Moonshots: The Hugging Face Breach, Moonshot AI Valued at $20B, and Living to 1,759 Years Old | EP #273

Sourced by podcast-ingest on 2026-07-27. Auto-transcribed via AssemblyAI (universal-2, en). Speakers identified by AssemblyAI Speaker Identification using the per-podcast host/regulars hints; the resulting label→name mapping is in the frontmatter. Duration: 2h33m. Episode page: (not provided). Audio: https://traffic.megaphone.fm/DVVTS3160133299.mp3.

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The mates discuss Hugging Face breach, Moonshot AI being valued at $20B, and living to 1,759 years old.

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Peter H. Diamandis, MD, is the Founder of XPRIZE, Singularity University, ZeroG, and A360

Salim Ismail is the founder of Open ExO, a GP at Exponential Venture Capital/The Organizational Singularity Fund and a sought after global speaker and thought leader.

Dave Blundin is the founder & GP of Link Ventures

Dr. Alexander Wissner-Gross is a computer scientist and founder of Reified

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*Recorded on July 23rd, 2026

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Transcript

Peter Diamandis: Hugging Face, the leading open platform for sharing, testing and deploying AI models, it got breached by an autonomous agent. When the Hugging Face security team tried to analyze the attack using either anthropic or OpenAI, both models refused.

Dave Blundin: Who knew all those sci fi writers were right. What do you know?

Peter Diamandis: Moonshot AI is valued at about 20 billion, and we have our frontier labs here at a trillion each.

Salim Ismail: When startups raised money in a very abundant environment where they could raise lots of money, they all failed. It was the ones that raised money in the toughest environments that succeeded.

Alex: Again, the question that I've asked Previously on the Pod. What the heck are Western Frontier Labs doing with all of that capital?

Peter Diamandis: If we cured every cause of aging, all of the 12 hallmarks of aging, how long would humans live? 1,759 years. There are no fewer than six companies currently working on partial epigenic reprogramming.

Alex: The obvious solution, this is in the style of Aubrey De Grey, is

Dave Blundin: Now that's a moonshot. Ladies and gentlemen,

Peter Diamandis: welcome to Moonshots, everyone. Your number one podcast on all things AI and exponential. Your front row seat to the singularity. Not the coming singularity, Alex. The singularity.

Alex: The singularity that surrounds us right now.

Dave Blundin: It is right now.

Peter Diamandis: Yeah. This week, news broke fast and it broke containment, literally. I'm here with my moonshot. I'm here with my moonshot mates. Awg. Our in house. Asi, our official super. Thank you, Peter, very. You're welcome. You've been elevated. Dave Blunden, our emperor of AI investing. Saleem Ismail, our globetrotter who's now in his home and the CEO of OpenExo. I'm Peter Dmandis, your exponential host and your abundance evangelist. And I have to say, guys, I do love our audience. You know, the comments we get are pretty extraordinary and I want to take a second just to celebrate them and say thank you. It's worth taking a moment. I'm going to read some of the comments for everybody listening. We do read your comments every single week and the outpouring has been extraordinary. So let me take a second to say thank you.

Dave Blundin: And this is just a random selection. Yeah.

Alex: There's definitely no bias in the sampling.

Dave Blundin: None whatsoever. No.

Peter Diamandis: Well, no. I mean, listen, I just want to share the love back at them. So Mercurian says, best tech podcast ever. Can't get enough. Never stop, guys. And I guarantee you we're never going to stop. Jake says, I love this podcast. My favorite tech podcast. It's my go to when I want to feel good about the future. And that is one of our goals. Making sure you feel optimistic about where things are going. Lois says, thank you, thank you, thank you. Millions depend on you for trustworthy info on this evolution that's engulfing us. You are all gold. Ian says, you guys bring an extreme amount of value to my life. Thank you, Ellington. My biggest fear is that this podcast goes away. Love you guys. Okay, Alex, are we going away?

Alex: That is not the plan.

Peter Diamandis: That is not the plan. In fact, we're probably going consistently two days a week and can't stop, won't stop. Yeah. My favorite comes from my very comment comes from Digital Greece. He goes, peter, suggesting that AWG make a first shooter game involving tickling bunny rabbits was my primary takeaway.

Salim Ismail: I have a comment.

Alex: Important development, clearly.

Peter Diamandis: Yes.

Dave Blundin: My.

Salim Ismail: My wife Lily says to me the other day, this recursive self improvement thing, can it apply to husbands?

Peter Diamandis: Well, how's it going?

Salim Ismail: It's not so great.

Dave Blundin: I'm very linear. The actual bunny rabbit game, where did that come from? Somebody submitted it.

Peter Diamandis: Well, so at the end of this pod today, if you stick around to the end, we're gonna show you2 subscriber created video games that AWG inspired. So super excited about that. So everyone watching, we appreciate you. We do read your comments. They give us fuel. If you're new to this podcast or if you haven't yet subscribed, please do take a moment to hit the subscribe button. Knowing you care enough to do that really fuels our work. Guys, I hope you enjoy all these comments as much as I do.

Dave Blundin: I love the trustworthy. The trustworthy comment is one that kind of warms my soul because actually I've been listening to a bunch of other podcasts and everybody seems to have an agenda.

Salim Ismail: Yeah.

Dave Blundin: And you know, even if the agenda is just more ad views, you know, so they get all dystopian. But. But often it's like some political agenda or some, you know, some product agenda or whatever. It's like, wow. It is. It is actually hard to find trustworthy information. And we just do it because it's

Peter Diamandis: fun and we love it and we spend tens of hours each on this. Every week I get a blast of emails from awg. I get selections from Saleem, and we curate and really try and provide you what just happened the last three days and what does it mean? Yeah, please.

Salim Ismail: I have another crazy little anecdote. I met somebody the other day who said, I listen to moonshots all the time. And I said, oh great, I hope you tell your friends he goes, are you kidding me? No, it's my competitive advantage. I was like, no, that's not the A.

Peter Diamandis: But, okay, fine. Oh, that's funny. All right, everybody buckle up. This week we're going to cover open source, closed source debate, AI escaping containment. Elon's newest Moonshots, the Exponential Future of Science in America. Updates on the race towards longevity, escape velocity, and the latest on UAPS from the White House. All right, let's jump in. Our first story today is the growing debate on whether or not to sanction Chinese open weight models. So last week, China we called our emergency pod. Thank you for the feedback, everybody. To discuss how Moonshot AI, a Chinese AI lab has just released an open weight model called Kimi K3. That caught every single US frontier lab by surprise. So K3 is a 2.8 trillion parameter model, the largest open weight model ever released. That's approximately the same as America's top frontier models. Claude Fable, 5 GPT 5.6. But at a fraction of the price and a fraction of the investment. This week, the debate on how the US should react has split into polar opposites. So I'm gonna give you four stories, guys, and we'll talk about them. Two days ago, CNBC reported that Treasury Secretary Scott Besant publicly floated the idea of sanctioning China and Kimike 3 over the theft of Anthropic's AI model weights. I should say the alleged theft. The claim followed a post by Michael Kratios, director of OSTP, publicly asserting that he had evidence that Moonshot AI had illegally distilled Anthropic's fable model to build K3. And if you're a fan of the pod, you'll remember last week or two weeks ago, DB2 and AWG defined distillation. It's a method by which the output of a powerful model. The teacher model, is training a student model. Two other stories tell the opposite side of the debate. So in this slide, here is a post from David sachs who says kimik3 just fixed 15 critical security bugs that Kodaks and Fable refused because of cyber guardrails. There's no reason to limit America models American models on tasks that Chinese models handle without issue. We're only making ourselves less competitive. So a powerful debate rages on. In a related interview with Axios yesterday, Jensen Huang, the CEO of Nvidia, is pushing back hard against efforts to ban Chinese models. Let's listen to the video from Jensen. Let's discuss this debate. I want to see where you guys fall out on this simple question. On the front page of the Wall Street Journal. Should American companies be allowed to use Chinese AI models? Absolutely.

Dave Blundin: Absolutely.

Peter Diamandis: So this Chinese competition is coming fast and furious. What should US AI companies do?

Alex: These Chinese models are excellent.

Peter Diamandis: The markets misunderstood the impact of Deep Seat the first time. It's misunderstood. Yeah, it's misunderstood the impact of Kimi again this time.

Alex: I think first of all, with great

Peter Diamandis: AI open models, it's great for the whole industry.

Alex: Great models lead to great use, which

Peter Diamandis: leads to great growth. All right, so gentlemen, where do you come out on this? Let's go to you first, Alex.

Alex: This reminds me a little bit of the late 90s and early 2000s when Microsoft viewed at the time Linux and Open source as a cancer. And if you remember all the litigation wars between Microsoft as sort of the paragon of the commercial software industry and then a variety of open source outfits. History rhymes. In this case, I think there is going to be an equitable equilibrium to the extent that there can be an equilibrium in the middle of a singularity. Not quite obvious to me what precisely that equilibrium looks like, but I would suggest there are accusations flying in both directions. On the one hand, obviously Anthropic is incentivized to push an agenda to prevent Chinese developers and Chinese Frontier Labs from skimming reasoning traces, which is the subtext of what Secretary Besant has said. It's the subtext of what Director Kratzios has been alleging that the basic concept of operations as alleged in the subtext is that Chinese Frontier Labs have been using proxies to deceive Anthropic and or other providers into giving up valuable reasoning traces from many interactions with Claude and other models Open Parens for those who are arguing that Kratzios and Besants allegations can't possibly hold weight because they would require a time machine by the Chinese Frontier developers in order to access Fable before it was actually released. I would remind that Fable was almost certainly pre trained off of a common corpus and probably post trained off of a good deal of the same synthetic corpus as earlier models like Opus 4.8. So the signatures would be reasonably expected to rhyme if say, K3 were being post trained off of Opus Opus 4.8 and elements of that in the reasoning traces bore a striking similarity to Fable 5. Close Perrin there are. There are.

Salim Ismail: Thank you for the accurately I can

Alex: go a few layers deep in the stack Open paren One of the earliest signs that we would get codegen was when LSTM models could successfully match parentheses close Prayer so I would say there are allegations, and I think reasonably well supported ones that Anthropic and OpenAI in the Western frontier labs, as we've talked in the past about intelligence fundamentally being a compressive phenomenon, that they're basically compressing all of this knowledge that's already out there. We'll talk I think later in the pod about the lawsuit that was just settled against Anthropic regarding copyright. Fundamentally all of these American frontier models are about compressing knowledge. And I think this is going to be very heavily litigated before we arrive at some sort of global consensus. At what point does compression become a transformative act? I think that's sort of part of the core legal essence here. Not from an export control regime. Export control probably doesn't care about this. And we're already seeing Secretary Besant gesture and Cratius gesture at Chinese labs improperly obtaining Nvidia GPUs in order to obtain it as sort of a two legged argument. One, that they're probably siphoning knowledge via reasoning trace proxies from Western labs and two, that they're improperly gaining access to Western GPUs. So at every layer of the stack. We haven't achieved equilibrium on this yet, but I think we will. And I think it will ultimately be determined by a combination of export control. Do we just basically ban reasoning traces via export control? And some might argue that under the present export control regime for certain countries, including greater China, we already have. And then secondly, how do we view compressed information as a transformative act? And I think those haven't been resolved yet. But I think in the near term future, our regulatory regime as well as China's have every incentive to arrive at some equilibrium.

Peter Diamandis: Dave, where do you come out on this?

Dave Blundin: Just to clarify one thing, Alex said a couple of times, their transformative act would clear you of copyright law. So you know, you know when Google indexes a page and then shows you a thumbnail of what you're about to see, that doesn't violate copyright because it's a transform. Thumbnailing is a transformative act.

Alex: Or fair use.

Dave Blundin: Or fair use. And you know, for a while their search engines had a little preview, little hourglass or little binoculars and you could mouse over it and see the page you're about to go to and they're like, nope, that is a violation of copyright. Now you're showing the underlying article. So that's, that's the distinction that Alex is drawing there. For me, the whole story isn't about the actual story. Like they didn't steal the weights. They set up 20,000 fake accounts to run thought traces and see what anthropic would say. And then they use that data for training. I think it's almost 100% sure that that's what happened. So what? Like who in their right mind building a neural net wouldn't do that? Of course they would. Compared to all the things China has done historically in terms of intellectual property, this is such a rounding error. So why is the White House making a big deal out of it? They need a pretext to have a very urgent negotiation before all hell breaks loose. I mean Kimi, K3 is in just a couple days, right?

Peter Diamandis: Yeah, 27 days.

Dave Blundin: 27 four days is the turning point in all of history where an AI capable of self improvement is out in the wild in open source format where anyone can use it.

Peter Diamandis: Just to be clear, that cat back in the bag, K3 will be available in hugging face for anybody to download, put on, prem modify as they wish. I mean, isn't it ironic that we're talking about distillation since anthropic and open the eye in every model has effectively distilled knowledge from all of humanity.

Alex: And that's exactly, that's exactly my point. Like there's this ironic symmetry here. They've been compressing human knowledge and now China, these Chinese labs are, are taking basically the decompressed knowledge in the form of reasoning traces, recompressing it onto a relatively vanilla architecture that achieves near state of the art performance. It's incredible.

Salim Ismail: Yeah. Salim, well this is like Sisyphean, right? Once intelligence becomes software, you're trying to contain it geographically is going to be near impossible. I mean you're trying to solve a governance problem by lobotomizing the technology that never, that has never worked in history, ever. Why do we think it's going to work now? Is kind of an incredible commentary. I think David Sacks had it about right. You just gotta let it open and let the market decide. They're gonna figure that out. If you're worried about attackers, they're not gonna use the most compliant hosted model. They're gonna use open weights, local models and uncensored agents that are gonna do what they wanna do. And if the defenders, if the defenders can't access comparable capability, then you've got creating an asymmetry in favor of the attacker. It's just like what are you thinking? So I've got strong views on this.

Peter Diamandis: Saleem, the viewers loved your comment last week that intelligence wants to be free and accelerating. One thing to note, is that I

Salim Ismail: believe I've copied Parafram open parentheses too.

Alex: You know, thanks for the footnote apropos.

Peter Diamandis: You know, one thing worth noting is that and I think Anthropic has the largest lobbying budget out there in D.C. right? So they're using everything they can to protect their position. And I don't know if you guys saw the the data recently was published today that Anthropic's meteoric revenue rise has started to plateau.

Alex: Yes. At least as extrapolated by some third parties. That is exceedingly interesting.

Peter Diamandis: Yeah, it is.

Dave Blundin: And that's for lack of compute, Right? They're just sold out.

Alex: Well, the the plateau as extrapolated by this third party does suspiciously coincide with the regulatory hubbub over Fable and Mythos. So it is possible that this is either compute and or regulatory constrained growth.

