to build a warhead that splits

into 100 little warheads than to build something that can take out 100 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. Because 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 orbital trajectory, send a rocket to somebody.

So okay, your intuition that there were intelligent civilizations out there,

but it's very possible that they're no longer there. It's kind of a sad picture.

They enter some steady state. They all wirehead themselves.

What's wirehead?

Stimulate their pleasure centers and just live forever in this kind of stasis.

Oh. 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?

About 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, right? 70,000 light years is nothing.

For some possible technology that you can imagine that can 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 sub light travel,

and you'd have taken over the whole universe. That clearly didn't happen. So something stopped it.

So you mean for like a few million years, if you sent out probes that travel close,

what's sub light? You mean close to the speed of light?

Let's say 0.1c.

And it just spreads. Interesting. Actually, that's an interesting calculation.

So what makes you think that we'd be able to communicate with them?

Why do you think we would be able to comprehend

intelligent lies that are out there? Even if they were among this kind of thing,

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 Steven 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

computation swimming around, how do we know they're not already here?

How do we know that 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 their 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 could have a fundamentally different physics, you know, like that we just don't even

comprehend. Well, I think, okay, 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

their remnants of our, be able to detect our modern civilization? 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.

Oh, 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 50s tracks of music.

True. And yeah, I mean, they'd have to do, 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, having talked to David Fravor. I don't know if you caught

what 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. Two, 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, some 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 David Fravor,

who is a Navy pilot, who's, you know, as legit as it gets in terms of humans who are able to

perceive things in the environment and make conclusions, whether those things are a 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 TikTok that moved in all kinds of weird

ways. They don't know what it is. It could be technology developed by the United States,

and they're just not aware of it and the surface level from the Navy, right? It could be different

kind 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 scythe. 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 MK Ultra kind of thing,

you know? What do you mean? Like, they made some weird thing and they called it an alien spaceship.

You know, maybe it was just to like stimulate young physicists minds and 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 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 60s 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. Well, 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 used to control information by censoring it. Then the internet happened and governments

were 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 as 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 this flag is everywhere. That's one way to maintain privacy,

right? 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 is the real one. This could be fake

right now. Classic steganography technique. Okay, another absurd question about intelligent life

because 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 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? And 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 are 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 wouldn't be that crazy.

Well, it's difficult to compile DNA to Python and then to C. There is a little bit of a gap

in the kind of languages we use for touring machines and the kind of languages nature seems

to use a little bit. Maybe that's just we just haven't understood the kind of language that

nature uses as well yet. DNA is a CAD model. It's not quite a programming language. It has no sort

of serial execution. It's not quite a CAD model. So, I think in that sense we actually

completely understand it. The problem is simulating on these CAD models. I played with it a bit this

year is super computationally intensive. If you want to go down to like the molecular level

where you need to go to see a lot of these phenomenon like protein folding. So, yeah,

it's not that we don't understand it. It just requires a whole lot of compute to kind of compile

it. For human minds it's inefficient both for the data representation and for the programming.

It runs well on raw nature. It runs well on raw nature and when we try to build

emulators or simulators for that, well the mad sloth kind of tried it.

It runs in that, yeah, you've commented elsewhere. I don't remember where that one of the problems

is simulating nature is tough. And if you want to sort of deploy a prototype, I forgot how you

put it but it made me laugh, but animals or humans would need to be involved in order to

you know, to try to run some prototype code on like if we're talking about COVID and viruses and so

on. Yeah. If you were to try 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 crazy biology in test tubes. I think

my bigger complaint is more all the tools are so bad. Like literally you mean like like

libraries and I don't know. I'm not pipetting shit. Like your hand in me, I gotta, no, no, no,

there has to be some like automating stuff and like the human biology is messy. Like it seems like

look at those Taranos videos. They were joke. It's like a little gantry. It's like a little

xy gantry high school science project with the pipet. I'm like, really? Gotta 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 pipet

50 milliliters of solution, I'm out. This is so crude. Yeah. Okay, 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

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, 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 byte code? Yeah. And not just humble ourselves, but like,

I'm not trying to like make people 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.

