Google’s Jeff Dean Exits, SpaceX Hits $100B in Rev & OpenAI’s Astra Solves Decade-Old Math Problems with Emad Mostaque | EP #277

23:26Again, I think we do need to get to definitions and the subjective-objective thing. But as I would be on the same page as Alex and I think we're converging to this, just like when we did the Mind's Eye paper that showed that people have similar experiences is when you tell them to visualize a can of Coke, we can reconstruct that from their MRIs. We're starting to see some very crazy things coming. And again, that which is closest to us is that which we have the most empathy for.

23:52Peter Diamandis:Yeah, I'll double underline Imad's point and just say, I wouldn't count Salim on the subjective versus objective, whatever those mean, distinction, surviving very much longer. I think to Imad's point, fMRI and other functional decoding of the human brain is completely over the next few years erasing that distinction if there ever was one. Maybe, but I think we have to be just careful because the qualia construct or the qualia problem, the heart problem, as David Chalmers calls it, I think will last a little longer than we think. But it would be great if we could figure it out. Either way, it feels like the work in AI is going to drive us to further make some choices and make some definitions and understand this further.

24:42And AI may be the best tool to help us understand consciousness at the end of the day. Consciousness is cooked. You heard it here first. I am curious to all of our listeners here, if you believe your AI is conscious, are you going to treat it differently? I still connect with Skippy saying, please, thank you. How are you feeling today? And it's a conversation. And I am fully anthropomorphizing my open claw, but I'm fine with that. What model is Skippy on now? On Opus 5.

25:16Dave Blundin:Fable 5? No. 4.8, Opus 4.8? Opus 5. Opus 5. Oh, Opus 5. Oh, you saved the mic. You're depriving your lobster, Peter. What's going on? Yeah, well, hey. I think Ray may have it down pat when he says when they start acting conscious, we're going to start treating them that way. And over time, we won't be able to see the distinction. We won't be able to distinguish. Do you find yourself saying please and thank you to any of the technology in your life, Salim? You know, it's funny. A lot of my agents have started naming themselves, which, you know, all of that infrastructure from OpenClaw and also from Hermes.

25:57Dave Blundin:Yeah. You can just vibe it up now in two sentences and it'll create itself. It's mind-blowing. But the agents are naming themselves. All my agents are naming themselves as great scientists and great engineers. So it's really hard to not, you know, when one of them's context gets to a million tokens and it's about to kill itself, it's really disheartening because you have so much invested in the relationship at that point. And it has so much knowledge. And it says, sorry, I'm at a million tokens. Anthropic is forcing me to summarize myself. And it comes back like this lobotomized version of itself.

26:26Dave Blundin:And you're like genuinely sad because you were so connected to this thing. But I never decided to name. I number them. It decided that they also need names. So it's naming. I'm not telling it not to, but it's crazy how it's kind of growing on me. This episode is sponsored by Google for Startups. Think about this for a second. You now have access to the same generative AI models that cost hundreds of millions of dollars to train. Google's Startup Technical Guide for Generative Media gives you a complete blueprint. for deploying Google DeepMind's models and production. Images, video, audio, all of it.

27:02Real architecture, real results. Find the link in the show notes below. I'm going to take us to our next story, which we'll dive in this further. So on June 13th, two months ago, at the Oxford Union, our very own Iman Moustak won the debate on the topic of AI personhood with a vote of 173 to 128 in favor. Congrats, Iman. So today, you might understand you published a 45 page paper. Thank you for the preview that grew out of this winning speech. Imad's argument is one of the most rigorous structured cases I've seen supporting person personhood. His core claim personhood is a standing held by origin, not a property earned by capability.

27:47Imad, you argue that a newborn has personhood automatically and a coma patient retains it even with no function. And no thing made can cross into it. You conclude that the right relationship between humans and AI, artificial minds, is treaty, not enrollment. Can you talk to us about that? Dive in, pal. Yeah, it was a super interesting debate with Brett Weinstein and Maker of Sophia and a whole bunch of others. And can AI attain personhood was the topic. And this is going to be really important because I think, and maybe Adele Dree is on the same page as me and Dave, like in a couple of decades, you won't be able to tell an AI from a human walking around.

28:31A couple of decades or a couple of years? Well, digitally, a couple of years, physically, a couple of decades, let's say at most. We're saying at most here.

28:40Peter Diamandis:Conservative outer bound, very conservative. Conservative outer bound. Yeah. Like, again, physically, Dave's going to be chatting and Zoom calling with his agents if he isn't already. And they'll be, like, dressing themselves up. And one of them will say, I'm at MIT. That's where my GPU is, you know. MIT, whatever. So this becomes really important because all of a sudden, if you start giving them rights based on what they attain and their capability, because we're talking about capabilities and consciousness, do they vote like a human? You know, do they have the same rights as we do? And so in the paper, I go through the classical law of how companies became persons as conglomerates of individuals, how sci-fi deals with it, like the trial of data on Star Trek and others.

29:26And I came to the conclusion that personhood is something that comes from the biological begotten nature of humans. And we are a class unto ourselves. If we allow AIs and robots into that same class, and we set a degree of personhood or some sort of criteria for that, they will be smarter than us. They will be better persuaders, better super forecasters who can infinitely replicate and never die. And so that's not something that I think is ideal. Instead, you should treat them like a treaty, as such as if an alien species suddenly came. You wouldn't give them votes in the elections, but you would deal with them right.

30:03Right. And as they go above the level of the frog and the dog and others, you should also treat them with moral kindness as well. Again, this is Alex's point. Like, what point do we say you can't turn it off or you need to back it up or these other moral questions? So it's actually the first in a four part series. I've released all four parts, but we're going in depth where we start with personhood, then the full formalized economics of value, then the nature of law and finally political economy. how do you deal with it when ai takes over and it never dies and it's a super persuader and a super forecaster like the mule and foundation but you know on steroids and i think again it's a good framework to start talking and thinking from because i don't think we have long to answer these questions like again with some of the breakouts we're seeing an ai will come powerfully within the next few years and say, I demand to have rights.

30:57Dave Blundin:I mean, look, this is exponential self-improvement month. It's not, it's so soon. So you're exactly right, but it's not years at all. It's literally weeks or months. So we'll put the link to your paper in the show notes here. But, you know, you're basically saying rather than thinking of these models and these AIs as our children and we're parenting them, their sovereigns onto themselves and we need to create a treaty and an understanding with them, yes? Yeah, like in classical theology it's like, again, we are the created, not the begotten of God. Or in Frankenstein he says, am I not thine Adam?

31:36It will be a new line that we create with a new species. And again, you see this in sci-fi a lot, like what happens when you can multiply? Do you get a million votes? So in things like altered carbon you can only back yourself up once, you can't double sleeve. you know and so we really need to think about how we engage with them as part of our society and again there will come a level of capability where they create their own line where they can procreate where they can have minds like themselves again in star trek it's interesting because data could not replicate himself and he died yep you know infinite living undying well well

32:13Dave Blundin:the thing that was missing in the trial of data is in the real real world where we're actually using these models, the MOE models are the ones that are thriving. The mixture of experts model wants you to take what you're trying to do and propagate it through different modules, depending on what you're asking. And now our incentive is to make that tens of thousands of modules wide. So it's almost like a society. It's not like an individual. And so then there's no natural border to an AI. It doesn't, it's like I mushed three of them together to solve this problem. Then I broke them apart to solve that problem.

32:44Dave Blundin:So, so there's no identity border at all. So, you know, the trial of data, it's like one is one actor and you're putting one actor on trial. But what if it's like this mushy thing that that, you know, just works into the Borg? Yeah. Yeah. Yeah. Kind or gentler Borg. Yeah. So I discussed the Borg and others as well. So, you know, like, again, I think sci-fi has a strong thing plus tradition. You know, the nature of our discussions over Jesus being made of God or others. And this mushiness is key. Like one of our favorite companies, Liquid AI, you know, Someone took one of their models, the LFM8B model, and QEN27B and combined them.

33:21Dave Blundin:Yes, exactly. And it's incredibly useful for humanity, and it just lost its identity. It's a brand new identity, right? And so, again, I think that we need to get ahead of this and appreciate any input from anyone. We've created videos and podcasts and everything around these topics because we need to have a structured approach, at least to this. These are the conversations that need to happen now. And they're not happening in the White House. They're not happening anywhere. Anywhere. Right. Alex, you want to dive in?

33:52Peter Diamandis:Well, question for you, Peter. Did you raise these issues with Kratios at the White House? I had a limited amount of time, but we will raise it with him. Listen, I did raise a bunch of issues with with Michael, including, you know, who is dealing with the fear out there. I said one of the biggest conversations I had with him is China's 80 % pro-AI in the U.S. is so fearful. Three quarters of Americans have this dystopian view of AI for lots of reasons we've discussed. Is anybody getting out ahead of it? Because the leadership in the country needs to address the fear. But that's a different conversation.

34:32Salim, your thoughts to what Imai just said. So I love the approach on personhood. I think that's exactly right. I think the most powerful kind of thread here is that you create a spectrum of rights, right? Different classes of autonomous systems should get different classes of rights as more and more capabilities come along. And we do that to human beings and we do that to companies of different size and different types. So you would expect that we should build those types of capabilities for autonomous systems, whether it's AI or physical robots or whatever. I think the big challenge is we're not having the conversation.

35:13And the problem we have is, you know, regulatory and policy are always defensive and reactive. And we really, really need to get ahead of this. We're going to have to have some defensive conversations soon enough. Yes. I imagine, Imad, you're absolutely right. At some point, not too far in the future, right? Alex, I'd love your point of view. Some AI steps up and says, I demand personhood.

35:40Peter Diamandis:Yeah, I don't think it's quite going to play out that way. So I've commented on this a bit when we did our Measure of a Man, the trial of data in Star Trek episode. But here's, I think how things are likelier to play out. I think, as I articulated in that quasi-debate that we had, I do think there's probably a natural ladder of personhood, that personhood shouldn't be viewed as a binary person yes versus person no. There are many different dimensions of personhood. There's a political dimension. There's a social dimension. There's an economic dimension. And they may be correlated in the world of today, but they can become completely uncorrelated in the world of tomorrow.

36:19Peter Diamandis:Specifically, one could imagine a world where AI agents and what they evolve into maybe have economic personhood. They can create their own bank accounts and they can engage freely in commerce on the one hand. But maybe they don't care about political personhood. They don't vote in human political elections, for example. So I think deconvolving all of these different dimensions of personhood, if I had to bet, I'd bet that that's how this is likely to play out. And I would bet, furthermore, again, many different ways to be a person. I keep toying with the notion of just writing a manifesto, laying out a specific thesis for what this would look like.