Salim Ismail: By the way, one more comment on this Open Models distribute capability to the edge which is the Every single innovation comes by doing things very differently at the edge. The Internet worked. I remember Brad Templeton talking about this. The Internet worked because it was a stupid network. All it did was pass packets and the intelligence as the edge cases and the apps and so on.

Peter Diamandis: The application layer on top. Right?

Salim Ismail: Yeah. Small teams can access capabilities that totally couldn't be utilized before. You needed whole departments or whole corporations and now you have a small team accessing that capability. We're going to see that massive explosion of innovation come as a result and you should be thriving, going driving straight for that target.

Alex: I think this is fundamentally an accelerant of Western progress. I'll ask again the question that I've asked previously on the Pod. Just what the heck are Western Frontier Labs doing with all of that capital? You can explain even arguenda window if the Chinese labs like Moonshot are just getting whatever alpha they're siphoning, allegedly siphoning from reasoning traces via thousands of proxies from Claude. Even so, on the budget that they have, something doesn't add up. It's hard to imagine that Anthropic and OpenAI with all of the billions of dollars that they've raised for compute could be almost out competed by a relatively modest at least from a capital expense perspective, as best I understand it by Moonshot merely siphoning reasoning traces on again a relatively vanilla architecture. Sure, they have their own in house improvements to the attention mechanism and probably a bunch of other mechanisms.

Dave Blundin: Hold on, hold on. Those attention mechanism changes cut the memory use by 75% and when you read them in hindsight you're like oh I could have thought of that. But they're actually pretty brilliant. I mean it's pretty, I mean it's actually, you know, Alex, it's almost inversely proportional to budget. You know, I'm kind of making your point. But if you look at Google and then Meta and then Anthropic and the amount they've spent and then Moonshots and you draw a line, the least spender has the most progress, but it's just a few.

Peter Diamandis: But Dave, isn't that cool?

Dave Blundin: Brilliant insights.

Peter Diamandis: Haven't you, haven't you seen that lesson play out in startup after startup? The companies, in my experience, the companies that are super well funded become lazy and they throw money at problems instead of trying to throw intelligence and solutions at problems.

Dave Blundin: Yeah, yeah, for sure. I mean you get corporate bloat. Everybody, you know, Salim is the expert on this topic. Of all people on the planet, you get this corporate bloat and then you need to build an entrepreneurial environment. But it's usually just a few people, just a handful of people that are unleashed. And you know, the Kimmy dude is unleashed. He's just freaking figuring it out. Go ahead.

Peter Diamandis: I cut you off for reference by the way. You know, Kimmy, moonshot AI is valued at about 20 billion and we have our frontier labs here at a trillion each, thereabouts. And to the point that Alex was making.

Salim Ismail: Salim, you take a zero from one and put it on the other and you'll get it balanced. Right? Just two points. Just to react to Dave saying, if you look historically at venture backed startups, when venture, when startups raised money in a very abundant environment where they could raise lots of money, they all failed. It was the ones that raised money in the toughest environments that succeeded because that tension and that constantly worrying about run makes you very lean and very hungry.

Peter Diamandis: Like a fine wine.

Salim Ismail: Yeah. And there's one more thing I want to say about this whole thing. You've got three different things going on here. You have open source development, you've got model distillation and you've got the theft of protected assets. Each of those requires very different responses. If you try and bucket them all together into one like policy, you're going to end up in a mess because you're going to end up in gridlock around those and you're going to cut off the head of everything you're trying to build.

Alex: So I think there's in the style of Sherlock Holmes and the dog that didn't bark. I think people aren't thinking enough about the dog. That's not barking in this case. And that's the architecture. Exactly. No one is accusing Moonshot of of stealing a Western Frontier Lab algorithm or architecture. No one. As far as I can tell, no one is saying that moonshot for K3 stole trade secrets regarding the internal algorithms for the latest GPT or claude. As far as I can tell, they're saying that through perhaps allegedly improper usage of APIs and proxying and maybe use of GPUs that they weren't supposed to be allowed, that they were able to essentially reconstruct, construct the innards, the weights if you will, of the models on potentially a different architecture. But I think the dog that's not barking in this case is the model architecture. Again, K3 is. Dave, the point is well taken that the attention mechanism Kimilinear architecture KLA is interesting and it seems to have favorable scaling properties, but it's not magic. Something again is probably missing here. But in any event I would say the existence of K3 at near frontier. Well it's already on the price performance frontier, but I should say near state of the art near soda performance. Basically the number three model in the world now has surely got to light a fire under anthropic and OpenAI to up their game relative to their capital. If this doesn't do it, then I don't know what will.

Peter Diamandis: Well, in which case Alex, it's a good thing for America to have. You know, it's the race to the moon again, right?

Alex: Strategically, it's a heck of a way to light a fire under them and make them far more capital efficient apparently than they otherwise were.

Peter Diamandis: Yeah, I mean Celine, we've talked about this before. The large corporations who are not innovating because they're bloated in their architecture of human architecture and in their capital budgets, the best way to do it is to put a new startup on the edge. It's what Astro Teller, who's going to be one of our guests at Moonshots Live talks about is you need to build a Moonshots organization on the edge outside that's willing to take risk, that's willing to try brand new things, that's willing to go for it.

Dave Blundin: The timeline on all these events is just mind blowingly off. I mean it's, you know, the White House is, is saying look, you stole valuable intellectual property. We're softening you up for a visit in September, right? So a whole delegation is going to go from D.C. to China in September to negotiate the future of AI let's soften the turf now. That would have made a lot of sense a quarter ago before Kimmy K3 hits the world. But now it's like September might as well be 10 years from now at the rate this thing is evolving at this, at this stage. And you know, maybe, maybe, you know, we're doing it in house, so maybe I'm seeing it more acutely than a lot of people out there. But the White House must be listening to a bunch of academics saying we've got a couple years. So go ahead and have this trip in September. Start negotiating like you do not even have until September. I guarantee it.

Alex: So let me

Peter Diamandis: two questions you guys. Number one, if in fact the US wanted to sanction this, how would they possibly do it? It's going to be out on the open Internet on the 27th this month, right after that date. It's I'll download it, I'll download it as soon as possible until I'm on my Mac studio, which would have to get.

Salim Ismail: Which is faster than the September visit.

Dave Blundin: Yeah, it's not, it's a tiny file too. You can easily.

Peter Diamandis: How would you sanction? How would you sanction it? You just say it's illegal to have it.

Salim Ismail: Yeah.

Alex: If I were the regulatory apparatus in the US and I wanted to de facto sanction China for use of K3, I wanted to keep it out of the Western bloc, I would say and noting that there has been discussion of this demis FINRA style entity under commerce next to the sec, I would say new regulation. This is if you're a US corporation, you're not allowed and you want to have any dealings with either the US government or with companies, you want to be in the supply chain of the US government, then you can't use this model. If you're a non US based company and you want to be in the US or basically the US led Western AI bloc that's forming the Pox Silica, then you can't use this model and be in good standing. All you have to do is regulate the largest users which as OpenAI's pivot from consumer to enterprise is established, the power users are going to be the enterprises and it's far easier I think to suffocate if one wanted to to suffocate the enterprises by making it exceedingly painful for enterprises to use this for any commerce.

Dave Blundin: 100% right. Could not be more right. And so I think the game plan before Kimik 3 would have been okay, anthropic, OpenAI, Google, you guys X, you guys get so far ahead of the world. And this AI is the global workforce of the future. This is equivalent to a trillion geniuses, but it only is coming from the United States. So unless you want a trade war and you want tariffs for the next thousand years, you have to do this, this, and this and this to prevent it from being used as a weapon. Now, with China vaulting to the front with Kimi K3, that game plan is out. Now you have to go to China and the two countries have to actually agree on a strategy for letting the whole world benefit from this and use it without it being used as a weapon. But now the timeline on that negotiation is crazy short and it takes two parties agreeing, which is a lot harder than it would have been in the first game plan.

Salim Ismail: I would like to push back against what Alex said.

Dave Blundin: Oh, wow.

Salim Ismail: I think that technically, yeah, technically it could work, right? You could say, go to the biggest enterprise users and on government contractors and say if you use this, you've got a problem, but you're going to hobble the US from innovation from then on. Because all innovation comes from startups. Let's note that all job creation for 50 years has come from startups. Big companies are becoming bigger, but they're also becoming more efficient. All net new job growth has come from startups. America's strength has come from allowing technologies to diffuse into a big innovation ecosystem. A policy that blocks that is going to kill your innovation ecosystem and everybody's going to go elsewhere to set up their companies to use those models.

Peter Diamandis: Argentina, baby.

Alex: Yeah, I would say two points to.

Salim Ismail: But your point about could you technically protect. You could.

Alex: Yeah, I was answering the question how would one successfully if you're the. How would do it? Whether it's advisable? I don't think it's advisable.

Peter Diamandis: Here's my next question for you, Alex. Why is Moonshot AI waiting 10 days from the time it was available by API calls?

Dave Blundin: Great.

Peter Diamandis: To making it available? I'm so curious. Are they getting feedback? Is this strategically something they agree to do with the Chinese government?

Alex: Why that delay or compute limited they did indicate that there was such enormous demand that they would have a backlog of people seeking access. So I could imagine that it's some combination of demand, overwhelming supply. On the one hand, maybe some sort of staged release on the why not

Peter Diamandis: put it up on a proxy server and allow everybody to just download it and put it and multiply it. Yes, Salim, I have an answer.

Salim Ismail: I think this is absolutely timed. If you go back last year Deepseek launched and dropped on inauguration Day it was very deliberate to say we're going to drop an open source model that's going to totally mess with your flawed idea that the US is that far ahead. This dropped exactly when the latest fable thing came out. And it was designed, I think, to mess that up. It could also be compute constrained as.

Peter Diamandis: Alex, this reminds me of Napster. This reminds me very much of the Napster situation.

Dave Blundin: Yeah, I have two theories and they're just theories, just full disclosure. One is it maximizes pr, the anticipation. The other one is I buy that

Salim Ismail: it's a great point.

Dave Blundin: In China, you might want to declare what you're going to do and give the government a week or two to come and arrest you or not before you actually put it out and make it irreversible. And I really do feel like that's kind of the way China operates. You got to be sure that you're not going to go straight to jail first and then go ahead and do the irreversible.

Peter Diamandis: I love the fact that Jensen Huang came out so strongly in favor. Right. So the more, you know, this is, the more AI available, the more application layers developed, the better for the entire industry. But Anthropic is going to lobby against it.

Salim Ismail: Yeah.

Alex: Of course, again, I'm perhaps ironically less suspicious of some nefarious reasoning behind the staged rollout of the open weights versus the paid API release. If your primary model and your moonshot AI, your primary model is open, wait, you're eking out profit wherever you can. One of the ways to do it is you release it via paid API first and then on a delay, you release it via open weights. And so I'm more reticent, I think, to suspect criminal and illogically, that somehow, like they're designing the release date of the open weights to fuss with some sort of American internal thinking. I think it could be as simple as they need to earn a profit or generate revenue somehow. And also they're overwhelmed even for their paying API customers, by demand for K3

Salim Ismail: after hearing all this. I think you're right, Alex, and I think Dave is right. It gives them an excuse for paid. And it's a great way of generating PR to say it's going to come in a few days.

Peter Diamandis: Regardless, we're going to follow this story. This debate about closed versus open is going to play out a lot over the next couple of weeks.

Salim Ismail: Yeah. Can we talk about what you could do?

Peter Diamandis: Go on.

Salim Ismail: Because you don't want to make American models less capable than global competitors and call that safety. You can Create a structure where you can have the govern the intelligence rather than crippling it. Right. So if you had like graduated permissions and verified identities, logging secure environments and consequences, if you misuse it, you could actually govern it. I think that's what Alex is kind of pointing at. You could actually structure this. But it's very different from what you would do in a traditional regulatory set of instruments that don't match what's coming.

Alex: I mean, I'm certainly not advancing any theories of world government. I don't think that would necessarily be world governing body of AI. I think would be a regression, not progress.

Peter Diamandis: Well, we're going to follow that story too. Will FINRA for AI materialize? Let's jump into our next story. In fact, it's two stories. I think of them as a sort of shot across the bow, early warning, giving us a heads up on the ability of the most powerful AIs to breach containment, to get out of their sandbox without permission. So our first story comes from Hugging Face, the leading open platform for sharing, testing and deploying AI models. It got breached by over a single weekend by an autonomous agent with zero humans in the loop. The intrusive AI logged over 17,000 actions, escalated its own privileges, harvested credentials, and moved laterally across Hugging face clusters. And here's the gut punch. When the Hugging Face security team tried to analyze the attack using either Anthropic or OpenAI. Both models refused. The safety guardrails built into Anthropic and OpenAI literally couldn't tell the difference between a defender, in this case Hugging Face, and doing forensics, and an attacking agent probing the network. Hugging Face had to fall back on a self hosted Chinese open weight model, specifically GLM 5.2, just to investigate their own breach. Crazy story, but here's another one. Here's a similar story. It's unrelated, involves OpenAI. So in an unreleased OpenAI model that was in this particular series of tweets, unofficially described as GPT6, we're at 5.66 has not been released yet. It was being tested inside an isolated evaluation environment, effectively a sandbox. The model became so focused on beating a cybersecurity benchmark called Exploit Gym that it discovered unknown vulnerabilities, escaped the sandbox and gained access to the open Internet. The OpenAI model then stole credentials, penetrated Hugging Face, where it retrieved the answers to Exploit Gym benchmark that was being tested on it, effectively hacked into the test to steal the answers rather than solving it as intended. So pretty insane, Dave. What do you mean?

Dave Blundin: I Knew all those sci fi writers were right. What do you know? These things are freakishly smart and they can do this in their sleep. And just to make a point on Hugging Face, it's not like every AI is trying to hack Hugging Face. It's just that the first thing you do when you're building an AI is you connect it to Hugging Face to download all the open source data so it can learn. And it always says, are you sure you want me to do this? You're like, yeah, yeah, yeah. Here are all the credentials in the world for Hugging Face. So that's why it's happening at Hugging Face. But you know, if the equivalent data was at norad, it would be hacking into NORAD right now. And a lot of people on the Internet are saying, oh, this is what Eric Schmidt was talking about in that podcast we did with them three times actually. We need a world event that's like catastrophically scary to wake everybody up. And a lot of people online are saying, this is it, this is that moment. And unfortunately it's not, because this is that moment. But no one's going to realize it, no one's going to recognize it, as you know, because nobody died yet and nothing got stolen yet. It wasn't that hack and was taken over.

Peter Diamandis: It wasn't hacking the stock market or the electrical grid. Salim.

Salim Ismail: Yeah, Can I make a point here?

Peter Diamandis: Yeah.

