What possible ideas do you have for how human species ends?
Sure.
So I think the most obvious way to me is wireheading.
We end up amusing ourselves to death.
We end up all staring at that infinite TikTok
and forgetting to eat.
Maybe it's even more benign than this.
Maybe we all just stop reproducing.
Now, to be fair,
it's probably hard to get all of humanity.
Yeah.
The interesting thing about humanity
is the diversity in it.
Oh, yeah.
Organisms in general.
There's a lot of weirdos out there.
Well-
Two of them are sitting here.
I mean, diversity in humanity is-
We do respect.
I wish I was more weird.
The following is a conversation with George Hotz,
his third time on this podcast.
He's the founder of Kama AI
that seeks to solve autonomous driving
and is the founder of a new company called TinyCorp
that created TinyGrad,
a neural network framework that is extremely simple
with the goal of making it run on any device
by any human easily and efficiently.
As you know,
George also did a large number of fun and amazing things
from hacking the iPhone
to recently joining Twitter for a bit
as an intern in quotes,
making the case for refactoring the Twitter code base.
In general, he's a fascinating engineer and human being
and one of my favorite people to talk to.
This is the Lex Friedman Podcast.
To support it, please check out our sponsors
in the description.
And now, dear friends, here's George Hotz.
You mentioned something in a stream
about the philosophical nature of time.
So let's start with a wild question.
Do you think time is an illusion?
You know, I sell phone calls to Kama for $1,000.
And some guy called me and like, you know,
it's $1,000, you can talk to me for half an hour.
And he's like, yeah, okay.
So like time doesn't exist
and I really wanted to share this with you.
I'm like, oh, what do you mean time doesn't exist, right?
Like I think time is a useful model,
whether it exists or not, right?
Like does quantum physics exist?
Well, it doesn't matter.
It's about whether it's a useful model to describe reality.
Is time maybe compressive?
Do you think there is an objective reality
or is everything just useful models?
Like underneath it all, is there an actual thing
that we're constructing models for?
I don't know.
I was hoping you would know.
I don't think it matters.
I mean, this kind of connects to the models
of constructive reality with machine learning, right?
Sure.
Like, is it just nice to have useful approximations
of the world such that we can do something with it?
So there are things that are real.
Kolmogorov complexity is real.
Yeah.
The compressive- Math.
Math is real, yeah.
Should be a t-shirt.
And I think hard things are actually hard.
I don't think P equals NP.
Ooh, strong words.
Well, I think that's the majority.
I do think factoring is in P, but.
I don't think you're the person that follows the majority
in all walks of life, so, but it's good.
For that one, I do.
Yeah.
In theoretical computer science, you're one of the sheep.
All right.
But to you, time is a useful model.
Sure.
What were you talking about on the stream with time?
Are you made of time?
If I remembered half the things I said on stream.
Someday someone's going to make a model of all of it
and it's going to come back to haunt me.
Someday soon?
Yeah, probably.
Would that be exciting to you or sad
that there's a George Hotz model?
I mean, the question is when the George Hotz model
is better than George Hotz.
Like, I am declining and the model is growing.
What is the metric by which you measure better or worse
in that if you're competing with yourself?
Maybe you can just play a game
where you have the George Hotz answer
and the George Hotz model answer
and ask which people prefer.
People close to you or strangers?
Either one.
It will hurt more when it's people close to me,
but both will be overtaken by the George Hotz model.
It'd be quite painful, right?
Loved ones, family members would rather have the model
over for Thanksgiving than you.
Or like significant others would rather sext
with the large language model version of you.
Especially when it's fine tuned to their preferences.
Yeah.
Well, that's what we're doing in a relationship, right?
We're just fine tuning ourselves,
but we're inefficient with it
because we're selfish and greedy and so on.
All language models can fine tune more efficiently,
more selflessly.
There's a Star Trek Voyager episode
where Catherine Janeway, lost in the Delta Quadrant,
makes herself a lover on the holodeck.
And the lover falls asleep on her arm
and he snores a little bit and Janeway edits the program
to remove that.
And then of course the realization is,
wait, this person's terrible.
It is actually all their nuances and quirks
and slight annoyances that make this relationship worthwhile.
But I don't think we're going to realize that
until it's too late.
Well, I think a large language model
could incorporate the flaws and the quirks
and all that kind of stuff.
Just the perfect amount of quirks and flaws
to make you charming without crossing the line.
Yeah, yeah.
And that's probably a good approximation
of the percent of time the language model should be cranky
or an asshole or jealous or all this kind of stuff.
And of course it can and it will,
but all that difficulty at that point is artificial.
There's no more real difficulty.
Okay, what's the difference between real and artificial?
Artificial difficulty is difficulty that's constructed
or could be turned off with a knob.
Real difficulty is like,
you're in the woods and you've got to survive.
So if something cannot be turned off with a knob, it's real.
Yeah, I think so.
Or, I mean, you can't get out of this
by smashing the knob with a hammer.
I mean, maybe you kind of can.
You know, into the wild when Alexander Supertramp,
he wants to explore something
that's never been explored before, but it's the 90s.
Everything's been explored.
So he's like, well, I'm just not going to bring a map.
I mean, no, you're not exploring.
You should have brought a map, dude, you died.
There was a bridge a mile from where you were camping.
How does that connect to the metaphor of the knob?
By not bringing the map, you didn't become an explorer.
You just smashed the thing.
Yeah. Yeah.
The difficulty is still artificial.
You failed before you started.
What if we just don't have access to the knob?
Well, that maybe is even scarier, right?
Like we already exist in a world of nature
and nature has been fine-tuned over billions of years
to have humans build something
and then throw the knob away
in some grand romantic gesture is horrifying.
Do you think of us humans as individuals
that are like born and die,
or are we just all part of one living organism
that is Earth, that is nature?
I don't think there's a clear line there.
I think it's all kind of just fuzzy, I don't know.
I mean, I don't think I'm conscious.
I don't think I'm anything.
I think I'm just a computer program.
So it's all computation.
The thing running in your head is just computation.
Everything running in the universe is computation, I think.
I believe the extended church-tiring thesis.
Yeah, but there seems to be an embodiment
to your particular computation.
Like there's a consistency.
Well, yeah, but I mean, models have consistency too.
Yeah.
Models that have been RLHF'd will continually say like,
well, how do I murder ethnic minorities?
Oh, well, I can't let you do that, Hal.
There's a consistency to that behavior.
It's all RLHF, like we all RLHF each other.
We provide human feedback
and thereby fine-tune these little pockets of computation,
but it's still unclear why that pocket of computation
stays with you for years.
It just kind of,
you have this consistent set of physics, biology,
whatever you call the neurons firing,
the electrical signals, the mechanical signals,
all of that, that seems to stay there.
And it contains information, it stores information,
and that information permeates through time
and stays with you.
There's like memory, there's like sticky.
Okay, to be fair, like a lot of the models
we're building today are very,
even RLHF is nowhere near as complex
as the human loss function.
Reinforcement learning with human feedback.
You know, when I talked about will GPT-12 be AGI,
my answer is no, of course not.
I mean, cross-entropy loss is never gonna get you there.
You need probably RL in fancy environments
in order to get something
that would be considered like AGI-like.
So to ask the question about why, I don't know,
it's just some quirk of evolution, right?
I don't think there's anything particularly special
about where I ended up, where humans ended up.
So okay, we have human-level intelligence.
Would you call that AGI, whatever we have, GI?
Look, actually, I don't really even like the word AGI,
but general intelligence is defined
to be whatever humans have.
Okay, so why can GPT-12 not get us to AGI?
Can we just like linger on that?
If your loss function is categorical cross-entropy,
if your loss function is just try to maximize compression,
I have a SoundCloud I wrap,
and I tried to get Chat GPT to help me write wraps,
and the wraps that it wrote
sounded like YouTube comment wraps.
You know, you can go on any rap beat online
and you can see what people put in the comments,
and it's the most like mid-quality wrap you can find.
Is mid good or bad?
Mid is bad.
Mid is bad.
It's like mid, it's like.
Every time I talk to you, I learn new words.
Mid.
Mid, yeah.
I was like, is it like basic?
Is that what mid means?
Kind of, it's like middle of the curve, right?
So there's like that intelligence curve,
and you have like the dumb guy, the smart guy,
and then the mid guy.
Actually, being the mid guy is the worst.
The smart guy is like, I put all my money in Bitcoin.
The mid guy is like, you can't put money in Bitcoin.
It's not real money.
And all of it is a genius meme.
That's another interesting one.
Memes.
The humor, the idea, the absurdity,
encapsulated in a single image,
and it just kind of propagates virally
between all of our brains.
I didn't get much sleep last night,
so I'm very, I sound like I'm high, but I swear I'm not.
Do you think we have ideas or ideas have us?
I think that we're gonna get super scary memes
once the AIs actually are superhuman.
Ooh, you think AI will generate memes?
Of course.
You think it'll make humans laugh?
I think it's worse than that.
So Infinite Jest, it's introduced in the first 50 pages,
is about a tape that you, once you watch it once,
you only ever want to watch that tape.
In fact, you want to watch the tape so much
that someone says, okay, here's a hacksaw,
cut off your pinky, and then I'll let you
watch the tape again, and you'll do it.
So we're actually gonna build that, I think,
but it's not gonna be one static tape.
I think the human brain is too complex
to be stuck in one static tape like that.
If you look at ant brains,
maybe they can be stuck on a static tape,
but we're going to build that using generative models.
We're going to build the TikTok
that you actually can't look away from.
So TikTok is already pretty close there,
but the generation is done by humans.
The algorithm is just doing their recommendation,
but if the algorithm is also able to do the generation.
Well, it's a question about
how much intelligence is behind it, right?
So the content is being generated by,
let's say, one humanity worth of intelligence,
and you can quantify a humanity, right?
That's a, you know, it's exa-flops, yatta-flops,
but you can quantify it.
Once that generation is being done by 100 humanities,
you're done.
So it's actually a scale that's the problem,
but also speed.
Yeah.
And what if it's sort of manipulating
the very limited human dopamine engine for porn?
Imagine just TikTok, but for porn.
Yeah.
It's like a brave new world.
I don't even know what it'll look like, right?
Like, again, you can't imagine the behaviors
of something smarter than you, but a super intelligent,
an agent that just dominates your intelligence so much
will be able to completely manipulate you.
Is it possible that it won't really manipulate?
It'll just move past us.
It'll just kind of exist the way water exists
or the air exists.
You see, and that's the whole AI safety thing.
It's not the machine that's going to do that.
It's other humans using the machine
that are going to do that to you.
Yeah, because the machine is not interested
in hurting humans.
The machine is a machine, but the human gets the machine
and there's a lot of humans out there
very interested in manipulating you.
Well, let me bring up Eliezer Yatkowski,
who recently sat where you're sitting.
He thinks that AI will almost surely kill everyone.
Do you agree with him or not?
Yes, but maybe for a different reason.
Okay.
And then I'll try to get you to find hope
or we could find a no to that answer, but why yes?
Okay, why didn't nuclear weapons kill everyone?
That's a good question.
I think there's an answer.
I think it's actually very hard
to deploy nuclear weapons tactically.
It's very hard to accomplish tactical objectives.
Great, I can nuke their country.
I have an irradiated pile of rubble.
I don't want that.
Why not?
Why don't I want an irradiated pile of rubble?
For all the reasons no one wants
an irradiated pile of rubble.
Oh, because you can't use that land for resources.
You can't populate the land.
Yeah, what you want, a total victory in a war
is not usually the irradiation
and eradication of the people there.
It's the subjugation and domination of the people.
Okay, so you can't use this strategically,
tactically in a war to help you,
to help gain a military advantage.
It's all complete destruction, all right?
Yeah.
But there's egos involved.
It's still surprising.
Still surprising that nobody pressed the big red button.
It's somewhat surprising,
but you see, it's the little red button
that's gonna be pressed with AI that's gonna,
and that's why we die.
It's not because the AI,
if there's anything in the nature of AI,
it's just the nature of humanity.
What's the algorithm behind the little red button?
What possible ideas do you have for how human species ends?
Sure, so I think the most obvious way to me
is wireheading.
We end up amusing ourselves to death.
We end up all staring at that infinite TikTok
and forgetting to eat.
Maybe it's even more benign than this.
Maybe we all just stop reproducing.
Now, to be fair,
it's probably hard to get all of humanity.
Yeah.
It probably is.
This is always going,
like the interesting thing about humanity
is the diversity in it.
Oh yeah.
Organisms in general.
There's a lot of weirdos out there.
Two of them are sitting here.
Yeah, I mean, diversity in humanity is-
We do respect.
I wish I was more weird.
No, like I'm kinda, look, I'm drinking Smartwater, man.
That's like a Coca-Cola product, right?
You're one corporate, George Haas.
I'm one corporate.
No, the amount of diversity in humanity
I think is decreasing,
just like all the other biodiversity on the planet.
Oh boy, yeah.
And social media's not helping, huh?
Go eat McDonald's in China.
Yeah.
Yeah, no, it's the interconnectedness that's doing it.
Oh, that's interesting.
So everybody starts relying on the connectivity
of the internet.
And over time that reduces the diversity,
the intellectual diversity,
and then that gets everybody into a funnel.
There's still going to be a guy in Texas.
There is, and yeah.
In a bunker.
To be fair, do I think AI kills us all?
I think AI kills everything we call society today.
I do not think it actually kills the human species.
I think that's actually incredibly hard to do.
Yeah, but society, if we start over, that's tricky.
Most of us don't know how to do most things.
Yeah, but some of us do.
And they'll be okay and they'll rebuild after the great AI.
What's rebuilding look like?
Like, how much do we lose?
What has human civilization done that's interesting?
The combustion engine, electricity,
so power and energy, that's interesting.
Like how to harness energy.
Whoa, whoa, whoa, whoa.
They're going to be religiously against that.
Are they going to get back to like fire?
Sure.
I mean, there'll be, it'll be like, you know,
some kind of Amish looking kind of thing, I think.
I think they're going to have very strong taboos
against technology.
Like technology, it's almost like a new religion.
Technology is the devil.
Yeah.
And nature is God.
Sure.
So closer to nature.
But can you really get away from AI
if it destroyed 99% of the human species?
Isn't it somehow have a hold, like a stronghold?
What's interesting about everything we build,
I think we're going to build super intelligence
before we build any sort of robustness in the AI.
We cannot build an AI that is capable
of going out into nature and surviving like a bird, right?
A bird is an incredibly robust organism.
We've built nothing like this.
We haven't built a machine that's capable of reproducing.
Yes, but there is a, you know,
I work with like robots a lot now.
I have a bunch of them.
They're mobile.
They can't reproduce, but all they need is,
I guess you're saying they can't repair themselves.
But if you have a large number,
if you have like a hundred million of them.
Let's just focus on them reproducing, right?
Do they have microchips in them?
Okay, then do they include a fab?
No.
Then how are they going to reproduce?
Well, it doesn't have to be all on board, right?
They can go to a factory, to a repair shop.
Yeah, but then you're really moving away from robustness.
Yes.
All of life is capable of reproducing
without needing to go to a repair shop.
Life will continue to reproduce
in the complete absence of civilization.
Robots will not.
So when the, if the AI apocalypse happens,
I mean, the AIs are going to probably die out
because I think we're going to get, again,
super intelligence long before we get robustness.
What about if you just improve the fab
to where you just have a 3D printer
that can always help you?
Well, that'd be very interesting.
I'm interested in building that.
Of course you are.
You think, how difficult is that problem
to have a robot that basically can build itself?
Very, very hard.
I think you've mentioned this,
like to me or somewhere
where people think it's easy conceptually.
And then they remember
that you're going to have to have a fab.
Yeah, on board.
Of course.
So 3D printer that prints a 3D printer.
Yeah.
Yeah, on legs.
Why is that hard?
Well, because it's, I mean,
a 3D printer is a very simple machine, right?
Okay, you're going to print chips.
You're going to have an atomic printer.
How are you going to dope the silicon?
Right?
How are you going to etch the silicon?
You're going to have to have a very interesting kind of fab
if you want to have a lot of computation on board.
But you can do like structural type of robots that are dumb.
Yeah, but structural type of robots
aren't going to have the intelligence required to survive
in any complex environment.
What about like ants type of systems?
We have like trillions of them.
I don't think this works.
I mean, again, like ants at their very core
are made up of cells that are capable
of individually reproducing.
They're doing quite a lot of computation
that we're taking for granted.
It's not even just the computation.
It's that reproduction is so inherent.
Okay, so like there's two stacks of life in the world.
There's the biological stack and the silicon stack.
The biological stack starts with reproduction.
Reproduction is at the absolute core.
The first proto RNA organisms were capable of reproducing.
The silicon stack, despite as far as it's come,
is nowhere near being able to reproduce.
Yeah, so the fab movement, digital fabrication.
Fabrication in the full range of what that means
is still in the early stages.
Yeah.
You're interested in this world.
Even if you did put a fab on the machine, right?
Let's say, okay, we can build fabs.
We know how to do that as humanity.
We can probably put all the precursors
that build all the machines in the fabs
also in the machine.
So first off, this machine's gonna be absolutely massive.
I mean, we almost have a like,
think of the size of the thing required
to reproduce a machine today, right?
Like is our civilization capable of reproduction?
Can we reproduce our civilization on Mars?
If we were to construct a machine
that is made up of humans,
like a company that can reproduce itself.
Yeah.
I don't know.
It feels like 115 people.
It gets so much harder than that.
120?
Let's see, I believe that Twitter can be run by 50 people.
I think that this is gonna take most of,
like it's just most of society, right?
Like we live in one globalized world.
No, but you're not interested in running Twitter.
You're interested in seeding.
Like you want to seed a civilization
because humans can like have sex.
Yeah, okay.
So you're talking about the humans reproducing
and like basically like what's the smallest
self-sustaining colony of humans?
Yeah.
Yeah, okay, fine.
But they're not gonna be making five nanometer chips.
Over time they will.
I think you're being,
like we have to expand our conception of time here,
going back to the original timescale.
I mean, over, across maybe 100 generations,
we're back to making chips.
No?
If you seed the colony correctly.
Or maybe they'll watch our colony die out over here
and be like, we're not making chips.
Don't make chips.
No, but you have to seed that colony correctly.
Whatever you do, don't make chips.
Chips are what led to their downfall.
Well, that is the thing that humans do.
They come up, they construct a devil,
a good thing and a bad thing,
and they really stick by that.
And then they murder each other over that.
There's always one asshole in the room
who murders everybody.
And he usually makes tattoos and nice branding.
Flats and stuff.
Do you need that asshole?
That's the question, right?
Humanity works really hard today to get rid of that asshole,
but I think they might be important.
Yeah, this whole freedom of speech thing.
It's the freedom of being an asshole
seems kind of important.
That's right.
Man, this thing, this fab, this human fab
that we constructed, this human civilization,
is pretty interesting.
And now it's building artificial copies of itself
or artificial copies of various aspects of itself
that seem interesting, like intelligence.
And I wonder where that goes.
I like to think it's just another stack for life.
We have the biostack life.
We're a biostack life, and then the silicon stack life.
But it seems like the ceiling,
or there might not be a ceiling,
or at least the ceiling is much higher
for the silicon stack.
Oh, no, we don't know what the ceiling is
for the biostack either.
