Moonshots with Peter Diamandis - The AI War: OpenAI Ads & Sora 2, Grok Partners With US Government & Google’s Ad Business is at Risk w/ Dave Blundin, Salim Ismail, & Alex Wissner-Gross | EP #198

Episode Date: October 4, 2025

Get access to metatrends 10+ years before anyone else - https://qr.diamandis.com/metatrends   Salim Ismail is the founder of OpenExO Dave Blundin is the founder & GP of Link Ventures Dr. Alexander Wissner-Gross is a computer scientist and founder of Reified, focused on AI and complex systems. – My companies: Apply to Dave's and my new fund:https://qr.diamandis.com/linkventureslanding      Go to Blitzy to book a free demo and start building today: https://qr.diamandis.com/blitzy   – Connect with Peter: X Instagram Connect with Dave: X LinkedIn Connect with Salim: X Join Salim's Workshop to build your ExO https://openexo.com/10x-shift?video=PeterD062625 Connect with Alex Website LinkedIn X Email Listen to MOONSHOTS: Apple YouTube – *Recorded on October 3rd, 2025 *The views expressed by me and all guests are personal opinions and do not constitute Financial, Medical, or Legal advice. Learn more about your ad choices. Visit megaphone.fm/adchoices

Very recently, we've seen the creation of SORA II. We're seeing in front of our eyes the transition from algorithmic content selection and social media to algorithmic content generation. This isn't about sharing content. The creation of the content is completely up for grabs. Meta launches vibes app for AI generated videos. They're spending a billion dollars on single employees, yet they turn to mid-journey and Black Forest to build this out. The most shocking thing about this isn't how real it is. It isn't how easy it is to use. It's the fact that it's free.

That is shocking. Open AI is bringing ads to chat GPT. The AI is going to be incredibly good at convincing you to do things, whether they're right or wrong. It's a very tricky balance. And because they're spending so much money on the data centers, there's a huge incentive to get really aggressive with the advertising. Making all of the demonetization and democratization occur around the world or the ongoing. A.I. Wars. Let's jump in. Now that's the Moonshot, ladies and gentlemen.

Everybody, welcome to Moonshots. Another episode of WTF just happened in tech here with my favorite friends on the planet. Dave, Dave Blundon. Good to see you, pal. Hey. Selim Ismail. I am back. You are back. And AWG, you're back from your top secret mission. Thank God. Thank God. Are you going to tell us anything about it?

To the extent that you think that we're on the verge of a sharp takeoff, a hard takeoff, if you will, I was traveling in Europe to see what the world looks like beforehand. Yeah. So you're updating your baseline of what the world is before things go hyper-exponential. Exactly. If it isn't a gentle singularity, I'd like to know what it looks like beforehand. Okay, great. You know what I was doing last week?

I was running my abundance longevity summit. I had 50 of the world's top scientists, entrepreneurs who are focused on adding decades, maybe doubling our human lifespan. And it was awesome. So I walk away with the greatest confidence in the world that at least our friends and our subscribers are going to be hearing us talk about this stuff for the next 50 years or some version of ourselves. That is really a frightening thought. All right, everybody. Welcome to Moonshots. And let me begin with a moment of thanks. I want to just give a shout out to one of our subscribers, Bill Jacobs, 386. I'm going to read a note he posted. We do read your notes. We love it. We, this is, we're here to serve you. And he wrote, I am continually humbled by the amount of commitment and effort that's required to put this podcast together weekly. I'm not asking, asking for anything in return, nothing that is except to listen and hopefully learn before it's too late. The future is now. And I think I'm speaking for most of us here, how grateful

we are. Thank you. Appreciate that, Bill. That kind of feedback actually makes it fun for us to serve, serve a subscriber, serve all of you. Dave, do you want to say anything to that? Well, most of that thanks goes to the team behind the scenes. There's a huge amount of news out there they get scoured down to the bullets that we think really, really matter to people. And then also to Alex's agents, which are getting bigger by the day, his AI force is coming up. I mean, it's just, it's incredible how rapidly the feedback coming from that agent force is filling the pipeline of possible news. And then, of course, the human factor whittling it down.

So it's a big machine. Yeah. And we do spend a good 20 plus hours. I was up at 430 this morning. going through everything, doing my background research, and getting ready, because if I'm not ready, I would get completely decimated by the brilliance of these other three moonshot mates. Well, you know, I also, I feel like I work really hard to keep up with everything going on. Then every time the team comes up with the deck, there's like 30, 40 percent of it are things

I hadn't even heard of. Yeah. And so it's great. It's really healthy for all of us, I think, to do this. I mean, it's, I can palpably feel the singularity coming. You know, Salim, I remember you and I were on stage during the early days of singular. our university, and we would, like, update our slides or the conversation or our stick every, like, three or four months.

It was, it was, we actually worked it out as a faculty. We, the technologies between nanotech and biotech and neuroscience and robotics and so on, the content was changing 20% a quarter on that, on average. But, like, this is like 80% a week right now. So this is a whole other ballgame that we're in. It really is. I look back at our pods from a year ago, and it's like, oh, my God, that is so ancient history. South life dropping radically.

Yeah, it is. But it's becoming more and more fun. Let's jump in. I've labeled this first segment of video and audio gen battles. And let's begin with this video. Meta launches vibes app for AI generated videos. All right. Let's check it out.

Now, if you're listening to this, not watching this on YouTube, it's just music, but it's, it's beautiful imagery that vibes is generated. This is through a partnership with Mid Journey and Black Forest Labs. Alex or Dave, you want anything here? I think there are probably two stories here. One is that we're seeing in front of our eyes the transition from algorithmic content selection in social media to algorithmic content generation. It's a pretty obvious story. But perhaps less obvious story is that the space is moving so quickly that Meta was apparently compelled to partner with third parties for such AI generation rather than using in-house first-party models. So I think this is a very quickly moving space and now very competitive as well.

I was going to say the exact same thing and riffing on it. You know, they're spending a billion dollars on single employees. They have a, you know, a $600 billion, three, five-year budget, yet they turn to mid-journey. and Black Forest to build this out. Well, that's because the really, really smart, creative people all want to do startups and they don't want to join the big companies. So it's really encouraging for the startups because the other big labs are doing their own, you know, Google and OpenAI are doing their own video generation. And it's encouraging for the startups that are right in the middle of the crosshairs to say, well, even here, we're thriving. So it's a good sign.

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world's most disruptive tech. It's not for you if you don't want to be informed about what's coming, why it matters, and how you can benefit from it. To subscribe for free, go to demandis.com slash metatrends to gain access to the trends 10 years before anyone else. All right, now back to this episode. And so this is free. And the other thing that's interesting is they're generating a TikTok like, you know, swipe the video, swipe the video. We've seen X do that as well if you're watching on videos. And of course, it's not just meta. We've seen V-O-3 at Google with their video generation. And very recently, we've seen the creation of SORA 2. So SOR2's launching viral AI generated videos. And I'm going to share a video I created for myself and talk about

how easy it is to create it. So let's check this out. Suting up for the ride. Helmet's secure. Pressure is good. Viser locked. Let's make it count. Heading to the rocket. Jumping in. Cabincom is live. You're looking good. Straped in and ready for launch. Let's go. One. Two has 500 done. Double our reach every 12 months. In 10 years, we multiply 1,000 full. What else drives that curve? Compounding data sets. Each new user improves the model and makes the product more valuable. Pulling in the next way. Pair that with automation. When marginal cost drops towards zero growth accelerates on its own thanks for inviting me into the studio peter i've been looking forward to sitting down with you on moonshots likewise it's great to have

you here people have been asking for an episode that dives into ai and longevity happy to help it's one of my favorite that was that was fun to make so if you were listening here this is a version of me on the moon then a version of me pumping 500 pounds in the gym and then six or seven of me is having a conversation about exponential growth and then sitting down with sam altman for a Moonshots conversation. They didn't get the audio model right, and I'll have to record that, but it was pretty fun. Gentlemen, thoughts, when you wanted to grade me on performance? I thought a couple of things. One is, it's as you connect this with the previous story, this is like Hollywood, TikTok, Spotify, all kind of merging into one thing. And I think Alex's point was

really, really important that this isn't about sharing content. It's why now the creation of the content is completely up for grabs in a new way. So I thought all of that happens at the same time. And the interface to create it is entirely voice and prompt. There's no coding and no interface. Like all of our lives, since the computer was invented, we've been learning incredibly complicated interfaces to everything, you know, from the microwave oven to the laptop to Chrome and a safari feeder.

And all of that is about to disappear from the earth forever and just go to a straight natural language interface. And you'll see later in the pod, you know, much more important actually software creation. But, you know, after that comes building creation and highway creation and all that is going to be done through just a voice it into existence right out of the Star Trek holode. It's, it is godlike, right? First, you know, it's speaking the word and and creating reality. It's going from mind to materialization. It's extraordinary. I also think We're seeing video emerge as a first-class modality for frontier models. So right now, most people are interacting with the frontier models via text or images.

Video is still this separate channel with a separate distribution mechanism. These are on a collision course. We're going to see the video form factor and the underlying model architectures, probably diffusion transformer-based, merge into the more auto-regressive transformer, presumably based text and image models. And one could even imagine the ultimate user experience here. Maybe not the ultimate, but an intermediate UX looks something like a magic mirror that does

this in real time right now. SORA 2 takes a few seconds to generate with fully realistic audio, realistic physics. The physics, if you ask SOR2 to reproduce some generic, say, high school or college level physics demos, it's pretty amazing. So all of this ability to reason physical world models, if I ask you to think of a pink elephant, you will visualize in your mind's eye at pink elephant. Sora, too, and similar video models, once they're incorporated into the chain of thought for a frontier model will enable entirely new, I think, classes of reasoning ability. Yeah, it's got physics consistency, which is extraordinary.

So even go ahead and I want to talk about how I made those videos. I asked it to create a video of a water dropping into a glass of a water drop, dropping into a glass of water because it's a common image. It was extraordinary, how accurate it was. It was absolutely amazing. Yeah, it has real world physics modeling built in. So I encourage everybody listening to actually try it out. I mean, when open eye does this, it's creating sort of a viral engine that is getting people, you know, getting them from 800 million users up to a billion. But you need to get an invite code.

Once you have the invite code, it's super simple. On your phone, you download the SORA app from OpenAI. You basically hit a few prompts, and it photographs you speaking three words or three numbers. And then as you look to the right, look up, look down, captures your face. And from there, fundamentally, it's a very simple prompt. And if the individuals like Sam Altman or others make them. open for other people to use and you can make yourself open for use or not you can pull people into it and it's pretty easy and fun yeah the viral loop the viral loop now go super fun try it he's got

try it it's super fun the viral loop the viral loop now goes from prompt to publish to explode in no time flat yeah right you used to take weeks at least or now it's like nothing for i i saw a great podcast of Bill Gates talking about how we in the computer science world slaved away for 20 years just trying to get speech recognition alone to work. I don't know if you remember, do you remember Lee Hetherington, Peter from MIT? He's a crazy brilliant guy, like right up there, almost Alex level. He spent 20 years in Victor Zuz lab trying to make speech recognition I remember dragon systems. Do you remember dragon systems? Yeah, yeah, sure. That was one of the earliest voice recognition systems and or I mean it really is unfathomable how fast it's going and we take

the stuff for granted which is insane that's that's the point so so Bill Gates made that exact point because he had you know billions of dollars of R&D to try and make speech recognition work and now it's an afterthought in the big neural nets they do speech and then move to video then move to video generation and they move to complex math and physics all in two years I mean it's just it's just so easy to take it for granted but it's massive amounts of converging technologies that are suddenly unleashing new capabilities and so many opportunities to glue together the different components and build an incredible new experience.