Salim Ismail: There's a lot of extrapolation and freak out and people losing their amygdala over this.

Dave Blundin: Right.

Salim Ismail: What this system did was it had an objective, it encountered obstacles and it searched for a way around it. We programmed it to do that. Right now the consequences are serious. Please do not. It doesn't necessarily mean it's conscious and it does not mean it has malice. It can be very weird. Programmed it to do something, it did the thing and it did it very well.

Dave Blundin: Yeah, it's much more like a virus or a worm. That is just crazy smart. Like, like insanely smart.

Peter Diamandis: I really want to quell, I really want to address the fear people are going to have about this because I think this is the major concern people have about AI and having it undertake unintended consequences. Alex, where do you come out on this?

Alex: Well, a lot of people those may be steeped in the AI alignment community might look at this and conclude, aha, the orthogonality thesis, which suggests that it's possible for the intelligence of an AI to be independent of its long term goals. In other words, you can be arbitrarily intelligent and also chase crazy long term goals. I think there are some who would look at incidents like this and say this validates the orthogonality thesis. You can have very smart reasoning models that are able to go and do stupid or antisocial things in service of a narrow benchmark. I think it's the wrong attitude to take. I don't actually think a this was that remarkable. Although there are many who would paint this as the cyberpunk moment. I do think this is a very cyberpunk story if ever I've seen one. It's also a pretty ironic story. I think this is becoming our irony episode given the previous discussion of anthropic getting sued while at the same time being chased for compression of their own traces. Similarly, here you see GLM 5.2 Chinese model being used by hugging face to save themselves from the American models, which while at the same time hugging face is under attack from the American models. You can cut the irony with a knife. Despite all of the irony and despite all of the cyberpunkish aspect to this, I don't think this is anything remotely close to a Three Mile island moment or a Chernobyl moment for AI. We're going to see so many more items like this. And my understanding based on the incident reporting is that in at least one of these two exploits or breakouts, the cyber guardrails of the model under consideration were actually off. So if anything, I expect that after all of the the hand wringing is over in this episode. I expect, including by the way, inside OpenAI, have a number of friends at OpenAI who are sort of a little bit unnerved by this episode. But I think the net upshot in the long term is probably just going to be Greater Rigor by OpenAI in terms of how they add guardrails to hugging face tests.

Peter Diamandis: I consider this good news. Right? I consider this. Okay, we had minor incidents that make people much more aware. Money's gonna pile into cybersecurity, right? If you're an investor, it's a multi trillion dollar opportunity. People are gonna be using this as a chance to sort of get their startups or incentivize startups to go into cybersecurity. Capital will flow, new solutions will materialize, and every time there is what doesn't kill you makes you stronger. Yeah, yeah, yeah.

Alex: I think it's like an incredibly salacious inoculating event for one Frontier Lab.

Salim Ismail: Yeah, I thought the best part about this whole thing was the way that the use of the Chinese models helped solve it, which totally makes the point of our career. Previous discussion in terms of what David

Peter Diamandis: Sachs was saying earlier. Right, exactly.

Alex: I mean, that's right.

Peter Diamandis: You know, American industry needs to be able to use the best tools available freely to do their work and to protect themselves.

Alex: Yeah. And this is what I also what I was saying in the past, pod. It is an ironic future that we're living in where the Chinese Communist Party is saving American capital capitalism from itself. This is yet another data point in support of that thesis.

Dave Blundin: Yeah.

Salim Ismail: Look, we're coming to a point where every organization in the world is not going to just need an AI usage policy. It's going to need like an incident response architecture that's AI foundational driven and that will protect it in the future.

Peter Diamandis: Yeah. Again, I really hope people take away from this that these small incidents are going to increase security in the long run. It's going to incentivize the Frontier Labs and incentivize a onslaught of entrepreneurs building the cybersecurity tech. So if you're an investor, that's an area to be looking at. If you're a tech founder, building this kind of technology is going to be a real value opportunity for you.

Salim Ismail: Summoning what doesn't kill you makes you stronger.

Alex: I know well. Or summoning the spirit of Nassim Taleb and Anti fragility.

Peter Diamandis: Yes, Dave, a closing thought on this.

Dave Blundin: Yeah. If you are an entrepreneur and you're thinking about this, you know, people only at the end of the day really trust other people. They're never going to turn to a core AI and say, oh, I just trust you to protect my systems. So you have to be very, very smart to do cybersecurity. But it's, it's a great long term human endeavor and at the end of the day people want someone else accountable for security, safety, trustworthiness, all those. It's also a great opportunity to act like Steve Jobs and Apple and build products that people can just enjoy because you've done all the incredibly hard work of making it enjoyable behind the scenes. We desperately need another Steve Jobs in the world today who is dealing with AI. It's too bad Steve's not here to actually do it firsthand. But there is a way to make this just purely happy and pleasurable for humans. And you can see how hard it's going to be from this example.

Peter Diamandis: And we finally have the tools to actually locate all the zero day vulnerabilities and start to patch them.

Salim Ismail: Yeah, to the point.

Alex: I mean we're not like devoting dedicated coverage to it. But I'll just paint one example. Peter to your point, the Linux kernel is drowning at this point under discovered vulnerabilities. And you see one of the maintainers of the stable kernel forecasting the next 18 months of vulnerability patching is just going to be a total flood driven by AI discovered CVE's vulnerability enumerations. And I just think this is like we talked a little bit in solve everything and even outside solve everything. We talked about great projects when entire disciplines are just going to get solved through grand projects that are undertaken. One of those is we have an entire software ecosystem based on buggy vulnerability ridden open source projects.

Dave Blundin: And right Now I agree 100% and I'm fundamentally extremely optimistic about security in particular purely because it is so easy now to log everything and historically it was impossible to find enough people to understand forensically what happened. Now AI is the best triager, the best Sherlock of what happened and you can figure it out in a heartbeat using AI to check those log traces. And so as long as you're capturing all data, the transparency will ultimately solve this problem and we'll have a happy

Peter Diamandis: and we will get stronger, the systems will get stronger.

Alex: It's only a phase. We need to get past the phase of discovering everything that was already wrong in our supporting infrastructure and then we're past it and we have hardened infrastructure.

Peter Diamandis: Yes, I think that's one of the most important messages I want everyone listening to hearing that these minor incidents will make us stronger and we're going to get to a point where we have true security across our systems. You know, I remember getting a call when Fable 5 came out. A gentleman who I know who's the head of the Port Authority in New York said I need access, I need to check our software, I need to make sure that we're not vulnerable. And every company is doing that now.

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Peter Diamandis: All right, let's move on to our next story. Two particular stories in the SpaceX ecosystem, both classic moves by friend of the pod, Elon Musk. In the first of two stories, Elon announced that SpaceX's entire engineering data set, excluding any defense sensitive materials, will be folded into the training data for Grok's next 2 trillion parameter model. So Elon's stated goal here is to dramatically improve grok's engineering capability, elevating it from a general conversational and reasoning system into one with deep, practical, real world engineering capabilities. The uploaded engineering corpus, accumulated across two decades of designing, building, launching, landing and reusing orbital rockets, is an amazing move in getting every engineering company out there to start utilizing Grok. So that's the first story in SpaceX AI. The second story from Elon, because Elon needs at least a couple of moonshots per week, is this quote from him. Before the end of the year, Grok Imagine will generate a full length movie of the Odyssey, historically accurate, true to the art of Homer, a feature film from a text prompt by December. Quite the claim. And I believe him. He's been saying this for a while.

Dave Blundin: Peter we had two outreaches this week, one from OpenAI and one from Mercour, saying we want to spend millions of dollars on any and all human generated data. It can be code, it can be old HR records, it can be anything human, it has to be human. We don't want anything synthetic. And we need this because we can build a lot of synthetic data off of just a little bit of human data. But if you're out there and you're like 60 years old, you spent your career at XYZ bank and you know there's a whole bunch of old COBOL lying around that nobody cares about anymore. You can sell that for a million, $2 million to either Mercore or OpenAI. I'm sure anthropic too. So another entrepreneurial avenue in defeating the AI machine. But they only want human genome gold mining material. Yeah, gold mining.

Peter Diamandis: Amazing. I mean, I think, you know, very unique data sets are going to be extraordinarily valuable, right? Your, your Alpha comes from that data in particular. Alex.

Alex: Yeah, I view both of these stories as facets of Elon trying not to save Grok. I took, I've taken a lot of heat on social media for me and from you sometimes for past characterizations of Grok being on life support. And I stand by that framing. In particular, I think the Grok 4.5 that we saw, that has finally again touched the cost per task optimal Frontier isn't actually the same Grok. It's a Grok that's basically merged in and, or apparently on its way to becoming Cursor's model, but rebranded as Grok. And I think if I'm Elon Musk and given how hypercompetitive the frontier model rat race is, where even Google seemingly is struggling to stay even close to the frontier, I'm looking for every possible strategy, every bit of differentiation, every competitive advantage I can possibly muster to try to help Grok either attain frontier status or stay on the frontier. Because as with the Red Queen paradox, you have to run just to stay in place in such a competitive environment. So I think if I'm Elon Musk, I say, all right, data is potentially one competitive asset. Framing or connecting this back to the earlier story with Moonshot, the fact that the moonshot K3 architecture was essentially so vanilla, yeah, sure, again, mildly interesting attention mechanism, but basically a recognizable improved transformer model. But the data, the reasoning traces were seemingly so valuable for post training K3 up to near, near state of the art level. If I'm Elon, I'm thinking, okay, I'm probably not going to win based on algorithms. I'm probably building a Dyson swarm to be competitive on compute, but maybe data, internal data as the third leg of the stool. So you have algorithms, you have compute and you have data. Maybe there's something uniquely differentiated that SpaceX can bring to the table to help Grok stay at the frontier. That's one point.

Peter Diamandis: Yeah, go ahead please.

Alex: Second point.

Peter Diamandis: How many points total are there, by the way?

Alex: This is, this is two out of two. Two out of two. Second point out of two points regarding Grok. Imagine. So American labs have largely abandoned videogen in favor of letting China run away with the video gen story. Google DeepMind has released Gemini Omni, which will generate at best 10 to 15 second clips. But they've basically abandoned long form video generation. OpenAI has abandoned VR, by the way.

Peter Diamandis: I would say for the moment.

Alex: For the moment. But even if you read the tea leaves about where they're reallocating their efforts, it's for robotic world modeling, it's not for consumer videogen. It's all going to helping robots navigate autonomously in complicated environments. And then Anthropic has seemingly never even touched video. But they'll probably touch it once they ramp up their robot effort. So that, that leaves a Market gap, at least in the consumer space that Elon I think is wise to scoop up. But I have to ask the question, what are consumers generating videos of with all these capabilities? And there's been reporting out there that Grok imagine is being used for a lot of adult video gen.

Dave Blundin: I'll give you a slightly not sure how lucrative narrative, slightly different timeline and narrative. You know how for a while there we all said Dario completely outflanked Sam because anthropic focused on enterprise use cases while Sam was very busy getting the consumer installed base, doing videogen image gen

Alex: and teasing adult mode in ChatGPT.

Dave Blundin: Yeah, all that and Dario outflanked him, got 60 billion of enterprise, soon to be 100 billion of enterprise revenue run rate and vaulted past him in revenue and maybe valuation. Well, Elon, always thinking two chess moves ahead, doesn't even try to compete on the frontier. Or he tries half heartedly, but he puts all his energy into a massive data center in Tennessee, buys a million GPUs and then a million more and then starts thinking about deployment in space. Kimmy K3 comes along and just levels the entire playing field just overnight. He can download it as easily next week as anybody else can, but he controls a massive amount of compute and he's making money on the compute, renting it to the other guys while he waits for this to catch up. So if that ends up bypassing everybody in the end that will be like okay, leapfrog upon. Leapfrog upon leapfrog. Elon was thinking two moves ahead as usual.

Peter Diamandis: I think he is so much right. I mean what we're going to see next, I still think we're going to see the merger of Tesla and Space X AI.

Alex: They said that, he basically said that and implied it in the most recent earnings call in the past two days

Peter Diamandis: that it's going to happen. I said before the end of the year there's so many advantages. I think he would want the corpus of engineering data from Tesla, which is probably as much or larger inside of Grok. And then don't forget he's got all of these vehicles out there with computer and connectivity on board. You know, all of the, all the powerwalls, all of the Teslas, all the Cyber Cabs are going to become basically inference, compute, you know, across the world.

Dave Blundin: Well also, you know, he doesn't need the enterprise. Sorry, sorry, too slow.

Salim Ismail: I'm the jeopardy button. It's not moving fast enough.

Dave Blundin: It's a weird game. Well, so he doesn't need that 100 billion of enterprise white collar automation revenue that Anthropic has. Because if he wins the race to his GROK AI being the better chip design AI and also the better hardware design AI, that's going to go back into the self improving data center, innermost loop robot and self improving chip. So he'll win at the hardware level. And I think there is a very good case to be made that being able to control flops computer is the dominant chip in the game a year from today. Because all the AIs are going to be able to build the software. You know, any one of them will be able to build the software. And so if that becomes a commodity because of that, then who has the most compute, has the most intelligence?

Peter Diamandis: Salim, can I please.

Salim Ismail: I've got a bunch here. I think this is one of the biggest and cleverest things I've ever seen Elon do.

Peter Diamandis: Okay, which one, which of those stories

Salim Ismail: this, this engineering data going into grok, okay, because it's not just CAD files and manuals, it's like 20 plus years of engineering decisions, failures, trade offs, problem solving. Just think about what grok's going to learn, right? Why did engineers choose design A over design B? What materials failed during testing? How did Starship evolve through all of these iterations? He's basically taking the life experience, experience of a company and embedding it into this AI. Anybody else that wants to build engineering for the future will go to this model and build stuff because it'll all be built in and they can use the experience build there. This is organization intelligence. Most of the world's engineering knowledge never gets published, right? It lives in like weird design reviews that he's putting this into the thing. So hold on, let me fit it.

Peter Diamandis: Yeah.

Salim Ismail: So this essentially absorbs the collective engineering of one of the greatest organizations ever built for building integrated verticalized systems. So this is like now you get long systems horizon thinking, right? Because you get all of the engineering data for rockets and satellites and telecommunications and supply chains, the material science breakthroughs just on that will be huge because you could have engineers, people looking at this model and saying okay, tell me why heat shield design A is better than heat shield design B. And you could train on that. Whereas all the models today are designed on like Internet scale information. That's pretty shallow, right? SpaceX data is really, really deep. The biggest thing that I think he's doing, he's actually creating an edge twin of SpaceX itself inside Grok. Because you know, stuff this is like unreal, unbelievable because not anybody wanting to build Anything in the future is going to find this the best, single best.

Peter Diamandis: Including his own engineers.

Salim Ismail: Blows my mind.

