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

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 than GB in the house, Gavin Baker from Atties. He's brought his main guy, Andrew Fox. And of course, I had to draft Clark Tang into the mix, my partner, 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 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 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 Taiwan last week with Jensen at Computex and 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, you know, maybe just kick it over to you, Gavin, talking about the SpaceX IPO. The IPO is in two days. You're a big shareholder. Congratulations. We're also a shareholder. You know, we also expect to be buying in the IPO. The Wall Street Journal's reporting you know the Goldman Sachs are both saying 160 billion in revenue in 2028. We know that the IPO is $135 a share 1.77 trillion. So when we think about kind of what the big levers are, there's so many moving parts in this IPO. 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?

Hey, hey, subject to revision.

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

We do know from Jensen that Elon brings data centers up faster than anyone. 122 days. Speed is literally cost because every day you're paying electricians and plumbers. That's cost. And they're now monetizing them at arguably the highest rate.

I mean I think one of the interesting things is you know the way you answered the question, right? We didn't talk about launch, right? We didn't talk about Starlink or Communications. Those up until really 6 months ago were the business. 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 terms of this. But what I want to do is go to Fox. Give us the breakdown. Three big lines of business, right? We've got the communication Starlink launch business. We've got the 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. This is the kind of crown jewel of SpaceX. It's something that no one else really has, notably 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? So I think rapid reusability is the main thing that we're watching for and I think most people should watch for. Elon talks about it a lot, but getting these rockets to fly at a cadence that's comparable to an airline, right? And Gavin has used this analogy before, but the old rocket industry was kind of like imagine boarding a plane, flying to California, getting off the plane, the plane explodes after. So I think what SpaceX are ultimately trying to achieve is have a Starship fly both stages, not just the booster, 30, 40, 50 times before you have to retrofit that ship. 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. But that's a really hard problem to solve.

Extremely difficult.

And look, I think the company have been loud and clear they're going to attempt to bring back the second stage of Starship later this year, right? And then make it reusable, you know, refly the second stage next year. 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 times are Starship just launch? Starship 3 just launched. How many launches do you think the consensus out there is assuming, you know, two or three years from now? Like what is the launch cadence? 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, 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.

I think the company's aspirations are thousands of launches. 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 keep a call on Sand Hill Road two decades into the mobile revolution. I mean, it's the craziest thing. It's like a third world. 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 because I don't want to lose that call on Sand Hill Road. So walk me through a little bit just again high level, 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 driven by direct to cell connectivity. Walk me through a little bit those economics.

Yeah. So look, it's actually interesting. The broadband business is still very early stage when you think about 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%. And that's the broadband. You know, you kind of have a base terminal at your house, on your car, in your boat, and in airlines now as well. So I actually think broadband can scale to hundreds of millions of terminals, okay? Hundreds of millions of users. And today the subscriber base is hundreds of millions if they get rapid reusability of Starship, which is really hard. If there's not competition, hundreds of millions, 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 I just think it's important to acknowledge that orbital compute, you know, Starlink, Starlink V3, Starlink direct to cell, we need first reusability for Starship V3 and then rapid reusability unlocks a lot of this.

Right. 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 largely have the revenue on connectivity, so let's call it Starlink direct to cell etc, going from, let's call it 10 billion to 50 billion by 2028. And so I'm not asking you guys 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 answer is yes.