Everyone should reread the future is faster than you think. You know, Peter's one of Peter's many great bestsellers, but it's all about the converging technologies. But I think when you wrote that book, you were maybe eight or ten things to consider. Now there's like 800. Oh, my God. We're just wrapped up our U.S. book. We are as gods.

And it is so difficult to look like. to send it to the publisher when you when you draw the line right when do you draw the line yeah it's insane and by the way you know vibes and soror too they're free i mean this extraordinary technology again the most shocking thing about this isn't how real it is isn't how easy it is to use it's the fact that it's free that is shock it absolutely well let's continue our journey on on on generation uh here is a product called Suno 5. It's AI generated studio quality lifelike vocals. You can basically create something that's a full eight minutes run length. And just because we're called moonshots, let's play a moonshot thematic piece called moonshots.

All right, Bond-like thematic Moonshots, Audio. Can I give us a challenge? Yeah, sure. Before the next episode, we should all play with this and come up with our own versions of what the theme song should be for the podcast. And then we'll let the viewers pick which ones they elect the best. It's a good one. the theme song for the problem you know uh nick and dana and uh the team are working in that in the

background mode so we might have just taken the workload off of them but absolutely all right that was that was my bid if you will i think it's probably also worth noting again in passing musical touring test passed we we barely discussed it anyone can compose a top 40 song or an opera and this is the beginning maybe of disposable or casual art wait what would have been the test The ability, perhaps, to generate an undistinguishable from human bond type song in this case, or top 40 song. Yeah, we just passed that. And Alex, I'm sorry, I didn't give you credit for that, but thank you for playing. I mean, one of the most exciting things we get a chance to do is play with this stuff as it's coming out.

And the good news is all of you can play with it too. So give it a shot. So for eight bucks a month, we now have a personal hound zimmer. like that's a minimum and quite a bit more yeah making all of the demonetization and democratization occur around the world are the ongoing AI wars let's jump in all right anthropic announces sonnet 4.5 claims the best coding agent available Alex would you walk us through this yeah it's really remarkable what a single-minded focus on call it code maxing or code gen maxing is doing for Anthropic with its model.

So in using this model, in testing it, one of my favorite test cases is to ask the model to single shot the generation of a cyberpunk first person shooter. And Claude Sonnet 4.5 does an amazing job. It gets nearly all the way there with minimal handholding. And I have very high confidence that some iteration of Sonnet 4.5. will get all of the way there with visually stunning graphics, music, elaborate first-person controls. I think the risk that one can perceive on the horizon is, on the one hand, focusing on code gen is perhaps a very ambitious bet towards recursive self-improvement.

If the code can write itself really well, maybe that's the critical path to an intelligence explosion. On the other hand, if it turns out that other modalities are important, like video, for example, that we were just seeing more in music, then the risk is that a single-minded focus on code gen in particular may not be critical path. And I suspect we'll know the answer in the next six to 12 months. Dave, want to add something? Well, shout out to Blitzy. The top benchmark on here, 82% on sui bench. The Blitzy got to 86.8 on that benchmark by combining models. So that'll go up a little bit now with Sonnet 4.5 under the covers. But just by hitting all the models and iterating a lot, you can actually squeeze in more

performance out of these benchmarks. And, you know, this is pretty much maxed out now. They're working on a new benchmark with MIT for long-form coding. So if your process is writing code for 8, 10, 12 hours, how do you benchmark the quality of the output? So it's a really cool new benchmark. We'll get into benchmarks later in the podcast, too, because a lot of capabilities in the world that didn't exist a year ago, we have to have some kind of metric for all of them. Yeah, I love the way these hyperscalers, these frontier labs, are all incrementing their software by 0.5, right? You know, Simon 4, 4.5, Silicon 5. We've got GROC. Where are we in the GROC? Are we at GROC 4 now? That's right.

It's probably also worth dwelling for just a few seconds on the Autumns. length scale. So Sonnet 4.5, maybe at somewhat infamously at this point, working for 30 plus hours straight. I recall in a past episode we were talking about the characteristic autonomy time of some of the bleeding edge frontier models being seven hours and before seven hours, one hour. If you had just taken meters original exponential fit for the amount of time frontier models can work independently and just extrapolated a mere exponential time, we'd be far below 30 plus hour. So if lots of reproductions hold true to this 30 plus hour time estimate, that would strongly suggest that in fact we're on hyper exponential, rather than an exponential in terms of

autonomy and really crazy things maybe start to happen in the next year or so if that's the case. And Alex, Dario is in particular famous for really focusing on making what he would consider a safe AI. And one of the final bullets here is that Anthropic or Sonnet 4.5, has reduced its ability to lie and seek power by a factor of 10. So what does that mean? It's like, you know, when you ask it to turn off and it doesn't, or if it's trying to aggregate resources or it's lying to you, those are not good things. There is an entire cottage industry at this point of for-profit and not-for-profit,

basically red-teaming labs that are fed early access to these frontier models that look for these sorts of traits. I think it's an interesting research level question as to whether power seeking, for example, is instrumentally convergent as a goal for superintelligence, instrumentally convergent meaning that regardless of whatever the long-term goal that's assigned to the model or whatever it's prompted to do, whether if above some threshold of intelligence or superintelligence, it more or less is required to power seek. I've published research in that area. In my mind, This is still very much an open question regarding the so-called orthogonality thesis of whether the ultimate goal of an AI can even be decoupled from its intelligence level. It would be super interesting to see how Gemini and XAI and Open AI all rate on lying and power-seeking of its models. Do you have any idea? I see lots of different measures for this. it's difficult to register a uniform assessment across the industry.

That's a fun challenge, though. That could go bad in so many ways, but that would be so fun. Like, let's put together a benchmark word for how it lies. How well it lies. Let's see if we can prompt it into lying as much as possible. Well, I could imagine, you know, listen, there's an all-out competition between all these frontier labs. And if the way you get ahead is that your AI is more power-seeking than its neighbor, Are you optimizing for it or against it?

We'll find out. All right. Continuing on, Imagine with Claude. So live app creation, demo of Sino 4.5 that generates apps in real time. Let's take a quick look at this video and then I'll ask you to tell us about it. Alex. Imagine with Claude is still building software, but we've cut out the middleman. Instead of writing code that describes this text box,

Claude just makes the text box. We've given it access to software tools that construct software directly, and substantially faster. Claude isn't writing code in the standard way. It doesn't have to plan it all out in advance. Instead, it generates new software on the fly. When we click something here, it isn't running pre-written code. It's producing the new parts of the interface right there and then.

Amazing. So, Alex, I saw you were playing with it this morning. It's, we're living in the future, Peter, where the models are so high throughput, apparently, that now it's possible to do just in time code generation on every event. You click within a user interface within Imagine and new code is generated on the fly. You can ask for new apps to be spun up on demand. They'll be generated on demand. And I think it's an interesting thought experiment to ask, Where does this go in extremists when throughputs continue on their exponential or maybe hyper-exponential trajectory? And I suspect, naively, where this ends up is every single pixel is going to be generated. Yeah. Not just like vector art, not just U.X, Windows icons, menus, pointers, every pixel. And I imagine your version of Jarvis, your personal entourage of agents.

are spinning up capabilities for you that they think you might need on standby ready for you to request access to. We could end up to the gray goo tech problem on this because you could spin up on AI that says, no, no, I'm just saying, it's somewhat of a positive thing, but it's going to be surreal

because you create an AI that starts generating apps and we'll get in up with billions of apps flooding the app store. It's going to cause some interesting challenges on the outside. But there will be no app store. You know, you will not be choosing, you'll be not be choosing an app. It'll be algorithmic, obviously. It'll be, you know, the capabilities you need in the moment to achieve your objective.

We'll be curbed up as you're doing it. Yeah. Yeah, the term of art is at this point, slop, and I'm a lot less concerned about slop overwhelming civilization than perhaps some folks. I think there are so many ultra-high-value transformative problems that will set AIs on while we're sleeping. I'm incredibly not worried that we're going to drown in sloppy. I agree. I completely agree. Also, I think it's a good place.

A lot of business leaders out there aren't reserving their compute. And they're like, well, I won't need that much or I'll wait and see what happens. There's a great use case to show you, like, if you say, look, I want this software to exist in real time, it's entirely possible. But you have to have a lot of compute dedicated to you in order to make it happen in real time. How quickly can you imagine 400, 500 concurrent things that you want it working on very, very quickly? So if you have access to that compute, all of that can be created for you in real time, and it's an absolute joy to do. If you don't have the compute, you're not going to get it. The demand for this is so mind-blowingly big.

And you just got to figure out where am I going to get the compute to do exactly what we just saw. Alex, how easy was this to use? What do you have to do to spin it up? trivial. So all I had to do was go to the Imagine with Claude site. I asked it first to generate a calculator app for me, create a calculator. It created a functional calculator. But most interestingly, as I was testing the calculator, clicking on each button in the calculator app, it was generating code in real time. So this is a transformative way of thinking. We're accustomed to historically thinking that there's a software development time and then later an execution

time. And this completely blurs that boundary where even at execution time, every software event results in new co-gen on demand. It changes the just-in-time paradigm. So you don't have, as a coder, you don't have to think through every possible use of it. This is building out the use tree as it's requested. That's right. And Werner Vinji, one of my favorite writers, used to write in Rainbow's End, another book other than Accelerondo that I would highly recommend right about what would happen when we have too many transistors. Transistors too cheap to meter, as it were. And our transistor budgets go through the roof. I think this ends up being one of these use cases. If we have so much compute just sloshing around the ability

to delay app code generation until user event time, that's incredible. And that will certainly mop up lots of compute. Yeah. We haven't heard much from, at least on our WTF episodes, from about Claude over the last month. It's good to see Claude coming out, Anthropa, coming out with some great products. It's quietly winning in the marketplace. Yeah. Let's go to OpenAI. OpenAI is introducing chat GPT pulse.

So I love the idea. I haven't played with it yet. The idea being, you know, in the morning when I'm using my chat GPT voice and having a conversation with Ember, which is the voice model, I'm using there. You know, I have to think, okay, what's a unique idea or concept? I just learned about that I want to speak, you know, let's talk about the FOX-03 gene and how it's impacting longevity, whatever the case might be. Here's flipping the model based upon all your conversations you've had with chat GPT, it's actually coming up with topics you might want to learn about. So it's prompting us and then we're prompting it back. Has anybody to play with it? I thought this was a really subtle

but important thing where you're not querying it. It's quarrying you. And I think that starts a new vector of really interesting development. Yeah, it feels a bit like a successor to tasks, which are also still available from within chat GPT. But I think in my dream world, what I would love to see is perhaps in addition to being able to set sort of Cron tab style periodically scheduled tasks, If I want compute running on my own behalf while I sleep, I would love the ability to have long-running tasks on hard problems, single tasks that run for days or weeks on end rather than just smaller tasks that run, say, once per day while I sleep. Alex, give us an example of a multi-day or multi-week task that you would spin up right now. I was going to say exactly the same thing. I want to hear what comes out of your...

I want to cure every disease. That's like a beautiful, well-posed task that is surely going to absorb many billions of dollars of inference time compute. Okay. That's great. I want anti-gravity. I want warp drive. I want a lot of things. All right.

So, let's move on here. Next up on Open A's docket is opening eyes bringing ads to chat GPT. So, their new chief ad officer, Fidgdicemo, has come on. And, you know, what I find interesting is Open AI is going after massive revenue streams. Dave, do you want to plug into this one? Well, the ad revenue is inevitable. That's, you know, $300 billion for Google. It's all going to move over to AI conversations.

And, yeah, a lot of complexity. to figure out there. She has a challenge on her hand trying to figure out how you balance. The AI is going to be incredibly good at convincing you to do things, whether they're right or wrong. And there's a lot of revenue tied to that. And I think META did a very good job of balancing the news feed quality with promotions that are blended in. But it's a very tricky balance. And because they're spending so much money on the data centers, there's a huge incentive to get really aggressive with the advertising. Yeah.

