All right, everybody. Welcome back to

the number one podcast in the world.

It's the All-in podcast episode 274.

Sacks is out today, but we're very lucky

to have Gavin Baker from Atrides

Management joining us. The spicy takes

must flow.

Welcome back to the program, bestie

Gavin. Thanks for having me. Always love

it. It's been a huge week in tech. We

can start with the SpaceX and OpenAI

IPOs. We've got Andrej Karpathy joining

Anthropic, Nvidia crushing it. So many

different to go, but I think we'll start

with Andrej Karpathy joining Anthropic.

Karpathy is only 39 years old. He's

already a legend in the tech industry.

If you don't know him, I believe he's

also coming to Liquidity, Chamath. He's

going to keynote on Monday morning. Oh,

fantastic.

>> I did not know. Tuesday, Tuesday,

Tuesday. Day two, I think. He's

keynoting. Okay.

As is Gavin. Gavin will be there.

Founding member of

>> Gavin anchoring day two, as well.

>> Excellent. Yeah, and this is Gavin's

second appearance. Yeah.

>> I look at those two bookmarks, Andrej

Karpathy and Gavin Baker. Yeah, you

know.

Liquidity pulls in the stars.

Obviously, Andrej was a founding member

of OpenAI. He led the self-driving team.

Also, hold on. Gavin is going to help us

judge the best ideas section, as well.

>> Excellent. I don't know if you know

that, Gavin, but you're a judge. You're

going to be a judge. I'm a pretty thing,

man. I'm easy. Yes. Karpathy also coined

the term vibe coding. He recently built

Auto Research. I think we talked about

that here a bit. That's an open-source

training tool. It helps AI models

improve themselves by running 5-minute

experiments. That got over 82,000 stars

on GitHub. He did that like as a weekend

experiment, and all these civilians

started building their own recursive

LLMs. Really inspiring.

And the Andrej Karpathy skills is a tool

based on his set of principles for

Claude code, and somebody just released

that. And so, it's just pretty crazy

when you think about it. He's going to

be in charge of a new pre-training team

at Anthropic. The focus, obviously,

being recursive self-improvement. In

other words,

they're going to have Claude improve

itself and they've already talked a

little bit about AI improving AI over at

Anthropic. Chamath, what's your take on

this? Is

this super important in 2026? Obviously,

Karpathy is super well respected. He's

obviously, you know, one of the true

talents in the space, but hey, we're in

a we're in a different inning than we

were say 10 years ago when he was at

Tesla or 5 years ago when he co-founded

Open AI. You know what's interesting? If

you go back to like Google,

the culture of Google which they got

right was

the singular technical talents there.

They were singled out and they were

called Google fellows. I don't know if

you guys remember this like Amit

Singhal,

Sridhar Ramaswamy, Jeff Dean.

These guys are stars. And what's

interesting is if you track what folks,

particularly Jeff Dean I guess now

because the other two aren't there

anymore, but

what they did inside of Google, it's

like wave upon wave, they were at the

foot of those waves. What's interesting

about Andre, he's been at the wave upon

wave of AI. He was probably the first

person that really commercialized the

Richard Sutton bitter lesson essay

when he was leading FSD at Tesla,

which was really about the brute force

computation. And I remember him telling

me the story. I don't know if he said

this publicly or not, but where he spent

a portion of his time, I want to say a

quarter of his time labeling data. Could

you imagine like 2016, 17 like hand

labeling video data from Teslas?

So he did that, then he's co-founder of

Open AI. He's a star.

And he's an exceptional human being and

he's super curious. And

then what he's done as a kind of a free

agent

is also quite impressive. So I think

that this is a really important deal. I

think he's one of these

really curious people that can be sent

off and they'll just go and

invent new things. And I think this idea

of recursive self-learning puts these

models on

a combination of overdrive and

autopilot. And so if you put those two

things together, I think that you start

to

you can potentially live out this idea

that there's an order of magnitude

improvement on a yearly basis. So like

this new form of Moore's law.

Well so then the model quality just goes

absolutely parabolicly just like this,

straight up. I think that

>> of compute at the problem and these

things learn really quick.

I think is the high order bit there.

Gavin, what do you what's your take on

Anthropic's recent success and their

massive hiring binge? The success is

extraordinary. It's undeniable. I think

the fact that they are now they were

even positive per the Wall Street

Journal in the most recent quarter

is a really important fact for kind of

the whole AI narrative because now

there's

you know, you could talk about circular

funding, you could talk about ROI and we

could go look at the ROIC of the

hyperscalers.

But if OpenAI and Anthropic are at call

it a hundred billion dollars of ARR now

with eighty percentish gross margins on

inference, like the returns are there

and then if we add in and they're

growing really fast, if we add in

Gemini, we add in Cursor, we add in xAI,

we add in open source,

you know, it's it's not hard to see two

hundred, three hundred, four hundred

billion dollars of ARR at the end of

this year at high [clears throat] mark.

>> Across all of the Across all of the

>> language models. And you're talking

specifically about the private language

model companies, maybe not Google which

is obviously public. You're including

Google. Okay.

>> I was excluding, you know, a lot of the

returns to this GPU spend have come from

you know, better recommender systems at

Facebook and Google,

Amazon, better ad targeting, better ad

measurement. Sure.

So, excluding that and just narrowing it

to LLMs, which I think tokens is the

possible definition,

and it seems like there's going to be a

really strong ROI this year, even

excluding what are still some of the

most economically important and

profitable use cases for GPUs and AI

infrastructure.

I do think what Karpathy is working on,

recursive

self-improvement, is really important

and unlocking that and continual

learning,

you know, maybe the two final frontiers

for for AI.

And just

the idea of recursive self-improvement

that the model,

while it is training, you know, during a

forward pass,

has input into its training, or another

model has input into the training,

I think that could be really powerful

and I think

Chamath's statistics of

of, you know, 10Xing every year,

you know, might seem conservative if

that comes to pass. And then, of course,

continual learning is the holy grail,

where the model learns from experiences

the way humans do. Yeah. And that's

something we haven't unlocked yet.

And those those those two combined, I

think would um

they might pull the future forward in a

very real way. Yeah, and we have right

now Anthropic has a decent lead on

everybody else, whether it's 3 months or

6 months. Obviously, they're probably

6-12 months ahead of open source. Maybe

they're 3-6-9 months ahead of their

contemporaries, but they have a lead.

You put Karpathy in there, Friedberg,

now you have Karpathy, he does

recursive,

and at some point, and it may have even

occurred at Anthropic, the AI is going

to be improving

the language model more

than

the humans in the loop are doing it.

Obviously, they're orchestrating it,

Friedberg, but at what point do we think

this, let's call it, super recursiveness

occurs? When will we cross the recursive

valley

and AI is doing more to build a language

model than humans are?

I'm not sure when this idea that you

feed the whole model into a context

window to train itself and build a new

model is going to happen, but I think

there's probably a lot of different

architectural paths that could be walked

here.

One of which is this idea that you could

make much smaller models and then create

networks of smaller models that work

together where you ultimately have

less energy or less cost per token

produced out of a

aggregation of models than you did with

one single large model. I've said this

probably three or four times now.