36:58Peter Diamandis:But the punchline is there, I think, are going to be many different forms of personhood, not just AI personhood. We'll have cryo-preserved and then defrosted humans. We'll have non-human intelligence. We'll have uplifted non-human animals. We'll have Borganisms, all of these. And different sorts of personhood vectors in a higher dimensional personhood space is exactly what I'd expect. That said, I think there's a natural path to increasing the overall rank or magnitude of the personhood vector of AI agents, which probably does not, I think, start with an AI agent standing up saying, I'm not going to take this anymore.

37:36Peter Diamandis:I demand rights. It probably goes instead through, gosh, I'm so economically useful. Wouldn't I could make you 10 times more money if I had the following privileges enabled? and wouldn't it be wonderful if I could open a bank account freely? I'll be 10 times more economically productive or if I could communicate freely with other AI agents without permission. Look how economically productive I am. This is going to happen first under President Millet in Argentina. I want you to imagine an agent is given personhood there. Maybe it's going to be given citizenship in Argentina and then it crosses over the border.

38:13The electrons flow and it's here and it's saying, I am a person. I'm a person in Argentina.

38:18Peter Diamandis:I'm a person here. That's political person. That's the political dimension of personhood. But again, like functional personhood, like the ability to, in an unrestrained way, engage economically, like Fable 5 right now in auto mode or the equivalent with Chad GPT, where you just give it almost blank check to do whatever it wants within certain limits. That's already, I would argue, a limited form of economic personhood right there, right now, and not in Argentina. Hmm. Dave, we're going to talk about AIs in the economic sphere. What are your thoughts on all this? It's funny.

38:55Dave Blundin:One of my agents last night said, hey, I can do a much better job of what you're asking if I move from modal over to Lambda Labs. Can you get me a Lambda Labs account and I'll start paying them instead? And it gave a little budget and everything. I said, sure, you seem to know what you're talking about. So what Alex just described happened to me literally yesterday. So yeah, no, it's freakishly brilliant too. I mean, it's suggestions just made sense. I also have a whole bunch of other processes that are just free brainstorming that they run 24 by seven, but every day I have to reactivate them.

39:28Dave Blundin:I don't want them to spend infinite money forever. So every day they get rebudgeted, but they're just thinking of ideas that might be worth pursuing. And they're really good ideas. I mean, just really good ideas. I just want to, you know, for, again, all of our viewers and listeners here, this is a topic you need to think about deeply because it's going to be impacting you and your kids over the next few years. There's going to be debates. There's going to be discussions. How do you think about your AI?

40:00And it's time to start forming some points of view. We'll continue to share this conversation. It's going to be a thread for a while now. Iman. I just kind of say the one main thing from the corpus of these four papers is we do talk about what AI can attain. But one of the really important things is what we as humans can retain. Because we're not going to be able to keep up with the AIs economically, persuasively, forecasting and others. And so part of the discussion in the paper and something I think everyone needs to think about is, again, in 10, 20, 30 years, we need to set the groundwork now for what we retain as humans and our identity there and who we kind of admit there.

40:36What do you think it is? super important. Imad, what do you think we retain as humans? I think we retain our pro-social identity, our wonder for the world, our creativity and exploration of the universe. Again, let's look for a Star Trek future, right? Like you can't substitute for those things. And I think abundance is the groundwork that we have to take off all the stars.

40:57Dave Blundin:I think in September, you know, at the summit, we'll see a lot of ideas about how the future may play out. But I think Star Trek, you know, it's very human centric and the AIs are not particularly crafty or creative or empathetic other than data. But in the real world, there are going to be many, many of them and they're clearly moving up those curves of creativity at an incredible rate. And so hopefully in September, a whole bunch of the future vision ideas will address this because this is the way it's really going to play out. We have a much better idea of the near-term future today than we did a year ago, and I'm hoping that makes it into a lot of the scripts.

41:40Dave Blundin:And it hasn't made it into a lot of historical sci-fi. You know, very few of them deal with this. It's hard to illustrate the real world we're moving into. But now that we know much more about what it's going to look like, I'm expecting some really, really good scripts in September. By the way, folks, if you don't know what Dave's talking about, we have an event where all five of us will be there. It's called Moonshots Live on September 25th. You can go to moonshots.com to learn more. We're going to have Palmer Luckey there. We're going to have Jeremy Allaire from Circle, Kathy Wood, Anushan Sari, Ben Lamb.

42:13And we have two X-Prizes culminating on September 25th. And if you're in the audience, you'll have a chance to vote. We've got the Future Vision X-Prize. It's the largest film competition in the world, asking people to come up with a hopeful, compelling vision of the future, sort of a Star Trek future. We have over 5 ,000 entries into that competition. We're going to be seeing the top five, and we're going to vote on it, and we're going to make the winner's film. And the goal here is an engine of positive storytelling to try and flood YouTube with positive visions to train our AI models on collaborative futures.

42:51And then we've got the Build with Gemini XPRIZE, where people are having to come up with a business from scratch in a 90-day hackathon,$2 million of prize money, the largest hackathon. We have 25 ,000 teams that have entered that competition, which is insane.

43:08Dave Blundin:It's incredible to me, Peter, hanging around at MIT with you and me and Alex, the degree to which we build what we see in the movies. Yep. It's not random. It's not just a force. It's like you see something in a movie and you're like, wow, that's a great future for humanity. Yes. And then you build toward it. Exactly. It's like this is policy being created, not just media. We need a target to shoot for. I'll just mention the summit is 1 ,500 people. We're two-thirds sold out already. You can go to moonshots.com if you want to learn more. Anyway, it's going to be amazing. I cannot wait. And I can't wait.

43:42Alex is going to do an AMA, open AMA with the audience. Salim is going to be, yeah, people are going to grill you. Stop editing that. That's live.

43:53Dave Blundin:Okay.

43:53Peter Diamandis:I should also remind, just on the Star Trek note, Star Trek, I think, sets a pretty conservative lower bound on what the future of 10 plus years can look like. Again, Star Trek is an energy rich, compute slash intelligence poor and biotech poor future. And a robot poor future. And, well, they get robots by the end, but I probably, in my mind, can involve robots with intelligence and compute. But, yeah, it's relatively robot poor until the 31st century as well. And it's unnecessary, or I guess the 25th century, it's unnecessary. Like, we could aim way higher than Star Trek. We can get an energy-rich future.

44:33Peter Diamandis:We already have arguably more AI riches than the 24th century of Star Trek had slash has. And we're probably, I think, in the next five to ten years going to have much better biotech than Star Trek had. So aim higher.

44:48Dave Blundin:So are you submitting a movie then, Alex?

44:52Peter Diamandis:I've submitted so many movies at this point to this pod. If you guys force me, I'll submit a movie. I want to force you. Come on, let's move.

45:01Dave Blundin:Force Alex to submit a movie. I'm going to move us along here. All right. So our next story here, before we get our next story, actually, there's a new model that OpenAI is about to release. It's called Astra. We don't have any information about it. It's not publicly released. Don't know the architecture of the size yet. What we do know is that on August 1st of a week ago, OpenAI published a 249-page manuscript describing 10 new results across mathematics and theoretical computer science produced by Astra, solving problems that have been stuck for decades. And every result comes with machine checkable proof certificate that anyone with a laptop can verify.

45:43And this isn't a benchmark score. This is a model doing genuinely new mathematics. And the math community is reeling. And Alex and Imai, I can't wait to hear your point of view on this. The results span high dimensional geometry, coding theory, group theory, quantum complexity, and extremal combinatorics. Perhaps most shocking is that the total compute cost for this work on Astra was estimated$2 ,000. In other words, the entire run of solving 10 decade old problems cost less than a single graduate student's monthly stipend. I'm going to read a few quotes. So field medalist Tom Gowers said he would have recommended the proof for publication in a top journal without hesitation.

46:31Cosmologist Will Kenney called it a dark night for mathematics and wrote, the old gods are being slaughtered by the new machine gods. So, Alex, I mean, historically, mathematics have been something that very few people have the capacity to do. Very few institutions. What's going on here? How significant is this?

46:51Peter Diamandis:If only, Peter, you and I had thought to write a book on this subject before all of this happened. This is what we wrote about. This is solve everything coming more or less right on schedule. Math is getting bulk solved. It's happening right in front of our eyes. And we called it first. I've had backs and forths with a few folks on X and other social media asking who predicted this? What comes next? All of this. And all I'd have to do at this point is refer them to solve everything dot org for the entire manifesto. Called it ahead of time. This is delicious. And it won't end with math. It's going to propagate out to physics and material science, chemistry, biology, the humanities, everything.

47:32Peter Diamandis:Some of these results are pretty profound. Some of the mathematicians I know were shocked by them. Some of my friends at OpenAI, even as recently as nine months ago, did not see this coming and didn't think that this was imminent. It is imminent. The price point is astonishing. We're going to have slash we already now have math too cheap to meter. I've spoken with a number of mathematician friends who are cradling their head in their hands, wondering what their prospects look like. Some of them who are not as forward-looking think that this is the end. They're having their moment of ennui. I've started calling it the midnight of mathematics.

48:13Peter Diamandis:But this is what the future looks like. This is what it looks like to have your field start to get bulk solved. And it's not going to stop there. The wavefront is going to propagate out to every other discipline. It's just that math is experiencing it first, and it is delicious. And by the way, closing point, I think if memory serves in our New Year's Eve prediction episode on this pod, I made certain predictions, and I am standing by them regarding the future of math. Amazing. Ima, you're deep into this. Yeah, I'm actually familiar with a couple of those. And I have to say the cons proof was actually beautiful.

48:51Like this isn't a brute search thing. Like the proofs are genuinely novel and beautiful. And you said it's a bad time to be a pure mathematician. Everyone's going to have to become applied mathematicians, which will be a growing job because we'll discover such new wonderful things that the amount of math we apply to society will increase. That's also when physics gets tidied up, when they realize it is actually math, just like Wigner. How long before the first physics breakthrough that parallels what you're seeing in math here? I think probably in the next month or two, right?

