SpaceX S-1, Anthropic Revenue Booms, OpenAI Cracks Erdős Problem | Diet TBPN

We have a massive show. There's so much tech news. People said the technology industry, they were out of news. They weren't. There's plenty of tech news.

They lied. They lied to you.

All over the Wall Street Journal. AI companies are duking it out for prime placement in the journal. SpaceX got top billing in the journal with the IPO filing. SpaceX sets its IPO in motion. The SEC filing starts Move to raise tens of billions of dollars in record debut. We've talked about this a lot on the show. Clock is officially ticking on SpaceX's huge stock offering. What are you laughing about?

Ryan says, "I knew Jordy couldn't do this suit two days in a row." Did I not do it two days in a row?

Nope. Haven't done two days in a row in months. We can roll the tape. I mean, after reading that piece about us, I feel like some brand differentiation is actually to our benefit since some people can't tell us apart. And so I've become, a fan of the split in—

Casual Friday, Thursday.

Yeah, of just a casual look over there, more buttoned down, buttoned up, button left and right over here.

Someone's gotta be buttoned up.

Someone's gotta do it. SpaceX on Wednesday revealed new details about its financials and how Chief Executive Officer Elon Musk will try to grow a sprawling enterprise dedicated to advancing cutting-edge technologies in space and back on Earth. The company disclosed the information in an investor prospectus, Publication of the document sets SpaceX on course to potentially raise $80 billion or more from a stock sale as soon as next month. The rumored date is what, June, July?

Was it June 12th?

June 12th. That's just 20 days away, basically. They're gonna beat out Saudi Aramco that raised $26 billion when it went public in 2019. Musk has touted out-of-this-world objectives for the company from deploying a huge number of artificial intelligence satellites in the future to colonizing Mars. Texas-based SpaceX has distinct businesses ranging from rocket launch to satellite operations to a nascent AI unit that is racing to catch up with rivals. Founded by Musk nearly a quarter century ago. Yeah, it has been a long time. SpaceX revolutionized the commercial space industry. The company has grown from a startup with a handful of employees that almost went out of business to one of the world's most valuable private companies with over 22,000 workers as of March 31st. It controls technologies that competitors and even nation states haven't been able to fully match. SpaceX reported its revenue last year at $18.67 billion, and Dan Primack had a post saying that the business was smaller than he expected. He's going on CNBC today to talk about the IPO, has had a couple interesting takes. People are going back and forth. Overall, the reception has been, "The S-1 is an extremely enjoyable read," Kevin Kwok. Says it's the most enjoyable S1 read in a long time. Reads so easy, like sci-fi or fiction. And, uh, it's kind of the perfect—

it's kind of the perfect post, or just regular, because if you're pro-tech, you like space, you're excited about space, that could be a positive.

Yes.

But if you're— if you're a bear, yeah, you can say it reads almost like science fiction. Of course, the best ham slide ever?

Probably the best TAM slide ever. Sawyer Merritt has the screenshot here. SpaceX in IPO filing: We believe we have identified the largest actionable total addressable market in human history. We estimate that our quantifiable TAM is $28.5 trillion, consisting of $370 billion in space from space-enabled solutions, $1.6 trillion in connectivity across $870 billion in Starlink broadband and $740 billion in Starlink mobile, as well as additional opportunities in enterprise and government. $26.5 trillion in AI across, $2.4 trillion in AI infrastructure, $760 billion in consumer subscriptions, $600 billion in digital advertising. That's massive.

Well, is that for X? I don't know.

The idea—

so, so everything else is more believable. Everything else is more believable to me than X getting meaningful digital advertising penetration.

