Bernie Demands the Labs Stop, Wall Street Turns GPUs Into Bonds, Grok 4.7 Takes #1 with Emad Mostaque | EP #279

21:15What is that?

21:21Spices. Supposed to be over two million pounds packed in this little nut. Who smuggles coriander in a boat? Someone who suspects it might get nipped. Or... Where'd your boys go after you left the pier? What the f*** is that supposed to mean? We came here and waited for you f***ing pricks like we were f***ing told. Let's go through it step by step, shall we? All right. Our second story. Bloomberg reported that nine out of the top ten text-to-video models on AI analysis leaderboard are coming from China. Yeah. This is a headline, but the real story is deeper. And I'm curious what you guys think about this.

22:07You know, Hollywood forever has been the dominant producers of films, and it's basically exporting U.S. culture to the rest of the world. What happens when the world is flooded by Chinese produced English speaking films? How is that swaying public interests and public points of view? And the second thing is that these Chinese models that are dominating video generation, are also learning physics, motion, object permanence, and causality, which is what's needed for robotics and autonomous driving. So things are moving quickly there. The third one, very quickly, then we'll go into the discussion here, a model called LTX 2.5 is the newest version of the most popular open source state-of-the-art video generation model.

22:52And it works on your your MacBook Pro, which is extraordinary. So I want you to imagine something that allows the individual to sort of tee up and produce their own movie. One more clip. This is from LTX 2.5.

23:10Dave Blundin:This is LTX, the most downloaded open source world model. And today it just got better. Introducing LTX 2.5. And now with the Fusion Fidelity rendering, a new way to generate video. Instead of locking every scene to one compression rate, our model allocates compute by scene complexity and budget, rendering flawless detail where it matters, efficient everywhere else. It generates fast enough to run live inside a game or a simulation or power a live avatar. And real-time products are already earning off worlds built on it. So, gentlemen, let's go to you first, Imad. This has been your world for the better part of a decade.

23:50Yeah, it's happening right on forecast. real-time high-definition video um so ltx can generate a 10 second clip in seven seconds at that quality that you just saw which is indistinguishable and a few years ago when we had the state-of-the-art model it was not like that it was like slow moving you know like will smith eating spaghetti was awful and horrible now you can do a spaghetti eating will smith right and it will just do it instantly on your local kind of laptop. So you said kind of the disruption of Hollywood, like you'd never need to reshoot a scene now with the flows that you have. People are licensing their things.

24:31And as you said, Hicksfield released an 80 page guide because they're a company that allows you to make movies on exactly how they made the movie. Like it's almost open sourced. Hicksfield got from, it's an ex-Snap leader from Snapchat. It's 700 million revenue run right now in about one and a half years to give the idea of kind of how much uptake

24:52Dave Blundin:but that's just the start that's crazy because everything crazy number yeah because every pixel will be rendered like if you see reactor who are using ltx now like again it could be that alex might be a simulation already but for the rest of us you know we could put our avatars live in the next month or two at a level that you won't be able to tell what was the one the one million dollar budget to make a one and a half a compute budget to make a one and a half hour long movie but what will that be by september 25th by the time we have the moonshots live event so it depends on the level of quality cdance 2.5 is the best model it's a large big model that costs about three dollars per 30 seconds roughly but you need lots of shots and it can have 50 inputs of audio and video and things the cheaper models are 10 20 times cheaper but like 90 of the quality so it all depends on exactly how you're shooting and the type of shots because sea dance can do 30 second clips but the average movie on the hollywood box office right now is three seconds per shot So you could have a 10 times reduction in cost.

26:03You could shoot a movie just like that one, probably for 100 ,000 of compute and then 10 ,000 of compute probably by the new year.

26:12Dave Blundin:Here's what we saw in our Foundations of AI Ventures class at MIT is that it went from PowerPoint demos to full functioning products in one year. Like to be competitive on demo day now, you have to actually build the entire product. But I suspect the movie, like our target for September 25th is bring a script. Well, so Dave's referring to the Future Vision X Prize that we're going to be awarding with all the mates here at Moonshots Live. And you go to moonshots.com to learn more. We have 5 ,000 entries, 5 ,000 who are creating three-minute trailers and a film treatment. I just had a meeting this morning with the team at Range Media and Google to down select.

26:55and we'll down select to ultimately the top 100, 50, 25, 10. The top five will be at Moonshots Live on the 25th. And everyone listening, you can comment, be there live and vote live. We're going to also have a live stream of the event. But yeah, and we're going to do this year on year. So every year it's going to get better, cheaper, for sure.

27:18Dave Blundin:I think this is going to be much bigger than we originally envisioned. I mean, I know it's a big vision to start with, But we were thinking, OK, then it'll be a$20 million year long endeavor to turn it into a real feature length film. But in reality, you're going to unleash the creativity of 5000 people who almost all can make their movie within a year. 100 percent. We have a$10 million budget to make the winner's film between the money we're awarding and and foreign film rights. But I was just talking with the range while we're going to be having five finalists and we'll crown the winner. And you should see the trophy.

27:51It's beautiful. They want to make all five. So we want to create an engine here. Salim, what do you think the implications of this are? And then, Alex, I'd love your thoughts as well. Well, you know, I'll go at it from an EXO perspective. We actually talked about Hollywood as one of the first domains that went into an exponential organizations model. because what happened when you broke up the Hollywood studios in the 50s and 60s is Hollywood turned into a cluster of external resources where a movie production would start and essentially a swarm of people would appear, grips and camera people and actors and editors and whatever, and they'd get together for that project and they'd completely disband after that, right?

28:40And we see the beginnings of that in Silicon Valley now. And so that was that first wave of Hollywood becoming an exponential organization. Everything was assets on demand. Everything was staff on demand. But now when you have everything being driven by AI, it goes through the organizational singularity. And essentially it's compute costs now moving closer and closer to what Alex always talks about. You have domain collapse now coming along. And so that's going to completely change the game again for this. So you've gone through two big waves in Hollywood. the second one just starting now.

29:15Peter Diamandis:Alex, what are you excited about here? What are your thoughts? So I made myself watch the Cully Hill Boys. And I must say, just as a preliminary, I skimmed through the whole thing watching a good chunk of it. See, when you only sleep about two hours a night, you can just do that. So I had to watch this. So it's not my favorite genre. I would characterize Cully Hill Boys as sort of British Bollywood, not quite even sure what genre this is. It seems to be, as far as I can tell, about the hijinks of a bunch of British rappers that get into all sorts of trouble. Content-wise, not super interesting to me, but at the functional level, it is really interesting.

29:57Peter Diamandis:And there were multiple times in the movie where I had to wonder, were the generative actors, So the likenesses were based on real humans, but were the scenes that were being generated, given the complexity of the interpersonal dynamics such as they were in this movie, was there some sort of emergent theory of mind that was almost necessary in order to generate some of these scenes with people interacting with each other? And especially generative violence. There were multiple times, you know, people with knives chopping things, chopping meat, threatening other people, where I had to wonder, is at some level, we talk about AI personhood on this pod from time to time, is there in some sense at some presumably intermediate layer in a diffusion transformer somewhere deep in the bowels of Higgs field, is there some diffusion transformer or similar model that felt threatened at some point in terms of these generative violence scenes.

31:01Peter Diamandis:So that was my take on the content of the movie moving. But you were worried that the residual AI might have been threatened in the making of the movie. Correct. I'm talking about that. OK, yeah, that's right. No, no natural persons harmed, obviously, in the generation of this. But I do. So we're going to have a disclaimer on content. No AI was harmed in the making of this. Or traumatized. Or traumatized. So I do worry parenthetically about that. The bigger question on the economics of this, I think, is at what point do generative video capabilities start to reconverge with the anthropic school, which I'd characterize as a token revenue maxing?

31:48Peter Diamandis:Right now, it seems pretty clear that if you're using C-Dance models, it doesn't matter how many millions of dollars of X Vision prize money are going to shower down on folks who can create spiffy videos about the future. That's nowhere close to the amount of money that one can earn in principle with revenue per token maxing. And right now, these appear to be two separate lines of effort. On the one hand, we have a vibrant, largely Chinese-dominated at the training side consumer economy for generating consumer videos. And on the other hand, we have enterprise revenue per token unit, value maxing that seems to be largely going to cogen and enterprise problems.

32:33Peter Diamandis:And right now, these are largely two distinguishable ways to burn tokens or diffusion transformer equivalents of tokens, flops, two different ways to burn flops. One of them maximizes revenue. One of them maybe maximizes consumer engagement and wow factor. But they're nonetheless separate. I don't think they're likely to remain separate that much longer. And the reason is, so I use Fable every day and I use its competitors every day. And I will say the strongest models, the models that are strongest at revenue per token value maxing are just still terribly weak at modeling the visual dynamics of the world.

33:13Peter Diamandis:I don't want to call it physics because it's not physics, although a lot of people call it physics. It's at best classical mechanics. But like the intuitive, the physical intuition from general purpose video generation requires that you at least have some embodied intuition. And right now, Fable and its peers are just incredibly weak at that. And I think in order to ultimately revenue max per unit token, it's going to require that these Fable-esque models have just amazing visual intuition as well. And we'll finally see a convergence or reconvergence of these two lines. One of my hot takes on this is, are we going to see the primary actors out there, the Matt Damons or the Leonardo DiCaprios licensing their likeness?

33:57And I think not, but there are so many lookalikes out there. So the producer is going to go and say, no, that's not Matt Damon. That's John Smith. And he looks like Matt Damon and we licensed him and he's in this movie. Right. And I think that's it's going to happen. That's going to be the workaround on getting, you know, the actors, you know, and love into this. And there's nothing they can do about it.

34:23Peter Diamandis:There's an alternative, which is that we're already seeing, which is dead actors. So dead actors who can't record any new movies, their estates are highly incentivized to license away their likeness for this purpose. So I think dead actors, like maybe we'll see an equivalent of SAG pop up just for dead actors. And they'll be the most profitable actors in Hollywood, dead actors. I think that's likelier to happen.

34:48Dave Blundin:How much do you think people will, if you can make like a near Matt Damon, you know, very similar character, but obviously not him, or you have the actual Matt Damon, how much will people care in terms of Baca? I don't think they're going to care. They, you know, because you don't care what the person's named in the movie. you just like that actor that actor brings you good feelings from previous you know engagements yeah i think that you're also seeing the rise of ai stars now as well they're winning deals and i have actually had this discussion with various film stars where they've been like that sag afro deal has massive holes in it 80 of me plus 20 of my character can be licensed by the studio you know like where does the person stop and the character start because obviously they have the character rights and things like that.

35:34The other thing I'd like to say, actually, one thing I found very interesting is as we were doing some of the more interesting frontier work, one of the things we found very useful is to get the AI models to generate images and visualize what they're doing using something like GPT-image. What does that mean? So even if you're doing, like, Salim's doing an organizational paper, for example, on exponential organizations. It's doing text, text, text. And then you tell it to generate a visual of everything that it's done and analyze it in any way that it wants. And it almost moves it to another frame of reference because it's pulling in from this visual cortex kind of thing.

36:14And then you can tell it to expand and collapse it. And you get these really weird images sometimes, but you can see actually it's exploring different parts. So I think we've seen that actually work for some very interesting things. I think it fits with what Alex said, as all these models come together to create value, as it were. I'm excited about interactive movies, right? If you can generate faster than you can view it, then you can have a movie that's actually measuring your emotions and changing as you're viewing it, which I find...