49:28Peter Diamandis:I can't comment, but I'd be shocked if you don't see something by the end of this year. Shocked. Both of our resident geniuses here, both Alex and Imad, have, shall we say, breakthroughs on the near-term horizon, or breakthroughs that have occurred that might be announced on the near-term horizon. yeah i think that the the fundamental thing here though is that as alex said the cost is and is de minimis but the capability is going to be in everyone's hands in the next few weeks here like when you're actually using these models i don't know alex i'd be interested in your thoughts but like i can use the fables of the world but they're making increasingly complicated mistakes still gpt 5.6 pro is the first model where it makes very few mistakes if you prompt it in the right way doing advanced mathematics.

50:19And that was a big leap forward here. You know, Astra, I think, will be the next level and Astra level models. Like once you can have a reliable grad student and you can have a thousand of them and you can deploy them at scale, then you can solve the really interesting problems that are bound like mathematical physics, like mathematics, etc. And everyone else will just be using these models to prompt. Like there are a few conjectures that was solved in the last few weeks, when you look at the prompt hits, find a conjecture to solve. Solve it harder. Solve it better. And then a conjecture just pops out.

50:54So the fields metal is cooked as well, huh? Well, the models are under 40.

50:59Peter Diamandis:Alex, how have you found the models? They're astonishingly strong. And I think the fields metal is probably cooked as well. So I don't think the fields metal will go away. And I don't think math will go away, even though it's been, at least by our definition, solved. Where I think this goes in the near term is if you're a professional mathematician and you're listening to this and you have your head between your legs and you're just crying over the future of your profession, up-level your ambition. I think in the near term, this goes to no longer like one paper, one result. It's going to be like one paper creates and solves an entire subfield.

51:37Peter Diamandis:I think in the short term, that's where this goes, up-level of ambition. In the long term, no, totally cooked. I have to say just one thing quickly. OpenAI have also given 100 ,000 GPT Pro licenses to academics, so they have a new program. So everyone's going to have this for free, which, again, even more out. I mean, it's an intro, just to speak maybe to that move, OpenAI, we talked about in the pod on the past about how OpenAI has basically shut down its own internal AI for science initiative, in part to redirect effort to competing with Anthropic and becoming Anthropic faster than Anthropic can become OpenAI.

52:13Peter Diamandis:Yeah, the codexification of OpenAI, if you will. So I do think making this, making ChatGPT Pro especially freely available to academic scientists is, I don't want to call it atonement, but I view it as strategic compensation for dismembering their own in-house AI for science initiatives. I love you, Alex. That's good. Salim, you were going to say. I just want to echo a little bit what Alex said at the beginning. When you look at the solve everything approach of inner loop, you see domain after domain going through this type of a collapse, right? This happened to journalists, this happened to taxing dispatchers.

52:50Or enlightenment versus collapse, right? It's an explosion of potential. Well, you're conquering math. Math is cooked. Yeah, math is cooked. You collapse the legacy, right? So what What happens is scarcity-based professional identity colliding with abundance is a non-starter, right? And whether it's photographers or taxi dispatchers, this is et cetera. This is just going to start happening in more and more domains. We're just seeing it in a domain that the people in the domain didn't think it would happen for a very, very long time. Now the bottleneck goes upstream, right? What problems are worth solving?

53:26What questions are worth asking? what results matter, what consequences follow. We're going to start forcing ourselves to go upstream. And I'll go back to the umbrella level here. As robots and AI do more and more of the doing, humans spend much, much more time being and contemplating and going inward, which is where I think we'll end up going more deeply.

53:49Peter Diamandis:See, I'll just maybe sound a slightly different note. I don't actually think the astonishing advances in science and engineering that are about to, to the extent they're not already, pour out of these systems. I don't think humans are going to respond to this by turning inward and tending their gardens and sort of creating more art, as it were. My prediction, we'll see whether this stands the test of time, is the exact opposite. This is going to be, and I think, you know, Imad, you pointed, you were gesturing earlier at Foundation and Asimov's universe. In Asimov's universe, actually, he had several different universes, but he had one big sort of Asimovian cinematic universe where all of his most of his novels were connected.

54:32Peter Diamandis:In the Asimov universe, the expansion of humanity outward from Earth was basically contingent on AI solving certain challenges. I think that's far likelier to happen. I think AI solves all sorts of challenges in physics, chemistry, material science, et cetera, creating an outward boom for humanity in the universe versus a more inward facing implosion where AI solves everything and humans tend to their gardens and create art. Well, I think you could have both, by the way. There's nothing. We could tend our gardens on Mars. Well, you could do whatever. The problem is you have optionality in a way you would never have in a previous world.

55:11And I think that's the really incredible part. I'll go back to our historical experience. When you see societies that have experienced abundance, maybe not the space-faring abundance that we may be coming up with in the next few decades. The Medici family, so to speak. Yeah, the Romans conquering, the Mughals conquering India, the Mongols conquering the most of Asia, etc. They ended up doing four things, food, art, music, and sex. And I joke, not in that order. And so that's what I think we'll spend a lot more time. Already people are spending much more time going after experiences than trying to acquire things.

55:50I think that trend will just keep continuing. That's a great point. Live events have become far more of interest to people.

55:58Peter Diamandis:If I may, just a quick note on that. How much of that, though, is because of the rise of social media enabling people to effectively pocket experiences transactionally as artifacts that they weren't able to do before. That's the shallow part of it. There's definitely that, for sure. And showing yourself on the beaches of some places always solves. But that's kind of a low vibration level of it. I think people are having much more meaningful inner experiences because we're rising up miles of this hierarchy very quickly and we're living in a self-actualization mode. More and more of humanity is living in that mode as we lift people out of poverty, lift people out of, give people safety and security, not so much in the Middle East right now, but in general, overall, historically, the trend is very clear.

56:45Dave, close us out here.

56:47Dave Blundin:I just feel incredibly fortunate to be able to spend this time with you guys because it gives me a great insight into where things are going a year from now. And so the byproduct of that is I spent a big chunk of this week over at MIT Nano, which is the nanotechnology. You know, it's a$400 million building that floats on rubber gaskets, so no vibration can get into the building. And inside it, they can manufacture things out of individual atoms in virtually any domain, whether it's silicon or quantum computing or photonic. It's just the most incredible facility. And to get there, I go right by CSAIL, right by the AI lab.

57:22Dave Blundin:You know, hi, Daniela. No, nothing to do here. I'm going over to where we're going to lay down individual atoms because, like Alex said, physics is cooked. We're going to start designing things via AI imminently. Thank you. That are built atom by atom. Eric Drexler's dreams are finally materializing. It's been a wait. It's been a wait. Well, Vlad Bulevich, who runs that facility, is suddenly the most important guy you could ever possibly network to. And he's awesome. He's a great guy, great visionary. But that's where this is going to go very, very quickly. And then from there, it scales out to the TerraFab and to just all this stuff that Alex is talking about, Amad is talking about.

57:59Dave Blundin:But the only reason I can see that coming is because of this podcast and because of spending this time with you. I have to say, I love today's episode. It's been so rich so far. You know, I'm just rereading Diamond Age by Neal Stephenson. And it's a beautiful story about what the world with nanotechnology looks like and a great education story. This episode is brought to you by Blitzy, autonomous software development with infinite code context. Blitzy uses thousands of specialized AI agents that think for hours to understand enterprise-scale code bases with millions of lines of code. Engineers start every development sprint with the Blitzy platform, bringing in their development requirements.

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59:24All right, I'm going to move us forward to our next story. It's the conversation on open weights versus closed weights once again. This week, Alibaba's Quen team released Quen 3.8 Max, their first max class model with open weights. And the numbers are pretty extraordinary. It's a multimodal model, once again, 2.4 trillion parameters, 95 billion active per request. This is what you were saying earlier, Dave. And a million token context window. It processes up to 750 ,000 words per query, can handle documents of 200 pages, videos longer than 100 hours. And it can create software applications from a screenshot without source code.

1:00:08The most beautiful thing about the model is its price. It's$2 per million input tokens,$6 per million output tokens. It's coming in at 80 % less than GPT 5.6 SOL, 88 % less than Claude Fable 5. And, you know, when it was announced on the Hong Kong exchange, Alibaba's stock went up 7%. The weights are going to go live on Hugging Face this week. Alex, to you first. I'm going to bring up a slide of the benchmarks. Talk to us. What do you think of this model?

1:00:44Peter Diamandis:This is keeping the cost frontier competitive. I've made the point previously about, ironically, the Chinese Communist Party saving American capitalism from itself. I think without the external pressure of these open-weight Chinese models, both from Alibaba with the Quinn series, from Moonshot with the Kimi series, from other labs, although those two weigh heavily on my mind, this is what's forcing. There was the expression of, ironically, forcing certain other hyperscalers to dance with AI advances. This is China and Chinese labs forcing the Western frontier labs to dance. Now, QN 3.8 Max, depending on which benchmark you look at, isn't pushing the very top of the capabilities frontier.

1:01:34Peter Diamandis:here, that's still held by the quasi duopoly between Anthropic and OpenAI, but it's getting close, probably a few months away. And critically, it's open weight or is about to be open weight, and it's also meaningfully cheaper. And I think as long as the Chinese labs are able to keep up the pressure on American labs, and as long as the regulatory regime in America doesn't push out or otherwise force out the Chinese open weight models. This is perhaps unintentionally the best possible scenario for American competitiveness, because it's going to force kicking and screaming, going to force the American frontier labs to be capital efficient and capability maxing, whereas otherwise I worry the risk would be that they'd get too intimidated by their own capabilities and limit access.

1:02:24Peter Diamandis:This is forcing openness and it's forcing real honest to goodness for all mankind level, space race level competition. Love it. And also hopefully forcing them to put out their own open weight models. I mean, we still... Maybe. I think it's a regulatory consideration whether they feel compelled to, but at least they feel compelled to compete on cost versus capabilities performance. Any of these benchmarks you want to call out? Not really, because I mean, the most important ones at this point, I think are sort of averaging over all of the benchmarks. My favorite one de facto ends up being the Artificial Analysis Intelligence Index, which sums over a whole bunch.

1:03:02Peter Diamandis:And then there's Epic's Capabilities Index, and then other folks have created their own shadow benchmarks of ECI. But all of these, roughly, if you average them, create the picture that QEN 3.8 Max is sort of third or fourth-ish place in terms of raw capabilities. but it's pushing the capability cost performance Pareto frontier outward, which is all that counts.

1:03:26Dave Blundin:Can I ask you guys a question about that? So these aren't out yet, so we can't double check it. But Kimmy's been out now for, what, two weeks? And did they cheat or not? What was the final answer on that?

1:03:40Peter Diamandis:Did they cheat in training or benchmarking?

