The SpaceX IPO, Fable 5, AI Capex Update & Market Check w/ Gavin Baker, Andrew Fox & Clark Tang

And I think we're all pretty AIDS. And

if you're AIDL, that means we got to build a lot more compute than the world thinks and that these models are going to be a lot more valuable than people think. You combine that with their core

think. You combine that with their core business. I don't know another

business. I don't know another entrepreneur or another business that's a better bet on the future, right, than SpaceX. And so I think for most

SpaceX. And so I think for most institutional investors, it's a must buy, a must own. It's set it and forget it, right? in order to have a a real bet

it, right? in order to have a a real bet on both the space and the AI future.

All right, here we go. Early morning

Silicon Valley BG2 is back. We're

chopping it up on all things tech and markets. To do that, I have none other

markets. To do that, I have none other than GB in the house, Gavin Baker from Atties. He's brought his main guy,

Atties. He's brought his main guy, Andrew Fox. And of course, I had to

Andrew Fox. And of course, I had to draft Clark Tang into the mix, my partner, um, to talk to talk about some of the big questions of the day. You

know, how should we be thinking about the SpaceX IPO? You know, what are the big levers? There are big numbers out

big levers? There are big numbers out there for what's going to happen over the course of the next few years. So,

let's break that down a bit, help simplify it for folks. I Mythos launched yesterday. I want to talk a little bit

yesterday. I want to talk a little bit about like who's up, who's down in the race for super intelligence. Where are

we? What did we learn with the Mythos launch? and Clark was in uh in in Taiwan

launch? and Clark was in uh in in Taiwan last week um with Jensen at Computex and GTC. So, what was our takeaway there?

GTC. So, what was our takeaway there?

What's going on with GPUs, memory, where are the bottlenecks, and where do we go from here? To start everything off, um

from here? To start everything off, um you know, maybe just kick it over to you, Gavin, talking about the SpaceX IPO. The IPO is in two days. Uh you're a

IPO. The IPO is in two days. Uh you're a big shareholder. Congratulations. We're

big shareholder. Congratulations. We're

also a shareholder. Uh you know, we also be expect to be buying in the IPO. the

Wall Street Journal's reporting um you know the Goldman Sachs are both saying 160 billion in revenue in 2028. Um we

know that the IPO is $135 a share 1.77 trillion. Um so when we think about kind

trillion. Um so when we think about kind of what the big levers are, there's so many moving parts in this IPO. Um

nobody's better than you at just breaking it down, simplifying it. What

are the key levers that we ought to be thinking about that you're thinking about over the course of the next few years?

Sure. Um, so great to be here. Thank you

for having me. I thought we were going to call it BGGB, but but we need to stick with BG2. I'm in your house.

Hey, hey, subject to revision.

That's okay. That's okay. So, I think there's two big levers or variables that I think people should focus on. And, you know, I'm not going to comment on where I

think um those variables go, but one is um you guys have this chart. Um, did you did you post this on X?

I did. I did before and then we also included a new addition with uh XAI's new deals as well.

Yeah.

Yeah.

So, Clark, who I've known for many years, um, uh, made a did a great analysis here and he shows that XAI's

deal um, with Google for cloud computing generates more operating profit per gigawatt than Anthropic, then Meta, than Google, than OpenAI. uh their deal um

actually with uh Anthropic also generates probably more operating profit than anyone but um Anthropic and so you know um the your your

colleague at alttimeter Freda also she calculated a 55% IRR on Colossus one you know if you can borrow money at six seven 8% and invest in something with a 55% ARR

I'm not the most sophisticated thinker but that math maths right And so I think the most important variable, one of the two most important is how quickly they bring on terrestrial data centers.

We do know from Jensen that uh Elon brings data centers up faster than anyone. 122 days. Speed is literally

anyone. 122 days. Speed is literally cost because every day you're paying electricians and plumbers. That's cost.

Um and they're now monetizing them at arguably the highest rate.

And so I think, you know, everybody should run their own math on that, but that is a massive variable. Yes.

Um truly massive variable. The second

thing is you know we have a chart um and it's wildly out of date now. It's kind

of freaking amazing. This chart is I think is this chart from 10 days ago but um in like the 10 or 12 days since this chart since we made this chart which

shows the paro curves for opus 4.7 for coding for codeex from openai. Um and now we've had opus 4.8 date. It was already out of date and now we have fable totally

and mythos which is freaking wild at 10 days like we would have had to update the chart twice. Um but what the paro curve

chart twice. Um but what the paro curve show shows is how much intelligence you can get for a given amount of cost and I do think being all revenue will acrue to the paro curve all at least kind of

frontier model revenue will acrew to the paro curve and this is paro curve for co coding and what I think is so impressive is that um you could see in the chart

that composer 2 was paro dominant um or you know at at the lowest level of intelligence with very little training this reflects and I know you know cursor well. I think you know cursor a shitload

well. I think you know cursor a shitload better than I do. A vast amount better than I do. Um but my understanding is that cursor and enthropic have more

tokens of proprietary coding data than anyone else and each have more tokens of proprietary coding data than exist on the public internet. And so they fed

cursor fed um used Kimmy K.25 25 used their own private data did some RL some supervised fine-tuning and they got a really good model and then they spent

three weeks in the Colossus 2 cluster and they got a model that 12 days ago was parto dominant with composer 2.5.

Now it's on their own benchmark um cursor bench so maybe take it with a grain of salt but I think this just suggests that the cursor data is very

valuable for coding and when it is trained you know chinchilla optimal or beyond chinchilla optimal with reinforcement learning you know I think it suggests that XAI and SpaceX AAI has

a shot of being a real player in coding I mean I think one of the interesting things is you know we you the way you answered the question right we didn't talk about launch, right? We didn't talk about Starlink or

right? We didn't talk about Starlink or Communications. Those up until really 6

Communications. Those up until really 6 months ago were the business.

Yeah.

Right. And you know, and then we merged in X.AI and we merged in Cursor and then we announced these deals where it was very clear he was kind of building AWS right under our nose, you know, in in in

terms of this. But what I want to do is go to go to Fox. Give us the breakdown.

Three big lines of business, right?

We've got the the the communication Starlink launch business. We've got the, you know, AI compute business and then I want to come back to X.AI that you were just clicking on. But if we just go to

the core business, what do we have to assume goes right in the core business both with launch and with Starlink in order to achieve the numbers that are out there?

Yeah, sure. So, look, I think the thing that's foundational to everything is the launch business. Right.

launch business. Right.

Right. This is the kind of crown jewel of SpaceX. Um, it's something that no

of SpaceX. Um, it's something that no one else really has, notably reusability, right? and soon rapid reusability.

right? and soon rapid reusability.

Right? This is I think what you need to believe in to get to the economics in AI that make orbital compute something that's very economically attractive

outside of the idea that we are in shortage for power, shortage for chips, right? Um so I think rapid reusability

right? Um so I think rapid reusability is the main thing that we're watching for and I think most people should watch for. Mhm.

for. Mhm.

Um, you know, Elon talks about it a lot, but getting these rockets to fly at a cadence that's comparable to an airline, right? And and Gavin has used this

right? And and Gavin has used this analogy before, but um, the old rocket industry was kind of like imagine boarding a plane, flying to California, getting off the plane, the plane

explodes after. Um, so I think what

explodes after. Um, so I think what SpaceX are ultimately trying to achieve is have a Starship fly both stages, not

just the booster. um uh 30, 40, 50 times before you have to retrofit that ship.

Um and when you do that, you're advertising the cost of the vehicle over many flights, right? And that's what brings the cost down significantly. Um

but that's a really hard problem to solve.

Extremely difficult. And look, I I think the company, you know, have been loud and clear they're going to attempt to bring back the second stage, right, of Starship later this year, right?

Um and then make it reusable, you know, refly the second stage next year. Um and

from there, ramp up the cadence. But at

the end of the day, driving down the cost of launch is what enables all of these other businesses and is what makes them so attractive relative to incumbent. So how many how

many times are Starship just launch Starship 3, you know, just launched. How

many launches are, you know, do you think kind of the consensus out there is assuming, you know, two or three years from now? Like what is the launch

from now? Like what is the launch cadence? Are we launching one of these

cadence? Are we launching one of these every day? Are we launching one of these

every day? Are we launching one of these every week or every month? Like where

are we in terms of expectations?

Yeah. So look, I think expectations for now, you know, we're going from, you know, call it 160, 165 launches last year up into the high hundreds of launches in the next several years and,

you know, getting into the thousands of launches probably in the next three years thereafter.

Okay.

Um, I think the company of aspirations thousands of launches you're launching, you're doing two or three launches a day, right?

Right. And then talk to us a little bit.