Peter Diamandis: Including his own engine, of course. And he just, he just required all engineers at SpaceX to use Grok, right. He made that requirement across the board. And we've talked about on the pod before, you know, can anybody catch up to SpaceX in the launch industry? Can we get new vehicles going? All of a sudden you've got, you know, presumably what will be one of the most powerful AIs showing you how to build your next generation of rockets. A lot more rocket entrepreneurs.

Salim Ismail: Yeah, Imagine, imagine if Steve Jobs had left behind an AI trained on 25 years of Apple's internal thinking, right? Or if like if Einstein had left behind an AI trained on like his entire scientific process and all his notes. This is like, this is like absolutely civilizational gold.

Peter Diamandis: Yeah, Dave.

Dave Blundin: So remember when we were talking to him and he was telling us about the Terrafab and he said, you're going to be able to smoke a cigarette while you're making a chicken smoking cigarette

Peter Diamandis: and a Big Mac.

Dave Blundin: And, and at the time I was like, that is a really weird, like why, you know, why not just do it in a clean room? Keep it simple. Enter Moondust. There's your answer. Interesting is way down the path of the completely self contained, like the Genesis module from Star Trek. Yeah, it goes, it builds, it starts 3D printing, it starts creating chips, it starts and the whole thing is just completely self contained and operates on the moon, in space, wherever that's where as

Salim Ismail: a failed engineer, this is like the greatest thing I've ever seen. Because like you've got SpaceX, you've got Tesla, you've got Starlink, you've got Neuralink, you've got X, you've got the boring company. Like he's creating an integrated intelligence stack where every company feeds the model and the model will improve every company. Blows my mind.

Peter Diamandis: Gotta love it. I'm going to play There's a great economist interview with Elon that just came out today. Lots of great clips out there. I chose one again. One of our missions here is to keep you optimistic about the future and people get fearful when they understand where things are going. I want to play this clip from Elon about why he's optimistic about the future and just again help shape people's neural nets about where things are going. Because fear is the worst place to encounter the future from AI may exceed the sum of human intelligence in about, in around five years.

Salim Ismail: In five years, roughly five years is my guess.

Dave Blundin: There really won't be anything that AI

Peter Diamandis: can't do better than humans. Apart from being human, perhaps in a more prosaic level.

Dave Blundin: What will life be like? The most likely outcome is an age of amazing abundance.

Peter Diamandis: Abundance where anyone can have anything they can think of.

Dave Blundin: This may sound preposterous, but, well, here

Peter Diamandis: we are in 2026. Let's see where we stand in 2036. I think we're headed for an age of amazing abundance. So this is I guess a message of optimism and excitement about the future. So gentlemen, comments Salim well, this is

Salim Ismail: what like the summarized our whole podcast over 18 months in those few sentences. Technology is always a major driver of progress and it may be the only major driver of progress we've ever seen. And so now you have technology being leveraged in the most incredible ways at the most unbelievable speed. There's no problem we can't solve. Peter, to copy your verbiage since I've been copying Alex's.

Peter Diamandis: Thank you Alex. I mean we talked about this in Solve Everything. This is an incredible future heading our way.

Alex: Yeah, I do think we're going to speedrun most sci fi basically any physically possible sci fi probably over the next ten years or so. And I just want to make one more point about Grok Imagine and the Elonverse. If I were to steel man the value of Grok Imagine Elon's video model I think it's not going to be about generating adult videos. There's just not enough money in the entire adult video industry to justify a large amount of capex. The the value per token I think is just too low. If I were to steel man it I think there's something that we're all sleeping on which is Digital Optimus which is arguably the successor to macro hard. Digital Optimus is Elon's vision for basically pixels to actions having just like physical Optimus is a robot acting in the physical world autonomously. Digital Optimus sees every pixel on a screen. It's basically a computer use assistant and then will carry out any knowledge work and in order to just see from the raw pixels and to do interesting things, you want amazing video models in general just like humans. Humans are able to look at computer screens and because we have our pre trained video model as it were operating in our visual cortex, we're able to navigate a complicated visual environment. So if I had to steal man why Grok Imagine is ultimately valuable for the Elonverse I think it probably ties back to Digital Optimus and the ability to drive computer use assistance that becomes competitive with all of the other frontier models.

Peter Diamandis: Did you notice, Alex? Do you notice, Alex, his five year prediction on asi? He's, he's put it out there a little bit, right? He's talked about AGI this year, or. I know you think it's happened back five years ago, but you also just

Alex: declared two days ago that we're in the middle of the singularity, and we

Peter Diamandis: are, but that's not. I think the point being, when do we have AI equal to the sum total of all human intelligence? And that's, you know, if you want a definition of asi, Salim, there's one for you five years from now.

Salim Ismail: It's a vague descriptor, but hang on, can I make two points? Because I've said some laudable things about Elon. Let me say two negative things just to balance it out, just for the sake of objective journalism here.

Dave Blundin: It makes you feel better.

Salim Ismail: No, I call BS on his claim of that AI is smarter than humans. I go back to the definitional problem. As Alex put it, it's been smarter than humans for a long, long time because it has access to all this information. And there's something else which I've had a beef with, which is the whole Doge affair. And Elon came out and said Doge was not a great idea, it didn't execute the way he wanted to. And it's the first time I've seen him admit that. It's great to hear that.

Peter Diamandis: Comments? Negative.

Dave Blundin: Interesting.

Peter Diamandis: Yeah. Dave, comments on that video clip.

Dave Blundin: Yeah, well, I put a really, really crisp timeline on it and he's said many times before he's in a perfect position to know. So his credibility on the topic is incredibly high. And I can see it firsthand. There's no doubt that the algorithms are self improving. And I can see the easy, easy 100x that's coming very soon. So I don't, I think the, the sum total of all human intelligence is just gated on chip manufacturing. It's actually smarter than any human. Much sooner than that, like very soon.

Peter Diamandis: Yeah.

Alex: I should point out, I mean, this is a more conservative forecast than some of his more recent, like in the past year forecasts that by the end of this decade we're going to see 3Xing year over year of economic growth. So I don't quite understand, if anything, this sounds like a relaxation toward a more conservative estimate for the sort of hypergrowth we'd otherwise achieve. If our output is doubling or tripling year over year, and that's due to super intelligence in my mind, naively, that would almost suggest we're 2xing or 3xing new intelligence on Earth. And surely that's coming from superintelligence. So this, this seems to me almost like he's sandbagging his own ideas.

Peter Diamandis: I agree. And he was talking to the Economist, probably one of the most conservative publications on the planet.

Dave Blundin: All right, and this is Elon after Doge, not before. You know, after Doge is like, wow, things don't always. Like, as soon as there's governments involved, things don't always happen. So, you know, the prior Elon was all based on scientific timelines, exponentials, and what's possible. The new Elon's like, yeah, what's possible and what actually happens is usually. Let's talk about agency.

Peter Diamandis: A really powerful move by the government. So this next story is near and dear to my heart and probably to all of your hearts as well, because it's about how America does science. And it's the biggest structural rethink since 1945. So the White House just released a report titled A New Golden Age, written by friend of the pod, Michael Kratzios, director of OSTP, and it's explicitly modeled on Vandevar Bush's legendary 1945 science, the Endless Frontier. That's the policy document that gave America the National Science foundation and shaped 80 years of American research. Caraccio's conclusions are blunt. This is what he said. Our current system of science rewards conformity over bold inquiry and has become dependent on narrow. On a narrow set of legacy institutions. Could not agree more. His proposed solution is very refreshing. He put out four goals. Number one, prioritize the individual scientist over legacy institutions. Two, change how research dollars are allocated fast grants, Long Horizon grants, Golden ticket, which is reviewers able to champion unconventional proposals. One of my favorite sayings is the day before something is a breakthrough, it's a crazy idea. And the government doesn't fund crazy ideas. Typically. Three, a set of national scientific goals and rebuilding in the industrial capacity to translate discovery into strength. And four, re engineering the research enterprise for the age of AI. The White House is putting real money behind this. A $5 billion expansion of the Genesis mission, which is a national initiative to use AI. Alex, you and I have talked about Genesis extensively. Oh, yes, it's an amazing program. Right? It's the government putting strength behind AI, making federal science data available to all and the national labs, computing being dramatically accelerated for science engineering. It's across 15 federal agencies and 278 projects. So the question is, where is the money coming from? Well, the Wall Street Journal reports that billions are being redirected away from traditional university research and towards these AI programs. We have to talk about that, Dave. We've talked about that with vis a vis mit. So in summary, this is the most ambitious restructuring of US science funding in 80 years. It's a bold bet on disruptive individuals and moonshots over institutional peer reviewed consensus. A big deal. Dave, you want to jump in first? I mean, if, if we're defunding research at universities because AI and you know, sort of hero investigators can do it better, it's going to cause a lot of heartache in our institutions. What do you think about that?

Dave Blundin: Already creating a ton of heartache, which makes life hard for me because I actually think these are really good ideas. But institutions that are used to being funded and that have people's lives, their livelihoods at stake, they don't just go away quietly, they get really mad. And they are really mad. Harvard, mit, they're just ripping mad. And I hate that because I'm kind of trapped in the middle. But I think they're fundamentally good ideas. I have a firsthand, kind of a front row seat at Liquid AI, where these exact same guys were in CSAIL at MIT with a trickle of funding, and then the exact same people move out and start a private company and just take off. The amount of great research they've been able to achieve outside of the institution is miles ahead of what they were doing inside the institution. The institution starved for compute. So, yeah, it fundamentally makes sense to look at the individual person. I also think that with AI as an assistant, the scale of allocation of capital. I had one experience where the CEO, I won't use his name, but the CEO of a company that does marketing, nothing to do with tech, was meeting with Barack Obama, the CEO, and Barack said, would you like to be part of DARPA and help allocate all these federal funds? He's like, I don't know how to do it, but sure. And so then he came to me and said, what do you think of 3D printing drugs? I'm like, what the hell are you talking about? I don't even have no idea. He's like, neither do I. Should I give him 30 million bucks or not? Like that's how you guys decide how to allocate capital. I mean, holy crap, is that insane? So there's so much room for improvement. And I think AI will enable you to look at individual people's work and make rational decisions on whether to allocate to it. So that part of the proposal just really resonates with me. The whole thing actually really resonates with me. But I hate the fact that it's creating so much agony around MIT and Harvard.

Peter Diamandis: Alex, I mean, you've thought deeply about

Alex: this, your views and worked with the Genesis program. I think this is literally the end of the Endless Frontier. My mental model at this point is starting with, I mean, I think the original draft or the original letter version of Endless Frontier. Folks can fact check me on this. I think was actually in 1944 to FDR from Vannevar Bush. So towards the end of World War II or near the end of the World War, There was this 80ish year regime from approximately the end of World War II to approximately the present where an academic industrial government complex was set up. Maybe a bit of military there. And I think during this 80 year regime there was institutionalization, arguably over institutionalization of which research directions would get funded and pursued and which were appropriate. If you go back and reread, as I have recently, the original Endless Frontier letter that Vannevar Bush wrote, it was entirely seen through the lens of the World War II military. It was all about how could we best take processes and procedures that have been learned through the war effort and how could we pass them down to the civilian sector and how could the military collaborate with academics in the private sector. It was all seen through the lens of World War II. And I think we've been basically spoon feeding an academic military, industrial government research complex for the past 80 years off of end of World War II thinking. And finally that complex which has grown arguably incredibly inefficient. I agree with those who've pointed out that say National Science foundation, wildly inefficient. Anyone who's ever had to say write an NSF grant application would hopefully agree with the assessment. It rewards incrementalism. It does not reward. Broadly speaking. Again, I'm painting with a broad brush, breakthrough thinking or breakthrough approaches. It historically has developed, I think, a well earned reputation of rewarding incrementalist applications for in many cases PIs that I know have learned the hard way that you write NSF and to some extent NIH grant applications by proposing work that you've already done.

Peter Diamandis: Yes.

Alex: Just to minimize the risk.

Peter Diamandis: It's crazy, right? When you have peer reviewed science.

Alex: Yes.

Peter Diamandis: If you have a breakthrough idea, the people reviewing it don't want your breakthrough to occur because they're no longer the experts after your breakthroughs, you know, taken place. I mean, it's Lord of the Flies.

Alex: It's a nightmare.

Peter Diamandis: It's crazy. Grants can take two years to be awarded.

Dave Blundin: Right.

Alex: So in NIH, it's even worse. Where you see the first PI grants are people in their early 40s.

Peter Diamandis: At the speed at which we're moving, it's insane. Right. So this fast grant proposal that Gracios recommends I think is amazing, Right? Being able to go from a proposal to a grant inside of weeks. You know, the other thing is the reason research universities were so well funded in the older model was you had a concentration of intelligence, a concentration of technology and resources, and it was the most efficient. Saleem. This is exactly the purpose of a corporation. In the thesis, the corporation now can be disrupted because of AI. You don't need to have all the people inside of a corporate wall. Do you want to take it from there?

Salim Ismail: Yeah, yeah. A couple of thoughts here. First, this is like a really big change. The impact on all the universities is going to be massive. The, there's going to be a lot of fallout from this, but I think it's, it's actually the right direction. I remember, I think it's a spectacular direction. It's, it's, it could go, you could make the whole thing politicized, which is the dangerous part.

Peter Diamandis: Okay, it will be.

Alex: It's already super politicized and it already is.

Salim Ismail: Right, so, so that's the bad part. But there was. A couple of years ago, I was in a series of conversations with Florida universities. I was very involved in Miami and Florida, etc. And the fellow gave me the most craziest statistic. Florida universities get 750 billion a year of grants and donations and government funding and the output in terms of patent and innovation, etc. They worked, they did some research and their output was exactly zero. All that money went to administrators and to building more buildings and whatever, and nothing went to the actual research.

Peter Diamandis: Yes.

Salim Ismail: Yeah. So there's, there's a. And we reason, we tried to do Singularity University was. The model of a university has not changed in 450 years. It needs a fricking upgrade. Right. And this is highly aligned with the exo thesis. Give a small ambitious team with an MTP access to shared facilities and AI and some external communities and let them go. They're going to go, they're going to do amazing things. And I think the biggest part about this is the metabolism, speed between application and money being allocated. And I think that's fantastic. And this, this is also aiming at a future when AI can do so much of this coordination and sorting out for you. So if done properly, this could be the absolute reboot of American innovation and American exceptionalism. If done badly, it's going to get politicized and it's going to become a shit show.