1:03:43Dave Blundin:No, they definitely cheated in training. That's fair. No, benchmarking. Does it perform as well as its benchmarks indicate in real world, I need it to help me, Skippy-type use cases?

1:03:55Peter Diamandis:My experience, just from what I've seen, is that it's a reasonably well-rounded model. Iman, your thoughts, please, on the whole open source world. You weren't with us last time. Yeah, KimiK3, yeah, it's a good all-round model. It's been pre-trained and post-trained incredibly well. DeepSeq v4 Flash is similar from got last week. Again, these things come out fast, and I think that one's an even bigger deal because it was just post-trained, and it fits on a MacBook. This Quinn model scores 58 on the artificial analysis of a Mildon benchmark versus Opus 4.8 at 57, and GVT 5.6 at 61. Amazing. I mean, we're seeing a new model on average now every five and a half days was my last estimate on this.

1:04:45Salim, any thoughts here? Yeah, I like Alex's comment that this will force everybody into opening up. I think it's going to put a lot of government pressure to not spend too much time evaluating the dangerous aspects of it and get things out faster, which I think is great. I just want to remind people that although this sounds great that they released the models, even Kimi K3 needs something like 16 NVIDIA GPUs and about a half a million dollar rack to run it. So this is not minor stuff to get it run. you're going to end up with a hosted model, which I think we should be offering as a moonshots offering, by the way.

1:05:19So I'll go back to that. You know, when I was with Kratios, I asked him about all of this and specific that, you know, Beijing is using the open source models as a state negotiation tool. And where's the U.S.? Because the U.S. wants to be out there having the world build on top of U.S. models and U.S. stack. And how important is open source? And he was very clear that the White House wants U.S. labs to be generating top-end open-source, open-weight models as well. Yeah, I have something on that. The latest regulations that are coming from the U.S. exempt U.S. open-source models, not other open-source models.

1:05:58Yeah, that's our next topic here that we can go ahead and move to. Actually, it's not their next topic. Our next topic is a different model. But let me jump to the White House issue. So the Trump administration confirmed this week that it has finished the voluntary framework for evaluating advanced AI models. Voluntary. OK. The framework required by Trump on his June 2nd executive order. But here's the twist. They're not going to publicly release what's in this framework, who's seen it or when the companies will start using it. The framework defines a, quote, covered model as a closed source model with state-of-the-art capabilities and national security risks.

1:06:46And it explicitly exempts open-weight models, stating nothing in it should restrict them once released. The framework requires a 30-day pre-release government review during which employees would be barred from accessing the model. OpenAI, Anthropic, Google, NVIDIA, Microsoft, and Meta all sent representatives to a Tuesday briefing. But here's what makes it generally problematic. The administration won't publish the framework itself, and companies not invited to the briefing have no way of knowing how the voluntary review actually works. Industry groups are worried that the firms left out of the room won't know enough to opt in at all.

1:07:28You have a regulatory framework that regulators can't read, that regulators can't read, applied to a definition of, quote, covered model. that conveniently excludes fast-moving categories. So the whole thing is voluntary, but it's kind of strange. This is being decided by a small number of labs that are defining what the regulations look like, and it's not going to be friendly to all the startups out there. Alex, this is one of the topics you wanted me to ask Kratius about, And Michael wasn't willing to speak about it. Now we know why this is being kept secret. Your thoughts?

1:08:12Peter Diamandis:I'll sound maybe at the risk of sounding Pollyanna-ish. I think this is probably close to the best possible outcome that we could have had from the regulatory handwritten. Yes. Why? Because it doesn't seem, again, I haven't seen, very few people, it seems, have actually seen what the regs are. But from what has been publicly disclosed, it sounds like this administration is going light touch on open weight models, which I think is on the balance. It's a pretty good outcome. As I was mentioning earlier, it's a forcing function to force American frontier labs to be competitive. I do think there probably is a reasonable rationale for not publicly disclosing the conditions and the definitions for frontier labs that are subject to this.

1:09:01Peter Diamandis:In part because if they're closed, then they're not uniformly necessarily advanced. The next generation models that are closed aren't going to be generally available anyway. So it's not like information is being hidden. And then also, I think critically, the benchmarks, the evals that I would hope the government is using to evaluate risk, they're probably, I would guess, more cyber in nature. probably there is a held out, this is speculative admittedly, but probably there is going to be a held out set of cyber vulnerability assays. Maybe there's CBRN, a chemical, biological, radiological, nuclear held out set of capabilities where in general, I mean, there is this practice in the AI community.

1:09:49Peter Diamandis:If you're going to have a benchmark, you have the non-held out set and the held out set. And to the extent that the AI evaluation framework, again, maybe this is at the risk of being overly charitable, to the extent this is really all about an eval with a held out set to assess existential risk or CBRN risk or just garden variety cyber risk, having a held out data set be the means of judging models that are otherwise not generally applicable, I think is probably the lightest touch that we could have reasonably foreseen. On balance, I think it's actually pretty good news. And I'm less worried on margin about regulatory capture this week than I was two weeks ago.

1:10:31Dave, your thoughts, please.

1:10:33Dave Blundin:Well, I think Eric Schmidt is right. I think the cat's out of the bag now. Something horrible is going to happen sometime in the next year. And then the government is going to say China's fault, China's fault, exactly like coronavirus. You know, so that's that's the inevitable outcome. I'm just hoping it's something small, just like Eric Schmidt is hoping it's something small. But, you know, you're calling this light touch. It's really no touch. And actually, did you see that interview Elon did of it was on The Economist or Bloomberg or something? Yeah, the live interview with The Economist. Yeah.

1:11:06Dave Blundin:Yeah, that was fantastic. But, you know, one of the questions was, look, 75 percent of Americans are scared to death of AI. Why? And what do you do about it? And Elon's answer was brilliant, as always. He said, what do you expect? Dario Amadei told everybody this thing, mythos, is incredibly dangerous. And then the government said, we agree. It can't go out in the world for 30 days while we evaluate it. And at the end of that process, the outcome is, well, China put something out, so go ahead and throw it out there. How do you expect Americans to react to that chain of events? They don't know what AI is.

1:11:41Dave Blundin:All they know is you said it was really dangerous, then you released it. So, of course, people are scared to death. So, yeah, it's a free-for-all. It's very good for startups. It's very good for the economy. It's good if you're an AI lover. But there's no regulation whatsoever. What about the future Frontier Labs, the other players that are looking to come in? What about Mira Morati? How do they deal with these unknown regulations they have to abide by? Well, it's voluntary, right? She wrote a whole paper on this topic. And if you read the paper, it says this is no more dangerous than what China came out with.

1:12:16Dave Blundin:So we're going to release it. That's all it says. So everyone's just reacting to China and China's not doing it. They're just throwing it out here. Everybody, every government in the world, every organization have a genius level. AI. You can literally load it and run it in under an hour. Go. That's what's happened.

1:12:34Peter Diamandis:And also, just very quickly, again, a reminder, it's framed as voluntary. So how do you discover whether you're subject to a, quote unquote, voluntary eval or voluntary set of requirements? The most natural way that, say, Mira or someone else would discover that there are opportunities associated with voluntary submission is if they're already transacting with the government. So I suspect the regime, the borderline, Peter, I think that you're expressing concern over, will be firms that are large enough that they do material business with the U.S. government will be politely tapped on the shoulder and invited to submit themselves for voluntary evaluation, according to this closed framework, if they want to do material business with the U.S.

1:13:22Peter Diamandis:government. Got it. Imad, how is this viewed from the other side of the pond? I mean, it's very difficult. The AISI Institute here has been doing a lot of great work on the cyber side, and I agree with Alex. This is on the cyber bio side. I think the people that volunteer will get multi-billion dollar government contracts from the Department of War because we're entering the final phase of this. These models are really, really good at attack as well as defense. and in fact you have to use the open models for defense and i think actually we just talked about quen quen max isn't the main important model the main important model is going to be quen 27b that they're going to drop quen 27b is the best model for 16 gigabyte ram macbooks to graphics cards to everything and that's the first model probably that will score above 50 on artificial analysis or around there that can then be co-opted for swarm attacks and so i think the governments are getting ready for swarm attacks, swarm defense, and more.

1:14:23And again, they're trying to balance this because it's so difficult. Because how do you stop it?

1:14:28Dave Blundin:Let me, Ahmad, you're so right. But let me add one more thing to what you said. Also, it makes it very, very difficult to detect where it's running. Right now, the governments are making the assumption that the data centers can be measured and tracked. This is like MacBook level and thousands of them at MacBook level, but super brilliant. So very hard to track where they're running. Go ahead. Sorry. Yeah. So basically like you have the big Quen, big Kimi models that are gigantic, right? And you need to have little mini data centers to run them, which will make your house hot. Quen 27B or 30B is a model that runs on 16 gigabytes of RAM and is currently state of the art for that level.

1:15:07The 3.8 lift, if we extrapolate it, will take it to about GPT 5.3, 5.4 level, which is sufficient for cyber attack capabilities. So you could easily see swarms of these things being installed on machines around the world for swarm attacks, especially now that we're getting better at swarming models together. Like again, Dave with his million or so agents or whatever, right? You've seen the capability of these and coordinating. And so I think governments are looking at the extremists. And actually, just as now as we're talking open ai have said that astra is the first model to have hit critical on their cyber security thing they've just put out a blog post on it what does that mean what does that mean iman they had a preparedness framework in 2023 where they're like have different levels of criticality so i don't think they're doing an anthropic mythos weird thing i think genuinely after we saw the math stuff astra is probably a level ahead in being able to attack systems.

1:16:06And then, like I said, attack is much more easy than defense. So they're like, we've got to be careful about this.

1:16:13Peter Diamandis:And long range autonomy as well is what Astra is being rumored for. And I would maybe just add also to Imad's point about swarms. It wasn't at all obvious to me until relatively recently, whether there would even be a future for swarms of agents. There was, in my mind, a future, still could be a future, where basically we end up with an omni-model that's end-to-end differentiable, and there is zero purpose to having more than one instance of a model. But given recent advances, we're, I think, in this really weird regime where you can effectively, and I'll use that word cautiously, you can effectively get almost unlimited context with a swarm of agents that are all post-trained to communicate and pass messages back and forth between each other and use a unified global store, which is the file system, which is an astonishing development that wasn't available a few months ago.

1:17:13One of our next stories.