What does this enable? Obviously, you

know, I'm here in Silicon Valley. I

can't even I can't even keep a call on Sand Hill Road two decades into the mobile revolution. I mean, it's the

mobile revolution. I mean, it's the craziest thing. It's like a third world.

craziest thing. It's like a third world.

It It's It's a major business problem when you're freaking out here.

It's crazy. It's crazy. Right by the Starwood dead zone. And I'm like, how can this possibly be? It's almost like it's a joke. It's the epicenter of technology in America and you can't maintain a call. Okay. So, we're all

going to switch to Starlink Mobile when it comes along cuz I don't want to lose that call on Sand Hill Road. So walk me through a little bit just again high level um it's a big portion of the

revenue growth expected in the business over the course of the next 2 to 3 years. My hunch is a lot of this is

years. My hunch is a lot of this is driven uh by uh by direct to cell connectivity. Walk me through a little

connectivity. Walk me through a little bit those economics.

Yeah. So look I it's actually interesting um the broadband business is still very early stage when you think about um the percent of households that have actually been penetrated to date. You

look at the percent of global households with Starlink, it's less than 1%. Uh,

and that's the broadband. You know, you kind of have a base terminal at your house, on your car, in your boat, um, and in airlines now as well. Um, so I actually think broadband can scale to

hundreds of millions of terminals, okay?

Hundreds of millions of users. And today

the subscriber base, hundreds of millions if if they get rapid reusability of Starship, which is really hard. um you know if if there's

really hard. um you know if if there's not competition um hundreds of millions um it's possible but maybe I always say around here it's funny I

love seeing PM and kind of analyst in this situation it's exactly what I do with Clark will say something I'll say the future is a distribution of unknown probabilities it's either more likely or less likely so give me the distribution

are we talking 20% 30% it's hilarious well no 100% the same thing and like I've watched Elon do many hard things and this is a really hard thing so I think It's reasonable to think that they're going to succeed with rapid

reusability, but just I just think it's important to acknowledge that like orbital compute, you know, Starlink, you know, Starlink V3, Starlink direct to

cell, we need we need first reusability for Starship V3 and then rapid reusability unlocks a lot of this, right? When I see when I see the models

right? When I see when I see the models that the banks are putting out there, right, in Wall Street Journal, everybody's reported on these these things have been widely leaked. they

they they largely have the revenue on connectivity so let's call it Starlink direct to sell etc going from you know let's call it 10 billion to 50 billion u

by 2028 and so I'm not asking you guys to react to you know to tell me your specific numbers but when I'm talking to Clark all I'm trying to size up is order

of magnitude do we think we can 5x the business over the course of the next three years is there enough TAM both in terms of broadband and direct to consumer and I think the of that is yes.

Yeah. Here's what I just say very simply is I have um I I travel with Starlink. Um I'm I'm a big video gamer and very consistently wherever I am in the world, Starlink is the best connection.

Yes, it's the fastest. it's lowest latency.

And I do think once they get to rapid reusability, it's also going to be they're going to have the cheapest cost per gigabyte or megabyte delivered. Um,

and better, faster, cheaper has been a winning formula. And so 50 billion,

winning formula. And so 50 billion, that's, you know, 0.3% penetration of the global telecom market. Now, maybe

there's some deflation with Starlink pricing. Um, but that's the way I'd

pricing. Um, but that's the way I'd frame it up.

I like betting on better, faster, cheap.

Um, Clark, I would say probably the biggest surprise of the last six six weeks is that Elon, you know, we talked about it on allin podcast, we called it EWS,

Elon Web Services, right? That that he struck these huge deals with Anthropic and Google. I don't even think people

and Google. I don't even think people were thinking about SpaceX in the AI compute game, right? We, if you looked at the models as of a few months ago, it

was connectivity, so Starlink, and then it was X.AI AI the model, but this whole category of taking all of this compute, which he's uniquely good at standing up,

right, and then reselling it in a way that's highly profitable, was not in a lot of people's forecast. Now, it's a major component of the forecast. You

know, you and I did this podcast with Jensen where Jensen said Elon is an N of one.

What they achieved is is singular, never been done before. Just to put in perspective, 100,000 GPUs, that's, you know, easily the fastest supercomputer

on the planet. That's one cluster. Um, a

supercomputer uh that you would build would take normally three years to plan, right?

And then they deliver the equipment and it takes one year to get it all working.

Yes.

We're talking about 19 days.

Wow. N of one is right. Elon is an N of one. and his ability to secure supply,

one. and his ability to secure supply, stand up the supply, you know, deploy it in a way that's uh, you know, coherent and effective for both himself and I

guess now for others. So, walk us through kind of that. It looks to me again like this is a major component of the revenue story.

Totally. I mean, so we we were all at the macro hard data center and it was just very evident the amount of engineering that was that had gone into building these sites. Um, you know,

people always talk about Google and their ability to to build a TPU and sell the TPU to Enthropic to generate revenues for AI. I think it's a pretty

similar dynamic here with Elon able to secure power uh build these sites faster than anyone else and also be able now to

monetize it to um to the this massive AI market that's ahead of us. Um if you look at the the relationships that he's forged with a lot of his suppliers, you

know, be it Jensen, be it, you know, all of these different um different sites that actually want XAI as a tenant. Um

his a his ability to finance these deals at at very attractive uh financing rates relative to a lot of the other players in in the space. You know, these are advantages that compound over time. And

when you've built the credibility to stand up these sites and monetize at these levels, um you know, it's it's actually a very attractive uh very attractive proposition for for a lot of

folks involved. Um and actually, you

folks involved. Um and actually, you know, if you look at the these deals in particular, Gavin, you you pointed out, but you know, they're they're actually monetizing, you know, perhaps better

than other players in the space by selling this infrastructure, a lot higher. Um, Google is obviously paying SpaceX a huge premium for this compute. Fox, you said something that I

compute. Fox, you said something that I thought was really important, which is, you know, it may very well be that in order to get, you know, first in line on space compute, which Google certainly

wants to do, that they're willing to pay a premium for their terrestrial compute.

And so, to me, that's how you kind of square the circle as to why the premium.

Any thoughts?

Yeah, look, I think there's some of that embedded there. But um look at the end

embedded there. But um look at the end of the day SpaceX can stand up compute quickly. They can stand it up coherently

quickly. They can stand it up coherently and they can stand up a lot of it in one place and have it readily available. So

look I think that's most of the premium but outside of that certainly people are going to space over time. So

pay a little call option to get first in line for space.

There you go. Good.

We've all been investing in the NeoCloud space. So like there's a fundamental

space. So like there's a fundamental belief around this table that that we lack the compute needed to continue to push the frontier on intelligence. So we

have to build a lot of compute. Okay.

Now there's a there there's competition going on. On one end you have the

going on. On one end you have the hyperscalers who are building out that capability. Then we have AI dedicated

capability. Then we have AI dedicated clouds that are bu building out that capability. And now literally in a

capability. And now literally in a matter of weeks right we have a a you know a giant that's emerged in this category which is SpaceX.

The question to you Gavin is can they consolidate this market right? Because

if I think about a marketplace, Elon has a unique ability to get the supply. He

has a unique ability to cut deals on the other side and nobody can stand it up like he can stand it up. So I think there might be a real consolidation in the AI compute market where you have the

hyperscalers on the one hand and on the other hand, you know, he may emerge as the largest strongest player in the AI compute market.

Yeah. So I think they are are they the number four or number five hyperscaler today after the Google deal? um it will be number four.

Kind of wild, right?

In 30 days, we went from not being an AI hyperscaler to being number four. And we passed a lot of companies, including Oracle.

Corweave is a huge business, right? That

we're investors in, you know, and have been investors in, right? But there are a lot of other players, the Nebuses of the world, the Irons of the world. And I

would say that there probably 50 Neolabs being funded in Silicon Valley right now as we speak because of the shortage in compute. Absolutely. Um, so that's kind

compute. Absolutely. Um, so that's kind of crazy in 30 days. That's just

extraordinary.

What I would say is there I think there is a belief that these data centers are commodities.

Mhm.

And I do not share that belief. Um, I

don't think anybody around this table shares that belief. And in the same way that Elon was able to re-engineer a rocket from first principles and make it reusable, he engineered an electric car from first

principles. you know, everyone else was

principles. you know, everyone else was trying to, you know, make an electric car, like an internal combustion engine car, and he thought about it differently. And um I think he looked at

differently. And um I think he looked at data center design from first principles, and he designed something fundamentally different. And I did

fundamentally different. And I did actually ask the team. I said, "Hey guys, maybe it be a little less public about things that are very obvious to you

about how to design a data center, but are revelations to other people because I think what you're doing is maybe um more differentiated than you perhaps realize because what you're

doing is so logical to you, but maybe lo not logical to everyone else." And

that's how he was able to do it 122 days.