Everyone knows that's kind of fun. I'm referring more to like, economy, you know, this idea that

we got up our stock price. Or 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 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, 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 more cruel

than 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

Hott's 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 an 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. Isn't that beautiful? I know if you play Diablo, they used to have, I think, cow level

where it's, so everybody will go just, they figured out this, like the best way to gain

experience points. This is 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 they're 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 a year time in cow level. 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 joints on

weird dopamine drug kind of way. So you don't like those games. You don't think that's us humans

feeling the nature. And that was the point of the talk. So how do we hack it then?

Well, I want to live forever. And this is the goal. Well, that's a game against nature.

Yeah. Immortality is the good objective function to you.

I mean, start there and then you can do whatever else you want because you've got a long time.

What if immortality makes the game just totally not fun? I mean, 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, how long do you think you'd live?

Until I get bored.

See, I don't think people, like brilliant people like you that really ponder

they're living a long time, are really considering how meaningless life becomes.

Well, I want to know everything and then I'm ready to die.

As long as there's...

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.

Bukowski talked about love like that.

Then let me solve immortality. 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. All right? I'm okay with some self manipulation like that. I'm okay with

deceiving myself. Oh, 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. Revert, yeah.

Well, 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 copies.

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.

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. So...

That's what you say now because your life is finite.

You know, I think self modifying systems comes up with all these hairy complexities.

And can I promise that I'll do it perfectly? No.

But I think I can put good safety structures in place.

So that talk and your thinking here is not literally referring to a simulation in that our

universe is a kind of computer program running on 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 like 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?

Like somebody on Twitter asked George what signs we would look for

to know whether or not we're in the simulation, which is exactly what you're asking is like

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.

Yeah. 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, you know, 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.

Yeah, yeah, yeah.

And thereby discover shortcut.

Yeah. Maybe a memory leak means the other thing as well,

but I mean like, yeah, like an ability to read arbitrary memory.

Yeah.

Right. And that one's not that horrifying.

All right. The right ones start to be horrifying.

Read it. Right. So the reading is not the problem.

Yeah. It's like Heartbleed 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, even without that,

like even some of the, you know, the nanotech stuff that's coming, I think.

I don't know if you're paying attention, but actually,

Eric Weisstein 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, Steven Wolfram's theory of everything,

of like, hypergraphs is super interesting and beautiful.

But 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 like a 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,

yo, I want, I want, I want the clarity of that.

I want a hundred gigahertz processors.

I want transistors that are smaller than atoms.

I want like power.

That's, 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 Haas?

Is it thousands of distributed hackers across the world?

Is it governments?

You know, is it Mark Zuckerberg?

There's a lot of people that,

I don't know if anyone trusts anyone 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 company, 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.

Can you tell me the story 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 optimism is the spin, the company's called Optimism.

It's a 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 the blockchain's already so secure.

Can we trade some of that off for speed?

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 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 cryptocurrency, 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 turned complete.

Ethereum is not technically turned complete with a gas limit, but close enough.

With a gas limit?

What's the gas limit?

Resources?

Yeah, I mean, no computer is actually turned complete.

They're just fine at RAM.

You know, guys, I can actually solve the whole problem.

What's the word gas limit?

You just have so many brilliant words.

I'm not even going to ask.

Well, that's not my word.

That's Ethereum's word.

Gas limit.

Ethereum, you have to spend gas per instruction.

So like different op codes, you 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,

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 just have to make sure

that 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 kind of systems.

So it's effectively a sandbox which runs contracts.

And like just like any kind of normal sandbox,

you have to replace syscalls with calls into the hypervisor.

Uh, 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 is doing a rendering.

Can't, for example, read a file from the file system.

Yeah.

It has, if it 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 a hypervisor process

or like, I don't know what it'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, 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.

Yeah.

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, 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 called 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?

All 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 I'm like, well, okay.

And yeah.

You wrote the compiler.

Yeah, I modified.

I wrote a 300 line diff to the compiler.

It's on source.

You can look at it.

Yeah, I looked at the code last night.

Yeah, it's cute.

Yeah, exactly.

Oh, too massive.

Cute is a good word for it.

And it's C++.

C++, yeah.

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, the people who I was working for were amused that I said that.

It doesn't really mean anything.