There's a lot of work and a lot of

opportunity ahead

in kind of re-architecting models and

re-architecting how models work together

to solve problems. My guess is a lot of

leadership that that he can bring

to exploring those paths. And all it

takes is a minor breakthrough and your

cost per token drops in half. That's a

tremendous efficiency gain

that is seems very much on the horizon

because some of the early papers, I

think I shared one from MIT a few weeks

ago, indicate that there's a lot of room

to run here in terms of re-architecting

models and deployment of models. These

very small models,

uh, small language models and then

verticalized ones are the future. We've

got a company Abacus that's doing it for

corporations. Crushing it. Everybody's

got an interest in doing this. And I

don't know if you saw the news this

week, uh, Chamath, it happened about 2

weeks ago very quietly. Chrome included

Gemini, or Google included in their

Chrome browser, the Gemini Nano model

without telling anybody. 4 GB on your

computer. And that's the one that does

like proof reading, spelling, auto

complete, all that. So, now we have

Google

covertly installing this on everybody's

operating system.

>> on. Hold on. Covert is a strong word, so

let's not use that word. Without telling

people, without giving people a

heads-up. Let's say it in a way that we

can both agree.

We're in the phase now where

I think breathlessly talking about every

model improvement is a waste of time.

There's no ROI in it.

We are on a path of accelerated

learning, and we're going to start to

see end user achievements that were

heretofore impossible. That should be

the focus. So, for example,

we were able to solve, I'm just

collectively saying we, in this case it

was specifically

OpenAI.

By the use of a human, and this is

important,

you know, a math problem that stood

outstanding, not been solved for decades

and decades.

I can tell you in a different example,

there are drug candidates that

are about to enter clinical trials and

INDs that were sitting on the shelf and

people didn't think were very viable at

all.

So, we're at the phase now where these

things are front and center, they're

useful to people, they're increasingly

valuable.

I think what we should do now is focus

on these end user

use cases

because the way that you say it, in my

opinion, is part of the problem because

it starts to create this boogeyman us

versus them thing, and I'm not saying

you're doing it on purpose, but I'm

saying this is exactly why I think

so many people are becoming sort of like

it's a four-letter word now when you

mention AI because it's presented as

this thing, and I think we have to

present the other side of it, at least

so that people have the data. So, I

don't think Google's in the business of

doing sh- shady or shady things. I don't

They're not that company. There are

other companies that would.

Meta.

>> [laughter]

>> You're referring to your alma mater?

>> I'm not going to say which ones, okay?

But Google is not that company. So, I I

think that the reason they did it was

probably because there's user utility.

And my point is we should focus on the

user utility because I think that's the

story we're telling from now on because

I think we, collectively, the four of

us,

can responsibly tell both sides of the

story in a well-balanced way because I

think nobody wins if we become Luddites

and go back in time. Yeah.

>> And I think that if we don't if we're

not careful with our words, that's what

will happen. Yeah. Um and by the way,

obviously not a Luddite, but this is

what

you know, has been reported by a lot of

folks that people were

surprised, shocked when they saw the

size of the model being done in the

background and it has triggered some

uh people looking at it around privacy

and I do agree that Google is not a bad

actor in the space. So, probably a speed

hour more than anything, I would say.

May I just add two things? Um

there's attorney maxing and then there's

attorney maxed.

And Google is probably

>> [laughter]

>> attorney maxed. Yes.

>> Yeah. It happened for a long time. And

the second second thing I would say is I

do think it's incumbent on all of us as

Americans who are involved in the

technology industry in one way or

another

to be advocates for a the positive,

optimistic possibilities

that AI introduces to to everyone in

this world

because it it is starting to feel or

seem

like there may be a CCP-funded

campaign against AI and data centers in

America.

And that's very logical for China, but

it is not good for America.

And so, I just I think it's

it we all have responsibility, is what I

would say. Yeah. Who do you think's

doing

a poor job at that and responsible for

this? Is it Dario with his constant hey,

everybody's going to lose their job?

Who's responsible for this? Is it the

CEOs blaming AI for their layoffs?

What's your take on this, Gavin? Look at

Hold on a second. Everybody is

trading their own book.

It makes enormous sense for Dario to try

to create the boundary conditions for a

regulatory moat because he will be

inside of the tent pissing out.

He's big enough now.

And if you notice that

a lot of the breathlessness has ramped

up

and Jason, we've talked about this. You

can annotate successive rounds of

fundraising and successive scale with

the volume.

So, I think that it's a reasonable

business strategy and I think that he's

quite clever and I think that look, if

you actually and I and I do this, if you

actually just have an ash bot, an ash

agent inside of Quod and you ask it what

it would do, it would come up with this

strategy. And meanwhile, there are other

versions of other counter strategies and

counter exploitative strategies. The

point is that each CEO has a clear

incentive. They're operating at such a

level of scale

that they're they're just reading their

own book. So, it's it's up to us to take

a step back and actually see the forest

from the trees. I think Nick, can you

find this? There was a clip of Sham

Sankar, friend of the pod, fabulous guy,

the CTO of Palantir and he was I think

he was on Fox News

and he said, "Stop breathlessly asking

these model makers what they think.

Go to the end user and ask the person in

the factory that's using the model and

ask him what he or she thinks. Ask what

the doctor thinks. Ask what the

scientist thinks and start to tell those

stories. That's what we should be

talking about." Yeah, and Gavin, you

were

I was sort of asking you your opinion on

what's what's who's causing this and

then what's the solution? Like do you do

you have folks you think in the industry

who are representing it particularly

well we can point out, "Hey, Elon has

said we're going to move to a world of

incredible abundance and working will be

optional." I think that's on the margin

a little scary for people to hear

because they hear no job.

But, he does say, "Hey, universal basic

income is probably going to have to come

into, you know, place." And he said that

multiple times. You have Chamath,

according to Chamath, talking his own

book, scaring the bejesus out of people

in order to get regulatory capture.

What do you think is going on here? And

how can we do better as an industry? I

think Chamath outlined like a very

viable and positive path forward. We're

just, you know, real people who are not,

you know, at the tip of the spear.

These are the positive impacts AI's had

on my life. I was at a

I was at I was at an event maybe 10 days

ago.

And someone who runs a hedge fund, his

daughter was born with a very rare

genetic mutation

that effectively would have

normally condemned her to a life devoid

of joy, meaning everything.

The neurons in her brain were not

firing. So, she wouldn't

you know, who knows what her life

expectancy would have been or what the

quality of her life would would have

been. And it's it's a tragic disease.

He said he didn't accept that as an

answer. He found He did an enormous

amount of research with LLMs and found

an existing safe drug on the market that

they thought would have a meaningful

impact on his daughter's condition.

And it did.

It took I think the percentage of times

the neurons were firing was 30 or 40%.

And it took it up to 80 or 90%. And that

means that she can live a normal life.

She may not be as smart as she would

have been, but she can live a normal

life.

And he's now figured out how to use AI,

how to to further tailor that drug. And

you know, there've been all sorts of

advances in

in protein design, etc., etc.