Yeah, I guess the time matters here because a lot of these markets aren't this big currently, I think. I don't know. But I guess over time, if you think about the next 25 years, the next 100 years, I don't know if these are inflation adjusted, but there's lots of things that could happen. For illustrative purposes of sizing our addressable market, SpaceX excluded China and Russia from global estimates. I feel like you might wanna put in China and Russia over the next couple decades. Who knows? Maybe we become best buds with both countries. You know, anything can happen. World peace might come and that's going to expand TAM. That's an economic incentive for world peace. I like to see it. There were some beautiful photos that were shared in the start of the episode. Lots of pictures to start and then it gets very text dense. But the photos were— I liked them. I thought that they were unique. I hadn't seen them like that often and they felt like they were kept in the back pocket for a while. And they, I don't know, they just like remind you of SpaceX. It's like a beautiful thing. Dan Primack says, incredible that Goldman beat out Morgan Stanley for the SpaceX IPO. Lead left. Given that Michael Grimes returned to Morgan Stanley in part for this deal. Of course, Morgan Stanley is on the deal, but that is— it is a big win for Goldman that DJ Space X is at the helm. Goldman Sachs Co., LLC lead left in the joint bookrunning managers, but everyone's getting a piece of the SpaceX IPO at this size. Will Bitski says, shout out to the Goldman analyst that was ritually sacrificed to win this lead left IPO. It must have been an incredible amount of work. It's not just the biggest IPO of all time. It's not just this incredibly complex structure with multiple businesses. It's also you're reporting to Elon Musk. Elon Musk is your client, and he's going to ask for things probably more aggressively than anyone who's a CEO of a company that's going public. Lots of winners from the SpaceX IPO. Luke Nosek is a huge one. He was at Founders Fund, co-founded Founders Fund with Peter Thiel. His next role will be leading— this is from a long time ago— he left to start GigaFund, which was billed at the time as a new investment firm that initially will be focused on raising capital for Elon Musk's SpaceX, a Founders Fund portfolio company where Nosek is a director. And so David Kwon says, today I learned Luke Nosek left FF to start a fund exclusively focused on investing in SpaceX. There are a few of those that we're hearing about these days, of course. Exclusive does not mean 100% of the capital went into SpaceX. It just means that they were very, very focused on that. GigaFund has a lot of different companies in the portfolio. We've had a bunch of founders on the show who have raised money from GigaFund. But SpaceX is where Luke is a director, deeply involved, and has focused on participating in many, many rounds. And so conviction will do that to an MF, says Pocket Jacks Capital. Lots of big winners. Frank asked Codex for SpaceX fair value based on the S-1. Should be an interesting build-up to the IPO. What was the result from—

Said, Lance, around $1.1 to $1.5.

It's not bad. That's not bad. Bull case gets to $1.7 to $1.9 if investors assume Anthropic sticks, AI infrastructure margins are strong, Starship unlocks major new markets, and public market scarcity drives demand. But $2 trillion means the market is effectively assigning something like $800 billion to $1 trillion to the AI orbital compute story on top of an already rich Starlink valuation possible as an IPO mania print, but that's not what I'd call for fair. So we'll see what happens. I mean, the big news was the partnership with Anthropic where Anthropic is spending over $1 billion a month, I think. It's ramping up.

$15 billion a year.

And that's huge for SpaceX given that they did $18.5 or something last year. This is a huge jump up in, I mean, they have to be one of the biggest neo clouds like overnight with this.

Yeah, I was trying to find—

Huge, huge.

I was trying to find some of our conversations from last year where we were— xAI and Groq was growing, but maybe not at the rate that— not close to the rate that would require that much infrastructure.

Yeah, finding product market fit on the actual distribution side. Obviously, we love X, but it's not the biggest platform.

Yeah, it wasn't— it's certainly a shoot for the stars. And if you miss, you have a pretty great NeoCloud business, right? Anthropic has to pay way above traditional NeoCloud pricing for this compute. And so ends up being a great outcome for SpaceX.

Peter Haag says, just reading the SpaceX SEC document, one thing that sticks out is the capital spend on AI is 3x that on space. It's an AI company with some rockets, which is a wild, wild, pivot at the, it's the 11th hour. You know, this has been a rocket company for 20 years or 15 years, then an internet company with Starlink, but that was still so tied and so clear and so quick to get to like a logical link. Like you needed the launch capacity to build Starlink. And so you had this new capability, satellite internet, it was amazing. And it went from idea to launching the satellites to consumers actually using it when they're traveling, camping off the grid, real, and then showing up in planes and all sorts of different applications. It became very, very relevant, very real, very quickly. And the Colossus XAI, that felt like a different company because it was, but it has just become so, so, so big so quickly.

Yeah, and looking back at the plays Elon and his investors have made around this over the last year, right? There was that, felt like somewhat of a coordinated effort Beginning of this year or late last year when suddenly everyone started talking about space data centers very suddenly. Remember Gavin Baker?

Yeah.

Started coming out talking about it. That's around the time when they sort of floated the— December of last year, floating the idea of like what the potential valuation would be. Started building that AI narrative, started, you know, made a play for Cursor, you know, partnered with Anthropic even though, you know, only a few months ago they were, much more combative.

Yeah.

And so calling—

so yeah, he's, you know, I think this is why Elon has been able to accumulate so much capital is like he is pretty much the best in the world at like making, just making plays. Yeah, making plays and doing whatever it takes.