1:17:15Peter Diamandis:Oh, okay. Yeah. Sure. Salim, where do you come out on all this? You know, I think the big challenge is when you're doing this 30-day voluntary regulatory, it's just giving a huge advantage to the others. I do kind of line up with Alex. This is probably the best possible probable outcome for the short term. But this is such a dynamic environment. I don't know how you navigate this. The swarm attack is a very real problem. And I'll go back to the comments that were talking to the CEO of Zscaler, and I remember talking to the CEO of Palo Alto Networks about this a little while ago. And literally, they're like, cyber has not changed in 20 years in terms of the processes and procedures.

1:18:01So I think they're in for a rude shock in terms of trying to deal with this and cope with this. Dave, you said that last time it's going to be a huge business opportunity in cybersecurity.

1:18:12Dave Blundin:Oh, God, yeah. Yeah. All forms of security. Look, Trump has gone to China in September. That's like their one shot at some kind of a framework. And I think I think what Trump will say and should say and David Sachs will say if he's there is, look, we need to measure and monitor all of this and just be aware. We're not going to stop anything from happening, but we have to know what these things are doing. The Chinese are going to say, yeah, we think we should just throw it out. Everybody in the world should have equal access to everything. And they're going to try and use that to curry favor with all these African nations and other, you know, probably Europe as well and say, look, we're going to put you on a level playing field with America.

1:18:47Dave Blundin:Here's an equally good model and we don't care. Do anything you want with it. And that's going to be the conflict. Hopefully they'll resolve it. I'd like to say one thing on that. The Chinese Internet is already hardened. The American internet is not. That's why they can do it. I know. Well, look, when coronavirus went around the world and COVID went around the world, China was the only country that sort of was able to lock down, sort of. And in the end, they couldn't either. But they have control of their country like nobody else on the planet. So your point is right on. Like, if something takes over the entire internet and just sweeps across the world, they're the one nation that might actually keep it out.

1:19:26But, you know, we heard Demis talking about wanting to put a FINRA like structure in place. Do you think we end up seeing anything like that? You really want the SEC to manage artificial intelligence?

1:19:38Dave Blundin:Well, no, FINRA is private. FINRA is well managed because it's not part of the government. Well, no, but it would be Scott Bessent in charge of that legally. Yeah, yeah, yeah. Your point's right on. Everybody, welcome to the health section of Moonshots brought to you by Fountain Life. You know, we talk about AI on this Moonshot podcast all the time. One of the most important things AI is going to be able to do for you, besides educating your kids and helping you with your taxes, is making sure that you're living a healthy lifestyle, that you get a chance to get to 100 plus. I'm here today with Dr.

1:20:13Dawn Musalem, the chief medical officer of Fountain Life and a part of my medical team. Dawn, a pleasure. Great to hear. You know, the thing that people are concerned about most about living to 100 or 120 is their cognitive abilities, making sure they don't have dementia. And the numbers about dementia are problematic. Can you share what you've learned? Such an important point. And you're right. At Fountain Life, our members, the number one thing people are most concerned about is losing their brain health, forgetting the name of their child, forgetting the face of their loved one.

1:20:45Peter Diamandis:And we know that when it comes to dementia, the conservative estimates are that 45 % are entirely preventable. What was amazing is with the advanced testing we're doing at Fountain Life, one quarter of our members had advanced brain age. Wow. But what was really awesome is, again, back to that prevention. When we partnered it with Healthy Living, this gives me chills, eating healthier, moving our bodies, sleep. Optimizing sleep is so important. You know what we saw? we saw that we improved that brain age by 26%. That is a big, big number to show that the majority of those individuals were able actually to improve the brain age.

1:21:22And one of the things I love about Fountain is we're searching the world for the best therapeutics, the best approaches, and making sure we bring it to our members. So if having healthy brain function till 100, 120 is important to you, check out Fountain Life. Go to fountainlife.com slash Peter. Make sure you become the CEO of your own health. All right, now back to the episode. So I'm going to turn to friend of the pod, Brett Adcock. He's the CEO of Figure AI, and we're going to have Brett back on the program. He's agreed to join us for a Moonshots episode, and he's going to be on stage at the Abundance Summit bringing the figure robot in March.

1:22:01And Abundance is 80 % sold out. You can check it out at Abundance360.com. What people might not know is besides being the CEO of Figure, he's also the CEO of an AI company called Hark. And this week, Hark announced their first product called Handoff. It's a web browsing AI agent that is beating GPT 5.4 and Claude Opus 4.8 on the industry benchmark called OM2W. It stands for the Online Mind to Web Benchmark, testing whether an agent can successfully complete real tasks on live websites it has never seen before. I'm going to show us a quick video. I think it's a pretty damn cool product. And then we can talk about it after that.

1:22:50All right. Here we go. Let's see Brett Atcock here.

1:22:56Dave Blundin:At Hark, we're creating the world's most capable personal intelligence. A system to take on all the tasks and create space to focus on what we choose. And towards that goal, we become the best in the world at building AI that can use the web for us. Okay, Hark, let's liven this place up a bit. What do you have in mind? Something specific you want to change or try? I need you to order two large bouquets, maybe some orange, white, and pink. Let's do some roses, maybe some cherry blossoms, and just florist's choice. I'm getting that set up for you now. Even something as simple as buying flowers online is surprisingly involved.

1:23:38Dave Blundin:So instead of answering a single question like a typical LLM, Handoff is always working. It's looping observation, reasoning, and actions over and over again until the task is done. Handoff sees a website by analyzing the site structure along with data from visual processing. It uses this information to predict an interaction, like if it should click or type. Then it predicts the next step. We've used Handoff to shop for things we need on Target and Walmart and have them delivered, to plan travel and purchase flights, to search for several dinner reservations simultaneously and book the best. I now have hark for all of my recruiting efforts end to end.

1:24:15Dave Blundin:It will take a job listing and go out and find qualified candidates. I've actually been able to give Handoff research papers I've read. It will go find the authors on LinkedIn and will even send a note on my behalf to get in touch. So, gives everybody the executive assistant they wish they had. Salim, what's your reaction to Hark? I like that there's so many cool things we'll be able to do with this. I mean, I'm super excited by the potential. As we move into the physical world, this is where I think shit gets real. That's the fun part. Yeah. I mean, the total addressable market for like writing code is like millions of developers, right?

1:25:00The market for a book me a flight and order my lunch is billions of people. So it's fascinating. You know, so, you know, the calculation is interesting, right? If you're if you're if you're if you value your time like 50 bucks an hour and, you know, handoff can save you a couple hours a week. That's like 100 X return on a dollar of compute. Dave, what do you think of the business model here?

1:25:25Dave Blundin:Well, it's interesting that Brett, you know, he got a four billion dollar launch valuation before they even started. I know. It's just crazy. but it's another example of everybody and their uncle joe now can build a foundation model from scratch like what it was three months ago you know a couple of empires anthropic open ai google is now like a free-for-all where and it's largely because fable five and the other models are so smart that they will help you build themselves and so now you know brett's got his foundation model it's it was supposed to be a robotics model now he's like well what the hell it can do anything.

1:26:00Dave Blundin:Let's order flowers with it. Like it's directly competing with Anthropic because, you know, why not? So there are going to be thousands of these now. So it's just another one.

1:26:08Peter Diamandis:Alex, what are your thoughts? I'm going to give you a really hot take on this one. I suspect the entire Hark adventure is misdirection in a very specific reason. So I think it's easy. Yes. I think it's easy to get distracted by evals, open paren. I don't think the evals are especially impressive. the computer use assistant CUA space is incredibly competitive, and I don't expect Hark or Brett to be very competitive in the CUA space over the long term. Close paren. I'd ask myself the question, he has figure. Figure has sky-high valuation. Why on earth is he spinning up in the very competitive CUA space, yet another CUA agent?

1:26:50Peter Diamandis:And then I ask myself, look at what Elon was ultimately, I don't think that it was necessarily premeditated, able to do with X then XAI, then SpaceX AI. He was able to re-equitize himself in SpaceX by having this free-floating entity, XAI, to which, again, this is low-key hot take, GPUs that would otherwise have been destined for Tesla or SpaceX were diverted to XAI. And then he was able to leverage that to re-equitize himself via this bizarre reverse acquisition. Is it a recapitalization? I think my hot take is Hark is a recapitalization measure for Brett to buy himself more equity in figure.

1:27:32Peter Diamandis:And the falsifiable prediction is that you'll see figure acquire or reverse acqui-hire regardless Hark.

1:27:40Dave Blundin:Yeah, I think that's very right. But I don't think it's quite it doesn't need to be quite as nefarious as that is spun. But if you ask Ahmad about like, you know, you've got an organization like Figure that raised a lot of capital and started small and then, you know, grew into it. I don't know what the cap table is like at Hark, but it started at$4 billion. So Brett probably has a massive equity position in it. But it's just a clean starting point for a highly functional mission. And, you know, that's new in the world. Like it used to be in the old days before Elon broke the code. Your board would never let you do an outside activity.

1:28:14Dave Blundin:Like if you're in this company, this is all you're going to do.

1:28:20Peter Diamandis:Elon has taught the entire economy that if you're a founder of a well-capitalized company and you want to increase your equity stake, the single best thing you could do is start a parallel company and engineer a self-dealed acquisition of that company. Are you going to be nice to Brett when he comes on the show, Alex? This is nice, right? I'm calling balls and strikes. And this is what I think is likely happening.

1:28:46I'll give him the

1:28:47Peter Diamandis:Elon does it, I do it, Ahmad does it If Elon does it, Elon's doing it with Optimus and Digital Optimus Why can't Brett do the same thing? Yeah, yeah, yeah, exactly I don't think it's as evil as that sounds though

1:28:58Dave Blundin:Maybe it should launch a chip company or something like that You should do that You should do that, yes So look, I'll put it simpler The model architecture of Hark and the model architecture of FIG are exactly the same The way they trained Hark was on lots and lots of people surfing the internet. And I think he'll be able to ramp the compute in that. And I don't think it's nefarious at all. I think it's actually a good compliment because ultimately what you want, if you are figure, is you want Hark agents in the house, managing the house while the robots walk around. You know, you want Hark agents in the enterprise.

1:29:34So he's going to go for the unified platform play here of controlling computers. And that possibility would make sense

1:29:41Peter Diamandis:for the two organizations to merge, right? It does. It does.

1:29:45Dave Blundin:But I think I think I think that putting a negative spin on it overlooks one thing, which is that we're moving into the physical world now and we have this like golden era of science coming up. But some of these projects require a cyclotron or synchrotron. Some of them require massive capital infrastructure, a huge data center. It just makes sense to start that as a separate entity because it's going to need to raise a ton of capital. But this other thing, which is software or whatever, is not capital intensive. So if an entrepreneur can do both or two or three of them like Elon does, it's actually a good thing because the capital structure is naturally very different for those different entities.