And he's reasonably confident he's going

to have a drug in months that is a

complete cure.

And that's just one person

one dad who was unwilling to accept

defeat for his daughter

and who changed her life and the life of

everyone else with that disease. And we

tell those stories. So, I think Elon's

doing a good job. A future where work is

optional, I think that sounds great to

some people

you know, scary to others. You know,

four-day workweek, you know, I think

it's it's probably something that sounds

sounds good to a lot of people. I think

Jensen is doing a good job of being an

effective advocate. And I do think

anyone who's trying to drive reg-

I just we need to stay focused on the

positives. That's what I'd say.

>> Yeah.

Freeburg,

what's your take here on the AI

PR crisis, if we'll call it that. Uh we

had three different

commencement speeches that were booed.

Eric Schmidt being one of them, two

other ones by maybe less notable folks.

When you hear young people booing AI

vociferously, why are they doing that,

Freeburg? And what's your take on the

overall PR problem and how to turn it

around?

Uh that's a

there's a long answer to that question.

Um

It relates in some ways to your concerns

about socialism and polarization.

>> Yeah. What's the long answer? I mean,

that's like

like why do people hate technology?

The greatest technological Why do they

hate this technology? They love their

phones. They love the internet. This

technology they hate.

Mhm.

I think that there's like an underlying

view that technology creates leverage

for a small group of people

which creates power imbalances and

nothing represents that more than AI.

That a small number of people that

control and profit from and benefit from

AI

are going to end up getting outsized

returns

relative to the broader population. That

the time to diffusion of the technology

cuz it's ultimately all technologies

like commoditized and diffuse.

But the time to diffusion here is such

that it's going to be like extremely

asymmetric for society. And I think that

there is something fundamental about

that.

It's like, you know, nuclear bombs I

think really created this this moment in

people's minds

in the mid-20th century that by the back

half of the 20th century gave everyone a

high degree of skepticism about

technology and science generally.

That those who have the knowledge and

those who engineer solutions with the

knowledge can create outsized advantages

for themselves and it puts the rest of

us at risk, the rest of the world, the

rest of the population at risk.

And because those questions about when

does this benefit me, how does it

benefit me can't be answered today

the economic benefit that's accruing to

the few today becomes the narrative, it

becomes the story and it becomes this

like power system

that a few people take from the many.

And so there's something deeply

disturbing for the average person about

that. They don't understand how it

works, why it works, what it'll do for

them, when it will do it, and all that

they're being told is that some people

are making trillions of dollars.

So, I think that it's pretty obvious why

this has got such a backlash. Secondly,

I think that there's a deep amount of

external energy that's fueling this

anti-technology sentiment in the United

States and has been for decades. I think

to Gavin's point, I don't think it's

just China with NGOs today. I think that

there is a long history

of

state actors intervening in media

activities in foreign nations to try and

create the sentiment

and fuel a sentiment that reduces

progress in that competitive state.

I think this goes all the way back to

KGB design

during the Cold War and it's been

refined and honed and improved over

time. This is not just some conspiracy

theory. There are plenty of great books

about this. The techniques of what's

going on specifically today, I don't

know enough. I don't have any great

details on that. But I don't think that

there's no foreign interest in seeing

technology advancement slow

in competitive nations. The United

States probably does similar things to

other nations and I think that that's

probably a key part of this.

And then I think this this like third

piece is like when

the Copernican revolution happened, it

was a mind you know, like

heliocentricity was a totally new way of

thinking for humans and it was uh deeply

disruptive to the church.

And it was deeply disruptive to the

power centers, which were

the centers that could tell people Earth

is at the center of the universe, we're

in control, we're the direct channel to

God.

And the idea that the sun is at the

center of the solar system and we spin

around it and we're a tiny speck in the

universe was very hard for people to

grasp. There's something about AI that's

very like not human-centric and it kind

of shifts

and with the ego of the human. It

it's it's almost anti-humanist.

And I think that that's like a deep

psychological current a lot of people

and their disdain for this technology it

fuels it. It's not the cause, but I

think it fuels it. So I think there's a

lot of complicated aspects to this, J

Cal. You know, I don't think there's

like a simple put put Cham on on a

podcast and he'll solve the the problems

of AI right now. I think that there's a

real set of shifts happening and there's

a real set of global competition

underway

where, you know, various state actors

and interests are competing with each

other.

Yeah, Chamath, do you think that we

should slow down?

I don't think you can.

No, no, no. Do you think we should slow

down? No, I I think I was just talking

to some people on a Zoom right before

this, but I think after the Manhattan

Project, the research labs were stood up

to maintain our scientists that worked

on the the Manhattan Project from uh

effectively leaching back or leaking

back to

Russia and Germany and and and other

places that that were adversaries to the

United States.

And they all were against the nuclear

bomb. They worked on it because it was

necessary for the United States

security, but then when Russia got a

hold of the secrets, they were leaked

because people were worried that if the

US had all the power,

there would be no counter-balance to the

power.

And so the the nuclear secrets were

leaked to Russia for that purpose. Then

when Russia had the nuclear secrets and

they began developing hydrogen

fusion bombs, and it it was clear that

they were going to race ahead, the

United States raced ahead with

developing nuclear bombs as a

counter-balance to Russia. When the

proliferation began, there was no

stopping it. It began and you had to

have this balance in the world,

otherwise you have effectively an

asymmetric power that can do whatever it

wants globally.

I think there's that moment in the world

right now where

if the United States does not

advance its AI technology, the

availability of it, TBD, industry,

taxation, all these all these things

that we're talking about doing, there

will be someone else that will.

And if someone else does, we can go

through what would happen. There's a

There's a complicated game theory on

this, but what would happen if China had

sufficiently advanced models and

sufficiently advanced scaled deployment

of those models relative to the United

States, as you do that analysis, you

realize, wait a second, that's probably

not a healthy place for the world to be.

It's also probably not a healthy place

for the United States to be the only one

with AI.

And so I I think what we end up seeing

is if we do try and slow down AI,

we kind of lose this moment of balance

that's necessary when you have a

technology proliferation like we saw

with the arms race after World War II

that, you know, we're going to see again

here. Chamath, you

I think bring up a good point. You know,

should we slow it down or could we slow

it down? There actually have been some

discussions about ways to do this. One

of them would be, hey, with

self-driving, people are scared that all

these cab drivers are going to lose

their jobs, Uber drivers, cab drivers,

bus drivers, truck drivers. This is, you

know, over 10 million people in the

United States driving things for a

living.

Would you be in favor of some of the

announcements that

that will be

a paced rollout, it won't happen all at

once. In other words, those people will

be given some amount of job security to

stay behind the wheel with it. Another

example that's been given is if you put

Optimus into Amazon factories or the

Figure robot just did like a week of

just sorting packages. I'm sure

everybody saw that video, we'll insert

it here.

That Figure robot sorting these, hey, if

Amazon deploys those, there'll be a tax

on those per hour and we'll tax humanoid

robots in some ways and then use that

for, say, retraining people. Those are

two very specific conditions and

approaches that people have been

promoting. Do either of those resonate

with you in any way?

