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.
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?
Sure. So great to be here. Thank you for having me. I thought we were going to call it BGGB, 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 those variables go, but one is you guys have this chart. Did you post this on X?
I did. I did before and then we also included a new addition with XAI's new deals as well.
Yeah. So, Clark, who I've known for many years, made a great analysis here and he shows that XAI's deal with Google for cloud computing generates more operating profit per gigawatt than Anthropic, than Meta, than Google, than OpenAI. Their deal actually with Anthropic also generates probably more operating profit than anyone but Anthropic. And so you know your colleague at Altimeter, 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. 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 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.
And so I think, you know, everybody should run their own math on that, but that is a massive variable. Yes. Truly massive variable. The second thing is you know we have a chart and it's wildly out of date now. It's kind of freaking amazing. This chart is I think from 10 days ago but in the 10 or 12 days since we made this chart which shows the paro curves for opus 4.7 for coding for codex from OpenAI. 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. But what the paro curve shows is how much intelligence you can get for a given amount of cost and I do think all revenue will accrue to the paro curve, at least kind of frontier model revenue will accrue to the paro curve and this is paro curve for coding. And what I think is so impressive is that you could see in the chart that composer 2 was paro dominant or 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 better than I do. A vast amount better than I do. But my understanding is that cursor and Anthropic 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 used Kimi K.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 paro dominant with composer 2.5. Now it's on their own benchmark, 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 chinchilla optimal or beyond chinchilla optimal with reinforcement learning, you know I think it suggests that XAI and SpaceX have a shot of being a real player in coding.
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.
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.
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.
Yeah. Here's what I just say very simply. I travel with Starlink. 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, they're going to have the cheapest cost per gigabyte or megabyte delivered. And better, faster, cheaper has been a winning formula. And so 50 billion, that's 0.3% penetration of the global telecom market. Now, maybe there's some deflation with Starlink pricing, but that's the way I'd frame it up.
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. So I think they are the number four or number five hyperscaler today after the Google deal? 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. CoreWeave 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 are probably 50 Neolabs being funded in Silicon Valley right now as we speak because of the shortage in compute. Absolutely. So that's kind of crazy in 30 days. That's just extraordinary. What I would say is there is a belief that these data centers are commodities. And I do not share that belief. 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. Everyone else was trying to make an electric car like an internal combustion engine car, and he thought about it differently. And I think he looked at data center design from first principles, and he designed something fundamentally different. And I did actually ask the team. I said, 'Hey guys, maybe 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 more differentiated than you perhaps realize because what you're doing is so logical to you, but maybe not logical to everyone else.' And that's how he was able to do it in 122 days.
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.
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?
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 Amjad Masad posted something very interesting, the founder of Replit. 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 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 necessary for the IPO valuation, but it's certainly important and it's well, maybe another way to say it is 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. And the ability to scale it up to consume 10% of global GDP. But 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 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.
Yeah. Just very simply, I mean, just to say, it cost $60 billion to put a gigawatt on the ground today. And we'll call it 35 of that is 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. 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 billion that may be deflationary over time, but what we need to consider is the reliability and the maintenance. And so as long as everybody can do the math, but as long as these satellites in space aren't failing at an astronomical rate, the math maths. And by the way, we know GPUs melt and lasers fail. We know this happens in data centers, particularly during big training runs. And yeah, I mean GPUs melt. 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.
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?
Right now, so composer 2.5 was paro dominant 12 days ago. It was trained on the Kimi 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 scaling laws that that 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 to me is 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 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 Valley may not 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 this way to monetize compute that gives you this call option that you can pull all that compute in-house 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 thoughts, Clark, on what you think is being overlooked or areas that you think are misunderstood about the business today?
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.
By the way, I do think it is important. Grock 4.3, I think the cursor if they acquire it may end up being very important. But Grock 4.3 was on the paro frontier as of 10 or 12 days ago and 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, Google with Gemini 3.1 Pro, and then the rest of it was dominated by Anthropic and OpenAI. But they were on the paro frontier. Now we'll see what they do with cursor.
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.
I think that's the thing that's least talked about.
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.