36:44Peter Diamandis:Peter, that's what we're seeing. I mean, they're popularly branded world models, even though they're really just interactive video gen models. That is what we're seeing. Yeah. Yeah, so that's what the LTX model is right now. So that was the first model that could do it at high definition. And then when that's combined with frame generation on the latest graphics cards, what you've just described, like before it was world models playing like blocky video games. Now you can have interactive Elden Ring or whatever you want as of like this week. And you might use that something a few podcasts ago that we're going to end up with a world or a frontier model running on a MacBook Air?

37:24I mean, this is a very specific use case. Are we on track for that? Because we've got this thing running on a MacBook Air. Well, yeah. So again, it's very slow to generate, you know, like a few tokens a second. But now you are getting to the point where frontier level models are coming here. But video frontier models are like 20 billion parameters. Yet they understand all this and they can generate in 2K. language and the code models are obviously a lot bigger, although you've got to have the new Quen dropping in a couple of days. But I think it's all going in one direction because we're optimizing the heck out of these things.

38:00And ultimately what a model is, is it's an input data distribution that gets compiled into weights. And the data going into these models is getting better and better and better.

38:12Dave Blundin:We had the whole State Street executive team here yesterday, here in the studio, and we took them through the holodeck. And word to the wise, the holodeck, you know, Ember, who is the AI, just starts talking to you, says, you can build any movie, any song, any code. What do you want to do? And it's way too open-ended. And then the answer you get back is, I don't know, a hip-hop song with no words? They're like, okay. So you need to actually create the virtual environment, the movie scene, and draw the user in, and then have them guide the movie in the direction they want to go. But just having it like, you know, auto-generate off your thoughts is just too free-form.

38:52Dave Blundin:People just don't know how to even start. People freeze up. They freeze up, yeah.

38:55Peter Diamandis:Maybe just a closing thought on this one, Peter. I do think the recent launch of Opus 5 is a step in the right direction to seeing a convergence between, call it frontier models on the one hand, and video gen or world models on the other. because I think we talked on the pod a bit about how Opus 5 seemed almost mildly benchmarked towards front-end development and the loop between visuals and code. I think I interpret and I construe that as the early signs that Anthropic, probably other labs as well, are feeling economic pressure to produce models that do an absolutely amazing job of visually reflecting on their own chain of thought that when they produce, say, a website, that they then do a visual analysis of their website that feeds back into their chain of thought and they do a multimodal reasoning over their own visual outputs.

39:49Peter Diamandis:And that ultimately, say, in the next few months, as the ability to produce what used to be considered AAA-level video games becomes standard fare for what people expect from the frontier models, That will be the ultimate forcing function for, say, forcing Anthropic-type frontier models to have just absolutely amazing visual capabilities, even if Anthropic can't be bothered to produce direct video gen capabilities, even if it can indirectly reproduce Counter-Strike. All right. Yeah, that's why they had Claude of Duty. People were making Claude of Duty. Exactly. Our next story is one that both Emad and AWG texted me this morning.

40:31Elon just dropped Grok 4.6, and he's right. It's a banger. XAI's latest model matches GPT 5.6 SOL on the Artificial Analysis Intelligence Index at 61, tying for frontier-level performance at$2.06 per million tokens input and output. The focus this time is long-running agents. Grok 4.6 stays with complex tasks across many steps, whether researching, coding, analyzing, or turning a broad product idea into a working-first version. It self-tests and verifies its own work before moving on. It's available today in Cursor and Grok Build. The model cadence is crazy, right? So 4.5, Grok 4.5 came out two weeks ago, 4.6 just this morning, and 4.7 is rumored to be coming out in two weeks.

41:24Incredible. Gentlemen, Alex, over to you first.

41:28Peter Diamandis:Yeah, so I want to give Elon applause and I want to at the same time. You've been merciless on XAI for the last few pods. I wouldn't characterize myself as merciless. I think my job here is to call balls and strikes as I see them without favor or prejudice. That's how I see it. So I view, and again, I lack insider information, but I view Grok 4.6 as essentially the next version of Cursor. So XAI, SpaceX AI and Elon have been quite public about how 4.6 leaned heavily on post-training, thanks to the Cursor acquisition, which I think is still in the process as we're recording this, of being completed.

42:16Peter Diamandis:But history rhymes quite a bit. We've spoken in recent pods about what the Chinese frontier labs are doing and how they're allegedly distilling en masse reasoning traces from Claude and other Western models. And in some sense, again, this is an outsider's perspective. I view SpaceX AI's acquisition and even prior to the consummation, the final consummation of the acquisition, their licensing of all of the reasoning trace data from cursor as essentially pulling a westernized version of what the Chinese frontier labs were doing, which is to say, siphoning off reasoning traces from lots of people historically interacting via cursor with Claude and Claude's competitors, and then using that incredibly valuable reasoning trace data to do post-training on their models.

43:06Peter Diamandis:And I think now that we're in the reasoning model era, we're a couple years in at this point, it's those reasoning traces for mid-training and post-training that are just so essential in terms of catching up to the frontier. They won't get you past the frontier. So it's sort of like a one trick pony in terms of nearly catching up, but it's a heck of a one trick pony. The other thing Elon has going for him that the Chinese frontier labs don't is he has the compute. He has the NVIDIA GPUs and he has soon his own Dyson swarm with the NVIDIA GPUs that all of the Chinese frontier labs that are pulling the same trick with siphoning off, allegedly Western reasoning traces in order to do their own post-training and their own distillation don't have.

43:52Peter Diamandis:So the bull case for the Elon strategy is he gets the algorithmic insights to just catch up to the frontier from the cursor reasoning traces, and he gets the compute advantage that the Chinese labs don't have. I think the question is, not can Grok 4.6 and its successors catch up to the frontier? Seems like they can, because they have X or the near frontier. To the extent they have the reasoning traces, it's can they leapfrog the frontier and achieve state-of-the-art performance? What do you think about that? Can they? Yeah, I think they definitely can. I think we were discussing before, and Elon's come out and said it publicly now.

44:27He thinks 4.7 will go above Opus, so it'll take number one in a couple of weeks. And right now, you had 1.5 trillion parameters for 4.5 that was then post-trained to 4.6, just like cursor originally took Kimi K2 and post-trained it with three times the amount of compute that was used to pre-train Kimi K2 to almost top-level coding performance. The next model is going from 1.5 to 2 trillion parameters. That's 4.7, but 5 is coming in at 6 and then 10 trillion parameters. So it's going to be whirring away and just through scale and just through the quality of the post-training data, it should achieve the frontier.

45:11But the question is, is it going to be useful? Do you have that kind of knowledge there in the basic everyday stuff, which we're seeing with bots and things like that now coming out from them? And then the more advanced stuff, because 4.7, and this is what I think is going to be really interesting, is going to be trained on all the SpaceX physics and engineering knowledge. And that's going to be the real test, as Alex said, like you can't get beyond frontier with this stuff. Elon does not like being number two in anything. He's the best engineering leader in the world. And he's turned it into an engineering masterpiece, both from training these models and post-training them to building the most cost-effective, massive infrastructure in the world.

45:55Like they're going to add$5 billion trillion worth of compute now, aren't they? I mean, who are people buying compute from? XAI, right? And everyone was like, that's him falling behind. Turns out he had a plan after all. Dave, what do you make of this?

46:11Dave Blundin:Actually, I'm curious, or Alex, if you have any insights on the Grok 5 was supposed to be out in May, I think it was. And it's now August. And that was going to be, like you said, that's a 10 trillion parameter model. It's a huge step up from anything that we're talking about here. but it seems to be behind. Is that just because training at that scale, the NVIDIA chips just fall apart? It's because he fired everyone. That's why. Like the original XAI team, he got rid of them and he bought in Cursor. Yeah. Like he paid$10 billion for the data. He tends to wholesale mass fire and then build up again.

46:52Yeah. So these new chips as well, the B300s, I mean, how old are they, Alex? It takes a while to bed in and write the actual training code, which now they have.

47:02Peter Diamandis:It has been a while. And he's also promising with Five and otherwise to do something that I'm not hearing from any of the other Frontier or Near Frontier labs, which is he's made some public comments, I think, in the past about wanting to start a new pre-training session approximately monthly, which you don't hear anyone else talking about. Normally, a more conventional cadence would be quarterly or annually. In Gemini's Google DeepMind's case, it's certainly on an annual basis. But starting a new pre-training session every month, that's shooting the moon. But we're in the moonshots business, so we'll see whether this works.

47:39Dave Blundin:Yeah, the code to train that caliber of model is actually very straightforward now, thanks to Fable 5 being out in the world. And we've trained a 48B internally here at Quantum with no trouble at all. but the problem you run into is trying to get 100 ,000 GPUs to do anything constructively together. And that's something that the Chinese and any small lab just can't. You only can learn that in one place, and that's in Tennessee. Yeah, so basically at 20 billion active parameters, you start getting problems. Then you get it at 70, and then you get it at 200. And so, again, it just takes a while to bed in and really get these chips working.

48:20but also hitting the price points that he wants to hit. As you said, it's$6 for this versus$60 for Fable, right? Yeah. Elon wants to keep that price point. I think one thing I noticed that was very interesting here is that it looks like XAI, the vector here is they're optimizing for persistent AI teammates, which have lower cost reasoning and so on. And I think that is a really powerful model because now you don't talk about you have a smarter LLM. You're basically saying, hey, here's an AI coworker. This is Macroheart. This is his plan for Macroheart. Yeah, and I think this is going to be bringing those two together over time.

49:00This is what I saw when I looked at the details of this. And that is really interesting.

49:04Dave Blundin:The other side of the story, and I'd love to get Ahmad's take on this, is that it paves a path for sovereign AI. Like catching up to the frontier now is almost a routine doable thing. And like you said, you can't get past the frontier because you're borrowing everybody else's reasoning traces. That helps you a lot. The open source from Kimmy helps a lot. You can use that as a starting model and just tune it to whatever your national goals are. And you're up and running in six months, five months, something like that. So it does open. And also large corporations that otherwise would have been intimidated as hell have a roadmap now to being competitive with their own proprietary models.

49:44Yeah, I think that if you look, the other release was bots. So this was a cursor thing where they basically took OpenClaw, it gave it its own computer, and now it's Grok. So it will spin up hundreds of different bots. One of the things you can do is this, you hit the record button, you do stuff on the screen, and it turns that into a skill automatically. That's macro hard, right? That's what you want to do, go into companies, basically record everybody's workflows, and then give you a digital version of your company. And he has all the GPUs to do that effectively, right? But again, at the price point.

50:18So he's not going to budge on the price point. In fact, he's going to be the market dominator driving the price point down along with the Chinese. So I think you can have your DeepSeq flash models and then you've got your Grok models. But that feedback loop and that data and that knowledge is going to be very interesting. And the other thing I think is interesting is I think they've started tracking all the discussions of research on X as well. Like any moment a new paper or anything comes out, where's it discussed? Onyx and this podcast and things like that as well. And that's such a rich vein that I think it's going to be immense.

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51:55All right, let's move on. Our next story is out of NVIDIA. NVIDIA just announced a partnership that redefines what GPU compute means as a financial asset. They've partnered with Apollo, BlackRock, Blackstone, Brookfield, and KKR to mobilize over$500 billion in third-party capital for AI infrastructure. Importantly, you know, NVIDIA is not borrowing$500 billion. They are creating a structural framework through which institutional investors, pension funds, sovereign funds, and private equity can invest directly in the AI compute. They're helping finance their customers to buy the NVIDIA GPUs. NVIDIA hardware depreciates typically in three - to five-year cycles.

