when the history of the 21st century is

written, you know, there was like the

Victorian age. I think this will be like

[music] the age of Elon and Jensen

because they are fundamentally altering

the fabric of human society and

civilization.

>> What happens if there's like a massive

supply shortage?

>> Every time you've had a real profound

new technology, you get a bubble because

the markets get really excited and they

get ahead of themselves. Things get

overvalued. That overvaluation leads to

an overbuild. One of the things that I

think has been correct but ineffective

is this idea that we need to stay ahead

of China.

>> You're opposed to data centers. Well,

you know what? It's probably the best

thing that has ever happened to

workingass Americans. We are

re-industrializing America and it's

awesome.

>> Assume that you're right. There's not a

physics reason why this can't work.

>> An increasing fraction of the world's

compute is going to be in orbit. This

sounds crazy, but asteroid mining is

going to be a very real thing. It has

more gold, silver, platinum, every

[music] precious metal in it that exists

in the earth's crust.

>> Every LP conversation that we have

starts with like, how's this all going

to go wrong?

>> Gavin, uh, you've been out here hanging

out on the West Coast over the summer

and you've been talking about the fact

that you're like trying to find someone

to make you to give you like a a bearish

case, like to make your sentiment more

negative. Um, have you found anybody?

>> No. And I ask everyone, my standard

question is, can you tell me one

quantitative data point in your business

that's getting worse? Just one. That's

my standard question. And it's at least

in July and August, I haven't been able

to find a single person. Now, if we're

being honest, you know, Anthropic is um,

you know, in a quiet period, so maybe

they've slowed down a little bit, but I

do think the rest of the world

has accelerated. You know, OpenAI is

clearly accelerated. Open source, I

think, has accelerated more. And then I

do think Grock, particularly after

Grockbot, has had a pretty experience,

has had a pretty dramatic acceleration.

And so AI overall, it accelerated in

July. It accelerated in August, and it

can't keep accelerating forever, but

it's just kind of wild that, you know,

public stocks have kind of fallen out of

bed over the last, you know, two months.

And I mean,

you know, it's uh that, you know, they

you can you can drown crossing a river

that's on average 2 ft deep. And so, you

know, there's not a lot of action at the

index level,

>> right?

>> But some of these AI names are in pretty

significant draw downs. And they b they

bounced a little bit um in August, but

still pretty big draw downs and things

are broadly accelerating.

>> Yeah.

>> It's um you know, our friend Eric

Fishery did a podcast with Patrick

Oanessy and he said maybe everyone wins.

>> Yeah. you know, Anthropic wins, OpenAI

wins, SpaceX wins, Meta wins. Um, you

know, Google wins by selling a lot of

TPUs. Um, open source wins, NeoClouds

win, inf you know, inference cloud, uh,

the inference clouds win on top of the

Neoclouds. Um,

>> applications win.

>> Yeah. Every Yeah. And that kind probably

maybe not all applications applications

that I think execute well and navigate

this

but that feels like a very possible

scenario to me and there's so much zero

someum thinking in the world and by the

way on anthropic what is

my hypothesis would be if you're

anthropic one I think they probably tred

up and cleaned up some accounting

>> yes definitely

>> you would you'd rather do Yes.

>> So you rebased and now you're comparable

to OpenAI.

>> Yeah. In terms of revenue added, like in

terms of the definition and now I think

kind of revenue added.

>> Exactly. So you kind of rebased and then

they you know they did their testing the

waters. Um [clears throat]

and then you know I would hypothesize

because they've executed well probably

the next disclosure is a reaceleration.

And then there's always this kind of

funny game between the frontier model

companies. They always have more

advanced checkpoints. Anthropic is

clearly waiting for OpenAI to release

Astra.

>> Yes.

>> And then it's like the next

>> the next day.

>> Here's Fable 5.1.

>> Yes. Exactly.

>> Magically and just happened to be

available several hours after Astra.

>> Yeah.

>> So I think they're being thoughtful um

and you know heading heading into this

IPO and everyone is shooting at them.

>> Yes. everybody's shooting at them and

they're in a quiet period so they can't

really shoot back. Um, and so it's, you

know, there's a lot of gamesmanship, but

I do think

having OpenAI anthropic be public

companies is going to be helpful for the

market just cuz it's,

you know, it's such a uh powerful force

and a lot of public investors, you know,

you hear, oh, you know, Sarah Frier said

this at an all hands meeting and it's on

the cover Wall Street Journal. Okay,

we're going to put that into our model.

>> Yeah. And it's just a lot I think it'll

be better for them to be public. I am a

little um you know Anthropic is now in

their culture interviews saying how

would you feel if the equity went to

zero?

>> Yeah.

>> Because we're looking for people who are

mission aligned.

>> Yeah. Mission not mercenary. Yeah.

>> And and that's great. We we want we want

missionaries, but we also want people to

make money. And at the end of the day,

you can't afford the compute you want

for your mission if you go if the equity

goes to zero. Like I'm no expert, but

I'm pretty sure on that

>> in that I do think they are

>> they're like the accidental enterprise

company.

>> Oh, for sure. Oh, yeah. They're kind of

like the accidental everything.

>> Enterprise is just a byproduct of like

the the the mission, the objective at

the end. Yeah. Whereas I think open eye

is a little more commercial and

obviously SpaceX a little more

commercial.

But all of these companies like let's

just let's let's just say um let's just

say they have 10 gigs of power and

they're allocating eight to inference

and let's just say they're monetizing

that inference at you know whatever um

you know 60 60 billion a year. Um, so

$480 billion a year in revenue,

>> which is like a on a revenue payback

basis would be like a one-year payback

on a revenue basis, not a gross profit

basis.

>> Yeah. On a revenue basis. Yeah. Yeah.

>> Um, and I've tried to use conservative

numbers. You know, people seem to think

and open are both monetizing at hundred

billion dollars a gigawatt today.

>> Yeah.

Let's say they have a big research

breakthrough and they decide, "Wow, it

is to our long-term advantage

to go from eight gigs allocated to

inference, two gigs allocated to

training to 8 gigs on training and then

your revenue just went from 480 to 120."

And I think they your annualized revenue

and I actually think they would do that

>> make that decision.

>> Yeah. And this is just something that

like public markets are going to really

have to get used to.

>> Yeah.

>> It as you say, open AI may be a

different animal. And I do think like

the realities, you know, everybody

everybody has these ideals about how

they're going to manage their business,

then they go public and the stock is

volatile and it really impacts, you

know, employee morale, recruiting,

retention. So, I'd be surprised if they

did such a dramatic cut, but a lot of

the revenue is kind of under their

control based on what checkpoint they

release.

>> Yeah.

>> Where they price um along this, you

know, kind of paro curve and then how

much they allocate between training and

inference. So, it's just

it's going to be, you know, Meta and

Google and these kind of internet

companies. It was just it was pretty

smooth fundamentally even if the stocks

were volatile.

>> Well, there was no like massive

trade-off they had to make in terms of

the cost or infrastructure to serve

revenue side. Like they were totally

separate

>> 100%.

>> Yeah. It's it's fascinating. Um so, you

know, if you go back to Eric's point of

like it's all going to work like I

actually think that's a great point.