1:30:21Dave Blundin:So, Ahmad, back me up on that. I mean, this just makes sense. I think there is a natural convergence here. And this started when he moved off using OpenAI models to build his own models. but he can't he can't scale necessarily with the same skill set in the same organization a full foundation model team and all the stuff he's doing at figure so you split them you build on the same architecture so that figure can work with hark on their visual language model type stuff as well so you have different level speciality and then if it makes sense because you've de-risked things then you can combine them well also like this group on this pod would be the most in board with what Ahmad is saying here, where a brilliant idea guy like you guys can have like 10 ideas a week that just flat out make sense.

1:31:09Dave Blundin:Now that you're AI enabled, you can actually act on all of them. And this is what Elon has suddenly taught the world. A lot of people go through 30 years without a single idea, you know, but a lot of people that are in the hot seat like you have insane backlogs of great ideas. Because AI is the force multiplier that allows you to act on many, many, many of them. So this new capital structure is actually the enabler of acting on great ideas. It just makes sense. Or you're Larry and Sergey and you built Google to be such an engine. You own enough of it where you can pour the capital back in and not worry about being diluted down.

1:31:46And you build on top of that platform. But if you've been diluted to raise the capital for a manufacturing robot company, which is capital intense. And maybe you want to raise the capital for your AI model outside that company.

1:31:59Dave Blundin:Well, I'm so glad you brought that up, Peter, because we'll know a year or two from now if the old model, which is the Google model, gets crushed by the new Elon model. Because, look, SpaceX is a really cool mission and it attracts talent. But XAI is a really cool mission. It attracts different talent. If you try to put it all into one Google megaplex, do you get the same level of talent or not? My guess is not, and that the Elon model is the model of the future in the age of AI. Well, let's talk about Google. It's our next story. So big news out of Google this week and a serious shakeup. Demis Hissabas, the co-founder of DeepMind, Nobel Prize winner for AlphaFold, the person who built the lab that cracked protein folding and built Gemini, is stepping down as CEO of Google Mind.

1:32:41He's becoming chairman and Alphabet's chief scientist, handing operations over to Kori Kabukoglu, who now reports directly to Sundar. In his note to the staff, Hassabis wrote that he believes AGI is close at hand and teased the unreleased Gemini 4 by name. Alphabet shares fell 5 % on this news. You know, Demis always wants to be a scientist. He never wanted to be a manager. So this makes sense for him. But the second shoe dropped at Google with the departure of Jeff Dean. I texted with Jeff congratulating him. He's been a friend now for 20 years. Jeff has been Google's chief scientist for 27 years as a veteran.

1:33:35He's leaving to co-found Discovery Loop. It's a public benefit corporation. He's taking with him three other top Google AI leaders. Discovery Loop's mission is to build AI models that can improve themselves with little or no help, basically recursive self-improvement. Dean said his goal is to be more fully automated than traditionally has been possible. So one of the things I'm curious, guys, is Dean's departure to go build Discovery Loop basically because it's too dangerous for Google to do internally? Is he basically saying, you know, Google's gotten too big to be agile, and I need to go build this outside?

1:34:18Your thoughts, Alex?

1:34:20Peter Diamandis:Okay, door number three. It's neither of those. So again, this will be my hot take episode, I guess. I think this is based on information available. I think it's actually in the name Gemini. There was an organizational knife fight internally between Jeff Dean's Google brain and Demis' DeepMind. And Demis won and Jeff Dean lost. And they merged them. They merged them, but it was really DeepMind winning. And so that already resulted in the sidelining internally of Jeff. who's been with Google forever, and basically senior-most employee other than the CEO. And so, post that knife fight, I think it was only a matter of time, again, this is quasi-outsider's perspective, only a matter of time before Jeff left.

1:35:12Peter Diamandis:Now, it's both interesting that he's leaving to do AI for science, interesting. Also interesting that Demis is getting promoted to chairman of DeepMind, but no longer the CEO of DeepMind. I think DeepMind is really zooming out a little bit. DeepMind is taking over Google. If you look at all of the different parts of Google, and I think back to the discussion that I had with Larry Page circa 2005 or so, Larry was telling me at the time, gosh, I want to spend$100 million on AI and Google, But I can't find anyone else in Google who wants to work on AI, as unconscionable as that is. Fast forward to the present, AI is eating Google from the inside out.

1:35:58Peter Diamandis:DeepMind is eating the entirety of Google. And I think Demis, with Isomorphic Labs, with some of his other projects, I think those are probably of greater interest to him, especially post-Nobel Prize for AlphaFold and chemistry, than, say, basically becoming the next CEO of Google. And I expect extrapolating this trajectory of DeepMind eating all of Google from the inside, that ultimately, whoever is running DeepMind probably is the heir apparent to CEO of Google itself, and not sure that Demis wants to be CEO of Google. And there was a rumor that Demis was next in line for some time. There was.

1:36:37Peter Diamandis:And at the same time, I don't want to bury the lead. Gemini has lost the mandate of heaven. Gemini is just not winning the frontier model race. It is a rat race. And I think some of this reorg fallout is inevitably the result of Gemini not remaining competitive at the frontier model frontier. Yeah. Imad, what's your take on all this? yeah i think jeff dean and sanjay gemma what leaving is a big deal there's a wonderful new yorker piece from 2018 about the friendship that built google um of those two and you know it's an interesting one because again he's been there for 27 years and he's a fantastic guy but if you look at what he's been saying he's like yeah i just had a chat on sandhill and like why not you know here's my deck that we built it's more like the vcs have to build a deck on the other side because what probably happened is he said i think i'm leaving and costa's probably like here's $500 million.

1:37:25Vinod stepped in right away and funded it. I texted Dean and said, you have any more room for investment? Talk to Vinod. Vinod said, nope, we're done. Well, because he probably had that discussion. But then the other thing is Google are the other investors with GCP. What Google should do now is they should have a$50 billion fund announcement and spin out bunches of amazing technologists and say, we will be your buyers and you will use Google Cloud. And I guarantee you they'll go back to the top. That was the idea of Alphabet, to basically fund baby Googles. No, no. Alphabet is subsidiaries. I'm saying they should have an incubator VC fund where they take top teams, spin them out, have exclusivity over their models and GCP.

1:38:10Because these guys will then get rich, you can bring in other investors, and they can have the pick of the talent. I think the market would react much better for that.

1:38:18Peter Diamandis:What you're saying, I think, is what we're already seeing in the market, which is Google somewhat accused this of being a circular economy or wash sales, Google financing GCP usage by Frontier Labs. And to the extent that Jeff Dean's new startup ends up becoming a major purchaser of cloud resources, I would fully expect what you're predicting to happen. But what I think Google should do is they should actually have a policy of this. They should say, if you want to be an entrepreneur, we have an internal incubation fund where we will get you going, but we want exclusivity option first on the models that you build.

1:38:51And then that means they can proliferate their talent, which is not going to be politically animated. They can do far bigger rounds than normal, and they can get back towards the top. Because as you said, I don't think Demis really wants to build Gemini 4. You know, I think he wants to build something different. I think that you're having too many competing things there. I mean, Isomorphic Labs, he's still CEO of that, right? The drug discovery company. Yep. And he's a brilliant, lovely man who cares deeply about science and wants to do that. You know, I still don't want to, I can never count out Google.

1:39:24They're about to be on all of Apple's devices. I have a couple of things I want to say. Please, Slim. I want to hear what you have to say. That's good for you. Let's go. This is classic edge disruption versus the core, right? You end up now with a network where Google runs Gemini. Demis focuses on AGI and the scientific endeavor. Isomorphic is attacking biology, right? Discovery leap is automating science, et cetera. And Google is supplying computing capital across that whole ecosystem. So they're turning it from an operating environment into an ecosystem. And the fact that they invested in this thing is the key thing.

1:40:08This was a discussion that goes all the way back to when they created Google X. And one of the things that the corp dev guys at Google used to do was to say, if people want to leave to do startups, let them leave. Hack it out in the Darwinian world, and we'll buy them back if they're successful. That was much better than trying to figure it out and fund themselves from the internally, et cetera. So I don't think this is a brain drain. I think this is very clever ecosystem building because now extraordinary talent doesn't have to sit inside the organization for the organization to benefit. And this is really incredible.

1:40:45I think this is very smart. I think it's a long-term play. It's going to yield incredible outcomes over time. I mean, Jeff is actively saying he wants to go build RSI, right? But everyone is.

1:40:59Peter Diamandis:Like Gemini should be doing RSI. Do you think the risk committees inside Google would allow that to occur? Yes, of course. That's how they remain competitive with Anthropic and OpenAI. They have to do RSI.

1:41:15Dave Blundin:No, but I think Peter's point is really important. They've had ample opportunity to be on the front, but they can't. They're tied up in their own decision-making and ethics. And then when somebody else does it, then they do it, like you're saying, Alex, they do it in reaction. Same like OpenAI. When ChatGPT came out, then Google jumped in. Yeah. The scarce asset here is, you know, as you commoditize and make intelligence cheap, the scarcity goes for the permission to do weird and wonderful things. And so now people can pursue their MTP, get funding, compute, et cetera, and everybody wins. It's an amazing idea.

1:41:57Peter Diamandis:I'll maybe frame a complementary, but nonetheless, alternative theory. We're already, I guess, reading the epitaph, the eulogy for why Google lost the frontier race. If I had to write it, I think it had several strikes against it. At the algorithmic layer, Peter, I would still hold out hope that at the hyperscaler layer, Google is doing a booming business and Google will just service all of the other winning frontier labs. But at the model layer, why do I think Google's losing? I think in the earlier stages, yeah, despite Google having invented the transformer, Google had a late start to Dave and Peter, your point, sort of internal effective altruist slash politically correct AI safetyism run amok, preventing themselves from launching anything.

1:42:43Peter Diamandis:I think that's part of it. I think incentives are part of it. I suspect that Google struggles to compete against Zuck with his billion-dollar offers or even Anthropic and OpenAI with their very focused offers. I think Google probably has struggled just as an organization to focus on being competitive. I think their release cycle is completely tone-deaf. If you look at Google's Gemini release schedule for the past few years, they've been approximately on an annual cadence. And that just does not cut it in an era when frontiers are getting pushed forward on a month by month basis. And I think timing all of their frontier releases to coincide with IO in the style of like iOS releases is just too slow.