I like betting on better, faster, cheaper. Clark, I would say probably the biggest surprise of the last six weeks is that Elon, you know, we talked about it on All-In podcast, we called it EWS, Elon Web Services, right? That he struck these huge deals with Anthropic and Google. I don't even think people were thinking about SpaceX in the AI compute game, right? If you looked at the models as of a few months ago, it was connectivity, so Starlink, and then it was X.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 singular, never been done before. Just to put in perspective, 100,000 GPUs, that's easily the fastest supercomputer on the planet. That's one cluster. A supercomputer 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. We're talking about 19 days. Wow. N of one is right. Elon is an N of one. And his ability to secure supply, stand up the supply, deploy it in a way that's 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 were all at the macro hard data center and it was just very evident the amount of engineering that had gone into building these sites. You know, people always talk about Google and their ability to build a TPU and sell the TPU to Anthropic to generate revenues for AI. I think it's a pretty similar dynamic here with Elon able to secure power, build these sites faster than anyone else and also be able now to monetize it to this massive AI market that's ahead of us. If you look at the relationships that he's forged with a lot of his suppliers, be it Jensen, be it all of these different sites that actually want XAI as a tenant. His ability to finance these deals at very attractive financing rates relative to a lot of the other players 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, it's actually a very attractive proposition for a lot of folks involved. And actually, if you look at these deals in particular, Gavin, you pointed out, but they're actually monetizing perhaps better than other players in the space by selling this infrastructure, a lot higher. Google is obviously paying SpaceX a huge premium for this 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 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 at the end of the day, SpaceX can stand up compute 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 belief around this table 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 competition going on. On one end you have the hyperscalers who are building out that capability. Then we have AI dedicated clouds that are building out that capability. And now literally in a matter of weeks, we have a giant that's emerged in this category which is SpaceX. The question to you Gavin is can they consolidate this market? 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, he may emerge as the largest strongest player in the AI compute market.

Yeah, to that point, Brad, yesterday we were meeting one of our portfolio companies and we were talking about behind the meter and we're really thinking about it. There's only maybe two or three players now that can actually reliably engineer behind the meter data center and 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 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 we'll see, right? Hey, Brad. But this is just terrestrial. I do want to hit on and then you can flip it back on me. Talk to me. Okay. So let's assume that they continue to build out the terrestrial landscape. They continue to find buyers for that. Walk us through what this unlocks and how this is related to space data centers because I think 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 debate in the world. I heard Jeff Bezos say, you know, I think it's more like six years, but Elon's going to say three because if he says six, then it will take even longer. So say three and we may get it in four or five. But are space data centers integral and essential to the IPO? And what do you think the timeline is to either of you guys?

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 the gigawatts it costs, the dollars per gigawatt. Great. Walk us through the economic case.

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. So 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 and the power, right? But I think for most investors, yes. Right. 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 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 look with orbital I think the key thing is two-stage reusability. And beyond that rapid two-stage reusability. So today with Starship they've shown that they can successfully reland the booster. 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. 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 about going from $1,500 per kg on Falcon, somewhere in that range to 250, right, per kg, something lower. And the more that you can reuse the rocket, the more that price comes down. Right. Because you're just depreciating the cost of the launch. And eventually you asymptote to the cost of the fuel. Right. Assuming you can use a rocket for forever. Which will take a very long time for us to really achieve that. But 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. Elon did a great, 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 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. And the math that you get to before you account for things like 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 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.

When we look at this, okay, so we went through Starlink and we said okay, it just stands to reason we're going to have direct to cell on Starlink. 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 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 months ago, X.AI was competing. They're doing pretty well, but they've done something dramatic over the course of the past couple months, which is they bought Cursor, right? Cursor is 700, 800 people, was already doing incredibly well from a revenue perspective. Our own projections were that they could exit this year at up to 10 billion of revenue. So, they were growing very fast. One of the leading coding agents but they also had this incredible team with the potential to really build a frontier level model but they were compute constrained. So all of a sudden they get bought by X. X has massive compute that they can now train on. And when I think about the revenue in AI, 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 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, Gavin?

I would say what the last few weeks have proven is that Elon and their team can stand up all this compute. Actually, if you just went back one and a half years, they were behind in the race to stand up compute. They didn't have that many H100s. They brought in Colossus, then they brought in Colossus 2 at a scale much larger than anyone else. And now, as we gear for Vera Rubin, from a lot of my conversations, it looks like they've secured maybe up to 20% of Vera Rubin capacity, especially in the early days when these chips are very scarce, that they're going to have a lead on all of this because people think that they can stand up this compute better. So I think what the last few weeks have actually shown is that Elon will take a shot at hitting the frontier but if for whatever reason they have over-procured some capacity, this is a very scarce asset that they've shown that they can monetize at best-in-class margins and payback periods. I mean the irony is like you and I have been doing this long enough to know, I mean that's why Bezos built AWS. He had to build capacity for Black Friday. 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. Meanwhile he was digging the biggest gold mine in the history of the world.