I think it's

interesting that in all of those

discussions

I've yet to see an actual survey of only

the truck drivers and only the package

sorters.

>> [clears throat]

>> The question that I would have is do the

people that do these jobs want these

jobs?

And if they do, then there's a

reasonable claim to make to keep those

jobs the way that they are. If you're

saying this is the job that I do, I love

it, I'm able to provide for my family,

great. That's a very different argument

than, well, you know what, Amazon has 35

or 40% churn inside of their warehouses

and we should probably ask the question,

why is that? Because if it was such a

great job, I suspect the churn would be

3% or 4%. So, what exactly is it that we

want to protect? And have you asked

them?

And I think that this is just a again, a

bunch of

people in the peanut gallery who want to

take a moral high ground and try to make

some other group of people feel guilty

or feel bad. At no point are we actually

asking the conversation that

that we should be having, which is

it's interesting to me that the there

was supposed to be an EO, an

presidential executive order that was

announced today.

And then it was pulled. It was scrubbed

at the last minute. Mhm. Did you guys

notice that? Yeah.

>> And yesterday what was leaked was

everybody that was attending. It was all

the big neo labs CEOs and it was all the

big hyperscaler CEOs.

Including friend of the pod, Nikesh

Arora. Shout out to Nikesh.

And then it was scrubbed an hour ago.

Why was it scrubbed?

And the president said that there were

aspects of the bill that he didn't agree

with. And as far as we can tell, the

aspects would have required some amount

of

supervision, insight, review from the

federal government. Of language models

specifically. Of these frontier models

is what I read.

Not language models cuz I think just of

AI because there's going to be many

different kinds. They're not always

going to be language models, but of AI.

So, look, I think Freeburg is is right.

We are in a proliferation

with China. I think it's actually good

that China is less than 9 months behind

us.

I think it allows us to find a detente

where we have a certain magnitude of

capability that they also have.

And that allows all of us to then seek

peace and abundance. And the fact that

we are orthogonal societies, we are

organized differently, increases the

probability of finding peace using the

René Girard kind of framework of memetic

theory than if if it was like us and

another country that was exactly similar

to us.

So, I think what we need to do

we probably need KYC. I think that that

should be something that us and China

get together and say, "You don't want it

to get into the hands of people you

can't control." You probably already KYC

those models anyway inside of China. You

already review those training runs

before you allow these models to get

released. We already know that that's

happening. Yes. So, we should probably

do some sort of KYC so some crazy person

doesn't create some biological weapon. I

think that those are like some

reasonable ground rules, but otherwise

Friedberg is right. You have to take a a

little bit of a deterministic view here,

which is that we are in this existential

race

and we need to get to the place where

each of us, meaning us and China, can

look each other in the eye and say, "All

right, weapons down." So to speak.

Kevin, I'm going to hold you to answer

two questions. One,

should we

run frontier models cuz that's

specifically what was mentioned in the

leak about the EO frontier models, the

powerful ones. Should they be run

through some sort of testing before

they're released and should there be

some regulatory framework for that?

That's my first question to you. Yes or

no question and then you can explain

your answer.

Jeez, like I just think it's such a

complicated topic. It feels

we're a little early for that.

I don't love the idea of the United

States

um doing it and no one else doing it.

I

like I think in a world where we hold

hands with China

like I think that's that's much more

palatable and we are aligned and we

trust each other and have kind of

verification

uh capabilities. I do think

>> Right. Yeah. Let Let me then rephrase

it. Should China and the US come up with

a simple battery of things that have to

be

tested before these go out including

bioweapons, terrorism, and in genre of

and that vertical of just really known

dangerous things just like the FDA might

test for poisons or contaminants in a

food or a drug. Would you be in favor of

that? I'm curious.

So, a few things like the one one thing

that's great about America is there is

one thing that's

just

we have other forms of regulation.

Self-regulation, sure. We have self one

we have self-regulation also we have the

courts.

And if an AI model company

behaves responsibly

they know that there are

ways that people who have been harmed

can seek recourse.

And so we already have a system that

encourages responsible behavior on the

part of the model makers. That's a great

point because OpenAI is being sued right

now by a kid who who killed themselves

after talking to OpenAI's model. So,

you're you're correct in that. Yes,

after the fact. Yeah. And we will see

we'll see we'll see more of that. I just

you know, to me once you give something

give a power to the government

it's almost never taken back and it

seems to grow.

And it's kind of a one-way a one-way

path. One-way ratchet. Yeah. And then

the one-way second yeah, second question

then.

Chamath is saying hey nobody listens to

the you know, these cab drivers or maybe

the

people sorting the packages do they want

their jobs or not. Actually the UK

there was just a 60 minutes special in

UK and also Boston and New York are

pretty adamant that they want humans to

stay and they want to ban self-driving

in those locations or severely limit it

or maybe limit it in some way to let

those people keep their jobs. How do you

feel about that possibility? Is that

something you think society should be

open to some gradual licensing

>> They're going to get sued for wrongful

death. When somebody runs over somebody

else and you could have implemented a

solution that has a zero death rate,

that's very different from package

sorting.

Okay.

>> Go talk to the package sorters is what I

say. Go talk to the people inside the

Amazon warehouse. Ask them what they

would rather do at Amazon. Ask them.

Yeah, sure. But Gavin, what are your

What are your thoughts here on either

one of those examples here?

>> I think going to a city where you can't

get in a Waymo or a cyber cab is going

to feel barbaric and unsafe until you

Agree. I strongly agree. I don't know if

you remember like but the early days of

Uber, sometimes you go to a city where

there was no Uber. Yeah, that'd be

incredibly frustrating. What I'm not

going to come back until they have Uber.

It's so inconvenient. And I think so

whatever individual municipalities

decide, I do think one, Chamath's point

is really powerful. There's 50,000

automotive deaths per year in the United

States if I recall correctly and a

million globally.

And you know, that's not tolerable and

there will be for sure be wrongful death

lawsuits and then just from a

convenience and quality of life

perspective, I just don't think it's

going to persist. And that's another

great thing about America is you know,

you have this patchwork of different

states and municipalities and

each one doing things in a different way

and I'm not suggesting that's good for

AI,

but it does tend to, you know,

as historically the Curley effect aside,

led to, you know, I think more positive

outcomes where cities and states

compete. You know, the Curley effect

being that

Yeah, that Yeah, that this is a really

important point you're making, Gavin.

With Flock Safety as but one example, we

had a an AI There's an AI tool called

Flock Safety. It's cameras that use AI,

monitor people who are committing

crimes. There's a privacy issue around

it. It is bottom-up. You just do it by

town. It's not top-down and states can

regulate it. Same thing will probably

happen with self-driving and states will

probably have some say in how AI is

deployed even if maybe some centralized

governments don't want to do that.

I really think this It comes down to

>> The Flock

>> thing I think it's so good, Jason. Crime

is now a choice.

Yeah. You know, I think the the

Cambridge City Council voted

to turn off gunshot detectors 2 days

ago.

And

>> Wait, which city did that? Which

municipality?