Yeah. So the most recent play unrelated to the news that made the front page of The Wall Street Journal, Anthropic revenue surges, set to post first profit sales seen reaching $10.9 billion in second quarter. Up 130% over previous quarter. Truly in the title of the— in the actual URL of the Wall Street Journal article, they call it mind-blowing growth about to propel Anthropic to its first profit. Absolutely fantastic execution. So Tom Brown, co-founder of Anthropic, says we're expanding our partnership with SpaceX and we'll be scaling up GB200 capacity on Colossus 2 throughout June. Appreciate Elon Musk and the team helping us find good homes for the Claudes. Is Claude plural? I thought it was all one Claude and the purpose of Anthropic was to build Claude and Claude will eventually build Claude. But I guess you have multiple instance of the instances of Claude running on different servers on different GB200s. Anthropic's Q2 revenue is set to increase by over 200%. Will post an operating profit The AI will never be profitable group is in absolute shambles right now. There have been a lot of folks who have been just doubting time and time again, will this ever make money? Will this ever make sense? And Dylan Patel sort of laid out on the Dwarkesh Patel Show this idea that at a certain point, the leading models might actually be able to raise money because they're— or raise prices because they're driving so much economic value. Semi Analysis also put out a table showing for particular workflows that would take them, you know, $1,000 of human time that they would have to hire more people for, they were able to use AI and actually get an equivalent result for a 10th of the cost or a 100th of the cost or even, you know, a 30% savings sometimes.

Anyway. Says, can someone check on Gary? February 23rd, 2026, he said, turns out GenAI was a scam.

I had to check the date on this because this seems like something he would've written in like 2024 and I would've been like, ah, okay, yeah, maybe the usages are a little limited. Maybe there is some sort of wall here, the data wall, or you know, maybe we won't be able to, you know, maybe we'll need new paradigm. But to write this in 2026 when we're in like the fastest period of acceleration in terms of actual value from these models is, Pretty, pretty remarkable. I'm interested to see where he goes from this. Is he going to double down? Is he going to stick with this? It has been a couple of months since I think—

I think there's— I think the entire crypto boom and NFTs in particular just broke a lot of people's brains.

Yeah. And VR metaverse too.

Metaverse is another thing that was like overpromised and underdelivered. Metaverse, yeah, potentially even more.

Yeah, yeah, yeah. There was a lot of discussion about This will destroy Hollywood. This will destroy movies. Like, everyone's—

With the metaverse, there was never a moment where you could use a product and have a mind-blowing experience.

Well, without paying for it. Like, you had to buy it.

No, no, I'm just saying, like, period.

No, no, no. The Apple Vision Pro demo, like, there was a day you called me and you were like, why is everyone losing their mind on the timeline over the Apple Vision Pro? Do I need to buy one of these? And I was like, eh, it's kind of like a preview. It's not like— perfectly there. I like it, but it's—

I don't even think I— I don't think you're remembering correctly because there was no moment where I wanted to buy one.

No, no, no, you didn't want to, but you recognized that it was the current thing when the Apple Vision Pro launched for like that week when everyone got them delivered and they tried them. There were a lot of people that they had Vision Pro psychosis. Vision Pro psychosis. A lot of people had NFT psychosis, all sorts of psychosis. We'll see how the AI psychosis develops. It goes both ways.

Yeah, but anyways, comparing it, anyone can have a pretty wild experience with AI.

Yes.

In, you know, on like a ton of different services.

Yeah.

You could never do that with the metaverse.

So Lisanne Al-Ghaieb is contrasting Gary Marcus's Substack post with what's happened in the AI industry. Anthropic valuation up 173% since the start of the year. Posting profits in Q2, according to the Wall Street Journal. OpenAI valuation up 67% since the start of the year. And OpenAI general purpose model solves longstanding and well-known Erdős problem.

I believe it's Erdős.

Erdős. Erdős problem without a scaffold. And so there was a lot of questions about, you know, how hard is it to solve these problems? But fortunately, we have Tyler Cosgrove, who's going to take us through what actually happened with this solution to this math problem that people are very excited about. Noam Brown said, today we are sharing that a general-purpose internal OpenAI model achieved a breakthrough on one of the best-known combinatorial geometry problems. Less than one year ago, Frontier AI models were at IMO gold-level performance. I expect this pace of progress to continue. And Siddharth Ramesh, I don't know if he was joking about this bet, but he says, I have lost my $30,000 bet. That AI would never solve the planar unit disk.

Yes, I believe that was a joke.

That's a narrative.

That's a joke.

Yeah. I think if you go to the talk—

He jokes around a lot, but no. But a lot of people were surprised and a lot of people were excited about this. So take us through what actually happened.