Like I I I describe it differently. I've

had this conversation with LPs a lot cuz

every LP conversation that we have it's

probably the same for you starts with

like how's this all going to go wrong

>> and it's like what's what's going to

crash and I'm like this is the this is

the and like oh are the are the large

models screwed or the labs screwed

because of open source and I'm like this

is this is this is all wrong like this

is not an or thing it's an and thing

right like this is an and thing um

Frontier is going to work really well

like N minus one models are going to

work really well open source is going to

work really well um there's going to be

a bunch of application companies that

work really well. Like the clouds are

probably going to be fine. They're

probably going to work really well.

>> Like the five lab companies are probably

going to do really well.

>> Yeah. And Nvidia is

at the center of all of it.

>> Yes. Yes. They're probably going to do

pretty well.

>> Yeah.

The last um 26 years have taught me not

to bet against Jensen.

>> Yeah. He's he's he's in a pretty good

position here. Um I want to come back to

that. The the point that you made about

training verse inference is an

interesting one. It seems to me like the

labs will decide to take all incremental

profits and probably much more than

their profits and invest them in

training for a long period of time.

Would you think that's fair? Like this

is very different than like the clouds,

you know, cuz like the the cloud like

the internet companies and the clouds,

they just end up being supply demand

driven and they generate tons of profit

and they can still grow a certain amount

like but they don't have some maybe with

the exception of Meta like some big

long-term bet that's like a multi-year

payoff.

>> Yeah, I think it's important to kind of

be precise. They I for sure I don't

think they will generate free cash flow

anytime soon. I think they're going to

generate a lot of operating cash flow

and then they'll use that to buy a lot

of, you know, GPUs,

um, XPUs, whatever, whatever we're going

to call them. Um, or maybe they

subsidize heavily. Like we do know that

that's happening at the labs.

>> Subsidize what heavily

>> their first party products. So token

consumption of their first party

products. So like they're doing all this

research and they're spending a lot on

data on compute

>> and the first products that are like a

heavy subsidy

>> products today, right?

>> Yeah. So it's 8 gigs of inference and

two gigs is for internal research and

then you know two gigs is actually

training.

>> Yeah. Exactly.

>> Um and you know including probably the

inference that goes into post- training.

>> Yeah. I don't I I think given the belief

systems that they all seem to have about

scaling laws

which continue to hold I don't think any

of them are going to be that focused on

generating free cash flow and you've

seen right we saw Satcha blink.

>> Yes.

>> And Satcha really regrets that I think.

>> Yeah. Yeah. um you know he kind of

blinked I think it was last year

you know he gave that great interview

for Davos and they asked him about all

the capex and he said I know I'm good

for my 80 billion

>> right

>> and and I think they blinked a little

they slowed down they regret that and

then Daario famously he went on a

podcast and he made and he said listen

some people are being super

irresponsible with their spending and

it's a hard decision because if you

don't spend enough you could lose a lot

of shares But if you spend too much, you

could go bankrupt. And like those are

both bad things, but bankruptcy is worse

than losing shares. So I'd rather be

conservative. And he was conservative.

And OpenAI was aggressive. And now

OpenAI is back in the game.

>> And SpaceX was aggressive.

>> And SpaceX was aggressive.

>> And so, you know, like there are clear

high ROIs on those independent of supply

demand mismatches that are happening.

Like clearly that seems to be the right

decision short-term and long-term.

>> Yeah, absolutely. I mean, we we

calculate, you know, Nebius um and

Corweave both gave some interesting

disclosures, but you can kind of get to

a 9 to 10 month payback for Nebius

because you know, okay, you bring on a

gig, it costs 50 billion. You get you

can get an upfront payment for 50 to 60%

of that for customers. Yeah.

>> So now, you know, you're talking about

25 or 30 billion and then you can

monetize it if you put it into the spot

market.

>> The spot. Yeah. at a spot spot paybacks

are probably much faster than nine or 10

bucks.

>> Yeah, you got to assume like a smoothed

out level like two two bucks, three

bucks even with that. It's very very Now

you can get like five bucks or eight

bucks and Yeah.

>> And then SpaceX cuz they build these

really big clusters and and I think at a

really important point is they bring

them on fast.

>> Yes.

>> They have an even faster payback and

they can monetize at you know higher. I

I have tried to shift um you know to

think of pricing and you know per

megawatt rather than per GPU because it

seems like it's where where the world

>> world is but like SpaceX the payback

feels well inside of that.

>> Yes.

>> And I just in my career as an investor

there haven't been that many

opportunities where you have companies

that could deploy tens hundreds of

billions of dollars and get sub one-year

paybacks.

>> Yes. And it's kind of crazy. And then

also like we should also talk if

particularly if you're buying Nvidia

GPUs to a lesser extent TPUs, you can

finance these.

>> Yes.

>> And there's a very sophisticated, you

know,

>> Yeah. very low cost of capital to

finance them today.

>> Yeah. And everybody's, you know, worked

up about, you know, circularity and it's

like, well, I don't know. Um, I know a

lot of smart people who work at

Blackstone and KKR and Apollo

and they're the ones that are financing

>> the ones who are financing it at a

relatively low cost

>> at a relatively low cost. And I think

one reason that's happening is useful

lives just keep getting extended and has

these models get better and better and

better and the ROI on token spend goes

up, you know, the monetiz monetization

rate per gigawatt goes up. So, I mean,

the true equity payback like might be

way inside of a year.

>> Yeah. Exactly. Exactly. Yeah. And look,

there's a case you could make that the

prices actually of all the stuff go up,

which could make the the supply side

economics even more compelling, right?

Like, you know, so on the supply side,

like that's the dynamic today. Like, it

just is what it is. Like, there's a ton

of data points out there that paybacks

are within a year.

>> Yep. Um I think it's actually

interesting to think about the demand

side too because the knock would be well

in all these cycles you get some

overbuild and then that you know

destroys the economics of the supply

side. The demand side today like what

are we monet like the monetization of

these companies which are doing call it

80 billion of revenue or something in

that direction um is on the back of what

like 30 million actual heavy paying

users like re getting real value. I'm

talking about like developers like

>> I might take the under on 30 million

>> so call it yeah actually what we see

inside our companies is you know

obviously there's a power law in which

companies are spending a lot on tokens

like old banks are probably spending 1%

very techforward companies are spending

high single digits but if you actually

look at the sort of the the power law of

what's happening of the actual engineers

in those companies the highest spending

engineers are spending 10 or sometimes

is 100x more than the median engineer.

And so, yeah, your 30 million is

probably way overstated. It might be sub

10. And so, there's this question of

like where are we at in diffusion?

There's one and a half billion knowledge

workers. Like, it feels like we're

nowhere on the demand side and we're

massively supply constrained.

>> And what are I'm just curious across the

A6Z portfolio if what are your best

companies spending on tokens per month

relative to human compensation? What

rough range?

>> Oh, high single digits, some at 10%,

like some of the very AI native ones

like 10% plus. And so, you know, and and

then old economy companies are spending

the ones that are probably doing a good

job like 1%. So, it feels to me like

when I look at the supply demand

characteristics, it's like supply stuff

people say, is that sustainable? Well,

like when you pair it with the demand

stuff, I it feels it feels specific.

Like there could be things that

disappoint us in terms of like diffusion

into the real economy,

but it feels like over a 10-year

stretch, like we're nowhere.

>> Yeah. Absolutely nowhere. And I just

>> my So at a trade is our internal token

consumption has gone up 100x from the

month of March. March through August.