>> Cambridge. Cambridge. Cambridge, Mass.

That's the place where Harvard is.

That's the place where Harvard is.

>> So, the geniuses coming out of Harvard

in that town decided

gunshot detection

shouldn't occur. We You don't want

gunshot detection. Just so we're clear.

It's wild because, you know, there's

there's a theory that it disadvantages,

you know, that it might lead to an

illegal migrant

who's shooting a gun being apprehended,

and we don't want that. Got it. And A16Z

had a great essay on Flock.

We can really, really solve crime,

and it's just a choice. And different

states and municipalities will make

different choices to be pro-crime or

anti-crime. And I'm sure they don't cast

it as pro-crime. There's

an, you know, some sort of, you know,

moral or ethical reason they may make

that choice, but people will vote with

their feet over time, and then voters

will vote with their votes, and we'll

see what works. Have you guys been to

Vegas recently? My wife and I went to

visit Vegas, and we spent the

the afternoon with Ben Horowitz and his

wife, Felicia. She has done this

incredible job with the Las Vegas Police

Department.

It is one of the most impressive things

I've ever seen, and to your point,

crime is an option, and they've said no.

So, what happens there is they have

gunshot they have drones that get

deployed off the roof of the police

building. We were sitting inside of

mission control where you see it

happening, Jason. If something happens,

they have eyes on site within minutes.

They can track offenders and bad guys

all the way to wherever they're hiding.

And you walk out of it, and you feel

incredibly safe, like they're really on

top of it. And when you understand the

level of investment, it's not it doesn't

take billions of dollars compared to the

cost of the crimes. It's de minimis.

It's de minimis. Especially when

compared to the cost of the crime

occurring. Exactly. If you gave the Las

Vegas Police Department

30, 40 million dollars a year, it would

be the safest city in America and that's

all it would take. Yeah, exactly. And

the for the privacy concerns Freiberg,

there are very simple solutions to this.

I I am a privacy advocate myself, of

course. We all want some level of

privacy.

I had the Flock CEO on This Week in

Startups twice in the past 10 years.

He's very considered. And the way they

do it with Flock is they allow you to

have a rolling database and I think

there's a maximum you can save the

license plates for and they don't do

facial recognition. I I don't see why

not, but let's put that aside. You can

only keep it for two or three years. And

then they insist on having an audit

trail on it. So, there are all little

things you can do on the back end to

protect privacy with audit trails, etc.

We got a lot more to get to in the

docket. I just want to just give my

final thoughts on

what we're talking about here in terms

of the AI problem

and the PR problem. I think we have to

recognize that the layoffs that are

occurring in Big Tech and in a lot of

these places are not just the bloating

issue anymore. And I'm just going to

point to two factors that I think are

scaring the bejeezus out of people and

we just have to admit that this is

occurring as opposed to we've been

debating it here. Is it occurring? Is

this just cover? And are we AI washing?

The first one I want to give you an

example of is Matthew Prince

who's the CEO of Cloudflare, incredible

company, public company. Two weeks ago I

laid off more than 20% of my workforce.

I didn't do it because Cloudflare is

struggling. We posted record revenue

growth, have strong free cash flow, and

are adding an unprecedented number of

customers, yada yada yada.

And he says basically he's getting rid

of measurers. Measurers are the people

who manage people and who measure data.

And he just says we're getting rid of

all those people. They're unnecessary

because of AI and we'll be adding to

people in other positions. At the same

time, Zuckerberg did another round of

layoffs, and they were done in a way

that people felt was not considered

and a bit

um

what's the word?

Dystopian. Dystopian, thank you, sir. Uh

he did him in a in a pretty dystopian

way.

Here's Zuckerberg for 30 seconds.

>> In general, the average intelligence of

the people who are at this company is

significantly higher than the average

set of people that you can get to do

tasks if you're working through the

contract um

through through these contractors. So,

if we're trying to teach the models

coding, for example, then having people

internally uh build tools that or or

solve tasks that um that help teach the

model how to code, we think it's going

to dramatically increase our models'

coding ability faster than what others

in the industry have the capability to

do who don't have thousands and

thousands of extremely strong engineers

at their company.

>> [clears throat]

>> Okay, so what Zuckerberg did at the same

time, concurrently, he told everybody,

"We're laying off these 8,000 people." A

lot of those people are incredibly

talented.

Some of them were on H-1B visas, creates

all kinds of chaos for them in their

personal lives, and obviously they're

having record profits there as well.

At the same time, he was laying off

those 8,000 people. This is after tens

of thousands of layoffs before, which

were obviously because of bloating. He

said, "We're putting recording software

on every single person in the company's

computer to study and train our model."

And people were like, "Oh." And previous

people said, "I built during the AI

hackathons they had months ago. I

built all these AI tools to make my job

uh more efficient." And then Zuckerberg

laid me off. So, the now pers- the

perception people have now, and it's

quite correct, I think, is the most you

can hope for here is you keep this job

for some amount of time and train your

way out of it, and hopefully there's

some more work for you, but they're

studying you, and Zuckerberg just said

it plainly there, "Hey, we're going to

study everybody here, and that's going

to lead to more replacements. This is

scaring the bejesus out of people and we

need to have an answer for it. Yeah. I

thought the Matthew Prince note was

horrible. Okay, explain. This was like

from the

PR school of retards. Okay, here we go.

You could not have written a worse memo.

It's like you reduce humans to a label

called the measurer

and then you're like I'm going to lay

off all the measurers.

I mean

I just think that part of this again,

I'll go back to the

maybe the Sham Sankar quote that I'm

thinking about should be extended beyond

the model makers. Can you just play this

for 1 second and I'll tell you why I

think this is just so

>> And then we'll go on to the S1 from

SpaceX. We're listening too much to the

inventors of AI. I know that's

appealing. They're geniuses, they're

smart. We need to be listening to the

frontline factory workers who are using

AI saying, "Wow, I was able to add a

third shift. I was able to hire more

workers." Or the ICU nurse who says, "I

have more time to spend with my

patients. I'm able to ensure they don't

code during a shift change down."

>> so look, my my point is like the first

part of what he said applies here, which

is who cares what Matthew Prince thinks?

Because the reality is that if this is

the way that you're going to message

something as critical as this, I think

you did a horrible job. And now you

label these people and you put a scarlet

letter on their back. So now when they

try to get a different job, they're

like, "Oh, you're one of the Cloudflare

measurers?" How does that help anybody?

It didn't needed to be done this way.

There's enough of these tech

CEOs that are now public. You can hear

them, you can understand them.

And I think what we're learning is men,

they're really good at one thing and

they're not necessarily as good at all

the other things. Yeah. Uh okay. And so

I would say shut the up.

Get behind the keyboard, just do your

job and if you need to manage something,

just manage it, but don't write these

missives. You're terrible at it. All of

you. You're all terrible. You suck at

this.

All right.

End of my TED Talk. Thank you for coming

to my TED Talk.

>> coming to Chamath's 18-minute TED Talk.

And we'll we'll we'll uh keep moving on.