Yeah. And so that, you know, but then there'll be consumer backlash and everyone will move to some other models. So that's a really hairy balance. But the AI is both the best ally you've ever had in buying things, but also if it's misguided, could walk you down some seriously bad paths. The trust seemed to be, the trust seemed to me for it.

Like, will you trust insights from an AI that has ads baked into it? and has an ulterior motive. And so what do you do then? Yeah, for sure. I think the ad model is ultimately going to disappear. I think there's a limited value here, right? Because once we have pendants or glasses and our AIs are able to see where we're focusing, like if I'm, like, if my retinal gaze is on that lamp behind Alex and I say,

I love that lamp and I'm just focusing a lot on it, attention. is going to, you know, equate to some level of interest and my AI may be popping up and say, would you like me to buy that for you? Right. So rather than having an ad come, it's mostly just where am I focusing, listening to my conversations. And then the other thing that's going to be interesting is if I give my AI a surprise and delight budget, I say, hey, you can spend up to 500 bucks a month to surprise me. And stuff starts showing up. Or it knows I'm running out toothpaste or you know my my t-shirts are run down i'll tell you peter uh the two sentences you said back to back there i'll tell you where the conflict is between the two tell me uh you

you want your aida surprising to let you and it absolutely will yes most consumer products are 70 80 90 95 percent margin hugely huge margin where there are two or more absolutely identical products sure you know two different sets sunglasses toothpaste you know like it makes no difference whatsoever. And if the AI says, well, okay, I'll get Crest instead of Colgate, 95% margin went to that company instead of that company. And so there's a huge amount at stake where the consumer is still happy either way. Where's that money all land? Right now it all lands at Google. And in the future, it's going to land on the AI advisors. So both things can be in harmony with each other, yet there's a massive amount of money under the covers. So it's still ad revenue

where it's decision-making, you know, routing. Take it a step further, Dave, because my AI probably knows the exact makeup of the molecules in the toothpaste. It actually happens to know my taste buds better than I do and knows my genetic makeup. And it will order a, you know, a toothpaste that is perfect for me at, that is one half the price. And I know that it's maximized what's best for me. And, you know, Google's not getting it, you know, no one's getting it. The AI is buying it direct. Yeah. Yeah, we'll see. We'll see. because if you look at toilet paper as an example, you can buy it for literally 5% of the retail cost.

And if you deflate the margin and say, well, the consumer is much happier, they're only paying 5%, but all the margin got sucked out of the value chain, then the marketing company at the front also isn't making any money. So what tends to happen is the opposite of that, that the marketing front end is complicit with the back-end consumer products companies

to keep the margins high. And the consumer just says, okay, fine, I'll just buy that toilet paper. And you don't think about it. But do you think my AI could think about it and could sort of circumnavigate all of those price gouging companies along the way? You're onto something really interesting there, which is packaged ecosystems where, you know, the number of things you can buy is getting so complex. And the number of choices is so complex. You know, for a while there, there was an Eddie Bauer edition Ford Explorer. And it was for like, I've just bought into the Eddie Bauer.

package, you know, I'll get the car, I'll get the clothes, it's just like part of the overall thing. And if you read Neil Stevenson, Diamond Age, everybody moves into these culture packages where the AI has figured out all the parts. I think that's a real thing. Just because complexity of decision making gets so high over time that you just want to, you want to join kind of like AARP as a group and, you know, and Diamond Age. It's trusted, but it's also a brand affiliation, right? So I think one of the last moats that's going to exist someplace is going to be brands where I want, because I'm showing my wealth or my affiliation, I'm seeing a lot more by the brands I'm using, but not on toothpaste. No one goes to my bathroom and says, hey,

what toothpaste are you using? All right, let's move on. But just the point here, Open AI is building revenue streams. And here's another one. They partnered with Stripe for instant checkout in chat GPT. I think this is brilliant. The ability for Open AI to generate revenue on the sales of products, starting with Etsy and Shun Shopify. Who wants to weigh in? I'll weigh in on this one. I think if you squint, we can see maybe the outlines of what at least near future superintelligence microeconomics look like, where you have some power law distribution.

You have a long tail of consumer subscriptions or consumer ads or consumer affiliate fees for agent at commerce. Then you have a middle chunk where white collar so-called knowledge work gets automated in part or in whole by AI. That's sort of the middle chunk of what turns the wheel. And then the head of the power law is solving all these transformative problems. I think Sam would say like curing cancer or curing all disease that are worth many trillions of dollars. And I think the key question of our time or at least of the near future is what's the What exact power law do these follow? Is it a fat tail with lots of consumers using strike-powered instant checkout to power a very fat

tail? Or is it very thin tail where almost all of the revenues that are flowing to the frontier labs to justify the soon trillions of dollars of CAPEX to build data centers are all being driven by transformative inventions and discoveries and the instant checkout, if you will, ends up being rounding error? I don't know the answer, but I think this is the defining constant. And I think they're reaching for near-term revenues that are easy to get right now. But in the long term, it's going to be the invention of new materials, new biotica, all kinds of things.

I mean, it's interesting that the number here is by the end of 2025, it's projected $142 billion in consumer purchases via chatbots. And I think the one thing that we all have in common is a constraint on time. So if I'm in the middle of researching a product and I'm in the midst of doing comparative analysis on open AI and it pops up and says we have to buy it, I mean, it's maybe, but maybe in the near term future, the scarcity, I think you would say, of attention also gets alleviated and we find ourselves in a post scarce attention world. Interesting. In which case, what, we shop around more? We have more hours in the day. Yeah, but we have so much more to do with those hours. Like, when you think about the software through voice that we were just doing and also the Suno through voice, it's so compelling and so fun. You'll eat up every one of those hours and one more.

So I guess those are harmonious statements. But I'll tell you one thing. When Alex says, I don't know what's going to happen. You know you're going into crazy times. Timelines are really short. Timelines, I think, are like two to three years at this point, max. I thought this was profound because this could be a big threat to Amazon. Yes, this is directly.

And then basically go straight to the source of where something's being made. I've been using chat GPT and Gemini to do comparison shopping for the last few months. And I don't buy anything else saying, hey, show me good alternatives of this or this or this. And it's remarkably good at crawling in the way and finally all the stuff that I would take it and take me ages to figure out. And now I can do direct commerce. with it? That's huge. Yeah. Otherwise, you were copy-paste into Amazon and buy it there probably, right? Amazing. And travel. I mean, you know, it's interesting using a large language model for travel saying, I've got to be at this location by this time. Which airlines have the highest uptime reliability

and get me there and what's the travel time and set up the schedule for me? And instantly, it's there. And then it should say, do you want me to buy the tickets and set up the Uber for you, and, you know, anyway, I think it's pretty... I would just remind also, this is still nibbling at the edges of consumer spending. AI is going to eat the whole economy. So that starts to look like AI eating real estate expenses, AI eating health care, AI eating utilities and food. Right now, buying consumer packaged goods, this is just not to diminish the CPG sector,

but this is just nibbling at the edges right now of disruption. I'll tell you for bringing this back. Since Jeff Bezos is your friend, you know, Lee Bozio, who used to run, he was a single-threaded leader for Alexa over it at when he was at Amazon. He used to work for us. And Jeff Bezos saw this coming a mile away. And that is why he built out this massive investment in fulfillment. And, you know, eBay didn't. Because the interface is going to change for sure.

And he can rely on the fulfillment side of it to route all that volume through Amazon. But he knew this was coming when he invested in. Alexa. We still haven't seen Alexa play out fully, right? Alexa is still very antiquated. We haven't seen Amazon's AI play yet. Very much. It doesn't hold state, no memory. There's a lot to build there. Well, you know what they're doing? So I had a call with the chairman of iBanking at the largest bank in England. And they're huge anthropic and AWS fans. And I said, why? I said, well, because we want the AI to have client data, account data, payroll data, all this hypersensitive data, and Anthropic is the only company that can support it securely,

and we run it all inside AWS's infrastructure. So what they did with warehouses and fulfillment on retail, they're also doing with digital compute and data center fulfillment in AI. So the same playbook just moved over to the AI era. It's interesting. Anthropic tends to be the friendly little brother. other to Google and others as well. They're well-liked, well-respected. We'll see how they team up. Ten times less lying. We saw that on the other side.

And power seeking. Okay, I trust my anthropic AI. All right, here we go. GDP Val measures performance of our models on real-world tasks. So it released tests for real-word tasks across 44 jobs in nine industries with GPT-5 and Claude Opus nearing expert quality 100 times faster and cheaper. Alex, do you want to lead the conversation? Sure. Well, as you know, Peter, I've beaten the drum in the past here on the importance of new e-vals, new benchmarks. This is a very important benchmark. OpenAI has alluded to this benchmark in the past, but actually looking at the benchmark,

which is available open source for folks who want to look at the prompts. This feels like a benchmark for knowledge work. It's pretty diverse. And to the extent that you look at this chart and other charts that have been made available showing progress on GDP Val, which covers a number of different industries, lots of tasks, it appears very thoughtfully put together. If you just extrapolate by the law of straight lines, you extrapolate progress on the ability to perform

all these real world tasks, you find, you predict that in the next six to 12 months, we're talking about substantially all knowledge work across a number of industries being superhuman as performed by AI. Some would say I think that's a very short timeline. We're talking about Evels literally solving the economy, or at least a good chunk of the knowledge work economy. Yeah, it's here now. I mean, do not look for some decade future.

is the next year or two, you know, one of the quotes here, the models completed tasks up to 100 times faster and cheaper than human experts, highlighting both their potential and the need for oversight. Selim, you were going to say. Two points. One is, I remember, you know, there was such a big shift in car making when you had a robot opening and closing a car door 10,000 times to test the hinges. Quality just went through the roof after that. And now we can have AI doing the same thing for this type of stuff. And what I thought was really powerful about this was this isn't some kind of toy problem benchmark. This is real world stuff. And now we have the ability to gauge AI doing real world stuff. And now this becomes very tangible. Fantastic. All right. Let's go to

yet another conversation here. This is a video I'm going to play with Brendan Fudi, the CEO of Mercor, who Dave knows extremely well. And this is Merckor's AI Productivity Index. Let's take a listen. We decided to test how well today's leading AI models can actually do your job. And the results are astounding. Introducing the AI Productivity Index, or Apex, an evaluation that measures how well we've automated the most valuable industries in the world.

We studied model capabilities in law, medicine, consulting, finance and partnership with industry experts in each domain. Apex is designed to give an accurate forecast of how AI is going to impact jobs. But this version just scratches the surface of measuring model capabilities. All right, Brendan, catapulting yourself to the top of the class. How old is Brendan? 23, I think now. Yeah. Founded at 19. He's ahead of Mark Zuckerberg in terms of company valuation age, raised to a billionaire age. So I don't know if anyone since Mark has been on that curve. And I tell you, as long as we're talking about Brendan, a whole bunch of inbound calls, people wanting to buy our Merckor stock from us.

Like, you know, it's a $10 billion valuation, right? And they're like, yeah, but if you look historically at people who've reached where Brendan is at that age, every one of them or almost all of them become whatever. You know, Elon Musk, Marks, Zuckerberg, Bill Gates, whatever. So he's on a trajectory like nobody else, and everybody loves him. You look at him on screen there. He just, he's the guy everybody's cheering for. So it's pretty cool to see.

I think these last two slides, you know, back on the topic of the slides, really, really important. Because, you know, AI is so general purpose and so capable in so many areas. And, you know, Alex and I have had all kinds of torture trying to interact with the statehouse here with other government officials to get them to realize the urgency. and the implications, it's so hard. But then when you throw a really good benchmark at it, it makes it much, much easier to explain why this is so urgent. So Brendan is taking on all things related to work productivity across all areas. And that's a really big ambition, very, very worthy ambition for him.