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

Yeah, Google search might want to have a discussion.

Yeah. I want to come back to that in a 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.

What do you think?

Least talked about, 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, I think, 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 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, 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 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 are here to pump the IPO at 1.77 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 that it's higher from here? What's the probability? 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 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 institutional investors, it's a must buy, a must own. It's set it and forget it, right? in order to have a real bet on both the space and the AI future.

I mean, listen, I again, I think that you're going to have to 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 shows the average max draw down post IPO for like 20 companies from Facebook, Twitter, Alibaba, Shopify is over 50%. And so maybe that again we'll end this section 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. How do you as a manager try to manage that? Do you try to trade around the IPO? Do you set it and forget it? I would say from an Altimeter 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 a particular moment. But any thoughts on this chart or how you guys are thinking about it in particular? You obviously own a lot going into it.

50%ish.

Yes. No, it's by the way, have you ever seen that happen?

Can I give you a hug, Brad?

Can I just say one thing about the 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. 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 have chosen to own it. Now there's a new valuation and we'll see what they do. But just this is utterly unprecedented and we'll see.

I mean, it's hard to say that Anthropic's not up. Like after the revenue numbers they put up, after the Fable 5 release, and Mythos is evidently even better. But I just think that Noam Brown post from yesterday 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, because we don't have time to appropriately evaluate their intelligence before the next model comes out. I mean, this is a profound statement. Just imagine, I always say 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 of course you would think that over time that is superior to humans who are 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.

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.

Right. So that is a... You know, we saw when that was probably what really unlocked Opus 4.6. It was the first really long-running model that could maintain that context, maintain that memory, solve some of these longer running problems. For us, the signal was in January. 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 more useful. So, one of the things that the consensus going into this year, 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? I think the consensus at the time, at least on this podcast, the debate with Bill was that open-source models, cheap tokens, were catching up on the frontier, that perhaps these models were beginning to asymptote. 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. Frontier tokens are capturing the vast majority of all the revenues, and that in fact if you believe in the long-running capabilities and more compute allows you to do that, they may actually be extending their lead on some of these models that were built on distillation. So I just open it up to anyone around the table. What are your thoughts on whether or not we have challenged this thesis that cheap open source tokens are going to always close the gap on these frontier models, or are they extending their leads?

I think this 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, you can just see all of the revenue has actually just occurred at the frontier. And that's because every time we release the frontier, a whole new slew of use cases that previously we could have never tackled before, like coding, but also just you know, we've just been locked at our desks for the last day just hammering Claude because it's just fascinating the things that now we can do with Fable 5 that we just couldn't do with Opus 4.8 just a day before.

So what are some of those things man? I'm curious.

So I think it's really really good at multi-agent orchestration now. Anthropic released a blog post about six different agent orchestration patterns that they've talked about. But really, once you start being able to manage all these agents, the harness and the model itself are being fused closer and closer together, but the model can understand the extent of your work. So one of the things for instance, I just threw in like seven of our models and just said okay, I want to create a master view of my beliefs given all of these assumptions of all these companies, TSMC capacity like, and then produce me a report on all this stuff. And the model is able to reason through all of our assumptions. Like actually if you believe this, what are the contradictions? It was fascinating. Before we never do that, but now I think we're just step one into multi-agent orchestration. We're going to do this even further. I've also dumped all my notes into it and it reason across all my notes from the last 3 years and said here are some of your ideas that were consistent, here are the sources that were actually the highest signal to what actually played out. It was super fascinating. We've just blown through our limit.

Yeah. I would just say two things can be true. The majority of economic value may continue to accrue to the frontier, and man has it ever accrued to the frontier thus far and for sure the first six months this year, but the majority of tokens consumed in the world may be open source, and they are today.

We hear the same thing. We did an enterprise survey that we'll post of 300 companies, how which ones were optimizing. So these are folks who are 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. And then what is their expected use of frontier model tokens? 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 context of JP Morgan. If they're doing some back of the house stuff on customer service or whatever, they may very well use an open source model. Now, I think they're loath to use Chinese open source models. So they're waiting on US open source models to 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 routed there. That will probably be a majority of the tokens. But I think the really high value stuff, coding as an example, they don't want to write second tier code. I think the vast majority of that will continue to be on the frontier.