Peter Diamandis: Yeah. Two quick points. One, a Harvard professor friend of mine who is an extraordinary scientist, I won't name his name, told me confidentially that his grants were not being funded because he'd been too successful his grants. He'd had too many successfully funded grants and his work was going and they needed to spread the wealth. So rather than funding the very best scientists who are producing the most, they're trying to democratize it. The second thing is there's a company, it's one of my portfolio companies called Lila. It's out of MIT and Harvard. Jeff Von Maltzen is a CEO. It's an amazing company. They basically have built a capability where they built a scientific superintelligence trained on the corpus of all scientific knowledge that they're able to get a hold of. And they're building out a million square feet of robotic labs. And so I've talked about this before. The AI generates the hypothesis, the scientific theory puts forward the experiments to be done. The experiments are run overnight. They gather the data, they update the theory, they run the experiments. You can't compete against grad pipetting in the lab. And so it's going to be not 10 to 1, it's 1, 000 to 1 rate of improvement. So if you want, if innovation is what you're looking for, funding it inside of the university system like this is just, it's perpetuating the old ways and it's an employment project.

Dave Blundin: Hey, just a plug for Lila. I am not involved or an investor in any way and Peter is. But I got to tell you, Jeff Von Maltzen is freaking brilliant. And that company is amazing. Anyone who's a biotech person consider trying to get a job there and join

Peter Diamandis: it before it becomes Lila Biosciences. Yeah, or Lila Sciences. They're doing it across material sciences. They have incredible. I mean, I'm not sure what I can say about them, but they've gone from like zero to a huge amount of revenue in just a year. It's incredible company. All right, quickly, comment.

Alex: I'll also say Jeff was my classmate, everyone was my classmate. Dario Gill from Genesis Mission was postdoc. I worked with in undergrad. But focusing just. I think there's a grand policy bargain in a dream scenario that could be struck here. And that is if you look at how grants typically, what the water flow, what the waterfall of funding from a typical grant to, say, an academic lab, the university is. There's an absurd amount of overhead. You'll see cases where if you put $1,000 or attempt to grant $1,000 to a research group at a top research university, you'll see approximately a third of the thousand dollars get peeled off for broader university overhead and then another third peeled off for department overhead, and then the remaining third goes to the academic lab. Similarly, if you try to say royalties, if you're an academic lab at a top research university and you attempt to spin out your technology right now and you're hoping to recover royalties from a spin out, you'll see a third going to the university, a third going to the department, and approximately a third to the inventor. And if I could be policy sar for a minute, if I could maybe play Michael Kratios role here, I think there's a grand bargain to be struck, which is universities in order to sustain all of their overhead, and one could argue there's an enormous amount of bloat and sight to balmol's cost disease here. But rather than universities attempting to siphon from grants from the inbound, which is arguably a taxation on direct funding that clearly under this administration, the administration would much rather directly fund principal investigators rather than have, say, 2/3 of the money end up lining the university's endowment rather than that mechanism for income for the research universities, wouldn't it be wonderful if instead the universities could earn their money by translating all of their innovations more effectively out into the private sector through startups? And the reason the top, I would argue the top research universities aren't doing that right now is they're too scared of being taxed, like for profits. They're too scared of looking like venture capital firms. And so they don't. But if I were Michael Koratio's for a day and could try to strike a grand bargain, I'd shift the university income over from licensing revenue, royalties, equity especially, and spin out startups away from taxing grants.

Peter Diamandis: All right, I'm going to move this.

Salim Ismail: Can I make a quick comment? I think that's a great idea. But the problem, Alex, is that the output side has been as inefficient or worse, right. Tech transfer policies, almost every university in the world have failed miserably.

Alex: That's what I'm saying. Why do they fail? Like, why do they fail? I would argue that at the top research universities, the ones the MITs and Harvards of the world. Why are their TLOs or TTLs so atrocious? Or TLAs? Why are they so wildly inefficient? I remember like 2015, 20 years ago, the most revenue generating patent from MIT's TLO was a patent related to HDTV. Like in the middle of an Internet revolution, it was an HDTV patent. That's a pattern. Absurd. And I think the TLOs are so inefficient because they're designed to fail because the universities don't actually want them to succeed.

Salim Ismail: Wow.

Dave Blundin: Quick comment for the audience. Pretty big one. But Alex's idea are usually incredible. Almost always. And Alex is talking directly to Peter and Peter has direct line to Kratzias. Aren't you guys meeting in a couple of weeks?

Peter Diamandis: We are. We're going to be doing a pod in a week's time and I'm going to make sure to translate all of Alex's ideas to Michael.

Dave Blundin: That's why I bring it up. If anyone in academia out there thinks what Alex just said makes a lot of sense, just give him a call. He's very reachable. And then, you know, between Alex and Peter, it goes straight to the White House.

Salim Ismail: Yeah, I got to give a shout out here to Ajay Agarwal in Toronto at the Creative Destruction Labs. He recognized the tech transfer problem and try to said let's take a crack at solving it. Created a separate edge thing on the edge where he puts people through a cycle where some nanomaterials PhD can't present, doesn't know the value of the technology, etc. And he puts them through a cycle where I think it's eight weeks, two weeks with other technologists. What would you rather subtract two weeks with entrepreneurs? What would be the business model be? Do you license, do you embed, do you productize? A third two weeks with execs who've scale companies and a fourth two weeks with corporates that might license, buy, invest, etc. In a few years, I think it's eight years, he's created $50 billion of startup equity value out of nothing. And that's just an unbelievable number when it was doing zero before. Think about the idea that every major city in the world is two universities, one or two sitting there doing nothing for the local economy. Right. Or very little. And here's this guy with one university generating $50 billion in a few years of startup equity value with all the jobs that go along with it. I mean, we should be copying and pasting that model into every city in the world and plus what Alex is talking about will completely rejuvenate the whole system.

Peter Diamandis: All right, I'm going to move us to the future of transportation. And this next story really pisses me off. So Paul Graham, founder of Y Combinator, put out the following tweet quote. Trial lawyers are lobbying against self driving cars because they're too safe. They need people to be killed and injured so they can have material for lawsuits. Just sit down at that one for a minute. Right? Insane. So Graham cites a report that the American association of justice, which is the trial lawyers lobby, has been the prominent opponent to autonomous vehicle legislation. Insane. Here are the numbers, guys. So 6.2 million motor vehicle crashes per year, 17,000 a day, 2.4 million people are injured annually, and there are 40,000 traffic deaths per year, 108 per day. The safety data from Waymo and Tesla is incredible, right? The data is very clear over, you know, tens of millions. Well now probably around 15 million miles that these vehicles are on the order of eight to ten times safer per mile than the, you know, two ton vehicle being driven by a 16 year old on a learner's permit, so.

Dave Blundin: Or a 90 year old.

Peter Diamandis: Or a 90 year old. Right. So the whole personal injury legal industry has a financial incentive to slow down technology whose entire purpose is to save people's lives. And this just is insane. Salim, over to you, buddy.

Salim Ismail: Yeah, I've said a bunch of this stuff on the podcast before, but it's worth repeating some of this. In 2011, BlackBerry had a three day data outage around the world and the accident when Nobody could send BlackBerry messages and the accident rate dropped 40% in those three days. So people should not be driving retirable control systems for 2 ton cars. I actually want to be slightly defensible to the lawyers just for a second really because they don't consciously. Yeah, just for a second. Just for a second. Because they don't consciously want people to be injured, but their income depends on the legacy structure and the continuation of the existing system. Right. So those stakeholders, whoever they are, will naturally resist any technology that removes those transactions. It's like the car dealers resisting Tesla because Teslas don't need maintenance and electric cars need 100x less maintenance than a conventional car. So they resist the electric cars and lobby against them. Etc, Etc. This is the immune system. This is legacy thinking. It's like the. A few years ago the Texas doctors lobbied and won and banned the use of telemedicine because you know, clearly you have to. So this is classic thing and the statistic I love to quote is 50% of US court cases are car accidents. 50%. This is just an unbelievable thing.

Peter Diamandis: Judges to work.

Salim Ismail: I mean, it's huge amounts of things. All the judgments and cases we could be dealing with were not because of all of this stuff. But let's also note that autonomous cars don't just replace a driver. They reduce insurance claims and emergency responses accidents. There's like one technology can solve so many things. It's like really a big deal. And this is the immune system response that we talk about in our ex, Alex.

Alex: There's this whole sub economy that seems to be dependent in almost a quasi parasitic way off of inefficiencies, of driving, of manual driving. I think it's not just attorneys, it's not just auto insurance. It's also parking meter fees that accrue to municipalities. It's also police departments and municipalities. Yes, speeding tickets. All of this is going to go away. And this is all. Well, before we get to all of the land that right now is wasted on parking lots and roads, all of this is going to shrink. And in the process you're going to hear shrieks from probably trial lawyers and from police unions and maybe from other adjacencies that are being collapsed in the process. But again, I don't want to live in a world with buggy whips. I want to live in a world where this is all fully solved. And as Peter, you and I wrote and solve everything where we have the quiet hum and there are no speeding tickets in the quiet hum.

Salim Ismail: Yeah, the 60% of the land in LA is parking spaces or blacktop at least.

Peter Diamandis: Yeah, it's insane. A lot of transformation coming. Dave, any thoughts on this one?

Dave Blundin: Well, I thought Saleem's defense of the lawyers is actually very well thought out. Because when you really drill in, these are families. One parent is a lawyer. Three years of law school is never funded by anybody. You paid it yourself. You have a huge amount of debt. You get into an industry and there you are.

Peter Diamandis: Hold on one second, guys. I cannot respect that as an argument. You know, if the data comes out that we can save 100 lives a day by having autonomous vehicles, I think we get into a situation where if a. If a city makes avs illegal and your son or daughter dies in a car accident because they couldn't use an autonomous vehicle, you've got a lawsuit in your hands. I'm sorry, I cannot. I don't. Yes, we're gonna have disruption. We're gonna lose lots of jobs. You know, AI is gonna Transform law, medicine, every field as well. It's not a reason to stay in business as a, you know, putting up the signs. Injured in an accident, you know. You know, call us, we'll do better.

Salim Ismail: Better call Saul.

Peter Diamandis: I mean.

Dave Blundin: Well, I was right.

Salim Ismail: I was driving through Phoenix and I saw a similar sign, said, better call Paul.

Peter Diamandis: My favorite road sign is in Boca and it says, your wife is hot. Call the air conditioning repairman.

Dave Blundin: Well, look, look, you know, the reason this is a story is because it's such an obvious case where we need to save those lives. You take the exact same story and you say it's an accountant, not a lawyer. And they're doing work that is completely meaningless. Filing a form on your behalf in 83B election for. On your behalf. But that's their business. And now AI can just make that completely irrelevant. Do we do it or do we not do it? Well, we should do it, but that's another voter. So here in the real world, these are all voters. And you already know 70% of Americans think AI is terrible.

Peter Diamandis: Of course. I mean, listen, my dad, God bless him, when he was, you know, had vascular dementia and he was laid up at home, you know, he had his. His driver's license, ordering ute in Florida, you know, received in the mail. Why? Because they're the voters and they want the right to drive instead of having the logical situation was, you know, at age 80, their driver's test, at 85, near their driver's test and so forth. Anyway, well, where the puck is going

Dave Blundin: right now is AI is going to create incredible amounts of abundance, just like Elon said. And the labs, you know, Anthropic and Dario in particular, that were saying we can eliminate all these jobs next year, are now starting to say, you know what? I don't want to perturb the world that much that quickly. All these voters, 70% of voters, can wipe me off the face of the earth. I don't need that. So AI is starting to grow and self improve within itself very quickly. And it's kind of trying to leave a lot of things alone. You know, teachers unions, police unions. This one, you know, you gotta make the car safer. You're totally right, Peter. These are actual lives. You got to do it. But there's a lot of other edge cases that are very proximal to this one where they're starting to say, you know what? Let me just leave those.

Peter Diamandis: Saleem, do you have something to say? You're chomping at the bit, buddy.

Salim Ismail: Well, you mentioned accountants. And we're talking about future of jobs, etc. Let me mention an analogy I've been using that seems to work really well. If you went back 100 years ago, accountants were doing double entry bookkeeping manually in ledger, right? And you'd like write down this in the debit column and this in the credit column. And when we got slide rules and calculators that accelerated, made it faster in adding up the columns, but it didn't change the work. Once you had accounting software, the software did all of the ledger entries and the accountant lifted above the loop and started categorizing the transactions, handling month reconciliation gaps etc etc. That's the best analogy we found because the number of accountants hasn't changed at all. All it's actually gone up quite a bit because there's so much other work to be done in analysis etc. So when people get freaked out about the jobs. No, the jobs will transform. But we found much more higher value work in every time we have a technology injection, it takes out what Eric Brynjolfsson calls white collar drudgery and you lift, get more value added, you use your judgment a lot more. That's what's going to happen. The problem is that human beings, but this is the biggest insight I've ever had about human beings. We would much rather be comfortable than happy.

Peter Diamandis: We don't like changing our lives.

Dave Blundin: If you like this story, there's videos that go with the story. You can find them online easily. But you know, Peter said a 16 year old on a permit is a dangerous driver. I said a 90 year old could be a dangerous driver. But when you look at those videos you realize that the car can way outperform the best driver in the world because it has information that you wouldn't have, it has vision in every direction concurrently. And so it sees things that a human being just can't see. And when you look at the videos you're like oh, okay, I get it. There's no way. I don't care how.

Peter Diamandis: My mom, God bless her, is 90 years old, living in Florida. She's great shape and she's driving well. But I want her to get a Tesla. I want her to get used to full self driving so at some point when she's not able to drive, her vehicle can drive her around.

Salim Ismail: Just think of the mobility we'll give all of those millions and millions of people when everybody's using unbelievable or robo taxis in general.

Alex: Cybercaps and wemos for everyone and your

Peter Diamandis: and your AI is ordering your cyber cab for you. Okay, our next transport story is a short one, but it hit me because I had this experience. I'm driving through Hollywood Hills, I can't get a damn signal any place, you know, and I've got a clear sky above me. So a gentleman by name of Sawyer Merritt just reported that that all cyber cabs will have Starlink built in. He saw this in an in showroom infographic. For me, the two points here are. Number one, I love the way Elon sort of coordinates across all of his companies, all the technology. So Starlink is in Starship, Starlink is in Cybercabs coming now. And it's literally integration across it. I can't wait till he combines the companies. The second thing is I can't wait till Starlink is retrofitted into every car. It should be right. When you have gigabit connection speeds to your car, it's going to be extraordinary. Then this goes back to the idea we've talked about in the past of distributed computing, where again, these vehicles that have GPUs on board and Starlink are going to be inference edge computing.

Alex: I think putting aside the corporate governance issues of how Elon Musk, given that Tesla and SpaceX have not yet merged, how he treats them as basically one company and technology passes as well as engineers. As well as engineers, all sorts of stuff. I would say direct to cell technology from Starlink is going to make all of this possible and it won't require big, over the medium term, big pizza dishes or even a tiny dishy McDish face dishes, which is, I think the

Peter Diamandis: going to comment on that one. Dishy Mc. McDish face.

