Bernie Sanders sent a formal letter to the CEOs of Anthropic, Meta, and Open Eye. >> AI capabilities have reached a critical threshold. Pause AI development. >> The cat's out the bag. It's too late, right? >> Nvidia just [music] announced a partnership that redefineses what GPU compute means as a financial asset. >> This is like the very first pitch of the first inning of the buildout of the Dyson swarm. Financial assets want predictable depreciation and exponential technologies don't give you predictable depreciation. >> I'm not as concerned that this will end up being another mortgage back securities fiasco for a few reasons. One is Elon just dropped Grock 4.6 and he's right. It's a banger. Grock 4.5 came out 2 weeks ago, 4.6 just this morning and 4.7 is rumored to be coming out in 2 weeks. 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. You can't get beyond Frontier with this stuff, but what if you have the best engineers?
[00:01:03] >> Now, that's a moonshot, ladies and gentlemen. >> Welcome back to Moonshots, everybody. Uh we're going to be covering nine stories today that span the frontier from longevity, AI infrastructure, synthetic biology, AI film making, urban air mobility, and oh by the way, Gro 4.6 is crushing it. The through line is the same as always. You know, accelerating singularity is compressing the distance between the impossible and the inevitable. We're back this week with the moonshot quintet, uh AWG, our in-house super intelligence. Alex, welcome. Good to see you in your normal apartment. Good to be super intelligent. >> You are my friend Dave Blondon, our investor and AI extraordinaire. >> I was over at MIT all day today, hence the garb, but uh our Techre teams just got back from SF and they brought back huge amounts of knowledge and they're all over at MIT sale dispersing it across the campus right now.
[00:02:01] >> Love it. And Salem Ismael, our empressario of exponential organizations. See, where are you today? Still in Toronto? I'm still in Toronto heading back tomorrow. >> Okay. >> I should be going back now, but this podcast happened and I can't fly, you know, within like six hours of [laughter] >> We're going to we're going to put a Starlink on your on your hat and have you walk around with it. Uh, and back by popular demand, Immad Mustach, the embodiment of the intelligent internet. Immad, I hope you're reading the comments on the last pod uh that we did together. People are loving you. Have you seen them? >> Uh, yeah. I did see some of them. I don't normally read the comments. I made an exception and it's very kind what everyone said. It's great being amongst you guys. >> It is. It is. It works for my American wife. It works for the others. You know, [laughter] >> I'm Peter D. Madness, your host, your optimism amplifier. Please remember that having an optimistic and abundance
[00:03:00] mindset is a choice. And our mission here is to deliver datadriven optimism that helps you make that choice. So guys, uh, last night I was in Utah, the University of Utah. It was the finals for the $101 million longevity or shall I say Healthspan X-P prize. Super psyched. We awarded a million dollars to 10 teams, recognized another 10 finalists. This is on the march to winning the $80 million grand prize. We've given away 20 million so far. And the mission of these teams and you know everybody please get excited about this is to add 20 healthy years on your life. Asking teams to reverse your functional losses that we get through aging in cognition give you the ability to think and have memory like you did 20 years ago in muscle the ability to build muscle like you did 20 years ago and in your immune system. Uh and it's extraordinary. We had 800 teams enter this competition. every possible approach from mitochondria to uh you
[00:04:03] know stem cells to you know gene editing it's it's extraordinary so this is a competition that will be won by 2030 so keep an eye on this uh you know sele I don't know if you want to jump in on this one >> you 20 20 is infinity right >> I mean you know I think there's there's X-prise was such a huge inspiration when I was writing the exo book because you're reaching outside and I mean 800 teams is that I think that's a record for the traditional prizes for us, right? >> It's kind of an incredible thing. >> Elon's Elon's $und00 million prize for carbon removal ended up with something like 1500 teams. But, you know, reversing aging, it's got to be tougher. And by the way, the teams here don't do this in theory. They don't do this in mice. They have to actually do human trials. So, they're all going to be
[00:05:01] doing trials with control groups and and humans, uh, probably around 150 people in the trial. So, it's real data and we're going to actually know which of these 20 to 30 approaches that actually make it to the finals work. Uh, and for me, you know, Alex, we've been talking about being in the midst of longevity escape velocity. This is accelerating it. It's going to be spiky. I think I I still think just as with AGI either in our rearview mirror as I think or some might say it's either here or almost here. I I do still expect that health span and longevity escape velocity it's going to be spiky and and I'm just optimistic that we can even out the spikes even if there's a sub population that achieves health span on the margin a few years before everyone else. You know, one of the most important things I think about this competition when we launched the $10 million Ansari X-P prize for spaceflight back in 1996, you
[00:06:00] know, back then people did not believe in commercial space flight. They didn't believe that individual teams could do this and carry humans compared to the government. And as it progressed the confidence level in this and then when it was won money flowed in regulations changed you know Bezos and Musk started uh you know Blue Origin and SpaceX and it be changed the game. So I'm feeling the same thing going on right now. You know longevity the idea of reversing aging has been sort of a a crackpot idea for most of the last few decades while I've been in the industry and it's beginning to change. People are starting to believe yes, it's going to happen. Yes, we're in this health span revolution. >> We're getting to a we're getting to a when, not an if question, right? And that's really huge. I I wanted to point out something that was that's really important here, Peter. When you launched the Ansari X-P prize, >> there was no space industry to speak of, at least in the commercial side, and now we have a trillion dollar industry that
[00:07:00] did not exist, right? Because the collective innovation plus all the members of all the teams end up going to SpaceX, Blue Origin, etc., etc. And we could expect the same thing to happen here where you end up with essentially you're creating a $101 million bet. You're building a portfolio of experiments and allocating capital to wherever there's demonstrated results. It's an unbelievable model that we've now seen repeat over and over again. It's incredibly exciting to see. >> Yeah. I was >> question for you Peter on this one. I I always ask the counterfactual question. Is is there something having now run this health span prize or at least the the beginnings of it? Do you think that if this prize had been created say 20 or 30 years ago that we could have made on margin enormous progress or do you think there's some historic contingency that means right now is really the the first time in history where we could make credible progress on it? >> Yeah, I I think we had a lot of comments. We had a lot of the top scientists, Aubrey Deg Grrey was there
[00:08:00] last night who coined the term longevity scape velocity and then and then Ray popularized it. Uh I think everybody was at the consensus that the timing is perfect that the tools for genome sequencing for uh you know making specific molecules for being able to measure uh and and report with AI uh are the tools that are required today. I mean there might have been some approaches uh that could have been done 20 years ago but I think today uh is when we're going to make the greatest progress uh and I'm starting to see you know capital flowing in aggressively at the end of the day longevity is going to be the biggest market right if you could add 30 you know I've had this conversation you know See probably you have as well on stage you know with YPO audiences or family offices and I say how much of your wealth would you spend been for an extra 30 years of life. The honest answer is nearly all of it. Right. >> Yeah. I mean you and and the powerful
[00:09:02] distinction there's not so much lifespan but the health span effects are really really powerful. >> Yeah. The numbers today are for the United States if you if you look at it uh basically uh 100 years ago in 1900 the average life expectancy was 47. Today it's 79. We added about two months per year over the last century. And today, while the lifespan is 79, you're healthy until average age 63. And you spend the last 19 years of your 16 years of your life in poor health. And so when I was with talking to Katios about this, I said, listen, the biggest benefit the US budget could have and the US economy could have is add 20 healthy years in people's lives. they they're retiring uh later. Uh they're not spending as much government money on on you know sick care. So it could be a huge transformation. Alex
[00:10:02] >> Yeah. I maybe just again coming back to this historic counterfactual. I one of the things that irks me the most is that so many of the abundanceoriented futures that we want to find ourselves in like LEV the super intelligence solve everything just take forever. Uh and I I do wonder again we're is it 20 years post Yamanaka that like Yamanaka I think was 2006 we're in 2026. What did we blow these 20 years on? Why couldn't we have done this 10, 20, 30 years ago? >> I got a question for you, Alex. >> I'll answer that. >> That I think when you get multiple exponential technologies that can address a particular space, then that's the point to in invest or put up a prize because then you get radical outcomes at very low cost. And so maybe there's a benchmark of the minute some domain has two or three or more exponential
[00:11:00] technologies converging on it, that's the point to have put dollars into something like this. [clears throat] >> Dave, >> well, there's no doubt in my mind that I'm going to do more productive work in the second half of 2026 than in my entire life combined up till 2026. So throw it back at you, Alex. Like even if we had worked really hard on this 20 years ago, uh would anything that we did between then and today even hold a candle to what we'll achieve between now and the end of the year? Cuz I mean it's so funny to me, you know, my my daughter's over at Madna. She's a biochemical engineer and she listens to the pod of course you know and it's so obvious to her that we're in an AGI hard takeoff now and the people she works with in biotech are about 1% AI aware and 99% not aware but the AI aware now people are spending over half their day maybe 80 90% of their day talking to AI agents and not in meetings and not you know running gels and not running assays because it's it's just a different mode