100x our token spend. And we just got

access to uh Grockbot Enterprise and

with two people using it like it looks

like it token spend might 10 or 20x in a

month.

>> Yes.

>> From August.

>> Yes.

>> Like like I

>> But but it's actually extremely

valuable. Like we have some heavy

Grockbot users here and like it is very

productive use. Like this is not like

wasteful tokens, but

>> yeah, I was and and listen like I I try

super hard. I you know I always when I

use AI, I just remember when my parents

like I was trying to get them to shift

to an iPhone and an iPad and like you

know get them used to it and like you

know and they did a good job. I give

them loads of credit and but you know

I'm 50 years old you know like how old

are you David?

>> 42. 42 and you see these like 23-y old

kids and just the way they use AI,

they're just fluent and native in it. I

just feel like maybe in a way that no

matter how hard I try, I will never be

and I'm trying really hard. But, you

know, like we got cloud code, I try I

you know, I built some stuff, did some

cool stuff and in like I don't know

three minutes of type creating Grock

bots, I had much better versions of

everything I created, you know. You

know, so I went on this Patrick Oannessy

pod podcast like 5 months ago and I

said, you know, like I love having a

podcast summarizer. Everybody's like,

"How'd you do it?" I was like, "Well,

just use AI and do it."

>> Yes. Pretty simple.

>> It takes 10 seconds and Grockbot.

>> Yes.

>> It's amazing and it's so good.

>> Yeah.

>> And then, you know, a Substack

summarizer, an X summarizer, um an Xs

sentiment tracker for topics and stocks.

>> Yeah. And like that all of those would

have taken me I don't know hours working

with cloud code and they each took 7 to

12 seconds with Grockbot and it's

better.

>> Yeah.

>> So to to me Grockbot does feel like

another um at least for me like kind of

chat GPT moment because Claude code

>> like I can see in the data was it was

powerful. I did some really cool stuff

with it that was like empowering and

this is neat.

>> Um

>> you know like family calendar apps,

things like that.

>> Yeah.

>> Um but this is just 10 seconds and it's

way better than what I was able to do.

>> Yeah. Yeah. Yeah, the cloud code thing

like was obviously the shift in coding

and you know our our most sophisticated

engineers you know were doing whatever

20% of their code you know with with

with AI to like you know whatever 90

plus% and so now I think everything you

described in what you built with cloud

code or codec

>> is still kind of reactive

>> in a way right like it's it's still you

know it's like summarizers yeah

preparation it's all like knowledge

enhancing which is part of your job, but

it's not actually doing the work for

you.

>> Yeah. And now you have a Groc bot that

says, "What are the recommended

actions?" Yes. Exactly.

>> Based on everything the other bots have

learned today.

>> Yeah.

>> What recommendations do you have for me

today? And that for sure is like

>> and it it was so easy to build. Um I now

have it. So I'm I'm like horse racing

all these which is like I have uh uh

Crockbot doing it, Codeex doing it. All

the like action taking for just I want

to know

>> make me better at my job. Look at

everything I do. Give me give me

recommended automations you can do. I

have Town doing it as well which is one

of our companies very good at it.

>> Um but and we're like kind of on the

bleeding edge of trying to do this

stuff.

>> Just wait till everyone does this stuff

>> and then and then when we actually click

like yes go just automate this.

>> Yeah. It feels like that's sort of

endless token

>> and but I do we should acknowledge like

the the history of financial markets,

>> you know, dating kind of back to like

the South Sea bubble is whenever you get

this transformational new technology.

Um, I actually went on a podcast, I said

I thought the South Sea bubble was

connected to like the invention of

longitude and the ability to sell. Turns

out it was not. [laughter]

It was just it was kind of like a more

of a tulip episode. But like every time

you've had a real, you know, profound

new technology, you know, whether it's

the automobile, the TV, the radio,

internet, the PC, um, railroads,

>> steel mills, you get a bubble because

the markets get really excited

>> and they get ahead of themselves. Things

get overvalued. That overval

overvaluation

leads to an overbuild. And then

particularly if you're funding it with

debt um and and even today a majority of

this is still being funded out of

operating cash flow which I think is

really helpful. Um you know debt funded

built buildouts they demand immediate

ROI not an ROI in three years.

>> Yeah. You can't be off in the time. You

can't be off off on the time, but I'm

just more, you know, like I um, you

know, I talked to Jazz about how Watson

wafers Jazz I guess and Patrick Watson

wafers are these fundamental constraints

and just that the buildout is so big and

we're so early that we are

it's like impacting the raw productive

capacity of so many industries. you

know, now you know, everybody in

everybody in copper, there's like an AI

thesis and like we're going to have to

like think about it to like fill the,

>> you know, if if

>> 10% of what we just talked about comes

true, you know, we're in this acute

shortage with, I don't know, several

million people are driving a crazy

global compute shortage. What happens

when that's 500 million? And you know,

how many copper mines do we need to

build to like support this? Yeah,

>> it's kind of a wild thought. And so like

these fundamental constraints, I think,

are slowing us down.

>> And I

>> and I think that's good. I actually

think that's good for society. And I

would now say rates and regulation, you

know, real rates are going up. Yes.

>> And it just is what it is, which makes

sense because we're like investing a

lot. So it makes sense um that real

rates are going up. And then regulation,

man. It's it is like I'm kind of shocked

at what's happening in America.

>> We're in a really bad place.

>> Yeah. [clears throat]

And just, you know, I had this exchange

with with um Schulto for from Anthropic

and and and Daario on X last weekend.

You know, Daario said, "Hey, I don't

think I've been negative. You know, I've

written I've written two essays. One was

positive, one was negative." So being

50% negative and particularly when it's

like a terrifying negative

>> like an existential

>> an existential negative everybody might

be out of out of a job like that Eleazar

Yukowski guy says if we build it

everyone will die and it's like how

about if we build it like we're going to

cure cancer we're all going to live

forever. I thought one of the best

things Dario said was like what we need

to do is stop talking about curing

cancer and actually cure cancer.

>> Actually cure cancer and actually make

breakthroughs like

>> but just somebody like that my favorite

line in the Bible is the truth shall set

you free.

>> Yes. But the only person who can the

only group that can tell the AI

industry's truth is the AI industry.

They need to just start telling the

truth. Hey when we Okay, you're opposed

to data centers. Well, you know what?

It's probably the best thing that has

ever happened to workingclass Americans.

>> Yeah, exactly.

>> You know, it's like going to college

might be significantly NPV negative now

because you can go learn how to be an

electrician, a plumber, an HVAC tech,

and make ungodly amounts of money. Yeah.

>> So, this has been amazing for

working-class Americans. We now have a

lot of data that particularly with

behind the meter power generation, when

a data center goes in,

it transforms a town. like tax revenue,

it doesn't double. It like 10xes and it

is re revitalizing all of these like

dying small towns all over America. And

listen, we're getting we're getting much

better at addressing the environ

environmental stuff. Generally, they use

natural gas, which is a pretty clean

fuel.

>> The the water the water consumption

thing is totally debunked. It's totally

debunked. Yeah.

>> It's nothing. It's nothing. So these are

like really really really good and

they're having a really positive impact

on the world. That's without even

considering things like curing cancer,

but somebody needs to tell that story.