Yeah. to I mean to that point Brad yesterday we were meeting one of our portfolio companies and we were talking about behind the meter and we're you know really thinking about it there's only maybe two or three two or three

players now that can actually reliably engineer behind the meter data center and you know there's real engineering work that goes into all this.

So if you think about this if you're a gas combustion if you're Verova and you say we only have a certain number of gas combustion engines now we can sell them to X.AI AI or we can sell them to one of

these startup NeoClouds. Who are you going to sell them to?

Well, and there's another dynamic.

Everyone starts making more money when the GPUs get energized and sold faster.

Exactly.

So, literally speed is money for all of the suppliers, right? Power, land,

turbines.

So, I think it's we we'll see, right? Hey,

right? Hey, Brad. But but this is just we're just

Brad. But but this is just we're just talking terrestrial. I do I do want to

talking terrestrial. I do I do want to hit on and then you can flip it back on me. Talk to me. Okay. So let's let's

me. Talk to me. Okay. So let's let's assume right that they continue to build out uh the terrestrial landscape. They

continue to find buyers for that. Um

walk us through you know what this unlocks you know and how this is related to space data centers because I think you know once you start talking terapab capacity and beyond. So we're talking a

thousand gigs right and this year what we're doing 25 or 30 gigs just to put it all in perspective.

Yeah. 20 25 gigs.

Okay. So once we start scaling up, walk us through, do we have to have space data centers in order to get excited about buying the IPO, right? And then

there's obviously this this debate in the world. I I heard Jeff Bezos say, you

the world. I I heard Jeff Bezos say, you know, I think it's more like six years, but Elon's going to say three because if if he says six, then it will take even longer. So say three and we may get it

longer. So say three and we may get it in four or five. But are space data centers integral and essential to, you know, the IPO? And what do you think the timeline is to either of you guys?

So I don't think I think if you think about those variables around what cursor could mean for XAI.

Yeah. And we do have an existence proof that once you really get on that paro frontier revenue can scale rapidly and it's called anthropic and there does seem to be an exhaust there seems to be a lot of

demand for coding and I do think uh Amjad Msad posted something very interesting the the founder of replet the founder of replet he called it bitter lesson adjacent that

coding may be the fastest path to AGI and ASI because if you're really good at coding you can write code if a model's good at coding to do anything.

Correct.

So I think that's a profound point and I think coding is going to continue to be very important. So I think if you think

very important. So I think if you think about that variable, if you think about Starlink direct to cell enabled by Starlink V3 and you think about how quickly they can or cannot bring on

terrestrial compute, I don't think orbital compute is is necessary for the IPO valuation, but it's certainly important and it's

well maybe another way to say it is you think you you may think we're going to get to ASI faster than we're going to get to orbital compute that may take us

from 300 IQ to 400 IQ, 500 IQ and beyond. Um, and the ability to scale it

beyond. Um, and the ability to scale it up to consume 10% of, you know, global GDP. But maybe maybe that's where we

GDP. But maybe maybe that's where we should move next.

No, no, I think on orbital compute I think Foxy would be great or Clark to lay out the math from first principles on, you know, Clark has this great chart on, you know, the gigawatts it costs, you know, the dollars per gigawatt.

Great.

Walk us through the economic case.

Yeah. Yeah. So I mean on this point of is orbital key to investing here? I

don't think it is. And the first point I'll make is what are the implied monetization rates based on expectations today for the AI business. You know I think you throw out the $160 billion number that's been leaked out there that

people are talking about.

The implied monetization rate on that number is something like 14 billion per gigawatt per year for the AI business.

They just signed Anthropic at 22 to 23.

They just signed Google at 50.

Right.

Right. So I I think you can invest behind the AI business terrestrially and still be excited about it. But with

orbital, it's an important point.

Excited about it if they can get the land of the power, right? But but but I mean I think for

right? But but but I mean I think for most investors Yes. Right. They get they have an easier time getting their head around how SpaceX wins terrestrially.

Like can they go get land, power, and chips? The answer to that is high

chips? The answer to that is high probability yes. Okay. And what we're

probability yes. Okay. And what we're saying is at the rate they're monetizing that that gets you to the numbers that are being leaked out there before you even have to take the leap of faith that they're going to extend the lead with orbital data centers. But take us there

on that too.

Sure. Yeah. So so look with orbital I think the key thing is um two-stage reusability.

Yeah.

And beyond that rapid two-stage reusability.

Yeah.

So today with Starship they've shown that they can successfully reland the booster.

um the second stage. We'll see what happens later this year. I think they're attempting to bring that back and then make it reusable by next year. Um but

the thing that's important about two-stage reusability when it comes to the economics for orbital compute, right, is the cost per kg comes down significantly. You know, we're talking

significantly. You know, we're talking about going from $1,500 per kg on Falcon, somewhere in that range to 250, right, per kg, something lower. Um, and

the more that you can reuse the rocket, the more that price comes down.

Right.

Right. Because you're just depreciating the cost of the launch. And eventually

you asmtote to the cost of the fuel.

Right.

Right. Assuming you can use a rocket for forever.

Yes.

Right. Which will take a very long time for us to to really achieve that. But

um, and at that point, we're talking about something well south of 250 per kg.

So then you look at the specs of these AI satellites. You know, Elon did a

AI satellites. You know, Elon did a great Yeah, that p that that pod was incredible that he laid out the other day the specs on the satellites.

It was really great because I think they are finally showing people here's how you could viably design one of these satellites and how heavy is the satellite, how many could

you fit into a Starship launch? And when

you back into the numbers, you get to something like five megawatts of capacity per Starship launch, right? There's 100 metric tons in one of

right? There's 100 metric tons in one of those starships. So you can back into

those starships. So you can back into the math of how much will it cost, right, per gigawatt to launch these satellites into space, right?

Launch this compute into space.

Um, and the math that you get to before you account for things like um bad GPUs, bad satellites, right? These will all be things that happen, but the math you get

to is it's about $5 billion per gigawatt of capex to put these in space, right?

For comparison, terrestrially, talk about the switch gears, the generators, the transformers, the shell, getting the power, that today is about 25 20 to 25

billion per gigawatt. So we're talking about a 5x reduction in cost on half of your bill of materials right for the data center, right?

Which is a huge number.

Yeah. Just just very simply, I mean, just to say put it cost $60 billion to put a gigawatt on the ground today.

And we'll call it 35 of that is are the GPUs and the silicon that's doing the training and the inference and 25 billion is the land, the shell, the power, and the cooling. I would

hypothesize that those elements are probably going to be inflationary. So

that 25 billion may not go down. And

because space, power, cooling are effectively free in space. And when I say space, I mean land, you know, there's no land in space, but there is a lot of space. There's a lot of space in space.

Um, you're you're talking about putting a gigawatt into space for 30 billion and having lower operating costs. Now the

dynamic versus 60 billion that's inflationary and that 30 and that 30 billion that five may be deflationary over time but what we need to consider is you know the reliability and the

maintenance and so as long as you know everybody can do the math but as long as these

satellites in space aren't failing at an a at an astronomical rate the math maths has and by the way we know GPUs melt and lasers fail We know this happens um in

data centers uh particularly during big training runs and yeah I mean GPUs melt.

Um so as long as the reliability and maintenance is not dramatically lower the math is there once we have reusability and then rapid reusability for Starship V3.

I when you when we look at this okay so we we went through Starlink and we said okay like it it just stands to reason we're going to have direct to sell on Starlink. like the assumptions there

Starlink. like the assumptions there are, you know, again, seem like you can get your head around. Then when it comes to building terrestrial data centers, again, not a hard one to think that based on these couple deals that Elon's

going to build a much bigger Starling's going to build or SpaceX is going to build a much bigger business there. And

then you have this call option on space that would drop the price even further.

The one thing we haven't talked about is their model, right? And I find this surprising, right? Six six months ago,

surprising, right? Six six months ago, X.AI was competing. They're doing pretty well, but they've done something dramatic over the course of the past couple uh couple months, which is they

bought Curser, right? Curser is 700 800 people, was already doing incredibly well from a revenue perspective. Our own

uh projections were that they could exit this year at up to10 billion of revenue.

So, they were growing very fa fast. uh

uh one of the leading coding agents but they also had this incredible team with the potential right to really build a frontier level model but they were compute constrained. So all of a sudden

compute constrained. So all of a sudden they get bought by X. X has massive compute that they can now train on. Um

and when I think about the revenue in AI that like if I look at that line item in the models having it go from $10 billion to 150 billion. Yes, a lot of that will

be the coreweave type business that they have. But the question is how much of

have. But the question is how much of that is going to be the core X.AI business that's really powered by the new team from cursor. So any thoughts on that Kevin?