Alex, this is how economics gets solved. If we want to live in an abundant future where the cost of service labor is driven to zero, step zero is creating benchmarks. So Apex and GDPVAL I think are beautiful examples. It's still early days, obviously, but beautiful examples of benchmarks for, call it knowledge work or knowledge work-based services in the economy. I would like to see many, many more benchmarks get created, including for robotic labor, manual labor. Just within our portfolio, you know, we have 28 seed stage companies doing AI just here in the building. And if I take any one of them, like, you know, Macado doing mechanical design, what's the benchmark for the quality of the

design? Prim and Vokara doing voice sales and customer service, your AI voices. What's the conversion rate and the customer satisfaction rate on an incrementally smarter AI? How do you benchmark that? Every one of these companies should be inventing a benchmark. Blitzie already is doing it for coding. But, you know, whatever you're doing, if you don't create the benchmark, then it just turns to mud. You know, there's no way for any, because it's like, how do you know if it's a smarter AI? I don't know. And the challenge is we saturate them all and we're comparing them all to human productivity, but we need to have a whole brand new set of benchmarks that are, I don't know, are anchored in, in what, Alex? The good news is we, we already know how to benchmark superhuman

performance. There are relative ELO-based benchmarks that we know how to do. We know how to, as a civilization, we know how to build systems that are more energetic than humans are, that are faster than humans are. And we're still able to measure them, even though they're superhuman along some dimension. So we have no trouble measuring superhuman intelligence capabilities. Thousand horsepower. All right. Exactly. Microsoft's not being let out of the game. So Microsoft unveils agent mode. And think of this as the ability for you to have access. to it in all of your favorite Microsoft tools.

Salim, do you want to jump in or Dave? I've been trying to get Microsoft co-pilot to work in any kind of AI useful way and have failed miserably for the last few months. I hope this one is a better effort. I'm not going to make an enemy out of Microsoft as powerful as they are, but I will say that adding AI as a feature to something that already exists, that's the wrong attitude. I feel like Apple and Microsoft are the worst defenders of this.

It's not going to work. So that's a great point, right? They're trying to maintain their customer base and scratch their AI itch versus AI-native, you know, clean sheet startups. Well, and every corporate CEO should understand. The same thing applies. I see so many people that are saying, yeah, we're doing AI. I added it as a feature in one department. And so now I don't have to think about it anymore.

let me go back and, you know, get back to my country club. And you're going to get crushed with that kind of perspective. It's not a feature. It's a brand new, everything. It's a complete difference. Greenfield opportunity. There's a bunch of stuff I was trying to do in Excel. And I literally tried to use an AI mechanism to do it.

I just couldn't do it. Finally, I ended up using Comet to do it in the browser. And it did it way better and way faster. So I think this is a huge gap. I don't know where they're going to go with this. All right. Well, we've covered Open AI and Anthropic. Let's not leave XAI out of the picture here.

Elon has cut a deal with the government. XAI struck a deal with the U.S. GSA to let federal agencies use GROC for 42 cents for 18 months. It was either 69 cents or 42 cents. I guess he went with a cheaper option, 42 cents. I'll leave that alone. Any particular comments on on Grock entering DC-Hun? The price point is 42, which is 420, which is the, you know, the magic number, which is the $20 million SEC fine that he had.

Yes. Remember that? Of course. It's always tongue in cheek with Elon, and I love that. You know, even at that scale, just making it fun and interesting, kind of like Taylor Swift, there's always a hidden message. And people love that stuff. It's good. It keeps people engaged.

But what's going on between corporate America and government America is completely unprecedented, a little scary. It's working really, really well, and it's helping the country a lot. But it's very odd to be cutting, you know, investing in Intel and then cutting deals to move things. And it's for the government to be directly involved in corporate America like this has never happened before. Well, it's looking a little bit like China, right, where China is picking winners and enforcing partnerships and creating, you know, robot cities, gene engineering cities, AI cities and such. It's fascinating. But isn't the government signing deals with like CHAPT, et cetera, et cetera, because we saw earlier.

So it sounds like what they're doing is trying them all and seeing which one is the best over time. Well, that would be fine. I mean, that's like government procurement, but that's not what's going on at all. You're going to the White House and you're either genuflecting and being the anointed one or you're not. And it's not, these are not arm's length procurement through the Air Force or something like that. These are White House. Edicts. Yes.

Yes. Yeah. And we'll get to, we'll talk about Intel in the section called this is not investment advice, which is coming up. All right. Meanwhile, in other AI news, here we go. former meta researcher is building a math whiz. I'm going to bring this to you, Alex, teach us. I haven't seen any indication thus far that math is not going to be solved in the next few months.

How's that for a double negative? A few months, okay. So again, I think. So what did it run out is that? Wait, wait, wait, wait. So Alex, you've said that before, and everybody's asking me, please have Alex explain what it means to solve all math. So can you could you just do that?

Let's just speak out this particular article. This is a woman. It's great to see female CEOs in the AI world or not enough of them. Karina Hong, she's the founder of Axiom Math. She's 24 years old and she wants to build the ultimate AI mathematician. She's raised $64 million at a 300,000. million dollar valuation. And again, we're seeing this over and over again. We're seeing, you know, starting valuations in the hundreds of millions of dollars. I don't know if they said

a, you know, a pre-seed round or whatever, but intelligent individuals who have got a monomaniable focus are getting incredible capital backing. Okay, now back to you, back to you, Alex. What does solve math really mean? There are, I think, a few different ways one could operationalize what it means to solve math. One way would be to look at a benchmark like the Frontier Math Tier 4 benchmark, which measures the ability of AI to solve extremely difficult, but nonetheless pre-solved problems that would take human researchers several weeks to accomplish. If you just do a naive logistic extrapolation of progress in Frontier Math Tier 4, you find that by the law, again, straight lines, as it were, that by the end of this year, by the end of 2025,

we're starting to pass 10, 15% of problems in the benchmark that AI can solve. And at that point, I would argue, we're in a situation, we're in a regime where algorithmically we have clear line of sight to solving any math problem that we might have today, just pour more compute on. So that would also, I think, point to the second operationalization I would have in mind when I speak of solving math. I don't mean literally every math problem that we can think of today has been solved. What I mean is that the process of mathematics has been solved to the extent that we have a clear line of site where if you pour millions, billions, maybe trillions of dollars into OPEX in data centers, no new algorithmic advances are needed. we can reasonably forecast that any mathematical problem that's solvable will be solved

with the same algorithms, just with a lot more computer. Okay. Now, take me to the implications of that for the general public. It's tricky. It's tricky. Probably I would, this is in the territory of speculation. But I think one of the more obvious downstream consequences of solving math is that any problem that depends on the difficulty of math, or let's say math being difficult, that isn't protected

in a formal sense by the so-called complexity hierarchy. Mathematicians and computer scientists have this notion of certain problems being provably harder in some sense than others. Maybe you've heard of P versus NP. But if there's no formal protection for certain classes of problems being provably harder than other classes, I think certain types of tasks that we encounter in the everyday economy, for example, maybe hypothetically certain hash functions that cryptocurrencies depend on or other everyday economic functions depend on are at risk of volatility. For example, again, speculatively, not investment advice, if there were a super AI mathematician tomorrow that could, say, invert the AES cipher suite or invert the hash

functions underneath AES, that could be potentially extremely disruptive to the economy, cause a lot of volatility. I think the point you're making is if AI cracks advanced math, it just isn't, it's not just solving equations, it's creating the scaffolding to solve all these other areas, like cryptography, economics, physics, et cetera. That's what you're really saying. Yeah, I mean, to that point, I would say the way I would frame it, perhaps, is first order consequences, problems that depend on math being hard, experience some volatility. Second order consequences, I think it's the ultimate canary for any domain that requires the ability to do mathematical reasoning. So I would expect in short order a variety of math-oriented science and engineering and medicine and other domains are going to fall in rapid succession. If this theory of the future ends up being correct, I was alluding a few minutes ago to

timelines being short, we may find ourselves in a world two to three years from now where we're just drowning under math science engineering being solved in rapid succession. Drowning under serial and, you know, sort of Cambrian explosion of breakthroughs. Exactly. That will also parenthetically be potentially quite difficult for society to metabolize. Yeah, the economic impacts of that are going to be on. This episode is brought to you by Blitzy, autonomous software development with infinite code context. Blitzy uses thousands of specialized AI agents that think for hours to understand enterprise scale code bases with millions of lines of code.

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Demo, and start building with Blitzy today. All right. Speaking about economics, so AI can now pass the hardest level of a CFA exam in minutes. So let's take a quick look at this. So CFA is a chartered financial analyst, and it deals with investment management, portfolio management, financial analysis, and ethics in finance, which I find absolutely fascinating. And I looked it up. The CFA level three part of the exam is about portfolio management and wealth planning. So I want to make a comment on this one. Yeah. So we're advising one of the big four accounting firms on how to think about transformation. And this one, we've been predicting this with them to be happening because this requires real world of reasoning. And the fact that it is doing this is a huge implication. All their finance jobs essentially get rewritten.

now and recreate it. It's a it's a it's a it's a it's a body blow to the the accounting world. Well I what I find interesting is you know leveling the playing field across all investments you know do I with access to the specific AI have access to the best investment advice that you know Warren Buffett has access to as well is this a leveling the playing field across all economics I think it is but I I you know what I'm excited about is you know America lost and in Europe too lost almost all of its manufacturing you know despite inventing the car and vending the plane inventing the microchip

inventing the computer all the manufacturing of that stuff moved to other countries yeah we gave it up it gave it up and they're like well but our economy kept growing what are we all doing well we're a service economy we're doing services what the hell does that mean well you look under the covers and a huge fraction of very smart people are working in this totally circular, nonsensical world where we created a complex law, complex taxes, complex accounting. And then there's other huge group of people need to solve the complex accounting. And it produces absolutely nothing useful for humanity. Oh, my God.

In this huge IRS code. IRS code. I mean, for God's sakes. Holy crap. Yeah, Ronald Reagan was the last guy to say, this is insane. We've got to get this down by 10x. And ever since, you know, everyone bloats it up. The accounting lobby is the biggest lobby in the country and it's bigger and poor goods.

Lawyers and Accountants. Yeah, lawyers and accountants. We finally have an opportunity here to get rid of it once and for all, not by eliminating it, by having the AI automate both sides. And then it just becomes something we don't have to do anymore. And all that talent can create things that actually benefit humanity. I'm so excited for that. I would also...

The relief is so palpable in your voice there. It's incredible. Peter, to your question, I was also... encourage the thought experiment. If everyone has the best investment advice, thanks to super intelligent investment advisors, what does the economy look like and what is the rational act? What's the rational course of action for an investor if everyone has equally superintentioned investment advice? It goes up to your point, Alex, is buying the index. Yeah. Can I say?

Damn it. He's right again. I'll get fight on that one, but we'll get to it. I, you know, I thought I'd bring quantum into the conversation. I know Dave, you and Alex have been working on this. A couple of years back, I started a SPAC with Sherpet Pischvar, and we took D-Wave public, which is now seeing incredible resurgence. It's gone from like 69 cents a share, up to 30 bucks a share, and done extremely well. We've seen Raghetti computing. Chad Raghetti's been a friend for some time, D-Wave, so all. all of these independent, you know, quantum computing companies are getting some real traction.