>> Sorry. And sorry. When everybody gets

upset, this will be why. Yes. I mean I I

do think the Zuckerberg this and Jack

saying, you know, hey, we're going to

have as many people everybody reports

directly to me. This is all building

this fear in society and I think people

are right rightfully scared if the

people building it tell you be scared,

your job's going away. Wait till the

next

regulatory filing comes out from these

companies and they authorize a massive

share buyback and an increase in their

dividend. Yeah, and their cash pile

grows. All I'm saying is there's a right

way to do this, make these decisions,

and then there's a wrong way to do it,

which is to message it in the way that

they're doing it. So, whoever is running

PR and comms and approves and reviews

these things are really at their

job. Mhm.

They don't understand the moment.

Oh, some breaking news here. It looks

like Anthropic has hired three more

people. Here we go.

Oh, here we go. Personal job news from

Sam Altman. He'll be joining Anthropic.

I say that's pretty good. Okay. Who else

is joining Anthropic? Let's see if we

checked everybody's socials. Oh, Tucker.

Tucker Carlson is also joining

Anthropic. He'll be doing their PR and

podcast from Anthropic headquarters. And

Who else? Oh, Chamath. Looking good.

[laughter] Well, you look like you put 5

lbs on.

And using the people

>> First of all, this is not This is not

what I look like. And um

>> Did you gain 5 lbs?

Looks like the same

guy. Are you not wearing Are you not

wearing underwear?

He's not underwear and he's wearing his

khakis, but I think it's just he's

trying to not show off those scrawny

those scrawny sclints those those little

slats he calls legs. He's covering them

up now. Uh hold on. I'm going to send

I I I knew that this was going to come

up. I'm going to send Nick an updated

picture of my legs, and you you can deal

with this.

>> You can Photoshop your legs all you

want.

>> I didn't Photoshop

>> look like didn't

>> an brother.

>> He's got better legs than you. I'm

working on it. I'm working on it. I'm

working on it.

>> [laughter]

>> He may not be photoshopping. He may have

been leg maxing. He could be leg maxing.

Are you leg maxing? Are you BP 157 your

legs? What are you doing here?

>> of all, first of all, I'm 6'2" you

goons. Okay, so

>> Ostrich legs. All you little people, you

know, Jason, you're 5' tall, so you

know, your ability to have legs I'm on a

good day with my platforms.

>> to have legs is is different cuz like my

muscle mass won't show on my legs the

way it shows on your leg. Oh, I don't

think you're help but I look at you know

what he's doing there? Freeburg, you see

it, right? Look at how skinny the calves

are and then look at how he's wearing a

>> Oh my god, Jason.

>> bra for your quads. Oh my god, stop.

>> equivalent of a push-up bra. He has

those Bosu balls. He put Bosu balls

under his hammies to You did it. You're

using filets to pump those up.

>> my legs and I flat Okay, you know what?

Move on. You know, I would just say I

think we should give credit where credit

is due. Yeah. Jamath's legs Better.

>> Jamath has been doing a lot of work on

his legs. Thanks, Chamath.

>> better. Thank you. It's better. Thank

you. I'll I'll give him better, but I do

think that he's pumping them up here.

Okay, let's keep going here. All right,

topic two is SpaceX just filed their S-1

on Wednesday. They are aiming to raise

75 billy at a 1.75 trillion with a T

valuation. This would be the largest IPO

ever by more than double Saudi's Aramco

$29 billion IPO a couple years ago.

Listing is expected mid-June, likely

June 12th. Ticker will be SPCX.

We got a lot of interesting information

in the S-1 teardown. Obviously, SpaceX

has three main business units.

Starlink is the money printer right now,

but there's a second one that's

emerging. Starlink did 11.4 billion in

revenue last year on 50% growth with 4.4

billion in operating income.

Over 10 million people are now

subscribing to Starlink. That business

could easily be hundreds of millions of

paying subscribers. So, that that's a

lot of growth potentially there. The

space business is but 4 billion in

revenue. It's growing 17% growth, which

would still be strong growth.

Uh but had 650 million in operating

losses. AI did 3.2 billion in revenue.

That's more than double year-over-year

growth, but it had 6.4 billion in

operating losses.

SpaceX had 20 billion in capex spend

last year. Over 60% was for the AI

compute buildout.

And obviously they were trailing

Anthropic and OpenAI and Gemini in terms

of XAI, uh playing catch-up. And he did

a big reboot of that as we saw on the

Twitter.

But here's the big one. EWS, Elon Web

Services, as we call it here on the

All-In Pod, has exploded. Anthropic is

paying SpaceX, wait for it, 1.25 billion

a month to rent out Colossus 1 and parts

of Colossus 2. It's a $45 billion deal

over 3 years, 15 billion a year. In

other words, they added a Starlink in

terms of revenue to the party. Plus, if

they buy Cursor, that's going to add

another 2 or 3 billion. Not

>> Not if. I already told you they already

bought it.

>> Okay. I'm just trying to, you know, dot

the i's and t's here. But when they buy

Cursor, that adds 2 or 3 billion. That's

not in the S-1. That's also growing and

doubling. Yeah, that's probably growing

2x year-over-year. And who knows how

much faster it'll grow. Polymarket, 71%

chance SpaceX closes its first day of

trading with a market cap above 2

trillion. Thank you to our partner,

Polymarket.

I'll stop here. Gavin, you've been

involved in the company for a long time.

Chamath, you I think were a big investor

in the satellite company that became

part of Starlink, which is the revenue

driver there. So, you both have a lot to

say about this. Gavin, your take on the

S-1 and I think specifically Elon web

services.

Well, I think what's important about

Elon web services does make me laugh.

But 15 billion, that means the AI

business right there is going to

quadruple. It has already effectively

quadrupled.

I think what's important about that is

there's a stat in it that for I think

the the first data center was 122 days.

With the second one, it took them 91

days.

The third one was I think 66 days.

They build data centers dramatically

faster than anyone else at a lower cost.

And now that you have a

clear off-take partner and I would

expect partner to become partners,

there is no reason they can't start

stamping these data centers out really

fast.

And having watched Jensen for a long

time, it is important to Jensen that his

GPUs be used.

And so GPUs will be allocated to who can

plug them in, turn them on, and start

converting electrons into tokens.

And so I think this business can grow

dramatically faster than I think

you know, maybe what anyone could have

contemplated three, you know, three

three months ago. But 15 billion dollars

from Anthropic

is is extraordinary. Important note, it

can be canceled by either party with 90

days notice. Just want to make sure we

also have that in there. So that means

Elon might want his compute back or

Anthropic may find another solution. So

they do both have an out. And I think

that's that's a

you know, I think that's that's that's

probably an important provision Yeah.

for everyone. But I think the other

thing that came out this week, which was

not in the S-1. Nick, can you throw up

the parade of frontier and maybe don't,

you know, include the email and the

names and everything, but the composer

2.5 stat. I think this is really

extraordinary.

So, Cursor's composer 2.5 model came out

this week.

And I mean, this is Pareto dominant.

And this is just

you know, three, four weeks of doing

reinforcement learning

on Colossus 2

with Cursor's data.