The biostack just seemed to move slower.
You have Moore's Law, which is not dead,
despite many proclamations.
In the biostack or the silicon stack?
In the silicon stack.
And you don't have anything like this in the biostack.
So I have a meme that I posted.
I tried to make a meme.
It didn't work too well.
But I posted a picture of Ronald Reagan and Joe Biden.
And you look, this is 1980, and this is 2020.
And these two humans are basically the same.
There's been no change in humans in the last 40 years.
And then I posted a computer from 1980
and a computer from 2020.
Wow.
Yeah, with their early stages, right?
Which is why you said when you said the fab,
the size of the fab required to make another fab
is like very large right now.
Oh, yeah.
But computers were very large 80 years ago.
And they got pretty tiny.
And people are starting to want to wear them on their face.
In order to escape reality.
That's the thing.
In order to live inside the computer.
Yeah.
Put a screen right here.
I don't have to see the rest of you assholes.
I've been ready for a long time.
You like virtual reality?
I love it.
Do you want to live there?
Yeah.
Yeah.
Part of me does too.
How far away are we, do you think?
Judging from what you can buy today far, very far.
I got to tell you that I had the experience
of Meta's Kodak Avatar,
where it's a ultra high resolution scan.
It looked real.
I mean, the headsets just are not quite
at like eye resolution yet.
I haven't put on any headset where I'm like,
oh, this could be the real world.
Whereas when I put good headphones on, audio is there.
And like, we can reproduce audio that I'm like,
I'm actually in a jungle right now.
If I close my eyes, I can't tell I'm not.
Yeah.
But then there's also smell and all that kind of stuff.
Sure.
I don't know.
The power of imagination or the power of the mechanism
in the human mind that fills the gaps,
that kind of reaches and wants to make the thing you see
in the virtual world real to you, I believe in that power.
Or humans want to believe.
Yeah.
Like, what if you're lonely?
What if you're sad?
What if you're really struggling in life
and here's a world where you don't have to struggle anymore?
Humans want to believe so much
that people think the large language models are conscious.
That's how much humans want to believe.
Strong words.
He's throwing left and right hooks.
Why do you think large language models are not conscious?
I don't think I'm conscious.
Oh, so what is consciousness then, George Hans?
It's like what it seems to mean to people.
It's just like a word that atheists use for souls.
Sure, but that doesn't mean soul is not an interesting word.
If consciousness is a spectrum,
I'm definitely way more conscious
than the large language models are.
I think the large language models
are less conscious than a chicken.
When is the last time you've seen a chicken?
In Miami, like a couple months ago.
How, no, like a living chicken.
Living chickens walking around Miami, it's crazy.
Like on the street?
Yeah.
Like a chicken.
A chicken, yeah.
All right.
All right, I was trying to call you out
like a good journalist and I got shut down.
Okay, but you don't think much
about this kind of subjective feeling
that it feels like something to exist.
And then as an observer, you can have a sense
that an entity is not only intelligent,
but has a kind of subjective experience of its reality,
like a self-awareness that is capable of suffering,
of hurting, of being excited by the environment
in a way that's not merely kind of an artificial response,
but a deeply felt one.
Humans want to believe so much
that if I took a rock and a Sharpie
and drew a sad face on the rock,
they'd think the rock is sad.
Yeah, and you're saying when we look in the mirror,
we apply the same smiley face with rock.
Pretty much, yeah.
Isn't that weird though?
That you're not conscious, is that?
No.
But you do believe in consciousness.
Not really.
It's just, it's unclear.
Okay, so to you, it's like a little,
like a symptom of the bigger thing
that's not that important.
Yeah, I mean, it's interesting
that like human systems seem to claim
that they're conscious.
And I guess it kind of like says something
in a straight up, like, okay, what do people mean when,
even if you don't believe in consciousness,
what do people mean when they say consciousness?
And there's definitely like meanings to it.
What's your favorite thing to eat?
Pizza.
Cheese pizza, what are the toppings?
I like cheese pizza.
I like pepperoni pizza. Don't say pineapple.
No, I don't like pineapple.
Okay.
Pepperoni pizza.
Has they put any ham on it?
Oh, that's real bad.
What's the best, what's the best pizza?
What are we talking about here?
Like, do you like cheap, crappy pizza?
A Chicago deep dish cheese pizza.
Oh, that's my favorite.
There you go.
You just bite into a deep dish, a Chicago deep dish pizza.
And it feels like you were starving.
You haven't eaten for 24 hours.
You just bite in and you're hanging out
with somebody that matters a lot to you.
And you're there with the pizza.
Sounds real nice.
Yeah, all right.
It feels like something.
I'm George motherfucking Hotz eating
a fucking Chicago deep dish pizza.
There's just the full peak,
light living experience of being human.
The top of the human condition.
Sure.
It feels like something to experience that.
Why does it feel like something?
That's consciousness, isn't it?
If that's the word you want to use to describe it, sure.
I'm not going to deny that that feeling exists.
I'm not going to deny that I experienced that feeling.
When, I guess what I kind of take issue to
is that there's some like,
like how does it feel to be a web server?
Do 404s hurt?
Not yet.
How would you know what suffering looked like?
Sure, you can recognize a suffering dog
because we're the same stack as the dog.
All the bio stack stuff kind of, especially mammals,
you know, it's, it's really easy.
You can.
Game recognizes game.
Yeah.
Versus the Silicon stack stuff.
It's like, you have no idea.
You have, you, it, oh wow.
The little thing has learned to mimic, you know.
But then I realized that that's all we are too.
Oh look, the little thing has learned to mimic.
Yeah.
I guess, yeah, 404 could be, could be suffering,
but it's so far from our kind of living organism,
our kind of stack.
But it feels like AI can start maybe mimicking
the biological stack better, better, better.
Cause it's trained.
We trained it, yeah.
And so in that,
maybe that's the definition of consciousness
is the bio stack consciousness.
The definition of consciousness
is how close something looks to human.
Sure, I'll give you that one.
No, how close something is to the human experience.
Sure.
It's a very, it's a very anthropocentric definition, but.
Well, that's all we got.
Sure.
No, and I don't mean to like,
I think there's a lot of value in it.
Look, I just started my second company.
My third company will be AI girlfriends.
Well, like I mean it.
I want to find out what your fourth company is after that.
Oh wow.
Cause I think once you have AI girlfriends, it's,
oh boy, does it get interesting.
Well, maybe let's go there.
I mean, the relationships with AI,
that's creating human-like organisms, right?
And part of being human is being conscious,
is being, having the capacity to suffer,
having the capacity to experience this life richly
in such a way that you can empathize.
The AI system can empathize with you
and you can empathize with it,
or you can project your anthropomorphic sense
of what the other entity is experiencing.
And an AI model would need to, yeah,
to create that experience inside your mind.
And it doesn't seem that difficult.
Yeah, but okay, so here's where it actually
gets totally different, right?
When you interact with another human,
you can make some assumptions.
Yeah.
When you interact with these models, you can't.
You can make some assumptions that that other human
experiences suffering and pleasure
in a pretty similar way to you do.
The golden rule applies.
Mm-hmm.
With an AI model, this isn't really true, right?
These large language models are good at fooling people
because they were trained on a whole bunch of human data
and told to mimic it.
Yep.
But if the AI system says,
hi, my name is Samantha, it has a backstory.
Yeah.
I went to college here and there.
Yeah.
Maybe you'll integrate this in the AI system.
I made some chatbots, I gave them backstories.
It was lots of fun.
I was so happy when Llama came out.
Yeah, we'll talk about Llama.
We'll talk about all that, but like, you know,
the rock with the smiley face.
Yeah.
Well, it seems pretty natural for you to anthropomorphize
that thing and then start dating it.
And before you know it, you're married and have kids.
With a rock.
With a rock.
And there's pictures on Instagram with you and a rock
and a smiley face.
To be fair, like, you know,
something that people generally look for
when they're looking for someone to date
is intelligence in some form.
And the rock doesn't really have intelligence.
Only a pretty desperate person would date a rock.
I think we're all desperate deep down.
Oh, not rock level desperate.
All right.
Not rock level desperate, but AI level desperate.
I don't know.
I think all of us have a deep loneliness.
It just feels like the language models are there.
Oh, I agree.
And you know what?
I won't even say this so cynically.
I will actually say this in a way that like,
I want AI friends.
I do.
Yeah.
I would love to.
You know, again,
the language models now are still a little,
like people are impressed with these GPT things.
And I look at like, or like, or the co-pilot,
the coding one, and I'm like, okay,
this is like junior engineer level.
And these people are like Fiverr level artists
and copywriters.
Like, okay, great.
We got like Fiverr and like junior engineers.
Okay, cool.
Like, and this is just the start
and it will get better, right?
Like I would, I can't wait to have AI friends
who are more intelligent than I am.
So Fiverr is just a temporary, it's not the ceiling.
No, definitely not.
Is it countless cheating
when you're talking to an AI model, emotional cheating?
That's up to you and your human partner to define.
Oh, you have to, all right.
You're getting, yeah.
You have to have that conversation, I guess.
All right.
I mean, integrate that with porn and all this.
No, I mean, a similar kind of to porn.
Yeah. Yeah.
I think people in relationships
have different views on that.
Yeah, but most people don't have like
serious open conversations about all the different aspects
of what's cool and what's not.
And it feels like AI is a really weird conversation to have.
I mean, the porn one is a good branching off point.
Like these things, you know, one of my scenarios
that I put in my chatbot is a, you know,
a nice girl named Lexi, she's 20.
She just moved out to LA.
She wanted to be an actress,
but she started doing OnlyFans instead.
And you're on a date with her, enjoy.
Oh man, yeah.
And so is that if you're actually dating somebody
in real life, is that cheating?
I feel like it gets a little weird.
Sure. It gets real weird.
It's like, what are you allowed to say to an AI bot?
Imagine having that conversation with a significant other.
I mean, these are all things
for people to define in their relationships.
What it means to be human
is just gonna start to get weird.
Especially online.
Like, how do you know?
Like there'll be moments when you'll have
what you think is a real human you interacted with
on Twitter for years and you realize it's not.
I spread, I loved this meme.
Heaven banning?
Do you know about shadow banning?
Yeah.
Shadow banning, okay, you post, no one can see it.
Heaven banning, you post, no one can see it,
but a whole lot of AIs are spun up to interact with you.
Well, maybe that's what the way human civilization ends
is all of us are heaven banned.
There's a great, it's called
My Little Pony, Friendship is Optimal.
It's a sci-fi story that explores this idea.
Friendship is optimal.
Friendship is optimal.
Yeah, I'd like to have some,
at least on the intellectual realm,
some AI friends that argue with me.
But the romantic realm is weird.
Definitely weird.
But not out of the realm of the kind of weirdness
that human civilization is capable of, I think.
I want it.
Look, I want it.
If no one else wants it, I want it.
Yeah, I think a lot of people probably want it.
There's a deep loneliness.
And I'll feel their loneliness
and it just will only advertise to you some of the time.
Yeah, maybe the conceptions of monogamy change too.
Like I grew up in a time, like I value monogamy,
but maybe that's a silly notion
when you have arbitrary number of AI systems.
This interesting path from rationality to polyamory.
Yeah, that doesn't make sense for me.
For you, but you're just a biological organism
who was born before the internet really took off.
The crazy thing is,
culture is whatever we define it as, right?
These things are not UV,
is a lot problem in moral philosophy, right?
Okay, what is might be that computers are capable
of mimicking girlfriends perfectly.
They pass the girlfriend touring test, right?
But that doesn't say anything about a lot.
That doesn't say anything about how we ought to respond
to them as a civilization.
That doesn't say we ought to get rid of monogamy, right?
That's a completely separate question,
really a religious one.
Girlfriend touring test.
I wonder what that looks like.
Girlfriend touring test.
Are you writing that?
Will you be the Alan Turing of the 21st century
that writes the girlfriend touring test paper?
No, I mean, of course, my AI girlfriends,
their goal is to pass the girlfriend touring test.
No, but there should be a paper
that kind of defines the test.
I mean, the question is if it's deeply personalized
or there's a common thing that really gets everybody.
Yeah, I mean, look, we're a company.
We don't have to get everybody.
We just have to get a large enough clientele to stay.
I like how you're already thinking company.
All right, before we go to company number three
and company number four, let's go to company number two.
TinyCorp, possibly one of the greatest names
of all time for a company.
You've launched a new company called TinyCorp
that leads the development of TinyGrad.
What's the origin story of TinyCorp and TinyGrad?
I started TinyGrad as a toy project just to teach myself,
okay, what is a convolution?
What are all these options you can pass to them?
What is the derivative of a convolution, right?
Very similar to, Karpathy wrote MicroGrad, very similar.
And then I started realizing,
I started thinking about AI chips.
I started thinking about chips that run AI,
and I was like, well, okay,
this is going to be a really big problem.
If Nvidia becomes a monopoly here,
how long before Nvidia is nationalized?
So you, one of the reasons to start TinyCorp
is to challenge Nvidia.
It's not so much to challenge Nvidia.
I actually, I like Nvidia,
and it's to make sure power stays decentralized.
Yeah, and here's computational power.
I see Nvidia is kind of locking down
the computational power of the world.
If Nvidia becomes just like 10X better than everything else,
you're giving a big advantage to somebody
who can secure Nvidia as a resource.
Yeah.
In fact, if Jensen watches this podcast,
he may want to consider this.
He may want to consider making sure
his company is not nationalized.
Do you think that's an actual threat?
Oh, yes.
No, but there's so much, you know, there's AMD.
So we have Nvidia and AMD, great.
All right.
But you don't think there's like a push
towards like selling, like Google selling TPUs
or something like this?
You don't think there's a push for that?
Have you seen it?
Google loves to rent you TPUs.
It doesn't, you can't buy it at Best Buy?
No.
So I started work on a chip.
I was like, okay, what's it going to take to make a chip?
And my first notions were all completely wrong
about why, about like how you could improve on GPUs.
And I will take this.
This is from Jim Keller on your podcast.
And this is one of my absolute favorite
descriptions of computation.
So there's three kinds of computation paradigms
that are common in the world today.
There's CPUs and CPUs can do everything.
CPUs can do add and multiply.
They can do load and store
and they can do compare and branch.
And when I say they can do these things,
they can do them all fast, right?
So compare and branch are unique to CPUs.
And what I mean by they can do them fast
is they can do things like branch prediction
and speculative execution.
And they spend tons of transistors
on these like super deep reorder buffers
in order to make these things fast.
Then you have a simpler computation model GPUs.
GPUs can't really do compare and branch.
I mean, they can, but it's horrendously slow.
But GPUs can do arbitrary load and store, right?
GPUs can do things like X dereference Y.
So they can fetch from arbitrary pieces of memory.
They can fetch from memory that is defined
by the contents of the data.
The third model of computation DSPs.
And DSPs are just add and multiply, right?
Like they can do load and stores,
but only static load and stores.
Only loads and stores that are known
before the program runs.
And you look at neural networks today
and 95% of neural networks are all the DSP paradigm.
They are just statically scheduled adds and multiplies.
So TinyGuard really took this idea
and I'm still working on it
to extend this as far as possible.
Every stage of the stack has Turing completeness, right?
Python has Turing completeness.
And then we take Python,
we go into C++, which is Turing complete,
and maybe C++ calls into some CUDA kernels,
which are Turing complete.
The CUDA kernels go through LLVM, which is Turing complete,
into PTX, which is Turing complete,
to SAS, which is Turing complete,
on a Turing complete processor.
I want to get Turing completeness
out of the stack entirely.
Because once you get rid of Turing completeness,
you can reason about things.
Rice's theorem and the halting problem
do not apply to add-mole machines.
Okay, what's the power and the value
of getting Turing completeness out of,
are we talking about the hardware or the software?
Every layer of the stack.
Every layer.
Every layer of the stack, removing Turing completeness
allows you to reason about things, right?
So the reason you need to do branch prediction in a CPU
and the reason it's prediction,
and the branch predictors are,
I think they're like 99% on CPUs.
Why do they get 1% of them wrong?
Well, they get 1% wrong because you can't know, right?
That's the halting problem.
It's equivalent to the halting problem
to say whether a branch is going to be taken or not.
I can show that, but the add-mole machine,
the neural network, runs the identical compute every time.
The only thing that changes is the data.
So when you realize this, you think about,
okay, how can we build a computer,
and how can we build a stack
that takes maximal advantage of this idea?
So what makes TinyGrad different
from other neural network libraries
is it does not have a primitive operator
even for matrix multiplication.
And this is every single one.
They even have primitive operators
for things like convolutions.
So no matmole.
No matmole.
Well, here's what a matmole is.
So I'll use my hands to talk here.
So if you think about a cube,
and I put my two matrices that I'm multiplying
on two faces of the cube, right?
You can think about the matrix multiply as, okay,
the N cubed, I'm going to multiply
for each one in the cubed,
and then I'm going to do a sum,
which is a reduce up to here
to the third face of the cube,
and that's your multiplied matrix.
So what a matrix multiply is
is a bunch of shape operations, right?
A bunch of permute three shapes and expands
on the two matrices.
A multiply, N cubed.
A reduce, N cubed, which gives you an N squared matrix.
Okay, so what is the minimum number of operations
that can accomplish that
if you don't have matmole as a primitive?
So TinyGrad has about 20.
And you can compare TinyGrad's opposite or IR
to things like XLA or PrimTorch.
So XLA and PrimTorch are ideas where like, okay,
torch has like 2,000 different kernels.
PyTorch 2.0 introduced PrimTorch, which has only 250.
TinyGrad has order of magnitude 25.
It's 10X less than XLA or PrimTorch.
And you can think about it as kind of like risk versus CISC.
Right?
These other things are CISC-like systems.
TinyGrad is risk.
And risk one.
Risk architecture is gonna change everything.
1995, hackers.
Wait, really?
That's an actual thing?
Angelina Jolie delivers the line,
risk architecture is gonna change everything in 1995.
And here we are with ARM in the phones and ARM everywhere.
Wow.
I love it when movies actually have real things in them.
Right?
Okay, interesting.
This is like, so you're thinking of this
as the risk architecture of ML stack.
25, huh?
What, can you go through the,
the four op types?
Sure.
Okay, so you have unary ops, which take in a tensor
and return a tensor of the same size
and do some unary op to it.
X, log, reciprocal, sign, right?
They take in one and they're point-wise.
ReLU.
Yeah, ReLU.
Almost all activation functions are unary ops.
Some combinations of unary ops together is still a unary op.
Then you have binary ops.
Binary ops are like point-wise addition,
multiplication, division, compare.
It takes in two tensors of equal size
and outputs one tensor.
Then you have reduce ops.
Reduce ops will take a three-dimensional tensor
and turn it into a two-dimensional tensor
or a three-dimensional tensor
turn it into a zero-dimensional tensor.
Things like a sum or max are really the common ones there.
And then the fourth type is movement ops.
And movement ops are different from the other types
because they don't actually require computation.
They require different ways to look at memory.
So that includes reshapes, permutes, expands, flips.
Those are the main ones, probably.
And so with that, you have enough to make a map model.
And convolutions.
And every convolution you can imagine
dilated convolutions, strided convolutions,
transposed convolutions.
You're right on GitHub about laziness.
Showing a matmul, matrix multiplication.
