The OpenAI Internet Browser Has Arrived: ChatGPT Atlas w/ Dave Blundin & Alexander Wissner-Gross | EP #203

28:13That's why the AI labs are talking about this use case so much, because it's life. It's preserving lives. Yeah. Yeah. And by the way, Jeff, Jeffrey by Melton and Lila will be at the Abundance Summit. Super excited for them to present our theme in March of 26th at the summit is super intelligence and the rise of human robots. So he said, OK, that's definitely a subject I want to cover. All right, let's move on. Wikipedia says human traffic has been dropping down 8 % year on year. Less humans are coming to Wikipedia. We can dive into this. I'm still waiting for Grokipedia to come online. Alex, what are your thoughts here?

28:59Yeah, I get asked the question a lot, how do we incentivize humans to create new knowledge in an era of generative AI. And I suspect the question itself is probably faulty. I think knowledge gathering is likely itself to transition to AI. I think we'll see investigative reporting that's AI-based. So I'm not losing sleep over human traffic dropping in an era when knowledge synthesis is abundant, but knowledge generation by AI is not yet abundant. And I think AI-generated knowledge is right around the corner. Yeah. Okay, Dave, go ahead and then I have a rant on this. All right. Well, this is right in my wheelhouse, so I need to wax poetic for a minute on this topic.

29:47So I've been the founder of 20 direct-to-consumer AI companies. First and foremost, every time someone complains about their traffic going down, it's going somewhere else. It's not going away. Overall traffic is going up very, very quickly. And so, you know, I'm involved in a company I can't name right now that's gone from nothing to$600 million of revenue purely from online arrivals,$100 million of profit on the bottom line. And so when Wikipedia says, hey, traffic is going down, it's going to some other place. And the formula for getting the traffic is well known now. You know, first and foremost, you need to create huge amounts of AI-generated content, but it has to be good content.

30:26But you also have to pay the man. You got to pay Google. You got to pay Facebook. And if you do that concurrently with putting your content out there, then they'll give you the traffic. Also, you need to reformat your content so it's easily readable, interpretable by the AI, hence GEO at the bottom of the slide, generative engine optimization. Because in the future, people do not go to Wikipedia for their content. They just ask the AI. The AI has got all the information. But it still needs to be factually accurate and correct. And so that role. And I'm a big Wikipedia fan. But, you know, I was at the Washington Post when it was getting obliterated by the Internet, and it felt like, hey, we're important for the country.

31:05We're factual. It doesn't matter. You're going away. And so that's what's happening. My rant on this, you know, I've been trying to update my Wikipedia page for literally two years. I hired consultants to update my Wikipedia page, and every time it's updated, they bring it back to what it was. It's like so stuck 20 years ago. and you know i don't know i i used to use wikipedia i don't anymore and the ability for an ai to actually search the web and get consistent and relevant and accurate information about me so i i think maybe grackopedia will be a solution here or in fact any ai that just says you know spin up a page on dave blunden i can send somebody that's going to be awesome i'll give you one other pro tip, get a similar web account, similarweb.com, get a similar web account, and you can see exactly where that user went.

32:00The guy that would have gone to Wikipedia yesterday, where did he go instead today? And so then if you track where it's all moving, replicate that behavior and you'll succeed. Amazing. All right. Next article here is GPT-5 Rediscovers Long forgotten math connections. This has Alex Wiesler-Gross written all over it. Dr. Gross, please tell us. Peter, I talk frequently about how superintelligence is and will be solving math, science, engineering, medicine, other fields. There was a lot of hand-wringing over the past week plus about a specific set of math problems and whether AI in general and GPT-5 specifically was actually uncovering new math.

32:46And I think this story sort of beautifully encapsulates the fog of war we're in right now. The water level of intelligence is rising day by day, and some of the earliest math problems, open math problems, to be solved, I think will be math problems where the solutions were known to a subset of humanity, but not to all of humanity. And we're going to wring our hands collectively as a civilization quite a bit over, well, was this open problem in math really open or was it solved or was it half open where some people knew how to solve it and other people didn't know that it had even been solved? That's the fog of war phase that we're in.