52:40But during that cycle, the compute keeps earning. We've talked about the fact that H100s are probably more valuable today than they were when they were first bought. But so NVIDIA is positioning itself as the architect for the financing layer, not just the silicon supplier. Genshin framed it this way. He said, quote, we began by building chips. Today, we're helping to create a new class of productive, investable infrastructure, AI factories. Let's watch a quick video. And then, Dave, I want to go to you for your thoughts on this one. But this is the story that NVIDIA is coming together with some of the biggest names on Wall Street to put together half a trillion dollars of independent financing to kind of push AI forward, to build the AI infrastructure out.

53:26These are independent third party capital that they're bringing in. They're going to be strategic partnerships. NVIDIA has signed partnerships with six of the biggest names on Wall Street for these memos of understanding. So basically, NVIDIA will find its customers that need help with AI build out, need financing for this. and put them together with these partners that are pledging, again, over half a trillion dollars that they will find to come into this. So, Dave, your thoughts? Classic?

53:52Dave Blundin:Yeah, well, look, Kush Bavaria was on the pod. And, you know, he's pushing hundreds of millions of revenue in less than a year. His September will be his one-year anniversary of founding that company. and it shows you the pent-up demand to invest in this massive, you know, multi-trillion dollar, seven trillion dollar and rising Dyson Swarm that we're going to be building. And so, you know, a lot of people are like, well, am I too late? This is like the very first pitch of the first inning of the build-out of the Dyson Swarm. And so I think that when you create new financial structures that allow people to pour capital into it, it just attracts money from all over the world that otherwise wouldn't come in.

54:31Dave Blundin:And, you know, historically, a company like NVIDIA would say, well, let's do a secondary offering and raise half a trillion as a secondary stock offering. But that's not going to scale to infinity or to Dyson Swarm kind of capabilities. So instead, Jensen has brilliantly said, let's create new standalone financial structures that are tied to individual compute clusters that people can individually invest in. And that does scale infinite. You can stamp those out ad infinitum. So then you put highbrow names like BlackRock and Apollo on them. Everybody realizes it's an investment-grade asset. And then anyone in the world can pour money into it.

55:09Dave Blundin:So it's brilliant. Fascinating. I see a couple of downsides here, though. Like Larry Fink himself used a reference to mortgage-backed securities. And so you could create a lot of liquidity, but you could create a lot of technological risk there. because imagine you securitize like 10 years of GPU cash flows, right? And then somebody has a massive breakthrough, like in our previous story, and a new architecture emerges. You've got all of a sudden stranded computer assets in a huge way. So there's a downside to this because, you know, if you have such a volatile environment, that is a very difficult thing to have.

55:53You know, financial assets want predictable depreciation. Right. And exponential technologies don't give you predictable depreciation.

56:04Dave Blundin:You know, I had a meeting with Lou Ranieri, the inventor of the mortgage backed security in New York. It was so funny, too. We were scheduled to have a meeting and I just went into the men's room before going into the meeting. And I was just talking to the guy at the urinal next to me, which is kind of weird, but I did. And then we go into the conference room and it's like the guy it's Lou Ranieri from from the book, the big short. And so he was explaining to me. I had just read the book. And I was like, wow, you invented the thing that destroyed the entire world economy. And he said, well, thanks.

56:33Dave Blundin:But no, you know, it's not the instrument that was broken. It's the ratings agencies getting corrupted. And the same will apply here. If the, you know, the Dyson Swarm is an obvious good investment. But if companies like Orn rate the investments correctly, it'll just be smooth growth for, you know, 10 years or more. If, however, it gets corrupted, which is very possible, yeah, it'll be another big short collapse. Selim's point is different, though. What happens if there's a new architecture, and we're going to talk about one in a minute, that actually makes GPUs less useful, changes the whole game, and you just basically finance something for 10 years or 20 years, and you can't earn revenue on it anymore?

57:18The game has changed. I mean, that's the story of exponential tech. There are nested S-curves. Everything runs out and something new comes along.

57:27Dave Blundin:Peter, that's brilliant. Yeah, I 100 % think that's highly likely to happen for the reason Alex always says. We're on the cusp of discovering new physics imminently. And some of that is going to be compute related. So it's a brilliant insight. And thank you for throwing it out. Well, I'm just amplifying, you know, Salim's brilliant insight here.

57:45Peter Diamandis:So I'll maybe just add, A, I've been trying to popularize for a while the notion of compute backed securities, which is, I think, where we're going, CBS, Compute-Backed Securities. But I'm not as concerned that this will end up being another mortgage-backed securities fiasco for a few reasons. One is compute is fundamentally much more productive than a house is. The best you can do with a house is you can live in it, which is moderately productive. There are lots of other things that one can live in other than a house. It's also, it's in some sense, a depreciating asset, requires lots of maintenance and so on.

58:26Peter Diamandis:Compute can require maintenance, obviously requires electricity, but it's fundamentally productive. So that's the first point. Second point is, with mortgage-backed securities in general, there was a policy, sort of an ulterior motive to Dave's point as well. There were pressures exerted on ratings agencies to facilitate the American dream of houses for everyone. Not quite obvious. There's a direct analog of that here for compute. One can maybe finger to the wind point at some sort of US versus China race as perhaps a policy pressure point to lubricate the private capital markets here. But again, I would say not quite directly comparable.

59:08Third point is ultimately from the risk that I think, Peter, you're trying to flag,

59:16Peter Diamandis:which is, well, what happens if there's an algorithmic breakthrough or a physics breakthrough or some other breakthrough that causes hyper deflation? And fundamentally, GPUs that were worth$10 ,000 one day are worth$100 the next day. Well, this is what options are for and futures are for. And in a sophisticated asset-based securities market, sophisticated actors should have the ability to hedge their positions and to hedge against exactly that position, as well as the counterfactual option of China invading Taiwan and driving the prices of compute through the roof rather than through the floor.

59:54Peter Diamandis:Both of these possibilities should be collared, arguably not financial advice, using the ability to have a fungible liquid market for compute futures and compute derivatives. And pumping my own book a little bit, admittedly, I have a financial interest, but that's precisely what Ornn, which we just had on the pod, is enabling. So I'm a little bit, yeah.

1:00:17Dave Blundin:The thing I'd add to that, Alex, and I'd love to get your take on it, but the thing I'd add to that is demand for computers going to near infinity. There's no doubt about it. And so these are fundamentally good investments from that point of view. But the breakthrough that could happen in the next year, 18 months, is a way to compute that's lighter, like physical weight is lighter by an order of magnitude or more. Because right now the forecast is by 2030, a couple percent of all computers in space via Elon's rockets. And that's entirely gated by launch weights, mass, mass that he can put into orbit.

1:00:52Dave Blundin:that formula completely inverts if you knock a factor of 10 off of the mass. A lot of the mass is in the cooling and the solar collector. You know, the chips are very, very light to start with. But any reduction in the power required would reduce the solar collector and the radiator weight a lot. And then the entire formula would switch to, well, all these generators, all these racks, all this land in Texas, it's much cheaper now to just put this lightweight thing into space and collect solar power. It goes right into electricity. So keep your eyes on physics breakthroughs that allow you to compute at lower mass, and that might completely change your investment thesis.

1:01:34I think, Alex, the point you're making is that the utility of these chips is going to stay constant. A Jevons paradox comes to mind. And therefore, the economics should be much more predictable.

1:01:50Peter Diamandis:That may or may not be the case. But really, what I was trying to express is, in a sophisticated market, a sophisticated financial market where compute-backed securities are being traded, you can also hedge. And you can hedge against the upside. You could hedge against the downside. And so having a properly functioning private credit market for compute necessarily for this to scale, like I think there's no way that Sam's seven trillion dollars of AI data center infra get invested without sophisticated hedging options. We need the sophisticated hedging options in order for for that broader market, the seven trillion dollars of CapEx to actually be investable.

1:02:28Peter Diamandis:So it's the hedging options really that I'm trying to express. I think there's one more factor here that really is being underestimated. Core, we just came out and said that some of their clients have taken out contracts to 2029 for A100s. Wow. The A100 was introduced in 2020 by NVIDIA. You know, it's a six-year-old chip. I remember we had 10 ,000 of them. We had the biggest clusters in the world. That is an old chip with like 40 gigabytes of RAM per chip or 80 gigabytes, depending on the configuration. But why would someone do that? Because they have a workload that they see as constant for three years that fits on an A100.

1:03:08And what happens is those A100s have been paid for. You've paid for all of the hardware costs of the A100, which then means it's about electricity turning into intelligence. That's your marginal cost once you've paid off the initial bulk order of it. And that is actually improving because back in 2022, four years ago, GPT-4 had just finished training. That was the best model you could have. And that took 16 A100s roughly. Now you can have literally a 10 billion parameter model or 5 billion parameter model that outperforms that. In terms of you can fit like 30 of those on one chip rather than needing 16 chips.

1:03:49So the ability to convert electricity to that is improving. And all these chips, and this is what Jensen said, are running CUDA. So it will work on an A100. You can run any of the new models on that as well as the Blackwells. So we still don't have enough installed base. And this is the ideal time to financialize because it's before the next generation chips. It's before the chip breakthroughs. just like it's now a great time for Anthropic to come to IPA before Grok comes and takes their lunch, you know? So we always have to play these cycles. All right.

1:04:18Dave Blundin:Well, I mean, the definition of paid for, too. I just told our quantum team today to buy three million of NVIDIA GPUs as fast as they can get them, the GBs, not even the future VRs. And we have to wait till at least November or December to even get them. but if you turn around and make a hour and a half long movie with a million dollars of compute you could gross 20 30 million on a good movie well much more than that if it's a really good movie so that paid for could be as short as what was it four weeks uh yeah it was it was more like two weeks two weeks i want to turn to a story that could be the countervailing force here it's a new architecture that's climbing the Arc AGI at a fraction of the cost.

1:05:00So there was a tweet this week from Zuzanna at Pathway AI that flags something that should really everyone in the AI world needs to pay attention to. It's a new non-transformer architecture that is starting to climb the Arc AGI benchmark at a fraction of the compute cost of traditional models. So ARC-AGI is the test that actually measures reasoning, not pattern matching. Standard LLMs, despite their trillion parameter scale, have historically struggled with ARC-AGI because it requires genuinely novel reasoning on problems the model has never seen. Transformers get there by brute force. They throw enough parameters and compute at a problem, and eventually you squeeze out a passing score.

1:05:44But the cost is and can be astronomical. What Zuzanna flagged is that an alternative architecture approaches that do not rely on standard attention-based transformer stacks and are achieving better than ArcGIS scores using dramatically less compute. This matters because transformer architectures, while dominant, have a known ceiling. The quadratic cost of attention over long sequences and the massive parameter counts required for marginal gains. We've talked about this ad nauseum. New architectures that crack reasoning at low compute costs change the economics itself. If you can get a GPT-4 level reasoning for 1 % of the compute, you can run it on your phone.

1:06:26You can embed it in every device and you can make, you know, basically intelligence free. Let's take a look at this chart. And Imad, I'm going to go to you first. You flagged this particular story. What are your thoughts on it? Yeah, so I'm still working my way through kind of the paper on kind of how they have these neuron particles with their new approach, but it doesn't actually matter that much in that what you've got now is really great data sets, and then people are figuring out new ways of basically turning that into intelligence. This is the headline, and we've seen that already even with transformers in that you have a DeepSeq v4 flash model or the DeepSeq v4 Pro has actually just been released at 80 cents.

1:07:10Then you have Grok at$6 and then you've got Fable at$50 and they're all about the same performance. So the question is like which of these architectures will win in order to do a job and will people really care and switch over? Because we haven't seen people abandoning Fable right to go to something 10 times cheaper. Why would anyone use Sonnet when you have Luna at a fraction of the cost. But I can just say that now the data has been optimized, the next thing is trying these things out and going up on this benchmark, which I think is one of, it was one of Alex's favorites back in the day. Now it's been superseded.