Okay. Yes. So I can basically go through like a simple explanation of what the problem actually is.

Okay.

So just for some context, Paul Erdős, kind of this legendary mathematician throughout the 20th century, he basically proposes— I think the number is like a little over 1,200 different, like, little problems. These are the Erdős problems. People talk a lot about these as, like, goals for AI to solve. And you've heard, like, over time there's been kind of, like, small iterative kind of solutions to a lot of these problems.

Yeah, sort of like collaborative, a mathematician working alongside AI model.

Yeah, and sometimes—

Or an easy one, just getting—

There's, like, a main kind of place where all of the solutions go. So sometimes people will find, like, AI will, like, find a different paper that wasn't actually put on the website, and then they're like, oh, AI solved it, but it's honestly true. But this is kind of the first time we've really seen kind of a big step change. Like, this is actually a new solution. This is using like, you know, kind of novel ideas here.

Yeah, it doesn't exist in papers out there already.

So this was problem number 90. So I can kind of read—

Please.

—read the question, then I can explain what it means. So it's, does every set of n distinct points in the real plane contain at most n to the 1 plus O of 1 over log log n many pairs which are 1 apart. Okay, so like what does that mean? Basically we have like the real plane, right, 2D, and we have a bunch of points on it. What is basically how many like pairs of those will be basically 1 unit apart, and what's like the max number? Like how do we basically organize those points such that we have the max number of them, right? So— It's not just a grid? No, so you would think that, but I can basically explain why. So let's kind of like formalize this better. So we have U of n, right? And this is basically the largest number of unit distance pairs among n points in the plane. Okay, so basically like we're thinking about like how do we solve this? Naively, it's like, okay, what if we just take all the points? We have n points. We just put them in a line. And unit distance apart, right? So it looks something like this. Right, so for this example, we have 4 points, but it doesn't matter, it's just n. So 1, 2, 3, 4, how many pairs are there? There's 3. Right? Okay, yeah. So basically this scales with n 1. Yeah. Right? So you would have a billion points and there's 9999 whatever. N 1. Yeah. Okay, so now if we put it in a grid, what happens, right? So if we have a square grid here, there's 9 points here. And then how many pairs are there? I believe there's 12. And basically as this number scales up, it's still linear. So it's 2n. Okay. Basically if you do a billion points, it's 2 billion pairs. 2 billion pairs. Yeah. Okay, so then basically specifically that line, the line represents— yes, yes, because it's one unit distance, right? Because diagonal doesn't count because it's not one. Yeah, it's not a unit distance. Got it. So, so then, um, okay, what's the next thing we can do? Um, the next kind of configuration is, is what's called the, the lattice construction. Okay. Um, and so if we can pull up a picture of it, it's this kind of crazy looking grid that has all these, uh, super like intricate lines in between. You can see it on the, uh, this is from the OpenAI blog. If we can pull it up here.

Oh, I think I saw this.

So this is what it looks like. Okay. So if you can like zoom in on any of these points, you see that, you know, it somehow— it looks like a grid, right? Yeah. But there's not just kind of pairs at the edges, right? There's like way more. Okay. So this scales at n to the 1 plus O 1 over log log n, right? This is basically the best kind of example that we know works. Yes, but not a proof. We know we can find this, but is this the upper bound? We don't know. Okay, so this is basically the lower bound. Okay, so then the question is like, we have the lower bound, which is that this is the best one we found. Yep. This is the most number of pairs, and then we've theorized that the high bound, upper bound, scales with n to the 4/3. And then so Erdős, the original conjecture that he thought that the upper bound is still going to be less than n to the 1 plus O of 1. So this means O of 1, it's like as it scales, as n scales to infinity, right? So O of 1 basically scales to 0. It goes to 0 as n goes to infinity. Basically OpenAI figured out that this is not true and that there actually are some, there are some n's for which this kind of max number of pairs is greater than the original Erdős conjecture. So for infinitely many n, this is not for every single n, right? So it's not like 5 points or whatever, but there are infinitely many n's for which this is true. That it's greater than n to the 1 plus some constant. Okay, so that was basically the big thing, right? This is like, you know— Huge if you're into math. Decades-old problem, right? This is an incredible thing. Terence Tao was like, "Wow, this is incredible." But yeah, that's basically the overview of the problem. But yeah, it's very exciting because this is not like a math model. This is just internal model. General reasoning.

You could say it's generally intelligent.

Yes, I think you could say that. And then I think it's interesting because from public perception, it seems like this didn't take that many tokens. This was not millions of dollars of inference time. Sure. Maybe something like hundreds to thousands of dollars of inference compute.