33:28So there was a lot of discussion over the past week, like, was this a real accomplishment, a real discovery in math by AI, one of the Erdős problems, number 1043, for example? But there was, I think, ultimately, a lot of really revealing discussion and commentary on this particular problem and also other Erdős problems that actually this is just a phase right now. But early days, we're still cleaning up the house, as it were, in terms of understanding even which problems are open, closed, or somewhere in between. And after this phase, I predict we'll get to a phase where a lot of the uncertainty is reduced regarding whether a given problem is actually open or not.

34:13When you say open, you mean solved, right? You mean solved by open. Open means unsolved. Closed means solved. I think this is also a great little case study in how the academia world is like, well, this proves that it didn't really solve it. It looked up an ancient, like, when you're trying to do something, you don't care a whit how it solved it. It came back with the right answer. This is a lot like, you know, Thinkstruct in our lab. It's a company that does academic research and now patent research using AI. So, Nikki Abate and Julius Heidkutter. and it is actually turning out to be a really good hybrid of writing your patent application while doing all the background research for all prior applications and all prior knowledge and so those two things are are integrated and this is where you're seeing ai being superhuman because normally you'd say oh well research of old documents is this guy but thinking of new things is this other guy the ai doesn't care it just does both i'm so excited about the use of ai in writing up and submitting patents and talk about something that is extraordinary.

35:20But one of my favorite applications of AIs and patents was the following. This was a conversation with an abundance member who was like, you know, I want to figure out how to use these technologies on my business. And I said, well, why don't you just ask? And so what I showed her said, okay, here are three patents you're interested in. put them in the browser and say, this is my business. How would I combine these three patents together to make a new product or service in my business? And oh my God, it's extraordinary, right? This is literally a creative engine. All right. Well, anyone who's a real fan of this podcast by now has to have read Accelerando because Alex Wisner Gross says it's the best piece of writing in the history of humanity.

36:05If you heard that and then didn't read it, Something's wrong with you. But the very first chapter, the opening scene, is exactly what we're talking about right now. The lead character makes a living with AI-generated patent filing. Yes, consistently, and then giving it away. Anyway, let's not go there. All right, our next article here is Uber tests microwork for drivers to train AI. So Uber is paying between 50 cents to a dollar per task that can take two to three minutes and get processed within 24 hours. So is this sort of a digital task rabbit? What is this, Dave? Dave? This is really, really cool because Mercore is almost closing in on a billion of revenue, going all over the world, grabbing expertise and getting it into a format where the AI can assimilate it and then the AI can be an expert in that topic too.

36:58Well, you got all these Uber drivers driving around. They're sitting around a lot of the time. Do they have knowledge that may be a contributor back into the great AI machine? Because a lot of what's missing is physical motion, common sense, just all this information. So why not use that same platform you've already got to be another Mercore-type AI data-gathering machine? Alex, your thoughts on this? Yeah, I think this points directionally to the future of the gig economy. The gig economy historically was focused on the physical world, physical tasks, inclusive of driving other people to their locations or driving food to a person's location.

37:38I think this points toward a near future where training robots to perform service economy tasks is the new de facto gig economy. Yeah. So fascinating that Uber turned this way. It's all about the relationships it has, right? It has a relationship with a large number of people that it knows wants to earn money on the margin. And we'll probably see other companies follow suit as well. Well, you know, during COVID, you know, Lyft got annihilated and Uber did fine because they had launched Uber Eats. So they're, you know, they're very, very thoughtful about this, you know, and in fact, when, when, I don't know if you remember Travis Kalanick when Uber was going public, but he got on stage and he said, Uber is not a ride sharing, hailing cab company.

38:25We're a internet fabric. It was some, some like really ethereal, but now they're actually doing it. It makes sense in hindsight. So they don't view their platform as being about cars and rides. They view it about like Gals is saying. We're going to spend time with Dara, the CEO of Uber. He's going to be on stage with us at the Abundance Summit and have a longstanding relationship with Dara. We'll talk about what he's doing on the data side, but also, you know, they're now partnered with Waymo. You can, in certain places, hire a Waymo through Uber and they're hooking up, I think, with Joby on the flying cars, let's call it that, for the moment.