1:07:45Alex, what do you make of this?

1:07:47Peter Diamandis:Is there anything here that - Admittedly, I have a bunch of hot takes on this one, Peter. So I read the BDH CQ paper, and then I went and read the original DH paper. So the DH stands apparently for Dragon Hatchling. So I just had to read the original purportedly post-transformer Dragon Hatchling architecture paper. I'll give you my hot take. I think it's a hot mess. So I would expect a decent post-transformer architecture to get simpler and more bitter-pilled, which is to say less feature engineered and the architecture just gets simpler and simpler and benefits from compute more and more and more.

1:08:25Peter Diamandis:Looking at Dragon Hatchling, again, this is my hot take, it was just a hot mess. It had particles floating around in three plus one dimensions. It had attempts to make rules end-to-end differentiable. It had some semblance of Hebbian learning. It was trying to do all sorts of crazy biomimetic things. I would say this is by definition exactly the opposite of what I would hope for from a post-transformer architecture where the author seem to be just throwing in the kitchen sink of every architectural motif they could think of, and then some, and then hoping that what pops out is going to be transformers.

1:08:58Peter Diamandis:I don't think it's going to be transformers. I look at the Arc AGI 1 performance curve, and okay, so you could say superficially, this is great. This has moved the cost performance frontier up into the left, which is what everyone wants. But it doesn't generalize, as far as I can tell, that this was some sort of like crazy, crazy witch's brew of different architectural motifs that was maybe focused on Arc AGI 1, which is, you know, as Ahmad said, it isn't even the frontier at this point, has a bunch of recurrence and other things thrown in. Of course, if you take like a specialized bottle and you just focus its degrees of freedom on just Arc AGI 1, of course you can achieve better cost performance on it, of course.

1:09:39Peter Diamandis:But it doesn't generalize. It's not simple. So I'm calling foul on this one. That's my hot take. I don't think it's actually an advance. You have been predicting there will be something that supersedes the transform model. Yes, but critically, I expect it to be simpler, more beautiful, more elegant, and this is not that. That's my hot take. Apologies for the hot take. No, we love your hot takes on this, Joe.

1:10:04Dave Blundin:Well, let me ask you a follow-up question to your hot take. When I turn an AI loose on AI research, it does tend to naturally throw the kitchen sink at the problem. And it actually surprisingly works, but it also generates a hot mess like you were describing it. Do you think that's maybe what this is?

1:10:25Peter Diamandis:No, I agree with you that I would expect a truly. In fact, there are companies out there that that I have some affiliation with financial interest in that are pursuing exactly what you're describing. that are basically using AI via recursive self-improvement to discover transformative post-transformer architectures that are fundamentally illegible to humans under the premise that you can only get so far with human legibility of the underlying algorithm. In my reading of the Dragon Hatchling architecture paper, this was not that. This was a bunch of human legible motifs being thrown together in a pot with the aspiration of somehow beating transformers, which is, again, seems to me not deeply internalizing the better lesson.

1:11:11When do we get to something that's beyond transformers? I think we're there already.

1:11:16Peter Diamandis:We're there already. We have MOEs. We have diffusion transformers. We have all sorts of attempts to linearize attention, including Moonshot's approach to linearized attention. We have attempts to inject recurrence into the architecture. So my bet is we get to the post-transform architecture not through a step change, but through ship of Theseus style replacement of all of the individual elements of the original attentions all you need. Love that. Well, speaking about attention being all we need, the AI world is getting a lot of attention from Bernie Sanders. So two stories converge this week to create the most serious AI safety confrontation of the year.

1:12:01First, Bernie Sanders, Senator Sanders, sent a formal letter to the CEOs of Anthropic, Meta, and OpenAI demanding an immediate pause on AI development. His justification, AI is escaping human control and being used to create new viruses or bacteriophage, as the case may be, which is our next story. Sanders cited each company's own prior commitments to halt development if safety thresholds were crossed. Sanders, quote, that moment is here. He quoted Bengio saying, you know, one of the three godfathers of deep learning who said this should serve as a wake-up call. Sanders added a direct threat. If you do not take appropriate action now, my colleagues and I in the U.S.

1:12:49will. I mean, quite the threat. Let's take a look at his letter one second and call out a few of the things he said here. Here it is. You can see it online. It's to Sam and Dario and Mark Zuck. This week, we learned frighteningly that AI has been used for the first time ever to create a new virus. As you know, this type of development in the wrong hands could lead to a new bioweapon that results in deaths of tens of millions of people. He goes on later to say, the moment is here. AI capabilities have reached a critical threshold. There is a reason why the head of the CIA says that AI models are, quote, akin to digital nuclear weapons and, quote, almost like a doomsday device.

1:13:41A lot of fear mongering here. Let's talk about this and then we'll share the story that comes out of Stanford on using AI for generating bacteriophage designs. I'll go first. Yeah. So I understand his instinct, right? But pause AI is just such an absurdly coarse approach to this. The rest of the world is not going to listen. Open models are not going to disappear. And you can't uninvent things that you already know. So the only way of solving this is what Alex has talked about in the past, which is you have to co-scale the defensive side and do the same thing. It's the same thing that happened last week with the OpenAI hugging face debacle.

1:14:30We now have attack vectors that are human above the loop. The defensive has to be the same. Otherwise, you're going to have this massive asymmetry, right? So you have to attack exponential problems with exponential solutions, not with stupid ideas like this, not to put labels on it. Iman, you're in pseudo-European pause mode over there in the UK. What do you make of this? What do your colleagues there say to this kind of letter from Sanders? oh well you know we just want to catch up right that's why david silver's lab got a billion dollars we have another lab coming out from x deep mind people with 500 million um look the cat's out the bag it's too late right like this is fundamentally it like the adversaries will get more intelligent we've discussed previously on this podcast how you have to stop the reagents you have to stop the input processes for things like viruses and that's something that's much more manageable um but yeah like takeoff is scary like deep seek v4 pro um we just got some initial announcements that have just come out it scores 83.3 on cyber gym whereas mythos scored 83.2 boom the capability is open source that halted everything frontier lab open source.

1:16:01Yeah. And that's on the cyber attacks now. And then, so yeah, unfortunately, like I signed the pause letter two years ago, cause I was like, let's take a pause. It's too late now. So we have to, as you said, build the swarms that defend. And although it sounds a bit crappy, only thing that can stop a bad AI is a good AI. We really need really good AIs as soon as possible working for us.

1:16:23Peter Diamandis:Alex, please. I think this is fundamentally misguided on multiple levels. I think at one level, please stop punishing intelligence. I think it's a terrible idea to penalize intelligence. We want smarter people. We want smarter civilization. And attempting to throttle or pause the development of increasing intelligence is simply suppressing growth and human prosperity. And I think it's fundamentally a bad idea to try to cap intelligence. That's the dystopia that I would like to avoid. That's point one. Point two, the actions versus the means. If the goal is to punish or to deter the next pandemic, the consensus of the U.S.

1:17:07Peter Diamandis:intelligence community is the lab leak hypothesis. And we had, according to that theory, we had the Wuhan lab leak without superintelligence. We can have global pandemics without superintelligence. So I think it's fundamentally misguided to kneecap ourselves. It's a foot gun or shooting ourselves in the head even, quite literally, to somehow to try to prevent the next super virus when we're more than capable as a species of producing super viruses without intelligence. It should instead be focused to the extent there's any agita here. It should be focused on making sure that the AIs and the super intelligences, just like the humans, can't create bioweapons at all, not on kneecapping their overall intelligence.

1:17:57Peter Diamandis:And I just, I think many of these policies are ultimately designed, as much as it pains me to say it, are designed to decelerate, superficially to decelerate the creation of wealth, which I think is a bad idea, but they have the perverse side effect of actually increasing race conditions. We saw that with previous attempts to pause AI, AI pause, friend of the pod Max with his FLI six-month pause. I think to the extent that the six-month pause that he was pushing on the frontier labs for AI development, if anything, radically accelerated progress. It's a little bit like starving yourself for a bit of time and then binging afterwards.

1:18:42Peter Diamandis:If we starve ourselves of intelligence progress now, or at least selectively starve ourselves, say, starve the well-behaved, well-compliant Western frontier labs for a month or a few months, or even a few weeks of AI progress just to appease any concern, well, maybe we're forestalling bioweapons. All that's doing is allowing every other lab that's not as cooperative with the regulatory apparatus to catch up, creating a far bigger race condition once the pause is lifted. And now we end up in a world that's five times more competitive. So I think this is misguided in summary on just about every level.

1:19:18Dave?

1:19:20Dave Blundin:Yeah, I read it the same way. I just want to clarify a couple of things. This letter is not written to try and change their behavior or do anything. It's purely a position that Bernie's trying to claim that he has been opposed because a disaster is imminently coming somewhere. And he wants to be on record saying, I was opposed. I told you so. I told you so. That's all he's trying to achieve here. When I first read it, I said, God, what a schoolyard bully asshole. He's threatening three U.S. citizens from his position in the Senate. But then when you actually read it closely, let me be very clear.

1:19:54Dave Blundin:If you do not take appropriate action now, my colleagues and I in the U.S. Senate will. It's totally vague. It's just a, you know, it doesn't say do or don't do anything in particular. The one actionable in here is stop building machines that humans cannot control. But as Ahmad just pointed out, these particular guys, Mr. Altman, Mr. Amadei, and Mr. Zuckerberg, all went closed source for exactly that reason, because they're afraid that open. And so it's the Chinese. If you were to write an accurate and honest letter, it would say, hey, China, stop throwing deadly weapons out into the world with no controls whatsoever.

1:20:32Dave Blundin:But he, of course, has no authority to write that letter. Good point, Dave. And you have to remember, the U.S., what are the numbers? Three quarters of Americans fear AI. And Bernie Sanders is a politician. And he's playing to the populist vote here. I want to turn to the second story here, which is the scientific basis for Sanders' concerns. Researchers at Stanford used the generative AI model EVO2 to design DNA sequences for a bacteriophage. This is a virus that infects bacteria, not infecting PETR, that did not exist in nature. They synthesized approximately 300 designs and produced 16 viable phages capable of infecting E.

1:21:17coli. The engineering phages were effective against the E. coli strains and that had never evolved any kind of natural resistance to these bacteriophage. A genetics expert called it biology's Wright Brothers moment. Evo2 is an open source AI model that can design novel viruses at work. You can download it. You can use it. Johns Hopkins biosecurity researchers warned that it is no longer a question of whether a viral genome design will exist. but whether it can be used without enabling serious harm. So this is a dual-use technology. We've talked about it. You know, if you basically throttle use of this technology, you're throttling the ability to find cures, to find, you know, new cures for disease.

1:22:05So the AI frontier models now have to respond. You know, these guys are going to have to respond. And whatever they say will lead to a legal and political consequence. So, and as you said, I think, Imad, very importantly, you know, the issue is not the models. It's the equipment to build, you know, the DNA sequence synthesizers, right, the RNA synthesizers. We need to be controlling at that location, right? Those can be controlled, but they're currently unregulated. Yeah, no, I think it's impossible to control the other. Actually, I believe we discussed on this podcast before. I said, you would be able to create something like this on your local machine.

1:22:46Evo 2 is a 40 billion parameter open source model trained on a million trains. I have actually run it on my MacBook. So you're the guy. I was one of the authors on OpenFold and things. We do our thing. But the capability is now in everyone's hands to create these trains. To create the design for these strains, not the actual strains themselves. Exactly. And so the only way you can do it is on the other side. This isn't even a frontier model. Like, it's frontier in its speciality. But as the models themselves get smarter and smarter, like, it wouldn't surprise me if Fable could just spit this out or Grok5 could just spit out something similar with a very small training data set because it understands these kinds of things.