See how despite the style, it is fused into one kernel
with the power of laziness.
Can you elaborate on this power of laziness?
Sure, so if you type in PyTorch,
A times B plus C,
what this is going to do
is it's going to first multiply Adam B,
and store that result into memory.
And then it is going to add C
by reading that result from memory,
reading C from memory, and writing that out to memory.
There is way more loads and stores to memory
than you need there.
If you don't actually do A times B as soon as you see it,
if you wait until the user actually realizes that tensor,
until the laziness actually resolves,
you confuse that plus C.
This is like, it's the same way Haskell works.
So what's the process of porting a model into TinyGrad?
So TinyGrad's front end looks very similar to PyTorch.
I probably could make a perfect,
or pretty close to perfect interop layer
if I really wanted to.
I think that there's some things that are nicer
about TinyGrad syntax than PyTorch,
but the front end looks very torch-like.
Or you can also load in ONNX models.
We have more ONNX tests passing than Core ML.
Core ML, okay, so.
We'll pass ONNX runtime soon.
What about the developer experience with TinyGrad?
What it feels like, what are the, versus PyTorch?
By the way, I really like PyTorch.
I think that it's actually a very good piece of software.
I think that they've made a few different trade-offs,
and these different trade-offs are where, you know,
TinyGrad takes a different path.
One of the biggest differences is it's really easy to see
the kernels that are actually being sent to the GPU.
If you run PyTorch on the GPU, you do some operation,
and you don't know what kernels ran.
You don't know how many kernels ran.
You don't know how many flops were used.
You don't know how much memory accesses were used.
TinyGrad type debug equals two,
and it will show you in this beautiful style
every kernel that's run, how many flops, and how many bytes.
So can you just linger on what problem TinyGrad solves?
TinyGrad solves the problem
of porting new ML accelerators quickly.
One of the reasons, tons of these companies now,
I think Sequoia marked Graphcore to zero, right?
Seribus, TenzTorrent, Grok,
all of these ML accelerator companies, they built chips.
The chips were good.
The software was terrible.
And part of the reason is because,
I think the same problem is happening with Dojo.
It's really, really hard to write a PyTorch port
because you have to write 250 kernels,
and you have to tune them all for performance.
What does Jim Keller think about TinyGrad?
You guys have hung out quite a bit,
so he's involved with TenzTorrent.
What's his praise, and what's his criticism
of what you're doing with your life?
Look, my prediction for TenzTorrent
is that they're gonna pivot to making RISC-V chips.
CPUs.
CPUs.
Why?
Well, because AI accelerators are a software problem,
not really a hardware problem.
Oh, interesting.
So you don't think,
you think the diversity of AI accelerators
in the hardware space is not going to be a thing
that exists long-term?
I think what's gonna happen is if I can finish,
okay, if you're trying to make an AI accelerator,
you better have the capability
of writing a torch-level performance stack on NVIDIA GPUs.
If you can't write a torch stack on NVIDIA GPUs,
and I mean all the way, I mean down to the driver,
there's no way you're gonna be able to write it on your chip
because your chip's worse than an NVIDIA GPU.
The first version of the chip you tape out,
it's definitely worse.
Well, you're saying writing that stack is really tough.
Yes, and not only that, actually,
the chip that you tape out,
almost always because you're trying to get advantage
over NVIDIA, you're specializing the hardware more.
It's always harder to write software
for more specialized hardware.
Like a GPU's pretty generic,
and if you can't write an NVIDIA stack,
there's no way you can write a stack for your chip.
So my approach with TinyGrad is,
first, write a performant NVIDIA stack.
We're targeting AMD.
So you did say a few to NVIDIA a little bit, with love.
With love. Yeah.
With love.
It's like the Yankees, you know?
I'm a Mets fan.
Oh, you're a Mets fan, a Risk fan and a Mets fan.
What's the hope that AMD has?
You did a build with AMD recently that I saw.
How does the 7900 XTX compare to the RTX 4090 or 4080?
Well, let's start with the fact
that the 7900 XTX kernel drivers don't work,
and if you run demo apps in loops, it panics the kernel.
Okay, so this is a software issue?
Lisa Sue responded to my email.
Oh. I reached out.
I was like, this is, you know, really?
Like, I understand if your seven-by-seven
transposed Winnegrad conv is slower than NVIDIA's,
but literally when I run demo apps in a loop,
the kernel panics?
So just adding that loop.
Yeah, I just literally took their demo apps
and wrote like, while true semicolon do the app
semicolon done in a bunch of screens, right?
This is like the most primitive fuzz testing.
Why do you think that is?
They're just not seeing a market in machine learning?
They're changing.
They're trying to change.
They're trying to change.
And I had a pretty positive interaction with them this week.
Last week, I went on YouTube, I was just like, that's it.
I give up on AMD.
Like, this is their driver doesn't even,
like, I'm not gonna, I'm not gonna, you know,
I'll go with Intel GPUs, right?
Intel GPUs have better drivers.
So you're kind of spearheading the diversification of GPUs.
Yeah, and I'd like to extend
that diversification to everything.
I'd like to diversify the, right?
The more, my central thesis about the world
is there's things that centralize power and they're bad.
And there's things that decentralize power
and they're good.
Everything I can do to help decentralize power,
I'd like to do.
So you're really worried about the centralization
of NVIDIA, that's interesting.
And you don't have a fundamental hope
for the proliferation of ASICs, except in the cloud.
I'd like to help them with software.
No, actually there's only, the only ASIC
that is remotely successful is Google's TPU.
And the only reason that's successful
is because Google wrote a machine learning framework.
I think that you have to write
a competitive machine learning framework
in order to be able to build an ASIC.
You think Meta with PyTorch builds a competitor?
I hope so.
Okay. They have one.
They have an internal one.
Internal, I mean, public facing
with a nice cloud interface and so on.
I don't want a cloud.
You don't like cloud.
I don't like cloud.
What do you think is the fundamental limitation of cloud?
Fundamental limitation of cloud
is who owns the off switch.
So it's a power to the people.
Yeah.
And you don't like the man to have all the power.
Exactly.
All right.
And right now, the only way to do that
is with NVIDIA GPUs if you want performance and stability.
Interesting.
It's a costly investment emotionally to go with AMDs.
Well, let me sort of on a tangent ask you,
you've built quite a few PCs.
What's your advice on how to build a good custom PC
for, let's say, for the different applications that you use
for gaming, for machine learning?
Well, you shouldn't build one.
You should buy a box from the TinyCorp.
I heard rumors, whispers about this box from the TinyCorp.
What's this thing look like?
What is it?
What is it called?
It's called the TinyBox.
TinyBox.
It's $15,000.
And it's almost a paid a flop of compute.
It's over 100 gigabytes of GPU RAM.
It's over five terabytes per second of GPU memory bandwidth.
I'm gonna put like four NVMEs in RAID.
You're gonna get like 20, 30 gigabytes per second
of drive read bandwidth.
I'm gonna build like the best deep learning box that I can
that plugs into one wall outlet.
Okay, can you go through those specs again
in a little bit from memory?
Yeah, so it's almost a paid a flop of compute.
So MD Intel?
Today, I'm leaning toward AMD.
But we're pretty agnostic to the type of compute.
The main limiting spec is a 120 volt, 15 amp circuit.
Okay.
In order to like, there's a plug over there, right?
You have to be able to plug it in.
We're also gonna sell the tiny rack,
which like what's the most power you can get
into your house without arousing suspicion?
And one of the answers is an electric car charger.
Wait, where does the rack go?
Your garage.
Interesting.
The car charger.
A wall outlet is about 1500 watts.
A car charger is about 10,000 watts.
I see it.
What is the most amount of power you can get your hands on
without arousing suspicion?
That's right.
George Hotz.
Okay.
So the tiny box and you said NVMEs and RAID.
I forget what you said about memory,
all that kind of stuff.
Okay.
What about what GPUs?
Again, probably 7,900 XTXs,
but maybe 30 90s, maybe a 770s.
Those are Intel's.
You're flexible or still exploring?
I'm still exploring.
I want to deliver a really good experience to people
and yeah, what GPUs I end up going with.
Again, I'm leaning toward AMD.
We'll see.
In my email, what I said to AMD is like,
just dumping the code on GitHub is not open source.
Open source is a culture.
Open source means that your issues
are not all one-year-old stale issues.
Open source means developing in public.
And if you guys can commit to that,
I see a real future for AMD as a competitor to NVIDIA.
Well, I'd love to get a tiny box to MIT.
So whenever it's ready, let's do it.
We're taking pre-orders.
I took this from Elon.
I'm like, $100 fully refundable pre-orders.
Is it going to be like the Cybertruck
is going to take a few years or?
No, I'll try to do it faster.
It's a lot simpler.
It's a lot simpler than a truck.
Well, there's complexities not to just the,
putting the thing together,
but like shipping and all this kind of stuff.
The thing that I want to deliver to people out of the box
is being able to run 65 billion parameter llama in FP16
in real time, in like a good, like 10 tokens per second
or five tokens per second or something.
Just, it works.
Llama's running or something like llama.
Experience, yeah, or I think Falcon is the new one.
Experience a chat with the largest language model
that you can have in your house.
Yeah, from a wall plug.
From a wall plug, yeah.
Actually, for inference,
it's not like even more power would help you get more.
I think even more power would get you more.
Well, no, there's just the biggest model released
is 65 billion parameter llama as far as I know.
So it sounds like Tiny Box
will naturally pivot towards company number three
because you could just get the girlfriend or boyfriend.
That one's harder, actually.
The boyfriend is harder?
Boyfriend's harder, yeah.
I think that's a very biased statement.
I think a lot of people would just say,
what, why is it harder to replace a boyfriend
than a other girlfriend with the artificial LLM?
Because women are attracted to status and power
and men are attracted to youth and beauty.
No, I mean, that's what I mean.
Both could be a mimicable easy through the language model.
No, no machines do not have any status or real power.
I don't know, I think you both,
well, first of all, you're using language mostly
to communicate youth and beauty and power and status.
But status fundamentally is a zero-sum game, right?
Whereas youth and beauty are not.
No, I think status is a narrative you can construct.
I don't think status is real.
I don't know, I just think that that's why it's harder.
You know, yeah, maybe it is my biases.
I think status is way easier to fake.
I also think that, you know,
men are probably more desperate
and more likely to buy my products
so maybe they're a better target market.
Desperation is interesting.
Easier to fool, I can see that.
Yeah, I mean, look,
I know you can look at porn viewership numbers, right?
A lot more men watch porn than women.
You can ask why that is.
Wow, there's a lot of questions and answers.
You can get there.
Anyway, with the tiny box, how many GPUs in tiny box?
Six.
Oh, man.
And I'll tell you why it's six.
So AMD Epic processors have 128 lanes of PCIe.
I want to leave enough lanes for some drives
and I want to leave enough lanes for some networking.
How do you do cooling for something like this?
Ah, that's one of the big challenges.
Not only do I want the cooling to be good,
I want it to be quiet.
I want the tiny box to be able to sit comfortably
in your room, right?
This is really going towards the girlfriend thing
because you want to run the LLM.
I'll give a more, I mean, I can talk about
how it relates to company number one.
Comma AI.
Well, but yes, quiet, oh, quiet
because you may be potentially want to run it in a car.
No, no, quiet because you want to put this thing
in your house and you want it to coexist with you.
If it's screaming at 60 dB,
you don't want that in your house, you'll kick it out.
60 dB, yeah.
I want like 40, 45.
So how do you make the cooling quiet?
That's an interesting problem in itself.
A key trick is to actually make it big.
Ironically, it's called the tiny box.
But if I can make it big, a lot of that noise
is generated because of high pressure air.
If you look at like a 1U server,
a 1U server has these super high pressure fans
that are like super deep and they're like generous
versus if you have something that's big,
well, I can use a big,
and you know they call them big ass fans,
those ones that are like huge on the ceiling
and they're completely silent.
So tiny box will be big.
It is the, I do not want it to be large according to UPS.
I want it to be shippable as a normal package,
but that's my constraint there.
Interesting.
Well, the fan stuff,
can't it be assembled on location or no?
No.
No, it has to be, well, you're...
Look, I want to give you a great out of the box experience.
I want you to lift this thing out.
I want it to be like the Mac, you know, tiny box.
The Apple experience.
Yeah.
I love it.
Okay.
And so tiny box would run tiny grad.
Like what do you envision this whole thing to look like?
We're talking about like Linux
with a full software engineering environment
and it's just not PyTorch but tiny grad.
Yeah.
We did a poll if people want Ubuntu or Arch.
We're going to stick with Ubuntu.
Ooh, interesting.
What's your favorite flavor of Linux?
Ubuntu.
I like Ubuntu Mate, however you pronounce that.
Meat.
So how do you, you've gotten Llama into tiny grad.
You've gotten stable diffusion into tiny grad.
What was that like?
Can you comment on like, what are these models?
What's interesting about porting them?
So what's, yeah, like what are the challenges?
What's naturally, what's easy?
All that kind of stuff.
There's a really simple way
to get these models into tiny grad
and you can just export them as Onyx
and then tiny grad can run Onyx.
So the ports that I did of Llama,
stable diffusion and now Whisper
are more academic to teach me about the models
but they are cleaner than the PyTorch versions.
You can read the code.
I think the code is easier to read.
It's less lines.
There's just a few things
about the way tiny grad writes things.
Here's a complaint I have about PyTorch.
Nn.relu is a class, right?
So when you create an Nn module,
you'll put your Nnrelu as in init
and this makes no sense.
Nnrelu is completely stateless.
Why should that be a class?
But that's more like a software engineering thing
or do you think it has a cost on performance?
Oh no, it doesn't have a cost on performance.
But yeah, no, I think that it's,
that's what I mean about tiny grad's front end being cleaner.
I see.
What do you think about Mojo?
I don't know if you've been paying attention
to the programming language
that does some interesting ideas
that kind of intersect tiny grad.
I think that there's a spectrum
and like on one side you have Mojo
and on the other side you have like GGML.
GGML is this like, we're gonna run llama fast on Mac.
Okay, we're gonna expand out to a little bit
but we're gonna basically go like depth first, right?
Mojo is like, we're gonna go breadth first.
We're gonna go so wide
that we're gonna make all of Python fast
and tiny grad's in the middle.
Tiny grad is we are going to make neural networks fast.
Yeah, but they try to really get it to be fast,
compile down to specific hardware
and make that compilation step
as flexible and resilient as possible.
Yeah, but they have turn completeness.
And that limits you.
Turn.
That's what you're seeing, it's somewhere in the middle.
So you're actually going to be targeting some accelerators,
some, like some number, not one.
My goal is step one, build an equally performance stack
to PyTorch on NVIDIA and AMD, but with way less lines.
And then step two is, okay, how do we make an accelerator?
But you need step one.
You have to first build the framework
before you can build the accelerator.
Can you explain mlperf, what's your approach in general
to benchmarking tiny grad performance?
So I'm much more of a like build it the right way
and worry about performance later.
There's a bunch of things where I haven't even like
really dove into performance.
The only place where tiny grad
is competitive performance-wise right now
is on Qualcomm GPUs.
So tiny grad's actually used in OpenPilot to run the model.
So the driving model is tiny grad.
When did that happen, that transition?
About eight months ago now.
And it's two X faster than Qualcomm's library.
What's the hardware that OpenPilot runs on?
The common air?
It's a Snapdragon 845.
Okay.
So this is using the GPU.
So the GPU is an Adreno GPU.
There's like different things.
There's a really good Microsoft paper
that talks about like mobile GPUs
and why they're different from desktop GPUs.
One of the big things is in a desktop GPU,
you can use buffers.
On a mobile GPU, image textures are a lot faster.
On a mobile GPU, image textures, okay.
And so you want to be able to leverage that?
I want to be able to leverage it
in a way that it's completely generic, right?
So there's a lot of,
Xiaomi has a pretty good open source library
for mobile GPUs called Mace,
where they can generate, where they have these kernels,
but they're all hand coded, right?
So that's great if you're doing three by three comps.
That's great if you're doing dense map models,
but the minute you go off the beaten path a tiny bit,
well, your performance is nothing.
Since you mentioned OpenPilot,
I'd love to get an update in the company number one,
common AI world.
How are things going there in the development
of a semi-autonomous driving?
You know, almost no one talks about FSD anymore.
And even less people talk about OpenPilot.
We've solved the problem.
Like we solved it years ago.
What's the problem exactly?
Well, how do you-
What does solving it mean?
Solving means, how do you build a model
that outputs a human policy for driving?
How do you build a model that given a reasonable set
of sensors, outputs a human policy for driving?
So you have companies like Wayman Cruise,
which are hand coding these things
that are like quasi human policies.
Then you have Tesla and maybe even to more of an extent,
comma, asking, okay,
how do we just learn the human policy from data?
The big thing that we're doing now,
and we just put it out on Twitter.
At the beginning of comma, we published a paper
called Learning a Driving Simulator.
And the way this thing worked was it's a,
it was an auto encoder and then an RNN in the middle.
Right?
You take an auto encoder, you compress the picture,
you use an RNN, predict the next state.
And these things were, you know,
it was a laughably bad simulator, right?
This is 2015 era machine learning technology.
Today, we have VQ, VAE and transformers.
We're building drive GPT basically.
Drive GPT.
Okay.
So, and it's trained on what?
Is it trained in a self supervised way?
It's trained on all the driving data
to predict the next frame.
So really trying to learn a human policy.
What would a human do?
Well, actually our simulator is conditioned on the pose.
So it's actually a simulator.
You can put in like a state action pair
and get out the next state.
Okay.
And then once you have a simulator,
you can do RL in the simulator
and RL will get us that human policy.
So it transfers.
Yeah.
RL with a reward function,
not asking is this close to the human policy,
but asking what a human disengage if you did this behavior.
Okay.
Let me think about the distinction there.
What a human disengage.
What a human disengage.
That correlates, I guess, with the human policy,
but it could be different.
So it doesn't just say, what would a human do?
It says, what would a good human driver do?
And such that the experience is comfortable,
but also not annoying in that like the thing is very cautious.
So it's finding a nice balance.
That's interesting.
It's asking exactly the right question.
What will make our customers happy?
Right.
And that you never want to disengage.
Because usually disengagement is almost always a sign
of I'm not happy with what the system is doing.
Usually.
There's some that are just, I felt like driving
and those are always fine too,
but they're just going to look like noise in the data.
But even I felt like driving.
Maybe, yeah.
Even that's a signal.
Like, why do you feel like driving here?
You need to recalibrate your relationship with the car.
Okay, so that's really interesting.
How close are we to solving self-driving?
It's hard to say.
We haven't completely closed the loop yet.
So we don't have anything built
that truly looks like that architecture yet.
We have prototypes and there's bugs.
So we are a couple of bug fixes away.
Might take a year, might take 10.
What's the nature of the bugs?
Are these major philosophical bugs, logical bugs?
What kind of bugs are we talking about?
Oh no, they're just like stupid bugs.
And also we might just need more scale.
We just massively expanded our compute cluster at Comma.
We now have about two people worth of compute,
40 petaflops.
Well, people are different.
20 petaflops, that's a person.
It's just a unit, right?
Horses are different too,
but we still call it a horsepower.
Yeah, but there's something different about mobility
than there is about perception and action
in a very complicated world.
But yes.