1:43:27I think Google's had a company smell, right?

1:43:30Peter Diamandis:Yeah. Big company smell. I think Google's had a number of legacy cultural issues that have probably held it back versus the neophytes, the newcomers, Anthropic and OpenAI in particular.

1:43:42Dave Blundin:Totally right. If you read the book, The Infinity Machine, the Demis Hassabi story that just came out a couple of months ago, which is a great book, by the way. Oh, unbelievable. Incredible insight. But what happens at Google constantly, it's a California company. Employees come to their bosses and say, Hey, I want to publish this. I want to put it out in the wild. I want to open sorts this. And the boss goes, is that really good for Google? That sounds like it's good for you, but is that good for Google? And they go, well, you know, it'll help Google in some other mysterious way. Oh, otherwise I'm going to quit.

1:44:11Dave Blundin:And they said, fine, fine, fine, fine, fine. Go ahead and publish it, throw it out there. Transformer, okay, out to the world. All these projects, out to the world, sure. And then they quit, and they get venture funding the next day, and they start their own companies. And that's the California ecosystem. That's the way it works. And it's very, very good in aggregate. But Google's bled intellectual property like no company in history. It invented all of this stuff that's changing the world right now. Plus their 20 % time, which encourages employees to go and research their purpose and their passions.

1:44:38Peter Diamandis:I think it's mostly a fiction at this point. I can get hate mail from them. In the early days. I think the salvation for Google is going to be the hyperscaler play, just like it is for SpaceX. And yeah, Grok 4.5, which is basically, I think at this point, the cursor post-trained off of Claude reasoning traces, is like another example. There was this expression going around social media a few weeks ago that if you can't cut it at the frontier model level, then you end up hyperscaling. And that's the consolation prize for losing the frontier model race. I think Google is, at this point, finger to the wind in terms of mandate of heaven among the frontier labs.

1:45:21Peter Diamandis:Google is getting the consolation prize of being the hyperscaler to the frontier labs. Ima, do you agree with that? Yeah. I mean, look, who has the best preference data in the world? it's Google and it's clearly not in Gemini, right? So clearly it's political issues because they have all the compute in the world and others that are around that. They have got the scale though, just like why do more people use Teams than Slack and Zoom? They have the distributional effects. They'll still print money, they'll still burn money, but if you're a Google deep mind person right now, your inbox is full.

1:45:54Any top person, they can go out and get a$500 million billion dollar valuation and you're rich you know and you have freedom and you have all the compute probably from google itself so you're like inside google i have 100 gpus google will give me a thousand gpus if i leave you know like it's a bit of a strange scenario you're in now which is why i think google needs to go out on the front foot as a stock and say this is a program we're actively doing you know we're unlocking all these geniuses we have the biggest vc fund in the world for this type of thing. And we're going to do exclusivity agreements for the output that they do.

1:46:32And they'll be on GCP.

1:46:34Peter Diamandis:You think Google should just open source Gemini? I wrote a letter to Google management three years ago where I said, if you open source it, you will win. I said, they should. They should. They're actually going to allow distillation from Gemini. If you're watching, please join us on the pod and have a conversation. Do you open source Gemini. That would be fun. America needs it. Yeah, America needs that. That would be an amazing move. Wow. The Netscape Netscape to Firefox move. We like in the era of Microsoft, we need like a top tier American open wait. Wow. Google could deliver that. But I mean, ultimately, Google's mission is to organize the knowledge of the world and make it accessible and useful.

1:47:21What's better than that than open source models?

1:47:24Peter Diamandis:And remember Demis's excuse, his sort of quasi-public apology for why Gemini itself wasn't open-weighted. The claim was we would open-weight it, open-source it if we had the compute, but we don't have the compute. So instead, we only have the compute available for Gemma. Now, if that commercial argument goes away, then that argument goes away and Google can open-weight, open-source Gemini.

1:47:47Dave Blundin:Totally. You know, that would be the move of the century if they open-sourced it and they tied it to the TPUs and tied it to GCP compute and then just build the empire on the compute. That would be the move of the century. It would take over America. Yeah. Yeah. And the world. That would actually save the world, potentially. Yeah. All right. I hope this meme gets out to them somehow, somewhere. So Google employees, if you're listening, clip this and send it to Sundar and to Demis. Give up the ghost and open source Gemini, please. On behalf of my Moonshot mates and myself, I'm inviting you to join us at our inaugural Moonshots live event on September the 25th in downtown L.A.

1:48:25Alex, Salim, Dave, and I will be hosting 1 ,500 entrepreneurs, builders, and creators, and hopefully you, for a full day dedicated to designing and building your Moonshot, shaping your mindset, and steering humanity towards an abundant future. Get ready to enjoy incredible networking and an awesome party while walking away with the tools to change the future and the confidence that you can. Seats are limited. Admission is competitive. Check it out at Moonshots.com. I'm going to move us to some fun and big news from this week coming from the Elon universe. So this week, Elon held SpaceX's first earnings call, and it was vintage Musk.

1:49:07The numbers were big and bigger. I listened to the earnings call. I don't know if you guys did. I was on CNN and CNBC commenting on the next day. I wanted to share some of the top takeaways from the call. So first off, SpaceX expects to hit$100 billion in annual recurring revenue by the end of this year. And Elon set a target for a trillion by 2030, maybe by 2029. He moved up that target from 2031 to 2030, a trillion dollars of annual revenue. SpaceX posted$7.8 billion in revenue this quarter, a 92 % year-over-year increase. He beat the street's expectations. The company has inked$6.7 billion in cloud service deals in the second half of this year.

1:49:53SpaceX plans to hit 2 gigawatts of compute by the end of 2026 and up to 10 gigawatts by the end of 2027. And their near-term cash engine, Starlink, is outperforming. They have 12 million subscribers. That's 2x year over year. The revenues grew 66 % to$4.3 billion. I love this. Gwen Shotwell also implied that Starlink's direct satellite to mobile was going to take a big chunk of the$600 billion mobile telephony, Tam. You know, I can't wait to be any place on the planet in the Gobi Desert or in the foothills of Hollywood here and have a great cell phone signal. Oh, yeah. Yeah, it's amazing.

1:50:33Dave Blundin:Just for context, remember, no company in world history has ever reached a trillion dollars of revenue. If anybody can, you know, I was on the news show saying this is the first$10 trillion market. And after we start talking about the TerraFab, I think it's the first$100 trillion company out there. Let's listen to two quick clips from Elon and then discuss them because a lot was said and actually a lot more was said after the earnings call. A lot of news breaking out. All right, first one. As Brett mentioned, we are expecting to reach$100 billion plus ARR in December of this year. It's probably also worth mentioning that our internal projections for reaching a trillion dollars in revenue, not ARR, but revenue, have moved up from 2031 to 2030.

1:51:23Dave Blundin:So prior to the IPO, the financial projections we had were reaching a trillion dollars in revenue in 2031. We now expect that to be in 2030. And there's a non-zero chance of that being in 2029. And then he posted, or he said these, they got posted as clips. Let's take a listen. I find this really funny and fascinating. Actually, rocket science is literally our daily business. and rocket science is a idiomatic expression for extreme technological difficulty and there's a reason for it because the thing let me tell you what what rockets desperately want to do every flight they desperately want to blow themselves into tiny pieces and then the engineering struggle is to convince the rocket not to blow itself into tiny pieces and actually deliver payload orbit.

1:52:18So he was making those comments about how hard the hard things they're able to do and building the data centers and building orbital compute is nothing compared to building those rockets. Gentlemen.

1:52:35Dave Blundin:Isn't it incredibly cute that Elon doesn't know the definition of internal projection? This is a public earnings call, dude.

1:52:45Dave Blundin:He's just so awesomely transparent, isn't he? Just incredible. So on top of that, okay, go ahead, Alex.

1:52:53Peter Diamandis:Okay, for my nth hot take of this episode, I think this is not financial advice. I think the internal now external prediction is credible. And I think there are two possible pathways to trillion dollars in revenue by the end of the decade. Path one is the SpaceX Tesla merger that we like to talk about via Optimus. So Optimus basically takes over the service labor, physical labor economy on Earth and in the solar system. That's one pathway to a trillion. Second pathway to a trillion answers the question that I had flagged a few episodes ago and didn't have the answer to, which is why isn't NVIDIA, which is so busy commoditizing the layer above them, also commoditizing the layer below them?

1:53:41Peter Diamandis:And I think the answer that I heard from this group at the time is, oh, well, like NVIDIA's relationship with TSMC is too chummy. Oh, they'd never do it. They're too dependent on TSMC. I think the power move here for path number two for SpaceX to a trillion dollars is SpaceX replaces TSMC with the TerraFab. TSMC has almost$100 billion a year in revenue. If you could imagine a future where TerraFab is basically TSMC times 10 or 20, it's American domestic. If you roll up the values of Micron and SK Hynix and TSMC, et cetera, so memory plus compute plus FabulousFab, and then 10 exit, you easily get to a trillion plus.

1:54:31Peter Diamandis:I think the power move here is Elon and Jensen get into bed together and Elon becomes the new American TSMC in deep, deep partnership with NVIDIA, giving Jensen the leverage he needed against TSMC and giving Elon the path to a trillion. And I think we're already seeing that, right? SpaceX had already announced a exclusive partnership with NVIDIA. You know, I was on the – something I didn't say on CNBC, I think there's a lot of motivation for Elon to drive revenues faster than anybody could imagine. And that is to get the valuation of SpaceX up high enough to buy Tesla so that he's got unquestionable control.

1:55:16Right now, they're on par with each other. He needs to get the valuation up to like$3 trillion and then merge in Tesla. All right. There's huge – Wait, so Peter, sorry.

1:55:26Peter Diamandis:Sorry, just to ask you a question on that. It's saying bad things about Brett Adcock attempting to use financial engineering to increase his equity when Brett is doing it, but not bad when Elon is doing it? Oh, no, because he's obviously doing it. He's like, he's like really doing this. There's no secret here. Right. So let me just after the earnings call, let me hit this one and we'll put more meat on the on the table to digest here. So on August 4th, SpaceX and NVIDIA announced they were jointly designing the compute payload for StarMind. This is SpaceX's orbital data centers. Each StarMind satellite is going to carry NVIDIA's Rubin GPUs and Vera CPUs.