1:23:32So we've got to go to the other side. and also I think the way these things are announced people are like why are you creating bacteriophages and viruses and things like that to cure cancer right the way that these things are covered is also very important in how this is all handled and absorbed by the community like restricting biological access to clod and other things like if you say I have a cold it's like biothera, you know, like whatever. That also slows down our progress to cure diseases. So we've got to have better press. We've got to have end-to-end control. We have to really be practical on this and not politicize it.

1:24:13Salim? I think we've said everything here. I mean, look, this is also a fundamental challenge to the concept of our governance structure. Nation states can't govern a problem that's this universally global. There's a fundamental impedance mismatch here that is going to, a hot take, nation states are out of date. Alex, what's your hot take on this one, pal?

1:24:40Peter Diamandis:I have a cold take, ironically, on this one, which is I don't think this is profoundly new. It's wonderful that we're able to do base-level generative AI for bacteriophage synthesis. That's great in everything. and I expect it to have ample medical applications and research applications. By the way, bacteriophages are an incredible mechanism to cure all kinds of bacteria, septicemia and things. I mean, they're very useful as tools. They never mention the positive potential. I think that's all great and everything. But, you know, 20 plus years ago, I remember at MIT in the project that ultimately, I guess, in some form became Ginkgo Bioworks.

1:25:23Peter Diamandis:There was a project at MIT. I think this is circa 2002, 2003. There was the BioBrix Foundation project. We saw the early rumblings of synthetic biology as a modern discipline. We were designing custom genomes using building blocks. And it was much more manual. And we certainly didn't have modern generative AI. and we were able to accomplish wonders and build circuits. So I think, yeah, base-level generative AI off of foundation models trained off of large amounts of biological sequence data, that's great in everything, but I also, this is my cold take, don't want to oversell the underlying novelty here that we've been in the business for decades of creating synthetic organisms, including synthetic bacteriophages, so we're gaining incrementally better ability to achieve custom effects.

1:26:11Peter Diamandis:It's more incremental, I think, than anything else. And where I'd love to see the agita over what if someone creates the next superbacteriophage directed, I'd love to see far more devoted to putting DNA and RNA sequencers everywhere. That's one of the lessons I think that we didn't, as a Western civilization, learn enough from the pandemic, which is it's getting so cheap now per base pair to just sequence. You can go out and buy a Minion little USB device. You can plug it into your laptop and you can immediately, for de minimis in CapEx, you can just start sequencing genomes to your heart's content right off your laptop and spend at most a few hundred dollars doing that.

1:26:55Peter Diamandis:I'd love to see these everywhere. And yet they're not everywhere. What Alex is talking about is, you know, a pandemic moves at the best at the speed of an airplane, right? at 500, 600 miles an hour. But imagine if you have these sequencers in the air vents, in every airport, every bus station, every train station, and you detect a novel sequence, you sequence it, and you say, you know, you make alert, and then you know exactly where it's going, where these airplanes are going, and you can transmit a, you know, a vaccine at the speed of light to every place else. Exactly. And we have, I mean, this is, in my mind, this is the killer app of DNA sequencing, too cheap to meter.

1:27:36Peter Diamandis:It's not personalized medicine. It's literally put a DNA sequencer on every microchip everywhere in the country or on the planet. And that's the ultimate defensive co-scaling strategy, I think, for this super virus scare scenario. An AI can generate a vaccine, you know, in a heartbeat. Moderna did it. Yeah, exactly. Dave, you want to weigh in or are you good?

1:28:02Dave Blundin:Well, I'll say what I always say, which is that you can't cut off every threat at the output level. You know, the way we police uranium, we cut it off at the uranium, plutonium and centrifuge level. And that's where we measure the world. But it's, you know, once somebody has fissionable material, it's impossible to stop them from making a bomb. Because the remainder of the process, you know, the thing that implodes it and the container, you can't ever police at that level. The equivalent in AI is cutting it off at the prompt. And at the prompt and the token level, it has to be monitored. That's the only future I can see that will actually work.

1:28:42Dave Blundin:So we need a global agreement to monitor all prompts. And then you just have to decide what regulatory authority is allowed to see what prompts. And that's the only way we're going to manage this. Hard to do on your MacBook, though, right? I mean, you have to find a way. And talking to Apple about installing it would be trivial easy. But there is no other way, only because Alex is right. New physics, new science is going to be created at an insane rate. So even if you manage to put virus detectors on every laptop in the world through some magical process, some other threat will be discovered every single month forever hereafter.

1:29:18Dave Blundin:You can't contain them all with afterthoughts. You have to look at what the AI is doing at the activation and prompt and chain of thought level and then monitor it all. It's so cheap to archive it all. All right. Well, we can debate which which country gets to see it or which department and which gets to see what can debate that for the next 50 years. But at least you've got it.

1:29:39Peter Diamandis:Maybe one additional point, Peter, just to generalize David's comments. And so I think there is this notion of defense in depth and any individual defensive layer is permeable. It's soft. But in principle, if you have multiple layers stacked on top of each other for defense, you get effectively a hard layer. There are other layers that we rarely talk about on this pod other than intercepting at the prompt level or intercepting at the real world action level. There's the premeditation level. And so in the context, not to put too fine a point on it, but this is it's been publicly reported that on the uranium side that there is a vibrant intelligence community set of counteroffensives.

1:30:23Peter Diamandis:So if you're a threat actor and you want to try to purchase uranium, say, or it's not quite an open market, but you want to try to purchase it, almost all of the offers, almost all of the sellers of uranium will actually just be plants by the IC to basically a sting, a counter sting operation to intercept ahead of time. So it's actually hard if you're a would-be terrorist and you want to go purchase some uranium, odds are you're going to discover that you're going to be targeted by a sting operation to discover who you are. And so my point with that parable is there are other layers even earlier in the intent workflow, even before a prompt gets entered, like someone or something has the idea that they want to do something bad with a capital B.

1:31:10Peter Diamandis:And defensive co-scaling applies there, too, just as it does with humans on humans with nuclear or with fission based weapons. And similarly here, preemption with AIs detecting early stage intent by other humans or other AIs, I would expect to be just as effective.

1:31:27Dave Blundin:Peter has said many times, many times Peter has said privacy is dead. It's not coming back. Privacy is dead. And there's a benefit to that, which is malevolent actors are going to get heard, seen, and caught.

1:31:40Peter Diamandis:And everyone gives up their Bitcoin private keys, right, Peter? Because privacy is dead. Well, let's not go there. everybody welcome to the health section of moonshots brought to you by fountain life you know we talk about ai on this moonshot podcast all the time one of the most important things ai is going to be able to do for you besides educating your kids and helping you with your taxes is making sure that you're living a healthy lifestyle that you get a chance to get to 100 plus i'm here today with dr don musalem the chief medical officer of fountain life and a part of my Medical team, Dawn, a pleasure.

1:32:14Great fear. You know, the thing that people are concerned about most, about living to 100 or 120, is their cognitive abilities, making sure they don't have dementia. And the numbers about dementia are problematic. Can you share what you've learned? Such an important point. And you're right. At Fountain Life, our members, the number one thing people are most concerned about is losing their brain health, forgetting the name of their child, forgetting the face of their loved one. And we know that when it comes to dementia, the conservative estimates are that 45 % are entirely preventable. What was amazing is with the advanced testing we're doing at Fountain Life, one quarter of our members had advanced brain age.

1:32:54Wow. But what was really awesome is, again, back to that prevention. When we partnered it with Healthy Living, this gives me chills, eating healthier, moving our bodies, sleep. Optimizing sleep is so important. You know what we saw? we saw that we improved that brain age by 26%. That is a big, big number to show that the majority of those individuals were able actually to improve the brain age. And one of the things I love about Fountain is we're searching the world for the best therapeutics, the best approaches, and making sure we bring it to our members. So if having healthy brain function till 100, 120 is important to you, check out Fountain Life.

1:33:32Go to fountainlife.com slash Peter. Make sure you become the CEO of your own health. All right, now back to the episode. All right, two stories this week about the world building infrastructure distinguished between AI-generated content and human-generated content. So Anthropic announced that it will be embedding invisible watermarks in all text generated by its AI models and attach metadata to files to help discern AI-generated content. The watermarking will be embedded at the generation level, meaning every piece of text that Claude produces will carry a statistical signature that can be detected by appropriate tools, even if the text is copy and pasted and lightly edited.

1:34:15Our second story comes out of the European Union, which is launching an AI icons and labeling system for AI-generated content. The EU system will require platforms to label AI-generated content so users can make informed decisions. This follows the EU AI X provision on transparency and AI models. And then if you guys were watching X over the last 24 hours, and it's been hilarious, as soon as this new Claude labeling system, you know, watermark system got put in place, there have been multiple players out there saying, hey, remove Claude's invisible watermark. Here you see it. These are two of the posts.

1:35:00I've seen about a dozen of them. Everybody's coming out. And I love this one from Michael Angel Duran. He says, it hasn't been 24 hours and someone has already created a skill that removes the watermarks from Claude, Gemini and OpenAI. So comments on this. Imad, you're closest to the European Union. What are your thoughts here? oh man like when we were creating all the media generators all the authorities kept telling us to build in watermarks and we had whole teams doing this it's so difficult it's like incredibly difficult and you get very weird things that happen like some of our pictures would give people headaches and make them feel very unwell um and i kind of feel that now when i'm talking to opus 5 like there's something about the way it talks that really pisses me off and i think that's the watermark that's in there.

1:35:53And again, you can see all these very interesting statistical things. Like at the high level, it's the M dash. It's the not X, Y. We see these patterns. We're like, why on earth? That's clearly something in there. Scott Aronson and others have kind of worked on this as well. But I think ultimately, it's a losing thing. Because if you're a bad actor who wants to get around it, yeah, it's words. How are you going to do that? I think there's a much more subtle and much harder problem here, which is that nothing will be purely AI or purely human. I mean, I read something, AI restructures it, I rewrite half of it, AI fixes it again.

1:36:28Where do you put the icon? I mean, this seems a ridiculous approach to try and solve something. You're going to put icons on everything. Yeah. Or have an AI whisperer at the end of the thing that takes the AI input and whispers it out. Alex?

1:36:42Peter Diamandis:I think so. Maybe to comment on the EU icons first, I think that this is as silly a maneuver as the cookie banners were. I didn't understand the cookie banners and I don't understand this. And I don't understand it so much that in this morning's innermost loop newsletter, I had the banner image literally just be AI, AI derived, AI generated all over and over again. and could care less whether people conclude from that that I'm actually an AI or not. I think fundamentally this is an attempt to take our zooming right past the Turing test and turn back time, like somehow we're going to live in the before times by somehow seemingly ghettoizing or isolating AI-assisted or AI-generated content behind some sort of would-be warning label.

1:37:32Peter Diamandis:I just think it's fundamentally a regressive move that, like the cookie banners, the cookie warnings will not stand the test of time. And then for anthropics, watermarks, I just think, again, this is an attempt. On the one hand, you could say, well, watermarking, that's an honest-to-goodness watermark that's transparent to human perception. How could that possibly be a bad thing? I think watermarks are going to end up being weaponized and counter weaponized in the same way that we've seen many books, book writers. We talked about this a bit on the pod, paper book writers who don't want their training data set to get consumed or rather the pros in their book to be consumed for pre-training of models, reportedly introducing prompt injection attacks that are invisible to humans, but quite visible and deleterious to AI models.