Right now so composer 2.5 was paro dominant 12 days ago. It was trained on the Kimmy K2.5 base model.

Right now what's happening is the Grock 4.3 1.5 trillion parameter model is training. one would hypothesize based on

training. one would hypothesize based on scaling laws that that will might be a better base model and then the cursor data is being injected into the

pre-training process not just reinforcement learning and we'll see and I think that is going to be a very important data point when that comes out and I just think everyone should keep in

mind that once you are at multiple places on that paro curve if you have compute you can scale really rapidly you know that that to me is if If I had

to say what the one piece that's being lost in the story, right? Like it's easy for everybody to get excited about the deals with Anthropic because you can put your hands around that, you know, how much revenue it is. I see debate about,

you know, the 90-day termination and how long they last and what multiple do you put on those revenues. But I think the thing that's getting lost is I think they've dramatically advanced their capability when it comes to building a

frontier model. People outside Silicon

frontier model. People outside Silicon Valley may not know, you know, Michael and the team at Cursor as well. This is

an extraordinary team that he just downloaded right into SpaceX. SpaceX was

already building good models. And what

they have is an they have this way to monetize compute that gives you this call option that you can pull all that compute in-house right to train a model and then to run the model. I suspect if

there's an upside surprise, if we went around the table, I'd say this is the place that's getting the least amount of attention and could have the biggest upside surprise. Any any thoughts,

upside surprise. Any any thoughts, Clark, on what you think is being overlooked or areas that you think are misunderstood about the business today?

I I would say I would say what the last few weeks have proven is that Elon um their team can stand up all this compute. Actually, if you just, you

compute. Actually, if you just, you know, went back one and a half years, you know, they were behind in the race to stand up compute. They were, you know, they they didn't have that many

H100s. They brought in Colossus, then

H100s. They brought in Colossus, then they brought in Colossus 2 at a scale much larger than anyone else. And now,

you know, as we gear for Vera Rubin, you know, from, you know, a lot of my conversations, it looks like they've, you know, secured maybe up to 20% of Vera Rubin capacity, especially in the

early days of, you know, when, you know, these these chips are very scarce that that they're going to have a a lead on all of this because, you know, people

think that they can stand up this compute better. So I think they'll you

compute better. So I think they'll you know what what the last few weeks have actually shown is that Elon you know Elon will take you know take a shot at

hitting the frontier but if it you know if for whatever reason um they they have overprocedured some capacity this is a very scarce asset that they've shown

that they can monetize at actually you know best-in-class margins and payback periods. I mean the irony is like you

periods. I mean the irony is like you know you and I have been doing this long enough to know I mean that's why Bezos built AWS right he had to build capacity for Black Friday.

Yeah.

Right. But then the rest of the year he sat on all this capacity they had to build and he figured out a really incredible way to monetize this. And by

the way investors at the time 2009 2010 when he was building out the capability around AWS hated it because he was consuming all that free cash flow. M

meanwhile he was digging the biggest gold mine in the history of the world.

One of the biggest one of the biggest among them among them at the time was probably the biggest.

Yeah, Google search might want to have a might want to have a discussion.

By the way, I do think it is important.

Grock 4.3 I think the cursor if they acquire it that may end up being very important. But Grock 4.3 was on the prao

important. But Grock 4.3 was on the prao frontier and as of 10 or 12 days ago and this these things move fast most intelligent 500 billion parameter model in the world

and they were on the frontier and there are four companies on the frontier XAI SpaceX AAI Google one with Gemini 3.1 Pro and then the rest of it was dominated by anthropic and open AI but

they were on the paro frontier. Now

we'll see what they do with cursor.

Yeah.

Um I want to come back to that in a second. By the way, man, I want to ask

second. By the way, man, I want to ask you some questions. What do you think?

So, you think the biggest source of potential upside is the model.

Yes.

What do you think?

I think that's the I think that's the thing that's least talked about.

Least talked about, right? And so listen,

right? And so listen, when I look at the bull bear case on the IPO, right, the bears are looking at last year's revenue, say it was $18 billion, and they're looking at the

forecast from the banks of $160 billion, you know, three years from now, and they're saying, listen, not many companies in the history of the world have basically 8xed their revenue over three to four years, right? So that's

where, you know, I think, and people get nervous about the valuation. When I look at this again, when you break it down as an analyst first principles part by part, which is what I tried to do here,

right? When you look at Starlink, it

right? When you look at Starlink, it looks totally doable. When I look at what they're building in AI compute terrestrially, looks totally doable over the course of the next three years. When

I look at the model itself after the acquisition of cursor, you know, combining those things around the compute they have, that looks to me like it could be an upside. So, I would say that I think that uh you know in the

IPO, but I think when you look back three years from now, there's a decent chance that everybody's like, "Oh my god, that was super obvious, right?"

Even though today all of these things have risk associated back to where we started. I'm not, you know, none of us

started. I'm not, you know, none of us are here to pump the IPO at 1.77 trillion. It's really to just break it

trillion. It's really to just break it down as we do inside our shop and to say what is that distribution of future probabilities? What's the probability

probabilities? What's the probability that it's higher from here? What's the

pro? And I think we're all pretty AIDS.

And if you're AIL, that means we got to build a lot more compute than the world thinks and that these models are going to be a lot more valuable than people think. You combine that with their core

think. You combine that with their core business. I don't know another

business. I don't know another entrepreneur or another business that's a better bet on the future, right, than SpaceX. And so I think for most

SpaceX. And so I think for most institutional investors, it's a must buy, a must own. It's set it and forget it, right? in order to have a a real bet

it, right? in order to have a a real bet on both the space and the AI future.

From your lips to God's ears.

I mean, listen, I I again, I think that I I I think that you're going to have to wait. But, you know, we had this chart

wait. But, you know, we had this chart last week, right, that came out.

Everybody was sending around Twitter conveniently timed. And, you know, it's

conveniently timed. And, you know, it's like shows the average max draw down post IPO for like 20 companies from Facebook, Twitter, Alibaba, Shopify is,

you know, over 50%. And so maybe that again we'll we'll we'll end this section here. You know, Gavin, you and I have

here. You know, Gavin, you and I have been doing this a long time. We know

it's going to be bouncy around the IPO.

Um you know, how do you as a manager try to try to manage that? Um do you try to trade around the IPO? Do you set it kind of and forget it? I would say from an

altimter perspective, what we tend to do is we take a base position that we set and forget, right? and then we may size up or size down depending upon how the

market reacts in you know in a particular moment. Um but any thoughts

particular moment. Um but any thoughts on on this chart or you you know how how people you guys are thinking about it in particular? You obviously own a lot

particular? You obviously own a lot going into it.

First agree with absolutely everything you said and I actually think about it the same way. Set it and forget it.

You've talked about you have ballast you move around and you move the ballast to one side of the ship when you want to the ship to lean into the wind to go faster and you move it to the other side. We don't want the ship to tip

side. We don't want the ship to tip over. I think that's a great analogy.

over. I think that's a great analogy.

Think about all important companies in the portfolio the same way. So 100% agree. I mean this

same way. So 100% agree. I mean this this chart is a bummer.

Yeah.

What I would say is, you know, this data on IPOs, but what I would just say is this is a really unprecedented situation. Yes,

situation. Yes, we've never had an IPO this big.

We've never had an IPO that's going to go into an index this quickly. We simply

do not know how much selling there will be from investors. I would hazard a guess. I mean, I'm I don't know, but

guess. I mean, I'm I don't know, but Elon, I don't think he needs liquidity.

And I think he owns what does he own, Foxy?

50%ish.

50% of the And by the way, he's locked up for 365 days or 366 days. So, we know he's not selling right?

So, I just think it's an unprecedented situation. And the right answer

situation. And the right answer is I don't know what's going to happen in the short term.

And the right answer that I would just you know encourage every investor making their own decision is to just think exactly the way you articulated it. We have these different

articulated it. We have these different levers. We have these different

levers. We have these different variables. Think about each one of them

variables. Think about each one of them from first principles. Make your own decision.

Do your own due diligence. Be

thoughtful. But there are a lot of variables here. And that it is a little

variables here. And that it is a little funny to me that uh you know it was a hundred times trailing TTM revenue.

Well, after the deals they signed, I think it's 39 times.

That can change fast.

So, they added $29 billion in a month.

Yes. No, it's

by the way, have you ever seen that happen?

Never. Never. And, you know, it just goes to show first um Elon is not only a great engineer, he and Gwen and the team are great at business.