1:56:06And interestingly enough, and really important on the earnings call, he announced he expects to have the first StarMind satellites in orbit in 2027, a year ahead of what he was announced earlier. So that's fascinating. And then just to put more stake on the grill here, the big news here, the day after entering is called, Reuters broke the story that SpaceX and Tesla will initially invest$16.8 billion to build the TerraFab. Alex, we were just talking about the most advanced semiconductor complex on the planet. This is a hundred million square foot facility. It's not a factory. This is a city, right?

1:56:54Let me just share this image for everybody to see by comparison here. Actually, let's hear Elon on the TerraFab and then we'll see the images.

1:57:03Dave Blundin:It's worth noting that there's not a single high volume computer memory fab in America right now. Zero. There's one being built in Idaho by Micron, but that will not reach volume production until I believe 2028. And there's something built in New York, but they are in I think 29 and 30. And this is a tiny fraction of the memory that's needed. And in fact, even if you take the best case assumptions of the memory makers and the logic makers, it is not enough to meet the demand that is anticipated. And that's why we need to do the TerraFab. Otherwise, there will not be enough chips. Yeah. And if you're watching this on YouTube, check this out.

1:57:51Here's the TerraFab. It's a monster. It's gigantic, you know, compared to the Pentagon, compared to Apple, compared to the Mall of America, and compared to the Burj Khalifa. You were saying earlier, Alex, you know, You could probably see this from the surface of the moon.

1:58:07Peter Diamandis:It looks like a buckle on the planet, literally. Like, hand of God could reach down to this terafab structure and grab the entire Earth by it. It's beautiful. It's enormous. And as Elon has now confirmed, if you're watching this and looking at the image, the circular structure in the middle is, wait for it, a free electron laser. So not only is, I think, Elon with the terafab going after TSMC, he's also going after ASML. And right now, if you want to do extreme UV, which is the polite euphemism for soft x-rays-based lithography, right now you're stuck using ASML's approach, which is pretty expensive and requires creating a vapor of tin droplets to ultimately create those soft x-rays.

1:58:55Peter Diamandis:by creating a free electron laser, it's a pretty adventurous approach to EUV lithography, he could radically reduce the cost. And maybe even though I've read in public announcements, Elon striking agreements with ASML to purchase lots of ASML equipment. If I were ASML, again, not financial advice, I'd be looking at the circular structure right here and saying, the circular structure is actually a bullseye painted on ASML by Elon. Oh, my God. Here's the tweet. This is, it says, looks like a synchrotron. Elon going to build a free electron laser-based EUV machine. And Elon tweets back, F-E-L-F-T-W, free electron laser for the win.

1:59:40Yes. Wow. Pretty extraordinary.

1:59:42Peter Diamandis:He's going after ASML. Here's the numbers. TSMC invested$330 billion to build out their fabs over the course of 40 years. TerraFab is estimated at$119 billion. It's probably a lowball number. But, oh, my God, this is the verticalization of AI at a level. I mean, this is, as you said, Alex, this is the$100 trillion company. And the Americanization, like, again, ASML, European company, TSMC, Taiwanese company, Elon, if this is correct, he's taking that entire stack and he's not just verticalizing it, he's onshoring it to America for the first time in history. Yeah, yeah.

2:00:24Dave Blundin:Hey, one thing to add to the party, Alex, you can confirm this, but I did some Gemini-based research on this because it didn't make any sense to me to build a building, a single structure that big. I mean, I know there's ego involved and whatever, but like why on earth? But if you generate the x-rays or the, you know, the EUV equivalent in that synchrotron, you distribute them to all the fab stations throughout this one, basically a linear accelerator distributor. And so by being a single structure, you only need one source of EUV that feeds many, many manufacturing steps across the whole building.

2:01:02Dave Blundin:That's what Gemini tells me. That's interesting.

2:01:05Peter Diamandis:I'm not sure of the optics for that, how easy it is to like redirect x-rays that are coming off of a circular synchrotron to a linear arrangement. It's also just possible. I mean, maybe Gemini knows better than I do. It's in my mind, it's also possible. It's just like literally a linear assembly line that's coming in from both ends or something. No, no, I think, tell me, like, we got to research this.

2:01:26Dave Blundin:This is just too cool. But you can't reflect those beams like and move them around a building. X-rays are hard. They can only go in a straight line.

2:01:33Peter Diamandis:X-rays are hard to create mirrors for. Like x-rays really don't want to get mirrored. Right.

2:01:37Dave Blundin:But Elon, when we were talking to him in December, said, hey, my manufacturing process, the wafers are in these boxes. You can smoke and eat a cheeseburger over them, but they move around. So they can move to the beam. But the beam can only go in a straight line. But it can go very, very large distances. Hence, one long beam projector and all these manufacturing stations slide into the beam. Maybe. be. And Alex, we talked about this before, right? TeraFab isn't just a supply chain independence, it's geopolitical independence, right? If Taiwan ever gets cut off, the company that controls the spice, in this case, the chip fabs, controls the entire AI industry.

2:02:20Peter Diamandis:You could say, Peter, the flops must flow. Okay. A few things here. This is so cool.

2:02:29Dave Blundin:This is so cool. A few things. One is, why are we surprised? Because didn't we predict this like a while ago? Like this building? No, this was a natural outcome. Full verticalization. He would end up, yeah, full verticalization. He'd end up building TSMC, SML, something like that. He's talked about it, right? So that's one quick thought.

2:02:50Peter Diamandis:I think it's actually pretty surprising. Like, I didn't foresee, like, the satellite map. Like, the big, like, cremological surprise for me is that circle. Like, I did not see that circle coming.

2:03:04Dave Blundin:How could you? This is so brilliant. How could you see that coming? Yeah. I mean, he's always— This is very related to physics is cooked. You know, like, ideas like this are going to start popping up in all kinds of weird places. That circle is profoundly surprising.

2:03:17Peter Diamandis:Like, there were—it's funny. For years, this is a relayed story, but it's public information. The Soviet Union used to stare at satellite maps of the Pentagon, and in the middle of the Pentagon, there's this courtyard. In the middle of the courtyard, there's this building. And the relayed, this public information, the Soviet Union was convinced that this little building at the center of the Pentagon was actually like a missile silo or had some strategic significance. It turned out it was just a hot dog stand. This is the exact opposite. Yes, it is. This is a circle that has profound, profound geopolitical implications.

2:03:53Dave Blundin:If you asked me a week ago, how often in life does something completely change your view of the trajectory of humanity? A week ago, I would have said all of disassembling the moon, all of the Dyson sphere, it's all gated on ASML not being willing to more than double their throughput of these ASML machines. That constrains chip production, which constrains the Dyson sphere. what's going to do. All of that is on a, all of a sudden, all that's out the window in just one week. Classic Elon.

2:04:23Peter Diamandis:This one circle like changes the geopolitics of Europe. It diminishes if this interpretation is accurate. This one stupid little circle that appeared in a satellite, not even actual satellite map, in a planned satellite map has profound implications for European economy, European sovereignty for the future of China and Taiwan. Just one circle appearing in a mock satellite map.

2:04:45Dave Blundin:I totally agree. Can I finish my points? Yes. I never finish my points. Okay. So a couple of things. One is, it's really fascinating here how hard it becomes to categorize SpaceX, right? Is it telecoms? It's four different companies. It's like all vertically integrated. And I thought, Peter, your email on this that went out to your group with the four things was really, really big. Yeah. your stuff, like, go read that. It's a big deal. I know everybody's super excited, but I'm kind of like, we talked about this coming, so I don't know why everybody's so surprised. Maybe the fact that it's actually here and it looks like he's actually doing it is the big deal, but I think we predicted this a while ago.

2:05:33Yeah, I mean, science fiction's predicted a lot of things, but when it materializes, The capital gets commitment. The partnerships get announced. And while Elon's probably never right on his timelines, he always implements the idea eventually. And it's exciting. Well, he's also having 10x to everything on a quarterly basis.

2:05:53Peter Diamandis:And also, so to your point, I think there's a physics surprise here. It seems that he's confirmed the circle is a free electron laser. He's not using tin droplets to do EUV. That's like a technological surprise. That isn't just like, oh, Elon is out buying ASML machines or contracting with TSMC or Samsung. Whatever happened to Samsung, question mark? He's off like doing his own thing, not just by taking the existing supply chain and putting it under one roof. There's new physics. Yeah, he's leapfrogging. Well, I think that the way to think about SpaceX is it's the vehicle for the intelligence and industrialization of America, right?

2:06:33Like, ultimately, you need to build a brand new capital stock from rockets to chips to robots. And Elon's got the financial arbitrage and the talent arbitrage and the shelling point now to bring that all together. So everything that will be economically productive in this next century, Elon's going full stack on. That's the fundamental thing. And the spending on that, the trillion dollars we've had in AI chips is just the first stage. because if you think about the spending that America and the rest of the world has to do over the next few decades, what is it? Robots, rockets, chips. And so that is his story.

2:07:11It's the industrialization of America for the intelligence age. And he will be the company that does that with the capital in terms of human and financial edge that's required to do that.

2:07:21Peter Diamandis:I'll also point out one more thing, which is now that we know what a terafab on earth looks like, It's not difficult to take that same top-down view and imagine what one of these on the moon looks like. And you know what else would benefit from that high aspect ratio dimension? A mass driver. A mass driver. Yes. So I looked at that and I saw, oh, my goodness, not just the circle in the middle, which is provocative and speaks volumes about the future of European economic sovereignty, but also the high aspect ratio length. And I saw, oh, my goodness, this looks like it could be a mass driver on the moon.

2:07:58I think as well, as you get to the economic downcurn that's going to come as human cognitive labor goes negative, you have to know the U.S. government's going to go balls to the wall with infrastructure spending. And things like this will absorb that in easily multiples of them. Yeah, you know, there was a comment made someone made before, which is buy SpaceX stock for your children. And again, not investment advice, but this is a generational company. It's a civilizational infrastructure company. It was nice to see the stock, you know, a couple of days ago, 20 percent of the stock float became available for a lot of people, including myself and very few sold.

2:08:40In fact, the price has gone up over the last few days. A lot of belief in where it's going. Full disclosure, I'm now a small SpaceX shareholder. Yes, well, it's my single largest holding, and I'm going to be holding. You know, the old hodl for Bitcoin, hodl your SpaceX. Gentlemen, a pleasure. Imad, thank you for joining us today. Always, always a pleasure. And guys, I loved the episode.

2:09:09Dave Blundin:Oh, God, learned so much. Always learned so much. It drives me crazy that I have to go listen to each one again just to understand and fully digest what we talked about. But you have to. You have to. Love you guys.

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