Moonshots with Peter Diamandis
SpaceX’ $75B+ Historic IPO, GPT 5.5 Outperforms Polymarket, and AI Solves 80 yr old math problem | EP #257
23 May 2026
Chapter 1: What are the implications of SpaceX's $75 billion IPO?
SpaceX filed for what's expected to be the largest IPO ever, $75 billion being raised at a valuation probably north of $1.75 trillion. He's about to have a currency to go on a shopping spree.
That sentence is so out of band with any point in human history. Anyone out there doing a startup, there is capacity for a thousand unicorn transactions. Remember, unicorn is called unicorn because it's supposed to be extremely rare.
GPT-5.5 is now beating prediction markets. on forecasting the future. It beat polymarket crowd predictions for the Super Bowl. This is the worst psychohistory models will ever be.
The concentration of wealth effects from this would be insane. The financial singularity. So this was a problem posed by the famous Hungarian mathematician Paul Erdős about 80 years ago. Now AI has just solved it. Not only was it faster, not only was it able to brute force, but it was also smarter. This is like a much bigger moment in history than just solving a math problem.
Hashtag solve everything, Peter. We're seeing it. Now that's a moonshot, ladies and gentlemen.
Welcome, everybody, to another episode of Moonshot. I'm here with my extraordinary Moonshot mates, Salim, the father of organizational singularities. You're spawning singularities everywhere, buddy. Alex Wiesner-Gross, our in-house polymath. Dave Blunden, our wizard of AI investing. I'm Peter Diamandis, your host, and hopefully your abundance whisperer for an optimistic future.
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Chapter 2: How is GPT-5.5 outperforming traditional prediction markets?
You know, we've loaded the show today with extraordinary stories, hopefully stories that get you excited about being a builder, literally starting to build before this episode is out. Gentlemen, good to see you all. I have to ask our normal where's Waldo question. So today, Dave, where are you, buddy?
Back at Stanford. Had a whole bunch of really fun meetings with AI founders here.
Awesome. And Salim, I know you're not home because you're never home. Where are you today?
No, I'm in Brazil like we did yesterday. So I'm still here till tomorrow and then I fly back.
Okay. Well, and Alex, you and I are in our normal haunts. That's right. Yeah. Amazing. So let's begin. You know, we've stacked the show today.
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Chapter 3: What does AI's solution to Erdős' conjecture mean for mathematics?
Here's a quick look and preview of what we're going to be covering. SpaceX just filed their biggest IPO in human history. It's extraordinary. And later today, after we record this episode, we've got Starship V3 scheduled to launch. OpenAI is just disproved a conjecture in the mathematics realm. We'll be talking to Alex about what that all means.
GPT 5.5 is now beating prediction markets on forecasting the future as well. ChatGPT just became your financial advisor. A lot to cover. Our mission, keep you optimistic, informed, and ready for the supersonic tsunami heading our way. So with that, let's get started. Our first story here is, in fact, the SpaceX IPO.
SpaceX filed for what's expected to be the largest IPO ever, $75 billion being raised. at a valuation probably north of 1.75 trillion, the biggest in history, you know, over 2.5 times that of Saudi Aramco. Elon is maintaining his super voting rights with insiders controlling 86% of the voting power. And I love this. SpaceX's IPO prospectus says it expects an addressable market of $28.5 trillion.
I mean, that's quite a TAM. Dave, let's go to you first on this one.
You know, the TAM is just under the size of the entire US GDP, and I'm sure they landed it We don't want to claim to be bigger than the entire U.S., so we'll be just one notch below. But Eric Brynjolfsson hosted Maura and I for dinner last night at his house. Eric is a professor of economics and AI at Stanford HAI. That's the AI lab of Stanford. And he was the first guy to mention this to me.
And I was like, come on, $25, $28.5 trillion TAM. So he was going off on, yeah, but there's no way to disprove it. There's no reason it shouldn't be true. You know, Elon, remember Elon's core thesis is that we can 10X the global economy in 10 years. Most people think it's possible, but it's longer than 10 years.
But regardless, if the global economy 10Xs, then his TAM should easily fit within 25 or $28.5 trillion.
I looked at the breakdown of how he got to $28.5 trillion, and it's interesting. So $870 billion, you know, just a mere bit under a trillion is Starlink's business. $740 billion is Starlink's mobile unit. $600 billion is their digital advertising market through X. $2.4 trillion is their AI infrastructure. And get this, $22.7 trillion is kind of come from MacroHard.