39:05So Uber has been an incredible platform for experimentation and sort of integration of various exponential technologies. So that'll be fun. All right. I can't wait. Alex, I'm going to turn to you on this one. DeepSeek is packing text into images. Talk about this, pal. This isn't a significant transformation, isn't it? Yeah, this is a major advance from DeepSeq. So a new model that DeepSeq announced, DeepSeq OCR. So maybe a bit of background first. Foundation models, frontier models like GPT, aren't thought to perceive text in the way that humans perceive text. Humans look at text on a page and we see text visually.

39:47The frontier models, the foundation models, most of them are believed to still consume text in the form of chunks of letters called tokens. And they don't perceive, have any, based on publicly available information, any visual perception of letters on a page. So they don't visually see the shape of a character or formatting or desktop publishing type layout on a page. They perceive none of that. They perceive at best maybe like HTML formatting instructions. So I think DeepSeek OCR, which is, again, if you squint at the model architecture, it's sort of an autoencoder that does optical character recognition after a fashion, but in a really interesting way.

40:34It consumes raw images of entire pages and encodes those as image tokens, not as text tokens, and then tries to decode those image tokens into text tokens. So a few things fall out of this. One, optical character recognition at high accuracy rates, which is pretty incredible. But secondly, this is able to perceive formatting the way humans do. And I think the practical upshot of this would be better grounding. Like, wouldn't it be wonderful if we could have desktop publishing type formatting of outputs from frontier models with beautiful layouts? I would expect that to fall out for free or better understanding of mathematical equations that are dependent on the way the equations are written and how they appear visually.

41:19I think better understanding of fonts. All of these I expect eventually to fall out of this line of research. Interesting. And we're going to be seeing an article later about Amazon getting into the AR glass marketplace. And we're going to see from Meta and Google and probably OpenAI and all of them were transforming from a phone as the medium of interface to glasses at this medium interface. So I'm assuming that this kind of technology is going to help your glass effectively translate everything you're seeing into something that can be understood, read, and responded to. I think that that's table stakes.

42:01So yes to that, but also having AI that understands at a visual level all the text, I think that is going to be quite transformative. Dave, you want to comment on this? Well, I'm still blown away that if I'm writing code in Cursor or Windsurf and I take a screenshot and say, hey, there's a bug in here somewhere. It's an image. It's not text. And I just slap that right back into Cursor. It has no problem with it at all. Now, I know under the covers it's not doing this. It's actually converting it to text and then moving forward from there. So this will put the AI engine much more in tune with human thinking because you're using the same exact pixel-by-pixel interface that we use with our eyeballs for everything, whether it's text or images or whatever.

42:45So it'll be a big advantage in multimodal. But what works already is just mind-blowing to me. Do you expect, Alex, that we're going to see this type of OCR come into all the models next? Yeah, I think we're moving towards a near future with universal tokens, tokens that span modalities. And I've long thought it wouldn't be wonderful aspirationally if we had just a single modality that everything else flowed through. So rather than having a text modality and images and audio and video, we just had maybe like a single universal, maybe video style modality that everything else flowed through. It might have certain benefits.

43:23You know, what's really interesting about that, Alex, is that that's happening and it puts the models much more in touch with humans. And at the same time, it's going the other direction in very specific domains like magnetic bottles and quantum computing where the knowledge is so far out of the human domain that you want completely different data representations at the front end of the funnel. And so these first models are going to use the second models as tools. It's really cool to watch the two kind of spread apart and think about how they're going to end up interacting. This episode is brought to you by Blitzy, autonomous software development with infinite code context.