>> It's now and and I think the problem

with it now is like the burden of proof

is on not curing cancer, but actually

delivering some real tangible everyday

American benefits beyond using chat, you

know, or Grock to like answer your

questions or substitute

>> for a search engine, right? It it does

feel like we're pretty close to that. Um

yeah, it does. And and by the way, like

one of the things that I think has been

correct but ineffective is this idea

that we need to stay ahead of China.

>> Like it's like it is true. Like I'm very

much like I'm a patriot. Like I believe

that. But it's way too abstract. Yeah.

The abstract for the average American.

Like

>> nobody's worried about China invading

America.

>> Yeah. Exactly. Like they ocean is really

big.

>> Yeah. like affordability and like how is

this going to change my life for the

better or worse, right? And so

>> I think there's a pretty immediate

impact you could feel like I my favorite

is, you know, Lowden County, Virginia,

which is like the highest uh highest per

capita income uh zip code in the US or

county in the US

>> and it has the highest density of data

centers.

>> Yeah.

>> And they and they make a tremendous

amount of tax revenue from data centers.

Like we should we should do this

everywhere.

>> Yeah. It was actually very funny. a

someone very opposed to data centers

said, "Oh, you're for data centers. I'd

like to see them put in the highest

income zip code and the highest, you

know, income county." And they're like,

"Actually, the highest income zip code

in America and the highest income county

has the highest per capita concentration

of data centers." So, we've done that

[laughter]

>> and it worked out really well.

>> Yeah. But, you know, hey, don't bother

me with the details. I'm on to my next

talking point.

>> That's good. That's good.

>> And all those talking points, it's

tragic. Like there is an organized CCP

funded campaign. I think against data

centers here in America like I think a

lot of it gets laundered through Tik Tok

and it's just tragic because the other

thing that's happening is this is

re-industrializing America. The

combination of having the straight of

foremost closed which is amazing for

America. You know natural gas here is

two or three bucks.

>> It's now 25 bucks

>> in Europe and Asia or 20 bucks or

whatever it is. And natural gas is an

you know important input to the cost of

electricity which is an important input

to almost all manufacturing processes.

And so we have a huge cost advantage for

that basic input now.

>> And you have that happening and you have

this kind of data center boom happening.

We are re-industrializing America. And

it's awesome. This is what everyone in

both parties has wanted for a long time.

>> Yeah. Exactly.

>> Like bring industry back. small towns

that were left behind by the steel mills

closing. Well, data centers are bringing

them back.

>> Yeah. But somebody has to tell that

truth. I mean, I try to do it on every

podcast, but like I'm just a dude.

>> Yeah. And like your audience is the tech

audience that that already believes

you're you're preaching the choir, if

you will. Um, but yeah, the story the

story I met Meta is probably doing the

best job of telling that story, I would

think.

>> Yeah, it seems.

>> You know, and I think one reason it's

really wired into Meta's DNA. So, one of

the first things they started doing as a

public company I don't remember if it

was on their first attorney's call, but

Cheryl would run through Cheryl Samberg

would run through 10 or 15 very specific

small businesses that had started using

Meta's advertising products and the

impact it had on that business.

>> Yeah. you know, this cake bakery in De

Moines started, you know, worked with

Meta and, you know, it was it was it was

two women who were single mothers

working by themselves and now they have

15 locations. They employ 50 people.

>> Yeah.

>> And this has been amazing for De Moine

and it's been transformative for them.

>> Yeah.

>> And they would just run through that

every time. And and I do think the

entire AI industry um like I'd love to

see, you know, everybody SpaceX,

Enthropic, OpenAI, Google, Meta say,

"Hey,

>> here are real businesses and real

Americans and like either name the

business or get permission to if you can

name the American or anonymize it." This

is a really positive thing it did it it

had on their life.

>> Already very tangible. Yeah.

>> Yeah. Same. Nvidia, AMD, Broadcom, all

of them.

>> Yeah. just run through specifics because

the truth will set you free but only if

you tell it.

>> Yeah. Exactly. Exactly. Yeah. So it

seems more likely than given that fact

pattern if you go back to just the sort

of macro situation that we're in that we

we underbuild on the supply side.

>> Oh yeah. For for like through 28. And

and by the way like there's no capacity

available with all the forecast builds

that will happen through 28 which are

probably now going to be delayed given

the political dynamics they have. So,

um,

>> everybody's worried about over supply.

I'm like more worried about

>> massive massively under supply. Yeah,

exactly. Which, which Okay. So, then if

that's the scenario,

like you could see a scenario where you

see, you know, big price increases

actually to access the intelligence.

Yeah.

>> Which is the opposite direction of where

everybody thinks this is going to go.

>> Yeah. Well, Dorcash had a wild point. I

forget what it was, but he was positing

>> um I forget the

>> like the cost of a token could go up 10x

or something like that. Yes. Yeah,

>> which is crazy, but like we do live in a

supply demand world.

>> Like it's conceivable if the demand goes

massively. And by the way, the whole

premise of this that's happening so far

is that there's a massive amount of

consumer or user surplus being

generated, right? So like why do people

select the frontier tokens when they

could use the cheaper tokens to do most

tasks? There's many reasons why, but

like the biggest one is because there's

a tremendous amount of surplus even if

you're using the frontier tokens, right?

Absolutely. And so yeah, what happens if

there's like a massive supply shortage?

Well, I think that would be the, you

know, kind of funny the consequence of

like the these like data center

degrowthers

um

may be like real compute inequality

where big companies and wealthy people

can afford compute and then you know two

years from now they'll be on about that

and it's like well that happened because

of you. Yeah.

>> You know that happened because you

wouldn't let us build data centers.

>> Yeah. And by the way, we've we've seen

this, right? Like the path to a lowcost

product delivered to consumers in a mass

market is advertising. It takes a long

time to build an advertising business.

>> Yeah.

>> Um as we've seen with all the, you know,

consumer internet businesses that we've

invested in over the years.

>> Um and so there may be a disconnect in

the period where you can't actually

offer that.

>> Yeah.

>> And that would be a terrible outcome.

>> That'd be a terrible outcome for the

world. Nobody wants that. So we need to

build a lot of data centers.

>> Yeah. Exactly. Exactly. Yeah. like a

compute in inequality like future that's

that's not a good that's not a good

future for anyone which is another

reason open source is so important

[gasps] and just one of the things um

you know I you know I had uh Grock make

me make me like a meme of that like

three-headed dragon and one of the heads

is like kind of confused about like all

of the really like stupid

>> bearish AI narratives but people have

this idea that open- source tokens are

free they're

And it's like it takes the exact same

amount of compute.

>> Yeah.

>> All else equal to make an open source

token as a you know Frontier token for a

comparably sized model. Now there's a

lot of nuances there but that's broadly

true.

>> It's just a question of what are the

margins that are charged on top of that.

And even then, the Kimmy license,

something that I don't think a lot of

people appreciate is the Kimmy license

stipulates a 30% um share of any

revenue.

>> Yeah. Yeah. Yeah.

>> So like Kimmy has taken a 30% cut of all

the revenue generated on its and this is

because it's open weights, not open

source.

>> Yeah. Exactly. Yeah.

>> Yeah. But it's also extremely token

hungry too, right? So it's more it's

it's far even we're talking on a token

basis, but on a task basis, it's far

more inefficient. So it's very costly.

>> Yeah. And I just always like Jensen,

he's a great patriot, great American.