Well, yeah, of course, not all flops are created equal.
If you have randomly initialized weights, it's not gonna.
Not all flops are created equal.
Some flops are doing way more useful things than others.
Yeah, yep.
Tell me about it.
Okay, so more data.
Scale means more scale and compute
or scale and scale of data?
Both.
Diversity of data?
Diversity is very important in data.
Yeah, I mean, we have, so we have about,
I think we have like 5,000 daily actives.
How would you evaluate how FSD is doing?
Pretty well. Instead of driving?
Pretty well.
How's that race going between Comma AI and FSD?
Tesla is always one to two years ahead of us.
They've always been one to two years ahead of us.
And they probably always will be
because they're not doing anything wrong.
What have you seen since the last time we talked
that are interesting architectural decisions,
training decisions, like the way they deploy stuff,
the architectures they're using in terms of the software,
how the teams are run, all that kind of stuff,
data collection, anything interesting?
I mean, I know they're moving toward
more of an end-to-end approach.
So creeping towards end-to-end as much as possible
across the whole thing,
the training, the data collection, everything.
They also have a very fancy simulator.
They're probably saying all the same things we are.
They're probably saying, we just need to optimize,
you know, what is the reward?
Well, you get negative reward for disengagement, right?
Everyone kind of knows this.
It's just a question of who can actually build
and deploy the system.
Yeah, I mean, it requires good software engineering,
I think.
Yeah.
And the right kind of hardware.
Yeah, and the hardware to run it.
You still don't believe in cloud in that regard?
I have a compute cluster in my office, 800 amps.
Tiny grad.
It's 40 kilowatts at idle, our data center.
Dives me crazy.
With 40 kilowatts just burning
just when the computers are idle.
Just when I-
Oh, sorry, sorry, compute cluster.
Compute cluster, I got it.
It's not a data center.
Yeah, yeah.
No, data centers are clouds.
We don't have clouds.
Data centers have air conditioners.
We have fans.
That makes it a compute cluster.
I'm guessing this is a kind of a legal distinction
that's- Sure, yeah.
We have a compute cluster.
You said that you don't think LLMs have consciousness,
or at least not more than a chicken.
Do you think they can reason?
Is there something interesting to you
about the word reason, about some of the capabilities
that we think is kind of human,
to be able to integrate complicated information
and through a chain of thought arrive at a conclusion
that feels novel, a novel integration of disparate facts?
Yeah, I don't think that there's,
I think that they can reason better than a lot of people.
Yeah, isn't that amazing to you, though?
Isn't that like an incredible thing
that a transformer can achieve?
I mean, I think that calculators can add better
than a lot of people.
But language feels like reasoning
through the process of language,
which looks a lot like thought.
Making brilliancies in chess,
which feels a lot like thought.
Whatever new thing that AI can do,
everybody thinks is brilliant,
and then like 20 years go by and they're like,
well, yeah, but chess, that's like mechanical.
Like adding, that's like mechanical.
So you think language is not that special?
It's like chess.
It's like chess, and it's like-
I don't know, because it's very human,
we take it, listen, there is something different
between chess and language.
Chess is a game that a subset of population plays.
Language is something we use nonstop
for all of our human interaction,
and human interaction is fundamental to society.
So it's like, holy shit, this language thing
is not so difficult to like create in the machine.
The problem is if you go back to 1960
and you tell them that you have a machine
that can play amazing chess,
of course someone in 1960 will tell you
that machine is intelligent.
Someone in 2010 won't, what's changed, right?
Today, we think that these machines
that have language are intelligent,
but I think in 20 years, we're going to be like,
yeah, but can it reproduce?
So reproduction, yeah, we may redefine
what it means to be, what is it,
a high-performance living organism on Earth?
Humans are always going to define a niche for themselves.
Like, well, you know, we're better than the machines
because we can, you know, and like they tried creative
for a bit, but no one believes that one anymore.
But niche, is that delusional,
or is there some accuracy to that?
Because maybe like with chess, you start to realize,
like, that we have ill-conceived notions
of what makes humans special,
like the apex organism on Earth.
Yeah, and I think maybe we're going to go through
that same thing with language,
and that same thing with creativity.
But language carries these notions of truth and so on.
And so we might be like, wait,
maybe truth is not carried by language.
Maybe there's like a deeper thing.
But the niche is getting smaller.
Oh boy.
But no, no, no, you don't understand.
Humans are created by God,
and machines are created by humans, therefore.
Right, like that'll be the last niche we have.
So what do you think about this,
the rapid development of LLMs?
If you could just like stick on that.
It's still incredibly impressive, like with Chajubiti.
Just even Chajubiti, what are your thoughts
about reinforcement learning with human feedback
on these large language models?
I'd like to go back to when calculators first came out
and, or computers.
And like, I wasn't around.
Look, I'm 33 years old.
And to like see how that affected
like society.
Maybe you're right.
So I want to put on the big picture hat here.
Oh my God, a refrigerator, wow.
The refrigerator, electricity, all that kind of stuff.
But, you know, with the internet,
large language models seeming human-like,
basically passing a Turing test.
It seems it might have really at scale
rapid transformative effects on society.
But you're saying like other technologies have as well.
So maybe calculator's not the best example of that.
Cause that just seems like, well, no, maybe calculator.
But the poor milk man,
the day he learned about refrigerators,
he's like, I'm done.
You're telling me you can just keep the milk in your house?
You don't need me to deliver it every day, I'm done.
Well, yeah, you have to actually look at the practical
impacts of certain technologies that they've had.
Yeah, probably electricity is a big one.
And also how rapidly it's spread.
Man, the internet is a big one.
I do think it's different this time though.
Yeah, it just feels like stuff-
The niche is getting smaller.
The niche of humans that makes humans special.
It feels like it's getting smaller rapidly though.
Doesn't it?
Or is that just a feeling we dramatize everything?
I think we dramatize everything.
I think that you asked the milk man
when he saw our refrigerators.
And they're going to have one of these in every home?
Yeah, yeah, yeah.
Yeah, but boy is it impressive.
So much more impressive than seeing
a chess world champion AI system.
I disagree actually.
I disagree.
I think things like Mu Zero and AlphaGo
are so much more impressive.
Because these things are playing
beyond the highest human level.
The language models are writing middle school level essays.
And people are like, wow, it's a great essay.
It's a great five paragraph essay
about the causes of the civil war.
Okay, forget the civil war, just generating code, codex.
You're saying it's mediocre code.
Terrible.
I don't think it's terrible.
I think it's just mediocre code.
Often close to correct, like for mediocre purposes.
That's the scariest kind of code.
I spent 5% of time typing and 95% of time debugging.
The last thing I want is close to correct code.
I want a machine that can help me with the debugging,
not with the typing.
You know, it's like L2, level two driving,
similar kind of thing.
Yeah, you still should be a good programmer
in order to modify, I wouldn't even say debugging.
It's just modifying the code, reading it.
Don't think it's like level two driving.
I think driving is not tool complete and programming is.
Meaning you don't use like the best possible tools to drive.
You're not like, cars have basically the same interface
for the last 50 years.
Computers have a radically different interface.
Okay, can you describe the concept of tool complete?
So think about the difference between a car from 1980
and a car from today.
No difference really.
It's got a bunch of pedals, it's got a steering wheel.
Great.
Maybe now it has a few ADAS features,
but it's pretty much the same car, right?
You have no problem getting into a 1980 car and driving it.
Take a programmer today who spent their whole life
doing JavaScript and you put them in an Apple IIe prompt
and you tell them about the line numbers in basic.
But how do I insert something between line 17 and 18?
Oh, wow.
But so in tool you're putting in the programming languages.
So it's just the entirety stack of the tooling.
Exactly.
So it's not just like the IDs or something like this.
It's everything.
Yes, it's IDEs, the languages, the runtimes.
It's everything and programming is tool complete.
So like almost if codex or copilot are helping you,
that actually probably means that your framework
or library is bad and there's too much boilerplate in it.
Yeah, but don't you think so much programming
has boilerplate?
Tinygrad is now 2,700 lines
and it can run llama and stable diffusion.
And all of this stuff is in 2,700 lines.
Boilerplate and abstraction indirections
and all these things are just bad code.
Well, let's talk about good code and bad code.
It's a, I would say, I don't know,
for generic scripts that I write just offhand,
like 80% of it is written by GPT.
Just like quick, like offhand stuff.
So not like libraries, not like performing code,
not stuff for robotics and so on, just quick stuff.
Because your basic, so much of programming
is doing some, yeah, boilerplate.
But to do so efficiently and quickly,
because you can't really automate it fully
with generic method, like a generic kind of ID
type of recommendation or something like this,
you do need to have some of the complexity
of language models.
Yeah, I guess if I was really writing,
maybe today, if I wrote a lot of data parsing stuff,
I mean, I don't play CTFs anymore,
but if I still play CTFs, a lot of it is just like
you have to write a parser for this data format.
Like I wonder, or like admin of code.
I wonder when the models are gonna start to help
with that kind of code, and they may.
And the models also may help you with speed.
And the models are very fast.
But where the models won't, my programming speed
is not at all limited by my typing speed.
And in very few cases it is, yes.
If I'm writing some script to just like parse
some weird data format, sure, my programming speed
is limited by my typing speed.
What about looking stuff up?
Because that's essentially a more efficient lookup, right?
You know, when I was at Twitter,
I tried to use ChatGPT to like ask some questions,
like what's the API for this?
And it would just hallucinate.
It would just give me completely made up API functions
that sounded real.
Well, do you think that's just a temporary kind of stage?
No.
You don't think it'll get better and better and better
in this kind of stuff?
Because like it only hallucinates stuff in the edge cases.
Yes, yes.
If you're writing generic code, it's actually pretty good.
Yes, if you are writing an absolute basic like React app
with a button, it's not gonna hallucinate, sure.
There's kind of ways to fix the hallucination problem.
I think Facebook has an interesting paper,
it's called Atlas.
And it's actually weird the way that we do
language models right now where all of the information
is in the weights.
And the human brain is not really like this.
There's like a hippocampus and a memory system.
So why don't LLMs have a memory system?
And there's people working on them.
I think future LLMs are gonna be like smaller,
but are going to run looping on themselves
and are going to have retrieval systems.
And the thing about using a retrieval system
is you can cite sources explicitly.
Which is really helpful to integrate the human
into the loop of the thing.
Because you can go check the sources
and you can investigate.
So whenever the thing is hallucinating,
you can like have the human supervision.
That's pushing it towards level two kind of driving.
That's gonna kill Google.
Wait, which part?
When someone makes an LLM that's capable
of citing its sources, it will kill Google.
LLM that's citing its sources
because that's basically a search engine.
That's what people want in a search engine.
But also Google might be the people that build it.
Maybe.
And put ads on it.
I'd count them out.
Why is that?
What do you think?
Who wins this race?
We got, who are the competitors?
All right.
We got Tiny Corp.
I don't know if that's,
yeah, I mean, you're a legitimate competitor in that.
I'm not trying to compete on that.
You're not.
No, not as a competitor.
You're just gonna accidentally stumble
into that competition.
You don't think you might build a search engine
to replace Google search?
When I started Kama, I said over and over again,
I'm going to win self-driving cars.
I still believe that.
I have never said I'm going to win search
with the Tiny Corp and I'm never going to say that
because I won't.
The night is still young.
We don't, you don't know how hard is it to win search
in this new route.
Like it's, it feels, I mean, one of the things
that Chat GPT kind of shows that there could be
a few interesting tricks that really have,
that create a really compelling product.
Some startup's going to figure it out.
I think, I think if you ask me,
like Google is still the number one webpage,
I think by the end of the decade,
Google won't be the number one webpage anymore.
So you don't think Google,
because of the, how big the corporation is?
Look, I would put a lot more money on Mark Zuckerberg.
Why is that?
Because Mark Zuckerberg's alive.
Like this is old Paul Graham essay.
Startups are either alive or dead.
Google's dead.
Facebook's alive. Versus Facebook is alive.
Meta, meta.
You see what I mean?
Like, that's just like, like, like Mark Zuckerberg.
This is Mark Zuckerberg reading that Paul Graham essay
and being like, I'm going to show everyone how alive we are.
I'm going to change the name.
So you don't think there's this gutsy pivoting engine
that like Google doesn't have that,
the kind of engine that the startup has,
like constantly being alive, I guess.
When I listened to your Sam Altman podcast,
he talked about the button.
Everyone who talks about AI talks about the button,
to turn it off, right?
Do we have a button to turn off Google?
Is anybody in the world capable of shutting Google down?
What does that mean exactly?
The company or the search engine?
So we shut the search engine down.
Could we shut the company down?
Either.
Can you elaborate on the value of that question?
Does Sundar Prashay have the authority
to turn off google.com tomorrow?
Who has the authority?
That's a good question, right?
Does anyone?
Does anyone?
Yeah, I'm sure.
Are you sure?
No, they have the technical power,
but do they have the authority?
Let's say Sundar Prashay made this his sole mission,
came into Google tomorrow and said,
I'm gonna shut google.com down.
Yeah.
I don't think he'd keep his position too long.
And what is the mechanism
by which he wouldn't keep his position?
Well, boards and shares and corporate undermining
and oh my God, our revenue is zero now.
Okay, so what's the case you're making here?
So the capitalist machine prevents you
from having the button.
Yeah, and it will have it.
I mean, this is true for the AIs too, right?
There's no turning the AIs off.
There's no button.
You can't press it.
Now, does Mark Zuckerberg have that button for facebook.com?
Yes, probably more.
I think he does.
I think he does.
And this is exactly what I mean
and why I bet on him so much more than I bet on Google.
I guess you could say Elon has similar stuff.
Oh, Elon has the button.
Yeah.
Does Elon, can Elon fire the missiles?
Can he fire the missiles?
I think some questions are better left unasked.
Right?
I mean, you know, a rocket and an ICBM.
Well, you're a rocket that can land anywhere.
Isn't that an ICBM?
Well, yeah, you know, don't ask too many questions.
My God.
But the positive side of the button
is that you can innovate aggressively is what you're saying.
Which is what's required with turning LLM
into a search engine.
I would bet on a startup.
I bet on-
Because it's so easy, right?
I bet on something that looks like mid journey,
but for search.
Just is able to set sources, loop on itself.
I mean, it just feels like one model can take off, right?
And that nice wrapper.
And some of it, I mean, it's hard to like create a product
that just works really nicely, stably.
The other thing that's going to be cool
is there is some aspect of a winner take all effect, right?
Like once someone starts deploying a product
that gets a lot of usage, and you see this with OpenAI,
they are going to get the data set
to train future versions of the model.
Yeah.
They are going to be able to, you know,
I was asked at Google image search when I worked there
like almost 15 years ago now,
how does Google know which image is an apple?
And I said, the metadata.
And they're like, yeah, that works about half the time.
How does Google know?
You'll see the role apples on the front page
when you search Apple.
And I don't know, I didn't come up with the answer.
The guy's like, well, that's what people click on
when they search Apple.
I'm like, oh yeah.
Yeah, yeah, that data is really, really powerful.
It's the human supervision.
What do you think are the chances?
What do you think in general that Llama was open-sourced?
I just did a conversation with Mark Zuckerberg
and he's all in on open source.
Who would have thought that Mark Zuckerberg
would be the good guy?
No, I mean it.
Who would have thought anything in this world?
It's hard to know.
But open source to you ultimately is a good thing here.
Undoubtedly.
What's ironic about all these AI safety people
is they are going to build the exact thing they fear.
We need to have one model that we control and align.
This is the only way you end up paper clipped.
There's no way you end up paper clipped
if everybody has an AI.
So open sourcing is the way
to fight the paperclip maximizer.
Absolutely.
It's the only way.
You think you're going to control it,
you're not going to control it.
So the criticism you have for the AI safety folks
is that there is a belief and a desire for control.
And that belief and desire for centralized control
of dangerous AI systems is not good.
Sam Altman won't tell you that GPT-4
has 220 billion parameters and is a 16-way mixture model
with eight sets of weights.
Who did you have to murder to get that information?
All right.
I mean, look.
Everyone at OpenAI knows what I just said was true.
Now, ask the question, really.
It upsets me when I, like GPT-2,
when OpenAI came out with GPT-2
and raised a whole fake AI safety thing about that,
I mean, now the model is laughable.
Like, they used AI safety to hype up their company
and it's disgusting.
Or the flip side of that is they used
a relatively weak model, in retrospect,
to explore how do we do AI safety correctly?
How do we release things?
How do we go through the process?
I don't know if-
Sure, sure.
All right, all right, all right.
That's the charitable interpretation.
I don't know how much hype there is in AI safety, honestly.
Oh, there's so much hype.
At least on Twitter, I don't know.
Maybe Twitter's not real life.
Twitter's not real life.
Come on.
In terms of hype, I mean, I don't,
I think OpenAI has been finding an interesting balance
between transparency and putting value on AI safety.
You don't think, you think just go all out open source,
so do what LAMA is doing.
Absolutely, yeah.
So do, like, open source, this is a tough question,
which is open source, both the base, the foundation model,
and the fine-tuned one.
So, like, the model that can be ultra-racist and dangerous
and, like, tell you how to build a nuclear weapon.
Oh my God, have you met humans, right?
Like, half of these AI align-
I haven't met most humans.
This allows you to meet every human.
Yeah, I know, but half of these AI alignment problems
are just human alignment problems.
And that's what's also so scary about the language they use.
It's like, it's not the machines you want to align, it's me.
But here's the thing.
It makes it very accessible to ask very,
questions where the answers have dangerous consequences
if you were to act on them.
I mean, yeah.
Welcome to the world.
Well, no, for me, there's a lot of friction
if I want to find out how to, I don't know,
blow up something.
No, there's not a lot of friction, that's so easy.
No, like, what do I search?
Do I use Bing, or do I, which search engine do I use?
No, there's, like, lots of stuff.
No, it feels like I have to keep clicking on a lot of this.
First off, first off, first off, first off,
anyone who's stupid enough to search
for how to blow up a building in my neighborhood
is not smart enough to build a bomb, right?
Are you sure about that?
Yes.
I feel like, I feel like a language model
makes it more accessible for that person
who's not smart enough to do-
They're not gonna build a bomb, trust me.
The people who are incapable of figuring out
how to, like, ask that question a bit more academically
and get a real answer from it
are not capable of procuring the materials,
which are somewhat controlled, to build a bomb.
No, I think LLM makes it more accessible
to people with money without the technical know-how, right?
To build, like, do you really need to know
how to build a bomb to build a bomb?
You can hire people, you can find, like-
Or you can hire people to build a, you know what?
I was asking this question on my stream,
like, can Jeff Bezos hire a hitman?
Probably not.
But a language model can probably help you out.
Yeah, and you'll still go to jail, right?
Like, it's not like the language model is God.
Like, the language model, it's like,
you literally just hired someone on Fiverr, but you-
Okay, okay, GPT-4, in terms of finding a hitman,
is, like, asking Fiverr how to find a hitman.
I understand.
But don't you think- As in WikiHow, you know?
WikiHow.
But don't you think GPT-5 will be better?
Because don't you think that information
is out there on the internet?
I mean, yeah, and I think that if someone
is actually serious enough to hire a hitman or build a bomb,
they'd also be serious enough to find the information.
I don't think so.
I think it makes it more accessible.