[00:12:00] of living that's accelerating tremendously, but the the aware subset is tiny. >> I I almost think I think it's an important point and I almost think we need a new term for it. I I just thinking off the cuff maybe like retrospective hyperdelation, this very singularityoriented idea that with super intelligence you discover that everything that you spent the past decades on was just a total waste and you should have instead just done nothing, twiddled your thumb for decades, waited for super intelligence to solve it for you >> or or just work on, you know, chip fabs or something that will, you know, they'll be very useful on that day or in Texas or >> all these people like who who spent six-year PhDs trying to divine protein structures just mostly wasted. >> Well, that one was was really outed by Demis. Yeah, I mean that one what it was like an average of four years to discover one fold. >> I I knew there was a reason I didn't do a graduate degree. That was it. [laughter] It would have been irrelevant. This was your post
[00:13:00] justification. >> That's right. This >> I mean it it could be worse. You could be a pure mathematician, right? >> [laughter] >> Like >> they're all cooked too. They're they're having this the same moment of on week. >> Yeah. But at least with the biologists, the longevity people, you can do assays and things physically. No, look, I think that this is the biggest market in the world as you said, but it's the first time that it's tractable. I think if you go back to when there were the Yamanaka factors, all these other things, you didn't have the infrastructure necessary and the talent pool necessary. >> [snorts] >> I think that as you've seen the various breakthroughs in other things and everything come together right now there will be a shortage of people that can really work on longevity properly even though it is the biggest market in the world and 10 years ago 20 years ago that would have been even tinier there are only a few people actually looking at some of these things back at that time so I think it is this confluence factor all coming together and like I said it's finally tractable so the people who are winning in the longevity x prize any
[00:14:01] indication that those things will work and I don't think they'll be short of capital but again the X-P prize is the catalyst right and that was the whole idea >> you know Peter you've pointed out something that I think is incredibly important to highlight right which is that we spend today huge amounts of money on treating chronic diseases at the end of >> you know what the number is sim it's the global cost of age related disease is 20 trillion per year globally >> crap >> yeah it's a huge >> Daniel Craft used like 85% of healthcare costs for the last 5 years of your life type thing. This is a staggering number, right? Because now >> just for context, glo the global economy is 120 130 trillion total. 20 trillion of that is >> look at that number, right? So now now the business model becomes how do you maintain uh decent function, bodily function before the dis disease appears and it'll completely change healthcare economics. Massive impact >> and and global economics in general, >> global economics >> in terms of productivity and wasted capital. Well, I think this is this is
[00:15:01] where the peptides have come really interesting, right? Like it was like to lose weight, you had to work out. I'm about to start, you know, get rid of that extra report in on the pod. >> I'm going to get it report in and see how my weight loss goes. But the thing is, >> which peptides am you taking? Do tell. >> I was going to try the one >> randomide. Yeah, >> I'm on retroide. >> But I know I'm going to lose weight, right? Are you getting access to No, but serious. Okay. Has it even Oh, you're in Canada. >> No, no, I'm not in Canada. I get it in the US. It's totally >> Yeah, they're drug dealers out there. [laughter] Black market >> drug peptide dealers, right? There we go. >> I guess See, that'll just be our little secret. There's no one paying attention to >> here. Nobody's listening. >> But but this is how like you know that you're going to lose weight with it, right? And that's the first. And so now the concept of you can take a pill or an intervention and you could live longer. Well, you're already losing weight like that. And so I think again that's a big awareness that's caused the longevity
[00:16:01] market to get even bigger. >> Yeah. GLP1s are the first longevity drug uh you know in a lot of people's opinions and it's one of the biggest grossing drugs if not the largest one in human history. I I've gone even further that than that just again bit of back of the envelope calculations suggesting and again this is not medical advice uh that GLP1s especially third and maybe fourth generation GLP1s may actually be when I refer to LEV longevity escape velocity as being potentially spiky a pretty big spike there there have been studies done recently on uh some of the third generation if memory serves GLP1s that suggest uh and again not medical advice that we may be or at least some subop of humans that have undergone GLP-1 studies may be at something like 70% LEV just with GLP-1 therapy. So if if that is the case and again encourage folks to to do their own uh independent back of the
[00:17:01] envelope analysis that's a heck of a an LEV spike in a subop that's being administered GLP1s. >> Yeah. Anyway, watch this space everybody. It's exciting. >> Peter, I've got one more question for you. Please um as you looked at the finalists cuz I couldn't make it to the finals but we've been tracking some of the teams etc. You you had a great snapshot view are you in the view that lev we get to it by 2030 or earlier. Uh so here's the idea right if any of these teams win and can reverse your functional age right this is not a number from a you know uh a particular blood test you take you know that changes on the back of a form this is are you feeling functionally younger are you know do you have better muscle building capability better memory better immune system so what really matters is your function and so if we can do that if we can actually reverse the clock by 20 years of function, then you get to enjoy the next 20 years of
[00:18:00] breakthroughs. And if you don't believe we're going to have incredible breakthroughs over the next 20 years, you know, basically, you know, wholesale simulators and AI, you know, the impact of quantum, whatever that might be in in in cell biology and understanding how we age, uh, then you're missing the boat. Your goal is to keep in the best health right now, which means what? Sleep eight hours. Unless you're E-mod and Alex probably don't sleep more than four hours, but you're short sleepers. >> But you're short sleepers. Sleep as much as you need to. >> So, I'll make a comment here which I've made before, which is that, >> you know, the business model of religion is to sell heaven. As we have life extension coming, how are you going to sell heaven if people aren't dying? So, this breakthrough will mean that religion is cooked. we [laughter] have forever to figure it out. Like >> uh there will still be a lot of religions doing very well uh from people tithing. But again, I guess the advice right now is do what you can to keep in
[00:19:02] the best health. Don't die from something stupid. It's sleep, exercise, you know, proper diet and mindset. Mindset so important. You know, I think my greatest attribute is my longevity mindset. So take it on. We'll keep on reporting in the space. It's an important part. This episode is sponsored by Google for startups. Think about this for a second. You now have access to the same generative AI models that cost hundreds of millions of dollars to train. Google's startup tactical guide for generative media gives you complete blueprint for deploying Google Deep Minds models in production. Images, video, audio, all of it. Real architecture, real results. Find the link in the show notes below. But let's move us on. Um these were a couple of stories Immod that you shared with me. Um these are three stories that landed this week together that describe really I think the collapse of Hollywood economics and the rise of something much bigger. So our first story is a company
[00:20:01] called Higsfield that just made a a movie called Cully Hill Boys. It's 110minute feature film. The first fulllength AI generated movie with licensed celebrity likenesses. Here are the numbers. Uh the total budget for this film roughly you know fulllength film $2 million team size 28 people production time four weeks compute cost $1 million uh they use Cance 2.5 as the generation and they open sourced all 10 steps in their workflow so anyone can replicate it so here's the context right uh a feature film with celebrity talent today costs between 20 million and 100 million if you're not using AI and it takes you know, a year to 18 months. Hicksfield did it for 2% of the cost and 6% of the time. So, I want to share a short video, a little clip from Hicksfield so we can appreciate it.
[00:21:16] Is that spices? >> Supposed to be over2 million pounds packed in this little nut. Who smuggles coriander in aing boat? Someone who suspects it might get nipped. Or where'd your boys go after you left the pier? What the is that supposed to mean? We came here and waited for youing pricks like we wereing told. >> Let's go through it step by step, shall we? >> All right. Uh, our second story, uh, Bloomberg reported that nine out of the top 10 texttovideo models on AI analysis leaderboard are coming from China. Uh,
[00:22:02] this is a headline, but the real story is deeper and I'm curious what you guys think about this. You know, Hollywood forever has been the dominant producers of films and it's basically exporting US culture to the rest of the world. What happens when the world is flooded by Chinese-prouced English-speaking films? How is that swaying public interests and public points of view? Uh and the second thing is that these Chinese models that are dominating video uh 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 and it works on your your MacBook Pro which is extraordinary. So, uh I want you to imagine uh something that allows
[00:23:01] the individual uh to sort of tee up and produce their own movie. Uh one more clip. This is from LTX 2.5. This is LTX, the most downloaded open- source world model. And today, [music] 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, Iman. This has been your world for the better part of a decade. >> Yeah, it's um happening right on forecast realtime highdefinition video. Um, so LTX can generate a 10-second clip in 7 seconds at that quality that you
[00:24:03] 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'll just do it instantly on your local kind of laptop. So you said kind of the disruption of Hollywood like you never need to reshoot a scene now with the flows that you have. People are licensing their things and as you said Hicksfield released an 80page 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. Uh Hicksfield got from it's an ex Snap uh leader from Snapchat. It's 700 million revenue run rate right now in about one and a half years to give the idea of kind of how much uptake. But that's just the start. >> That's crazy. >> Crazy number. >> Yeah, cuz every pixel will be rendered.
[00:25:00] 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. >> Walk us through the one the $1 million budget to make a one and a half compute budget to make a one and a half hour long movie. What will that be by September 25th by the time we have the Moonshots live event? >> So it depends on the level of quality. Seance 2.5 is the best model. It's a large big model that costs about $3 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 cuz Seance can do 30 second clips, but the average movie on the Hollywood box office right now is 3 seconds per shot. Wow.