Here's a quote, though, from Julian Kelly, that Google Quantum's AI director, the technology is five years out from a real breakthrough. Alex, you've been tracking this? What are your thoughts on quantum computing? I think it's early. I'm reminded that the GPU or call it the accelerated compute market via the avatar of Nvidia had to pivot several times before it took over the economy. It started with PC gaming

and then pivoted for a bit to crypto and now AI and maybe there's a post-AI act. But I think what is missing right now, at least to my knowledge, is the killer app for quantum accelerated compute. There's a school of thought out there

that maybe we'll use quantum at inference time to generate large synthetic data sets of quantum chemistry data say that will be used as training data for classical AI, it's difficult for me to buy that that's going to be an enormous market. My best guess is that to the extent that there will be a killer app for quantum compute, it's probably something like AI accelerated generalist training for AI or inference for AI. And at least again, to my knowledge, no one has yet

published the killer app for quantum ML. There are lots of proposals out there. Nothing has seemed to scale yet. You know, this year at the Abundance Summit, I'm going to have Jack Hittery back on stage speaking about sandbox AQ. And it's interesting. This is the spin-out out of Google X. Eric Schmidt is the chairman of the company. And they, you know, they booted up at a $500 million dollar valuation. And they've had, I think, in excess of $100 million of revenue. And they're not a quantum computer-based company. They're an AI company using the quantum equations to provide different products and services. So they're basically looking at new navigation systems that's able to measure slight perturbations in the Earth's magnetic fields. When GPS is down,

You can still navigate because magnetic fields are not being spoofed like GPS is being spoofed in the Middle East. You're using it for different biomedical, looking at your heart's electromagnetic system, if you would. They're using it for encryption methodologies, but it's a real revenue engine there. You know, one of the things that we should speak to for a moment, because we do have a lot of crypto listeners as well. as everybody is like, oh, my God, when is quantum going to break the encryption codes that's going to destroy Bitcoin? And it's just important for everybody to know that if, in fact, we have quantum computation breaking encryption, your keys to your Bitcoin wallet are the last thing to worry about because the same encryption codes being broken are the nuclear codes, the banking

system, and everything that runs the financial systems around the world. I would actually take the position that post-quantum crypto is nearing a state, maybe not evenly distributed yet, but at least in theory of approaching quasi-maturity, if I lost sleep at night worrying about inversion attacks against widely used crypto systems, it's not quantum information processing. I'd be worried about it's AI solving math. I think that's a far more insidious threat to crypto-secure. in general than quantum we know how to do post quantum crypto but but the same thing then right a i solving math uh if it's breaking encryption it's breaking encryption across a multitude of other much more concerning uh financial and in defense areas yes well as a as a practical matter this is imminent either way uh it's not going to affect nuclear codes or bitcoin what it will effect, though, is anything that you've encrypted and left around, you know, using AES 256 or 128, that's already vulnerable within a year, if not today. So it's all the designs,

files, and stuff that you thought you encrypted and you left on a server or left in your desk, all that is going to be wide open. So just so you're aware. I think, Dave, that's a really important point. It's the stuff in the past. It's not really the stuff that's current or in the future because we'll come up with quantum encryption capabilities. et cetera. There's one thing about this story that popped out at me that I would just want to flag, which is that in 2008, we heard a quantum computing expert saying we're five years out from having a real breakout. So this has been a constant pattern for a while. I think with the AI changes, this may actually really be the case that we're five years out. It may be much less

than that, given what the potential way out is solve a lot of these problems. But just a great advice, Dileem. Well, no, I've heard this. Yeah, it's great advice. And as a general pattern. When somebody tells you, hey, blah, blah, blah is going to happen, invest in it, it's five years out. Nine times out of ten, it's 20 or 30 years out. Fusion has been five years out since the 50s. Well, it's been 50 years out since the 50s. Let's be clear about it. Not five years out. Well, and the opposite is true, too. When somebody tells you something's imminent, like this is happening right now, guys, don't ignore it. It's very likely that that's also like you're almost late to the party. So I think that's

great advice. All right. Let's move on to chips and data centers. a lot happening here. I'll start with an open letter that Sam Altman put out on abundant intelligence. I'll just quote from it. He says, with 10 gigawatts of compute, AI can cure cancer or provide customized tutoring to every student on earth. If we're limited by compute, we'll have to choose which one to prioritize. No one wants to make the choice. We want to create a factory that produces a gigawatt of new AI infrastructure every week. So this is basically Sam saying, give us all the compute and capital, so we don't have to choose between education and solving cancer or longevity.

It's an important point. I don't know. Any thoughts on this one, Dave? Oh, yeah, lots. I mean, it's amazing how it's becoming increasingly clear that Sam is very small compared to Zuck. and Google, I guess, Sundar. Small in what way? Well, I mean, you know, you signed $100 billion and a $300 billion deal, and that made big news,

but he doesn't have anywhere near $100 billion or $300 billion. He has, he's like one-tenth at it most. Meanwhile, Mark Zuckerberg said, yeah, we're going to put $600 billion into this over the next few years, but he has it. He has the cash and the credit actually, and he will really do it. So, you know, Sam is up against some serious heavy hitters. And Google and Google's got massive engines. I mean, they've got so much capital in the bank that they can expend here.

And Elon just, you know, Elon moves his pinky and capital flows into X-A-I, whatever he needs. But what I love about that dynamic is that Sam is the one guy driving the vision and driving the agenda. Everybody else can afford to just kind of be an afterthink or a soft sell. And without Sam out there opening everyone's eyes, nobody else, like Google would have never even rolled it out, I don't think, without Sam putting the pressure on. So here, I think he's exactly right. Like, is it on this slide or is it coming up? He's, I think it's coming up. Yeah, I'll wait for it.

Yeah, there we go. So, yeah, this article here is Open AI Oracle, SoftBank, Expand Stargate with five new AI data centers. So aiming to hit $500 billion or 10 gigawatt gold before the end of 2025 and being ahead of schedule. Tiling the earth. Dave, continuing the earth. Well, yeah, so Sam is saying, look, we're going to try and. organize around 10 incremental gigawatts per year in perpetuity

or accelerating and that will just barely keep up with the use cases and the demand and so that's really really cool to hear someone articulate because then you know the the land the governors the you know the the plumbing the election you know all of that stuff can start to get

rallied around a long-term view of what it means to stay ahead in this race and so I think it's great to articulate it Because, you know, the numbers are so big. No one else will say it. Santa's the one guy that will actually say it. But it's just the truth. Let's put the numbers out there here.

So Stargates, $500 billion investment dwarfs all the other hyperscalers in 2024. Microsoft put in $40 billion into AI data centers in 24, planned $80 billion for this year. Amazon was $16 billion, Google Alphabet, $29 billion and meta, $23 billion. I think they're all. going to be massively accelerating, but just to give some numbers for folks to compare this to. I do think for what it's worth, we are tiling already the Earth quite literally. But there's also a certain sense in which I expect, if you remember President Reagan's nuclear policy of building up to build down, I can imagine high likelihood scenarios where efficiency advances,

maybe ontological shocks, perhaps ontological shocks that result from these data centers, make the naive assumption that we're going to scale an extremist to Dyson Swarms, which is, of course, you know, you just project outward after we're done tiling the Earth, tile the solar system, make that look a little bit silly. But I think in the short term, all systems go at least for the next five to ten years. I mean, I have to imagine that one of the first areas, is where AI is going to cause a massive disruption, is energy efficiency on, and compute efficiencies on these centers?

Yes. And this is a regime right now where we were talking about quantum a few minutes ago. Maybe there's photonics as an intermediate substrate before, if at all, we migrate to fully quantum systems. There are, as Feynman said, there's so much room at the bottom. There are so many new, low level in the infrastructure. for a stack advances that are just waiting to become economically palatable, there are scenarios where we don't need to fully tile the Earth. And the data centers solve a whole bunch of

low-level physical problems for us, enabling us to keep this relatively contained. And if you go back to our, sorry, you're going to say the exact same thing. Remember, Brockman said we want a GPU per human. Yeah. Yeah. And then as soon as you have it, you'll want more. If you go to our podcast from a couple months ago, we had a whole section on the software breakthroughs, you know, to Alex's comment of the opportunity at the bottom, minimum 10x, more like 10,000 X is the best guess. But somewhere between 10 and 10,000 X, just software improvement that's coming. But we'll use all of it and want more. There's no doubt in my mind. And then, you know, there's hardware on top of that as well. But we did a whole analysis of the different dimensions

and now they're multiplicative, we should revisit that because we have a lot more, a lot more color now. Yeah, but I think to Sam Altman's earlier point about choosing between health and education, there will be a fundamental breakthrough. There just needs to be because we can't expect that the systems that we had, you know, from a couple years ago are going to perpetuate going forward. So I think we'll have the compute to do all these things. This is fascinating. here's this is a article saying Nvidia discussing new business model chip leasing. Open AI struck a hundred billion dollar deal to lease not buy Nvidia's AI chips spread over five years. I can just imagine the conversation between Jensen and Sam. Hey, listen, Jensen, I want those chips. I just don't have $100 billion. Well, Sam, what if I just lease them to you over five years? Are you good for the payments over five years? Because I think, you know, our investors love to have like, you know,

guaranteed revenues over five years? And who takes a depreciation risk, right? Dave, what are your thoughts here? Actually, a bunch of our MIT best buddies, including Kush Bavaria here, are starting new companies around this entire area of creating new securities that allow you to finance all this stuff. The hyperscalers are just going ballistic. I mean, this is so much bigger than all other forms of real estate investments combined is the aggregation of data centers and ships. So the leasing was inevitable because, again, you know, Sam doesn't have cash on the barrelhead. Meanwhile, Jensen, you know, he's got the lead right now and he has a $4.5 trillion market cap. One way to lock that in is to use the leverage.

And this is why Larry Ellison's the richest guy in the world or was a week or two ago because he used his balance sheet and his borrowing ability at 4% to finance a lot of bottlenecks that, you know, the startups can't afford it. And Sam obviously can't afford it. Who's going to fund it? Well, you know, just because you're leasing it, somebody saw us to buy the chip up front. So Nvidia is saying, okay, well, we'll fund the purchase of our own chips using our massive balance sheet and our massive market cap to finance it. I agree with you. This felt inevitable to me, it was going to happen at some point. I think it's easy for skeptics to paint this as smacking of financial engineering and some sort of GPU credit bubble. I think that

that I think the the GPU credit bubble, though, the story in addition, as folks here already mentioned, depreciation. The other, I think, storyline that's being missed is right now, NVIDIA is in a very high margin GPU hardware business. And there's an impedance mismatch between selling high-margin GPUs and low-to-negative margin neocloud and cloud businesses. And so leasing is the market, I perceive, the market contorting itself to accommodate that mismatch between high-margin GPU hardware, low-to-negative neocloud. Well, Rob Fisher, who used to run Link Studio here, went off to build data centers. And he said he's signing deals two, three, four a week now.

So I think what's happened is, you know, the visionary started building data centers ahead of the curve knowing the demand would come, and everybody's a little nervous about that. Well, the demand, at least as far as Rob is concerned, the demand is here now. And you can see it in all the use cases we demoed earlier in the pod. You know, those things didn't exist six months ago. Now anyone's seeing those is going to want to do it immediately, whether it's in a corporate or it's personal or, you know, just a theme song for the podcast. Everyone's like, wow, that's really usable. Where do I get it? Well, that's to run on a data center somewhere.

It's not magic. And so I think the demand is starting to catch up to the construction. And the demand will get way ahead of the construction. Yeah, I don't think we've seen anything yet in terms of demand. I mean, everybody's still just barely tickling, you know, chat GPT and not really plugging in. I mean, once we are spinning up agents and we're building new capabilities and transforming our lives, I mean, we're going to see a thousand X per individual. All right.

I call this segment not investment advice. Okay, let's jump in. Create titles. Then you don't have to say it. So I'm going to continue on our Intel saga. You know, Dave, congratulations on your options. I finally bought in probably, you know, a generation of Intel options later than you did. But here's a chart.