If you remember, MacroHard is their partnership with Tesla where they want to emulate all digital work and create an AI-run software company. So pretty spiffy. I mean, a trillion here, a trillion there. It adds up to a lot, a lot of money. Alex, what do you think of it?
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Chapter 4: How might AI influence the future of financial advising?
The other thing, the tariff fab, where's the tariff fab in the prospectus? Maybe it's the same story. We don't need to promote things that are still hypothetical. $1.7 trillion is enough for now, maybe? Yeah, there were a bunch of assets that were shared. MacroHard itself was, if I remember correctly, characterized as in part shared with Tesla and in part being informed by Tesla AI.
And I also think Optimus, there's a curious split that I don't know how it's going to play out between the Optimus AI and the MacroHard slash XAI slash Cursor AI, where right now SpaceX in this bizarre sort of
incestuous ecosystem of Elon-affiliated companies, SpaceX is seeming to get, in some sense, the digital optimist, if you will, the macro hard worker for knowledge work labor, and Tesla is seeming to get the embodied optimist. And not obvious to me exactly how, from a governance perspective, all of this IP is supposed to flow back and forth between them.
A lot of predictions, Alex, about merging, obviously, SpaceX AI and Tesla into, you know, Musk Corp. I wonder if there's a poly market on the under over there. But, you know, a lot of there is a prediction market for it. Yeah. Do you remember what it might be? Maybe you can check in the background. Yeah, I'll check.
But honestly, I think within a year, we're going to see that when we've got two publicly traded markets, the ability to value them and merge them becomes a lot easier.
Well, the bullet two is really important in that, the super voting control. Remember, we mentioned on a podcast a while ago that Elon has never had what Sergey and Mark Zuckerberg have, which is a public entity that can raise you know, many billions of dollars in an overnight where he's the controlling shareholder. So this will be the first time that he's in that position.
Remember, he doesn't control Tesla. That's why he's constantly, you know, going to Delaware court over. Yeah, this will be, this will be a new thing in the Elon verse. And remember Peter, you know, you were an early investor in XAI. Remember that capital raise when it was getting off the ground? Yeah. The very first one. Yeah.
Remember the amount that he was raising, which seems like a lot at the time.
God, I don't.
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Chapter 5: What are the challenges of data centers in local communities?
And then mathematicians and others point to those exhaustive brute force solutions and say, gosh, maybe AI is more exhaustive, it's better at brute force, but it lacks human brilliance. It lacks... leaps of creative insight. This is not a problem like that.
This is a problem that has the top mathematicians in the world who specialize in this particular area looking at its reasoning traces and concluding that not only was it faster in some sense. Not only was it able to brute force lots of different theoretical approaches, but it was also smarter. And it was smarter, though, in an interesting way.
One of the commentaries, and definitely I would encourage everyone to go to the OpenAI website and read a number of professional mathematician commentaries on the reasoning chain of thought that it used to solve, really to disprove this conjecture.
there were some interesting comments to the effect that from looking at the reasoning chain, they could see that it was pursuing all sorts of call them exotic possibilities that humans would be too exhausted to pursue. So it was arriving at creativity by sort of both being faster, but also being able to brute force all sorts of outlandish possibilities.
And in the end, one of those possibilities was, And I think the language from the chain of thought that ultimately led to the solution began with something like, optimistically, if I pursued this, something might happen. And that turned out to be the solution.
So if we remember the infamous move 37 from AlphaGo's match with Lisa Dahl and how being able to brute force, but with clever learned policy search, the reasoning tree of a Go game, we're starting to see that play out in math. And by the way, That's going to play out everywhere else as well. It's going to play out in physics. It's going to play out in every science, engineering.
Hashtag solve everything, Peter.
We're seeing it. The starting gun. And, you know, while people may not relate to math, they sure are going to relate to physics and chemistry and biology, material sciences. These are going to give birth to trillion dollar outcomes.
I think, you know, in the past, we've had very hard humanities last exam questions on the pod and made the point that you would have to think hard for three or four hours to even understand the question. And then, of course, then Alex says, I think the answer is four. And it turns out to be right.
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Chapter 6: How is China leading in AI video generation technology?
A few months ago, like world models, including Gene, we already do that. That's what you're asking for. Interactive video generation and real-time world models already do that. I'll tell you, we remember, I don't know if you remember, Peter, but we saw Liquid AI a year ago generate images as quickly as you could speak, like instantaneously coming out of Liquid AI.