I will say there is a very, between spending time in the heart of like the West Silicon Valley and also spending time in Asia, there is like a very big deep-seated belief in one versus the other. Which is, if you spend a lot of time here, it's like all closed source, all traffic is going to go by way of this direction. And then you spend time in Asia, the overwhelming belief is that we're going to find the right model to the right workload and we're not going to overspend. I think the next year is probably going to be the most indicative of which way this falls. Because I think the reason why closed source models have captured so much of the value is because 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. Now the level of this intelligence has scaled so rapidly and we continue to push against the most economically valuable tasks which are coding and finance and all these knowledge work tasks. But for the long tail of tasks, if open source continues to maintain a six-month lag, we might actually see a lot more open source used for our everyday tasks that we might actually...

I'm not. Okay. Nor are we, but I'm very impressed by Misha and the team and what they're doing. I very much want a frontier open-source US lab to win. I heard you say recently and I believe it to be true: Nvidia, any day that they really wanted to, they already have some great open source models. They could absolutely build a frontier open source model whenever they chose to do it. 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 at that point in time, let's assume they get these long-running capabilities. Have the frontier labs now achieved something yet again that allows them to keep the stranglehold on the revenues?

Yeah, just double click on that for everybody at home. If they were to put an open source model out there, how does that impact the ASIC landscape?

Interesting. Clark, walk us through this chart.

Yeah. So I think one of the takeaways from spending time in Taiwan was there is certainly a lot of excitement around the next wave of ASICs. But I think it's a very clear moment now where Nvidia, it used to be an argument of Nvidia versus ASICs one or the other, total domination or one or the other. Now I think it increasingly, every year 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 look at the last few years, they've actually maintained their share very handsomely. Actually, if you accounted for the fact that Anthropic was not really using Nvidia, they probably actually gained share. So I think what was very interesting though was a new class of accelerators or ASICs, MediaTek with their new V8T versus Broadcom's V8I for TPUs, actually was a big topic of discussion. I think for ASICs, the argument now is that more and more will look custom to the actual workload, and that is one vector that people are moving in. Versus Nvidia now has kind of shown itself as the predominant provider of compute to a lot of the world. For internal workloads, perhaps they will go more and more custom and more down the stack. I remember one year ago when it was kind of a Broadcom or Nvidia battle, it seems there's a lot more nuance now to what type of accelerators will fit which workloads, customers, and business models. I thought that was a new realization.

Yeah, I was just shocked. 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 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 OpenAI gigawatt and you know Nvidia has 10. Broadcom has 10. AMD has 6 and they have warrants. And then Cerebras, our shared portfolio company, has a gigawatt. And that is what's on paper. What actually gets deployed, let's see. I will be very surprised if that 10 out of 27, what's that math? Let's see who's best at math. What percentage market share is that? 30%. I'll be very surprised if that is where they land. I think that is an extremely unlikely outcome, 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, 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. One of the most surprising things to me in this ASIC landscape, I would say Meta and Microsoft have been probably disappointing.

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

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 work. And I think that $300 billion is low, man. I just think it's low.

For sure. I would say consistently, Elon's been taking the over. Sundar has been taking the over. Sam, Dario, Dario did the podcast with Dwarkesh 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 $300-400 billion of revenue by 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 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 $400-500 billion by next year and a path to trillion plus by 2029, then the math works.

And we got to keep in mind that half of the spending is there for training, maybe a little less than half. What is it, Brad? It's probably depends on the lab, but 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 works. There's still a prisoner's dilemma where if you opt out, that may be an existential decision for sure. And I think coming into this year, going back to what narratives were violated, I think into this year everyone expected token pricing, the price of compute, it's all deflationary and it will be a smooth line deflationary over time. But I think this year what we've seen is the opposite. It all comes back to supply demand. The demand side of the equation seems to be far outstripping the supply. I think you look at the deals signed by SpaceX and others, the monetization rates per watt are increasing. And look, that is on a pretty small base of users. Alex at Whale Rock, he has this great way to frame it: less than 0.2% of people on Earth are actually using AI in an agentic way. I'm not a technical person, but I'm consuming 500 CPU cores in a VM instance, 5 GPUs 24/7. If you draw that out to any meaningful percentage of the population, we're going to be in this kind of shortage environment for some time. So I think that is all positive for this ROI question.