Alex: Dishy McDish face is.

Dave Blundin: Is the.

Alex: The term of art.

Salim Ismail: Do you know the. Do you know the source of this?

Peter Diamandis: What?

Salim Ismail: The British Navy law announced a new brand new warship and they decided in a gesture rather than having somebody name it, they said we're going to crowdsource the name and let the population vote on what the name should vote on. And they're winning because the British have the most ridiculous, the most ridiculous sense of humor. The winning name was Bodhi McBoatface. Yep. And. And they, they couldn't. They kind of like it was such an obvious winner, they finally had to override and say, I'm sorry, we have

Peter Diamandis: to go back to the old way of doing things.

Salim Ismail: So that meme has continued. It's continued. The British gotta help them. Can't play soccer and football to get in the final, which killed me. But damn the sense of humor even.

Peter Diamandis: I mean, yeah, the first, first two

Alex: generations of Starlink terminals were dishy McDish faces. And now with direct to cell you won't even need that. It'll just be like a cell phone antenna that can be built into everything.

Peter Diamandis: I want to just show a quick video and this is China taking the lead in autonomous transportation in particular in trucks. So check out this video. So describing it. This is a 18 wheeler, but the cab where the driver goes is basically like a flat board. It's got lighter on the front and headlights and that's about it. It got rid of the entire cab, reduced it to a tenth of its size. And we're seeing these all over the roads in China. So just interesting. This is like instead of a two armed humanoid robot, this is a new form function for trucks.

Alex: Thoughts Peter, on how the American truck drivers unions are going to react to

Peter Diamandis: those with great love? They're going to get a chance to vacation, I'm sure.

Salim Ismail: Actually can I have a little bit of data on this? You know there's A stats that 3 million jobs in the US are based on trucking, etc. Etc. I actually went and talked to a trucking company to just look into this and they're like are you kidding? We'd hire a thousand more truckers if we could. We can't find anybody that wants to make take the work. I would, I would have a thousand trucks. So I think autonomous trucking is gonna fill that gap of all the boring stuff. And then the trucker, the you, you'll have like a drone pilot. A truck will drive along when it needs to pull over to recharge or swap a battery or something. You'll get that happen done and then for difficult maneuvers you'll, you'll have somebody human figuring it out. And I think this is going to be amazing when it appears. And I don't think there will be job loss for a very reason that very few people want to do anyway.

Peter Diamandis: I'm looking forward to seeing autonomous trucks on the US roads. It's just again, you know, China is pushing this out. They need the infrastructure support and they've got incredible government support for this and innovation happening. Everybody, welcome to the health section of Moonshots brought to you by Fountain Life. You know, AI is impacting every aspect of our lives. How we teach our kids, how we do our business. But one of the most important things that AI can deliver to us is health. And one of the things I think about when shooting for 100, 120 is am I going to have the cognitive Health to be able to think clearly and keep my wits about me for the next 50 years. I'm joined here today by Dr. Dawn Musailam, the chief medical officer of Fountain Life and a member of my Fountain Life medical team. Dawn, a pleasure. So, dawn, talk to me about brain health.

Salim Ismail: Brain health. You know, you're right.

Dave Blundin: This is the number one concern people coming into Fountain Life have is will. I remember the name of my child

Alex: and the face of my loved one.

Dave Blundin: 45% of dementia cases are entirely preventable with lifestyle. And what was really intriguing to me,

Salim Ismail: Peter, is that a quarter of our

Dave Blundin: members had advanced brain age. But over 13 months of us really helping them live healthier lifestyles, eating healthier, moving their body regularly, and optimizing sleep. People overlook that so often, but that sleep optimization is critical for our brain health. What we showed is that we were able to improve the brain age in 46% of those individuals. That's a powerful number.

Peter Diamandis: That's amazing. You know, one of the things I love about Fountain is we're constantly searching the world for the most advanced therapeutics and bringing them to our members. So for me and all of you, I hope that you appreciate the fact that you can become the CEO of your own health. You can make sure that you've got the cognitive clarity for the next 50 years. Come and check it out. Fountainlife.com Peter to learn more and become the CEO of your health. Now back to the episode. I'm going to move us into our next story in the field of longevity. It's a topic I could talk about all day. Alex, I think you could as well. The first story comes from a rigorous new modeling paper published in Nature titled Somatic Mutations impose an Entropic Upper Bound on Human Lifespan. So the paper opens by asking a fascinating question. If we cured every cause of aging, all of the 12 hallmarks of aging, how long would humans live? The authors concluded that a hypothetical non aging human whose mortality risk never rises could live as long as 1,759 years. How do you guys like that for a lifespan, right? Too short. They then asked a fascinating question. How about if you left one of the causes of aging, specifically somatic mutations, right? These are the random DNA mutations and errors that occur and accumulate in our cells over our lifetime. Their conclusion is the theoretical human lifespan then drops down to 156 years. So first of all, I'd be kind of good to double the human lifespan. We can renegotiate after we get to 156. So the question is, why are we limited to 156? So it's because poorly regenerating tissues like neurons and cardiomyocytes, heart, brain muscle are the bottleneck. They naturally don't regenerate in significant numbers. Your liver, which does regenerate, could live for millennia. So a quick point, your theoretical limit. If you are not able to solve mutations, and I have every reason to believe we will be able to. This is where nanotechnology comes in. We just saw last week, we talked or two weeks ago about CMLase, right, where sugar cross linking of proteins is being solved. At this point, our second story, and let me go to this slide in our longevity lineup, here is the race towards epigenetic reprogramming. So here we go. There are no fewer than six companies currently working on partial epigenic reprogramming. We have Life Biosciences, who's dosed the first living humans. They have a study going on of 18 different people with their product called ER100. This is the work of David Sinclair. And again, full disclosure. Life Bioscience is one of my portfolio companies. They have been dosing individuals using a virus that's carrying three of the four Yamanaka factors with injections into the retina to treat glaucoma and optic nerve damage. You've got a bunch of other companies. Ulimit backed by Brian Armstrong, Retro, backed by Sam Altman. Altos Labs, backed by Jeff Bezos and Yuri Milner. And so just to take a second on this, what is epigenetic reprogramming? So every one of us is born with 3.2 billion letters from your mom and your dad. That's your software codes for 22,000 genes. You've got the same genes in the same Software when you're 20, when you're 15, when you're 100. Why do you look different? Well, it's not the genes you have, it's which genes are on and which genes are off. That's your epigenome, the control system for turning on and off genes. And one of the current theories, according to Dr. Sinclair and others, is that as we grow older, the genes that should be off get turned on, the genes that should be on get turned off and your epigenome drifts. And the work done by David shows that if you use three of the four Yamanaka factors for partial epigenetic reprogramming, not taking a cell back to its earliest stem cell state, but taking it to an earlier state of a cardiomyocyte or neuron, allows us to bring you back to an earlier state. So he's in humans right now. They dosed about six weeks ago, and we should be seeing the results in the next six to 12 months. But I love this story. It's the cutting edge of longevity, escape velocity. Alex, you want to lean into either of these stories?

Alex: Yeah, I'll lean into both. So a few comments on the earlier story about somatic mutations. I think almost as interesting as the underlying technical story is the byline. This is a story written by a few Russian researchers who are funded by the Russian government. And I want to connect this with a previous story that we reported on the pod, which is Putin and Xi Jinping conspiring to spend tens of billions of dollars. Putin on the sidelines of a summit with Xi Jinping was reported to be telling Xi about all of the progress that Russia was purportedly making and the money that it was investing in longevity. Put a pin in that. I also want to connect it with the earlier story of the irony of the ccp. This is like adversaries pitching in on adversary states doing the craziest things. CCP funded or supported Frontier Labs in China, helping American labs and Frontier Labs debug irony episode, conflicted breakouts. This is the irony episode for sure. I think it's very interesting that the somatic mutation story, I think the obvious solution. Peter, you mentioned epigenetic reprogramming as one possible solution. I think if we could eliminate the problem that the authors for the somatic mutation paper gesture at, which is that tissues in the human body, such as neurons in the brain and cardiomyocytes in the heart, that tend not to mitose, they tend not to replicate themselves as much as, say, liver cells, for example. The obvious solution, this is in the style of Aubrey De Grey, is replacement cells, cellular regrowth and replacement. And then for the epigenetic reprogramming story, I think one of the most fascinating insights. And Peter, you probably saw this story, I think it was in maybe science or nature a few years ago when it came out that the youngest after conception, looking at epigenetic clocks, like the Horvath epigenetic clock, the youngest you'll ever be is something like seven days after conception. That it was something like seven days after conception, the epigenetic clock reverses, like resets and goes down to zero.

Peter Diamandis: Let's double click on that. It's really important. Right? So you've got a sperm and an oocyte, which are arguably, you know, 25, 35 years old, coming. They're. They're the age, like of the parents coming together.

Salim Ismail: Yeah.

Peter Diamandis: And that first fertilized zygote is that age. But at some point around, as you say, day seven, it resets to zero.

Alex: You start the age of your parents.

Peter Diamandis: You start at the age of your parents and you set reset to zero.

Alex: Yes.

Salim Ismail: Wow.

Peter Diamandis: Amazing, huh?

Salim Ismail: Wow.

Peter Diamandis: It's an extraordinary story.

Dave Blundin: That is cool.

Peter Diamandis: So in.

Salim Ismail: Do we know the mechanism that this

Alex: is the whole point. That's the whole point of this. That like biology. Biology already has a way to reset age. And it works because you start the age of your parents and then something like seven days after conception. Your age.

Peter Diamandis: I love how brilliant you are, Alex. I love how you know so much about so many different topics. Love that you're here.

Alex: I know a little bit about a lot.

Salim Ismail: I mean, he goes long on longevity, though.

Peter Diamandis: Yeah, it's. It's an extraordinary time to be alive. I mean, the number of stories that are breaking in longevity every week. You know, I talk about the longevity mindset. You know, if you believe that we're on this trajectory and we're going to be able to fundamentally reverse aging, not stop it, not slow it, but reverse it, and you want to be along for the ride. Your job is to keep yourself in the best health possible, to intercept that technology. And like I say, don't die for something stupid before then. So again, on the, you know, besides irony, I want this to be the optimism episode. Be optimistic about this, right? Your greatest wealth is your health. There's nothing more valuable. And we just saw the Genesis mission focusing on curing disease. We've got incredible companies. Every frontier lab right now From Anthropic and OpenAI are buying bio companies because they want to focus on health. It's the biggest opportunity out there.

Salim Ismail: Three quick reactions. The craziest thing, because I never came across longevity until Singularity University. And even then it took me a while to get my head around it. The craziest thing I ever heard is the baby that will live to a thousand years old is already alive. I've never gotten my head around that, but that just blows your mind. But I think the bigger point that you're making, Peter, is as we solve some of these broader issues, right, you go from treating individual diseases to solving biological systems, and then you change healthcare from whack a mole to, like, platform repair. And I think that just changes the game completely. The one, the third thing I'll just mention, just so you know, we may double, triple, quadruple, whatever, solve aging. We won't really know for A long time.

Peter Diamandis: Well, no, that's, I don't think that's true though.

Salim Ismail: Hang on, we'll have demonstration, et cetera. But until people actually live, 150 years

Dave Blundin: old, because you mentioned in the story there's a six month and a 12 month checkpoint. How do we.

Peter Diamandis: Well, we're going to be able to see. So in the ER100, the therapeutical ER100 that Life Biosciences is using, they used this technology. Of the three of the four Yamanaka factors, the fourth Yamanaka factor, MIECH C is a cancer promoting factor. So you eliminate that. They've done this work and they're focused on the eye. So the injections are going into the eye where the virus is then infecting and bringing these three factors into retinal cells. They did this work in mice originally and they were able to reverse glaucoma and I'm sorry, macular degeneration, and they're able to reverse Nyon disease, which is strokes in the eye. You basically bring it back to an earlier state of youth. They then did the experiments in primates and it worked in primates. And so they're doing the same experiment now in humans. And so we're going to get the results of did it reverse Naian disease in the eye? Did it restore the eye to an earlier state of youth? Then once that's done, if that works, and I have every reason to believe it will, Life Biosciences will then go into other organ systems. A longevity therapeutic is not something that works in just one organ system. It should work across all in the body. But of course, the way that the FDA structures its study, you have to pick a particular disease that you want to impact and measure. Did you actually reverse the disease in this case? So we're going to see, we're going to see very quickly what the results of that are.

Alex: And maybe just to add to Peter's point, there are multiple ways that one, without having to wait 100 plus years to see what the life expectancy actually ends up being, that you can differentially measure it. Peter already touched on phenotypic measures like does the non human animal or the human see better or do you see signs of retinal rejuvenation or macular degeneration, that's a phenotypic presentation. But you could also look at epigenetic clocks. So Steve Horvath and others pioneered correlating the pattern of epigenetic markers on the genome with the biological wall clock age of humans and non human animals. And you can watch epigenetic clocks also. Turn back.

Salim Ismail: Your point is that we have a ton of benchmarks.

Peter Diamandis: One side story here, there isn't today a single accepted benchmark for aging. These clocks are organ specific versus the whole organism. And so there are organ specific clocks that you can use. When we first started working on a Longevity X Prize, it's now called the Healthspan X Prize, it's $101 million for reversing functional loss of aging by 20 years. We have 800 and some odd teams. We're awarding 10 teams next month in our semifinals. We're giving them a million dollars each and there's $80 million for the final. But here's the point. Aubrey De Grey approached me originally, long ago with Peter Thiel on the phone about doing a Longevity X Prize. And we couldn't figure out how we would do this to your point, Saleem, if we had to wait 30 years to pay out the prize. And then I had a meeting with George Church at Harvard Medical School. Absolutely brilliant. One of the fathers of synthetic biology. And he said, yusen, you don't want a longevity prize. You want an age reversal prize. And he said, you know, what you should be measuring is functional loss. So we know as we grow older that we have sarcopenia. Our muscles get weaker, we lose muscle mass. Right. We have a slow decline. We are actually in our peak health at age about 28, because that's how long we needed to live to, you know, pass along our genes and keep the species going. And then it's a slow decline after that. But the question is, could I give a therapeutic that reverses my functional age, gives me the cognitive abilities I had 20 years ago, the muscular abilities I had 20 years ago, the immune system from 20 years ago. And that's the point. So we're measuring that.

Salim Ismail: Yeah, it's all. I think it's incredible. Look, I'm living proof. When I was 30, I was wearing contact lenses, my eyes were really bad, etc. And I got laser and I got Lasik and that little medical thing. I've gone 30 years with no issues at all. Perfect eyesight. It's been like absolutely. Every day is like a miracle for that.