Like we're so lucky to have we're lucky

to have him and Elon like and I think

like you know kind of when the when the

history of the 21st centurion 21st

century is written you know there was

like the Victorian age I think this will

be like the age of Elon and Jensen.

>> Yeah. because they have they they are

fundamentally altering kind of like the

fabric of human society and civilization

with AI SpaceX making humanity

multilanetary Starlink you know bringing

lowcost internet access to the poorest

communities in the world which is

amazing um which is you know something

that people don't talk about but it's

like an amazing you know you talked

about consumer surplus that is an

amazing surplus

>> there was never there there was never

going to be an economic case to build

internet access in those places because

of the cost

>> and the willingness to pay and now you

could

>> without and any incremental internet

capacity like is not going to be built

in a traditional sense on Earth. It's

going to come from space and so like

that is a huge that is a huge unlock. I

agree.

>> It's a good thing but like we're you

know we're like you know we should we

should all be grateful for them because

I do think that you know they're you the

they're making the future as exciting

and inspiring as possible. say we are in

this supply crunch. Um it's so funny

when whenever I talk about SpaceX and

it's it's obviously near and dear to

both our hearts. Um you know I I say

like first of all the orbital data

center stuff it's not like big buildings

in space like it's helpful to actually

think of it's like the size of an

airplane.

>> People are picturing like the Death Star

like or the Pentagon floating around in

space. That's not what it is at all.

>> Yeah. It's a It's you know whatever the

size of an airplane, right? Rack of 72

whatever chips.

>> Yeah. It's it's like five of us standing

together is kind of roughly

>> is like the wings

solar wings.

>> Yeah.

>> And then you keep it in a suns

synchronous orbit.

>> So you have the radiator always in the

shadow of the rack.

>> That's how you cool it.

>> And it's I like I can't it's very hard

for me to engage. you know, there's all

these people on X and they're like, I am

a physics PhD and I this is impossible.

Um, [laughter]

and actually there's there's there's a

friend who's another investor who

actually is a physics PhD who had many

um arguments with him and he's like, I

am a PhD and this is impossible. And

then he goes to the SpaceX day and you

know he talks to the SpaceX engineers.

He's like, well, I was wrong. And so

like if let's say you're an astrophysics

PhD, you are brilliant. You're hanging

100 IQ points on me. Have you thought

about this for an hour? Have you thought

about it for 10 hours? Have you thought

about for five hours? Cuz you have

10,000 of the world's smartest engineers

at SpaceX who've thought about this each

for hundreds if not thousands of hours.

And the sum of that working with like

very sophisticated, you know,

engineering tools is it's a solved

problem. And in their minds, it's

dramatically simpler and easier.

>> Yeah.

>> Than a Starlink satellite cuz a Starlink

has to have the phased arrays and move

around.

>> I think it's like So, okay. So, assume

that you're right. I say it's like

physics. There's not a physics reason

why this can't work. Costwise, it seems

really imposing, but kind of the history

of the Elon companies is the cost curve

gets dramatically better. Like when we

first invested in SpaceX, you know,

Starlink like was not commercially

available and like we had all these

questions about how the economics would

proceed over time. The same on the

launch side, the same with the Model 3.

Like I I I just have to think that that

will get solved paired with the fact

that we're going to have massive under

supply self-inflicted on Earth.

>> Uh it feels clear to me at a minimum it

will be swing capacity.

>> Yeah.

>> And you know in the fullness of time

maybe it will be larger.

>> Well no it's really simple like if we

use 50 and it is the people the question

people should be asking about orbital

compute which is the one SpaceX is

focused on is Starship reusability.

>> Yes. Because the math is like let's

let's just say it's 50 billion a gig and

let's just say 35 of that is it. Yep. So

that's the same and maybe it grows a

little because it's it's going into

space. The rest is power, cooling,

labor, all sorts of things that you

don't need in space because you have the

so you have the solar panel and the big

radiator. Um [clears throat]

and that call that's 15 billion and

that's probably inflationary here on

Earth.

>> Yeah. Because [clears throat] labor

fundamentally feeds into that. We just

talked about what's happening to, you

know, electrician. Um,

>> yeah. Comp. Yeah.

>> Yeah. Electrician

>> materials are all going to go.

>> Yeah. All of it. Yeah. We're going to

have Yeah. We're going to run out of co,

you know, we're we're the the copper

bulls are, you know, focused on like

copper shortages. All of it.

>> Yeah. So that 15 billion is

inflationary.

And so what you have to compare it to is

the cost of launch. And with Starship

reusability, that goes to under a

billion. So the economics just instantly

flip. Now, you're always going to train

on Earth. There will always be

advantages to having, you know, GPUs

right next to each other. Like there

are, you know, speed of light

limitations are a real thing. Latency

matters. So, data centers on Earth,

they're not going anywhere. I think

they're going to continue to be very,

very valuable. But an increasing

fraction of the world's compute is going

to be in orbit. And you know, Elon said

that he and Jensen have co-designed a

Reuben rack

>> and they're it's gonna launch in the

fourth quarter of 27.

>> Yeah.

>> And let's just say let's just say he's

off by two quarters.

>> Yeah.

>> I mean, that's that's 2028.

>> Yeah. That's still okay. That's pretty

soon

>> that, you know, as Brad Gersonner says,

like nobody's really paying attention to

this and it's like kind of happening in

plain sight. And it kind of to me solves

for something, you know, mids single

just billions today,

>> which by the way, you know, is like

that's just like keeping share constant.

>> Yeah. Exactly.

>> You know, of like what's happening with

>> not presumably taking any share on on

Grockbot.

>> Yeah. Yeah. From from three billion. And

by the way, man, I would just I'd

probably take the over with Grockbot.

Yeah.

>> I bet it's like

>> changing by the day just based on my own

usage and the number of people who are

hitting their usage limits. And then you

are starting to get from you know

Grockbot like hey we're servers are

overloaded every once in a while and

like they have a lot of compute. Um so

it's just like okay you don't want to

debate orbital data centers

>> no problem. Well like Starlink mobile

like they have a pretty clear credible

plan

>> for how that's going to work and that

you know wireless is you know call it

another 8 900 billion of revenue that

they address. So your yeah your mobile

plus your broadband whatever it's call

it like close to two trillion of a

market

>> and [snorts] then you have a really

rapidly growing AI AR base.

>> Yeah. AI AR you've got the cloud you

know the sort of the cloud business.

>> Yeah. Um so I don't think great you're

an orbital computic no problem. It

doesn't matter.

>> Yeah. Exactly.

>> We don't even need to. We could just

look at things that are happening today

with terrestrial compute, with cursor,

with Grock, with Grockbot. By the way, I

think X ads are, you know, we have

telemetry.

>> They're also growing.

>> You know, I would expect at some point

you'll have like a Starlink

Grockbot

um Xadvertising [clears throat]

bundle. You know, kind of one of the

ways Google built their cloud business

as they bundled it with ads and like,

hey, we're, you know, maybe you're

bundling the ads with AI, but why not do

that?

>> Yeah. Yeah. I actually like the AI

position that they're in because it's

like heads you win, tails you win in the

sense that their first party business is

growing very fast and they they caught

up to the frontier like very quickly.

Yeah.

>> Um and so they've made the very

aggressive compute investments to enable

that first party work.