They they understand what needs to be done to raise the capital to get to the next phase. They have a long-term

next phase. They have a long-term mission in the business. And so to me again, what we saw over the course of the last few weeks with cursor, what we saw with these deals that they cut, I

don't know that any of the mag seven could have moved that quickly to adjust the business that they did. It's

exceptionally entrepreneurial at scale, which we very rarely see in businesses.

Two other things I would just say.

Can I give you a hug, Brad?

Two two other things I I I I would just say. Number one is people talk a lot

say. Number one is people talk a lot about the total amount of capital being raised. If you add up the capital here,

raised. If you add up the capital here, right, for anthropic, what they may raise, what open AAI may raise, what you know, SpaceX may raise, let's call it

$250 billion. That's 1% of the mag 7.

$250 billion. That's 1% of the mag 7.

Okay. It's 1% of the mag 7. Yeah. And we

will as well, you know, like that to me is like a bet on the future that we all believe in. And so if I said, where are

believe in. And so if I said, where are we out of consensus? What is our variant perception? We actually think it's going

perception? We actually think it's going to be bigger faster. And we've thought that for a couple years. Um, so first it's only 1% of the Mag 7 market cap and then you referenced it, the amount of

selling. Um, I've got a chart we'll post

selling. Um, I've got a chart we'll post here. This is, you know, the the dribble

here. This is, you know, the the dribble share release for SpaceX shareholders, you know, so there's not a lot that can be released um up until after the first earnings. This you we saw this in the

earnings. This you we saw this in the Cerebrus IPO. Um, there's a version of

Cerebrus IPO. Um, there's a version of it here in this IPO. And so again, I think the banks have been thoughtful here knowing that this is a very large IPO. And I'm not saying they won't trade

IPO. And I'm not saying they won't trade down like there's possibility, you know, these things trade down. But again, for me, telescope out, is there any company better positioned as a bet on the future? I think what they've shown over

future? I think what they've shown over the course of the last 5 weeks, they're they're they're probably number one. But

let's move on.

Can I just say one thing about the employees? I think another thing that's

employees? I think another thing that's unprecedented here is the employees and to a large degree the investors here have had liquidity every six months.

Exactly.

For like the last 10 years. Yes.

So if you're a SpaceX employee or former employee and you wanted to sell, you've had whatever that is close to 20 chances and it is a matter of historical

record that large investors have been able to sell.

So I would think a lot of the people Great point.

They've chosen to own it. Now there's a new valuation and we'll see what they do. But just this is utterly

do. But just this is utterly unprecedented and we'll see.

Yeah. No, it's it's it's a great point.

We've in fact called these companies quasi public. Um you and I both know

quasi public. Um you and I both know that SpaceX and I put Anthropic in in in this category as well, Data Bricks in this category. These things in many ways

this category. These things in many ways have been more liquid over the course of the past three years than some public biotech companies we know. Absolutely

right. And so there's a continuum of liquidity here. We we treat it as a

liquidity here. We we treat it as a binary private versus public, but it's really about this continuum. You know,

let's keep going on models. you know,

um, Anthropic launch Fable 5, which you referenced, um, yesterday, which is basically mythos, um, with some classifiers and safeguards, um, around cyber and biology, chemistry, um, and

distillation. When those things get

distillation. When those things get triggered, it fails back to Opus 4.8.

Um, you know, there's a Kaparthy tweet about this yesterday. He said, you know, it's soda on all the benchmarks, but what really makes it special is longunning tasks. Okay, you retweeted

longunning tasks. Okay, you retweeted our good friend, you know, Noam Brown, um, you know, chat GBT 5.5 also exhibited these capabilities. Um, you

know, it it led Noam, right, to suggest that it's not very relevant to do these snapshot benchmarks anymore. Like the

X-axis has to be time or tokens or compute because we can solve most problems now if we just let these frontier models for a very long uh point

in time. So Gavin, what is this new

in time. So Gavin, what is this new class of model right fable fable 5 chat GPBT 5.5? What does it mean for the race

GPBT 5.5? What does it mean for the race and super intelligence? Who's up? Who's

down? Who's still on the frontier? Um,

give us your thoughts. I mean, it's hard to say that Anthropic's not up. Yeah.

Like after the revenue numbers they put up, after the Fable 5 release, and Mythos is evidently even better. But I

just think that Gnome Brown post from yesterday polomial is so profound and just the idea that we do not know how smart these models are and we may

say more about that. Why don't we know how smart they are?

Because nobody has run mythos for a year continuously and we may never know how smart each generation of models actually is or was but because we don't have time

to appropriately evaluate their intelligence before the next model comes out. I mean this is a profound statement

out. I mean this is a profound statement and just just imagine okay so I always say like when you think about FSD just imagine a human being who never gets

distracted, never gets tired, never talks on the phone in the car, never drinks and drives, never yells at their kids, never has to go to the back seat to give their baby a bottle. And like of

course you would think that over time that is superior to humans who are distracted. I don't know how long. How

distracted. I don't know how long. How

long can you think deeply about one topic Brad?

Well, it could be an hour like an hour.

Like an hour.

Oh, man.

Yeah, that makes me feel terrible because I think I could think deeply about one topic continuously before having a stray thought enter my mind for like maybe 5 minutes. Now I can come

back to that.

Imagine if Albert Einstein Yeah.

had been able instead of, you know, maybe that maybe maybe he could think for three hours at a time. Clearly an

exceptional intellect.

But imagine Albert Einstein had just thought about fundamental physics.

24 hours a day.

Yeah.

He doesn't have to eat. He doesn't have to sleep. He doesn't have to relax. He

to sleep. He doesn't have to relax. He

doesn't drink and never gets old.

Never has dimmunition of intelligence.

And he think thought for one year.

I mean we might already, you know, have solved a lot of these intractable problems. So I just think that's an extraordinary thought. And just my takeaway was

thought. And just my takeaway was however bullish I was on compute before then, I'm just a lot more bullish.

Right. Right. Right. So, so, so that is a, you know, we saw when that was probably what really unlocked Opus 4.6. It was the first really

Opus 4.6. It was the first really longunning model that could maintain that context, maintain that memory, um, solve some of these longer running problems. Right? For us, the signal was

problems. Right? For us, the signal was in January. We knew We felt like that

in January. We knew We felt like that was a big moment, but then when you started to see the revenue go up, we knew that lots of people were voting independently that that was a profound

moment that they became much much more useful. So, but one of the things that

useful. So, but one of the things that the consensus going into this year, right, so the big question going into this year was was the AI revenue going to show up? Were we going to get to

these thresholds of intelligence that caused enterprises and consumers to use them more? And I think the consensus at

them more? And I think the consensus at the time, at least on this podcast, um the the the debate with with my with with Bill was that open-source models,

cheap tokens, were catching up on the frontier, that perhaps these models were beginning to asmmptote. Um that people wouldn't really pay for premium tokens.

And it seems to me that the evidence on the field 6 months into the year is just the opposite, right? that Frontier

tokens are capturing the vast majority of all the revenues and that in fact if you believe in the longunning capabilities and more compute allows you to do that they may actually be

extending their lead right on some of these models that were built on distillation. So I just open it up to

distillation. So I just open it up to anyone around the table. What are your thoughts on whether or not you know have we challenged this thesis that cheap

open source tokens are going to always you know close the gap on these frontier models or are they extending their leads? I I think this debate like this

leads? I I think this debate like this same debate has existed since the beginning of since we started training these models to begin with which was hey

we're always kind of three six months behind the frontier but empirically like you can just see all of the revenue has actually just occurred at the frontier and that I think that's because every

time we release the frontier a whole new like slew of use cases right that that previously we could have never tled before like coding um but also just

you know at you know we've we've just been locked at our desks for the last last day just you know hammering claude because you know it's just fascinating the things that now we can do with Fable

5 that we just couldn't do with Opus 48 just a day before so what are some of those things man I'm curious so so I think it's really really good at multi-agent orchestration now so they

there anthropic released a um a blog post about like different uh agent um six different agent like orch orchestration patterns that you know they they've talked about. But really

like once you start being able to manage all these agents, the harness and the model itself is being arled with one another. They're actually being you know

another. They're actually being you know fused closer and closer together but the model can understand the you know the extent of your work. So you know one of

the things for instance is um I just threw in like seven of our models and just said okay like I want to create a master view of like my beliefs given all

of these assumptions of all these companies TSMC capacity like and then and then produce me a report on all this stuff and you know the the model is able to reason through all of our assumptions

like actually if you believe this this thing is what are the contraduct yeah it's it was fas Fascinating and and and you know before we never do that but but now you know I think we're just step one

into multi-agent orchestration we're going to do this even further and that's one example I've also dumped all my all my notes into it and it's reason across all my notes from the last 3 years and

said you know here are some of your ideas that were consistent here are like you know the sources that were actually the highest signal to what actually played out you know and then it it was

actually just super fascinating what you do and we've just blown through our blown through our limit.