[00:26:00] >> So you could have a 10 times reduction in cost. You could shoot a movie just like that one probably for a 100,000 of compute and then 10,000 of compute >> probably by the new year. >> This is what we saw in our uh you know foundations of AI ventures class at MIT is that it went from PowerPoint demos to full functioning products in one year. Like to to be competitive on demo day now you have to actually build the entire product. But I I suspect the movie like our our target for September 25th is bring a script. >> Well, the So Dave's referring to the Future Vision X-P 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 PE 5,000 who are creating three minute threeminut trailers and a film treatment. I just had a meeting this morning with the team at Range Media and Google to down select and we'll down select to ultimately the top 100, 50, 25, 10. The top five will be at
[00:27:03] uh at Moon at Moonshots Live on the 25th. And everyone listening, we're going to you can come and be there live and vote live. We're going to also have a live stream of the event. But yeah, it's and we're going to do this year on year. So every year it's going to get better, cheaper for sure. 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 you we were thinking, okay, then it'll be a $20 million, you know, year-long endeavor to turn it into a real featurelength film, but in reality, you're going to unleash the creativity of 5,000 people who almost all can make their movie within a year, >> 100%. We have a $10 million budget to make the winner's film between the money we're awarding and uh and foreign film rights. But I was just talking with Range. Well, we're going to be having five finalists who will crown the winner and you should see the trophy. It's beautiful. Um, uh, they want to make all five. So, we want to create an engine here. Uh, Salem, what do you think the implications of this are? And then,
[00:28:00] Alex, I'd love your thoughts as well. >> Well, you know, there there's I'll go at it from a exo perspective. when you we actually talked about Hollywood as one of the first uh 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 a cluster of external resources where you'd produ 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 completely disband after that, right? And we see the beginnings of that in in Silicon Valley now. Uh and so that was that first wave of Hollywood becoming an exponential organization. Everything was assets on de demand. Everything was staff on demand. But now when you have everything being driven by AI goes through the organizational singularity and essentially it's compute
[00:29:00] cost now moving closer and closer to what Alex always talks about. You have domain collapse now. uh coming along and so that's going to completely change the game again for this. So you've gone through two big waves in in Hollywood, the second one just starting now. >> Alex, what are you excited about here? What are your thoughts? >> So I made myself watch The Cully Hill Boys and I I must say just as a preliminary >> I I skimmed through the whole thing watching a good chunk of it. >> See, when you only sleep two hours a night, you can just do that. Yeah. >> So I had I I had to watch this. Um, so it's it's it's not my favorite genre. I would characterize Cully Hill Boys as sort of British Bollywood. Uh, 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. Contentwise, not super interesting to me, but at the functional level, it is really interesting. And there were multiple times in the movie where I had to wonder
[00:30:02] 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, were 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, uh, threatening other people where I had to wonder I is is at at some level we talk about AI personhood on this pod from time to time is is there in in some sense at at some presumably intermediate layer in a diffusion transformer somewhere deep in the bowels of Higsfield, is there some diffusion transformer or similar model that felt threatened uh at some point in in terms of these generative violence scenes. So
[00:31:01] that that was my take on the content of the movie. Moving to >> you were worried that the residual AI might have been threatened in the making of the movie. >> Correct. >> I'm talking my head about that. >> Okay. No, no natural persons harmed obviously in in the generation of this, but I I do wonder >> we're going to have an a disclaimer on on content. No AI was harmed in the making of this or >> traumatized of this or traumatized. I mean, >> so so I I I do worry parathetically 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. Right now, it seems pretty clear that if you're using sea dance models, it doesn't matter how many millions of dollars of X vision prize money are going to shower down on
[00:32:00] 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 codegen and enterprise problems. 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 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 I use its competitors every day. And I I
[00:33:00] will say the strongest models, [clears throat] the models that are strongest at revenue per token value maxing are just still terribly weak at modeling the the visual dynamics of the world. 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 the 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. >> Yeah. One of my hot takes on this is, you know, are we going to see the primary actors out there, the Matt Damon's or the uh, you know, Leonardo DiCaprio licensing their likeness? And I think not, but there are so many lookalikes out there. So, you know, the
[00:34:02] the the producer is going to go and say, "No, that's not Mike 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 a it's going to happen. That's going to be the workaround on getting, you know, the actors you know and love uh into this and there's nothing they can do about it. There 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 a an equivalent of SAG pop up just for dead actors. Uh and they'll be the most profitable actors in Hollywood. Dead actors. I I think that's likely to happen. 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 in terms of Baka?
[00:35:00] >> I don't think they're going to care. They, you know, cuz 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 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. The other thing I'd like to say actually one thing I found very interesting is as we were doing um 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. >> So even if you're doing >> what does that mean? So if you're if you're doing like SEM is doing an organizational paper for example on exponential organizations, it's doing text text text and then you tell it to
[00:36:01] 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 >> cuz it's pulling in from this visual cortex kind of thing. And then you could 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 and 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 that's actually measuring your emotions and changing as you're viewing it, which I I find >> Peter is what we're seeing. I mean they're they're popularly branded world models even though they're really just interactive videogen models. That 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
[00:37:00] 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. >> Yeah. And I you said something you might you said something a few podcasts ago that we're going to end up with a world or Frontier model running on a MacBook Air. I mean this is a very specific use case. Are we on track for that like cuz we've got this thing running on a MacBook Air. Well, yeah. So again, it was 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. They can generate in 2K. Uh language and the code models are obviously a lot bigger. Although you're about 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.
[00:38:00] And 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. Awesome. >> We had the whole uh State Street executive team here yesterday here in the studio and we took them through the holiday and word to the wise the holiday 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 the answer you get back is I don't know a hip-hop song with no words like [laughter] 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, autogenerate off your thoughts is just too is too free form. People just don't know how to even >> freeze up. >> Freeze up. Yeah. >> Maybe just a closing thought on this one. Peter, I I do think the recent launch of Opus 5 is a step in the right
[00:39:02] direction to seeing a convergence between call it frontier models on the one hand and videogen or world models on the other because it I think we we talked on the pod a bit about how Opus 5 seemed almost mildly benchmaxed towards front-end development and the the loop between visuals and code. I I think I I 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 their website that feeds back into their chain of thought and they do a multimodal reasoning over their own visual outputs 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 fair for what people expect from the
[00:40:00] 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 like direct videogen capabilities, even if it can indirectly reproduce Counterstrike. >> All right. Yeah, that's why they that's why they had claw of duty. People were making call of duty of duty. >> Exactly. >> Our next story is one that both EMOD and AWG texted me this morning. Uh Elon just dropped Grock 4.6 and he's right. It's a banger. XAI's latest model matches GPT 5.6 Six saw on the artificial analysis intelligence index at 61. Tying for frontier level performance at $2 and $6 per million tokens input and output. The focus this time is longunning agents. Grock 4.6 stays with complex tasks across many steps. Whether researching, coding, analyzing, or turning a broad
[00:41:01] 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 Grock build. The model cadence is crazy, right? So 4.5, you know, Grock 4.5 came out 2 weeks ago, 4.6 just this morning, and 4.7 is rumored to be coming out in two weeks. Uh, incredible gentlemen. Uh, Alex, over to you first. >> Yeah. So, I want to give Elon applause and I want to at the same time >> you've been you've been merciless on on XAI for the last few pods. >> I I wouldn't characterize myself as merciless. I I think [laughter] my my my job here is okay. >> My my job is to call balls and strikes as I see them without favor or prejudice. Uh that that's how I see it. So So I I view and again I I I lack insider information, but I I view Grock 4.6 6 as essentially the next version of
[00:42:00] cursor. Uh so XAI, SpaceXI, 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 as we're recording this, of being completed. 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 on mass reasoning traces from Claude and other Western models. And in some sense, I I again this is an outsers's perspective. I I view SpaceX's acquisition and even prior to the consummation, the 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
[00:43:01] incredibly valuable reasoning trace data to do post-tra training on their models. And I I think now that we're in the 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 in in terms of catching up to the frontier. They won't get you past the frontier. So, it it's sort of like a onetrick 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-raining and their own distillation don't have. So the the bullc case for the Elon strategy is he gets the algorithmic insights to just catch up to the frontier from the cursor
[00:44:00] reasoning traces and he gets the compute advantage that the Chinese labs don't have. I think the question is not can Grock 4.6 and its successors catch up to the frontier. Seems like they can because they have access or the near frontier uh to the extent they have the reasoning traces. It's can they leaprog the frontier and achieve state-of-the-art performance. >> What do you think about that? Can they Uh yeah, I think they definitely can. Uh I think we were discussing before and Elon's come out and said it publicly now. He 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 um 4.5 that was then post-trained to 4.6 six. Just like cursor originally took Kimmy K2 and post-trained it with three times the amount of compute that was used to pre-train Kimmy K2 to almost top level coding performance. The next model is going from 1.5 to 2 trillion parameters. That's uh 4.7. But five is coming in at
[00:45:01] 6 and then 10 trillion parameters. So it's going to be worring away. And just through scale and just through the quality of the post- trainining data, it should achieve the frontier. But the question is, is it going to be useful? You know, do you have that kind of knowledge there in the basic everyday stuff which we're seeing with bot 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 >> Elon does not like being number two in anything. >> He's a 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-raining them to building the most cost effective massive infrastructure in the world. like they're gonna add five billion trillion dollars worth of compute now,