44:02Blitzy uses thousands of specialized AI agents that think for hours to understand enterprise scale code bases with millions of lines of code. Engineers start every development sprint with the Blitzy platform, bringing in their development requirements. The Blitzy platform provides a plan, then generates and pre-compiles code for each task. Blitzy delivers 80 % or more of the development work autonomously, while providing a guide for the final 20 % of human development work required to complete the sprint. enterprises are achieving a 5x engineering velocity increase when incorporating Blitzy as their pre-IDE development tool, pairing it with their coding co-pilot of choice to bring an AI native SDLC into their org.

44:50Ready to 5x your engineering velocity? Visit blitzy.com to schedule a demo and start building with Blitzy today. All right, let's jump into our next article here. This is OpenAI hires bankers to automate junior work. So OpenAI has hired over 100 bankers paying them 150 bucks an hour to train AIs on M &A, LBOs, IPOs. Effectively, these bankers are, in one sort of the way, traders helping to eliminate jobs of fellow bankers. So I don't know my first take on this is open ai is basically eliminating what i would have imagined an entrepreneurial startup would do i imagine lots of startups are looking to do this and this is sort of a shot over the bow well you know is open ai going to do this for every field um you know get rid of white collar work across the board um and well the answer to that is absolutely yes they are going to do this for every field and they're going to do it quickly and i just had this conversation with two of our companies, make sure that you're the guy that Sam calls.

45:57And they're like, well, Sam's not going to call me. Like, why would Sam call me? They said, okay, eliminate everybody else. He's not going to call State Street Bank. He's not going to call, like, he doesn't want to talk to big legacy bloated entities. All right. And he's also not likely to call two 22-year-olds out of Y Combinator who haven't even gotten to market yet. So if you're somewhere between those two things, you just need to position yourself, like Brendan Foody did at Mercore, get into the building and be the person that solves that problem for open AI. But yes, that's the answer. He'll do this in absolutely every category of human endeavor.

46:32So I would imagine this kind of a vertical would be something that an entrepreneur would say, okay, we're going to go and do this ourselves for whatever field. But again, we talked about this when we're up with Kevin, Kevin wheel, that is open AI going to be moving into and eliminating all the entrepreneurial vertical channels. Um, I find this fascinating. Yeah. Go ahead. I think the, the sort of the superficial story is that this is what the end of so-called white collar work looks like vertical by vertical labor category by labor category, each existing form of the service economy, each manifestation of it gets digested and and turned into AI automation.

47:16But I think that creates enormous entrepreneurial opportunities for everyone. There are thousands, if not tens of thousands of labor categories with domain-specific knowledge that will require automation. Same with industry subverticals. And every platform company always instills maybe a modicum of fear in other companies. Oh, well, the platform will just absorb what I'm doing and we'll lose our footing. But I don't think that's an accurate representation of the real economy where there is just tens of trillions of dollars of service economy labor that can be automated. And I do not expect a singleton scenario where any one company or any one platform or any one model just consumes the entire economy.

48:03We'll have, I think a completely heterogeneous economy and definitely into the future. So bottom line here is that this effort by OpenAI could eliminate between a quarter and half of the junior headcount across Wall Street within two years. All right, moving on. I love this article. So Google is prepping Genie 3 for public experiments. So Genie 3 is going to let users create interactive worlds with text prompts. We talked about this. Extraordinarily powerful. This is persistent and consistent worlds that are generated from a text prompt that are photorealistic, that you can get into and you can use for a variety of different areas.

48:52Alex, do you want to jump in? First of all, you have to admire that the user interface, which we're now seeing previews of looks identical almost to the grid of the holodeck in star trek yes i love that i have to admire that that we're catching up with the future it's very exciting a level deeper though i i do think world models so-called right now are going to merge with the foundation models i i think this is very likely to be an instrumental element of general purpose generalist foundation models and frontier models that you'll not just be able to have text-based conversations with them or audio-based conversations they'll create entire worlds that you'll be able to walk around on the one hand that's the consumer use case and the enterprise use case is these world models that are fully interactive will enable us to create new inventions create new products it this is the mode through which ai understands and will understand the physical world and be able to create economically transformative inventions it's the democratization of interactive content creation, right?