It's it's it's unlocking all this. I

mean like they gave examples yesterday in the release anthropic did you know 50 million line Ruby code base at Stripe that was you know uh refactored in a day versus many weeks with many people. You

think about where this is impacting biology and life sciences just across the spectrum. Um and to me it really

the spectrum. Um and to me it really gets back to this fundamental point.

Number one, if you believe this to be true about longunning agents, then we're going to produce and consume more tokens in the future as far as the eye can see.

So the world, this gets me back to, you know, Terraab and Space Orbital and all this because we we we may in fact unlock real thresholds of intelligence, but we're going to have to let these horses

run for a long time in order to get there.

Yeah. I would just say two thing I two things can be true.

Mhm.

The majority of economic value may continue to acrue to the frontier and man has it ever acrewed to the frontier thus far and for sure the first six months this year but the majority of tokens

consumed to the world may be open source and they are today.

Yes. I and I think that this current state is likely to persist. Harvey had a great um blog post that they put out on X and

they used and it's just amazing how everything gets out out of date like in five days, you know, but they use their own proprietary legal data to do

reinforcement learning and supervised fine-tuning uh with fireworks on an open source model and then they used a router and a router being something that picks which model you send which query to and

which model you use to check which model and they got better outcomes than Opus 4 either 4.7 or 4.8 at a lower cost and I think that is the future and the reality is

they were still consuming a lot of opus but a majority of the tokens they were processing probably were in their own open source we hear the same thing we did we did um

we did an enterprise survey that we'll post of 300 companies how which ones were optimizing so these are folks who are kind of looking at model routing and saying we're going to send certain tokens over here which ones are thinking

about optimizing which ones aren't optimizing Yeah. And then what is their

optimizing Yeah. And then what is their expected use of Frontier model tokens, right? And they're all expecting to

right? And they're all expecting to consume a lot more even though they're already in the process of optimizing.

Think of it in the in the context of JP Morgan. If they're doing some back of

Morgan. If they're doing some back of the house stuff, right, on customer service or whatever, they may very well use an open source model. Now, I think they're loathed to use Chinese open source models. So, they're waiting on

source models. So, they're waiting on kind of US open source models to, you know, be able to really deliver the bang that they need. But my hunch is for these enterprises, a lot of that back of the house stuff will get rooted there.

That will probably be a majority of the tokens. But I think the really high

tokens. But I think the really high value stuff, you know, coding as an example, they don't want to write second tier code. I think the vast majority of

tier code. I think the vast majority of that will continue to be on the frontier. Um,

frontier. Um, you don't need Albert Einstein to book you a a trip. You don't need Albert Einstein to do KYC.

But but but this is the debate. We had

it literally at this table two years ago. However, if you just look at the

ago. However, if you just look at the revenue curves, right? What bill but what folks concluded B when they said that they said therefore the frontier models will not acrue most of the

revenue and what we're seeing right now it's 90% of that has been decisively wrong probably more than 90% and it may continue to be decisively wrong frontier might be 90% of the econ economic value right

open source might be 80% of tokens something that I think is very important on open source is that you know I think there's this belief that it's bearish for AI it's

actually and maybe bearish for the frontier models. There's that bare case

frontier models. There's that bare case you talked about.

It's actually really bullish for compute and hardware because if the frontier models are capturing less of the margin, then you're going to spend more on compute.

So the better open source does, the better it is for compute providers. I I

I will say it there is a very I would say between um spending time in the heart of like the west Silicon Valley and also spending time in Asia there is

like a very big um like a deep-seated belief in one versus the other which is like if you spend a lot of time here it's like all closed source cloud every

all traffic is going to go you know by way of this direction and then you spend time in Asia you know the the overwhelming belief is that we're going find the right model to the right

workload and we're not going to overspend. And I think, you know, I

overspend. And I think, you know, I would say I would say the next year is probably going to be the most indicative

of which way this falls. Um because

I think I think the reason why uh closed source models have captured so much of the value is because um the models actually get the intention and actually carry through the work. And this was the

first year where we actually had agents that actually carried out user intention from just answering a chatbot request to actually producing useful work, right?

Um, now the the the level of this intelligent has scaled so rapidly and we continue to push against like the most economically valuable tasks which are coding and finance and all these like

knowledge work tasks. But like for the long tale of tasks, if open source continues to maintain a sixmonth lag, we might actually see a lot more open

source used for, you know, our everyday tasks that we might actually and that's basically Jensen's argument, right? Jensen's argument is you're going

right? Jensen's argument is you're going to have model routing. Um, and we're just in a moment in time where the frontier models gained the advantage, can do longunning tasks. The open source models couldn't do it very well, and so

they're acrewing all of the value. But

as soon as the open source models can do the longunning task as well which is not far away that they too will grab a bunch a bunch of this revenue. Are you

investors in reflection?

I'm not. Okay. Nor nor are we but I I'm very impressed by Misha and and the team and what they're doing. I very much want a Frontier open-source US lab to win. We

know that you know I heard you say recently and I believe it to be true.

Nvidia any day that they really wanted to, right? They already have some great

to, right? They already have some great open source models. They could

absolutely build a Frontier open source model whenever they chose to do it. And

so it's not a question in my mind as to whether or not the US is going to have a frontier open source model. It's just a question about timing. And then like at that point in time is that you know

let's let's assume they get these longunning capabilities. Have the

longunning capabilities. Have the Frontier Labs now achieved something yet again that allows them to keep keep the the strangle hold on the revenues?

Yeah. And I just think it's if you're Wow, that's a cute ASIC you've built there. That is so cute,

there. That is so cute, right?

How would you like um open source to join the frontier, right?

How would you like that? How do you like them apples? So, I mean, I'm not sure

them apples? So, I mean, I'm not sure that's the explicit calculation, but I do think Jensen same just double click on that for everybody at home. If you were if they were to put an open source model out there, how does that impact the ASIC

landscape?

Well, um you might not have the revenue to fund to fund that uh the revenue or the margins to fund that ASIC. And I do think Nvidia is highly likely to be the

world's dominant provider of open source AI. And I do think Jensen will bring

AI. And I do think Jensen will bring open source. You know, right now it's

open source. You know, right now it's whatever six months behind the frontier.

Yeah, we might see it creep closer and closer and closer.

And I do think Jensen has a big business decision. I see this, you know, chart

decision. I see this, you know, chart here. So, let's, you know, chop it up

here. So, let's, you know, chop it up about Nvidia as you say, but if all of his customers are going to compete with him, yes, then why not compete with his customers?

And we have all these Neoclouds.

So, that's a cloud computing business that can compete with all these cloud computing businesses. He has his own

computing businesses. He has his own models that are really really good.

Neatron 3 or 3.1 was actually really really cool from a compute efficiency perspective and he's always careful to release small models right so as to not tread on anthropic openi Google's toes

but I do think that is a choice he is making and just you know at if if the economics change right I think Nvidia can join the frontier and become one of the world's largest cloud

computing companies much faster than people think interesting interesting Clark walk us through this uh this chart Yeah. So, so

I think one of the takeaways from spending time in Taiwan was um there there is certainly a lot of excitement around the the next wave of A6. Um but I

think I think it's like a very clear moment now where Nvidia it used to be an argument of Nvidia versus A6 one or the other and you know total domination or one or the other. Now I think it

increasingly every year every everyone assumed that Nvidia was going to lose share dramatically on a revenue scale on a gigawatt scale on a unit scale and actually if you actually look at the

last few years you know they've actually maintained their share very very handsomely um actually um if you accounted for the fact that Enthropic

was not really using Nvidia they probably actually gained share against um if not for in 25 26. So I think um I think what was very interesting though

was a new class of uh accelerators or A6 MediaTek with their um with their new V8T

versus you know Broadcom's V8i for TPUs actually was a big topic of discussion and you know I I think for A6 the

argument now is that more and more will look custom to the actual workload and that is like one vector that people are moving in versus Nvidia now is has kind

of shown itself as the the predominant provider of compute to a lot of the world and for you know internal internal workloads um perhaps they will go more

and more custom and more and more down the stack and I I remember just you know one year ago when it was kind of a broadcom or uh Nvidia battle it seems there's a lot more nuance now to you

know what type of accelerators will fit which workload loads and fit which customers and fit which business models.

Um and uh yeah it it I thought I thought that was a a a new topic actually new realization though. I think we all kind of shared this view for a long time.