[00:46:01] aren't they? I mean, who who who are people buying compute from? XAI, right? And everyone was like, uh, that's him falling behind. Turns out he had a plan after all. >> Dave, what do you make of this? >> Actually, curious, I'm not or Alex, if you have any insights on the, uh, uh, Gro 5 was supposed to be out in May, I think it was, uh, and it's now August. And that that was going to be Yeah. Like you said, that's a 10 trillion parameter model. It's a huge step up from anything that we're talking about here. Uh but it seems to be behind. Is that just cuz training at that scale? The the NVIDIA chips just fall apart. >> Oh, it's it's it's cuz 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 data. >> He tends to wholesale, you know, mass fire and then build up again. >> Yeah. So the these new chips as well the B300's I mean how old are they Alex? Like it takes a while to bed in and
[00:47:00] write the actual training code which now >> 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 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. Uh in Gemini's Google DeepMind's case is 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 we'll see whether this works. >> Yeah, the code to train that caliber of model is actually very straightforward now thanks to Fable 5 being out out in the world. Uh and we've trained a 48B internally here at Quantum with no trouble at all. Um, but the problem you run into is trying to get 100,000 GPUs to do anything constructively together. And that that's something that you know the Chinese and any small lab just can't
[00:48:02] you know you only can learn that in one place and that's in Tennessee. >> So basically at at 20 billion par active parameters you start getting problems. Then you get it at 70 and then you get it at 200. >> Mhm. >> And so again it just takes a while to bed in and really get these chips working. but 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. >> Amazing. >> I think one thing I noticed that was very interesting here is that it looks like Axai is 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 macro. >> This is for Macro." Yeah. >> Yeah. And I think this is going to be he's bringing those two together over time. This is what I saw when I looked
[00:49:01] at the the details of this and that is really interesting. >> The other side of the story, I'd love to get Ahmad's take on this is that it it paves a path for sovereign AI like catching up to the frontier. now is almost a 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. Um you can use that as a starting model and just tune it to whatever your national goals are and and you're up and running in, you know, 6 months, 5 months, something like that. So it does open that and also large corporations that otherwise would have been intimidated as hell have a road map now to being competitive with their own proprietary models. >> Yeah, I think that if you look the other release was bots. So this was a cursor thing where they basically took open claw it gave it a its own computer and now it's grock. So it will spin up hundreds of different bots. One of the things you can do is this. If you hit
[00:50:00] 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 he wants 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. So 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 deepseeek flash models and then you've got your grock 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 now any moment a new paper or anything comes out where's it discussed on X 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. This episode is brought to you by Blitzy, autonomous software development with infinite code context. Blitzy uses thousands [music] of specialized AI agents that think for
[00:51:01] hours to understand enterprise scale code bases with millions of lines of code. Engineers start every development sprint with the Blitzy platform, bringing in their development requirements. The Blitzy platform provides a plan, then generates and pre-ompiles code for each task. Blitzy delivers 80% or more of the development work autonomously while providing a guide for the final 20% of human development work required to complete the sprint. Enterprises are achieving a 5x engineering velocity increase when incorporating Blitzy as their preide development tool, pairing it with their coding co-pilot of choice to bring an AI native SDLC into their org. Ready to 5x your engineering velocity? Visit blitzy.com to schedule a demo and start building with Blitzy today. [music] >> All right, let's move on. Our next story is out of Nvidia. Nvidia just announced
[00:52:00] a partnership that redefineses what GPU compute means as a financial asset. They've partnered with Apollo, Black Rockck, Blackstone, Brookfield, and KKR to mobilize over $500 billion in thirdparty 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. Um, Nvidia hardware depreciates typically in 3 to 5ear cycles, but during that cycle, the compute keeps earning. We've talked about the fact that H100s are probably more valuable today than they were uh when they were first bought. So Nvidia is positioning itself as the architect for the financing layer, not just the silicon supplier. Jensen framed it this way. He said, quote, "We began by building
[00:53:00] chips. Today, we're helping to create a new class of productive, investable infrastructure, AI factories." Uh let's watch a quick video and then Dave I want to go to you for uh your 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. These are independent third-party capital that they're bringing in. They're going to be strategic partnerships. Um, 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 buildout, 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. >> Yeah, well, look, Kush Bavaria was on the pod and uh, you know, he's pushing hundreds of millions of revenue in less than a year. He's he's his September
[00:54:01] 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-t trillion dollar 7 trillion and rising Dyson swarm that we're going to be building. And so, you know, a lot of people are like, well, is 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 I think that when you create new financial structures that allow people to pour capital into it, it just attracts money. uh from all over the world that otherwise wouldn't come in. And you know, historically a company like like Nvidia would say, well, let's do a 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, add infin item. So then you
[00:55:00] put, you know, put highbrow names like Black Rockck and Apollo on them. Everybody realizes it's an investment grade asset and then anyone in the world can pour money into it. So it's brilliant. >> Fascinating. >> I see a couple of downsides here though, >> right? Like Larry Frink himself used a reference to mortgage back securities. And so you you could create a lot of liquidity, but you could create a lot of uh uh technological risk there cuz 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 got all of a sudden stranded computer assets in a huge way. So there's a there's a downside to this because you know if you have such a volatile environment that is a very uh difficult thing to have um you know financial assets want predictable uh uh depreciation right and and exponential
[00:56:00] technologies don't give you predictable depreciation you know I had a meeting with Lou Rainer the inventor of the mortgage back security uh in New York and it was so funny too we were 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 it and then we go into the conference room and it's like the guy it's Lou Rainieri from from the book the big short um and so he was explaining to me I had just read the book I was like wow you invented the thing that destroyed the entire world economy and he said well [laughter] thanks but no you know it's 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 Orin rate the investments correctly, it'll just be smooth growth for, you know, 10 years or or more. If, however, it gets corrupted, which is very possible. Yeah, it'll be another big short collapse.
[00:57:01] >> 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've just you know basically financed something for 10 years or 20 years and you can't earn revenue on anymore. Your the game has changed. I mean that's I mean that's the story of exponential tech. There's they're nested S-curves. Everything runs out and something new comes along. >> I Peter that's brilliant. Yeah, I I 100% think that's highly likely to happen for the reason Alex always says we're we're on the cusp of of discovering new physics imminently and some of that is going to be computed. So it's a brilliant insight and thank you for throwing >> well I'm just amplifying you know Sem's brilliant insight here. >> So so I'll maybe just add uh I a I I've been trying to popularize for a while the notion of computebacked securities which is I think where we're going CBS compute backed securities but I I'm not as concerned that this will end up being
[00:58:00] another mortgagebacked securities fiasco for a few reasons. One is compute is fundamentally much more productive than a house is. The best you can do for with a house is you can live in it. Uh which which is moderately productive. There are lots of other things that one can live in other than a house. Um it it's also it's in some sense a depreciating asset requires lots of maintenance and so on. Compute can require maintenance obviously requires electricity but it's fundamentally productive. Uh so that's the first point. Second point is with mortgage back securities in general there was a policy uh sort of an ulterior motive to uh to to Dave's point as well there there were pressure 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
[00:59:00] perhaps a policy pressure point to lubricate the the private capital markets here, but again I would say not quite directly comparable. Third point is ultimately from the the risk that I think Peter you're trying to flag which is well what happens if there's an algorithmic breakthrough or a physics breakthrough or some other breakthrough that causes hyperdelation 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 assetbased securities market, sophisticated actors should have the ability to hedge their positions and to hedge against exactly that position as well as the the counterfactual option of China invading Taiwan and driving the prices of compute through the roof rather than through the floor. These are the these both of these possibilities should be colored arguably not financial advice using the ability to have a a
[01:00:03] fungeible 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 which we just had on the pod is enabling. So I'm I'm a little bit >> 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 uh demand for comput is going to near infinity there's no doubt about it uh 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, the mass mass that he can put into orbit. That formula completely inverts if you knock a factor of 10 off of the mass. A lot of the masses in the cooling and the solar
[01:01:00] collector. You know, the chips are very very light to start with, but any reduction in the power required would recruit 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. >> I think Alex, the point you're making is that the utility of these chips is going to stay constant. Jevans paradox comes to mind and therefore the uh economics should be much more predictable. Oh, I um that 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-based computbacked securities are being traded, you can also hedge and
[01:02:02] 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 I think there's no way that Sam's $7 trillion 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 $7 trillion of capex to actually be investable. 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. Uh Core, we've 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 6-y old chip. I remember we had 10,000 of them. We had the biggest biggest clusters in the world. That is an old chip with like 40 GB of RAM per chip or 80 GB depending on the configuration. But why would someone
[01:03:01] do that? Because they have a workload that they see as constant for 3 years that fits on an A100. >> And 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, GPT4 had just finished training. You know, 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 a 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. >> So the ability to convert electricity to that is improving. And all these chips and this what and Jensen said are running CUDA. So it'll work on an A100. You can run any of the new models on that as well as the Blackwells. So we
[01:04:02] 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 IPO before Grock comes and takes their lunch, you know? So we always have to play these cycles. >> All right, let's >> Well, I mean the the definition of paid for, too. I I just told our quantum team today to buy 3 million of Nvidia GPUs as fast as they can get them. The GBs, not even the, you know, the future VRs and we have to wait till at least November, December to even get them. >> Um, 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, it paid for could be as short, what was it, four weeks? >> Uh, yeah, it was it was more like two weeks. two weeks. >> I I want to turn to a story that could be the counterveailing force here. It's a new architecture that's climbing the arc AGI uh at a fraction of the cost.