49:57At a level of reality resolution, that is shocking. Just to hit on some of the ideas, right? For the individual, if you're thinking about this, how would I use it? You can build personalized gaming, it's creative storytelling, it's customized education. For companies, I think a lot of companies that can be using this for game development, for education tech, I personally think the most extraordinary way to educate and learn about something is to dive into that world. I've used this example so many times. If you want to learn Greek history, you can read a very dry textbook. You can even watch a movie.

50:34But imagine being able to drop into ancient Greece. You see a guy in a toga on a chunk of marble and you walk over and he says, hey, I'm Socrates. Let's go for a walk. Let me show you around. Meet my friends. That kind of immersive experience is the future of education without, for me, any question at all. Dave? Well, just not to disappoint everybody, but this is going to be another one of those things that everybody instantly loves. Just like deep research, if you've tried using Gemini Deep Research lately, you'll sit there for like 10, 15 minutes unnecessarily, and then it'll give you something great back, but it's just enough to frustrate the hell out of you.

51:15It's entirely... More GPUs. More GPUs, man. Keep tiling because people are going to love it. It's incredible. And unless you buy your own NVIDIA box, you're not going to be able to get the speed you want. All right. Our next article here is Meta borrows$27 billion to build an AI data center. So Meta SPV is borrowing this money at 6.8 % to fund a multi-gigawatt Louisiana data center. Dave, you had some thoughts on this one. Yeah, absolutely. So Mark Zuckerberg has taken every penny of cash flow from one of the biggest tech companies on the planet, from Meta, Facebook, and pumped it all into this AI initiative.

51:57And now is borrowing, going to the next level, and the stock market loves it. So what does that tell you as a CEO? Like if you're a true AI company and on a true AI mission, you can invest like crazy from your public capital or from your venture capitalists. And they love it because they see the future is here. But I don't think it's probably unprecedented in history for a company that used to be an absolute bottom line cash cow producing huge amounts of EBIT to take every penny of it and then more, then borrow even more to pump it into an initiative. I mean, Mark has said over and over again, he will do whatever he needs to get to digital superintelligence first.

52:40It's like his war cry. Alex? I think it's also worth adding the credit markets are just as interested in financing this project, call it tiling the earth with compute, as the equity markets. And the fixed income slash credit slash debt markets are enormous. And I think we're starting to see this financial model where the lower half of the AI infra stack is being funded by credit, as we're seeing here. And then the upper half, where the models and the applications live, is being funded by equity. So we're seeing sort of a whole of economy financing model emerge for this full AI infra stack. It's, you know, the implications of this, though, is capital from public equities, from sovereigns, from debt, all flowing into AI at the exclusion of so many other technology areas.

53:31One of our best partners, Kush Bavaria, phenomenal guy, just co-founded a company called Ornn, O-R-N-N. Yeah, check it out. But my point in this is that people that are kind of technical in engineering wouldn't normally get into the finance side of things. But, you know, kind of like Chase Lockmiller, they're getting drawn into this in a big way. And it's a very, very good strategic move. If you have any interest in finance whatsoever and you understand GPUs, chips, data centers, or just math, it's a great direction to go. It's just a huge amount of capital redirecting into this direction and making it move intelligently, the right investments, the right locations.

54:10That's not a trivial problem at all. So if you have an engineering mindset and you're interested in this area, you can really do well. Yeah, amazing. Okay, on the data center world, here's the news from Oracle. Oracle is planning a 16 Zetaflop AI supercomputer. We don't talk about Zetaflops all that often. So it's announced a next-gen cloud computer design scaling to 800 ,000 GPUs. You know, a Zetaflop here, a Zetaflop there. All right. I'm going to feed Alex on this one. I can't wait to hear what he has to say. But I remember on that podcast a couple months ago, we were talking about the 10E26 models.

54:49So the E26, that's the regulatory definition of an AGI superintelligent register it with the government type thing. So that's one E26. A zeta flop is what? One E21. So that's per second, though. That's that many flops per second. So we're talking about the exponent of... Yes, go ahead. Yeah, so to get from 10 to the 16s to 10 to 21, you need five more ooms. so that's 100 ,000 so every 100 ,000 seconds are orders of magnitude just to translate i have more rooms five more so 100 ,000 x so so every 100 ,000 seconds a one zeta flop computer can create a foundation frontier level ai model every 100 ,000 seconds so 100 ,000 seconds is 1.1 days as it turns out so every day you get a new foundation and that's at one zeta flop this is 16 Zetaflops.