Okay.

Yeah, 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.

Yeah.

What are your thoughts on crypto in general?

So, what parts technically or philosophically define especially beautiful maybe?

Oh, 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 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 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?

Well, okay.

That's brilliant.

Oh, 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 we have even something as simple as a safety deposit box.

A 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.

Let's say somebody dies and now we're going to go through a big legal dispute about whether,

oh, was it in the will?

Was it not in the will?

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.

And that's what all businesses want is certainty.

You know, they say businesses don't care via YouTube.

YouTube's like, look, we don't care which way this lawsuit goes.

Just please tell us so we can have certainty.

And I wonder how many agreements in this, because we're talking about financial transactions

only in this case, correct?

The smart contracts.

Oh, you can go to anything.

You can put a prenup in the theorem blockchain.

Married smart contract.

Sorry, divorce lawyer.

Sorry, you're going to be replaced by Python.

Okay, so 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 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.

People can look it up, but I'm like, wow.

Ethereum seems, the governance of Ethereum seems much better.

I've come around a bit on proof of stake ideas.

Because very smart people thinking about some things.

Yeah, governance is interesting.

It does feel like Vitalik, it does feel like it opens,

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.

Geniuses are helpful, like Vitalik.

Right.

Yeah, brilliant.

Leaders, I mean.

Are not necessarily, yeah.

So you think the reason he's the face of Ethereum is because he's a genius.

That's interesting.

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?

Right.

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.

What's Bayes rule?

Yeah, I mean, even, oh, wow, you're hurting my brain.

My standard was even lower, but I would have loved to see

just this 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 education history.

They just 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 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.

Because I've seen that with programmers too, right?

That's what great programmers do.

But yeah, it would be, 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 100 years, it's not the case, right?

Crypto world has one very powerful idea going for it.

And that's the idea of forks, right?

I mean, 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 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.

Yeah, like different business strategies and then try them out and see what works.

Like even take, yeah, take common 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

in all these different versions and see.

The beauty of common AI is someone can actually do that.

Please take common 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.

And 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.

And 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 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, 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 overall 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.

You eventually, the hilarity of this, especially since this is recorded,

it will reveal beautifully the absurdity when you finally do publish this book.

That guarantee you will.

The story of comma AI, maybe it'll be a biography written about you.

That'll be, that'll be better, I guess.

And 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.

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 don't know if there's a device on that, but it is an interesting curiosity.

When you become really busy, you're running a company.

Hard time.

Yeah.

But like, there's a natural inclination and trend, like just 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 get really good at certain things and it sucks trying things that you're not good at,

like trying to figure them out.

When you do this with your live streams, you're on the fly figuring stuff out.

You don't mind looking dumb.

You just figured out, figured out pretty quickly.

Sometimes I try things and I don't figure them out.

You fail.

My chest rating is like a 1400 despite putting like a couple of hundred hours in.

It's 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 stream.

All right.

Let's talk about Kama 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 shipable 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?

Deliver and shipable 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 are 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 able to do that.

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 cruise 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 kind of real capitalism.

Common is 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 $1,000 comma two from us, we're providing them at least $1,000 of value, but they wouldn't buy it.

Brilliant.

So can you give a world wind overview of the products that Kamiai provides 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 comma two.

Which is a piece of hardware with cameras.

So the comma two, 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 comma two are the same.

You're the same?

I have a little more compute than it.

It only has like the same computer.

How interesting.

B, you know.

You're more efficient energy wise for the compute you're doing.

Far more efficient energy wise.

20 pay to flops, 20 wants, crazy.

Do you lack consciousness?

Sure.

Do you fear death?

You do.

You want immortality?

Of course I fear death.

Does Kamiai fear death?

I don't think so.

I don't think so.

Of course it does.

It very much fears, well, fears negative loss.

Oh, yeah.

Okay.

So comma two, when did that come out?

That was a year ago?

No, two.

Early this year.

Wow.

Time, it feels, yeah.

To 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 comma two, feature wise?

So, I mean, maybe you can also link 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 is it, its features and capabilities?

I think our slogan summarizes it well.

Comma slogan is make driving chill.

I love it.

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 stay in the lane

and do it better and better and better over time.