If you try to do that now, today, you wait like a minute or more And the experience is nowhere near as much fun as the real time, like creating as fast as you can think. But we're so short on compute. And that's one of the reasons Liquid AI is doing well is because it's so much more efficient.
But, you know, that Holodeck experience we're trying to create is, you know, it's entirely possible to build the Holodeck today, but nobody has the compute available to deliver it.
Salim, any thoughts?
I'll echo what we talked about already, the amount of data that China has. I mean, TikTok and Douyin are huge, essentially training loops disguised as entertainment platforms. And so I think they'll stay ahead for a bit longer, but I think the models will catch up. This episode is brought to you by Blitzy autonomous software development with infinite code context.
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Chapter 7: What role does purpose play in AI-driven organizations?
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Our next story is an interesting one. I want to focus on this a little bit. Uh, uh, here's the deal. Here's the idea. The friend of pod, Eric Schmidt was giving a, uh, a commencement address at university of Arizona. Uh, as he mentions AI, he gets booed. Um, and it's pretty brutal to watch. We'll show the video in a second. Uh,
Gloria Caulfield, who's the VP at Tavistock, she's a friend, had the same treatment. The generation today that's entering the workforce is angry and scared about AI disrupting their career. Let's take a look.
Know what many of you are feeling about that. I can hear you. There is a fear. We do not know. We do not know the precise contours of what this transformation will be. The rise of artificial intelligence is the next industrial revolution. What happened? Okay, I struck a chord.
Selim, let's go to you first on this one.
Well, I mean, look, the students are sensing that companies and institutions are adopting AI and we've not redesigned the social contract, right? The backlash is not anti-technology, it's anti-extraction. And we need to kind of a new narrative around agency, not replacement here. And there's a huge legitimacy gap between AI elites and young people today. It's incredible to see. Yeah. Dave?
Well, this is clearly priority one for XPRIZE now. I mean, you've got $100 billion of charitable money suddenly unleashed at OpenAI. They don't want this at all. So, I mean, but historically, no one expected this to happen this quickly. So they put very little effort. This is their wake-up call. You know, look at these videos.
Like Eric Schmidt is a hero of, I mean, one of the greatest, if not the greatest business executive of all time. But when the job market is basically zero for college graduates coming out, what do you expect? And the sentences there weren't exactly inflammatory, right? AI is the next industrial revolution. That's not exactly a controversial.
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Chapter 8: What are the potential impacts of AI on job markets and education?
They should just be supervising the exams. If you want to make sure that calculators or AIs aren't being used or earn the vast tuitions that are being paid to the university and supervise.
I think, if anything, this points the direction, if higher ed is going to remain at all recognizable at all, and I'm not sure that it will or even deserves to, I think the direction of far more supervision, far more proctoring, maybe even some sort of wilderness camp
at a university level where students are denied technologies and asked in the style of Verner Vinge and Rainbow's End and Fast Times at Fairmont High. I love that book.
Students have to interact with actually the real world and interact with the real world in a way that's impossible to cheat without succeeding, like building their own actual businesses instead of writing business plans, actually solving hard problems in computer science instead of solving formulaic tests. that require humans be in the room to supervise. That's the direction this goes in.
Use AI to go 100 times bigger than you normally would. Exactly. Dave, you're teaching at MIT. What are your thoughts on this?
Well, I teach a class called Foundations of AI Ventures where you have to build a business plan. So it's already on exactly the mission that Alex was outlining. So if your business plan gets funded, you get an A. So it doesn't have this particular problem. But it seems obvious to me that you want to be teaching the students to use AI.
And if you just look at their prompt stream, you can grade them. You don't have to have tests at all anyway. So it's what Alex said, that the schools are struggling to hold on to something that, you know, it goes back to when graduation speakers would show up on horseback and you'd expect the crowd to hear wisdom they couldn't hear any other way from some great human being.
You know, why do we need graduation speakers today if we have podcasts? Well, we don't. Well, then why do we do it? Well, it's traditional. It goes back 150 years. Okay, well, you know, the exams do too. Of course, it makes no sense. But, you know, it's really hard to let go of tradition after tradition after tradition. But what do you think the singularity is going to be like?
I mean, is this actually cheating or is this what students should be doing? I mean, do you expect these students not to be using AI when they get to the real world? Why are you training them for something that isn't going to exist in the future?
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