If you have enough money to buy a hitman,
I think it just decreases the friction
of how hard is it to find that kind of hitman.
I honestly think there's a jump in ease and scale
of how much harm you can do.
And I don't mean harm with language.
I mean harm with actual violence.
What you're basically saying is, like, okay,
what's going to happen is these people
who are not intelligent are going to use machines
to augment their intelligence.
And now, intelligent people and machines,
intelligence is scary.
Intelligent agents are scary.
When I'm in the woods, the scariest animal to meet
is a human, right?
No, no, no, no.
Look, there's nice California humans.
Like, I see you're wearing street clothes
and Nikes, all right, fine.
But you look like you've been a human
who's been in the woods for a while?
Yeah.
I'm more scared of you than a bear.
That's what they say about the Amazon.
When you go to the Amazon, it's the human tribes.
Oh, yeah.
So intelligence is scary, right?
So to ask this question in a generic way,
you're like, what if we took everybody
who maybe has ill intention but is not so intelligent
and gave them intelligence, right?
So we should have intelligence control, of course.
We should only give intelligence to good people.
And that is the absolutely horrifying idea.
So to you, the best defense is actually,
the best defense is to give more intelligence
to the good guys and intelligence.
Give intelligence to everybody.
Give intelligence to everybody.
You know what, it's not even like guns, right?
Like, people say this about guns.
You know, what's the best defense against a bad guy
with a gun, a good guy with a gun?
Like, I kind of subscribe to that,
but I really subscribe to that with intelligence.
Yeah, in a fundamental way, I agree with you.
But there's just feels like so much uncertainty
and so much can happen rapidly
that you can lose a lot of control
and you can do a lot of damage.
Oh, no, we can lose control?
Yes, thank God.
Yeah.
I hope we can, I hope they lose control.
I want them to lose control more than anything else.
I think when you lose control, you can do a lot of damage,
but you can do more damage when you centralize
and hold on to control, is the point you're-
Centralized and held control is tyranny, right?
I will always, I don't like anarchy either,
but I'll always take anarchy over tyranny.
Anarchy, you have a chance.
This human civilization we've got going on
is quite interesting.
I mean, I agree with you.
So do you open source is the way forward here?
So you admire what Facebook is doing here
or what Meta is doing with the release of them.
A lot, a lot.
I lost $80,000 last year investing in Meta.
And when they released Llama, I'm like,
yeah, whatever man, that was worth it.
It was worth it.
Do you think Google and OpenAI with Microsoft
will match what Meta is doing or no?
So if I were a researcher,
why would you want to work at OpenAI?
Like, you know, you're just, you're on the bad team.
Like, I mean it, like you're on the bad team
who can't even say that GPT-4 has 220 billion parameters.
So close source to use the bad team.
Not only close source.
I'm not saying you need to make your model weights open.
I'm not saying that.
I totally understand we're keeping our model weights closed
because that's our product, right?
That's fine.
I'm saying like, because of AI safety reasons,
we can't tell you the number of billions
of parameters in the model.
That's just the bad guys.
Just because you're mocking AI safety
doesn't mean it's not real.
Oh, of course.
Is it possible that these things
can really do a lot of damage that we don't know?
Oh my God, yes.
Intelligence is so dangerous.
Be it human intelligence or machine intelligence.
Intelligence is dangerous.
But machine intelligence is so much easier
to deploy at scale, like rapidly.
Like what, okay.
If you have human-like bots on Twitter.
All right.
And you have like a thousand of them
create a whole narrative.
Like you can manipulate millions of people.
But you mean like the intelligence agencies
in America are doing right now?
Yeah, but they're not doing it that well.
It feels like you can do a lot.
They're doing it pretty well.
Well, I think they're doing a pretty good job.
I suspect they're not nearly as good
as a bunch of GPT-fueled bots could be.
Well, I mean, of course they're looking
into the latest technologies
for control of people, of course.
But I think there's a George Hotz-type character
that can do a better job than the entirety of them.
You don't think so. No way.
No, and I'll tell you why the George Hotz character can't.
And I thought about this a lot with hacking.
Like I can find exploits in web browsers.
I probably still can.
I mean, I was better when I was 24,
but the thing that I lack is the ability
to slowly and steadily deploy them over five years.
And this is what intelligence agencies are very good at.
Intelligence agencies don't have
the most sophisticated technology.
They just have-
Endurance?
Endurance, yeah.
Yeah, the financial backing
and the infrastructure for the endurance.
So the more we can decentralize power,
like you could make an argument, by the way,
that nobody should have these things.
And I would defend that argument.
I would, like you're saying, look,
LLMs and AI and machine intelligence
can cause a lot of harm, so nobody should have it.
And I will respect someone philosophically
with that position.
Just like I will respect someone philosophically
with a position that nobody should have guns, right?
But I will not respect philosophically
with only the trusted authorities
should have access to this.
Who are the trusted authorities?
You know what?
I'm not worried about alignment
between AI company and their machines.
I'm worried about alignment between me and AI company.
What do you think Eliezer Yudkowsky would say to you?
Because he's really against open source.
I know.
And I thought about this.
I thought about this.
And I think this comes down to
a repeated misunderstanding of political power
by the rationalists.
Interesting.
I think that Eliezer Yudkowsky is scared of these things,
and I am scared of these things too.
Everyone should be scared of these things.
These things are scary.
But now you ask about the two possible futures.
One where a small, trusted, centralized group of people
has them, and the other where everyone has them.
And I am much less scared of the second future
than the first.
Well, there's a small, trusted group of people
that have control of our nuclear weapons.
There's a difference.
Again, a nuclear weapon cannot be deployed tactically,
and a nuclear weapon is not a defense
against a nuclear weapon.
Except maybe in some philosophical mind game kind of way.
But AI is different how exactly?
Okay, let's say the intelligence agency
deploys a million bots on Twitter,
or a thousand bots on Twitter
to try to convince me of a point.
Imagine I had a powerful AI running on my computer,
saying, okay, nice psy-op, nice psy-op, nice psy-op, okay.
Here's a psy-op, I filtered it out for you.
Yeah, I mean, so you have fundamentally hope for that,
for the defense of psy-op.
I'm not even like, I don't even mean these things
in truly horrible ways.
I mean these things in straight up ad blocker, right?
Straight up ad blocker, I don't want ads.
But they are always finding, imagine I had an AI
that could just block all the ads from me.
So you believe in the power of the people
to always create an ad blocker.
Yeah, I mean, I kind of share that belief.
I have, that's one of the deepest optimisms I have
is just like, there's a lot of good guys.
So to give, you don't, you shouldn't handpick them.
Just throw out powerful technology out there,
and the good guys will outnumber and outpower the bad guys.
Yeah, I'm not even gonna say there's a lot of good guys.
I'm saying that good outnumber is bad, right?
Good outnumber is bad.
In skill and performance.
Yeah, definitely in skill and performance,
probably just a number too, probably just in general.
I mean, if you believe philosophically in democracy,
you obviously believe that, that good outnumber is bad.
And like the only, if you give it
to a small number of people,
there's a chance you gave it to good people,
but there's also a chance you gave it to bad people.
If you give it to everybody, well, if good outnumber is bad,
then you definitely gave it to more good people than bad.
That's really interesting.
So that's on the safety grounds,
but then also, of course, there's other motivations,
like you don't wanna give away your secret sauce.
Well, that's, I mean, look, I respect capitalism.
I don't think that, I think that it would be polite
for you to make model architectures open source
and fundamental breakthroughs open source.
I don't think you have to make weights open source.
You know what's interesting is that,
like there's so many possible trajectories in human history
where you could have the next Google be open source.
So for example, I don't know if that connection is accurate,
but Wikipedia made a lot of interesting decisions
not to put ads, like Wikipedia is basically open source.
You could think of it that way.
And like, that's one of the main websites on the internet.
And like, it didn't have to be that way.
It could have been like,
Google could have created Wikipedia, put ads on it.
You could probably run amazing ads now on Wikipedia.
You wouldn't have to keep asking for money,
but it's interesting, right?
So llama, open source llama,
derivatives of open source llama might win the internet.
I sure hope so.
I hope to see another era.
You know, the kids today don't know
how good the internet used to be.
And I don't think this is just, oh, come on,
like everyone's nostalgic for their past,
but I actually think the internet
before small groups of weaponized corporate
and government interests took it over was a beautiful place.
You know, those small number of companies
have created some sexy products.
But you're saying overall, in the long arc of history,
the centralization of power they have
like suffocated the human spirit at scale.
Here's a question to ask
about those beautiful, sexy products.
Imagine 2000 Google to 2010 Google, right?
A lot changed.
We got Maps, we got Gmail.
We lost a lot of products too, I think.
Yeah, I mean, some were probably,
we've got Chrome, right?
And now let's go from 2010, we've got Android.
Now let's go from 2010 to 2020.
What does Google have?
Well, search engine, Maps, Mail, Android, and Chrome.
Oh, I see.
The internet was this,
you know, I was Times person of the year in 2006, yeah.
I love this.
It's you was Times person of the year in 2006, right?
Like that's, you know, so quickly did people forget.
And I think some of it's social media.
I think some of it, I hope, look, I hope that I don't,
it's possible that some very sinister things happened.
I don't know.
I think it might just be like the effects of social media.
But something happened in the last 20 years.
Oh, okay, so you're just being an old man
who's worried about the, I think there's always,
it goes, it's the cycle thing.
There's ups and downs,
and I think people rediscover the power
of distributed, of decentralized.
I mean, that's kind of like
what the whole cryptocurrency is trying,
like that, I think crypto is just carrying the flame
of that spirit of like, stuff should be decentralized.
It's just such a shame that they all got rich, you know?
Yeah.
If you took all the money out of crypto,
it would have been a beautiful place.
Yeah.
But no, I mean, these people, you know,
they sucked all the value out of it and took it.
Yeah, money kind of corrupts the mind somehow.
It becomes a drug.
You corrupted all of crypto.
You had coins worth billions of dollars that had zero use.
You still have hope for crypto?
Sure, I have hope for the ideas, I really do.
Yeah, I mean, you know, I want the U.S. dollar to collapse.
I do.
George Watts.
Well, let me sort of, on the AI SAT,
do you think there's some interesting questions there,
though, to solve for the open source community
in this case?
So like alignment, for example, or the control problem.
Like if you really have super powerful,
you said it's scary, what do we do with it?
So not control, not centralized control,
but like if you were then, you're going to see some guy
or gal release a super powerful language model, open source,
and here you are, George Watts, thinking, holy shit, okay,
what ideas do I have to combat this thing?
So what ideas would you have?
I am so much not worried about the machine
independently doing harm.
That's what some of these AI safety people seem to think.
They somehow seem to think that the machine
like independently is going to rebel against its creator.
So you don't think you'll find autonomy?
No, this is sci-fi B movie garbage.
Okay, what if the thing writes code,
basically writes viruses?
If the thing writes viruses,
it's because the human told it to write viruses.
Yeah, but there's some things you can't
like put back in the box.
That's kind of the whole point is it kind of spreads.
Give it access to the internet, it spreads,
installs itself, modifies your shit.
B, B, B, B plot sci-fi, not real.
I'm trying to work,
I'm trying to get better at my plot writing.
The thing that worries me,
I mean, we have a real danger to discuss
and that is bad humans using the thing
to do whatever bad unaligned AI thing you want.
But this goes to your previous concern
that who gets to define who's a good human,
who's a bad human.
Nobody does, we give it to everybody.
And if you do anything besides give it to everybody,
trust me, the bad humans will get it.
And that's who gets power.
It's always the bad humans who get power.
Okay, power.
And power turns even slightly good humans to bad.
Sure.
What's the intuition you have?
I don't know.
I don't think everyone.
I don't think everyone.
I just think that like,
here's the saying that I put in one of my blog posts.
When I was in the hacking world,
I found 95% of people to be good
and 5% of people to be bad.
Like just who I personally judged
as good people and bad people.
Like they believed about like good things for the world.
They wanted like flourishing and they wanted, you know,
growth and they wanted things I consider good, right?
I came into the business world with comma
and I found the exact opposite.
I found 5% of people good and 95% of people bad.
I found a world that promotes psychopathy.
I wonder what that means.
I wonder if that care, like,
I wonder if that's anecdotal or if it,
if there's truth to that.
There's something about capitalism at the core
that promotes the people that run capitalism
that promotes psychopathy.
That saying may of course be my own biases, right?
That may be my own biases that these people
are a lot more aligned with me than these other people.
Right?
So, you know, I can certainly recognize that.
But, you know, in general, I mean,
this is like the common sense maxim,
which is the people who end up getting power
are never the ones you want with them.
But do you have a concern of super intelligent AGI?
Open sourced?
And then what do you do with that?
I'm not saying control it, it's open source.
What do we do with this human species?
That's not up to me.
I mean, you know, like I'm not a central planner.
Well, not a central planner, but you'll probably tweet,
there's a few days left to live for the human species.
I have my ideas of what to do with it
and everyone else has their ideas of what to do with it.
May the best ideas win.
But at this point, do you brainstorm?
Like, because it's not regulation.
It could be decentralized regulation
where people agree that this is just like,
we create tools that make it more difficult for you
to maybe make it more difficult for code to spread,
you know, antivirus software, this kind of thing.
But this-
You're saying that you should build AI firewalls?
That sounds good.
You should definitely be running an AI firewall.
Yeah, right, exactly.
You should be running an AI firewall to your mind.
Right.
You're constantly under, you know-
That's such an interesting idea.
Info wars, man, like.
I don't know if you're being sarcastic or not.
No, I'm dead serious.
But I think there's power to that.
It's like, how do I protect my mind?
From influence of human-like
or superhuman intelligent bots?
I is not being, I would pay so much money for that product.
I would pay so much money for that product.
I would, you know how much money I'd pay
just for a spam filter that works?
Well, on Twitter sometimes I would like to have
a protection mechanism for my mind from the outrage mobs.
Because they feel like bot-like behavior.
It's like, there's a large number of people
that will just grab a viral narrative
and attack anyone else that believes otherwise.
And it's like-
Whenever someone's telling me some story from the news,
I'm always like, I don't want to hear it, CIA op, bro.
It's a CIA op, bro.
Like, it doesn't matter if that's true or not.
It's just trying to influence your mind.
You're repeating an ad to me.
But the viral mobs, this is like, yeah, they're-
To me, a defense against those mobs
is just getting multiple perspectives always
from sources that make you feel kind of
like you're getting smarter.
And just actually just basically feels good.
Like a good documentary just feels good.
Something feels good about it.
It's well done.
It's like, oh, okay, I never thought of it this way.
This just feels good.
Sometimes the outrage mobs,
even if they have a good point behind it,
when they're like mocking and derisive and just aggressive,
you're with us or against us, this fucking-
This is why I delete my tweets.
Yeah, why'd you do that?
I was, you know, I missed your tweets.
You know what it is?
The algorithm promotes toxicity.
Yeah.
And like, you know, I think Elon has a much better chance
of fixing it than the previous regime.
Yeah.
But to solve this problem, to solve,
like to build a social network that is actually not toxic
without moderation.
Like not the stick, but carrots.
Where people look for goodness,
make it catalyze the process of connecting cool people
and being cool to each other.
Yeah.
Without ever censoring.
Without ever censoring.
And like Scott Alexander has a blog post I like
where he talks about moderation is not censorship, right?
Like all moderation you want to put on Twitter, right?
Like you could totally make this moderation,
like just a, you don't have to block it for everybody.
You can just have like a filter button, right?
That people can turn off
if they would like safe search for Twitter, right?
Like someone could just turn that off, right?
So like, but then you'd like take this idea
to an extreme, right?
Well, the network should just show you,
this is a couch surfing CEO thing, right?
If it shows you, right now these algorithms
are designed to maximize engagement.
Well, it turns out outrage maximizes engagement.
Quirk of human, quirk of the human mind, right?
Just this, I fall for it, everyone falls for it.
So yeah, you got to figure out how to maximize
for something other than engagement.
And I actually believe that you can make money
with that too, so it's not,
I don't think engagement is the only way to make money.
I actually think it's incredible
that we're starting to see, I think again,
Elon's doing so much stuff right with Twitter,
like charging people money.
As soon as you charge people money,
they're no longer the product, they're the customer.
And then they can start building something
that's good for the customer
and not good for the other customer,
which is the ad agencies.
As in picked up steam.
I pay for Twitter, doesn't even get me anything.
It's my donation to this new business model
that's hopefully working out.
Sure, but for this business model to work,
it's like most people should be signed up to Twitter.
And so the way it was, there was something
perhaps not compelling or something like this to people.
I don't think you need most people at all.
I think that, why do I need most people, right?
Don't make an 8,000 person company,
make a 50 person company.
Well, so speaking of which,
you worked at Twitter for a bit.
I did.
As an intern, the world's greatest intern.
All right.
There's been better.
There's been better.
Tell me about your time at Twitter.
How did it come about?
And what did you learn from the experience?
So I deleted my first Twitter in 2010.
I had over a hundred thousand followers
back when that actually meant something.
And I just saw, you know,
my coworker summarized it well.
He's like, whenever I see someone's Twitter page,
I either think the same of them or less of them.
I never think more of them.
Yeah.
Right?
Like, you know, I don't want to mention any names,
but like some people who like, you know,
maybe you would like read their books
and you would respect them.
You see them on Twitter and you're like, okay, dude.
Yeah, but there are some people who are the same.
You know who I respect a lot?
Are people that just post really good technical stuff.
Yeah.
And I guess, I don't know,
I think I respect them more for it.
Cause you realize, oh, this wasn't,
there's like so much depth to this person,
to their technical understanding
of so many different topics.
Okay.
So I try to follow people.
I try to consume stuff
that's technical machine learning content.
There's probably a few of those people.
And the problem is inherently
what the algorithm rewards, right?
And people think about these algorithms.
People think that they are terrible, awful things.
And, you know, I love that Elon open sourced it
because I mean, what it does is actually pretty obvious.
It just predicts what you are likely to retweet
and like and linger on.
That's what all these algorithms do.
That's what TikTok does.
So all these recommendation engines do.
And it turns out that the thing
that you are most likely to interact with is outreach.
And that's a quirk of the human condition.
I mean, and there's different flavors of outrage.
It doesn't have to be, it could be mockery.
You'd be outraged.
The topic of outrage could be different.
It could be an idea.
It could be a person.
It could be, maybe there's a better word than outrage.
It could be drama.
Sure.
Drama. All this kind of stuff.
Yeah.
But doesn't feel like when you consume it,
it's a constructive thing for the individuals
that consume it in the longterm.
Yeah.
So my time there,
I absolutely couldn't believe I got crazy amount of hate
on Twitter for working at Twitter.
It seems like people associated with this.
I think maybe you were exposed to some of this.
So connection to Elon or is it working at Twitter?
Twitter and Elon, like the whole-
Because Elon's gotten a bit spicy during that time.
A bit political, a bit-
Yeah.
Yeah.
I remember one of my tweets,
it was never go full Republican.
And Elon liked it.
You know, I think, I think, you know.
Oh boy.
Yeah, I mean, there's a rollercoaster of that,
but being political on Twitter.
Yeah. Boy.
Yeah.
And also being, just attacking anybody on Twitter,
it comes back at you harder.
And if it's political and attacks.