>> Um and that's the kind of heads you win

and like tails you win. Say they

overbuilt their capacity for what they

need for inference or training. they

have a very compelling sub six month

payback on the compute side um you know

with like massive scarcity supply and so

I think that's a really good setup

>> and there was a bare case that hey okay

well in in a in the open AI anth

anthropic maximalist view where they're

the only two companies and they're

designing their own chips then like

where what's the room for anyone else

well like I don't think they're going to

have a reusable starship and multiple

spaceports anytime soon and if the

economics of computer such that orbital

is where it makes sense increasingly

going forward because Starship should be

deflationary, you know, terrestrial

cooling, you know, power should be

inflationary. Well, like even in in a

world where

they fumble the ball with their first

party AI applications, like they do

still have

>> they're a massive infrastructure

business.

>> Yeah. Yeah. I I'm I'm so fired up about

the uh the Starbase Louisiana. Uh

>> Oh, yeah.

>> I can't wait to visit, man.

>> So cool. Yes.

>> Uh I was reading about it last night and

uh yeah, it's sort of like it's now the

they now have the infrastructure for you

know thousands of launches a year.

>> Yeah. And eventually I think you will

see like these star bases in multiple

places, multiple coasts all over the

world.

>> Yeah.

>> Like you know at some point you'll

probably see one somewhere in the Middle

East. You'll see

>> you know whatever European country is

like the least bureaucratic at the time.

You'll see one there. You know, you'll

for I think you'll see probably one in,

you know, whether it's Japan, South

Korea, who knows?

>> Yeah. Yeah. Yeah. Yeah. Yeah. It's

pretty exciting.

>> Yeah.

>> Yeah. The uh the capability to do to

call it, you know, whatever 5,000

launches a year, like that feels very

futuristic.

>> Yeah. I mean, it's wild. And I do think

a distinction that um you know, SpaceX

really tried to kind of hammer home

during their their IPO is there's a

difference between reusability and and

China. They did catch kind of a rocket

using this um it was actually kind of

ironic. It was this kind of juryrigged

system of kind of wires. Yeah.

>> That had actually been suggested on the

SpaceX subreddit.

>> Yes.

>> Like seven or eight or n or no no it was

before they landed the first Falcon. So

it's like more than 10 years ago

>> and like China's clearly paying close

attention to the SpaceX subre subreddit.

But that's very different catching that

thing from what they're trying to do

with Starship where you know the uh the

booster gets caught with the things and

then it gets moved and then the Starship

gets caught and then it gets stacked, it

gets fueled and just sent right back.

Yeah. Two a day. Two a day per pad.

>> Like those numbers add up pretty fast.

>> And there and I do think I think they're

engineering the pads for more than two a

day if I

>> Yeah. I think that's a conservative I

think that's a conservative assumption.

Yeah.

>> Yeah. Um but I mean

>> Yeah. What's the Okay, so SpaceX, like

again, you and I have talked a ton about

SpaceX.

What's like the most futuristic thing

that you think about with SpaceX? Like

the 10-year Okay, so you and I were at

this conference together and there was

this whole debate about um among a small

group of public investors of like what's

going to be the the first 10 trillion

company. And uh I think what you said

was like I have no idea, but I know

which one's going to be the first 20

trillion dollar company. Uh, so like

what's the most futuristic like product

or market or technology thing about

SpaceX that that you can think of?

>> Look, I mean this sounds crazy, but

asteroid mining is going to be a very

real thing. We're going to capture, you

know, there's asteroid psyche. It has

more gold, silver, platinum, you know,

every precious metal in it that exists

in the Earth's crust.

At some point, particularly with

Starship, you will be, you know, and we

may need that um lunar base to make this

happen. You'll be able to cap capture

these asteroids. You'll bring them into

a stable kind of geocynchronous orbit

over some, you know, Americanowned

atal in the middle of the Pacific. Um,

you know, no humans within whatever 50

miles. you'll, you know, you can imagine

like Optimus robots, you know, um doing

doing the work. Yeah.

>> Yeah. Doing the work. Um and then, you

know, delivery to Earth is free and for

sure some of it's going to burn up,

>> but I think that's going to happen. And

[clears throat] I always think um

Jeff Bezos said something very

interesting. He said, "I think in the

future Earth is going to be zoned

residential." And you know, somebody

asked him, this is like 15 years ago,

what do you mean by that? He's like all

heavy industry will take place in outer

space. And then this addresses the

pollution concerns. It addresses

everything.

>> You know, people always get like really

worried about, oh, you know, we still be

able to see the stars.

>> And it's just like I think it's hard for

like the human mind to understand how

big space is, how big outer space is,

>> you know, it's

>> we don't have to worry so much about

emissions up there. Yeah.

>> Yeah. Yeah. So I think that is um

that's probably the most futuristic

thing.

>> But in terms of an economic application,

but it does um [clears throat]

I mean

I I do think in the next few years

you're going to have a fleet of

starships land on Mars. Next few years I

mean I don't know let's just say at the

outside this is eight years away.

>> Yeah. They're going to land on Mars.

Going to have like, you know, a little

ramp's going to come out of the PEZ

dispenser and it's going to be a

modified Starship, the Mars colonial

transporter, and it's going to be wild.

You're going to have Optimus robots

holding American flags like walk down

and then, you know, they're going to

pull out a bunch of solar panels and

batteries and racks of compute and

they're going to set all of that up.

they'll be dropping Starlinks,

you know, and maybe the orbital

mechanics don't allow this, but I think,

you know, they'll they will figure out a

way to have, you know, capacity. So,

just think how crazy it is to watch like

the views from Pathfinder,

>> you know, or, you know, whatever these

different, you know, Mars um

>> rovers and stuff,

>> rovers are and like, you know, 4K video

through Optimus robots all over Mars and

then after that there will be humans

>> who can inhabit it. Yeah. Yeah. Yeah.

That is crazy to think about.

>> And that that's going to be an amazing

moment for America.

>> Yeah.

>> Oh, I mean, think about the moon

landing. [laughter]

>> This is a little bit bigger. Yeah.

>> Yeah.

>> Yeah.

>> Um, so that seems cool. Um,

[clears throat]

>> that's a good one. That's That's a good

That's a good one. Yeah. Not a lot of

chatter about that one out there. Yeah.

But I think it's highly likely to

happen.

>> Yeah. Yeah. Yeah. So, you mentioned

Microsoft.

>> Yeah. and the bet that they made which

is like a little bit of you know like

Apple's the extreme kind of bet against

the future kind of bet they made and

like Microsoft is kind of a gradient of

that.

>> Yeah.

>> Like what's your what's your outlook for

their decisions?

>> Well, I do think the world has gotten a

lot friendlier for their strategy. Um

you know they clearly tried to make a

frontier model. They failed.

>> Yeah.

>> You know Satia said we're going to have

our own models that are very

competitive. Like I think he said that

18 months ago. they don't have their own

models that are competitive, but what

you're seeing with um I think the future

is an ensemble of models. You know,

there's a paro curve. No one model is

going to be the best at everything. And

I think the future for certainly, you

know, kind of the global, you know,

10,000 biggest companies is you're going

to take whatever the best open source

model is, I think probably in the in the

very near near future that's going to be

an NVIDIA model.