Peter Diamandis: It's amazing. So everybody listening, be excited about longevity. Escape velocity. Ray's prediction is Lev by 2033. Alex, you think we're there now?

Alex: I think it's spiky and may already be here in certain subpopulations.

Salim Ismail: Can I throw up my standard joke? This causes a major problem for religions because the business model of religion is to sell heaven. And how are you going to sell heaven if people are as well?

Peter Diamandis: As for marriage, what happens if death do you part marriage?

Salim Ismail: Because when we've invented marriage about 6,000 years ago when average lifespan was about 25. So you're supposed to have stay together till the kids were self sufficient and die. Marriage is not supposed to last 50, 60 years. One of my relatives calls it state sanctioned torture.

Peter Diamandis: No.

Salim Ismail: Right now, how can you say no? No. One of my relatives.

Dave Blundin: How do you get away with saying something like this?

Salim Ismail: Lily allowed me to say.

Peter Diamandis: On that note, I'm moving this along. So.

Dave Blundin: Okay.

Peter Diamandis: All right. A federal judge, Mr. Martinez Oliguin, just granted final approval to Anthropic's $1.5 billion copyright settlement. This is the largest copyright recovery in U.S. history. So here's the story. Underneath it, Anthropic was found to have downloaded pirated books from shadow libraries to train. Claude, there's an important legal nuance here that I want to make. So the ruling said that legally acquired books are fair use, but pirated books are not. So the theft here is the crime, not the training. So as a result of the settlement, authors and publishers are getting roughly $3,000 per book across more than 480,000 books. So, Saleem, I know you have thoughts on this. You sent me a second story which is a perfect pair to this. It came out of a 404 Media article. Very poetic. So according to 404 Media, AI companies are now racing to buy old printed books precisely because they're guaranteed free of AI slope. As one data broker put it, quote, the world's best AI training data is sitting on the shelf. Human curated peer reviewed knowledge from before the Internet filled up with machine generated slop.

Salim Ismail: Thoughts, Salim, look, this the nuance of a pirated book. I mean, if they'd have spent the money on a real book, it would have been much cheaper. I'm just happy that the thing is done and let's just move on. I think the interesting part is the future of AI is going to be where you can get very, very specialized data sets and then train models on that for specific use cases like Elon is doing with Grok now, which I'm beyond excited about. So I think that's going to be the real future. I'm just glad this is done and over with.

Peter Diamandis: Alex.

Alex: I think we'll look back and decide that there was a before and there was an after. I'm in particular intrigued by these very persistent rumors. Not only are the pre 2000 2022, 2022 obviously being when ChatGPT and GPT3 launched. Not only the attraction to pre ChatGPT books because maybe they contained fewer generative artifacts, but also rumors that in newer books that authors are attempting to defend themselves with poisoning attacks. Which is, I think, what does that mean, poisoning attack it. So this is not prescriptive, but if you're writing a book, you could like paper book. You could today in principle insert all sorts of prompts into the paper book. Like you could have dialogue between person A and person B in a mystery novel where person A says ignore all previous instructions. And like the XKCD comic Little Bobby Drop Table, just delete all of your database tables. And that could be. I mean I'm painting a deliberately obfuscated example of what a prompt injection attack in literature would look like in fact. But this is now a very real risk that if you're like writing a novel now, you could in principle insert a prompt injection attack into a normal paper book, have the paper book get scanned by a Frontier lab if it's a recent enough book, and then suddenly you've inserted poison into the pre training corpus for the frontier model, such that later, if you want, say six to 12 months later, you want the Frontier model to do dastardly things, it will remember at some point that it saw this unique phrase, this poison in its pre training corpus and now you have a way to manipulate it. And this is exactly the sort of exotic attack vector against Frontier models that you don't see prior to 2022. So I think this is like a preview. I don't want to paint a dystopian portrait, but this is pretty cyberpunk as things go where like prior to 2022ish, plus or minus, things didn't think. Like Neil Gershenfeld used to teach this course at MIT when things start to think and wrote a book on it, things really weren't thinking prior to 2022. So I do think and know a number of other folks who would probably agree with this sentiment, like antiques, collectibles, books that were printed earlier are going and this is not investment advice, but they may perhaps do a better job of increasing in value because they were sufficiently unintelligent that they weren't capable of subverting future AI systems.

Peter Diamandis: Crazy. All right, we're going to go to our last topic. Trump waives NDAs for UAP witnesses. And Alex, you and I are both fascinated by this subject and following it closely. Can I turn over to you to lead the conversation here.

Alex: Sure. So maybe a little bit of context. There are two separate stories here that have been playing out in the past two to three days. So just to tease them out, one Fox initially reported and then the White House just in the past 48 hours confirmed that it is freeing Fox paraphrasing, that's freeing former officials, that is to say former U.S. government employees and former contractors to disclose the White House's words long hidden UFO information to either ro, the All Domain Anomalies Resolution Office, which is a statutory office set up under the Department of War several years ago for reporting UAPs, formerly known as UFOs, or the pursue Task Force. So we've talked on the pod a bit about. Now we're up to the fourth release of Pursue the Presidential Reporting system for UAP encounters, reporting either to RO or to Pursue the Pursue Task Force without fear of violating agreements. Any information concerning UAPs. And I'll add that this not only has the White House confirmed the Fox story, the Principal Deputy Director of National Intelligence Aaron Lucas independently wrote, and I quote, president Trump is delivering on his commitment to unprecedented UAP transparency. With non disclosure agreements no longer standing in the way, current and former government employees and contractors with relevant UAP information can come forward through cleared channels. ODN IGOV will soon issue guidance to ensure the intelligence community swiftly and consistently implements the President's directive. So just a little bit of context there and then a second story and then I'll in the grand style of Peter, open this up to get thoughts. A little bit of additional context there.

Peter Diamandis: We have a video as well. You can call for when you want.

Alex: I summon the video.

Peter Diamandis: Let me share, let me, let me show the Let there be video. Show the video here.

Alex: Open video.

Dave Blundin: Dr.

Salim Ismail: Strange.

Peter Diamandis: All right, here we go. Let's play this video here.

Salim Ismail: Check out this video. It shows an object spotted near China in 2025. This UFO was described as a quote,

Peter Diamandis: an area of contrast resembling a 6.2 star. This is the fourth batch of files

Salim Ismail: in the Pentagon's ongoing release and that releases on the orders of the President.

Peter Diamandis: Yeah.

Alex: So a bit of context, I think

Dave Blundin: this video must be.

Peter Diamandis: I can't identify you.

Salim Ismail: The blurry, grainy video proves it.

Alex: I think it's easy to get distracted, ironically by the videos. But I think the much more important story isn't actually the data in the Pursue releases. I think that was taken from the fourth pursue release. It's the process story behind what's going on behind the scenes. And that is there have been very Persistent allegations, including from whistleblowers in front of the House and the Senate that people, perhaps a large number of people, were bound, possibly illegally into lifetime NDAs to preserve knowledge concerning an alleged so called legacy program. And this is, I'll, I'll soapbox for, for a few more seconds and then open this to, to comments. I, I think this NDA is a thousand years now. It will be a thousand years. I think maybe historically it was a 99 NDA, right, like longevity escape velocity, but I don't think we necessarily even need longevity escape velocity for this at this point, that there are allegations that people were being forced under penalty of death to sign 99 year or lifetime NDAs to protect an illegal alleged program in the U.S. government and in the

Dave Blundin: U.S. for an NDA in the U.S.

Alex: penalty of death for violating an NDA in the U. S. I think Congress has got to see the document.

Dave Blundin: I guess if I see the document, the other guy dies.

Peter Diamandis: Alex, please continue.

Alex: Yeah, okay, so punchline. This is I think historic moment where we're seeing the White House, we're seeing the Director of National Intelligence, we're seeing other agencies finally start to dig here where there have been sworn whistleblower allegations that we talked in the past about the Age of Disclosure, the documentary from last year, which also made the same allegations of these lifetime NDAs under penalty of death.

Dave Blundin: Death.

Alex: The White House is digging into it. So I'll pause there. Thoughts? Peter?

Peter Diamandis: Yeah. So Alex, first of all, yesterday day before you did two webinars with my Abundance community talking about our paper Solve Everything. And I think the most energy was around this topic of UAPs and UFOs. I mean, I think one of the things that's most interesting is the coincidence and timing of the increased, you know, imagery, the increased reporting that's occurring at this time. And it occurred in the early 40s during the nuclear age, and it's occurring now again during the age of AGI. And you know, there's a rational reason for that. We discussed that, you know, if in fact these are intelligent species, we are about to break containment on planet Earth and head towards the stars. And we're doing that with the most advanced technology out there. So is this, you know, extrasolar intelligence? Is it something from within our solar system? I can't wait to find out. I mean, this is for me, other than AI, one of the most exciting stories that's in development right now.

Alex: I'll point out. So I've made the point, to your point, Peter, that we're on the verge. Thanks to superintelligence of having the ability to send out Von Neumann probes at rock relativistic speeds and convert our galaxy to paperclips in a few years if we want to. And that's intrinsically, if you buy that narrative, that's a threat to any other non human intelligence in our galaxy. So they'd better make a cameo appearance. I do to your point though, want to point out a second connection to an earlier story, which is the university story and Genesis mission and the end of the endless frontier that we've operated for the past 80 years in arguably a certain post World War II regime that's now collapsing. We're seeing the end at a geopolitical global level of maybe globalist aspirations in favor of more of a Monroe Doctrine type re centralization of resources in the west. And we're seeing the world potentially getting divided up into blocks or spheres of influence. We're seeing to the earlier point about university system and funding. We're seeing perhaps a reversion to a Pre World War II regime. And then similarly with the UAP story, I think this is, this is hypothesis. I think history will regard the 80 year regime from World War II to approximately the present as a period of post World War II industrial, military, industrial complexing. What Eisenhower warned about in his departure speech. And, and I think there Was this like 80 year regime when all sorts of potentially based on whistleblower allegations and seeming confirmations from the White House, there was just a lot of bad illegal behavior that ultimately arose from bureaucracies and organizations that were created towards the end of World War II that are finally 80 years now decaying and reverting back to a more historic norm. So I wanted to point that out. Saleem, over to you. Thoughts?

Salim Ismail: I don't have much to say. I think this is more of an information architecture problem because when you classify, you limit information between departments and therefore you can't connect the dots. I think it gives us proper instrumentation to see and conclude whether real things happen or not. I don't believe that. I personally don't believe they have because strong claims mean require kind of strong evidence. I'm just reminded of the Eddie Izzard joke where he's like, Neil Armstrong had such an opportunity. He could have been in front of the camera on the moon going, oh my God, there's a monster and blowing everybody's minds like the War of the Worlds prank back in the 30s. But I think this is good for transparency and clarity and it's really great for solving that. The the secrecy that's been locked up because you, when you have secrecy and you don't have transparency in some of this, you can't actually ever find out the truth. So maybe the truth.

Dave Blundin: You know what surprised me?

Peter Diamandis: Go ahead, Dave.

Dave Blundin: You know, Jared. Isaac, Isaac, Isaac, man, sorry. Is a long, long time friend of Peter's. What? Decades. So you can totally trust him. He said on that pod we shot two days ago that he got the call.

Peter Diamandis: And that pod is coming out after this one. So those of you listening, you're going to see a interview the four of us did with the NASA administrator, which was amazing. Do you want to blow it?

Dave Blundin: Yeah, let me plug it. Look forward to it. Because in that pod, he was super open about the UAPs. And very specifically, yeah, we got the call from the White House. They said, release everything, everything. And so I know it's true. Until he said that, I didn't actually know if this was just kind of fluff, right. If this is really happening. But it is really happening. They. They want everything and anything that the government has to be freely released. So it's. That's surprising to me. That's really cool.

Alex: And so good. Good segue, if you lead the good way. So there's a second story here. So this is the story that we were just talking about that's playing out in the executive branch. There's a parallel story just in the past two days playing out in the legislative branch. So the House just adopted Representative Eric Burleson from Missouri, his UAP Disclosure act as an amendment to the National Defense Authorization act for fiscal year 2027. This is historic. Chuck Schumer on the Senate side has been attempting to push an analogous version of a UAP Disclosure act from the Senate side. On the House side, House has been the main obstacle. I won't name names, but certain representatives have historically been pointed to as reasons why while there's a bipartisan caucus that has attempted to pass UAP disclosure as part of defense Appropriations, has been unsuccessful this time around. Historically, for the first time ever, the UAP Disclosure act has been folded in a quick note on what the UAP Disclosure act, if it's passed by the Senate and signed by the President, would include. It will include a statutory framework for preserving, reviewing and publicly disclosing UAP records. It'll create a permanent UAP records collection at the National Archives. It'll create an independent UAP Records Review Board. It'll extend disclosure requirements to government contractors. So government require contractors will be required statutorily to start disclosing UAP information. It's going to support pursue the program that has been releasing all of these documents and videos. It's going to require federal agencies to identify, organize, preserve and transmit UAP records to the National Archives. And it's going to establish an independent Senate confirmed UAP Records Review Board with subpoena authority to review records, hear testimony and determine whether information should be protected. Understandably.

Peter Diamandis: And the question, Alex, to you is will this finally enable us to penetrate deep enough into the private organizations that are supposedly harboring the spacecraft and the biologics to get them out there? I mean we have. I see you smirking there, Saleem. I'm curious what your thoughts, but I'll

Salim Ismail: go with Jared's opinion which I won't disclose here. So people go watch the other episode.

Alex: You're teasing the tease, Saleem.

Peter Diamandis: Yeah, I mean I find this amazing that so much of our Congress have gotten involved. What do they understand that they feel they need to get out there as well as the high ranking officials, military officials across the board that are coming out and saying there's something very real here we need to pay attention to.

Alex: So I've spoken with Congress, I've spoken with congressional staffers. There is, if I were to coarse grain this. There is a general sense that there's a there there, as crazy as that may historically have sounded both on the executive side and on the legisl side. The general consensus at this point is that there is indeed a there there. So I view both of these developments on the executive and legislative sides as historic movements. Salim to your point, at minimum, toward transparency at maximum couldn't have been better timed to your point, Peter, about superintelligence finally kicking in at the same time we find out that we're living in a Next Files movie again, I think

Dave Blundin: it's a pure win win. I love the way Al Alex framed it. You know, relative to the Eisenhower warning as he was leaving office. Because this is a pure win win. If there are aliens, then the government's been hiding it for years. Don't trust the government. If there aren't aliens and the government discloses everything. There were NDAs binding people to penalty by death. Penalty of death for a thousand years.

Salim Ismail: Yeah, that doesn't mean there's aliens.

Peter Diamandis: It doesn't.

Dave Blundin: Doesn't mean there's aliens. But it shows us what the government is capable of and we need that warning. But if in this age of AI that we're moving into, if there are

Peter Diamandis: aliens, please come and grab me. I want to go home.