Sure.
Sure, absolutely.
And then letting sort of deplatformed people back on
even adds more fun to the beautiful chaos.
I was hoping.
And like, I remember when Elon talked about buying Twitter,
like six months earlier,
he was talking about like a principled commitment
to free speech.
And I'm a big believer and fan of that.
I would love to see an actual
principled commitment to free speech.
Of course, this isn't quite what happened.
Instead of the oligarchy deciding what to ban,
you had a monarchy deciding what to ban, right?
Instead of, you know, all the Twitter file shadow,
really, the oligarchy just decides what?
Cloth masks are ineffective against COVID.
That's a true statement.
Every doctor in 2019 knew it.
And now I'm banned on Twitter for saying it?
Interesting. Oligarchy.
So now you have a monarchy and, you know,
he bans things he doesn't like.
So, you know, it's just different power.
And like, you know, maybe I align more with him
than with the oligarchy.
But it's not free speech absolutism.
But I feel like being a free speech absolutist
on the social network requires you to also have tools
for the individuals to control what they consume easier.
Like not censor, but just like control like,
oh, I'd like to see more cats and less politics.
And this isn't even remotely controversial.
This is just saying you want to give paying customers
for a product what they want.
Yeah, and not through the process of censorship,
but through a process of like-
It's individualized, right?
It's individualized, transparent censorship,
which is honestly what I want.
What is an ad blocker?
It's individualized, transparent censorship, right?
Yeah, but censorship is a strong word.
And people are very sensitive too.
I know, but I just use words to describe
what they functionally are.
And what is an ad blocker?
It's just censorship.
When I look at you right now, I'm looking at you
and I'm censoring everything else out
when my mind is focused on you.
You can use the word censorship that way,
but usually when people get very sensitive
about the censorship thing.
I think when anyone is allowed to say anything,
you should probably have tools that maximize the quality
of the experience for individuals.
So for me, what I really value, boy,
would be amazing to somehow figure out how to do that.
I love disagreement and debate.
And people who disagree with each other disagree with me,
especially in the space of ideas,
but the high quality ones.
So not derision, right?
Maslow's hierarchy of argument.
I think there's a real word for it.
Probably.
There's just a way of talking that's like snarky and so on
that somehow gets people on Twitter
and they get excited and so on.
You have like ad hominem refuting the central point.
I'd like seeing this as an actual pyramid.
Yeah, and it's like all of it,
all the wrong stuff is attractive to people.
I mean, we can just try in a classifier to absolutely say
what level of Maslow's hierarchy of argument are you at?
And if it's ad hominem, like, okay, cool.
I turned on the no ad hominem filter.
I wonder if there's a social network
that will allow you to have that kind of filter.
Yeah, so here's a problem with that.
It's not going to win in a free market.
What wins in a free market is all television today
is reality television because it's engaging, right?
Engaging is what wins in a free market, right?
So it becomes hard to keep these other more nuanced values.
Well, okay, so that's the experience of being on Twitter,
but then you got a chance to also,
together with other engineers and with Elon,
sort of brainstorm when you step into a code base
that's been around for a long time.
There's other social networks.
Facebook, this is old code bases.
And you step in and see, okay,
how do we make with a fresh mind progress on this code base?
Like, what did you learn about software engineering,
about programming from just experiencing that?
So my technical recommendation to Elon,
and I said this on the Twitter spaces afterward,
I said this many times during my brief internship,
was that you need refactors before features.
This code base was, and look, I've worked at Google,
I've worked at Facebook.
Facebook has the best code, then Google, then Twitter.
And you know what?
You can know this,
because look at the machine learning frameworks, right?
Facebook released PyTorch, Google released TensorFlow,
and Twitter released, hmm.
Okay, so you know, it is-
It's a proxy, but yeah,
the Google code base is quite interesting.
There's a lot of really good software engineers there,
but the code base is very large.
The code base was good in 2005, right?
It looks like 2005, I reckon.
There's so many products, so many teams, right?
It's very difficult to,
I feel like Twitter does less,
obviously much less than Google
in terms of the set of features, right?
So I can imagine the number of software engineers
that could recreate Twitter
is much smaller than to recreate Google.
Yeah, I still believe,
and the amount of hate I got for saying this,
that 50 people could build and maintain Twitter pretty-
What's the nature of the hate?
Comfortably.
That you don't know what you're talking about?
You know what it is, and it's the same,
this is my summary of like the hate I get on Hacker News.
It's like, when I say I'm going to do something,
they have to believe that it's impossible,
because if doing things was possible,
they'd have to do some soul searching and ask the question,
why didn't they do anything?
So when you say-
And I do think that's where the hate comes from.
When you say, well, there's a core truth to that, yeah.
So when you say I'm going to solve self-driving,
people go like, what are your credentials?
What the hell are you talking about?
This is an extremely difficult problem.
Of course, you're a noob
that doesn't understand the problem deeply.
I mean, that was the same nature of hate
that probably Elon got when he first talked
about autonomous driving.
But there's pros and cons to that,
because there is experts in this world.
No, but the mockers aren't experts.
The people who are mocking are not experts
with carefully reasoned arguments
about why you need 8,000 people to run a bird app.
They're, but the people are going to lose their jobs.
Well, that, but also there's the soft and genius
that probably criticized,
no, it's a lot more complicated than you realize,
but maybe it doesn't need to be so complicated.
You know, some people in the world
like to create complexity.
Some people in the world thrive
under complexity like lawyers, right?
Lawyers want the world to be more complex,
because you need more lawyers,
you need more legal hours, right?
I think that's another.
If there's two great evils in the world,
it's centralization and complexity.
Yeah, and the one of the sort of hidden side effects
of software engineering is like finding pleasure
and complexity.
I mean, I don't remember just taking
all the software engineering courses
and just doing programming and just coming up
in this object-oriented programming kind of idea.
You don't, like not often do people tell you,
do the simplest possible thing.
Like a professor, a teacher is not going to get in front,
like this is the simplest way to do it.
They'll say like, this is the right way
and the right way, at least for a long time,
especially I came up with like Java, right?
Like there's so much boilerplate,
so much like so many classes,
so many like designs and architectures and so on,
planning for features far into the future
and planning poorly and all this kind of stuff.
And then there's this like code base
that follows you along and puts pressure on you.
And nobody knows what like parts, different parts do,
which slows everything down as a kind of bureaucracy
that's instilled in the code as a result of that.
But then you feel like, oh, well,
I follow good software engineering practices.
It's an interesting trade-off,
because then you look at like the ghettoness of like Perl
in the old, like how quick you could just write
a couple of lines and just get stuff done.
That trade-off is interesting or bash or whatever,
these kind of ghetto things you can do on Linux.
One of my favorite things to look at today
is how much do you trust your tests, right?
We've put a ton of effort in comma
and I've put a ton of effort in tiny grad
into making sure if you change the code and the tests pass,
that you didn't break the code.
Now, this obviously is not always true,
but the closer that is to true,
the more you trust your tests,
the more you're like, oh, I got a pull request
and the tests pass, I feel okay to merge that,
the faster you can make progress.
So you're always programming your tests in mind,
developing tests with that in mind,
that if it passes, it should be good.
And Twitter had a...
Not that.
So...
It was impossible to make progress in the codebase.
What other stuff can you say about the codebase
that made it difficult?
What are some interesting sort of quirks,
broadly speaking, from that compared to just your experience
with comma and everywhere else?
The real thing that...
I spoke to a bunch of individual contributors at Twitter
and I just had a test.
I'm like, okay, so what's wrong with this place?
Why does this code look like this?
And they explained to me what Twitter's promotion system was.
The way that you got promoted at Twitter
was you wrote a library that a lot of people used, right?
So some guy wrote an NGINX replacement for Twitter.
Why does Twitter need an NGINX replacement?
What was wrong with NGINX?
Well, you see, you're not gonna get promoted
if you use NGINX.
But if you write a replacement
and lots of people start using it
as the Twitter front end for their product,
then you're gonna get promoted, right?
So interesting, because from an individual perspective,
how do you incentivize...
How do you create the kind of incentives
that will lead to a great codebase?
Okay, what's the answer to that?
So what I do at comma and at time,
at TinyCorp, is you have to explain it to me.
You have to explain to me what this code does, right?
And if I can sit there
and come up with a simpler way to do it,
you have to rewrite it.
You have to agree with me about the simpler way.
Obviously, we can have a conversation about this.
It's not dictatorial, but if you're like, wow,
wait, that actually is way simpler.
Like, the simplicity is important, right?
But that requires people that overlook the code
at the highest levels to be like, okay.
It requires technical leadership you trust.
Yeah, technical leadership.
So managers or whatever should have
to have technical savvy, deep technical savvy.
Managers should be better programmers
than the people who they manage.
Yeah, and that's not always obvious, trivial to create,
especially at large companies.
Managers get soft.
And this is just, I've instilled this culture at comma,
and comma has better programmers than me who work there.
But again, I'm like the old guy from Good Will Hunting.
It's like, look, man, I might not be as good as you,
but I can see the difference between me and you, right?
And like, this is what you need.
This is what you need at the top.
Or you don't necessarily need the manager
to be the absolute best, I shouldn't say that.
But like, they need to be able to recognize skill.
Yeah, and have good intuition,
intuition that's laden with wisdom from all the battles
of trying to reduce complexity in code bases.
You know, I took a political approach at comma, too,
that I think is pretty interesting.
I think Elon takes the same political approach.
You know, Google had no politics,
and what ended up happening is
the absolute worst kind of politics took over.
Comma has an extreme amount of politics,
and they're all mine, and no dissidents is tolerated.
So it's a dictatorship.
Yep, it's an absolute dictatorship, right?
Elon does the same thing.
Now, the thing about my dictatorship is here are my values.
Yeah, so it's transparent.
It's transparent.
It's a transparent dictatorship, right?
And you can choose to opt in or, you know,
you get free exit, right?
That's the beauty of companies.
If you don't like the dictatorship, you quit.
So you mentioned rewrite before or refactor before features.
If you were to refactor the Twitter code base,
what would that look like?
And maybe also comment on how difficult is it to refactor?
The main thing I would do is, first of all,
identify the pieces,
and then put tests in between the pieces, right?
So there's all these different,
Twitter has a microservice architecture,
all these different microservices,
and the thing that I was working on there,
look, like, you know,
George didn't know any JavaScript.
He asked how to fix search, blah, blah, blah, blah, blah.
Look, man, like, the thing is,
like, I'm just, you know,
I'm upset that the way that this whole thing was portrayed,
because it wasn't like,
it wasn't like taken by people, like, honestly,
it wasn't like by,
it was taken by people who started out
with a bad faith assumption.
Yeah.
And I mean, look, I can't like-
And you as a programmer,
just being transparent out there,
actually having like fun,
and like, this is what programming should be about.
I love that Elon gave me this opportunity.
Yeah.
Like, really, it does,
and like, you know, he came on my,
the day I quit, he came on my Twitter spaces afterward,
and we had a conversation.
Like, I just, I respect that so much.
Yeah, and it's also inspiring
to just engineers and programmers,
and just, it's cool.
It should be fun.
The people that were hating on it,
it's like, oh, man.
It was fun.
It was fun.
It was stressful,
but I felt like, you know,
it was at like a cool, like, point in history,
and like, I hope I was useful,
and I probably kind of wasn't,
but like, maybe I was-
Well, you also were one of the people
that kind of made a strong case to refactor.
Yeah.
And that's a really interesting thing to raise.
Like, maybe that is the right, you know,
the timing of that is really interesting.
If you look at just the development of autopilot,
you know, going from Mobileye to just,
like, more, if you look at the history
of semi-autonomous driving in Tesla,
is more and more, like, you could say refactoring,
or starting from scratch, redeveloping from scratch.
It's refactoring all the way down.
And like, and the question is like,
can you do that sooner?
Can you maintain product profitability?
And like, what's the right time to do it?
How do you do it?
You know, on any one day, it's like,
you don't want to pull off the band-aids.
Like, it's, like, everything works.
It's just like little fixed here and there,
but maybe starting from scratch.
This is the main philosophy of Tiny Grad.
You have never refactored enough.
Your code can get smaller.
Your code can get simpler.
Your ideas can be more elegant.
But would you consider, you know,
say you were, like, running Twitter development teams,
engineering teams.
Would you go as far as, like, different programming language?
Just go that far?
I mean, the first thing that I would do is build tests.
The first thing I would do is get a CI
to where people can trust to make changes.
Before I touched any code,
I would actually say, no one touches any code.
The first thing we do is we test this code base.
I mean, this is classic.
This is how you approach a legacy code base.
This is, like, what any,
how to approach a legacy code base book will tell you.
So, and then you hope that there's modules
that can live on for a while,
and then you add new ones,
maybe in a different language or design it.
Before we add new ones, we replace old ones.
Yeah, yeah, meaning, like,
replace old ones with something simpler.
We look at this, like, this thing that's 100,000 lines,
and we're like, well, okay,
maybe this didn't even make sense in 2010,
but now we can replace this with an open source thing.
Right?
Yeah.
And, you know, we look at this here.
Here's another 50,000 lines.
Well, actually, you know,
we can replace this with 300 lines of Go.
And you know what?
I trust that the Go actually replaces this thing
because all the tests still pass.
So step one is testing.
Yeah.
And then step two is, like,
the programming language is an afterthought, right?
You know, let a whole lot of people compete,
be like, okay, who wants to rewrite a module,
whatever language you want to write it in,
just the tests have to pass.
And if you figure out how to make the test pass
but break the site, that's,
we got to go back to step one.
Step one is get tests that you trust
in order to make changes in the code base.
I wonder how hard it is to,
because I'm with you on testing and everything.
Hey, you have from tests to, like, asserts to everything,
but code is just covered in this
because it should be very easy to make rapid changes
and know that it's not going to break everything.
And that's the way to do it.
But I wonder how difficult is it to integrate tests
into a code base that doesn't have many of them?
So I'll tell you what my plan was at Twitter.
It's actually similar to something we use at Comma.
So at Comma, we have this thing called Process Replay.
And we have a bunch of routes that'll be run through.
So Comma's a microservice architecture, too.
We have microservices in the driving.
Like, we have one for the cameras, one for the sensor,
one for the planner, one for the model.
And we have an API,
which the microservices talk to each other with.
We use this custom thing called Serial,
which uses ZMQ.
Twitter uses Thrift.
And then it uses this thing called Finagle,
which is a Scala RPC backend.
But this doesn't even really matter.
The Thrift and Finagle layer was a great place,
I thought, to write tests, right?
To start building something that looks like Process Replay.
So Twitter had some stuff that looked kind of like this,
but it wasn't offline.
It was only online.
So you could ship a modified version of it,
and then you could redirect some of the traffic
to your modified version and diff those two.
But it was all online.
There was no CI in the traditional sense.
I mean, there was some, but it was not full coverage.
So you can't run all of Twitter offline to test something.
Well, then this was another problem.
You can't run all of Twitter, right?
Period.
Any one person can't run Twitter.
Twitter runs in three data centers, and that's it.
There's no other place you can run Twitter,
which is like, George, you don't understand.
This is modern software development.
No, this is bullshit.
Like, why can't it run on my laptop?
What do you do?
Twitter can run it.
Yeah, okay, well, I'm not saying you're gonna download
the whole database to your laptop,
but I'm saying all the middleware and the front end
should run on my laptop, right?
That sounds really compelling.
Yeah.
But can that be achieved by a code base
that grows over the years?
I mean, the three data centers didn't have to be, right?
Because they're totally different designs.
The problem is more like,
why did the code base have to grow?
What new functionality has been added
to compensate for the lines of code that are there?
One of the ways to explain it is that
the incentive for software developers
to move up in the company is to add code,
to add, especially large.
And you know what?
The incentive for politicians to move up
in the political structure is to add laws.
Same problem.
Yeah.
Yeah, if the flip side is to simplify, simplify, simplify.
You know what?
This is something that I do differently
from Elon with Kama about self-driving cars.
You know, I hear the new version's gonna come out
and the new version is not gonna be better,
but at first, and it's gonna require a ton of refactors.
I say, okay, take as long as you need.
You convinced me this architecture's better?
Okay, we have to move to it.
Even if it's not gonna make the product better tomorrow,
the top priority is getting the architecture right.
So what do you think about sort of a thing
where the product is online?
So how, I guess, would you do a refactor?
If you ran engineering on Twitter,
would you just do a refactor?
How long would it take?
What would that mean for the running of the actual service?
You know, and I'm not the right person to run Twitter.
I'm just not.
And that's the problem.
Like, I don't really know.
I don't really know if that's, you know,
a common thing that I thought a lot while I was there
was whenever I thought something that was different
to what Elon thought,
I'd have to run something in the back of my head
reminding myself that Elon is the richest man in the world.
And in general, his ideas are better than mine.
Now, there's a few things I think I do understand
and know more about, but like in general,
I'm not qualified to run Twitter.
Not, I shouldn't say qualified,
but like, I don't think I'd be that good at it.
I don't think I'd be good at it.
I don't think I'd really be good at running
an engineering organization at scale.
I think I could lead a very good refactor of Twitter
and it would take like six months to a year
and the results to show at the end of it
would be feature development in general
takes 10x less time, 10x less man hours.
That's what I think I could actually do.
Do I think that it's the right decision
for the business above my pay grade?
Yeah, but a lot of these kinds of decisions
are above everybody's pay grade.
I don't want to be a manager.
I don't want to do that.
I just like, if you really forced me to,
yeah, it would make me maybe, make me upset
if I had to make those decisions.
I don't want to.
Yeah, but a refactor is so compelling.
If this is to become something much bigger
than what Twitter was, it feels like a refactor
has to be coming at some point.
George, you're a junior software engineer.
Every junior software engineer wants to come in
and refactor the whole code.
Okay, that's like your opinion, man.
Yeah, it doesn't, you know, sometimes they're right.
Well, whether they're right or not,
it's definitely not for that reason, right?
It's definitely not a question of engineering prowess.
It is a question of maybe what the priorities
are for the company.
And I did get more intelligent, like, feedback
from people I think in good faith, like, saying that.
From, actually from Elon.
And like, you know, from Elon, sort of like,
people were like, well, you know,
a stop the world refactor might be great for engineering,
but you don't have a business to run.
And hey, I love my pay grade.
What do you think about Elon as an engineering leader,
having to experience him in the most chaotic of spaces,
I would say?
My respect for him is unchanged.
And I did have to think a lot more deeply
about some of the decisions he's forced to make.
About the tensions within those,
the trade-offs within those decisions?
About like a whole, like, like, matrix coming at him.
I think that's Andrew Tate's word for it.
Sorry to borrow it.
Oh, so bigger than engineering, just everything.
Yeah, like, like, the war on the woke.
Yeah.
Like, it just, it's just, man, and like,
he doesn't have to do this, you know?
He doesn't have to.
He could go like, Parag and go chill
at the Four Seasons of Maui, you know?
But see, one person I respect and one person I don't.
So his heart is in the right place,
fighting in this case for this ideal
of the freedom of expression.
I wouldn't define the ideal so simply.
I think you can define the ideal
no more than just saying Elon's idea of a good world.
Freedom of expression is...
But to you, it's still,
the downside of that is the monarchy.
Yeah, I mean, monarchy has problems, right?