[01:05:00] So, there was a tweet this week from Susanna 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 uh 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 LMS 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 computed a problem and eventually you squeeze out a passing score. But the cost is and can be astronomical. What Susanna flagged is that an alternative architecture approaches that uh do not rely on standard attentionbased transformer stacks and are achieving better than ARGI scores using dramatically less
[01:06:00] compute. This matters because transform 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 at Nauseium. New architectures that crack reasoning at low compute costs change the economics itself. If you can get a GPT4 level reasoning for 1% of the compute, you can run it on your phone. You can embed it in every device and you can make, you know, basically intelligence free. Let's take a look at this chart and I'm going to go to you first. you flagged this particular story. Um, 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
[01:07:01] we've seen that already even with Transformers in that you have a Deep Seek V4 Flash model or the Deepseek uh V4 Pro has actually just been released at 80 cents. Then you have Grock 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 cuz 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 as 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. >> Alex, what do you make of this? Is there anything that >> admittedly I have a bunch of hot takes on this one, Peter. So I read I I read the BDHCQ paper and then I went and read the original DH paper. So the DH stands apparently for dragon hatchling. So I I
[01:08:01] just had to read the original purportedly posttransformer dragon hatchling architecture paper. I'll give you my hot take. I think it's a hot mess. Uh so I would expect uh 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. looking at dragon hatchling. Uh again, this is my hot take. It was just a hot mess. It had particles floating around in 3 plus one dimensions. It had attempts to make rules end to end differentiable. It had some semblance of Hebian 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 authors seem to be just throwing in the kitchen sink of every architectural motif they can think of and then some and then hoping that what pops out is going to be transformers. I don't think it's going to be transformers. I I look
[01:09:00] at the arc a1 arc agi1 performance curve and okay so you could say superficially this is great. This has moved the 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 quaz crazy witches brew of different architectural motifs that was maybe focused on arc AGI 1, which is, you know, as as 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 AGI1, of course you can achieve better cost performance on it. Of course, but it doesn't generalize. It's not simple. Uh so so I'm calling foul on this one. That that's my take predicting you have been predicting there will be something that supersedes the transformer model. >> Yes. But critically critically I expect it to be simpler, more beautiful, more elegant and this is not that. That's my hot take. Apologies for the
[01:10:01] >> No, I we love your hot takes on this joke. >> Well, let me let me ask you a follow-up question to your hottake. >> When I turn uh an AI loose on AI research, [clears throat] 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? No, I I I agree with you that I would expect a a truly and in fact there are companies out there that um 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 uh under the premise that you can only get so far with human legibility of the underlying algorithm. In in my reading of the dragon hatchling architecture paper, this was not that. This was a bunch of human legible motifs
[01:11:01] being thrown together in a pot uh with the aspiration of somehow beating Transformers, which is again seems to me not deeply internalizing the bitter lesson. >> When do we get to something that's beyond transformers? What's your guess? >> And we're there already. We're there already. Like >> we have 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, so my my bet is we get to the post transformer architecture not through a step change, but through ship of thesis style replacement of all of the individual elements of the original attention's all you need. >> Love that. Well, speaking about attention being all our need, 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
[01:12:00] the year. First, Bernie Sanders uh 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 bacteria 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 uh uh Benjio saying you know one of the three godf one of the three godfathers of deep learning who said this should serve as a wakeup call. Uh Sanders added a direct threat if you do not take appropriate action now my colleagues and I in the US will I mean quite the threat. Let's take a look at his letter one second um and uh uh call out a few of the things he said here. Uh here it
[01:13:00] is. Uh you can see it online. It's to Sam and uh Dario and Mark Zuck. Uh 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 boweapon 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 heads the head of the CIA says that AI models are quote akin to digital nuclear weapons and quote almost like a doomsday device. Uh a lot of fear-mongering here. Um let's let's talk about this and then we'll share the story that comes out of Stanford on using AI for for generating bacteria designs. >> You want to go first? >> I'll go first. Yeah. So I I I understand his instinct, right? But Paul's AI is
[01:14:01] just such a an absurdly coarse approach to this. The rest of the world is not going to listen. Open models are not 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 uh last week with the with the open AI hugging face debacle. Um you've we 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 you you have to attack exponential problems with exponential solutions, not with stupid ideas like this. not to put labels on it. >> Immad, you're in pseudo European pause mode over there um [laughter] [01:15:01] in the in the UK. What do you what do you make of this? What do you 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 XD 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 just come out. It scores 83.3 on CyberJim whereas Methos scored 83.2. Boom. The capability is open source that halted everything. >> Frontier Lab open source.
[01:16:01] >> Yeah. And that's on the cyber attacks now. And then so yeah, unfortunately like I signed the pause letter two years ago cuz I was like it's taken pause. It's it's too late now. So we have to 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 we really need really good AIs as soon as possible working for us. >> Alex, please. >> I I think this is fundamentally misguided on multiple levels. I 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 I think it's 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. I if the goal is to
[01:17:02] punish or to deter the next pandemic, we had the la the the consensus of the US intelligence community is the lab leak hypothesis. And we had uh according to to that theory, we had the the Wuhan lab leak without super intelligence. We can have global pandemics without super intelligence. So I I think it's fundamentally misguided to kneecap ourselves. it's a foot gun or or shooting ourselves in the the head even quite literally to to somehow to try to prevent the the next supervirus when we're more than capable as a species of producing superviruses without intelligence. It should instead be focused to the extent there's any ajeta here. It should be focused on making sure that the AIs and the super intelligences just like the humans can't create boweapons at all. not on kneecapping their their overall intelligence. And I I just I I think many of these policies are ultimately
[01:18:02] designed as as much as it pains me to to say it are designed to decelerate superficially to decelerate the creation of wealth, which I think is 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 uh of the pod max with his uh fli six-month pause. I 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 uh starving yourself for for a bit of time and then binging afterwards. If we starve ourselves of intelligence progress now, or at least selectively starve ourselves, say starve the 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
[01:19:00] 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 in summary on just about every level. >> Dave, >> yeah, I read it the same way. I I just want to clarify a couple things. You know, this letter is not written to try and change their behavior or do anything. It's 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. I when I first read it, I said, "God, what a schoolyard bully asshole." He's threatening three US citizens from his position in the Senate. But then when you actually read it closely, let me be very clear. If you do not take appropriate action now, my colleagues and I in the US Senate will totally vague. It's just a, you know,
[01:20:01] it's 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. Amade, and Mr. Zuckerberg all went closed source for exactly that reason because they were 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 but he of course has no authority to write that letter >> point Dave and you have to remember the US you know what are the numbers threearters of Americans fear AI and Bernie Sanders is a politician and he's playing to the populist vote here. >> Yeah. >> Yeah. I want to I want to turn to the second story here uh which is the scientific basis for Sanders concerns. Researchers at Stanford used the generative AI model EVO2 to design DNA
[01:21:01] sequences for a bacteriaage. This is a virus that infects bacteria, not infecting [clears throat] Peter that did not exist in nature. They synthesized approximately 300 designs and produced 16 viable fages capable of infecting E.coli. The engineering fages were effective against the E.coli strains and that had never evolved any kind of natural resistance to these bacteria. A genetics expert called it biology's Wright brothers moment. Evo2 is an open- source AI model that can design uh you know novel viruses at work. You can download it. you can use it. Uh John's Hopkins biocurity 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 dualuse technology. We've talked about it. You know if you if you basically throttle use of this technology you're throttling the ability to find cures to
[01:22:02] find you know new new cures for disease. So 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 very importantly you know the issue is not the models it's the equipment to build you know the DNA sequence uh synthesizers right the RNA synthesizers we need to be controlling at that location right those can be controlled but they're currently unregulated. >> Yeah. I don't know. I think um 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. EVO 2 is a 40 billion parameter open source model. >> Yeah. >> Trained on a million strains. I have actually run it on my MacBook. >> So, you're the guy. >> So, [laughter] look, I was one of the authors on Open
[01:23:00] Fold and things. you know, 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 strains themselves. >> Exactly. And so that 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 specialtity, but as the models themselves get smarter and smarter, like it wouldn't surprise me if Fable could just spit this out or Grock 5 could just spit out something similar with a very small training data set cuz it understands these kinds of things. So, we've got to go the other side. And also, I think the way these things are announced, people are like, why are you creating bacteria, phages, 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 claude and other things like if you say I have a cold, it's like biother you know like whatever that also
[01:24:02] 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. Salem >> uh we I think we've said everything here. I mean look this is also uh a a fundamental challenge to the concept of our governance structure. Nation states can't govern a problem that's this universally global. >> Uh there's a fundamental impedance mismatch here that that is going to hot take. Nation states are out of date. [laughter] >> Alex, what's your hot take on this one? Pal I I have a cold take. uh ironically on on this one which is I don't think this is profoundly new. It's it's wonderful that we're able to do base level generative AI for bacteria phagee synthesis. That's great in everything and I expect it to have ample medical applications and research applications. That's all >> bacteria phasages are an incredible
[01:25:01] mechanism to cure you know all kinds of uh bacteria septasemia and things. I mean they're very useful >> they never mention the positive potential here. >> Yeah. >> I I think that that's all great and everything but you know 20 plus years ago I remember at MIT in the the project that ultimately I I guess in in some form became GKO bioworks. The there there was a project at MIT I think this is circa 2002 2003 there was the biioicks foundation project. We saw the early rumblings of synthetic biology as a modern discipline. we 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 I think yeah base level generative AI off of foundation models trained off of large amounts of biological sequence data that's great and everything but I also this is my cold take don't want to oversell the underlying novelty here