That'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, 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 Wi Fi radio, it has an LTE radio, it has a screen.

We use every part of the cell phone.

And then the interface of the car is specific to the car,

so you keep supporting more and more cars.

Yeah, through the interface of the car, I mean,

the device itself just has four can buses,

has four can interfaces on it,

they're 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, what's a blob of weights?

What do you expect?

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 connects, it's the glue that connects everything together.

Runs the sensors, does a bunch of calibration

for the neural network, does, 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 can 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,

we would 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,

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 entrained on actual behavior of drivers

when they're driving the car manually.

And 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?

We have a lot of high quality data, right?

Like more than you need in the center.

Well, we've way more than we do.

We've way more data than we need.

I mean, 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 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 intelligence systems,

you have to pick data well, right?

And so would you have any hints, ideas of how to do it well?

So 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 in reinforcement learning,

the data depends on the weights.

Yeah.

Right?

And actually, both ways.

That's poetry.

So 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 it's supposed to be supervised.

It is definitely supposed to be supervised.

And we enforce the fact that it's supervised.

We look at our rate of improvement in disengagement.

OpenPilot now has an unplanned disengagement

about every 100 miles.

This is up from 10 miles, like maybe a year ago.

Yeah.

So maybe we've seen 10x improvement in a year,

but 100 miles is still a far cry from the 100,000 you're

going to need.

So you're going to somehow need to get three more 10xs in there.

And 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, 10x 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 100 gigahertz

processors tomorrow, right?

Like 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 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, the traffic light

detection, drivable area segmentation,

you know, vehicle, bicycle pedestrian detection.

There's some localization tasks in there.

Also predicting, like, yeah, predicting how the entities

in the scene are going to move.

Like everything is basically a machine learning task

where there'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, they're a good old cone guy.

They 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 tasks, supervised, trained

on the data of the actual driving of people they

use comma AI, like actual human drivers do 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 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.

Oh, 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 just have a few that work in the bishop, a few

that work in the Rook.

But is that not ludicrous today to think about in

the 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?

End to end is going to be the only solution for level five.

For the only way we get there.

Of course, and of course Tesla is going to come

around to my way.

And if you're a Rook guy out there, I'm sorry.

The Kone 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 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.

But 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.

So, but what do you think of the Tesla data engine

approach, which to me is an active learning task.

It's 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.

Yeah, 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 stock fish

and the code for alpha zero,

one is a lot shorter than the other.

A lot more elegant and required a lot less

programmer hours to write.

Yeah, but there was a lot more murder of bad agents

on the alpha zero side.

By murder, I mean agents that played a game

and failed miserably.

Yeah.

Oh, oh.

In simulation, that failure is less costly.

Yeah.

In real world, it's...

Do you mean in practice,

like alpha zero has lost games miserably?

No.

Oh, I haven't seen that.

No, but I know, but the requirement for alpha zero

is 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 entirety process of evolution?

Well, no, but do the evolution in simulation?

Yeah, that's the question.

Can we simulate?

So do you ever 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

in a learned dynamics model.

It's interesting.

It doesn't get enough love.

I was blown away when I was blown away when I read that paper.

I'm like, you know, OK, 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.

No.

So sit back and let the winning roll in.

So your sense, just to elaborate a little bit the link on the topic,

your sense is neural networks will solve driving.

Yes.

Like we don't need anything else.

I think the same way chess was maybe the chess and maybe Google

are the pinnacle of like 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 that you have to deliver products,

and it's possible that the path to full self driving cars will take decades.

I doubt it.

So how long would you put on it?

Like what?

What are we?

You're chasing it.

Tesla is chasing it.

What are we talking about?

Five years, 10 years, 50 years?

Let's say in the 2020s.

In the 2020s.

The later part of the 2020s.

With the neural network.

That would be nice to see.

And on the path to that, you're delivering your products,

which is a nice L2 system.

That's what Tesla is doing, a nice L2 system.

It just gets better every time.

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 100 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 is 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 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 it's all machine learning, none of that is hand coded.

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.

That's difficult to do every step into that direction

is a worthwhile stop to take.

It might be difficult to do really well.