Yeah, I was just shocked. I mean, I'm I'm out here. I did a board meeting with one of our companies and just, you know, their biggest one thing they emphasized is we thought the world would be have be

consuming less Nvidia than it is. And if

anything, Nvidia is accelerating and they just continue to outexecute their competitors.

And I think a lot of people are indexing to this um OpenAI Gigawatt and you know Nvidia has 10.

Broadcom has 10.

Um who has six?

AMD AMD has six and they have warrants and then Cerebras has our shared portfolio company has a gigawatt.

And I just that is what's on paper, right? what actually gets deployed.

right? what actually gets deployed.

Let's see.

I will be very surprised if you know that 10 out of 27, what's that math?

Let's see who's best at math. What

percentage market share is that?

30%. Yeah.

Yeah.

I'll be very surprised if that is where they land. I think that is an extremely

they land. I think that is an extremely unlikely outcome and especially as long as we are in a watt constrained world.

If you can get more tokens per watt, which is literally revenue with Nvidia, than a lot of alternatives, just if you build your factory with another chip, you may save some money, but you're

going to have less revenue and the margins may be lower. And that's a point that Jensen keeps hammering and I think is really important. And by the way, credit where credit is due. The most

important the most one of the most surprising things to me in this ASIC landscape I would say Meta and Microsoft have been probably disappointing.

Yes.

You know who made a good ASIC?

Yes.

Well, I know you Jalapeno.

Exactly.

From OpenAI.

They made a great chip.

Yes.

Now unfortunately needs to uh run at a much lower temperature than the Nvidia GPUs which means you need to spend more money on cooling and that consumes more power. They made a great chip. We can I

power. They made a great chip. We can I mean I I think the question there and the question for everybody is going to be is that the highest and best use of your time, right? Like I you know I tend to think that the frontier companies

like there's this belief that they got to be vert vertically integrated but if you believe like I do that the race to super intelligence particularly as we get these recursive loops working may be

over in the next two to three years then I think focus focus focus focus. you

exist to build the best intelligence in the world and to deliver the best intelligence in the world and you that means you have to have all the revenue because if you want to build out the compute that's going to be required to continue to push the frontier you have

to have the revenue in order to support it. So, I think that, you know, subject

it. So, I think that, you know, subject to the focus question, I think, uh, they certainly did. This all brings me back

certainly did. This all brings me back to kind of a reality check, though. Um,

you know, we just got done talking about test time compute, inference time compute, longunning agents. This is

really the thing that's unlocked the revenue this year. Um, it all pushes us in the direction of more capex. Google

just raised $80 billion, right? We've

now taken the mag five or mag seven free cash flow, you know, down dramatically 80% um from just a few years ago. Um and

Morgan Stanley, you've got this chart in front of you, upped their 2027 capex forecast from 950 billion to 1.1 trillion. I mean, we were talking about

trillion. I mean, we were talking about this with Jensen. That was his forecast two years ago. You know, obviously this doesn't even include SpaceX, Coree, etc. So I think the number on 2027 is likely

closer to 1.5 trillion. And if we compare this to the total incremental inference revenue. So the thing that the

inference revenue. So the thing that the market gets worried about, you know, back to my Sam Alman podcast, you know, in October of last year, can we really afford to spend 1.5 trillion of capex a

year if we're only generating X amount in inference revenue? The thing I think that lit the fuse this year was Anthropic showed up in a major way with revenue, right? And so we have, you

revenue, right? And so we have, you know, the AI lab revenue everybody combined at around $300 billion next year, right? So can't you know and go

year, right? So can't you know and go roll that out to 2027 uh or that is 2027 300 billion. So we're

spending 1.5 trillion of capex on 300 billion of inference revenue. Does that

math math for you? And what would cause you, you know, to to get more nervous again about our ability to continue to make these investments? Because the

second we get nervous about it, the entire semicmplex is going to come down a lot.

Well, what do you think the gross margins are on that 300 billion?

Yeah, let's call it 50%.

I I would guess they're probably a little bit higher than that. I might say 60 or 70, but I mean that math starts to math. And

what I would just say is I think that 300 billion is low, man.

Yeah.

I just think it's low.

From your mouth to Yeah, exactly. I

think I think we end this year well over 200 billion in inference revenue. Well

over. And so I think the math really maths. And I do think we have to give uh

maths. And I do think we have to give uh Jensen, our friend, some credit because he said some things that seemed outlandish, right?

And he was conservative. He was low. He

said a trillion two years ago and I mean he was really low, right?

And so like let's give the guy some credit and think about what he is saying right now.

For sure. For sure. And and and listen, I would say consistently Elon's been taking the over. Sundar has

been taking the over. Sam Daario, you know, Daario did the podcast with Dwarkish when he was talking about country geniuses in a data center. He

said that will be here by 2028. He said

revenues will go into the low hundreds of billions by 2028. So let's call that, you know, 3 400 billion of revenue by 2028. And he said that a while ago now.

2028. And he said that a while ago now.

So he may even be revising up his number. And he said, "It's hard for me

number. And he said, "It's hard for me to see that there won't be trillions of dollars in revenue before 2030." And if you're on that revenue trajectory, if we're on a trajectory to 200 by the end

of this year, let's call it four or 500 by next year and a path to trillion plus by 2029, then the math maths.

And we got to keep in mind that half of the spending, right, is there to, you know, for training, maybe a little less than half. What is

it, Foxy? It's probably depends on the lab, but it's I would say it's increasingly less than half.

Yes. Okay. So, we'll call it 35% is spending that's not revenue generating that is going to kind of make the next model. So, I think the math maths and

model. So, I think the math maths and there's still this prisoners dilemma where if you opt out, that may be an existential decision for sure. And I

think like coming into this year going back to this kind of what narratives were violated you know I think into this year everyone expected token pricing uh the price of compute it's all

deflationary and it will be kind of a smooth line deflationary over time but I think this year what we've seen is the opposite and you know it's all comes back to supply demand the demand side of

the equation seems to be far outstripping the supply right and I think you look at the deals signed by SpaceX and others the monetization rates

per watt are increasing.

Um, and look, that is on a a pretty nent small base of users, right? Like Alex at Whale Rock, he has this great um way to frame

it. Less than 0.2% of people on Earth

it. Less than 0.2% of people on Earth are actually using AI in an agentic way.

Right.

Right. Like I'm not a technical person, but I'm consuming 500 CPU cores in a VM instance, five GPUs 24/7.

I mean, if you draw that out to any meaningful percentage of the population, I mean, we're going to be in, you know, this kind of shortage environment maybe for some time. So,

I think that is all positive for this ROI question.

Man, Foxy 100 to watt CPU to GPU rat ratio. Kind of a workflow.

ratio. Kind of a workflow.

course. Fine, fine.

I'm being smart with my spend.

Good, good, good. Excellent.

I I will say also that ratio of 300 to 1 point, you know, call it 1.2, 1.5. Um

there there's also a rate that now physically we can only expand how much we can produce and how much we can actually increase that spend by. Whereas

we're seeing the opposite right now on the on the the willingness to pay for these tokens, right? And actually like when the willingness to pay for these when the monetization per gigawatt is

actually increasing from, you know, call it like 20 20 billion um in the in the best best of cases for at the beginning of the year to now like 30 to even pushing 40

per gigawatt per gigawatt.

Um, all of that is it's a very heavy fixed cost base, but all of that is like pure margin flow through now. And you're

actually, you know, as we scale like the willingness to pay for for all of this and and now all of this stipulated by like, you know, everything we're talking about of like how much is open source

versus not and all of these different flows. But really like as we're climbing

flows. But really like as we're climbing this curve, you know, the the the revenue is might actually outstrip our fixed cost base by by a significant amount. And I think that's why all the

amount. And I think that's why all the labs are pushing, you know, the the gas to the pedals be because they all they all see like within if we continue this curve within like 3 years, you know, we're just going to be so short on all

the computing.

This is a great I'm sorry, but I mean like it's a great point. Like if you thought you were getting when you made these decisions in November of 2025, you thought you were getting a certain return.

Yeah.

You may be getting triple that return today.

That's no way. No way did they think they were going to be anywhere close to break even. Yeah. Right. In in in in in

break even. Yeah. Right. In in in in in this part of the curve. And the reason like I I I called it accidental profitability that you know people have been talking about that because they want to spend a lot more money on comput. They've just had a hard time

comput. They've just had a hard time doing it. Now maybe with SpaceX you know

doing it. Now maybe with SpaceX you know they could take some of those dollars and and and go spend them other places.

But that to me is you know a a fundamental change. Um the first

fundamental change. Um the first argument against the Frontier Labs was they'll never generate revenue.