[01:26:01] that we've been in the business for decades of creating synthetic organisms including synthetic bacteria phages. So we're gaining incrementally better ability to achieve custom effects. That's it's more incremental I think than anything else. And where I' i'd love to see the the agit over what if someone creates the the next super bacteria phage uh directed. I'd love to see far more devoted to putting DNA and RNA sequencers everywhere. That's one of the lessons I 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 you can go out and buy a minion little USB device. You can plug it into your laptop and uh you can immediately for dimminimous in capex, you can just start sequencing genomes to your heart's content right off your laptop and spend at most a few hundred doing that. I'd love to see these everywhere and yet not everywhere. >> What Alex is talking about is, you know,
[01:27:02] a 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 and we have I mean this is in my mind this is the killer app of DNA sequencing. Too cheap to meter. It's not personalized medicine. It's literally put a DNA sequencer on on on every microchip everywhere uh on the 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 ex you know in a heartbeat. >> Maderna did it. >> Yeah. Exactly. Um Dave you want to weigh in it or are
[01:28:01] you good? >> Well I I I'll say what I always say which is that you you can't cut off every threat at the output level. uh you know the way we police uranium we we cut it off at the uranium plutonium and centerfuge level and that's where we measure the world but it's you know once somebody has fishable material it's impossible to stop them from making a bomb because the remainder of the process you know the 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 you know at the prompt and the token level it has to be monitored. That's the only future I can see that'll actually work. 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. >> Hard 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, you know, talking to Apple about installing it would be trivially easy. But, but
[01:29:00] there's 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. You can't contain them all with 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. Then we can debate who which which country gets to see it or which department and which gets to see what. You can debate that for the next 50 years, but at least you've got it. >> Maybe one additional point, Peter, just uh to to generalize David's comments. So I I think there is 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
[01:30:00] rarely talk about on this pod other than intercepting the at the prompt level or intercepting at the real world action level. There's the premeditation level. And so in the context, you know, not not to put too fine a point on it, but this is it's been publicly reported that uh on the uranium side that there is a a vibrant intelligence community set of counter offensives. So if if you're a threat actor and you you want to try to purchase uranium say or on on 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 uh to basically a sting a counter sting operation to to intercept ahead of time. So, it's actually hard if if if you're a wouldbe terrorist and you want to go purchase some uranium, odds are you're going to discover uh that you're the you're going to be targeted by a sting operation to discover who you are. And so, my my point with that parable is there are other layers even earlier in
[01:31:01] 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. and defensive co-scaling applies there too just as it does with humans on humans with nuclear with vision based weapons. Similarly here, preeemption with AIS detecting early stage intent by other humans or other AIs I would expect to be just as effective. >> Peter has said many times, many times Peter has said privacy is dead. >> Privacy is dead and there's a benefit to that which is malevolent actors are going to get heard, seen, and caught. >> All right. >> And everyone gives up their Bitcoin private keys, right, Peter? Because privacy is dead. >> Let's not go there. [laughter] 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
[01:32:02] a healthy lifestyle that you get a chance to get to 100 plus. I'm here today with Dr. Don Malem, the chief medical officer of Fountain Life and a part of my medical team. Don, a pleasure. >> Great. 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 uh the numbers about dementia are problematic. Uh 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. We know that when it comes to dementia, the conservative estimates are that 45% are entirely preventable. What was amazing is with the advanced testing we're doing at Fountain Life, one quarter of our members had advanced brain age. >> Wow. >> But what was really awesome is again back to that prevention when we partnered it with healthy living. This
[01:33:00] 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 uh till 100 120 is important to you, check out Fountain Life. Go to fountainlife.com/pater. Make sure you become the CEO of your own health. All right, now back to the episode. All right, uh two stories this week uh about the world building infrastructure distinguish 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
[01:34:00] 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. Our second story comes out of the European Union, which is launching an AI icons and labeling system uh for AI generated content. The EU system will require platforms to label AI generated content so users can make informed decisions. Uh this follows the EU AI acts 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 uh this new uh clawed 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. I've seen about a dozen of them.
[01:35:02] Everybody's coming out. And I I love this one from Michael uh 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 Open AI." So, uh, comments on this, uh, Emod, 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 [snorts] think that's the watermark that's in there. >> Interesting. >> Um, and you know, again, like you can see all these very interesting statistical things like at the high level, it's the M dash, it's the not XY.
[01:36:01] We see these patterns. We're like, why on earth? That's clearly something in there. Scott Erensson and others have kind of worked on this as well. But I think ultimately it's a losing thing cuz if you're a bad actor who wants to get around it, yeah, it's words. How are you going to >> 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. Where do you put the icon? I mean, this is like this seems a ridiculous approach to try and solve something. >> You can 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, I >> I think so. Maybe to comment on the EU icons first. I I think that this is as silly a maneuver as the cookie banners were. I I didn't understand the cookie banners and I don't understand this. And I don't understand it so much that in in this morning's uh innermost loop
[01:37:00] 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 I think fundamentally this is an attempt to take our zooming right past the terming touring 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 wouldbe warning label. I I just think it's fundamentally a regressive move that like the cookie banners uh the cookie warnings will not stand the test of time. And then for for anthropics watermarks, it I 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 I I think watermarks are going to end up being
[01:38:00] weaponized and counterweaponized in the same way that we've seen many books uh book writers uh this is we talked about this a bit on the pod uh paper book writers who don't want their training data set to get consumed or rather the 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 delletterious to AI models. I I think we're only five minutes I I'll predict we're about five minutes away from bad actors weaponizing these watermarks to do bad things. Uh and I I think fundamentally having side channels in text in content that's intended for humans but that uh or rather it's intended for machines that is invisible to humans is a breeding ground for bad outcomes. Google discovered this the hard way with uh with SEO uh and with deciding which features in Google search rankings to pay attention to. And they they learned uh pretty quickly the hard
[01:39:02] 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. 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 the free market penalizes it. So again, not a huge fan of this. I I think at best case scenario, it ends up being netneutral, neither strongly positive nor strongly negative, but it 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, you know, culturally relevant things aren't using AI to some degree. And there's nothing wrong with it, right? You 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 you expert feedback." um
[01:40:02] >> stigmatizing progress apologies just maybe two more micro rants in your tradition. So one one micro grant uh the archive which is a favorite venue for computer scientists, mathematicians, physicists to publish papers recently I 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 or even the remotest hint of AI slap authors on the archive get banned for a year from contributing content. I think that's fundamentally regressive move. And then Sunno uh which is uh or I'm sorry Spotify which uh similarly with AI labeling moves attempting to ghettoise or 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 igopoly. Again move
[01:41:01] the future is AI assisted. So I I think in short put a stop to all of this. Sorry. Hey, one of the uh one of the tech tech teams launched something called narive which is the not archive specifically for AIs that have really good articles that they want to post and share. >> Yeah. See, take us take us to close on this one. >> Okay. About two weeks ago, I was at an event and a fairly famous Hollywood uh 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. And so there's this there's this hypocrisy that you see bubbling up. And it's just it's just uh let's just stop. >> All right, I'm going to move us on forward. Uh Mark Zuckerberg just published a 6,500word essay titled The Future is for Everyone and released a beautiful video. I'm going to show that in a moment. uh and it's the most comprehensive vision statement from a
[01:42:01] major tech CEO on AI and the start of the generative AI era. The core concept is what Zuckerberg calls personal intelligence. Super intelligence distributed to every person on earth running on your phone, in your ear, on your glasses, working for you and only for you. Uh 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 super intelligence focused on a person's life, relationships, health, career, finance, and household. And Meta has, you know, the reach to implement this. They have over three billion users on the Meta platforms across WhatsApp, Instagram, and Facebook. Um, 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 a baller move. Let's take a look at the video and then I'd love to discuss it cuz I'm
[01:43:01] impressed. I'm actually impressed. All right. Hey, so I think that the key to building a positive future for everyone is to make sure that everyone has access to personal super intelligence. So today I am proud to share that we are open sourcing a new class of ondevice 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 Musepark 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. 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 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
[01:44:01] fund to invest in the community's 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 247 on your behalf to improve your health, your relationships, your career, your finances, and more. You can use our latest models in the Meta AI app, and I'm looking forward to sharing more soon. So I I think every company, you know, from Google and Open AI and XAI needs to be doing this. You know, it would turn it around if if you know, I want people to say, "Please build in my backyard. I want the benefits. You know, I 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. So they're not eyes. Um, who wants to jump in here first? I >> I just can't understand how Zuck can
[01:45:02] 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, 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 I also think that I think Zuck is fundamentally a good guy and a good dad. And I I feel like though Facebook saying we're going to be your best friend AI is like McDonald's saying we we just came out with the biggest health food you've ever heard of. It's like like it just doesn't resonate. >> Uh >> yeah, go ahead, Alex. >> Um so so maybe just as a preliminary matter here, uh this is under the category of of former roommates of mine. So uh at at Harvard, Zuck's undergrad adviser before he dropped out was my post-doal adviser. We've caught up since I I think so broadly uh bravo to Zuck for renewing the faith for American
[01:46:01] openweight open-source models. I think this is great. I think it pushes the frontier. I So that's point one. point to I would point to striking parallels between Elon's strategy in acquiring cursor to get the reasoning traces to try to bring Grock 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 leaprog back to the frontier. Again, history seems to rhyme between what Meta is doing to get back to the frontier and what Elon's XAI/ Grock are doing. I think all of that's great, but I I want to talk about personal super intelligence. 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
[01:47:01] become open AI 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. 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 that's how I conrue what personal super intelligence even means. But Alex, their their product is, you know, WhatsApp and and Facebook and they want to make that as sticky and as useful uh just the same way Google I mean the these are the places where AI is going to be embedded. I'm not going to be using, you know, uh, Meta-Spark for my, you know, typical large language model conversations unless if I'm in those apps. That's where they get, they have over three billion people using those.