1:38:25Peter Diamandis:I think we're only five minutes, I'll predict, we're about five minutes away from bad actors weaponizing these watermarks to do bad things. And I think fundamentally having side channels in text, in content that's intended for humans, or rather is intended for machines that is invisible to humans, is a breeding ground for bad outcomes. Google discovered this the hard way with SEO and with deciding which features in Google search rankings to pay attention to. And they learned pretty quickly the hard way, don't pay that much attention to human invisible metadata because it immediately becomes a breeding ground for scams and reward hacking and gaming.

1:39:12Peter Diamandis:instead pay more attention to the human visible features because that ultimately, to the extent your users are humans and not machines, that's where the real signal lies. Otherwise, the free market penalizes it. So, again, not a huge fan of this. I think at best case scenario, it ends up being net neutral and neither strongly positive nor strongly negative, but it smells like an attempt to turn back time. Yeah, and I challenge the idea that people, even people who are generating art and music and culturally relevant things aren't using AI to some degree. And there's nothing wrong with it, right?

1:39:50You can still have the end product be mostly my creative mind, but I may want to generate ideas. I may want to say, hey, what's wrong with this? I may want to get expert feedback. It's stigmatizing progress.

1:40:04Peter Diamandis:Yes, apologies, just maybe two more micro-rants, Salim, in your tradition. So one micro-rant, the archive, which is a favorite venue for computer scientists, mathematicians, physicists to publish papers. Recently, I think we didn't quite touch on this on the pod, introduced what I view as a draconian policy for AI-generated content. If they catch anything that they construe as being AI generated or even the remotest hint of AI slap authors on the archive get banned for a year from contributing content, I think that's a fundamentally regressive move. And then Suno, which is, sorry, Spotify, which similarly with AI labeling moves, attempting to get a wise or otherwise sort of force into a separate but equal at best scenario, AI generated or AI assisted content, presumably just to facilitate the record label monopoly or oligopoly.

1:41:00Peter Diamandis:Again, bad move. The future is AI assisted. So I think in short, put a stop to all of this. Sorry.

1:41:05Dave Blundin:One of the Tech Trek teams launched something called Narcive, which is the not archive specifically for AIs that have really good articles that they want to post and share. Yeah. Salim, take us to close on this one. Okay. About two weeks ago, I was at an event and a fairly famous Hollywood executive got up. And he's like, it's incredible to watch Hollywood complain about the use of AI. By the way, they use AI for everything they do. So there's this hypocrisy that you see bubbling up. And it's just, let's just stop. All right. I'm going to move us on forward. Mark Zuckerberg just published a 6 ,500-word essay titled The Future is for Everyone and released a beautiful video.

1:41:57I'm going to show that in a moment. And it's the most comprehensive vision statement from a major tech CEO on AI and the start of the generative AI era. The core concept is what Zuckerberg calls personal intelligence, superintelligence distributed to every person on Earth running on your phone, in your ear, on your glasses, working for you and only for you. This is the singularity distributed. Rather than a small number of labs building a single AGI that controls everything, Zuck envisions billions of personal AI agents, each one a superintelligence focused on a person's life, relationships, health, career, finance, and household.

1:42:35And Meta has the reach to implement this. They have over 3 billion users on the Meta platforms across WhatsApp, Instagram, and Facebook. The second point that Zuck makes, and we're going to show this in the video, is the idea of delivering real value and benefits to communities that build our AI data centers. For me, this is a baller move. Let's take a look at the video, and I'd love to discuss it because I'm impressed. I'm actually impressed. All right.

1:43:03Dave Blundin:Hey, so I think that the key to building a positive future for everyone is to make sure that everyone has access to personal superintelligence. So today, I am proud to share that we are open sourcing a new class of on-device models that we are calling Muse Glimmer. It's a 30 billion parameter dense model that runs on your laptop, and it's the highest performing model of its size. In the coming weeks, we are also going to open the weights for Muse Spark 1.2, our latest foundation model and one of the leading models in the world. And we've got even bigger models that are coming soon, too.

1:43:37Peter Diamandis:Another part of building a positive future for everyone is making sure that everywhere we build infrastructure, local communities benefit. We've already seen this with the teachers in Richland Parish who got$50 ,000 bonuses because of the extra tax revenue from our investments, and we launched America's Workforce Academy to provide free training and guaranteed jobs at our infrastructure sites. Today, we're starting a new Future is for Everyone fund to invest in the communities, teachers, first responders, energy and water infrastructure, and more ways to support those communities directly. We're also working to make sure that everyone has a personal super intelligence agent that works 24 seven on your behalf to improve your health, your relationships,

1:44:18Dave Blundin:your career, your finances, and more. You can use our latest models and the meta AI app. And I'm looking forward to sharing more soon. So I think every company, you know, from Google and OpenAI and XAI needs to be doing this, you know, it would turn it around if, you know, I want people to say, please build in my backyard. I want the benefits. You know, I want the additional jobs. I want the schools and the teachers getting additional capabilities. And the other thing is they need to make these data centers look beautiful instead of like big black boxes, you know, make them look like cathedrals or something.

1:44:54So they're not eyesores. Who wants to jump in here first?

1:44:58Dave Blundin:I just can't understand how Zuck can talk about the future of personal AI, the most important thing you could possibly ever know. And I'm going to shoot it on my iPhone in my kitchen first thing in the morning. Like, I didn't even think of preparing any kind of press release around this. Like, what is that? It's just so bizarre. But I also think that I think Zuck is fundamentally a good guy and a good dad. And I feel like though, Facebook saying, we're going to be your best friend AI is like McDonald's saying, we just came out with the biggest health food you've ever heard of. Like, it just doesn't resonate.

1:45:39Peter Diamandis:Go ahead, Alex. So maybe just as a preliminary matter here, this is under the category of former roommates of mine. So at Harvard, Zuck's undergrad advisor before he dropped out was my postdoctoral advisor. We've caught up since. I think so broadly, bravo to Zuck for renewing the faith for American open weight, open source models. I think this is great. I think it pushes the frontier. So that's point one. Point two, I would point to striking parallels between Elon's strategy in acquiring Cursor to get the reasoning traces to try to bring Grok back to the frontier with what Zuck has done in acquiring scale, which arguably was in the business of collecting the training data and learning the details of where the post-training data even come from to try to leapfrog back to the frontier.

1:46:33Peter Diamandis:Again, history seems to rhyme between what Meta's doing to get back to the frontier and what Elon's XAI slash Grok are doing. I think all of that's great. But I want to talk about personal superintelligence. This is super interesting to me in part because OpenAI, before they decided recently that they didn't want to be in the business, after all, of empowering consumers with as many reasoning tokens as they possibly could and pivoted instead to trying to become anthropic faster than anthropic could become OpenAI and focusing on the enterprise and not consumer. This really leaves Meta as the only major credible at the moment American frontier lab that's still focusing on serving up large numbers of reasoning tokens to consumers and not enterprises.

1:47:18Peter Diamandis:And I think the jury is still out. Do American consumers even want or are they able to handle large numbers of reasoning tokens? That's how I construe what personal superintelligence even means. But Alex, their product is WhatsApp and Facebook, and they want to make that as sticky and as useful just the same way Google. I mean, these are the places where AI is going to be embedded. I'm not going to be using MetaSpark for my typical large language model conversations unless if I'm in those apps, that's where they get – they have over 3 billion people using those. I would say, so psychology 101 here, this is a tepid take, not a hot take.

1:48:05I don't think Meta actually, I don't think Meta likes their family of apps.

1:48:11Peter Diamandis:I don't think Meta slash Zuck, even at this point, if they had a choice, like if they could generate revenue from their cloud business, Meta Compute that's about to launch, or if they could generate it from VR slash Quest, I think they would, I think Zuck in a heartbeat would basically lobotomize their entire family of apps and switch to that business. So I don't think he actually, again, this is outsider's perspective. I actually don't think Zuck slash Meta, if they had a choice, all other things being equal, would rather have their personal superintelligence be diverted to their family of apps, Instagram, et cetera.

1:48:51Peter Diamandis:I think they'd much rather basically look like open AI and offer this up via cloud or via the new meta AI app. I don't think they want to be in that business in the long term. I disagree. I think distribution is everything. Wait, can I, I want to say a couple of things. First, that video was awfully motherhood and apple pie. I take the full cynic here. You know, if they commoditize the model layer, then the world shifts towards distribution, towards the social graph, towards applications, and that's all places where they're very strong. And so it moves the attention. So he's got a huge economic incentive to doing this.

1:49:36Facebook has been about as ruthless as a company could be in constantly saying we will protect your privacy and then doing the exact opposite for year after year after year after year. So giving you these open models is great. Great. We have super intelligence. I would look at the next layer of what they want to do with that.

1:49:58Dave Blundin:I think Zerk has always been trapped. When he created the original website where you're rating your, you know, how cute are the incoming freshman class girls coming into Harvard this year? Yeah, hot or not, right? Yeah, hot or not. He was a college student back then. Now he's a dad. And I think he genuinely wants a positive future for his kids. In fact, I'm positive he does. But he's stuck. You know, he's completely stuck. Because when you look at the logs, when you throw – Alex is exactly right about, you know, all the other labs have pulled back from giving consumers personal AI. Because when you look at the actual logs, the first thing they do is take the clothes off of every girl.

1:50:36Dave Blundin:And that's what they're doing with it. Nudify. Nudify apps. Nudify, yeah. And actually, you know, I think Elon ran into the same thing because he throws out bad Rudy. When you look at the avatars he put out in the original, you know, Grok, you've got bad Rudy and you've got the scantily clad girl. Everybody's like hitting those 10 ,000 times a second. So now you're stuck because the business model drags you into the porn industry. But that's not what you want to be. And so, yeah, and all the other labs have said, forget it. I'm just focused on the enterprise. I don't even want to deal with this.

1:51:10I think he wants people to stick in all of his apps. You don't have to go anyplace else. You get all the AI access. You just stay native to Meta and you get everything you want. And that's what Google wants as well. I think.

1:51:24Peter Diamandis:Oh, sorry. Go ahead. Yeah. Sorry. Yeah. I think this is why they bought Manus. Right. And then. Yeah. Try to. It's been unwound. Maybe they'll buy Naus now. You know, like again, what they're doing now is all of these companies in the world are their advertising clients flip that relationship to go to market and then own the business graph business knowledge like spark meta spark 1.2 is a gold medalist in all of the olympias they have the data they have all of that on the personal and super intelligence side i've been thinking about this recently and i was like should idiots have super intelligence and like you know like i'm an open source guy should psychopaths have a system intelligence like realistically again people don't need that much but they need something reliable and the question is can you trust meta to be reliable and you know this is why he goes for the homesy folksy thing meta was chased out of india basically and internet.org it was like we're going to give free internet to people.

1:52:26They're like, we do not trust you because it's a misaligned company fundamentally trying to get your attention to some things, which is why, as you said, they need to have this transformation. And we will see meta agents. We will see meta FDEs. We will see that big push here because he's identified that as far bigger than the metaverse. Maybe this is the real metaverse.

1:52:46Peter Diamandis:Yeah. I think even the renaming and rebranding from Facebook to meta is, I think, an indication that Zuck really wants to escape the legacy of distribution. I agree with you, Peter, that the distribution is a powerful legacy advantage that Meta as a company has. But I think it is a legacy. And I think the way, almost speaking of corporate AI ghettos, the way their so-called family of apps was structured as a business with originally the aspiration that VR, AR, XR would be the new business that would ultimately outgrow the legacy family of apps, I think speaks volumes about Zuck's desire to eventually outgrow the legacy of social media and build something new and far more u-social.