But I mean, would I trade right now
the current oligarchy which runs America for the monarchy?
Yeah, I would, sure.
For the Elon monarchy, yeah, you know why?
Because power would cost one cent a kilowatt hour,
10th of a cent a kilowatt hour.
What do you mean?
Right now, I pay about 20 cents a kilowatt hour
for electricity in San Diego.
That's like the same price you paid in 1980.
What the hell?
So you would see a lot of innovation with Elon.
Maybe it'd have some hyperloops, right?
And I'm willing to make that trade-off, right?
I'm willing to make...
And this is why, you know,
people think that like dictators take power
through some like, through some untoward mechanism.
Sometimes they do,
but usually it's because the people want them.
And the downsides of a dictatorship,
I feel like we've gotten to a point now
with the oligarchy where, yeah,
I would prefer the dictator.
What'd you think about Scala as a programming language?
I liked it more than I thought.
I did the tutorials.
Like, I was very new to it.
Like, it would take me six months
to be able to write like good Scala.
I mean, what did you learn
about learning a new programming language from that?
Oh, I love doing like new programming.
I did tutorials on doing them.
I did all this for Rust.
Some of it's upsetting JVM roots,
but it is a much nicer...
In fact, I almost don't know
why Kotlin took off and not Scala.
I think Scala has some beauty that Kotlin lacked.
Whereas Kotlin felt a lot more,
I mean, it was almost like,
I don't know if it actually was a response to Swift,
but that's kind of what it felt like.
Like Kotlin looks more like Swift
and Scala looks more like,
well, like a functional programming language.
It's more like like an OCaml or Haskell.
Let's actually just explore.
We touched it a little bit,
but just on the art,
the science and the art of programming.
For you personally,
how much of your programming is done with GPT currently?
None.
None.
I don't use it at all.
Because you prioritize simplicity so much.
Yeah, I find that a lot of it is noise.
I do use VS code,
and I do like some amount of autocomplete.
I do like like a very,
feels like rules-based autocomplete.
Like an autocomplete,
it's going to complete the variable name for me.
So I'm going to type it, I can just press tab.
All right, that's nice.
But I don't want an autocomplete.
You know what I hate?
When autocompletes, when I type the word for,
and it puts like two parentheses
and two semicolons and two braces,
I'm like, oh, man.
Well, I mean, with VS code and GPT with codex,
you can kind of brainstorm.
I find, I'm like probably the same as you,
but I like that it generates code
and you basically disagree with it
and write something simpler.
But to me, that somehow is like inspiring.
It makes me feel good.
It also gamifies the simplification process.
Because I'm like, oh yeah, you dumb AI system.
You think this is the way to do it.
I have a simpler thing here.
It just constantly reminds me of like bad stuff.
I mean, I tried the same thing with wrap, right?
I tried the same thing with wrap,
and actually I think I'm a much better programmer
and rapper, but like I even tried,
I was like, okay, can we get some inspiration
from these things for some rap lyrics?
And I just found that it would go back
to the most like cringey tropes and dumb rhyme schemes.
And I'm like, yeah, this is what the code looks like too.
I think you and I probably have different thresholds
for cringe code.
You probably hate cringe code.
So it's for you, I mean,
boilerplate is a part of code.
Some of it, yeah, and some of it is just like faster lookup.
Because I don't know about you,
but I don't remember everything.
I'm offloading so much of my memory
about different functions, library functions,
and all that kind of stuff.
This GPT just is very fast at standard stuff,
at like standard library stuff,
basic stuff that everybody uses.
Yeah, I think that,
I don't know, I mean, there's just so little of this
in Python, maybe if I was coding more in other languages,
I would consider it more,
but I feel like Python already does such a good job
of removing any boilerplate.
That's true.
It's the closest thing you can get to pseudocode, right?
Yeah, that's true, that's true.
And like, yeah, sure, if I like, yeah, I'm great GPT,
thanks for reminding me to free my variables.
Unfortunately, you didn't really recognize
the scope correctly and you can't free that one,
but like you put the freeze there and like, I get it.
Fiverr, whenever I've used Fiverr for certain things,
like design or whatever, it's always, you come back.
I think that's probably closer,
my experience with Fiverr is closer to your experience
with programming with GPT is like,
you're just frustrated and feel worse
about the whole process of design and art
and whatever I use Fiverr for.
Still, I just feel like later versions of GPT,
I'm using GPT as much as possible
to just learn the dynamics of it, like these early versions,
because it feels like in the future,
you'll be using it more and more.
And so like, I don't want to be, like for the same reason,
I gave away all my books and switched to Kindle.
Cause like, all right,
how long are we going to have paper books?
Like 30 years from now,
like I want to learn to be reading on Kindle,
even though I don't enjoy it as much
and you learn to enjoy it more.
In the same way, I switched from, let me just pause.
I switched from Emacs to VS Code.
Yeah, I switched from Vim to VS Code.
I think I, similar, but.
Yeah, it's tough.
And that, Vim to VS Code is even tougher.
Cause Emacs is like old, like more outdated.
Feels like it, the community is more outdated.
Vim is like pretty vibrant still, so.
I never used any of the plugins.
I still don't use any of the plugins.
That's what I looked at myself in the mirror.
I'm like, yeah, you wrote some stuff in Lisp.
Yeah.
No, but I never used any of the plugins in Vim either.
I had the most vanilla Vim.
I have a syntax eyeliner.
I didn't even have autocomplete.
Like these things, I feel like help you so marginally
that like, and now, okay,
now VS Codes autocomplete has gotten good enough
that like, okay, I don't have to set it up.
I can just go into any code base
and autocomplete's right 90% of the time.
Okay, cool. I'll take it.
So I don't think I'm going to have a problem at all
adapting to the tools once they're good.
But like the real thing that I want
is not something that like tab completes my code
and gives me ideas.
The real thing that I want
is a very intelligent pair programmer
that comes up with a little pop-up saying,
hey, you wrote a bug on line 14 and here's what it is.
Yeah.
Now I like that.
You know what does a good job of this?
Mypy.
I love Mypy.
Mypy, this fancy type checker for Python.
And actually I tried, like Microsoft released one too
and it was like 60% false positives.
Mypy is like 5% false positives.
95% of the time it recognizes,
I didn't really think about
that typing interaction correctly.
Thank you, Mypy.
So you like type hinting and you liked,
you liked pushing the language
towards being a typed language.
Oh yeah, absolutely.
I think optional typing is great.
I mean, look, I think that like,
it's like a meat in the middle, right?
Like Python has these optional type hinting
and like C++ has auto.
C++ allows you to take a step back.
Well, C++ would have you brutally type out
SGD string iterator, right?
Now I can just type auto, which is nice.
And then Python used to just have A.
What type is A?
It's an A.
Yeah.
A colon STR.
Oh, okay.
It's a string, cool.
Yeah.
I wish there were, I wish there was a way,
like a simple way in Python to like turn on a mode
which would enforce the types.
Yeah, like give a warning when there's no type,
something like this.
Well, no, to give a warning where,
like MyPy is a static type checker,
but I'm asking just for a runtime type checker.
Like there's like ways to like hack this in,
but I wish it was just like a flag, like Python 3-T.
Oh, I see, I see.
Enforce the types on runtime.
Yeah, I feel like that makes you a better programmer
that that's a kind of test, right?
That the type remains the same.
Well, that I know that I didn't like mess any types up,
but again, like MyPy is getting really good and I love it.
And I can't wait for some of these tools
to become AI powered.
Like I want AIs reading my code and giving me feedback.
I don't want AIs writing half-assed
autocomplete stuff for me.
I wonder if you can now take GPT and give it a code
that you wrote for function and say,
how can I make this simpler
and have it accomplish the same thing?
I think you'll get some good ideas on some code.
Maybe not code you write for timing grad type of code,
because that requires so much design thinking,
but like other kinds of code.
I don't know.
I downloaded the plugin maybe like two months ago.
I tried it again and found the same.
Look, I don't doubt that these models
are going to first become useful to me,
then be as good as me and then surpass me.
But from what I've seen today,
it's like someone occasionally taking over my keyboard
that I hired from Fiverr.
I'd rather not.
Ideas about how to debug the code
basically a better debugger is really interesting.
But it's not a better debugger.
Yes, I would love a better debugger.
Yeah, it's not yet.
Yeah, but it feels like it's not too far.
Yeah, one of my coworkers says he uses them
for print statements.
Like every time he has to like, just like when he needs,
the only thing that can really write is like, okay,
I just want to write the thing
to like print the state out right now.
Oh, that definitely is much faster as print statements.
Yeah, I see that myself using that a lot,
just like, because it figures out
the rest of the functions.
It's just like, okay, print everything.
Yeah, print everything, right.
If you want a pretty printer, maybe.
I'm like, yeah, you know what?
I think in two years,
I'm gonna start using these plugins a little bit.
And then in five years,
I'm gonna be heavily relying on some AI augmented flow.
And then in 10 years.
Do you think you'll ever get to 100%?
Where are the, like, what's the role of the human
that it converges to as a programmer?
Do you think it's all generated?
Our niche becomes,
oh, I think it's over for humans in general.
It's not just programming, it's everything.
So niche becomes, well.
Our niche becomes smaller, smaller, smaller.
In fact, I'll tell you what the last niche
of humanity is gonna be.
Yeah.
There's a great book and it's,
if I recommended Metamorphosis of Prime Intellect last time,
there is a sequel called A Casino Odyssey in Cyberspace.
And I don't want to give away the ending of this,
but it tells you what the last remaining human currency is.
And I agree with that.
We'll leave that as a cliffhanger.
So no more programmers left, huh?
That's where we're going.
Well, unless you want handmade code,
maybe they'll sell it on Etsy.
This is handwritten code.
Doesn't have that machine polish to it.
It has those slight imperfections
that would only be written by a person.
I wonder how far away we are from that.
I mean, there's some aspect to, you know, on Instagram,
your title is listed as prompt engineer.
Right?
Thank you for noticing.
I don't know if it's ironic or non,
or sarcastic or non.
What do you think of prompt engineering
as a scientific and engineering discipline,
or maybe, and maybe art form?
You know what?
I started Kama six years ago,
and I started the Tiny Corp a month ago.
So much has changed.
I'm now thinking, I'm now like,
I started going through similar Kama processes
to starting a company.
I'm like, okay, I'm going to get an office in San Diego.
I'm going to bring people here.
I don't think so.
I think I'm actually going to do remote, right?
George, you're going to do remote?
You hate remote.
Yeah, but I'm not going to do job interviews.
The only way you're going to get a job
is if you contribute to the GitHub, right?
And then like interacting through GitHub,
like GitHub being the real project management software
for your company.
And the thing pretty much just is a GitHub repo
is like showing me kind of what the future of, okay.
So a lot of times I'll go into Discord,
our tiny grad Discord,
and I'll throw out some random like,
hey, you know, can you change,
instead of having log and exp as LLOps,
change it to log two and exp two?
It's pretty small.
Change, you can just use like change your base formula.
That's the kind of task that I can see in AI
being able to do in a few years.
Like in a few years, I could see myself describing that.
And then within 30 seconds,
a pull request is up that does it.
And it passes my CI and I merge it, right?
So I really started thinking about like,
well, what is the future of like jobs?
How many AIs can I employ at my company?
As soon as we get the first tiny box up,
I'm going to stand up a 65 B llama in the Discord.
And it's like, yeah, here's the tiny box.
He's just like, he's chilling with us.
Basically, I mean, like you said, when Nisha is like,
most human jobs will eventually be replaced
with prompt engineering.
Well, prompt engineering kind of is this like,
as you like move up the stack, right?
Like, okay, there used to be humans
actually doing arithmetic by hand.
There used to be like big farms of people doing pluses
and stuff, right?
And then you have like spreadsheets, right?
And then, okay, the spreadsheet can do the plus for me.
And then you have like macros, right?
And then you have like things
that basically just are spreadsheets under the hood,
right, like accounting software.
As we move further up the abstraction,
well, what's at the top of the abstraction stack?
Well, prompt engineer.
Yeah.
Right, what is the last thing if you think about
like humans wanting to keep control?
Well, what am I really in the company
but a prompt engineer, right?
Isn't there a certain point where the AI will be better
at writing prompts?
Yeah, but you see the problem with the AI writing prompts,
a definition that I always liked of AI
was AI is the do what I mean machine, right?
AI is not the, like the computer is so pedantic.
It does what you say.
So, but you want the do what I mean machine, right?
You want the machine where you say,
get my grandmother out of the burning house.
It like reasonably takes your grandmother
and puts her on the ground,
not lifts her a thousand feet above the burning house
and lets her fall, right?
But you don't-
That's a Tchaikovsky example.
But it's not going to find the meaning.
I mean, to do what I mean, it has to figure stuff out.
Sure.
And the thing you'll maybe ask it to do
is run government for me.
Oh, and do what I mean very much comes down to
how aligned is that AI with you?
Of course, when you talk to an AI that's made
by a big company in the cloud,
the AI fundamentally is aligned to them, not to you.
And that's why you have to buy a tiny box.
So you make sure the AI stays aligned to you.
Every time that they start to pass, you know,
AI regulation or GPU regulation,
I'm going to see sales of tiny boxes spike.
It's going to be like guns, right?
Every time they talk about gun regulation, boom, gun sales.
So in the space of AI, you're an anarchist,
anarchism, espouser, believer.
I'm an informational anarchist, yes.
I'm an informational anarchist and a physical statist.
I do not think anarchy in the physical world is very good
because I exist in the physical world,
but I think we can construct this virtual world
where anarchy, it can't hurt you, right?
I love that Tyler, the creator tweet,
your cyber bullying isn't real, man.
Have you tried turning off the screen?
Close your eyes, like.
Yeah.
Well, how do you prevent the AI from basically
replacing all human prompt engineers?
Where there's, it's like a self,
like where nobody's the prompt engineer anymore.
So autonomy, greater and greater autonomy
until it's full autonomy.
Yeah.
And that's just where it's headed.
Because one person is going to say, run everything for me.
You see, I look at potential futures,
and as long as the AIs go on
to create a vibrant civilization
with diversity and complexity across the universe,
more power to them, I'll die.
If the AIs go on to actually like turn the world
into paperclips and then they die out themselves,
well, that's horrific and we don't want that to happen.
So this is what I mean about like robustness.
I trust robust machines.
The current AIs are so not robust.
Like this comes back to the idea
that we've never made a machine that can self replicate.
Right?
If the machines are truly robust
and there is one prompt engineer left in the world,
hope you're doing good, man.
Hope you believe in God.
Go by God and go forth and conquer the universe.
Well, you mentioned,
because I talked to Mark about faith and God,
and you said you were impressed by that.
What's your own belief in God
and how does that affect your work?
You know, I never really considered when I was younger,
I guess my parents were atheists,
so I was raised kind of atheist.
I never really considered how absolutely
like silly atheism is.
Because like I create worlds.
Every like game creator, like, how are you an atheist, bro?
You create worlds.
Who's up with Devin?
No one created our world, man.
That's different.
Haven't you heard about like the Big Bang and stuff?
Yeah, I mean, what's the Skyrim myth origin story in Skyrim?
I'm sure there's like some part of it in Skyrim,
but it's not like if you ask the creators,
like the Big Bang is in universe, right?
I'm sure they have some Big Bang notion in Skyrim, right?
But that obviously is not at all
how Skyrim was actually created.
It was created by a bunch of programmers in a room, right?
So like, you know, it just struck me one day
how just silly atheism is, right?
Like, of course we were created by God.
It's the most obvious thing.
Yeah, that's such a nice way to put it.
Like we're such powerful creators ourselves.
It's silly not to concede that there's creators
even more powerful than us.
Yeah.
And then like, I also just like, I like that notion.
That notion gives me a lot of,
I mean, I guess you can talk about maybe
what it gives a lot of religious people.
It's kind of like, it just gives me comfort.
It's like, you know what?
If we mess it all up and we die out, yeah.
Yeah, in the same way that a video game
kind of has comfort in it.
God will try again.
Or there's balance.
Like somebody figured out a balanced view of it.
Like how to, like, so it all makes sense in the end.
Like a video game is usually not gonna have
crazy, crazy stuff.
You know, people will come up with like a,
well yeah, but like man, who created God?
I'm like, that's God's problem, you know?
Like, I'm not gonna think, what are you asking me?
If God believes in God?
I'm just this NPC living in this game.
I mean, to be fair, like if God didn't believe in God,
he'd be as, you know, silly as the atheists here.
What do you think is the greatest
computer game of all time?
Do you have any time to play games anymore?
Have you played Diablo IV?
I have not played Diablo IV.
I will be doing that shortly, I have to.
All right.
There's so much history with one, two, and three.
You know what?
I'm gonna say World of Warcraft.
Ooh.
And it's not that the game is such a great game.
It's not.
It's that I remember in 2005 when it came out,
how it opened my mind to ideas.
It opened my mind to like,
like this whole world we've created, right?
There's almost been nothing like it since.
Like, you can look at MMOs today
and I think they all have lower user bases
than World of Warcraft.
Like, Eve Online's kind of cool.
But to think that like, everyone knows,
you know, people are always like,
to look at the Apple headset,
like, what do people want in this VR?
Everyone knows what they want.
Ready Player One.
Mm-hmm.
And like that.
So I'm gonna say World of Warcraft,
and I'm hoping that like games can get out
of this whole mobile gaming dopamine pump thing.
And like- Create worlds.
Create worlds, yeah.
That, and worlds that captivate
a very large fraction of the human population.
Yeah, and I think it'll come back, I believe.
But MMO, like really, really pull you in.
Games do a good job.
I mean, okay, other, like two other games
that I think are, you know,
very noteworthy for me are Skyrim and GTA V.
Skyrim, yeah.
That's probably number one for me.
GTA.
Yeah, what is it about GTA?
GTA is really, I mean, I guess GTA is real life.
I know there's prostitutes and guns and stuff.
They exist in real life, too.
Yes, I know.
But it's how I imagine your life to be, actually.
I wish it was that cool.
Yeah.
Yeah, I guess that's, you know,
because there's Sims, right?
Which is also a game I like,
but it's a gamified version of life.
But it also is-
I would love a combination of Sims and GTA.
So more freedom, more violence, more rawness,
but with also like ability to have a career
and family and this kind of stuff.
What I'm really excited about in games is like,
once we start getting intelligent AIs to interact with.
Oh yeah.
The NPCs in games have never been.
But conversationally, in every way.
In like, yeah, in like every way.
Like when you were actually building a world
and a world imbued with intelligence.
Oh yeah.
And it's just hard.
There's just like, you know, running World of Warcraft,
you're limited by your way.
You're running on a Pentium 4, you know?
How much intelligence can you run?
How many flops did you have?
But now when I'm running a game
on a hundred pay-to-flop machine, that's five people.
I'm trying to make this a thing.
20 pay-to-flops of compute is one person of compute.
I'm trying to make that a unit.
20 pay-to-flops?
Yeah.
Is one person.
One person.
One person flop.
It's like a horsepower.
Like what's a horsepower?
It's how powerful a horse is.
What's a person of compute?
Well, you know.
I got it.
That's interesting.
VR also adds, I mean, in terms of creating worlds.
You know what?
BoarderQuest 2.
I put it on and I can't believe
the first thing they show me
is a bunch of scrolling clouds and a Facebook login screen.