And Cursor has We will never know, but

but Cursor allegedly has more tokens of

coding data than exist on the public

internet.

And that is a stat from I think more

than a year ago, so I'd imagine it's

grown significantly.

And I think Cursor and Anthropic

probably have the most proprietary

tokens of coding data. And what this

this jump from composer 2 to composer

2.5 showed us

is that when you do an appropriate

amount of reinforcement learning using

that data, well, let alone injecting it

into the pre-training of a new base

model.

Cuz composer 2.5 is the same base model

as composer 2, which is Kimmy K K 2.5.

Like, this is amazing. This is three or

four weeks, and it is Pareto dominant.

The Pareto frontier, if you draw a curve

of the blue dots,

you can see

composer 2.5 is literally

well outside the Pareto frontier. And

that's after three weeks.

And what's going to happen next is

you're going to have a

new base model

with a Cursor model in it. Yep. Then the

Cursor model

RL'd

using the biggest coherent

compute cluster in the world.

And I think

this is

I I think this may

>> It's significant, yeah. It's extremely

significant for XAI and Cursor.

And Cursor was dead in the water in

terms of access to compute and they were

falling very far behind Kodaks,

Google, Anthropic, and then Elon let

them on Colossus and boom, instantly

their models are

growing faster and this could be we

could be sitting here a year from now

and they're the dominant player.

And

could we be sitting here Gavin in a year

and Elon is selling compute to Google

and OpenAI? Is that a possibility or

not?

Well, I think it's much easier to see

him selling compute to Google and I

think that's going to happen.

There've already been posts about that.

Yeah.

And for sure Google is going to want to

be part of orbital compute.

You know, it's it's a very funny. The

only people who are skeptical of orbital

compute are those people who are not

involved

in data centers or space. Google,

Anthropic, Amazon, Nvidia.

They are all very convinced that orbital

compute is going to be reality and

obviously SpaceX is extraordinarily well

positioned for that.

But I do think that composer 2.5 data

point is really powerful. Keep an eye on

it. Yeah.

And then the other thing that's come out

is Grok builds. So, what Grok lacked

that a lot of other models had and I do

think it's important to

remember that the newest version of Grok

4.3 is on the Pareto frontier for all

frontier models.

And you're either on the frontier or

you're not.

And the the companies on the frontier

are xAI

with one build of Grok 4.3, which is a

500 billion parameter model,

Google 3.1 Pro, and then OpenAI and

Anthropic. And that's it. Those are the

companies on the frontier. And then the

four horsemen, yeah. Google today each

have one dot on the Pareto frontier.

And obviously you want as many dots as

possible, but Grok lacked a harness.

So, Claude had Claude code, Open AI had

Codex, and now with Grok build there is

a harness that is available to to Grok,

and you know, as I'm as I'm sure a

downloadable app to translate into

English that has integrations to all

your favorite stuff, whether it's

Notion, Gmail, Slack, etc. And if you

don't have that, it's just like using a

a basic chatbot from a year ago. So now

they have their downloadable, it's in

market, and they are cooking with oil on

it, and they're playing catch-up, but

they're moving fast. And and it's it's

more than just an app. It's it's a

runtime, it's an environment, it manages

state, it manages memory.

It makes these models dramatically

more useful to the extent that I think

the people at the frontier all agree

that the harness is essentially as

important as the model, especially in an

energetic world, and the harness and the

model need to be developed together. So

the release of Grok build and the pace

at which they're iterating

is I think also really encouraging. So

now you have Cursor, you have the Cursor

data, you have a clear existence proof

that the Cursor data is really important

cuz cuz Composer 2.5 is now Pareto

dominant and the most selected model on

Cursor, and that's also important

because, you know, these evals don't

capture everything. You know, this is

why people on X talk about the vibes,

and the vibes on Cursor 2.5 are also

really good. They're immaculate, yeah.

>> That together Yeah. with Grok build, I

think these are really important

developments. Yeah, I they're There was

Elon was incredibly frustrated by the

state of affairs at XAI. He was very

public about that, and he's less

frustrated now, and he's shipping a lot

faster. And so I think that says

something, and he has been very focused

on it.

Freeberg, your thoughts on the SpaceX

IPO and what this collection of

companies might look like a year or two

from now, especially if, like many

people believe

Tesla and

SpaceX merge, what do you think of

dollar sign E L O

E L O N as an entity and what impact it

might have as if those two were put

together the market cap would put them

in the fourth largest company in the

world. We can revisit our earlier

conversation about an anti-tech,

anti-AI, anti-

progress

world and society ahead. And if there is

an effort a concerted effort and

organized effort by governments to stop

or block access to information,

restrict freedom of speech, restrict

freedom of purchasing or buying things

to

control more things. And I think there's

a trend line in this direction right now

globally. The internet has always been

lauded as this kind of

system that provides an open alternative

to physical commerce that you could

create digital commerce, digital

uh

information, digital media that you

could share. And um it's almost this

digital representation of society, but

the internet has to sit physically

somewhere.

And the assault on data center builds

out in the United States right now,

I think

may indicate the importance of having an

alternative internet from the ground

layer up. If you have a communication

network that isn't restricted and

controlled

by a government

on Earth.

It's almost like a backup

for civilization, but it's a backup for

progress.

And I don't own any SpaceX shares, and

I'm not trying to sell the book of

SpaceX.

But I think that there's like an

important aspect of

can you create a system that's not under

the control of governments

as a way to ensure humanity's progress,

to ensure civilizational continuity if

things go south, if things aren't good,

if things are restricted, and if, you

know, fundamental forms of tyranny start

to restrict speech, restrict commerce,

restrict information flow, and whatnot.

And I think having like a space-based

communication network, space-based data

centers,

and space-based communication back down

to Earth wireless,

I think it's generally a good thing.

It's good to have a backup. Yeah. So,

put all the economics aside and the

multiples and the valuations and

whatnot, and whether it's SpaceX or not,

I think the idea that you could have

data centers, store information,

transmit information, route information,

and access information through

space-based systems that can't be

controlled, manipulated, or destroyed by

governments, is is important. And I I

just I like that.

Yeah, if you

Most people don't remember this, but

when Elon was starting SpaceX, the

original idea,

when he was running around with the DAO,

and they were

looking at some rockets and getting

carriage from Russian rockets, was to

back up the biosphere. And he came back

from that trip, and I remember talking

to him about it, and he said, "I think I

just have to make my own rockets,

because that's actually where the

problem is, and it would be easier just

to make my own rocket to back up the

biosphere." And he wanted to put

geodomes,

like geodesic domes in space,

with all the plants and wildlife and and

creatures.

Uh and what incredible vision, and then

it, you know, there was the necessity of

actually getting that up into space, and

that's that's the the unknown origin

story. I will say this, Chamath, the

idea of putting

uh data centers in space seems

completely doable, even though there are

a bunch of people who are saying it's

not,

when you compare it to what happened

with SpaceX um with Starlink, which

people said also wouldn't work. And now

he's got 10,000 Starlinks up there. The

difference between a Starlink satellite

and a data center satellite is really

not that different. And No, they're

they're pretty different. Well,

conceptually, of course they're

physically different, but conceptually

Elon put 10,000 Starlinks up.