>> Yep. The labs making AS6 create very

interesting

>> incentives for to get into each other's

business

>> incentives for Jensen and everybody's

well oh in a world where open source

wins who funds the training well this

the chip companies could fund the

training yeah

>> it's trivial to do a 50 to$100 billion

training run uh you know for Jensen and

maybe soon I do wonder if this is kind

of Google's like super long-term play

like they they they seem to like maybe

have opted out of the frontier race for

now um We're going to monetize our

compute at high rates and we're going to

um sell TPUs externally, but that

generates so much cash flow and open

source is getting closer and closer and

closer to the frontier. And it just may

be the winner is ultimately just who has

kind of the most cash flow to to fund

these big training runs. But I do think

you're going to see American open source

led by led by Nvidia get really close to

the frontier like they paid that

poolside acquisition was made for a

reason. Poolside actually had a lot of

really good American open source talent.

I they're they're you know they're doing

a lot of smart things but that that is

really good for Microsoft and at some

level almost every application software

company because what you can do now is

you can take a base model and Neatron to

date has not had a lot of post-raining.

It's kind of been a good pre-trained

model that you could do with what you

want. So if you take a really good

pre-trained base model and then instead

of sharing your own kind of enterprise

context that's truly your IP that's

truly the value you know of your company

is like you know the context embedded in

all of your data and like sharing that

with a frontier lab you know that may be

hazardous for your financial health.

Yeah, certainly with like the shift in

the ZDR policy like Yes.

>> Yes. And so you take a really capable

open source model and you do a lot of RL

and supervised fine-tuning on your own

data. So you own it and it's your model.

>> Yeah.

>> And then if intelligence is like a super

important input into your business, you

want to own and control your

intelligence, its capabilities, its

cost. And then what we've seen from a

lot of companies and you know Grockbot

my understanding is you know I think

it's Gemini 3.7 flash

>> um Grock 4.6

>> and some Opus

>> y

>> and what you and behind a router

>> and you will um

>> and I'm sure Elon is very focused on

having it all grow as soon as possible.

>> Yeah. Yeah. Of course. Um but I think

what you'll see these companies do is

they'll have their own model on their

data and it will work with one or two

other frontier models. Um not not you

know necessarily but just you know

checking each other it'll be kind of

transparent to you the the most frontier

for planning and then have execution run

by everything else that's lower costed.

Yeah, absolutely. And so I think that

feels like a very likely future to me.

And that's a that is a much Microsoft

friendlier future than one in which

there's just only two dominant frontier

models. And it certainly looks like

there's going to be at least three with

Grock. I do think you got to give Meta a

lot of credit.

>> They've done a great job.

>> Yeah. And I mean they were out of the

game and they got back in the game. And

it's just it's kind of amazing. Who

could have imagined a year ago, you

know, when it was like Gemini was

ascendant exactly that this is the

scenario

>> Gemini wouldn't even be in the

conversation

>> and Muse and Meta would be significantly

ahead of them from a capability

perspective.

>> Um, so it's just, you know, this is

>> kind of like the highest stakes game of

like corporate chess ever played.

>> And, you know, people, you know, some

people have made bad moves, they've made

good moves. You seem some people come

out of the game, others come back in.

Um, but a future where that future where

it's a, you know, I don't know if we're

going to call it multimodel, a hybrid

model, you I don't know what terminology

the world is going to settle on, but I

think that's the future.

>> Yeah.

>> And I'm actually surprised. I think the

best broad instantiation of that today

outside of Grockbot, outside of cursor,

outside of you know like Harvey's done

some cool things with that

>> where they've done it is actually just

the Fireworks Nexus product.

>> Yeah.

>> Where you can Yeah. You can

>> choose your frontier model.

Let us take whatever open source model

you want, RL it for you, for your data

for Gold Coleman Sachs, for Morgan

Stanley, for JP Morgan, for Fidelity,

for A16Z. You have all your own data.

you control your intelligence and we

make it transparent behind a router.

>> Yeah,

>> I think that is like a very plausible

future and that's clearly what um Lynn

from Fireworks, she was the first one to

say it and then Alex Karp and Satia,

they both kind of like

>> Yeah, they've they've taken their own

version of it. Yeah.

>> Yeah. But you know, Satia's essay of

specialized intelligence, like I think

it's very plausible,

>> but this stuff is really hard to do.

Like that that sounds easy.

>> I was it sounds easy to describe like

the way I describe it to people is like

who gets to be the abstraction layer to

the organization and the users with

intel like of of intelligence. It's like

the most whatever vi after space or

position that you could imagine in

business like in the history of

business.

>> Yeah, for sure.

>> Right. I think it's like the answer is

and again.

>> Yeah. Yes. And for sure it's Yeah. Who's

the arbiter of intelligence for global

enterprises and probably consumers? I

was a retail analyst and um

you know everybody kind of thinks

running one of these big chains is easy

and there's a lot into it and it's like

well it's really easy to start an

American retailer in any category cuz

America's so big it's worth over $50

billion almost any category.

>> Yeah. All you have to be able to do is

have a fleet of a thousand stores in 50

different states that have very

different climates, consumer

preferences.

You need to have them stocked with the

right products at the right time for

that region at the right prices. They

need to be staffed by friendly and

knowledgeable employees who don't steal

from you

>> who turn over at 100% a year.

>> Turn over at least 100% a year. The

stores need to be clean and well lit.

And if you can do that,

presto, $50 billion dollars. Yeah.

>> And like in the history of American

business, like you can I mean it's more

than one hand, but you don't have to go

through many.

>> Yeah.

>> It's really hard to do. And

>> having that abstraction layer, having it

work, having it seamless is, I think,

way harder to do than people think. And

I do think what something I think is

very interesting about cursor, I'd love

your opinion on this is like everybody

else in the lab space, you know, had

this like

we're creating a digital deity, you

know, and AGI and ASI like we're

>> and the Curser guys were just like we

want to make great product.

>> Yes. Exactly. in a in a strange way o of

everybody at the frontier. Um probably

Kerser and it was the most product

focused.

>> Yes.

>> Yeah. I'd say in you know now they're

part of SpaceX but that suits Elon and

his mindset really really well.

>> Yeah.

>> Let's make it an engineering problem.

You know create the model factory and

then we need to have a really good

product.

>> Yeah.

>> You know the you know the the the Tesla

cars they're amazing. I mean it's I

don't I don't know if you drive one but

it drives

>> everywhere. Yeah. Yeah. But like the

what cursor figured out is

>> they're they had I would say a similar

instate vision as what those others guys

had.

>> It was just a different path to get

there and it's sort of like a practical

meet the customer with what with where

they are meet the technology where it

is.

>> Um and I think you know they'll sort of

they have already demonstrated that they

kind of led their way up into autonomy

from from that starting point.

um coding is unique compared to

everything else in knowledge work. This

this would be like in support of the

point that Microsoft is in a good

position

>> because it is verifiable and perfectly

documented and like nothing else in

enterprise

>> is verifiable and perfectly documented

and so it will be messy like that that

leads you to a good you know bullcase

for something like Microsoft that

abstraction layer

>> if they execute but it's really really

hard to make it really simple for

>> oh you know click my co-pilot link to

all my stuff train a model yeah

>> on our data

convince me that you're not going to

share it with anyone else and then put

it behind a router that's seamless for

me and continuously upgrade that open

source model.