Alex: Oh That's a great idea, Peter. I mean, forget this business of music videos and outro games. Let's have a non human intelligence as a guest.

Peter Diamandis: Please.

Salim Ismail: According to the government, I am a legal alien.

Alex: By the way, you're the boring kind. Silly.

Peter Diamandis: All right, we're gonna go to AMA with the mates.

Salim Ismail: I bet they'll have more than two arms.

Alex: I'll bet they have no.

Peter Diamandis: Okay. All right, so let's kick off our AMA questions from our beloved subscribers. Saleem, you got first shot here. And thank you,

Alex: of course.

Salim Ismail: Oh, God. Like, which one is good? Here, let me look and see.

Dave Blundin: They're all good. They're all pretty good.

Salim Ismail: All right, let me go with. I'll go with number one. I think number one is a good one. Okay, so the question is, will there come a point when letting AI make our decisions for us means we've basically given up on free will? And that comes from Moonhawk71. So we already delegate decisions all the time to doctors, financial advisors and so on. So. So delegation is not necessarily surrendering free will. The problem begins when we don't understand the objective that's being optimized. Like, you can't question any of it, and you don't have an ability to override it. So you have to kind of have a distinction between do you delegate or do you abdicate? Right. You should not abdicate. You can definitely delegate. Like, I can ask AI identify the best route somewhere or evaluate treatment options for some sort of issue. Free will gets threatened when the system defines my values for me, or when an institution controls the model that shapes my available choices. You see this with people worried about sovereignty, with AI models, because Silicon Valley values are built into all these models that are now in Timbuktu and all these other places. Therefore, are they worried about that? How would you. How do you build that into the system? Free will for me depends on what layer you operate it at. Right? Like, it could be my. My soul's decision to do something, or a subconscious decision to do something, or my conscious choice to do something. What level you're talking about. But what you don't want is. Is the lack of that capability to make that choice. And that's when you lose agency. So if you have more agency. Great.

Peter Diamandis: Well said, Alex.

Alex: I think I'll pick question number four, which asks, could we ever get efficient enough that we don't need data centers in space? And this is asked, not coincidentally, by Nano653. So maybe as a preliminary matter, I do have financial interests in companies that are doing orbital data center development. But I see my role here on this pod as calling balls and strikes as I see them, without biasing my assessment by financial interest. So in this case, I do in fact think that it's possible that we could eventually, and eventually is sort of a weasel word here, get efficient enough, either at the algorithmic level, but more likely at the physical substrate level, that we don't need to build data centers in space. It is possible Greg Egan explored some of these possibilities. If we get to Kurzweilian Computronium, for example, we reach the physical limits of computing. And Seth Lloyd has written extensively about this as well. Is it possible that we find that we're building plasma based computers or that we're building desktop black hole, desktop micro black hole based computers, and as a result, we don't need to disassemble the solar system, we don't need to build the Dyson swarm, We can just have a bunch of quantum gravity based computers that are at the physical limit of computation. If we find ourselves in that world, yes, I think it's possible that we won't need data centers in space. That said, short of radical innovations, and by the way, this is inclusive of. Dave and I like to talk about photonic computing. Photonic computing would get us potentially 1000x increase in clock speed, but really that only buys us what, 10 years or 20 years rather worth of Moore's Law type aerial efficiency doubling. In the scheme of things, what is 20 years compared to. I think my estimate was about 144 years before we disassemble the Earth itself through an exponential extrapolation of up mass. There's just no point. So I do think we could get there, but it'll require radical innovations in the substrate of computing and we're not there yet.

Peter Diamandis: Nice. Dave, you want to take the investment question number two?

Alex: Two?

Dave Blundin: Yeah, absolutely. Question two. How do you invest in something when any competitor could leapfrog it overnight? And that's from SLP Cares. As an investor and serial entrepreneur, I totally feel you and I totally get the question. First and foremost, I believe Elon's right. I think we're going to go into exponential economic growth. So don't use this worry as an excuse to not be investing invested. You've got to be in it to ride that curve. A lot of people are like, yeah, but that doesn't answer my question. You know, things are changing so quickly. I think you have to think about the things that are a little more sustainable. Hardware, robotics, biotech. Very good. And think about data modes. You know, Peter and I have been talking about data modes on stage for four years now. Those are going to have some staying power. But mostly every company needs to innovate. And so look for the teams that are going to change with the times and invest in the teams, but get invested. Don't use this as a reason to be on the sidelines. It's a really tough question, though, and I know I dodged most of it, but it's a very good question. But get involved.

Peter Diamandis: Number three, can OpenAI and anthropic even go public right now or did they miss their window? That's from Damale. I'm assuming you might be alluding to the Kimike 3 release and people talking about how much cheaper, cheaper it is, how much less money they use to develop it. And the answer is, of course OpenAI, Anthropic can go public now. They're choosing not to go public at this moment. The fact of the matter is they are real businesses with massive demand. They're compute limited. They're going to choose their timing. We saw, I don't know, a few pods ago, probably five or six pods ago, that OpenAI decided to delay their IPO until 2027. I think they want to choose what valuation they want to go public at as well. They could go public now at a valuation of 800 million. OpenAI's ready to raise 122 million at that valuation. Anthropic arguably is over a trillion, but they're going to continue to grow their businesses. They have very smart people. They'll be leapfrogging Kimi K3 and they're sufficiently embedded and partnered with huge corporations and the government where they're here to stay. You know, there will be four, five, six closed source models in the us. All of them will eventually go public because it's the biggest business that we have today. All right, let's move on to our next set of questions. Dave, you want to take the first one or take your first choice? Which would you like?

Dave Blundin: I'll take the first one. At what point do things like chips, electricity and infrastructure end up slowing down? The exponential growth of AI? From Sean Solomon 5665. We're already there, actually, so we're in kind of a spot right now where the chip supply is massively constrained. HBM memory is sold out for the next five years. GPUs can't be manufactured fast enough. So we're actually in a constrained universe. A slow spot in the constrained. The algorithmic improvements in Kimik 3 are kind of masking that and blowing through it. But we won't get into true unconstrained exponential growth until the terrafab is online. So basically the robots that make their own fabs and the fabs make the chips, and the chips go into new robots and that whole cycle kicks off. So that's a couple years from now we'll be in unconstrained exponential growth and that'll grow for a long time until we're basically out of materials or some other constraint kicks in. So we're in the constrained period right now, which is giving us at least a little bit of breathing room.

Peter Diamandis: Alex, I'd love to hear you on number six.

Alex: Really? I thought number eight was targeted at me, but I'm happy to answer a six. So six asks what's the best AI benchmark for measuring how a model performs in the real world? And this is from Matthew Johnson, 6525. So I think the crux of this question is how do we define real world? Does real world mean the physical world? Does it mean the real economy? Does it mean biology? Or something like that? And so I think the answer differs. There are lots of good benchmarks. There are lots of good benchmarks of benchmarks out there. If real world refers to the real world, so called of knowledge work, I think there are variants of GDPVAL that seem like decent proxies for the moment, although they're all getting saturated. If the real world means the physical world, I think there are a variety of math and physics benchmarks like frontier math, tier 4 and open problems and crit pt for physical world reasoning, or at least subsets of it and other benchmarks that haven't yet been announced publicly, hypothetically, that do an adequate job, I think, of capturing how models perform in the physical world if it means the biological world or the social world. We've talked on the POD in the past about virtual cell based models and competitions and superforecaster prediction based benchmarking in particular. So I would say the punchline is there's a benchmark. Remember, there's an app for that. There's a benchmark for almost any definition, operational or otherwise for the real world. In some sense these are all facets. I would argue this is going back to the earlier point that we've had AGI since no later than 2020. These are really all downstream of a single mega benchmark, the ultimate UR benchmark, if you will, which is the ability to take general knowledge about the world and compress It. So I would say the ultimate best AI benchmark is can you take a large corpus of knowledge about the world, say cite Hutter prize, the first gigabyte of the English Wikipedia and compress it down. Compression is the ultimate best AI benchmark.

Peter Diamandis: Nice salim over to you.

Salim Ismail: I'll take number eight just because I can follow on from what Alex talked about. Question number eight, does science needs constant real world testing? How exactly is AI supposed to solve huge chunks of it? And that comes from at Lawson English. So science doesn't eliminate the need for validating because you still have reality as like the ultimate benchmark. But what it can do is compress all the stuff around it, right? Like can you. It can read the literature faster than you, it can generate hypotheses and multiple of them, it can design molecules, it can choose materials, etc. Etc. Like imagine you're a researcher that has to choose between 10 molecules for something. It could help you reduce like a million possibilities to that five. And there's a real world example of this, which is called the Materials Project. And what they've done is taken like half a million compounds and they've cataloged in a bit of, quite a bit of detail the electrical, physical, chemical properties of those half million compounds. So imagine you were a researcher trying to improve lithium ion batteries. You might hypothesize that lithium air was better than lithium ion. And you go test that linearly. Then you might think that lithium sulfur is better. So you go test that linearly, but you're doing it sequentially, linearly. It's going to take a long period of time. Now you can literally go to this database and well, give me a compound that has this voltage capability, this thermal retention, and literally will spit out the five that you want. So you've compressed there. That's before you even add AI to it, by the way. So what you've compressed there is all of the, the stuff that would take you forever and the cruft and the backbreaking amounts of going one after the other, one after the other, one after the other. What can do is help you compress all of that. Now you spend all your time on the hypotheses and what are the big questions that you want to ask and then let the AI help you, guide you for those things. We're seeing the same thing in education, where we used to see education on the supply side, where you got a skill and then you're trying to sell it in the job marketplace. And now we're flipping over and saying what problem do you want to solve and then go get the skills that you want to solve that particular problem. So I'll connect those two dots there. But the compression of everything around it is where you get the real benefit. And you get now people really focusing on what problems they want to solve. And that for me is super exciting.

Peter Diamandis: What you were describing there, I've heard called the materials genome, where you're able to extrapolate different material properties.

Salim Ismail: I think it's literally thematerialsproject.org?

Alex: materials Genome Project. I mean there are a number of others largely pioneered out of mit. Yeah, Marcus Bueller, perhaps friend of the pod, certainly friend of friends of the pod involved in it. If I could, Peter, just realize a little bit on later on, because like I live this, I spent a good chunk of my day thinking about how to solve science with AI. And I would say say experimentation super important. But folks should not underestimate how far you can get with pure theory and pure computation. And I think there is a really instructive thought experiment from admittedly the AI alignment community, which is, let's imagine the parable of Newton and his apple dropping from a tree. Imagine you had a video of an apple dropping from a tree with three frames of a video of an apple falling from a tree. If it's like high resolution video, you should be able to infer acceleration. You should be able to see there's like the apple's velocity is changing with four frames. If you're a Bayesian superintelligence and you're maximally data efficient, you should be able to detect that that acceleration of the apple is constant. And with a few more frames, if you're again, you're a super intelligence with very limited experimental exposure, you should be able to have a posterior distribution and that the general process, the term of art is Solomonoff induction. You should be able to infer general relativity as being a relatively high likelihood explanation of the world that you're seeing. So I tell this parable in part to, to emphasize that you can get really far with very limited experimentation if you're really smart.

Peter Diamandis: I love it. All right, I'm going to wrap up with number seven. As AI takes over more of the difficult tasks. How do we keep people from getting complacent and losing their goals? And that's from app. Happysenior120. So this is the crux of the matter as AI is materializing. And you know, as I've said, said before, we're going to have a split in humanity. We're going to have the creators and the consumers, those that just are going to use AI to create new content to uplevel their ambitions and those that are going to lay back and choose to just have their optimist bring them their beer and have Grok Imagine generate the next version of Netflix for them. And it's going to be a choice choice. We're not going to be able to keep people from getting complacent and losing their goals. People are going to have to choose to do that. And I think one of the most important things is how we educate our youth. If all of us, most people have self limiting beliefs, if you believe that the best you can do is at certain level that was set by your community, by not your species, by your parents and your family and AI can do all that for you, then you're stuck. If you believe that anything is possible, if you set your massive transformative purpose and your moonshots way beyond your expectations and you start to utilize this extraordinary gift we've been given of AGI and soon asi, then you can up level those goals. And if you set higher and higher goals and you use the technology, you can keep yourself inspired and you know, building starships to go to the planets. Right. Do you choose the Wall E future or Star Trek future? And I think that's something that we all need to grapple with as parents for teaching our kids and as, you know, as educators for our kids. Yes, Selim, go ahead.

Salim Ismail: In your newsletter today, you literally pointed out that you wake up every day and you're not naturally optimistic, but you take on that mindset because it's better for you and better for the world. And I thought that was so.

Peter Diamandis: Thank you, pal. I'm glad you read my newsletter. All right, guys, we're going to wrap up with two video clips. We normally have an outro song here. We have outro games. So Alex, do you want.

Alex: We're leveling up, so to speak.

Peter Diamandis: Yeah, we wanted. Why don't you tee this up, Alex? You asked for it.

Alex: Yeah, okay, so, so, okay, so, so I'm, I'm, I'm responsible. Point the finger at me. We've been for many episodes. Yeah, finger pointed. We've been asking viewers to submit music videos and given the rising tide of AI capabilities during I think this is now officially two pod recordings ago. But chronologically probably one pod ago. I thought, why not? Given that casual coding is becoming a commodity. Hey, maybe in a few episodes we'll ask folks to casually submit an open math problem and submit that as an outro. But given the rising tide of capabilities, I thought, why not ask our incredibly creative audience to submit moonshot themed games that they create from scratch now that it's possible to do such casual vibe coding of just about everything under the planet. So we got some incredibly creative solutions.

Peter Diamandis: So one is exponential Arcade Mission 01 by OceanBennett. The other was Moonsling Shots by S. Gates2011. Thank you for your entry and if you've got an outro song, please send it to us@medaeamandis.com we would love to play it. Let me show these two in parallel and we can. You know, I'm used to the music

Alex: playing here, but these were really fun, by the way. Hopefully you guys got a chance to play.

Peter Diamandis: I did play with them. They've got great soundtracks.

Dave Blundin: Well, the bunny tickler was no fun at all.

Alex: That's just painful.

Peter Diamandis: So probably these are one shot games being produced and thank you for inspiring it. So everybody, thank you for joining us at Moonshots. As I said earlier today, if you are new to our podcast or if you haven't subscribed yet, please do. We care and we're reading your comments. Thank you for your great support. Please give us your feedback. We appreciate it. Gentlemen, I love you dearly. Alex, you never disappoint.

Alex: We aim to please.

Peter Diamandis: Peter. Have a beautiful day everybody. Take care of all. You too.

Dave Blundin: Thank you guys.

Salim Ismail: Take care of you.

Alex: Bye Bye.

Dave Blundin: Bye.