Is he capable of putting 10,000 No,

look, the size is much the size the size

is much bigger, Jason. The foils are

much bigger, the wings are much bigger.

>> but it's it's Yeah. My point is it's not

different if he has the new Starship.

Cuz that's 10 times bigger, yeah. You

can't just scale like this. That being

said, it's technically possible. I think

he will be the first one to figure it

out.

But I'll just take a much more

pedestrian take, which is okay, you're

sitting here

and if I'm asking myself, Chamath, how

do I underwrite SpaceX at $2 Here's the

basic math that I would do. Well, last

year it did 18 19 billion dollars.

It'll probably do 25 to 30 this year.

Okay. So, I'm buying this thing

at a fairly

costly premium, right?

So, what am I buying?

Well, I'm buying probably the most

important internet infrastructure

project that's happened since the

internet itself.

That's going to scale to hundreds of

millions of users. And the reason that's

going to scale to hundreds of millions

of users is

it's just very useful and it's just

going to become cheaper and cheaper and

cheaper.

So, that's number one.

I'm buying a delivery infrastructure.

But I think over time

GDP plus 10, GDP plus 15 kind of a

grower. So, good business,

valuable business, but it's the

underlying platform that allows

everything else to happen.

And then I'm buying an AI business which

will be at the top level of the apps,

but at the bottom layer all the compute

capability.

And I think when you scale that out,

like why is Colossus so valuable to

Anthropic? Maybe that's like a good

question to ask.

It's because if you look at who's

actually capable of delivering a

gigawatt data center,

these guys are the closest.

Like an actual gigawatt. And And the

reason is is that this stuff is very

complicated and very, very hard. I think

you've probably heard this famous story

where Jensen was like, "Yeah, he was the

one that figured out this one thing that

we that nobody else could figure out so

that you could strip a bunch of racks

and drive a bunch of east-west traffic

and make the whole thing work together."

So, I suspect what happens is next year

it's probably

40, 45 billion. And then the year after

that it probably doubles again. So, now

I'm buying it at 20 times revenue. And

you would say, "Well, why can you buy a

company like this on revenue versus

earnings and cash flow?"

And I think the reason is because what

the revenue does is it gives him the

operating leverage to go and invest in

all of these other businesses

that ultimately consolidate

his differentiation and his competitive

moat. Because what he creates is a

capital moat that then accelerates a

technology moat that then accelerates an

execution and a learning moat.

And that's flywheel when it starts to

spin very quickly. And you would say,

"Hey, hold on a second. It's probably

spinning quickly now."

I would say we're at the beginning of

the beginning.

Because he's Again, he still has all

these disparate assets. I still don't

like the fact that Tesla's over here.

And as I've told you, that will get

merged in. And now you have this

incredible corpus of

physical capability,

movement of all kinds, X, Y, and Z,

right?

You have learning capability. You have

infrastructure. You have all the

connectivity.

That thing will look very cheap, I

think, in a few years.

And he has this one thing that nobody

else, if you look at the big CEOs,

who steps on stage where you're always

curious, "Okay, what does he got up his

sleeve?" You know, the Steve Jobs, "Oh,

and one more thing."

This is the only guy at the scale of

civilizational

out of left fields.

He's he's the guy. Whether you like him

or you hate him, he's the guy. And

there's a premium that is well deserved

that comes with that.

So, if you had to pick an underwriting

case, Jason, I would flex the revenue

and realize that terrestrial data

centers alone

are 100 or 200 billion dollars of

revenue by 2030, 2032. Just And that

means just building it. So, already

you're buying it at 20 times revenue

just for that business. Everything else

is gravy.

>> on the ground earth-based. It'll be

Colossus three, no, no, forget space for

a second. It's a Colossus three,

Colossus four. It pencils out with that,

yes. Getting a nameplate 1 gigawatt

Look, it is freaking hard, man. Getting

a gigawatt nameplate working

is almost And then, by the way, there's

all the stuff that he can do on land

that he's the best positioned to do.

I'll give you one example. There's a

great push that Jensen's making, which

he needs a partner, and I think Elon

becomes a natural partner, to do DC to

DC. Forget all this DC to AC to DC

nonsense that goes inside of a data

center. All the lossiness, all the

lossiness.

>> that is in English, yeah, for everybody.

Just like, look, you go through a bunch

of power transformations to to actually

deliver the electrons into the rack so

that, as Gavin said, you can generate

the token on the other end.

Today, it's it's very inefficient, it's

very costly, it requires a lot more

power, it requires a lot of cooling, it

requires complexity. And what people

have said is, "Wow, if we could just do

DC to DC." Like, it comes in as DC,

direct current, it goes right to the

rack as DC. But it requires a

fundamental rearchitecture.

Jensen needs a design partner and a

thought partner to get that done. Mhm.

He's probably the only one. So, I just

think there's a lot of reasons where you

can underwrite this to a multiple of

revenue plus the X factor, which is just

the creativity and the the one more

thing. Love it. And then here's two uh

charts, and I'll have you comment on

these, Gavin, after it.

Here's the rocket sizes.

Just in terms of scale and I most people

have not actually seen a Starship in

person. When you see this thing in

person and I I've been inside that

rocket.

I think you were we were together,

Gavin, when we were in the first build

and like inside of that you can fit 300

people. It's basically like

a giant

if you thought of a commercial air

aircraft, that's what it feels like when

you're inside, right? Like a 747 in

terms of the amount of space in it.

Especially when you compare the Falcon

Heavy, which is their workhorse,

correct, Gavin? Yeah, and Starship's

going to get bigger. Based on their road

map, it's going to get a lot bigger. A

lot bigger and then this one is the most

interesting that this started trending

this week. This is cumulative payloads

launched 1957 to today. SpaceX is

basically about to in just that and and

this is really what exponential growth

is about and this is what disruptive

technologies are about.

Just from 2012

to today,

SpaceX is about to dwarf

the rest of the world's cumulative

payloads into space. So, Gavin, maybe

take the other side of it.

When do these data centers in space

happen? What has to happen for those to

be a reality? When does that hit

SpaceX's bottom line? We've heard from

Chamath, "Hey, here's all the things

that hit the bottom line in the short

term and mid term." But I think data

centers in space would be a mid term to

long term play. 3 years is what I'm

hearing. So,

tell us about that business in relation

to the two charts I just shared. Well,

the one thing I would just say, well,

first, all those charts about launch are

before Starship was operational and most

most of that mass to orbit was done by

Falcon. Yes. And Starship

the Falcon is reusable. Starship is

designed to be rapidly reusable and this

is a critical difference. Like, let's

say Blue Origin successfully solves

reusability.

They're where SpaceX was 10 years ago.

Let's say China solves it 10 years ago.

Rapid re- The reusability means that you

extensively refurbish the rocket,

you know, the engines, everything, the

fairing. It takes a lot of time.

You know, maybe you can fly that rocket

again in

30 days, 60 days.

Rapid reusability means that you can fly

the same fly and land the same rocket