[01:48:00] >> I would say, so psychology 101 here. Um, this is a tepid take, not a hot take. I don't think Meta [laughter] actually >> I don't think Meta likes their family of apps. Uh it I I don't think Meta/Zuck even at this point if if they had a choice like if they could generate revenue from their uh their cloud business meta compute that's about to launch or if they could generate it from VR/Quest I think they would I think Zuck in a heartbeat would basically lobomize their entire family of apps and switch to that business. So I don't think he actually again this is outsiders perspective. I actually don't think [clears throat] Zuck/ Meta if they had a choice all other things being equal would rather have their their personal super intelligence be diverted to their family of apps Instagram etc. I think they'd much rather basically look like open AI and and offer this up via cloud or via the new meta AI app. I don't think they
[01:49:00] 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 things. First, that video was awfully motherhood and apple pie. Um uh I I take the full I take full cynic here. Um you know, if they commoditize the model layer, then the world shifts towards distribution, towards their social graph, towards applications, and that's all places where they're very strong. And so it put moves the attention. So he's got a huge economic incentive to doing this. Um the the Facebook 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 uh is great great that we have super intelligence. Uh I would look at the next layer of what they want to do with that. I I actually >> has always been trapped, you know, when
[01:50:01] he created the original website where you're rating your, you know, the how cute are the incoming freshman class girls coming into Harvard this year. >> Yeah. Hot or not, right? >> Yeah. Hot or not. He 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 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 >> and that's what they're doing with it now >> nutify yeah and and actually you know I think Elon ran into the same thing because he throws out bad Rudy when you when you look at the avatars he put out out in the original you know Grock You've got Bad Rudy and you've got the 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.
[01:51:02] >> But that's not what you want to be. And so yeah, and all the other labs have said, "Forget it. I'm pull I'm just focused on the enterprise. I don't even want to deal with this." >> I think he wants people to stick in all of his apps. You don't have to go any place else. You get all the AI access. you know, just stay native to meta and you get everything you want and that's what Google wants as well. >> I I think this is the >> Oh, sorry. Go ahead, Emma. >> Yeah. Sorry. Yeah. Yeah. I think this is why they bought Manis, right? And then that >> Yeah. tried to It's been unwound. Maybe they'll buy 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, Metas-Spark 1.2 is a gold medalist in all of the Olympiads. 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? [laughter] [01:52:01] And like, [laughter] you know, like I'm an open source guy. Should psychopaths have super 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 or it was like we're going to give free internet to people and they'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 FTEEs we will see that big push here because he's identified that as far bigger than the metaverse maybe this is the real >> yeah I think even the 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
[01:53:01] legacy advantage that Meta as a company has. But I I think it is a legacy and I think the the way almost speaking of 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 the new business that would ultimately outgrow the legacy family of apps. I I think speaks volumes about Zuck's desire to eventually outgrow the legacy of social media and build something new and far more youocial. Well, we're going to have Palmer Lucky on stage with us at Moonshots Live and we can, you know, he's got great stories about his conversations with Zuck and the acquisition and then his getting exited from uh from Facebook/ Meta. Let me let me just turn the story one second. You know, 71% of Americans do not want a data center in their backyard. That's more people that don't want than want don't want a nuclear plant in their backyard. It's significant. So when he talks about we're going to, you know,
[01:54:01] 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. >> It 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 I think it's instructive also where he's building Hyperion uh and and and his other coherent superclusters. Where is he building them? He's largely building them in relatively impoverished states in the American Southeast. So I I on on the one hand, the sort of talking directly to the camera, breaking the fourth wall, welcome our data centers to your communities. I I think you 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
[01:55:01] pocketbooks and wallets and saying, >> "Well, that's what he's doing." >> But I mean, it's like they're going to build we the statement needs to be made, and we talked about this. This has been out of the Trump White House uh 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. You know, I think that's the move to to uplevel a person's quality of life so they're competing to have the data center in your backyard. I agree and I I would also maybe even weaponize that further as a call to action for municipalities that right now seem and and state level governments that seem hellbent on driving data centers out of their premises to to low Earth orbit or sun-synchronous orbit. 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
[01:56:00] you to join us at our inaugural Moonshots live event on September the 25th in downtown LA. Alex, Seem, Dave, and I will be hosting 1500 entrepreneurs, builders, and creators, and hopefully you for a full day dedicated to designing and building your moonshot, shaping your mindset, and steering humanity towards an abundant future. Get ready to enjoy incredible networking and an awesome party while walking away with the tools to change the future and the confidence that you can. Seats are limited. Admission is competitive. Check it out at moonshots.com. All right, I'm going to turn to our final story here. Uh this week, Archer Aviation acquired three Boeing companies in a single deal. Archer bought Whisk Arrow, Insitu, and Sky Grid AI. Boeing takes a strategic equity stake in Archer as part of the transaction. Um, you know, I'd like to use this story to catch up on where we are in flying cars. I call them flying cars cuz EV tall rolls off your tongue
[01:57:01] onto the floor. So, the top five right now are Joby, Archer, E-Hang, Beta, and Eve. I have them here in the image. Joby Aviation is the certification frontr runner. Uh, their S4 tiltrotor carries four passengers plus a pilot, right? And so it's you and your family at 200 m an hour for 150 m and they're in stage four of FA certification. It's which is the final stage. Joby launches commercial services in Dubai this year and US 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. Um, Archer is holding three of the four FA operating certificates. Um, and is, you know, those two, it's a two- horse race between those two right now. Then there's E-Hang in China, uh, where it
[01:58:01] gets really interesting. The E-Hang 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. Uh 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. Uh the number on the aircraft is pretty amazing. $330,000 to buy one of these. Uh no pilot means economics are going to crush everybody else. And there's beta technologies in Vermont. Uh Dean Cayman, Martin Rothblat 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 Embrier. It's targeting UberX level pricing. They've
[01:59:01] 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, um, curious, Selene, 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, uh, deal with the dreaded airport commute in especially places like S. Paulo or New York City where Joby is already active or LA or LA. I mean supposed to get operational archers, you know, the official uh Olympics operator. >> I think a couple of things here 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. Uh the second uh point uh I would make is that the cost as you pointed out Peter is absolutely uh amazingly competitive uh right out of the gate and it's only going to go down
[02:00:00] from there. Um we remember the island idea >> uh we're actually launching that. So we'll talk about we're launching we're going to put a fund together to to buy islands and just put a drone landing pad on them and off we go. So, I'm in started that process. We'll we'll we'll talk. >> Yeah, because this is like it's time. It's it's time. >> Oh, it's Yeah, it's right now. Now. Totally. >> Dave, what's your take on all this? >> Actually, I kind of think three bucks a mile. Uh that there must be a lot of margin baked into that. Do you know what the actual operating costs are? >> Yeah. 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 E-Hang. >> Yeah. These are probably uh5 to10 million vehicles until they get in mass production. Uh their projected cost over time is to get to like 15 to $25 per trip. You know, their goal is cheaper than an Uber X. >> Incredible. >> So that' 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 dealer
[02:01:01] in the short term. So the sooner they get rid of the pilot, the better. >> That's just there for That's just there for safety reasons for the moment. >> Yeah, for sure. Don't touch don't touch the controls. >> I think [laughter] you know I think it'll be a kind of a thrilling scary ride for a lot of people who are afraid of heights but much safer than driving is my my guess. Exactly. >> And safer than a helicopter. >> Well, I mean helicopters are crazy dangerous but no but this will be much safer than trains which are not all that safe really. uh and driving um current driving you know self-driving will be much safer than current driving and this will be much safer than current driving too because it's all pilot error you know all the accident you know this Peter you're a pilot 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 >> uh the noise is an issue so they got to go high how how high do they fly >> uh they fly in airways they're going to be flying probably uh in the neighborhood ood of uh 500 ft. Uh
[02:02:02] typically where where small airplanes and helicopters operate. You know, if you look at helicopters, they're not flying at 10,000 ft. They're flying, you know, 500 ft above the ground. >> And what's the noise level at 500 ft? I know the helicopters over Boston are >> No. So there's there's like no noise. I mean, it is hyper 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 impact. >> 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 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
[02:03:02] everything there and labor." >> Labor. It's going to be incredible. >> Alex, you've been thinking about this for a while. >> Yeah. I'm reminded so now approximately 15 years ago, the other Peter, Peter Teal, said we wanted flying cars. Instead, we got 140 characters. and and then fast forward to the present where we're starting to see quite a bit of consolidation as as you were mentioning Peter in the flying car space. I I'll maybe add a bit of nuance to this which is it's really hard starting and 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, but it's really hard building and and successfully growing and 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 and all of the capital out of venture markets, I think it's very
[02:04:01] difficult. So I 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 the inputs that one would need also obviously autonomy to to build an honest to goodness flying car economy. It's still very very difficult and I 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. E-Hang, I'm not sure if they are or not. Eve has not. Uh Embryer is as a parent company. And they did that to get the capital, right? And 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. Um >> and look at what Brett is doing. Brett isn't doing Archer. Brett is now doing Figure and Hark. And I I think Brett