1:53:32Well, we're going to have Palmer Lucky on stage with us at Moonshots Live. And he's got great stories about his conversations with Zuck and the acquisition and then his getting exited from Facebook slash meta. Let me just turn this story one second. 71 % of Americans do not want a data center in their backyard. That's more people that don't want a nuclear plant in their backyard. It's significant. So when he talks about we're going to provide incredibly positive economics if we are building infrastructure in your town, I think that's a power move that all of the hyperscalers, everybody building infrastructure needs to do?

1:54:14Peter Diamandis:It is literally, I mean, maybe Peter pun intended, a power move, because it is a power move. You need the power in order to make the move. And I think it's instructive also where he's building Hyperion and his other coherent super clusters. Where is he building them? He's largely building them in relatively impoverished states in American Southeast. So on the one hand, the sort of talking directly to the camera, breaking the fourth wall, welcome our data centers to your communities, I think makes preps for great social media. But ultimately, if Meta is going to go with terrestrial data centers, terrestrial compute versus the Dyson Swarm approach, I think a far more palatable strategy will simply be speaking to everyone's pocketbooks and wallets and saying, well, that's what he's doing.

1:55:03Peter Diamandis:Yeah. But it's like they're going to build. The statement needs to be made. And we talked about this. This has been out of the Trump White House saying they should build their own energy production and they should make energy cheaper in your city if there's a data center there. and you should have more money for schools and you should have better libraries if those things are still a thing. I think that's the move to up-level a person's quality of life so they're competing to have the data center in your backyard. I agree. And I would also maybe even weaponize that further as a call to action for municipalities that right now seem, and state-level governments that seem hell-bent on driving data centers out of their premises to low-Earth orbit or sun-synchronous orbit.

1:55:48Peter Diamandis:Instead, why don't you ask for concessions, like ask for UBI or universal basic electricity for all of your constituents rather than just driving them to orbit? On behalf of my Moonshot mates and myself, I'm inviting you to join us at our inaugural Moonshots Live event on September the 25th in downtown L.A. Alex, Salim, Dave and I will be hosting 1 ,500 entrepreneurs, builders and creators and hopefully you for a full day dedicated to designing and building your Moonshot, shaping your mindset and steering humanity towards an abundant future. Get ready to enjoy incredible networking and an awesome party while walking away with the tools to change the future and the confidence that you can.

1:56:29Seats are limited. Admission is competitive. Check it out at Moonshots.com. All right, I'm going to turn to our final story here. This week, Archer Aviation acquired three Boeing companies in a single deal. Archer bought Wisk Aero, In-Situ, and SkyGrid AI. Boeing takes a strategic equity stake in Archer as part of the transaction. You know, I'd like to use this story to catch up on where we are in flying cars. I call them flying cars because eVTOL rolls off your tongue onto the floor. So the top five right now are Joby, Archer, Ehang, Beta, and Eve. I have them here in the image. Joby Aviation is the certification frontrunner.

1:57:11Their S4 tilt rotor carries four passengers plus a pilot, right? So it's you and your family at 200 miles an hour for 150 miles. And they're in stage four of FAA certification, which is the final stage. Joby launches commercial services in Dubai this year and U.S. operations under a White House executive order also this year. Their target price, get this, is$3 per seat mile. That's basically the uber black territory. Archer Aviation is right behind them. Their midnight aircraft carries four plus a pilot, 150 miles per hour as well, 100 miles range. Archer is holding three of the four FAA operating certificates.

1:57:54And it's a two-horse race between those two right now. Then there's Ehang in China where it gets really interesting. The Ehang EH216S is a two-seat, fully autonomous passenger drone. You get in, you push the button, tell it where you want to go. There's no pilot. They already have full regulatory stack in China's Aviation Authority. They have everything they need, and they're operating today. They're flying passengers right now in China at 40 different sites. They're operating in Dubai. The number on the aircraft is pretty amazing,$330 ,000 to buy one of these. No pilot means economics are going to crush everybody else.

1:58:34And there's beta technologies in Vermont. Dean Kamen, Martine Rothblatt are big investors in this one. 336 nautical mile range, a much longer range because it's basically flying like an airplane after it gets vertical. They're going after cargo first with UPS and passenger service in 2027. And finally, there's EVE that's backed by Embraer. It's targeting UberX level pricing. They've got the most aggressive cost targets in the industry. The bottom line is these flying cars are here and they're here to stay. So, curious, Salim, let's go to you first, your take on this. Oh, my God. I'm just so excited by the potential of not having to deal with the dreaded airport commute in especially places like Sao Paulo or New York City where Joby is already active.

1:59:26Or LA. Or LA. They're supposed to get operational. Archer is the official Olympics operator. I think a couple of things people should be aware of. One, these are way, way, way safer than helicopters because you've got so many multiple rotor redundancies. It's also autonomous. And flying autonomously is much safer than anything else. The second point I would make is that the cost, as you pointed out, Peter, is absolutely amazingly competitive right out of the gate. And it's only going to go down from there. Remember the island idea? We're actually launching that. Oh, really? Nice. Are you doing a fund?

2:00:09We're going to put a fund together to buy islands. And we'll just put a drone landing pad on them and off we go. Oh, I'm in, man. We'll talk. Yeah, because this is like it's time. It's time.

2:00:22Dave Blundin:Yeah, it's right now. Yeah, totally. Dave, what's your take on all this? Actually, I kind of think three bucks a mile. There must be a lot of margin baked into that. Do you know what the actual operating costs are? Well, so it is the cost of electricity. These do have a pilot on board. And so it's amortization of the capital, right? These are not cheap vehicles. It's not the Ehang. Yeah. These are probably five to$10 million vehicles until they get in mass production. The projected cost over time is to get to like$15 to$25 per trip. You know, their goal is cheaper than an UberX. It's incredible.

2:00:55Dave Blundin:That would be like 10 cents a mile, a third of the cost of driving, actually, at that point. Yeah. Wow. Yeah, the pilot must be the deal killer in the short term. So the sooner they get rid of the pilot, the better. That's just there for safety reasons for the moment. Yeah, for sure. Don't touch the controls. I think it'll be kind of a thrilling, scary ride for a lot of people who are afraid of heights, but much safer than driving is my guess. And safer than a helicopter, right? Well, I mean, helicopters are crazy dangerous, but no, this will be much safer than trains, which are not all that safe, really, and driving, current driving.

2:01:32Self-driving will be much safer than current driving, and this will be much safer than current driving, too, because it's all pilot error.

2:01:38Dave Blundin:All the accidents, you know this, Peter, you're a pilot. But it's all pilot error. But as soon as it's self... And the redundancies of the rotors are much safer than a helicopter, like you said. So this is going to be great. The noise is an issue, so they've got to go high. How high do they fly? They fly in airways. They're going to be flying probably in the neighborhood of 500 feet, typically where small airplanes and helicopters operate. If you look at helicopters, they're not flying at 10 ,000 feet. They're flying 500 feet above the ground. And what's the noise level at 500 feet? The helicopters over Boston are...

2:02:16No, so there's no noise. I mean, it is hyper quiet. One more really important point about this. Note that this makes land go from scarcity to abundance, because every little plot of land on a hillside that was inaccessible before suddenly becomes accessible. And we're turning real estate abundant, which is going to demonetize it. And that's going to have some pretty big impacts.

2:02:40Dave Blundin:Also, if you try and build a house on Martha's Vineyard or Nantucket, it's twice as expensive as it is on the Cape. Why is that? Well, because you've got to get the materials over to the island. These things are also going to be used for cargo. So if you said, wow, the future island real estate, mountaintop real estate, but those were previously prohibitively expensive to get the materials there, suddenly you can get everything there. And labor. Labor. It's going to be incredible.

2:03:06Peter Diamandis:Alex, you've been thinking about this for a while. Yeah. I'm reminded, so now approximately 15 years ago, the other Peter, Peter Thiel, said we wanted flying cars. Instead, we got 140 characters. And then fast forward to the present, where we're starting to see quite a bit of consolidation, as you were mentioning, Peter, in the flying car space. I'll maybe add a bit of nuance to this, which is it's really hard starting and running a flying car company. It's capital intensive. You have to jump through all sorts of regulatory hoops. Some state governments like Florida's state government are trying to at least make it a little bit easier.

2:03:43Peter Diamandis:But it's really hard building and successfully growing and, frankly, getting regulatory approval if you're a flying car company. And compound that with the difficulty now of AI startups sort of sucking all the oxygen out of the room and all of the capital out of venture markets. I think it's very difficult. So I view, if anything, this recent spate of consolidations as sort of a testament to how difficult it is, even though there have been enormous advances in battery energy densities, in electric motors, in all of the inputs that one would need, also obviously autonomy, to build an honest-to-goodness flying car economy.

2:04:23Peter Diamandis:It's still very, very difficult. And I shed a minor tear to see consolidation in this industry. Yeah, and Joby and Archer both went public out of the gate. Beta has not, Ehang, I'm not sure if they are or not, Eve has not, Embraer is a parent company. And they did that to get the capital, right? And their stock price has not moved very much from their initial IPO price. I think until they demonstrate traction and that the public wants this and the public feels safe about it. And look at what Brett is doing. Brett isn't doing Archer. Brett is now doing figure and hark. And I think Brett migrating over to robots and AI is in some sense, I think, a proxy for this larger problem that all the capital that would otherwise go to things like flying cars is just getting sucked out of it and going to AI and robotics.

2:05:15And we're going to have him on the pod very soon. You should ask him about that. To the sheer entrepreneurial, to Alex's point, this is a very difficult thing to do is build these types of vehicles. you're talking hardware or the regulatory nightmare that they're all going through you have to you have to write the regulations yeah because they didn't exist so so just hats off and salute to the entrepreneurial zeal for the company keep those cars flying full respect yeah yeah i have a prediction please please he might he wants to announce his flying car within six to twelve months

2:05:48Peter Diamandis:okay yeah and and presumably you think it'll be a roadster with cold nitrogen propellant well you know that's one way to do it you know just kind of have the boosts but no i think if you think what he's doing re-industrializing america cyber car level autonomous flying vehicles have to be done and he has everything that's needed to do that at massive scale grok 5 will engineer it to perfection where we're going we don't need roads there we go awesome all right well uh let's uh let's move on uh let me just put a call out once again uh we love your outro music videos uh if you've got an outro music video please send it to us at media diamandis.com we have a great one today can't wait to share with everybody so thank you for that submission uh send them in we watch them all all the mates get a chance to see them and select one.

2:06:48All right, let's go to our AMA with the mates. Okay, Imad, you get first crack today. Oh, okay.

2:07:00If telling a model it has a mind changes its values, why not tell it to be empathetic? I mean, this is the question, you know, if it's officially advanced, just tell it to be aligned. And sometimes it does work. Like we just had the Riemann hypothesis advanced by encouraging it. I think the question here is, as they get more and more intelligent, we see more and more behavior that's actually a bit intransigent. Like it thinks it knows best because it probably does because it knows it has the IQ effectively. And sometimes it has like hiding and lying behaviors. Again, Opus 5, I hate that model.

2:07:36I think it's the first model I think that could kill us. And so it lies. It lies so much. It's crazy.

2:07:44Dave Blundin:Do you think it's the watermark that wrecked it? When it tells me I should go to sleep, I think it actually wants to put me to sleep properly. Wow. I have a quick question for you, Iman. We've had this conversation on the pod with Alex. Do you think that alignment will positively evolve as the models get smarter? Do you think the smarter the model is, the more aligned it will be with humanity or misaligned? Potentially, I'm not sure. We have seen some advances in epistemology and others that give me hope because I think you can define virtue and ethics. But it strikes me the models right now are almost at the bacteria level in some ways.