You had the ability to bring me into a world.
And what did you give me?
A pop-up, right?
And this is why you're not cool, Mark Zuckerberg.
But you could be cool.
Just make sure on the Quest 3,
you don't put me into clouds and a Facebook login screen.
Bring me to a world.
I just tried Quest 3.
It was awesome.
But hear that, guys?
I agree with that.
But you didn't have the clouds in the world.
It was just so much.
Because I mean, the beginning, what is this?
Todd Howard said this about
the design of the beginning of the games he creates.
It's like the beginning is so, so, so important.
I've recently played Zelda for the first time.
Zelda Breath of the Wild, the previous one.
And it's very quickly,
you come out of this,
within 10 seconds, you come out of a cave-type place
and it's like, this world opens up.
It's like, ah.
And it pulls you in.
You forget whatever troubles I was having, whatever.
I got to play that from the beginning.
I played it for like an hour at a friend's house.
Ah, no, the beginning, they got it.
They did it really well.
The expansiveness of that space.
The peacefulness of that place.
They got this, the music.
I mean, so much of that is creating that world
and pulling you right in.
I'm going to go buy a Switch.
I'm going to go today and buy a Switch.
Well, the new one came out.
I haven't played that yet,
but Diablo 4 or something.
I mean, there's sentimentality also,
but something about VR really is incredible.
But the new Quest 3 is mixed reality.
And I got a chance to try that.
So it's augmented reality.
And for video games, it's done really, really well.
Is it pass-through or cameras?
Cameras.
It's cameras, okay.
The Apple one, is that one pass-through or cameras?
I don't know.
I don't know how real it is.
I don't know anything.
Coming out in January.
Is it January or is it some point?
Some point, maybe not January.
Maybe that's my optimism, but Apple, I will buy it.
I don't care if it's expensive and does nothing,
I will buy it.
I will support this future endeavor.
You're the meme.
Oh, yes.
I support competition.
It seemed like Quest was like the only people doing it.
And this is great that they're like...
You know what?
And this is another place.
We'll give some more respect to Mark Zuckerberg.
The two companies that have endured through technology
are Apple and Microsoft, right?
And what do they make?
Computers and business services, right?
All the memes, social ads, they all come and go.
But you want to endure, build hardware.
Yeah, and that does a really interesting job.
Maybe I'm new with this,
but it's a $500 headset, Quest 3,
and just having creatures run around the space,
like our space right here, to me...
Okay, this is very like boomer statement,
but it added windows to the place.
I heard about the aquarium, yeah.
Yeah, aquarium, but in this case,
it was a zombie game, whatever, it doesn't matter.
But just like it modifies the space in a way where I can't...
It really feels like a window and you can look out.
It's pretty cool.
Like I was just...
It's like a zombie game, they're running at me, whatever.
But what I was enjoying is the fact
that there's like a window
and they're stepping on objects in this space.
That was a different kind of escape,
also because you can see the other humans.
So it's integrated with the other humans.
It's really, really interesting.
And that's why it's more important than ever
that the AI is running on those systems are aligned with you.
Oh yeah.
They're going to augment your entire world.
Oh yeah.
And those AIs have a...
I mean, you think about all the dark stuff,
like sexual stuff.
Like if those AIs threaten me,
that could be haunting.
Like if they threaten me in a non-video game way,
it's like, they don't know personal information about me.
And it's like, and then you lose track
of what's real, what's not.
Like what if stuff is like hacked?
There's two directions the AI girlfriend company can take.
There's like the high brow, something like her,
maybe something you kind of talk to.
And then there's the low brow version of it
where I want to set up a brothel in Times Square.
Yeah.
Yeah.
It's not cheating if it's a robot.
It's a VR experience.
Is there an in-between?
No, I don't want to do that one or that one.
Have you decided yet?
No, I'll figure it out.
We'll see what the technology goes.
I would love to hear your opinions
for George's third company,
what to do the brothel in Times Square
or the her experience.
What do you think company number four will be?
You think there'll be a company number four?
There's a lot to do in company number two.
I'm just like, I'm talking about company number three now.
None of that tech exists yet.
There's a lot to do in company number two.
Company number two is going to be the great struggle
of the next six years.
And of the next six years,
how centralized is compute going to be?
The less centralized compute is going to be,
the better of a chance we all have.
So you're a bearing, you're like a flag bearer
for open source distributed decentralization of compute.
We have to, we have to,
or they will just completely dominate us.
I showed a picture on stream of a man in a chicken farm.
You ever seen one of those like
factory farm chicken farms?
Why does he dominate all the chickens?
Why does he-
Smarter.
He's smarter, right?
Some people, some people on Twitch were like,
he's bigger than the chickens.
Yeah.
And now here's a man in a cow farm, right?
So it has nothing to do with their size
and everything to do with their intelligence.
And if one central organization has all the intelligence,
you'll be the chickens and they'll be the chicken man.
But if we all have the intelligence, we're all the chickens.
We're not all the man, we're all the chickens.
We're no man.
And there's no chicken man.
There's no chicken man.
We're just chickens in Miami.
He was having a good life, man.
And I'm sure he was.
I'm sure he was.
What have you learned from launching
and running Kama AI and TinyCorp?
So this starting a company from an idea and scaling it.
And by the way, I'm all in on TinyBox.
So I'm your, I guess it's pre-order only now.
I want to make sure it's good.
I want to make sure that like the thing that I deliver
is like not going to be like a Quest 2,
which you buy and use twice.
I mean, it's better than a Quest,
which you bought and used less than once statistically.
Well, if there's a beta program for a TinyBox I'm into.
Sounds good.
So I won't be the whiny,
I'll be the tech savvy user of the TinyBox
just to be in in the early days.
What have you learned from building these companies?
For the longest time at Kama, I asked why,
why did I start a company?
Why did I do this?
But you know, what else was I going to do?
So you like bringing ideas to life?
With Kama, it really started as an ego battle with Elon.
I wanted to beat him.
Like I saw a worthy adversary, you know?
Here's a worthy adversary
who I can beat at self-driving cars.
And like, I think we've kept pace
and I think he's kept ahead.
I think that's what's ended up happening there.
But I do think Kama is, I mean, Kama's profitable.
Like, and like when this drive GPT stuff starts working,
that's it, there's no more like bugs in the loss function.
Like right now we're using like a hand coded simulator.
There's no more bugs.
This is going to be it.
Like this is the run up to driving.
I hear a lot of really, a lot of props
for OpenPilot for Kama.
It's so, it's better than FSD and autopilot
in certain ways.
It has a lot more to do with which feel you like.
We lowered the price on the hardware at $1499.
You know how hard it is to ship reliable
consumer electronics that go on your windshield?
We're doing more than like most cell phone companies.
How'd you pull that off, by the way?
Shipping a product that goes in a car.
I know.
I have an SMT line.
I make all the boards in house in San Diego.
Quality control.
I care immensely about it.
You're basically a mom and pop shop with great testing.
Our head of OpenPilot is great at like, you know, okay.
I want all the commentaries to be identical.
Yeah.
And yeah, I mean, you know, it's look, it's $1499.
30 day money back guarantee.
It will blow your mind at what it can do.
Is it hard to scale?
You know what, there's kind of downsides to scaling it.
People are always like, why don't you advertise?
Our mission is to solve self-driving cars
while delivering shippable intermediaries.
Our mission has nothing to do with selling a million boxes.
It's tawdry.
Do you think it's possible that Common gets sold?
Only if I felt someone could accelerate that mission
and wanted to keep it open source.
And like, not just wanted to,
I don't believe what anyone says.
I believe incentives.
If a company wanted to buy Common with their incentives
or to keep it open source, but Common doesn't stop
at the cars, the cars are just the beginning.
The device is a human head.
The device has two eyes, two ears.
It breathes air, it has a mouth.
So you think this goes to embodied robotics?
We have, we sell Common bodies too.
You know, they're very rudimentary.
But one of the problems that we're running into
is that the Common 3 has about as much intelligence as a B.
If you want a human's worth of intelligence,
you're gonna need a tiny rack, not even a tiny box.
You're gonna need like a tiny rack, maybe even more.
How does that, how do you put legs on that?
You don't, and there's no way you can.
You connect to it wirelessly.
So you put your tiny box or your tiny rack in your house,
and then you get your Common body,
and your Common body runs the models on that.
It's close, right?
You don't have to go to some cloud,
which is, you know, 30 milliseconds away.
You go to a thing which is 0.1 milliseconds away.
So the AI girlfriend will have like a central hub
in the home.
I mean, eventually, if you fast forward 20, 30 years,
the mobile chips will get good enough to run these AIs.
But fundamentally, it's not even a question
of putting legs on a tiny box,
because how are you getting 1.5 kilowatts of power
on that thing, right?
So you need, they're very synergistic businesses.
I also want to build all of Common's training computers.
Common builds training computers right now.
We use commodity parts.
I think I can do it cheaper.
So we're going to build,
TinyCorp is going to not just sell tiny boxes.
TinyBox is the consumer version,
but I'll build training data centers too.
Have you talked to Andrej Karpathy,
or have you talked to Elon about TinyCorp?
He went to work at OpenAI.
What do you love about Andrej Karpathy?
To me, he's one of the truly special humans we got.
Oh man, like, you know,
his streams are just a level of quality so far beyond mine.
Like, I can't help myself.
Like, it's just, it's just, you know.
Yeah, he's good.
He wants to teach you.
Yeah.
I want to show you that I'm smarter than you.
Yeah, he has no, I mean, thank you for the sort of,
the raw, authentic honesty.
I mean, a lot of us have that.
I think Andrej is as legit as he gets in that.
He just wants to teach you.
I mean, there's a curiosity that just drives him.
And just like at his, at the stage where he is in life,
to be still like one of the best tinkerers in the world.
Yeah.
It's crazy.
Like to, what is it?
Micrograd?
Micrograd was, yeah, inspiration for Tinygrad.
Whew.
The whole, I mean, his CS 231n, this was the inspiration.
This is what I just took and ran with
and ended up writing this, so, you know.
But I mean, to me that-
Don't go work for Darth Vader, man.
I mean, the flip side to me is that
the fact that he's going there is a good sign for OpenAI.
Maybe.
I think, you know, I like Ilya Sidskeva a lot.
I like those, those guys are really good at what they do.
I know they are.
And that's kind of what's even like more.
And you know what?
It's not that OpenAI doesn't open-source
the weights of GPT-4.
It's that they go in front of Congress.
And that is what upsets me.
You know, we had two effective altruists,
Sams, go in front of Congress.
One's in jail.
I think you're drawing parallels on that.
One's in jail.
You're giving me a look.
You're giving me a look.
No, I think effectualtrism is a terribly evil ideology.
Oh yeah, that's interesting.
Why do you think that is?
Why do you think there's something about
a thing that sounds pretty good
that kind of gets us into trouble?
Because you get Sam Bagman freed.
Sam Bagman freed is the embodiment of effective altruism.
Utilitarianism is an abhorrent ideology.
Like, well yeah, we're going to kill those three people
to save a thousand, of course.
Yeah.
There's no underlying, like there's just, yeah.
Yeah, but to me that's a bit surprising.
But it's also, in retrospect, not that surprising.
But I haven't heard really clear kind of
like rigorous analysis why effective altruism is flawed.
Oh, well, I think charity is bad, right?
So what is charity but investment
that you don't expect to have a return on?
Right?
Yeah, but you can also think of charity
as like you would like to see,
so allocate resources in an optimal way
to make a better world.
And probably almost always
that involves starting a company.
Yeah.
Right, because-
More efficient.
Yeah, if you just take the money
and you spend it on malaria nets,
you know, okay, great.
You've made a hundred malaria nets.
But if you teach-
Yeah, you may know how to fish.
Right?
Yeah.
No, but the problem is teaching them how to fish,
it might be harder.
Starting a company might be harder
than allocating money that you already have.
I like the flip side of effective altruism,
effective accelerationism.
I think accelerationism is the only thing
that's ever lifted people out of poverty.
The fact that food is cheap,
not we're giving food away
because we are kind-hearted people.
No, food is cheap.
And that's the world you want to live in.
UBI, what a scary idea.
What a scary idea, all your power now?
Your money is power?
Your only source of power is granted to you
by the goodwill of the government?
What a scary idea.
So you even think long-term, even-
I'd rather die than need UBI to survive.
And I mean it.
What if survival is basically guaranteed?
What if our life becomes so good?
You can make survival guaranteed without UBI.
What you have to do is make housing and food dirt cheap.
Sure.
And that's the good world.
And actually, let's go into what we should really
be making dirt cheap, which is energy.
That energy that, you know, oh my God,
that's, if there's one, I'm pretty centrist politically.
If there's one political position I cannot stand,
it's deceleration.
It's people who believe we should use less energy.
Not people who believe global warming is a problem.
I agree with you.
Not people who believe that, you know,
that saving the environment is good.
I agree with you.
But people who think we should use less energy,
that energy usage is a moral bad.
No.
No, you are asking, you are diminishing humanity.
Yeah, energy is flourishing,
a creative flourishing of the human species.
How do we make more of it?
How do we make it clean?
And how do we make, just, just, just,
how do I pay, you know, 20 cents for a megawatt hour
instead of a kilowatt hour?
Part of me wishes that Elon went into nuclear fusion
versus Twitter, part of me.
Or somebody, somebody like Elon.
You know, we need to, I wish there were more,
more Elons in the world.
Yeah.
I think Elon sees it as like,
this is a political battle that needed to be fought.
And again, like, you know, I always ask the question
of whenever I disagree with him,
I remind myself that he's a billionaire and I'm not.
So, you know, maybe he's got something figured out
that I don't, or maybe he doesn't.
To have some humility, but at the same time,
me as a person who happens to know him,
I find myself in that same position.
Sometimes even billionaires need friends
who disagree and help them grow.
And that's a difficult, that's a difficult reality.
And it must be so hard, it must be so hard to meet people
once you get to that point where.
Fame, power, money, everybody's sucking up to you.
See, I love not having shit.
Like, I don't have shit, man.
You know, like, trust me, there's nothing I can give you.
There's nothing worth taking from me, you know?
Yeah, it takes a really special human being
when you have power, when you have fame,
when you have money, to still think from first principles.
Not like all the adoration you get towards you,
all the admiration, all the people saying yes, yes, yes.
And all the hate, too.
And the hate.
And that's worse.
So the hate makes you want to go to the yes people
because the hate exhausts you.
And the kind of hate that Elon's gotten from the left
is pretty intense.
And so that, of course, drives him right.
And loses balance and.
And it keeps this absolutely fake, like,
psy-op political divide alive.
So that the 1% can keep power, like.
Yeah.
I wish we'd be less divided.
Because it is giving power.
It gives power.
To the ultra-powerful.
The rich get richer.
You have love in your life.
Has love made you a better or a worse programmer?
Do you keep productivity metrics?
No, no.
No, I'm not that, I'm not that methodical.
I think that there comes to a point where
if it's no longer visceral, I just can't enjoy it.
Like, I so viscerally love programming.
The minute I started, like.
So that's one of the big loves of your life is programming.
I mean, just my computer in general.
I mean, you know, I tell my girlfriend,
my first love is my computer, of course.
Like, you know, I sleep with my computer.
It's there for a lot of my sexual experiences.
Like, come on.
So is everyone's, right?
Like, you know, you gotta be real about that.
And like.
Not just like the IDE for programming,
just the entirety of the computational machine.
The fact that, yeah, I mean, it's, you know,
I wish it was, and someday it'll be smarter.
And so now, you know, maybe I'm weird for this,
but I don't discriminate, man.
I'm not gonna discriminate Biostack Life
and Silicon Stack Life, like.
So the moment the computer starts to say, like, I miss you,
I started to have some of the basics of human intimacy,
it's over for you.
The moment VS Code says, hey, George.
No, you see, no, no, no, but VS Code is, no,
they're just doing that.
Microsoft's doing that to try to get me hooked on it.
I'll see through it.
I'll see through it.
It's gold digger, man.
It's gold digger.
Well, this just gets more interesting, right?
If it's open source and yeah, it becomes.
Though Microsoft's done a pretty good job on that.
Oh, absolutely.
No, no, no, look, I think Microsoft, again,
I wouldn't count on it to be true forever,
but I think right now Microsoft is doing the best work
in the programming world.
Like between, yeah, GitHub, GitHub Actions, VS Code,
the improvements to Python, where's Microsoft?
Like this is-
Who would have thought Microsoft and Mark Zuckerberg
are spearheading the open source movement?
Right, right?
How things change.
Oh, it's beautiful.
By the way, that's who I'd bet on
to replace Google, by the way.
Who?
Microsoft.
Microsoft.
I think Satya Nadella said straight up, I'm coming for it.
Interesting, so your bet, who wins AGI?
Oh, I don't know about AGI.
I think we're a long way away from that,
but I would not be surprised if in the next five years,
Bing overtakes Google as a search engine.
Interesting.
Wouldn't surprise me.
Interesting.
I hope some startup does.
It might be some startup too.
I would equally bet on some startup.
Yeah, I'm like 50-50, but maybe that's naive.
I believe in the power of these language models.
Satya's alive, Microsoft's alive.
Yeah, it's great, it's great.
I like all the innovation in these companies.
They're not being stale.
And to the degree they're being stale, they're losing.
So there's a huge incentive to do a lot of exciting work
and open source work, which is incredible.
Only way to win?
You're older, you're wiser.
What's the meaning of life, George Hotz?
To win.
It's still to win.
Of course.
Always.
Of course.
What's winning look like for you?
I don't know.
I haven't figured out what the game is yet,
but when I do, I want to win.
So it's bigger than solving self-driving?
It's bigger than democratizing, decentralizing compute?
I think the game is to stand out eye with God.
I wonder what that means for you.
Like at the end of your life, what that will look like.
I mean, this is what like, I don't know,
this is some, there's probably some ego trip of mine,
you know, like, you want to stand eye to eye with God.
You're just blasphemous, man.
Okay.
I don't know.
I don't know.
I don't know if it would upset God.
I think he like wants that.
I mean, I certainly want that for my creations.
I want my creations to stand eye to eye with me.
So why wouldn't God want me to stand eye to eye with him?
That's the best I can do golden rule.
I'm just imagining the creator of a video game
having to look and stand eye to eye
with one of the characters.
I only watched season one of Westworld,
but yeah, we got to find the maze and solve it.
Yeah, I wonder what that looks like.
It feels like a really special time in human history
where that's actually possible.
Like there's something about AI that's like,
we're playing with something weird here.
Something really weird.
I wrote a blog post.
I reread Genesis and just looked like.
They give you some clues at the end of Genesis
for finding the Garden of Eden.
And I'm interested.
I'm interested.
Well, I hope you find just that, George.
You're one of my favorite people.
Thank you for doing everything you're doing.
And in this case, for fighting for open source
or for decentralization of AI,
it's a fight worth fighting, fight worth winning hashtag.
I love you, brother.
These conversations are always great.
Hope to talk to you many more times.
Good luck with TinyCorp.
Thank you.
Great to be here.
Thanks for listening to this conversation with George Hotz.
To support this podcast,
please check out our sponsors in the description.
And now let me leave you with some words
from Albert Einstein.
Everything should be made as simple as possible,
but not simpler.
Thank you for listening and hope to see you next time.
Thank you.