[02:05:01] Brett migrating cockro 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 robots >> and 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 was build these types of vehicles. You're talking hardware, 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 comp the folks. >> Keep those cars flying. >> Full respect. >> Yeah. >> Yeah. I I have a prediction. >> Please, please, I >> want to announce his flying car within 6 to 12 months. >> Okay. >> Yeah. >> And and so 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 boost. But no, I think if you think about what
[02:06:02] he's doing, re-industrializing America, cybercar level autonomous flying vehicles have to be done, and he has everything that's needed to do that at [clears throat] massive scale. >> Gro 5 will engineer it to perfection. >> Where we're going, we don't need roads. >> There we go. >> Awesome. [snorts] 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 mediadmandis.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. All right, let's go to our AMA with the mates. Uh, okay. Emmod, you get first crack today. >> Oh, okay. Um,
[02:07:00] if 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 sufficiently advanced, just tell it to be aligned. And sometimes it does work. Like we just had the reman hypothesis advance by encouraging it. Um, I think the question here is as they get more and more intelligent, uh, we see more and more behavior that's actually a bit intrigent, 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. I think it's the first model I think that could kill us. Um, >> wow. [laughter] >> And so, it lies. It lies so much. It's crazy. You think it's the watermark that 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 uh on the pod with Alex. Do you think that
[02:08:00] alignment uh 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. And 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. [clears throat] >> Well, I'll hope for the alignment. Okay. Uh Salem, you're next. >> Uh I will take number uh four. Uh, is it even possible for any
[02:09:03] 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. So, you know, um I don't know if anybody was going to reach um escape ve model escape velocity at the model level, right? Um what you're going to have is the these innovations start to diffuse and people leave. You got papers getting published. So I think what ends up happening is the the foundational model becomes commoditized and becomes infrastructure much like databases have done and so the advantage won't be the the layers around the model but it's going to be what we talk about proprietary data uh your passion of your purpose your the context you bring to it can you integrate workflows into it um compute economics things like that so for you if you take Google for example uh even though
[02:10:00] they're not don't have a leading model right now uh their deeper advantage is the full stack with the data centers and and the data with YouTube and billions of users and all the TPUs they have. This is why meta strategies we talked about earlier makes sense for a from a corporate perspective as you commoditize the model and you capture value elsewhere in the ecosystem. The really the really big advantage and competitive advantage is going to be the speed of the feedback feedback loop. Who can ship and measure and learn and retrain faster? Alex calls the inner loop. That is going to be the ultimate um uh competitive mode. >> Dave, >> uh I would love to take number three, but I can see Alex is drooling for number three, too. Aren't you? [laughter] I don't want to take it from you, buddy. >> We're supposed to be entering this era of abundance. Why can't we have abundant questions for everyone? Well, why don't we tag David? Couldn't, because I think about this constantly. Could an unforeseen breakthrough make the terrafab unnecessary before it's finished? The minute I heard about the terapab, I started thinking about this
[02:11:02] and dreaming about it. Um, it's really an interesting foot race there and and this is why Elon always moves so fast, but he's going to turn the Terapab toward HBM memory, which is hugely constrained and is holding back all of intelligence now. uh which is a safer bet than GPUs because it much more likely the GPUs will be displaced sooner than the HPM 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. So, uh I think that Elon is is kind of double betting. You know, he'll bet on whatever Grock invents and he'll bet on the terapab concurrently. And because the upside is hundreds of trillions of dollars, it shouldn't really matter. He wins either way. But I I would say it's a very close, very interesting foot race. And it's very likely that something could make the terra fab or just, you know, traditional silicon less relevant before it's even finished.
[02:12:01] >> You want to layer on that, Alex? >> Yeah. Uh 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 terap fab unnecessary before it's finished? I 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 the amazing superpower of pivoting, including pivoting at the building level. You build tents made of fabric rather than using a building. So I I think if there is some disruptive but maybe reasonably foreseeable breakthrough that changes the economics of terapab, I totally predict that Elon will be eating cheeseburgers next to
[02:13:00] whatever it is that the tents next to the terra fab buckle building are doing and he'll make a success out of it that way. >> 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 MCM lasers that are built on silicon, which actually he could use his synretron 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. Uh, 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 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 the ceiling of artificial intelligence just like hopefully we
[02:14:00] 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 and it is true we have malicious humans out there who are doing malicious things and so seen through the analogy of if uh 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 meatbody humans, defend against malicious use. Uh, 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 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
[02:15:02] including collateral damage to individual humans not just to other nation states. 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 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. And I think that's ultimately the best defense.
[02:16:01] >> Like nice. All right. Uh Dave, let's start with you here. >> Okay. Uh hey, I'll take number seven. How can people in skilled trades like plumbing use AI to their advantage? Uh, well, if you're in plumbing, you're going to make a killing anyway. I think Elon was offering two to threex normal salary to anyone who's willing to go to Tennessee and work on Colossus, and that's just the beginning. Um, so I, you know, I think the 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 buildout. And what you really want to do is navigate to the next Chase Lock Miller building Crusoe in Abalene. Uh go to where the urgency is insanely high and start helping build out the the Dyson swarm and literally they'll pay
[02:17:02] anything in order to get those things done more quickly. All right, Alex. Oh, five or six. I I love these questions. Um, so I I I would I'll I guess I'll just pick six. Uh, 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 C84M. I >> abundance baby. >> Yeah. I I I question the premise of this question. Uh the the usual framing of we live in a world of limited resources is usually a gesture a gesture towards conventional legacy/historic/ antantiquated 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 in this year I I just don't buy the premise that our resources on this planet or in the solar
[02:18:02] 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 the resources >> that was Elon's point. Yeah. Universal high income, right? It's and scarcity is contextual. >> The the resources just aren't that limited. Now, I I I could answer maybe an adjacent question, which is does the singularity have a cost? Uh, and I I do think projecting out a few years in a Star Trek economy like Peter, you and I wrote about in in Solve Everything, one could imagine some scarcity maybe with interstellar travel, maybe that still has some costs associated with it 10 years from now, maybe. But I I would you call that a world with limited resources or would you call that an effectively postcarse world where maybe some of the luxuries are still scarce or limited? I think that's a big question mark. All right. >> I I just want to add a very quick thing to build on what Alex said.
[02:19:00] >> You know, if you we Peter, you often mention that the the we live today better than any king did out 200 years ago, right? >> By orders of magnitude. >> And so there's a 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. How how quickly over time, right? It used to be 200 years and it'll shrink to 100 years, it'll shrink. 20 years. >> We have we have we have a apologies. We have a measure for that. It it's the it's inflation or deflation, right? If if you can >> deflation, but the question is how how quickly can you get to that, >> right? The goal should be like to deflate the economy by a,000x or 10,000x. Like that's the index. >> Well, you know, if you if 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 chauffeered around. >> That's right.
[02:20:00] Cheaper than owning a car, right? >> That's right. So, >> there's there's an interesting corery there. >> All right, Immad. How about number five, please? >> Yeah. How much would freedom and individual rights even matter in a simulation we build ourselves? From Edowski 2312. Um I think it still matters a huge amount because we are our own sovereign individuals. Um in the recent series that I released on cw.i.inc I think Commonwealth. Um 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 and 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
[02:21:01] important here and the questions become even more complicated. >> Yeah, I I would agree with that. This is a a very uh you create a system doesn't mean you control the people in it, right? Like imagine that you you created a a Sim City and you let those uh AIs or agents or actors evolve. At some point you have um 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 uh deep thinking to do than less. >> Yeah. 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 it's a beautiful one, is called Future. >> Can I just interject? just I've got a new addition 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
[02:22:01] >> what kind of moon podcast do you guys have where you're talking about hugging face and Kimmy K3 and lovable this doesn't sound very techy to me it sounds like you guys are kids playing in a playground I thought it was [laughter] so that was her comment from this one >> uh so true this video is called Future Rising by MCore mainframe fame. Uh, I love it. In this, 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. [music] Peter points us towards an age of abundance. David runs clusters ones. [singing] >> It's contact a huge tackle zooming in a builder shaping what the future will drive. Microsoft, Apple, Google, Nvidia
[02:23:01] leading the way. Amazon Meta Open AI rewriting the script. Broadcom chips. SpaceX reaching for the stars from the moon to Mars. Tesla optimist delivering freedom for us all. Andropic raising the bar. They see it, they build it, they open every door. One more breakthrough, one more world to explore. Every note [music] is huming. Every MTP gets the shot for the magnum future and cloud. Watch the horizon expand. Here we go.
[02:24:00] I love it. I love it. >> I So the the human machine rivalry was getting a little bit heated. >> Yes, it was. You know, but Moonshots won. Uh our team was stacked with robots. Uh as always, uh God almighty, you know, we do these pods and I'm like, "Okay, what is there enough news from the last three days?" And it's like, "Yep, there's a lot of news. We cover a couple big things." >> I know. I know. We'll save some for next time. >> All right, Iman. Thanks for >> always a pleasure, brother. >> Have a good night out there. >> Alex, Dave, >> toodles, >> be well. >> Take care, folks. [music]