That's very interesting because we were talking about like Goren's conjecture about like novel ideas coming from just like brute forcing different connections between things, and this is more token efficient.

Yeah, this is not just taking some solution to a different Erdős problem and just like spamming it on all 1,200 of the problems and, "Oh, one of them works." This is like kind of a new novel idea, like maybe this solution is The way that they found this, it's like super complex. You can read the proof. It's like 18 pages long. Wow. I don't really know what it means. But like there's a lot of the mathematicians are saying, okay, this actually could be useful to a lot of other problems. This is like a new way to do things. Interesting. So I think it's like very exciting. This is like maybe similar to, you know, AlphaFold moment or something where now this is like a real kind of step change in math capabilities.

The other news, rumors about OpenAI is being close, closing in on the IPO filing. And that pushed out NVIDIA's results, which is normally something I would expect on the front page, but there was too much AI news. NVIDIA results skyrocket on rise of AI agents. We talked a little bit about it yesterday, but the big news is that they're doing an $80 billion share buyback authorization. And Tae Kim, Tae Kim was bullish. People were wondering, where he would sit on NVIDIA. He laid out a pretty convincing case. You can go listen to the interview. It aired yesterday on TVPN. Let's click through the timeline, see if there's anything that we missed before we jump off. DJ Khaos has an idea here. Found a $10 bill. It took 5 seconds to pull— to pick it up. That's $63 million in annualized ARR. This is the thinking you need to be deploying.

I didn't know that Messi, the football player, had a Prime copycat called Moss. Moss. And it's shutting down after 23 months in business.

I wonder if that has to do with the logistics of shipping internationally, because he is an international icon, but setting up distribution and retail presence across many countries very quickly. It's not quite as easy as dropping it on Amazon and flying off the shelves. A lot of those are sort of one country by country. And I wonder if that has a piece of what happened. So this is shutting down fully. Moss+. Interesting. Well, Mitchell Baldridge recommends setting up a Vanguard account, not Fidelity, not Schwab. Vanguard. Smart advice, you might think. They do have the lowest fees. If you want to get up to speed on Vanguard, listen to the latest episode of the Acquired FM podcast. But he says, wrong, it's not because they have the lowest fees. It's because their interface is so awful you will never trade. It has made his clients millions.

Let's close it out with this video. What you got? Playing Catan with a billionaire. Yes. I think you'll like this one.

What is this face? Is this a face filter or a background replacement or both? Something funny is going on here.

Face filter. Okay, face filter. My turn.

I'm going to put down a data center. That's against the rules.

How else am I supposed to AI generate my Christmas card? Not popular. I'm not joking.

The way you walk, the way you understand me. Do you like it? No, it's blocking all the land.

Wait a minute, are you one of those paid protesters?

The way you move, the way you just whisper.

Next turn, I'm gonna use 7 water on my data center. That's not how that works.

That's not a resource.

How else am I supposed to The water stuff is really, it's so interesting that no one has moved to energy, like natural gas. There are natural gas turbines that would be opposed and yet people are focused on water. Stop giving them ideas. I know, I'm doing their job for them, I suppose. But it's like, I don't know how, I don't know why the water. I think it's just because like water's delicious and electricity is vague and abstract and you don't think about it. Like you can visualize a glass of water, It's hard to visualize a battery in the same way. But yeah, the— what is it? It's like dozens of LLM queries every day for a full year is equivalent to eating a single almond, something like that. But Matthew Ball is back at Xbox. Congratulations on the move. He announced it yesterday. We're going to try and get him on the show because he's one of my favorite people, favorite authors. If you haven't read his book or his blog, he has a fantastic mind for future of technology. And he— I could not be more optimistic about the future of Xbox with him on the team. Tae Kim says this hire is a literal game changer. Matthew Ball knows gaming and what needs to be done. This news makes me the most bullish I've been on Xbox in 7 years. And I completely agree.

And to close it out, the White House is awarding $2 billion in grants. Oh yeah. $1 billion of that going to IBM to 9 quantum computing companies and taking an equity stake. Equity stake? Other grants, but we're taking an equity stake. It's an investment.

It's an investment. It's an investment. And you, American taxpayer, will now own a basket of quantum computing companies. Spaghetti computing is up. That's not spaghetti computing, it's rigetti computing.

Spaghetti computing is up 30%. I'm gonna call somebody and be like, who came up with that?

That seems like a Trump, like something he would say. I created that. You created that?

Okay, just now. I'm sure I'm not the first person to think of it, but—

and we will see you tomorrow, Friday. Goodbye. Well, smoke— love you.

Have a wonderful evening.