Man, Gavin, 100:1 watt CPU to GPU ratio. Kind of a workflow. Of course. Fine, fine. I'm being smart with my spend.

Good. I will say also that ratio of 300 to 1 point, call it 1.2, 1.5. 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 willingness to pay for these tokens. And actually the monetization per gigawatt is increasing from, call it $20 billion in the best cases at the beginning of the year to now like $30 to even pushing $40 per gigawatt. All of that is a very heavy fixed cost base, but all of that is pure margin flow through now. As we scale, the willingness to pay for all of this, and now all of this stipulated by everything we're talking about of how much is open source versus not and all of these different flows. But really, as we're climbing this curve, the revenue might actually outstrip our fixed cost base by a significant amount. And I think that's why all the labs are pushing the gas to the pedal, because they all see that if we continue this curve within 3 years, we're just going to be so short on all the computing.

Yeah. And Clark, I think the point you made is dead on because you want to own asset heavy businesses in inflationary environments and token pricing is going up and supply demand is tightening. So, totally agree. As we begin to find our way to the exit ramp and wrap here, one of the things, you and I have been doing this for a long time, Gavin, couple decades. You may even sketch longer than me even though I'm a little bit older than you. I always like to do a market check because I find a lot of times that analysts come on these things and they talk their book. There are a lot of people who listen to these, retail investors and others, and it's just kind of like what do we really think? So I always characterize as kind of small, medium, and large. Like what am I doing? Do I have small exposure? Do I have medium exposure? Do I have large exposure? And if you look at what's happened in the markets, semis rip this year. I mean, you've been doing this a long time. I've never seen it before. I've never seen the doubles and the triples across the board like we saw, but there's been huge dispersion in the market. Internet's down 16%. Software is down 8% on the year. SPY and NASDAQ are up, but really up because of their components that are related to AI and compute. So the market itself has kind of struggled. Meanwhile, if you were in the stuff that we were invested in, we've all done pretty well. I think 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. But that showed up. We just had these huge months in April and May. For us, because prices came up so much, because I have some worry about geopolitics, the macro backdrop with what's going on with inflation in the short run, and just needing a little consolidation in this market to answer some of these questions, because now expectations are higher, we dialed back from what I would call large for Altimeter to something kind of like medium small. Again, it's never all or nothing for us. It's like what is the risk-reward at a given price. So we think this is maybe going to be a period of consolidation on way to much higher highs. Curious just how you run the book, how you think about it like a portfolio manager.

I would just say we're heading into a seasonally weak period with all these spheres. AI has actually been seasonal for the last three summers. Token consumption has plateaued, slowed down, and that's because college kids are big AI consumers and they don't use as much AI. Hopefully they're all using it to learn and not cheat. But that may happen. It may not happen because the 15-year-old is building swarms of agents, building a SpaceX model. He's going to the SpaceX IPO with me at the exchange on Friday. But he had to build an AI model using AI agents. He had to build a DCF before we go to the exchange. He is mesmerized. He is absolutely, it's extraordinary what he's building. So he's one kid who's not using less compute. He's burning it. 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 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, I just think there's reasons to look around, be careful, be 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 the market may need to take a breather. But when I think about what Noam Brown said, and when I see the capabilities of Fable, it's just hard for me to get too bearish. I mean to me, we have two of the most extraordinary guys of the next generation sitting in the room. At Altimeter, 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. But for the guys who are newer to the business, they might think this is the way that it always was. And this line, the steepening of the line of creative destruction, the steepening of the line of scale advantages, I always believed it 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. To get to the first trillion took over 20 years. In the last seven, we added another trillion, and that added $17 trillion in market cap. The forecast now is 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. Not seven companies, three companies, and in half the time. So I would say that 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 make sure America wins and that we evolve the social contract, lift the floor, take everybody with us on this ride. But it's a really exciting time to be doing what we're doing. It's fun to be doing it with you guys.

Thank you.