>> Yeah. It's not just some middleware like

it's very hard to do. Yeah. And and by

the way, they're going to compete

they're going to be competing with not

only the labs to be that abstraction

layer

>> but data bricks. So like

>> Palunteer um the inference the inference

providers um the application companies

right so like Harvey has done an

incredible job of this and you know like

legal has sort of in take off and um and

and I think they can see the future of

how to be that abstraction layer um and

do the work um but like legal is also

unique because it's very documented and

it's somewhat verifiable tax we'll see

that we see see things like that but

like the the one and a half billion the

really appealing brought by is going to

be very messy to go get.

>> Yeah. Although I do always think and um

you know I think probably in their heart

of hearts Harvey and Lora think oh if we

solve this

>> we could be that abstraction layer for

everyone.

>> I think probably in their heart of

hearts cognition thinks something like

that too.

>> I think everybody thinks and by the way

there's like massive validation of the

category because Kirkland Ellis said

>> we're going to spend 500 million bucks

to build this ourselves. Like first of

all you know like good luck that's going

to be very hard. Yes.

>> Um, but that actually tells you that the

pie is really big, right? Huge.

>> Yeah, it's massive.

>> And that's it's and you know, just um

and I'm sure they have a very smart head

of a head of AI, but it's not like a

$500 million onetime build. That model

has to be continuously updated,

switching out the base model. Then all

of that has to happen transparently. But

I think you're going to have this huge

collision between,

you know, products like Fireworks Nexus,

these legal agents, coding agents, big

companies like Microsoft,

>> Data Bricks,

>> Data Bricks, Snowflake coming up,

>> you know, for sure. Um, you know,

Salesforce, I think, is going to, you

know, Salesforce and Workday and all

these companies. This is like

everybody's going to go after it. It's

just going to come down to who executes

the best and

>> and this is just you know who has the

lowest costs.

>> Yes, exactly.

>> But it's going to be very hard I think

over time unless you're re if you're not

vert vertically integrated you have to

be so good to emerge as that abstraction

layer.

>> Yeah. Yeah. To be the lowcost provider

very hard

>> because yeah we you're just simply not

going to be the lowcost provider if

you're not vertically integrated if you

don't own your own compute over the very

long long term. Um and you know it's

that's another reason like I um you know

I increasingly look at these

hyperscalers on EV to net PP&E.

>> Yes.

>> Because net PP& is compute and that is

just what the market thinks you're going

to monetize your fleet of compute at and

you can kind of look at them and there's

some pretty obvious inefficiencies too.

>> Yeah. Yeah. Yeah.

>> Yeah. Kind of an AI version of price to

book.

>> Yeah. I like the price to book. Okay.

[laughter]

>> Um so okay you you mentioned Jensen. you

know, I I'd share your sentiment like

he's like carrying this industry

forward. Like tell me your thoughts on

Nvidia.

>> So, um

I think he's in a very very good

position and his strategy of being

vertically integrated but horizont

horizontally open and it's like okay

like let's just say um

you know let let's say there's some

accelerator that emerges that is really

really really really good. almost

certainly it will be better if it can

plug into and this is why like I know

you have an accelerator investment my

number one thing is if you're a

semiconductor CEO the only thing you

should ever say is thank you Jensen

thank you for creating this opportunity

thank you how can we work with you we

want to enable you sure we're going to

compete with you on the edges

>> but you know my rule of thumb for

accelerators every 1% share today is

probably worth a hundred billion Yes.

>> So there's no need to go head on with

Nvidia.

>> Yeah.

>> Um just pick a niche, get your 1%. Make

sure that you know

>> is very big.

>> He has he has nine chips. Yeah.

>> Um you know he's got he's got multiple

flavors of accelerators. He's got CPUs.

>> He's got you know Ethernet switches. He

has two kinds of GPUs. You know he's got

you know we've gone from just um scale

out networking being a thing. We have

scale up scale out scale across now

scale in.

>> Yeah. So just try to find a way to plug

into his ecosystem.

>> By the way, this is not foreign. Like

his biggest customers all have competing

products with various of those nine

chips.

>> Yeah. And just try to find a way to plug

in, but just be nice to him. Be nice. Be

nice. It's all personal. Yeah. You know,

and it's just like sometimes like, you

know, you hear some of these and it's

like, have you ever seen game tape of

the Chicago Bulls when Jordan was is,

you know, it's game 50 of the season.

>> Yeah.

>> And he's a little bored.

>> Yeah.

>> And the Bulls are down cuz, you know,

they're up eight games. You know,

they're up eight games over the number

two person in their conference.

>> And he's a little bored. And then

somebody

>> somebody talks

>> Somebody who's you who's who's kind of

young decides, I'm going to talk to

him because we're beating him. And then

he just looks

>> and it's like

>> and it's like

>> it's the best. Those are my favorite.

>> It's amazing. Yeah. Yeah. You We've all

seen, you know, whatever the last dance.

>> Just don't do that.

>> Yeah. Exactly.

>> You know, just just like, "Hey, Michael.

Man, I'm so happy to be on the court

with you." Like that's that's to that's

that's the move. But the reason it's

particularly important is because

Jensen's data centers are financable.

>> Yes. And it goes back to that point like

let's say it's $50 billion

um for an Nvidia data center you need a

$15 billion equity check.

>> Yeah.

>> Okay. You can finance the other 35

billion.

>> Yeah.

>> And it's not circular financing. I have

a lot of respect for the people I have

met from Blackstone and KKR and Apollo.

Yeah.

>> And they're underwriting each of those.

>> Yeah. and they finance it. And then

there's a residual value guarantee,

which as long as that residual val value

guarantee is less than the gross profit

dollars he's getting from selling the

chips into that data center,

>> it's like essentially it's super NPV

positive with very little risk for him.

>> Um, and then he, you know, he gets a

revenue share. So if you're um and his

data centers are the most financable.

>> Yes.

In I like let's just say a good case for

probably TPUs are the second most

financable.

>> It probably takes I don't know double

the equity check at least. Yeah.

>> And then the rates on the rest of it are

higher.

>> Yeah. Exactly.

>> And so cost of capital is a huge

advantage and that's why you just want

to be part of his ecosystem. And you can

see he's he's he has all these chips.

He's acquiring land power and shell

companies now matchmaking them with

offtake agreements. I think one reason

he's doing these RVGs is if he doesn't

do them, it's kind of an anthropic and

open AI dominated world because they can

pay the most for compute. He can

effectively help other people

>> compete with anthropic and open AI.

>> Yeah. In the same way that he stood up

the neo clouds in the first place. Yeah.

>> It's just democratizing compute which is

good for the world. Again, I think he's

a patriotic American. His his interests

are aligned with that though with with

with the patriotic American ones, right?

Fragmentation, right?

>> Fragmentation, no dominant AI. Exactly.

Which is which is really good because

he's like a he is a ruthless competitor.

And it's awesome that his incentives

around fragmentation of AI,

fragmentation of models, and you know,

fragmentation of power um are completely

aligned with what's good for America.

And just going back to open source, just

like I I just can't take it that people

think that Jensen is like the world's

biggest advocate for open source and

it's somehow the a giant risk to his

business.

>> Yeah, exactly. No, it's great for his

business. It's great for his business.

>> It's amazing for his business because it

means that instead of, you know, having

a 90% margin on top of a token made with

an Nvidia GPU,

>> maybe it's a 40% margin. So more of

those tokens are going to be consumed

which means you need more compute.

>> Yeah, exactly.

>> Um

>> in a supply constrained world

>> in a supply constrained world and you