Like, 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,

like when are we supposed to be tuned in?

Yeah.

And people are like,

oh, well, 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.

Yeah, well, they get annoyed.

You know, you know,

when they get annoyed, 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, something we have to monitor for.

Ooh, we don't know.

This is a great psychology experiment at scale.

Like, we'll see.

Yeah, it's fascinating.

Track it.

And making sure you have a good understanding of attention

is a very key part of that psychology problem.

Yeah, I think you and I probably have a different,

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.

So both offline and online, I had little chats with Elon.

Like, 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.

It's like, 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, and 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 monitoring.

Yeah, they ship the model in shadow mode.

With, though, 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's 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,

or 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.

Level three, four, level five.

And I'm willing to bet 10 grand on that.

And you bet 10 grand on that.

I mean, now I know what to take the bet,

but before, maybe someone would have thought,

I should have got my money in.

Yeah.

It's an interesting bet.

I think you're right.

I'm actually on a human level, because he's made the decision.

Like 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,

like what are you supposed to say?

Yeah.

Like, our cars don't have the thing that I think is right to have.

It's an interesting thing, but like on the other side,

as a CEO, I mean, 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.

You think Elon will?

Yeah, I do.

I think he'll come up with a good way

to make it psychologically okay for him.

Well, 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.

Like, 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.

But 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.

Yeah.

You have to also be good parents.

So, 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 is watching the person,

but never throws an alert, they'll never think about it.

Right?

The driver monitoring policy that you choose to,

how you choose to communicate with the user,

is entirely separate from the data collection perspective.

Right.

Right.

So, 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 ComAI, you don't have to manufacture

the thing into the car, is 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.

It started at three years ago.

I believe that we have the best driver monitoring

solution in the world.

I think that when you compare it to Supercruise,

it's the only other one that I really know that shipped,

and ours is better.

What do you like and not like about Supercruise?

I mean, I had a few.

Supercruise, 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 Supercruise would disengage.

Like, I was communicating to the car, I'm like,

look, I'm here, I'm paying attention.

Why are you really going to force me to disengage?

And it did.

So, it's a constant conversation with the user,

and yeah, there's no way to ship a system like this

if you can't 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,

that 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, you're right.

I mean, the game consoles used to not, right?

The game consoles were maybe the second thing that did.

Well, 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.

I love my iOS 14.

Yeah.

Well, one thing that I probably disagree with you

on, on driver monitoring is you said that it's easy.

I mean, you tend to say stuff is easy.

I'm sure, I guess you said it's easy

relative to the external perception problem there.

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

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 hot.

The uncertainty, if you have something that's detecting

whether the human's paying attention and 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.

Yeah, I think that's really well put.

I think that's the right, exactly the place where 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, but 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 something that complicated 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 my love and fascination is the human face.

And it feels like this is a nice place to 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 Kama AI or just any kind of system like a Tesla

or any of the autonomous vehicle companies

is because software is, there's much more sensors

and so much is running on 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 audiobooks.

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 for 100 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

when you have five seconds to basically.

So the five second thing that you think is possible?

Yeah, I think it is.

Oh yeah, not in all scenarios.

Some scenarios it's not.

It's the whole risk thing that you mentioned is nice

is to be able to estimate like how risk 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 was inviting

is like communicating uncertainty.

I guess comma doesn't really communicate uncertainty explicitly.

It communicates it through haptic feel.

Like what's the role of communicating uncertainty do you think?

We do some stuff explicitly.

Like 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 things the lanes are.

You can look at the path.

And we want to be better about this

when we're actually hiring.

We want to hire some new UI people.

UI people, you mentioned this.

Because it's a 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 and QT.

Is that what the UI has done with this QT?

Moving the new UIs and QT.

C++ QT.

Tesla uses it too.

Yeah.

Yeah.

We had some React stuff in there.

React.js or just React.

React has its own language, right?

React Native.

React Native.

React is a JavaScript framework.

It's all based on JavaScript.

I like C++.

What do you think about Dojo with Tesla

and their foray into what appears to be

specialized hardware for training on that?

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.

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.

In video.

In video.

Yeah. 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 and 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 in autonomous driving the winners

only the people who are like desperately falling back