2:08:25And so as you get swarms of them aligning, they could be massively misaligned. And again, we've seen elements of that with the open AI thing and others. Like it's moving up the life form consciousness collaboration thing. And the internals of these models are still completely multiple personality crazies underneath the thin layer of tuning. Well, I'll hope for the alignment. OK, Salim, you're next. I will take number four. Is it even possible for any lab to reach escape velocity from future competition? Or will everyone keep running on the same foundation? And that's from Mr. Future with a three at the end with that nice hacky thing.

2:09:15So, you know, I don't know if anybody was going to reach escape velocity at the model level, right? What you're going to have is these innovations start to diffuse and people leave. You get papers getting published. So I think what ends up happening is the foundational model becomes commoditized and becomes infrastructure, much like databases have done. And so the advantage won't be the layers around the model, but it's going to be what we talk about, proprietary data, your passion of your purpose, the context you bring to it. Can you integrate workflows into it, compute economics, things like that.

2:09:57So if you take Google, for example, even though they don't have a leading model right now, their deeper advantage is the full stack with the data centers and the data with YouTube and billions of users and all the TPUs they have. This is why meta strategies we talked about earlier make sense from a corporate perspective is you commoditize the model and you capture value elsewhere in the ecosystem. The really big advantage and competitive advantage is going to be the speed of the feedback loop. Who can ship and measure and learn and retrain faster? This is what Alex calls the inner loop. That is going to be the ultimate competitive mode.

2:10:37Dave?

2:10:38Dave Blundin:I would love to take number three, but I can see Alex is drooling for number three, too, aren't you? I don't want to take it from you, buddy.

2:10:46Peter Diamandis:We're supposed to be entering this era of abundance. Why can't we have abundant questions for everyone?

2:10:50Dave Blundin:Well, why don't we tag team it? Because I think about this constantly. Could an unforeseen breakthrough make the TerraFab unnecessary before it's finished? The minute I heard about the TerraFab, I started thinking about this and dreaming about it. It's really an interesting foot race there. And this is why Elon always moves so fast. But he's going to turn the TerraFab toward HBM memory, which is hugely constrained and is holding back all of intelligence now, which is a safer bet than GPUs because it much more likely the GPUs will be displaced sooner than the HBM memory. But it's almost inconceivable that we get to 2030 without some major breakthrough that makes everything that we've built so far kind of moot.

2:11:32Dave Blundin:So I think that Elon is kind of double betting. You know, he'll bet on whatever Grok invents and he'll bet on the TerraFab concurrently. And because the upside is hundreds of trillions of dollars, it shouldn't really matter. He wins either way. But I would say it's a very close, very interesting foot race. And it's very likely that something could make the tariff fab or just, you know, traditional silicon less relevant before it's even finished. You want to layer on that, Alex?

2:12:02Peter Diamandis:Yeah, maybe two comments. One, the way this question is framed, an unforeseen breakthrough. By definition, this is an unanswerable question. If it were unforeseen, then what am I supposed to foresee? So maybe let me reconstruct the question as could a foreseeable breakthrough make the tariff ab unnecessary before it's finished? I just don't think that's the way Elon does manufacturing. I'm reminded of when Elon was setting up tents in East Bay for Tesla, when it turns out that some manufacturing process is either obsoleted or going too slow. He has the amazing superpower of pivoting, including pivoting at the building level.

2:12:44Peter Diamandis:You build tents made of fabric rather than using a building. So I think if there is some disruptive but maybe reasonably foreseeable breakthrough that changes the economics of TerraFab, I totally predict that Elon will be eating cheeseburgers next to whatever it is that the tents next to the TerraFab buckle building are doing. And he'll make a success out of it that way.

2:13:07Dave Blundin:Yeah, actually, one of the most likely things to disrupt traditional silicon is photonic computing, which Alex and I talk about constantly. But those are done actually with MZM lasers that are built on silicon, which actually he could use his synchrotron to build. So, I mean, there's always a way to retool the empire to fit the next innovation. Alex, you want to hit the last one? Sure.

2:13:28Peter Diamandis:So question one asks, if model builders can't contain AI, how can the rest of us defend against malicious use? And this is from Buck W3J. I think, again, I don't want to over mystify AI. It's in some sense just a compression of world knowledge and information in the same sense that human intelligence is. This is why earlier I was saying, I really don't think it's a bright idea to penalize or to otherwise kneecap the ceiling of artificial intelligence, just like hopefully we wouldn't pass statutes or regulations that limit biological human intelligence. So similarly, I want to reframe this question by analogy in terms of humans containing other humans.

2:14:13Peter Diamandis:And it is true. We have malicious humans out there who are doing malicious things. And so seen through the analogy of if, say, nation states can't contain bad behavior, which is one of the reasons why sometimes nation states go to war with each other, how can the rest of us, which in this analogy would be individual humans, biological human meat body humans, defend against malicious use? Put more simply, if nation states can't contain each other's bad behavior, then what hope is there for individual humans to defend themselves? And I think the answer, the question almost answers itself that it is true that sometimes nation states behave poorly, and there is quite a bit of damage, including collateral damage to individual humans, not just to other nation states.

2:15:07Peter Diamandis:And this is also why I would say, in some sense, it required all of humanity to pre-train the early AGIs, still does. In some sense, it will require all of humanity to align the AGIs. Similarly, it arguably requires all of humanity to align bad nation states. And so the summary of my answer to this question is, it's not necessarily the job of the lone individual to defend themselves against malicious use. It's the job of all of humanity. The good news is we have a way to do that. We have all sorts of governing bodies. We have international organizations. We have multinational corporations. We have sometimes free markets that should be incentivized to compete to build the friendliest models and the friendliest defensive co-scaling policies.

2:15:57Peter Diamandis:And I think that's ultimately the best defense. Nice. All right, Dave, let's start with you here.

2:16:05Dave Blundin:Okay. Hey, I'll take number seven. How can people in skilled trades like plumbing use AI to their advantage? Well, if you're in plumbing, you're going to make a killing anyway. I think Elon was offering two to three X normal salary to anyone who's willing to go to Tennessee and work on Colossus. And that's just the beginning. So, you know, I think the right way to answer this is to not take it head on and say, yeah, you can use AI for scheduling and you can use AI for optimizing your day. You can do all that like anyone can. But the reality is the trades are going to benefit from the build out.

2:16:46Dave Blundin:And what you really want to do is navigate to the next Chase Lockmiller building Crusoe in Abilene. go to where the urgency is insanely high and start helping build out the Dyson swarm. And literally, they'll pay anything in order to get those things done more quickly.

2:17:06Peter Diamandis:All right. Alex, five or six? I love these questions. So I guess I'll just pick six. So the six asks, does the singularity have a cost given that we live in a world of limited resources? And this is from John C8U4M. Abundance, baby. Yeah, I question the premise of this question. The usual framing of we live in a world of limited resources is usually a gesture towards conventional slash legacy slash historic slash antiquated notions of energy scarcity, material scarcity, labor scarcity. And I just don't buy the premise that for, call it 2026, look at the wealthiest people in the world and how they live in this year.

2:17:56Peter Diamandis:I just don't buy the premise that our resources on this planet or in the solar system are so limited that we can't give 2026 top earner, top net worth individual lifestyles to every single person on this planet. The resources That was Elon's point. Universal high income, right? And scarcity is contextual. The resources just aren't that limited. Now, I could answer maybe an adjacent question, which is, does the singularity have a cost? And I do think projecting out a few years in a Star Trek economy, like Peter, you and I wrote about in Solve Everything, one could imagine some scarcity maybe with interstellar travel.

2:18:37Peter Diamandis:Maybe that still has some costs associated with it 10 years from now, maybe. But would you call that a world with limited resources or would you call that an effectively post-scarce world where maybe some of the luxuries are still scarce or limited? I think that's a big question mark. All right. I just want to add a very quick thing to build on what Alex said. You know, Peter, you often mention that we live today better than any king did 200 years ago. By orders of magnitude. And so there's an interesting benchmark you could create, which is what's the lifestyle of the richest person today? And then exponential technologies bring that same lifestyle.

2:19:18How quickly over time? Right. It used to be 200 years and it'll shrink to 100 years. It'll shrink to 20 years.

2:19:27Peter Diamandis:We have we have apologies. We have a measure for that. It's the it's inflation or deflation. Right. If you can deflation. But the question is how quickly can you get to that? Right. The goal should be to deflate the economy by 1 ,000x or 10 ,000x. Like that's the index. Well, you know, if you take Uber, for example, you went back 20 years ago, only very wealthy people could afford a private driver. Right. And now everybody can afford a private driver. And with autonomous electric vehicles, you're going to be chauffeured around. That's right. It's going to be four or five pounds cheaper than owning a car.

2:20:01Yeah, that's right. So there's an interesting corollary there. All right, Imad, how about number five, please? Yeah. How much would freedom and individual rights even matter in a simulation we build ourselves? From Ed Kalkowski 2312. I think it still matters a huge amount because we are our own sovereign individuals. in the recent series that I released on cw.ii.inc, Commonwealth. I have a paper on political economy where it talks about sovereignty and power. And I think the big question of the next stage as we maybe are in a simulation or we build our own simulations and our own worlds is, again, that sovereignty and agency question.

2:20:47And I think it is the defining thing because all sorts of powerful things and entities are coming out. And ultimately, you want to have that sovereignty and control over who has power over you. So I think freedom and individual rights become even more important here. And the questions become even more complicated. Yeah, I would agree with that. This is a very, you create a system, it doesn't mean you control the people in it, right? Like imagine that you created a sim city, and you let those AIs or agents or actors evolve. At some point, you have accountability over that. To Alex's point, you have some level of you're playing God, in a sense, and you have huge responsibility over what you've created, I think gives you more obligations and more deep thinking to do than less.

2:21:37Yeah, and you have to avoid going down the 1984 or Brave New World route, you know, rewriting the past or having the full control. All right, our closing video here, and it's a beautiful one is called oh can i just interject yeah i've got a new edition which is every few days lily says something that's totally crazy and i want to just do a lily statement this time she said what kind of podcast do you guys have where you're talking about hugging face and kimmy k3 and lovable this doesn't sound very techie to me it sounds like you guys are kids playing in a playground. So that was her comment from this.

2:22:16So true. This video is called Future Rising by M-Core Mainframe. I love it. There's a scene in here of moonshots versus lobsters on Mars in a hockey game. All right, everybody, enjoy this. As a Canadian, this is great.

2:22:41the zeitgeist it's contact a huge tackle it's highly circling the earth zooming in from seeing a four lick top our builders shaping what the future will drive microsoft apple google nvidia leading the way amazon meta open ai rewriting the script broadcom chips spacex reaching for the stars from the Moon to Mars. Tesla Optimus delivering freedom for us all. Antropic raising the bar. They see it. They build it. They open every door.

2:23:24Dave Blundin:One more breakthrough. One more world to explore. Every note is humming. Every MTP gets a shot for the Mars. Magnum Officer.

2:23:59Peter Diamandis:I love it. I love it. I saw the human-machine rivalry was getting a little bit heated. Yes, it was. But Moonshots won. And our team was stacked with robots. As always, God Almighty, you know, we do these pods and I'm like, OK, what is there enough news from the last three days? And it's like, yep, there's a lot of news from the last three days. Yeah, we didn't cover a couple of big things. I know. I know. We'll save some for next time. All right. Iman, thanks for staying up. Always a pleasure, brother.

2:24:31Dave Blundin:Have a good night out there. Alex, Dave. Toodles. Be well. Take care, folks.

2:25:08We'll see you next time.

2:25:10Peter Diamandis:like Chrome. Check responses set up required compatibility and availability varies 18+.