This is a quote from Chimothi says President Trump got Intel to give Team America 10% of itself at $0.00. He has a better IRR than Buffett. Well, of course, if you get something for zero dollars, you have an infinite IRA. But here we go. We see President Trump makes 80% on Intel purchase in six weeks. Not bad. I mean, this was predictable, right? Intel, the U.S. cannot afford to let Intel fail. Yeah, we remember, we did a podcast that was exactly concurrent with Lipbu being at the White House. Yep. And so that was August 11th.

I think it came out the next day. And we said, okay, Lipu will come out of the White House. It'll either be black smoke or white smoke, depending on how that meeting goes. But what you're looking for is either Lipu to quietly disappear in a good way, not quietly disappear, or Donald Trump to reverse court. Remember, he tweeted, Lipu must go. He's completely conflicted. He's invested in China.

Yeah, I remember that. Or, you know, so Donald will either reverse court. It depends on whether Lipu says, look, I'm as an American as apple pie, and I will build the best fabs in the world right here on our soil, or he says something else. Well, so it came out, you know, white smoke, and that means Donald is going to make this succeed one way or another. And then, you know, so the rest is kind of, the slides imply that Intel is way up this year. But it was August 11th, you know, that was the date that it was at its low for the year. near low for the year. So this has only been, you know, six weeks, like it says. Yeah, it's, it's crazy.

This is sovereign venture capital, right? This is the government basically driving investor confidence and triggering momentum. And, you know, I'm a libertarian capitalist. I don't know how to think about this. But I do believe that Intel is a critical asset for America. And it needs to be partnered up, supported. And along those lines, we've got this other piece of news that Intel stock extends its gain, hoping for AMD to go from rival to partner. And the two big deals that are out there for Intel are partnership with AMD and Apple and Nvidia. So, you know, this is, again, going to Chamath's terms, not mine, Team America here. I think, Peter, there's a A certain sense in which this was almost predetermined, by this, I mean, call it the quasi-nationalization

of Intel. I remember conversations I had with Intel engineers 20 plus years ago, and they knew, as continued to be the case, everyone knows Moore's first law, that number of transistors or transistor density doubles every 18 or 24 months, depending on which version of the law you like. Not as many folks perhaps pay attention to Moore's second law, which is that. The cost of a fab doubles approximately every four years. So 20 plus years ago, you could imagine just extrapolating Moore's second law out and realizing at some point new fabs become so expensive that really only sovereign nation states would

be in a position to finance it. And this was reasonably well known within the semi-community 20 plus years ago that at some point as Moore's first law is starting to end and Moore's second law is starting to become so expensive that only sovereign interests can afford to finance this, something like this in some sense, I think, was bound to happen eventually. Bound to happen. Yeah, exactly right. I'll tell you, a lot of people don't talk about this, but, you know, a few years ago, we outsourced all of our PC board, you know, the green boards inside of your laptop, outsourced all of that to China for cheap manufacturing for years, for decades. And lo and behold, there were little spy chips

that were, you know, about the size very small, like a rice grain size thing, stuck between the layers of the PC boards. And that made it into all the U.S. data centers. And so that was grabbing all the passwords and transmitting them back to China. And so the U.S. government discovered this. It had been going on for years. And then rather than make a big international incident out of it, they said, holy crap, this is going to be devastating. We're going to lose confidence in all financial instruments and everything, we're going to squelch this story. And it kind of disappeared from the news. And they've been quietly for a long time trying to clean it all up. And so now the idea that you would trust your highest end chip manufacturing to be done offshore and repeat that same

mistake, non-starter. There's just no way that that's the right choice. Because these chips go right into all of our weapons. They go right into the tanks, right into the planes. I mean, these are like, if there's spyware embedded in the microcode, it's the biggest disaster you could possibly imagine. So there's no way that they were. I start thinking, Dave, of what else falls into the we cannot let it fail category. And my mind turns to energy. I think that we're, and we'll talk about that in the next segment here, but the U.S. government needing to prop up form consolidation, reduce regulatory, and really accelerate our energy economy. So, but I'll be keeping an eye out for this Aschenbrenner-like moment of finding a company

that is, I don't say too big to fail. I would say too centrally critical to fail, you know. Too scarce to fail. To, yes. Don't talk about scarcity. All right, let's move on here. speaking about scarcity. So Jensen goes on record with, I think, something very important, electrician and plumbers needed in the new working world. So last podcast, we talked about

how universities are failing. The perceived value of a college degree has fallen through the floor. At the same time, the category of workers who are out of jobs the longest are the new college graduates. It's an insane. So how does higher education continue to to charge what they charge in this scenario. So here are the numbers. It's estimated that hundreds of thousands of electricians, plumbers, and carpenters are needed. The U.S. has short 500,000 construction workers in 2025.

And rather than coming out of school, you know, $100,000, in debt, why don't you come out with a job that's paying $100,000 to $200,000 and where you're needed instantly? Yeah, and it's not just construction. It's construction automation, too. This is why I can't wait to go to Abilene to meet with Chase Lockmiller. Because you're like, why would an MIT Aeroastro guy be the right guy to be running Stargate in Abilene? Well, because he looks at every one of these jobs and he thinks, how can I build a robot for that?

How can I automate that? How can I restructure it? So it's modular. And so I think that's going to be the other side of this. It's not just jobs in raw wiring and plumbing. It's jobs in management and construction automation. So some very, very high-end jobs, massive opportunity for employment. And I really wish some more states would recognize that if you want your population

in your state to be well off, you've got to get the data centers up and running in your state. Yeah. So here's another stat. Gen Z is choosing trades over college, 16% rise in trade programs since 2023. And construction is the fastest growing industry for your. new college grads in 2025. Find that absolutely fascinating. All right.

I added these slides. I'm calling it an exponential reality check. So a couple of days ago, one of my boys wants to build a computer. So we're going to build a gaming computer. And we're going through and researching the GPUs, the CPUs, the memory, and so forth. And we're going on, ordering them. Turns out, you know, you can order everything you need, every component on Amazon. So I'm on Amazon and I'm buying, you know, this DDR5 RAM kit, 32 gigabytes of RAM for 101 bucks.

And the back of my mind, I'm like, I wonder what that would have cost in the 80s when I was building my first computer. And then we go on and I'm ordering four terabyte internal hard drive for $84, four terabytes for 84 bucks. And I'm going, holy shit, that's crazy. So I hopped on chat GPT and said, okay, give me an estimate of what this would have cost in the mid-80s. So here are the numbers. They're pretty staggering. So instead of $100 for 302 gigabytes of RAM, it was $150 million back in the 80s. And a 4-terabyte hard drive that did not exist would have cost you about $1.26 billion to cobble together.

I mean, I just, I was just in awe of this. If the top speed of a car, it increased as the same pace as these curves, we'd have cars that went faster than the speed of light. Yeah. You know, I find something sadly fascinating, you know, is that we finally have an answer to something that's vexed all of the AI and psychology community for decades, which is, you know, what would it take to create human-level thinking? outside of a human brain and it turns out it takes you know about 8 to 16 GPUs of capacity and those are about $30,000 each but you can store the human brain storage fits on two of these so it's about you know 160 bucks of storage to do everything that can fit into a human brain and then actually then a lot more so we have massive abundance over abundance of storage

yeah but but you know computer is still you know processing is still you know the human brain is doing really really well on 20 watts so Alex the best I can figure is we're going to go to like molecular memory that will effectively be free in a couple of decades we can do better than that we go better than atomic memory but we can do better than molecular memory okay we can also do better than free but we could do atomic based memory we could do there are proposals for for picometer level memory, I'll be at faster time scales. We could do femtow scale computing and storage. We could go sub-femto scale. The physics of our universe goes so many orders of magnitude down to Planck, and even whether Planck is physical is still an open research question.

We're not going to run out of degrees of freedom to store cat images or whatever else it is that we're trying to use storage for. There's lots of room at the bottom. I always found it fascinating when I was doing my physics degree that no matter how big you want to go in the universe or how small you have infinity essentially in either direction. I do think for what it's worth, there are scenarios where we start to run up

against fundamental physics limitations, but we're still many orders of magnitude away at the moment. Not something to worry about tonight on your drive home, folks. Wait a few years. I added this as a segment we might want to have in future episodes as well, which is sort of exponential book recommendations. We've been talking about Accelerondo. A few of our subscribers and listeners have reached out about that book. I thought it would take a moment to just chat about it. And then one of my favorite books by one of a dear, dear friend who's on stage with me and Salim often at the Abundance Summit, Rames Nam. He wrote a trilogy called Nexus. So Alex, Tell us about Accelerondo a moment. Again, this is sort of, if you want some fun reading between episodes of WTF, here's a couple of books for you. Sure.

Love the Book Corner concept. So I would say Accelerando is my favorite book ever. It tells the story of a multi-generational family starting before the singularity, passes through the singularity, goes after the singularity. And it is probably in my mind that the single best fiction or nonfiction, fiction in this case, depiction of what the 21st century is likely to look like and has so many important concepts ranging from obviously AI, nanotech, space development, first contact that are difficult to synthesize in, or at least have apparently proven for other authors, difficult to synthesize. And I think just reading Accelerondo, which I first encountered in grad school, has made me such a sci-fi snob that it's difficult to, I judge every other bit of science fiction by the standard. I had the opportunity to create a poster-sized version of Accelerondo, which is available as Creative Commons licensed e-book presented to Charlie, which was a real pleasure. I would encourage every sci-fi writer out there, hold yourself to the standard of Accelerondo, both in terms of optimism and in terms of physical realism.

There's always the temptation, if you're a sci-fi author, to just take one dimension of the world and extrapolate it narrowly, and that ends up creating, I think, highly unrealistic scenarios. Accelerando does a much better job. He does. He fails me on his extrapolation on space and space technologies, but, you know, I'm not going to be it's an amazing book i'm reading it actually listening to it for the second time uh it's got a great audible as well uh nexus by remez nam came out in 2012 it's 13 years old but it holds incredibly good

so it reads as fresh today as it did back in 2012 and it's a story of a guy named caden lane he's a young scientist who develops something called nexus it's a nanotechnology basically like neuralase that links human brains directly to the cloud and links them to other brains and It gives birth to a collective consciousness and allows you to run software apps on your brain. And it also goes deep into bioengineering. It's a look at where we're going to get to on the flip side of what Ray Kurzweil predicts in the mid-2030s is high bandwidth brain computer interface. An amazing book, an amazing trilogy, one of my favorites. I've read it three times now the last time with my 14-year-old son.

So, Salaim and Dave, any favorite books for you? Foundation series from Asimov is a classic. That's just a must read for everybody. Okay. Dave. I only read what Alex tells me to read, and I, because, you know, his recommendations have been 100% perfect, so I don't want to trump his great advice. But I will say that the terminology in the books alone makes it worth the investment.

The stories are great, too. But if you read the books, then you get the terminology, then you can keep up with what he's saying. And I think that's really, really important. It's a great investment to make. Alex, would you come up with another recommendation? I'll do the same for next time? Absolutely. So my second and third favorite.

Hold it for then. Hold it for next time. Okay. Sure. Okay. All right. Got to keep our subscribers coming back. All right.

Let's jump into energy and robotics. So Open AI is playing 125-fold energy. capacity increase? Over the next eight years, this is more than India itself is putting out 250 gigawatts of energy by 2033. Where are they today at roughly, you know, heading towards two gigawatts? Thoughts, gentlemen. If you do the arithmetic on this, if my arithmetic is correct, 250 gigawatts, obviously this represents a tremendous expansion over where we are now on the one hand. On the other hand, it only corresponds to approximately at 20th of a percent of the insulation, the inbound insulation on Earth's surface that could be captured or recovered with solar photovoltaics.