Okay. And then we that got blown up.

Then it was like even if they generate revenue, it'll be really shitty gross margins and they'll never be able to get make money. And then kind of that that's

make money. And then kind of that that's blown up and and you know I think now you know people are falling back and they're saying well they're overcharging. This is token maxing. My

overcharging. This is token maxing. My

good friend you know Chamatha said there's no ROI on any of this spend.

It's all this token maxing. my best

evidence for why we all know of course when somebody puts on this much spend like at Ultimter we're not optimally spending every single dollar but the question is why are millions of

independent businesses small medium and large why are millions of consumers all choosing to do the same thing they're not dumb these are you know rational economic actors that are all

simultaneously saying I want to do this because it makes my life better it makes my business better etc to me that is the best evidence as to why I think this revenue can continue.

Yeah. And Clark, I think like the point you made is dead on because I mean you want to own asset heavy businesses and inflationary environments and token pricing is going up and supply demand is

tightening. So, totally agree.

tightening. So, totally agree.

Um, you know, as we begin to uh find our way to the exit ramp and and and wrap here, one of the things I you know, you and I have been doing this for a long time, Gavin, couple decades. Um you may

even sketch longer than me even though I'm a little bit older than you. Um you

know we have uh I always like to do a market check because I find a lot of time that analysts come on these things and they talk their you know talk their book and you know there are a lot of people who listen to these things retail

investors and others and it's just kind of like what do we really think and so I always characterize as kind of small medium and large like what am I doing?

Do I have small exposure on do I have medium exposure on? Do I have large exposure on? you know, and if you look

exposure on? you know, and if you look at what's happened in the markets, semis rip this year. I mean, like you've been doing this a long time. I don't I've never seen it before, right? I've never

seen, you know, the doubles and the triples across the board like we saw, but there's been huge dispersion, right, in the market. Internet's down 16%. Uh

software is down 8% on the year. You

know, SPY and and NASDAQ are up, but really up because of their components that are related to AI and compute. And

so, the market itself has kind of struggled. Meanwhile, if you were in the

struggled. Meanwhile, if you were in the stuff that we were invested in, we've all done pretty well. I think, you know, I've said it a couple times, I think if the anthropic revenue had not shown up this year because that was the overhang

on the market, I think the whole market could be down this year, right? Um, but

that showed up, you know, we just had these huge months in in in April and May. um for us you know because prices

May. um for us you know because prices came up so much because I have some worry about you know geopolitics the macro backdrop with you know with with what's going on with inflation in the

short run and just like you know needing a little consolidation in this market to answer some of these questions because now expectations are higher you know we dialed back from what I would call large

for altimter to something kind of like medium small um again it's never all or nothing for us it's like what is the riskreward at a given price. Um, and so we think this is a, you know, maybe

going to be a period of consolidation on way to much higher highs. Um, curious

just how you run the book, how you think about it like a portfolio manager.

Very similarly, man. I always think stocks, the markets, I imagine them as runners. Okay.

runners. Okay.

And like in 22 that runner had gone downhill. It had a lot of energy, man.

downhill. It had a lot of energy, man.

Yeah, it was painful. It wasn't fun. Um

but coming out of that there was a lot of kind of pent up upside in the market and you know the market particularly in the last two months it has run up a very steep hill and a lot of companies semiconductor

companies in particular you know ironically you know Nvidia and Broadcom they they have been lagards totally and so but a lot of these like I do see a lot on X about finding

the next bottleneck I think that was the last game that game is over you've had a lot of stocks that forget climbing a mountain or hill. They've

gone straight up a cliff.

Okay.

Yes.

They're tired.

They need to rest.

And we'll see.

Do they just rest at the top of that cliff they climbed?

Do they hang out on in their harness?

We'll see. And we've seen the last week, we've seen, you know, some retracement or do they need to go downhill for a bit?

We'll see. But I'm thinking very similarly to you.

But it is and I think there's, you know, the market is seasonal.

Yes. I think there's real real concerns around inflation and rates. What was CPI this morning?

It was uh 4.2. I think we added core came in at like 0.2 versus.3. So, a

little bit better. Um but, you know, clearly we're we're above four again.

And um and and there's short-term pressure on, you know, core PCE, etc. Um, and we have some unknown unknowns, but the market, I mean, if I had told you the fact pattern for this year, that

we're going to be in a war with Iran, that, you know, oil was going to be at a hundred bucks, that CPI was going to be creeping back up, that internet was going to be down 15%, software is going to be down 8%. You would have said, I

want nothing to do with that market, right? And here we are, the market's

right? And here we are, the market's done pretty good in the stuff that we traffic in because the world underestimated AI revenues and underestimated the amount of compute that was going to be needed.

It's I would just say, you know, we're heading into a seasonally weak period with all these spheres. AI has actually been seasonal for the last three summers.

Yeah, it's interesting, right?

Yeah. Token consumption has kind of plateaued, slowed down, and that's because, you know, college kids are big AI consumers and they don't use as much AI. You know, hopefully they're all

AI. You know, hopefully they're all using it to learn and not cheat. Um, but

that may happen. It may not happen because the 15year-old is building swarms of agents, building a SpaceX model. He's going to the SpaceX

SpaceX model. He's going to the SpaceX IPO with me at the exchange on Friday, but I he had to build an AI mod using AI agents. He had to build a model, a DCF

agents. He had to build a model, a DCF before we go to the exchange. He is

mesmerized. He is absolutely and it's extraordinary what he's building.

So, he's one kid who's not using less comput.

He's burning it. He's burning it.

Yeah. But you know if token consumption plateaus, if open-source takes some share, there's a silicon data index that has showed which is an index of kind of consumption and pricing. I think there

may have been a little bit of a shift over the last two weeks to open source tokens that are cheaper. I think people looking at that data as bearish or not understanding it. But nonetheless, like

understanding it. But nonetheless, like I just think there's reasons, you know, to look around, be careful, be thoughtful. I always assume a bullet is

thoughtful. I always assume a bullet is coming for me. Head on a swivel. It's

the bullet you don't see that gets you.

So, I've tried to spin as fast as I can, but yeah, it's the market may need to take a breather, but man, when I think about what Gnome Brown said, I know and when I see the capabilities of

Fable, it's just hard for me to get too bearish.

I mean, like to me, um, and we got two, I think, of the most extraordinary guys of, you know, the next generation, you know, sitting in the room. We have at Alttimeter, we have deep admiration for

the work that you guys do. I always

appreciate when you send me a note about the work that we do and we publish. Um,

but for the guys who are newer to the business, they might think this is the way that it kind of always was, right?

And like this line, the steepening of the line of creative destruction, the steepening of the line of, you know, scale advantages, um, I always believed

it was to was going to be true. I never

thought it would be true at this rate. I

went back last night. In the last seven years, we've added 1 trillion of revenue to the MAG 7 in the last seven years.

Okay. To get to a trillion, to get to the first trillion of, you know, took over 20 years.

In the last seven, we added another trillion and that added 17 trillion in market cap. That trillion dollars. Okay.

market cap. That trillion dollars. Okay.

uh the forecast now that we're going to add another trillion of revenue in just three companies, SpaceX, Anthropic, and OpenAI over the next four to five years.

Okay? Like not seven companies, three companies and in half the time, right?

And so I would say that, you know, we are going to have bumps in the road. I

know that it's going to be like this, but we're going to higher highs because the size of the prize. This is going to transform 5 10 15% of global GDP. There

is no doubt in my mind. And 10% of global GDP is 10 trillion. It's an

exciting future to be a part of. It's

fun to do it with you guys. I think

we're going to have to do our work to do the things to make sure America wins and that we evolve the social contract, keep everybody, you know, lift the floor, take everybody with us on this ride. Um,

but it's a uh it's a it's a really exciting time to be doing what we're doing. It's fun to be doing it with you

doing. It's fun to be doing it with you guys.

Yeah. I just want to say Brad, thanks for having us and thank you for what you've done with the Trump accounts. I

actually think it's super important for America, for the world to give people an equity stake at a very young age. They they will see it

young age. They they will see it compound over their lifetimes.

This is a great thing you've done for the world. So, thank you. I'd echo all

the world. So, thank you. I'd echo all your comments like deep admiration for you, your team, gratitude for the collegiality and friendship between our firms. I know Clark and Foxy, they hang

out like all the time.

That's a people think that you you know and there are people in our business who don't want to share anything.

Our view is like we open source it. Um

but there are very few people who we actually call and ask their opinion because there are very few people who do the thousands of hours of work that we do um that you know that are adding to that and you do it and we appreciate

that and you do as well Gavin. We

appreciate that. So with that love fest, let's call it a wrap. Thanks for being here.

Thank you.