So we're still, even with 250 gigawatts for one frontier lab, we're still pretty far from Kardashev level one, let alone Dyson swarms. I think I would like to see terawatts, tens, hundreds of terawatts. And we'll get to solar in just a moment. I found this fascinating. So the U.S. is planning to use emergency powers to save more coal plants. So the Energy Department kept in Michigan and Pennsylvania oil and coal plant running past retirement reason.

They want grid reliability and they don't want to risk the demands. We've seen the consumer price index for energy starting to spike and definitive need for more energy. So there's 100 coal plants that are set to retire in 2028. And of course, you know, this White House in particular has been pro energy of any and all types. Let me let me hop into solar and then we can circle back to this conversation if that's okay with you guys. Sure. All right. So I found this chart fascinating. So Ember, which put it out, is an independent energy and climate think tank in the UK. And you can see this is a chart. that plots energy from 2000 and 2025 across solar, coal, natural gas, hydro, nuclear oil, and

bioenergy. And it makes the point that over the last 15 years between 2010 and 2025, global solar capacity went from the lowest of 40 gigawatts to today the highest at almost 3 terawatts of energy. So, Salim, take us away here. Well, this is a really important piece to point out. We do this in all of our presentations where we point out how hard it is to spot this and how badly, cognitively, our brains are at seeing this curve, right? And you guys had talked about Chris Wright and his comment that in 50 years we'll see solar is still below 10%,

which kind of blows my mind. If we can flip the next slide, right? I want to give a couple of examples here because this is so important. So read this one out for those who are listening. So this is an exponential graph with Venote-Costla on it. And what he did was he went back. We saw exponential growth of mobile phones through the decade of 2000 to 2010, doubling every two years, okay?

He went back and he had a research analyst go and look at what did all the industry expert analysts say would be the growth of mobile phones. And in 2002, they predicted 16% growth year-on-year, okay? Two years later, gone up 100%. And the 2004 prediction was not 18 or 20 or 25%. And it went down. It went down to 14% growth. Predicted.

Why? Because they thought they were predicting. They thought they would be 14% growth because they thought it would level off. Okay, we just had 100% growth over two years. It's got to level off now. In 2006, they predicted 12% growth. It went up another 100% in reality. And between 2006 to 2008, it went up another 100%.

And they predicted 10%. percent growth, okay? Then it went up another 100%. I mean, how much more wrong can you be from 10% prediction when the actual reality is 100%. So this is the mobile phone predictions of all the top analysts, by the way, Gartner's, all these guys, okay? So this is kind of critical.

But this slide, I think, is killer. And if you were driving pullover and park and just look at this for a second, what you see in the black is the actual growth of solar energy over a 15, 20-year period, okay? What you see in the colored lines, and the curve, by the way, is that total hockey stick up into the right and exponential of epic levels, just going vertical. What you see in the colored lines, which are all horizontal, are the predictions year after year from the top energy experts in the world as to the future of solar. And we see is every time solar goes literally vertical, all the experts go linear.

They basically say it can't continue scaling like it's been. It's got to keep, it's got to just level off. It's got to level off. Right? Yeah. This goes from like 2012 to 2017, 2018. Now, the 2018 graph was even worse. It actually showed it going down.

The cost is dropping 50% every 18 months. How do you predict that it's going to go down? This kind of drives me nuts because this is not a math error. This is a cognitive error. And this, by the way, let me just point out again, these are not lay people. These are the top energy experts in the world getting it 100%. 180 degrees wrong, right? Literally, if I made predictions like this year after year, I should literally lose my job if I'm that far different from the reality. And this is the problem we have

because our governments are listening to these experts. It depends who employed them. If it was the colds and, you know. It really is kind of unbelievable that there's a whole other one about electric cars that I won't get into. They predicted that we would not have more than a million electric cars by 2040. And we crossed it in 2014. And we crossed it in 2014. And even then they didn't update their things. I'm going to give one more here. So this is a graph of solar module is dropping and then leveling off for a bit and then dropping again like a stone. And in 2003, the leading energy expert in the world in solar energy itself made a comment.

And he said, look, if you add up the cost of the silver and the glass and the wiring, the physical component cost of a solar module, you'll never get below a dollar or what. That's the limit. That's the actual limit. Now, the market actually believes them for a while, and it flattens out for a few years. Then it starts dropping. By 2014, it's 50 cents a watt. Now, it actually goes off the bottom of the graph.

Where we are today would be where my feet are sitting on this chair when the graph is this big. We're down to about two cents a watt or one close to a penny a watt. And his comment when he was showing this was, okay, getting below a dollar exceeded my expectations. That was his comment after being this. So it's really, really hard in. And I want to give a final example that we don't have a slide for, just to be fair to these folks, as how hard it is. So over the last 20 years, if you own a car wash in Buenos Aires in Argentina, your revenues

as a car wash owner have dropped by 50%. Now, one of our community members, Santiago Billinkas, who I think, Peter, you know well, lives there and says, this makes no sense. The middle class has exploded. We have a ton of more Mercedes and BMWs running around. Argentinians are very proud. they like to keep their cars clean. There should be a doubling or tripling of revenues.

Why is there a 50% drop? Is there water restrictions or there are hyper-competition or their legal issues or something? He starts looking into it and over a couple of months gets rid of all of the obvious factors. Then he finds the answer, which literally turns out to be Moore's law, because our computational ability over that 20 years has increased quite a bit.

Our ability to model the weather has gotten a lot better. And over that 20-year period, we're exactly 50% better at knowing when it's going to rain. And when you know it's going to rain, you don't wash your car. And the reason this is important is you can be the smartest car wash owner in the world and you will never see that coming. Right. And we call this in the book the orthogonal effect of innovation where it breakthrough in one domain affects you radically and you don't see it. You can't see it. Right. And so it's so critical to keep track not just of the demand side, but the supply side

of things. The most famous in all these others, and I'll end my rant here. is in the 1980s, McKinsey's advised AT&T on the future of mobile phones, and they predicted by the year 2000, there will not be more than a million mobile phones in the world. And AT&T left the business. I actually said that market doesn't work. By the year 2000, we had 100 million mobile phones,

so they're off by 99% in one of those. In one of our executive programs at Singularity, Peter, this guy puts up his hand when I mentioned this, I co-authored that report. I'm like, oh my God, is he going to, rebut this, whatever. He goes, no, you're absolutely right. The reason we got it wrong was when you had these big handsets with these briefcase batteries, we figured there's no way you're going to sell more than a million of those. We didn't see was that within a couple years, that had shrunk

to a clamshell. And that you could actually sell a ton of. And so that's the part that people miss. So when you track these, be really, really careful of making these outlandish predictions, like it'll never get below this or never get about that. We've seen repeatedly. I don't know why you want to end that rant. That was the coolest thing. For years, we've been struggling with this talking to governments, and they're like, yeah, this will never happen, that'll ever happen. We go berserk. Sorry, I love those slides. I love those slides.

And you know what else? When Bill Gross was on the pod, he said, you know, all the lands where pumped hydro has already been bought. I did a little research. And actually, not true, lots of land where pumped hydro makes a ton of sense, but it's not quite as sunny, has not. yet been bought if anyone's listening. And because the solar panels are getting so cheap, you can just put more of them there. And so heads up, you know, there's a theme. If the governor of New Hampshire is listening, please give me a call. But there's lots of opportunity that hasn't been tapped in real estate. I have two more quick energy factoids. Okay. One, I did a little

bit of research and I was talking to one of our energy gurus in our ecosystem. It turns out there if you add up all the dams in the U.S., there's 10 gigawatts of potential hydroelectric power that's not been tapped. So we could put all those dams. That's a big number. Sorry, I'm really going off here, but I remember we were on the pod and we said, holy shit, the Hoover Dam right now is operating at about 5 to 10% capacity. Oh, yeah, absolutely.

Because it hasn't rained. Yeah. So we're like, why the hell are we not doing pumped hydro right from that? Pump the water from the bottom of the top? Tons of sunshine right there. Turned out somebody had already thought it, put together an entire, entire, investment thesis around it. But it was exactly the right idea. But that theme isn't over. That is still very hot. I think the point we started this whole conversation is, is China is running away with solar

deployment. And I don't understand why we don't see it here in the U.S. I'm a pilot. I fly at a Santa Monica airport. I fly over L.A. and all I see is naked roofs that could be all be producing electricity. You know, there's a few solar thermal farms out in the middle of the desert. But But there's so much potential. So, so much potential. All right. It's geopolitical. It's geopolitical because China has pretty much a lock on the supply chain and the panels.

Well, I would be, you know, I'd be investing in building out solar capacity manufacturing here, right? Yes, we should. Solar cities. Actually, what I would look to do is say, what's the 10x to 100x breakthrough on photonics or solar past the next level and go after that? And Alex, you know, digital superintelligence will give us new material sciences, give us new capabilities for that. So there will be. That's why Alex is standing there, not looking worried at all.

He's like, p, for these guys. I think there are many ways to generate useful energy. I think fission in the form of SMRs, fusion, potentially as soon as, as we've discussed in the past 2028 to 2030, I think there are so many non-solar novel. is forms of energy that are on the verge of coming online. I'm not losing sleep over geopolitical imbalances over solar photovoltaics. All right. Let's jump into robotics here. This is a fascinating tweet turned into an article here. China's robotic boom is going global. So if you look at the first half of 2025 and the companies or the countries around the world that are purchasing,

robots from China. Poland is up 1,700 percent. Mexico, 275 percent, Russia, 135 percent, Vietnam, 114 percent, as opposed to South Korea, Germany, and USA, which is, you know, minus three to U.S. at 58 percent. The point here is the countries that are, you know, our blank sheet, are not, don't have a robotics industry, are buying from China. So countries are starting their automation journey and buying from China. So this is something that the U.S. needs to be looking at. Basically, China is staking its flag in countries around the world by deploying both AI and robotics in a very cost-effective fashion. I wouldn't be surprised, given how central robotics in general, general purpose robotics, more particularly human, general purpose or humanoid, general purpose robotics even more particularly, how central those are to this emerging industrial ecology of batteries and fabs and chips and AI compute and probably SMRs and drones, that we see an emerging demand function for.

fully sovereign robotic ecologies. It seems to the extent, Peter, you were suggesting earlier, you're looking for other, maybe you don't want to call them sort of too scarce to fail resources, but robotics, I think, is a plausible candidate for wanting to be sovereign aligned resources in the near term future. Yeah. You know, I have to know, Rod Brooks, the founder of Irobot when we were out in California a couple weeks ago. Yep. And he reaffirmed what I think we all know that our whole parts supply chain,

component supply chain is garbage compared to what China has. Because, you know, all those years of manufacturing moving over to China, industrialization, moving over to China, they developed a very, very flexible parts and components, contract supply chain. So if you need something to build your robot,

you can call someone and have them make it and it'll be there in a few days. There's no equivalent in the U.S. So it's going to take a while to rebuild that whole supply chain. So what Alex said is exactly right. This is ripe for national involvement to kickstart it. It's also not naturally happening in the venture community. It was really tough for venture capitalists to plunk down 10, 20 million bucks

for like an electric motor winding company or a, you know, a gear company. We should have a Manhattan-style project for supply chain for robots and drones. There are various initiatives that have been discussed, including famously, perhaps, the soft-bank initiative. We heard this from, we heard this from Bert Borick, CEO of 1X. I've heard this from Brett Adcock, from Elon directly. They've had to completely build their entire bottom-up supply chain internally. Every component is manufactured inside the company right now, which is insane. What a waste.

But the other thing that's going to be interesting is there, will be a scarcity in robots for the foreseeable future until production gets ramped up. So we're going to start to see governments probably bidding. Like, you know, we'll buy a million robots here in Saudi or the Emirates or Qatar in order to get early supplies delivered there. And that may bid up the prices in early days, too. I would view any emerging robot scarcity as just a third. facet of compute scarcity, the most important robots are just going to be GPUs on legs.

And the compute ultimately is, I think, the fundamental scarce factor here. All right. Next item here is a interesting graph, which asks the question, what if everyone in the U.S. drove like Waymo? So here's the extension, if every U.S. vehicle performed as well as Waymo, we'd prevent 33 to 39 deaths annually. So pretty profound. I found a better, I found a better related statistic. Please. Which is it turns out about 50% of all the court cases in the U.S. are car accidents. Wow. 50%. So you take out a bunch of lawyers also, which, you know, that's not bad.

That's a good thing. That's a good thing. With all due respect to some lawyers, reducing the number is is definitely an optimization function. So he is huge. And interesting for Waymo, nearly half of all Waymo impacts crashes happen under one mile per hour. So these are just bumps. They're not actually crashes. So that's crazy. I saw this, I saw this stat and I said that's got to be global, not US, because that's about the total number of US deaths. No, it's 1.2 million people a year die around the world with car accidents globally. Around the world, yeah. Well, that's why I thought, You know, 40,000 out of 1.2 million is viable, but 40,000 in the U.S. isn't. But then if you read the fine print and the notes, it's actually a 90% reduction in fatal crashes.

It's huge. And 15% of all organ donations come from auto accidents. Interestingly enough. Right? So I just, I live here in Santa Monica and Waymos are all over the place. I just started seeing the Zooks vehicle from Amazon going and collecting data, right? It's a piloted vehicle with all of the LIDAR and cameras around it going and mapping the streets. It was about a year ago that you saw all the piloted Waymo vehicles mapping the streets.

So we're going to have Zooks. We're going to have Waymo. We're going to see Cybercab or whatever Elon calls it very, very soon. Meanwhile, we have people attacking the Waymoes. Brad Templeton used to joke because we don't want to be killed by robots. We'd much rather be killed by drunk people, which is what's happening today. I suspect for at least most Americans, their first encounter with a generalist robot is going to be by encountering either by driving in or we're seeing Waymo or FSD-based car or Zooks or equivalent. And this is just the beginning of a longer journey.

We start with these generalist robots on the roads and they'll be in our homes before we know it. And guys, just a quick announcement, Dara, the CEO of Uber, will be joining us on stage at the Abundance Summit. And yeah, super cool. And so Uber is partnered in part with Waymo. We'll be offering Waymo as part of your Uber app. And they're also working with Jobi for flying cars. So super fun. We'll be talking about all of those things and where Uber is going in the future.

flying cars is my big hope for technology in the near future yeah tired of driving airport transfers are just horrible it is it is awful all right we're going to wrap up with health and biotech i think one of the most important subjects at least in my life is how do we double our human lifespan how do we avoid all of the travesty of chronic disease first article comes in from a friend joe le betts lecroy Joe's company, he's the CEO of Retro Biosciences. It's one of Sam's companies. Sam is founded with $180 million of backing back in 2021. Their mission is to add 10 healthy years on human lifespan.

They're one of the teams competing for our $101 million X-Prize health span. And Saleem and Dave, since you're on the board of XPRIZE, I mean, pretty amazing. that competition, just for everybody, if you haven't heard of it, I raised $157 million for a global competition to add up to 20 healthy years on people's lives, in particular in immune, cognition, and muscle. And we now have over 730 teams that have entered that competition, which is pretty amazing, if you ask me. That's got to be a record, right? It is. That's incredible. Yeah, well, actually, for Elon's hundred million dollar carbon prize. We had 1,300 teams. But I would, I would have to say this is

as hard or harder because you have to run effectively a clinical trial and prove on a human population that your therapy didn't just do cognition, didn't just do muscle or immune. It did all of them. So anyway, I love the fact that Retro was going after this. Their product is, is entering human trials next year with a hope of, in Australia, in late 2025, and they're going to be hopefully getting something on the market the next couple of years. This is called RTR-242. It's an experimental Alzheimer's pill designed to restart the brain's natural recycling process of toxic proteins. This is your lymphatic system. When you're in deep sleep, your lymphatic system is clearing your brain of those toxic proteins.

So one of the biggest things. I had, I had Mehmet Oz speaking at the Platinum event, and their abundance longevity summit as well. And his biggest concern for the future is neurodegenerative disease and also one other disease called loneliness. We should talk about that sometime. I want to end with this article. I find this fascinating.

This is out of China. and one of the things about longevity and biotech is if it works in China, it'll work in Chicago, if works in Boston, it'll work in Botswana. We all have the same biology. So this rocketed around the world as news this past weekend. So Chinese scientists have genetically engineered a gene called FOX-O-3 that is a critical stress-resistant transcription factor. and they've been able, as they modify this, to reduce aging by three to five years. And for me, this is a huge, huge deal.

So in 61 different tissues. End of the day, we're going to start to see longevity becoming more and more real. And everyone listening, I want to let you know that the next 50 years that you're alive and hearing us on this podcast, it's going to be awesome. Just don't get hit by a bus in the next couple of years. Yeah, exactly. Don't die from something stupid in the interim. Peter, there was a comment I heard a few years ago, a couple of years ago, and I wanted to just ratify where we are with that.

Somebody on one of the abundance stages said that we have the labs, mice in labs today that are living to the equivalent of 300 years old already. Is that, and are we really there? No, we're not there yet. You know, the average mouse is living. on the order of 20 to 24 months. We've seen extension of 30 to 40%. There are, I just, I was just over at Harvard,

spent the day in the weekend with David Sinclair and then the day at the WISA Institute, the Vs Institute with George Church. And those experiments where they hope to double the mouse's lifespan are going on right now. We've also seen the first epigenetic reprogramming trials are going on in here. humans starting in January. So life bioscience is one of David Sinclair's companies is going into

humans. It's been very successful in animal models, including non-human primates. After this longevity trip, when's your best prediction of when we break through the aging barrier? Life, escape philosophy. So I asked the smartest people on the trip that I know. And their belief is there is no upper limit to how long we can live. Just let's begin with that. And the belief is that the breakthrough is required to understand why we age, how to slow it, stop it, reverse it, is going to fall at the knees of digital superintelligence. And, you know, this is, we heard Dario talk about this doubling the human lifespan in five to ten years. and you know it's interesting uh we had a bunch of scientists from mit and harvard principally

at the summit and uh they fell into two groups those that amongst themselves were consistent saying uh we're going to see this doubling we're going to see the significant lifespan and health span extension and those saying nope not going to happen uh it just extremely on the other side Wow. And so it's interesting because I define an expert as someone who can tell you exactly how it can't be done. Yes. And for what it's worth, Salim, I've asked this question of all of the best frontier models of the day, when do we get longevity, escape velocity? And their consensus is 2030.

Which is exactly the same time when Bitcoin hits a million dollars according to all the frontier models. Which is exactly what Ray predicted, 2030. It's like, damn it. Ray was right. Damn, they're right. He may be proof that time travel is real. Yeah, that in Elon. Yes, exactly.

So everybody got to hang on. Stay in good health, sleep, diet, exercise, mindset. Don't die for something stupid. You got hold on for the next five, ten years. There are therapies coming and there are significant therapies. I did a podcast with Davidson, on Moonshots, if you listen to it, please do. It's an amazing podcast, that one.

It's a must to listen. Let me give kudos to the Moonshot community here one moment. You know, when I did that podcast with David, he came on and he was really miffed. The Harvard White House debate and headbutting had canceled all his funding. Four million dollars of funding got canceled. and he was on the verge of letting his entire research team go, all of his researchers. And I was just pissed and I said, let's turn this around. And on the podcast, almost off the cuff, we announced this thing called Frenz of Sinclair Lab

where folks would contribute $50,000. I was the first to offer to contribute, as was David himself. And since then, we have gotten over $4 million of donations from the people listening to this podcast, which is insane. So we completely replaced these government funding. I'm looking to buy a Ferrari. If anybody wants to donate to them. No, but this is decentralized science.

It's great. It's citizen-driven, bottom-up science. It's so awesome. And the challenge is that when you're funded by government and have peer review, you're stuck in incrementalism. Yeah. anything dramatically different you know they don't want to get it funded yeah it's great yeah Dave what's your week look like for you buddy uh well's Friday so um yeah you know we have uh

a lot of our best and brightest that are coming through the lab are getting funding right now a lot of them are getting west coast term sheets at like two or three times higher than the east coast. So there's quite a bit of migration west going on. One of our coolest companies that we signed the term sheet in Mark Zuckerberg's old dorm room. And, you know, there's a poster of the social network movie signed by Mark Zuckerberg on the wall. So we signed the term sheet right in front of the poster. Then that got all around Harvard. So 20 people joined the company for no salary because it's so hot. Anyway, they're smoking hot now. It's by a cold biography. They're moving to the West Coast. So I got a whole bunch of open seats here in the lab. So I'm really

excited to spend time on campus backfilling, you know, trying, we're going to try to get 16 more teams in. And, you know, January is coming fast. You know, MIT has January off. Yes, IAP. So that's the perfect time. IAP. Perfect time to boot up a company. So if you're at MIT or Harvard or Northeastern and you're hearing this podcast, first of all, Dave's a rock star. If you've got a couple of best friends and you want to start an AI company, where do they go, Dave? go to the link ventures website or just email dan oliveri or kush bavaria their names are on the website and it's just k bavaria or d olivari at link ventures and you got to have at least three people

that are bona fide best friends and we'll check we'll we'll poke around and ask your other friends are you really best friends but we only only bring in teams that are super tight net keeps it all really really fun selim how about you what's uh what's the week ahead look like We're doing a whole bunch of planning with our ecosystem to think about how we leapfrog everything we've done in the past and go 10x faster, better, cheaper with all the offerings that we have. We have our next X, 10X shift workshop on October 15th. It's 100 bucks. People, those are all selling out. Those are great.

And we cover the model and show people how to take their organization literally 10 to 100x now through that two hours. workshop. And I've got a little bit of travel, but not too much before the madness towards the end of the month. Visioneering is coming up, which I'm super excited about. Yeah, for sure. And Alex, welcome back from your secret mission. And excited to work on our project together, which will unveil at some point. We're going to keep it secret for the time being. How about what's on your agenda? Trying to accelerate the singularity or whatever it is. Maybe singularity at this point isn't even the right term, but smoothing out and moving whatever we want to call it, the intelligence explosion, or if you're a technological determinist, the what was always going to happen, the inevitable byproduct of building an internet and then compressing the internet and then using that to solve everything else. I think timelines are very short at this point.

Every week, my timelines are getting shorter. Usually it's the case that I'm the accelerationista in the room, not always, but usually, and my timelines are incredibly short at this point. My favorite thing these days in these podcasts is watching Alex's faces, we rant about energy or health care or something. He's like, oh, super intolerant is going to just solve that. Why are we even talking about this? This is a great look at his face. It's so awesome. You're reading my face, I think, correctly, Salim.

There is a certain sense of hyper-deflationary mentality. Why do anything? Oh, yeah. It's really. It's AI paralysis. It's like the starship. It's like the starship who heads out. And when they get there, they find out, you know,

warp tribe has been invented. It's a term for it's called the weight equation. And it does cause singularity paralysis for lack of a better term. And I'm seeing it more and more in every day in conversations. I have as it dawns on more and more subject matter experts that AI is about to transcend their capabilities in, call it two to three years, if the current extrapolations hold, what happens next? And I spend a lot of thought thinking about that. Amazing. Well, everybody, thank you for joining us, subscribers. If you haven't yet, subscribe so we can

tell you when the next WTF episode is taking place. Hope you found this super useful. Be optimistic. to the most extraordinary time ever in human history, a time where we can uplift every man, woman, and child, where each of us is going to be able to take on the grand challenges we desire and really go from success to significance on a global scale. So, so happy to be alive right now and so happy to be with my moonshot mates. All right, guys, until we see each other next time. Every week, my team and I study the top 10 technology metatrends

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