55:46So 16 times a day, you build a foundation frontier level model. Does that sound right, Alex? Did I get any of that wrong? I need to double check, but it sounds approximately right. I would add, so Oracle is, this is all in the public reporting, Oracle is both financing and operating Stargate Abilene. And Stargate Abilene is, I think, together with this 16 Zetaflop, super cluster, it is emblematic of a new form factor for computing. The personal computer was a major new form factor. The smartphone was arguably a major new form factor. These super clusters with approximately a million GPUs and tens of Zeta flops, this is a fundamentally new form factor for computing with high-speed interconnect, which we're not talking about, but which is arguably just as important as the raw compute power being a key architectural innovation.

56:47And it's not going to stop with Stargate Abilene. This form factor, again, in the spirit of tiling the Earth with compute, we are, unless something radical changes, we are going to tile the Earth and maybe near-Earth solar system with this type of new form factor of computer. Incredible. All right. Continuing on this conversation, Anthropic to expand to 1 million TPUs on Google Cloud. So their goal is to bring this compute online by 2026. I think there's a very loving relationship between Google and Anthropic. Anthropic's sort of the little brother there, and they're going closer and closer. Alex, what do you make of this?

57:32Well, I want to say something a little bit glib, perhaps, which is that when you have super intelligence that's incredibly thirsty for compute, it makes for some interesting combinations in the market. I think the thirst for compute is creating enormous pressure on the Frontier Labs to diversify their infrastructure. So we're seeing NVIDIA GPUs up against Google TPUs, up against Amazon Traniums, up against ASICs, including Frontier Labs specific ASICs. I think these are all in the mix. So for those who are worried about some sort of architectural monopoly or singleton where only one GPU or accelerated compute architecture completely dominates the market, I think this is a healthful dose of both diversity and reality that now actually we're seeing heterogeneous architectural combinations at multiple levels of the stack.

58:30The future light cone of compute architectures is not going to be dominated by any single company. Alex, for those who don't know the difference between TPUs and GPUs, would you give us a 101 here? gpus this is branding that was popularized by nvidia so graphics processing unit this was originally conceived and went to market for accelerating video games where nvidia was the arguably the chief actor for accelerating compute specifically for video game purposes and professional graphics as well then eventually it found its way to bitcoin and other crypto minings. And then fortunately, the need and the thirst for accelerated compute for AI arrived just in time to sort of recover from a bit of a mini crypto winter and step in.

59:19Meanwhile, TPUs, tensor processing units, this is a term from Google, but the underlying architecture is pretty similar to the way GPUs from NVIDIA and other firms handle AI operations. The T, the tensor refers, is a reference to this idea that the central operations that they need to perform in support of AI and machine learning is taking large matrices, which if generalized become tensors, sort of high dimensional matrices of numbers and multiplying and adding them. So that's sort of the, to oversimplify, that is the core operation of accelerated compute for machine learning, just taking matrices of numbers and multiplying them.

1:00:05That's a great problem. Appreciate that. We talked about this on the podcast we recorded at Visioneering a few days ago. Hopefully you enjoyed that episode. But I wanted to bring Alex and Dave into the conversation here. This is StarCloud bringing data centers to space. I'm going to play a short video from Philip Johnston. Actually, Philip, who's the co-founder and CEO of StarCloud, was here with me for the last few days. So it was fun to see his points of view. Let's play the video and we'll talk about it afterwards. The reason we're building data centers in space is mainly for the energy that we can draw from solar energy in space.

1:00:46So there's almost unlimited access to abundant solar energy in space. The problem on Earth is we're very quickly running out of space and actually energy on Earth to build large data centers. In space, we can have these enormous solar panels which can power these data centers. And then another advantage is we can then run large radiators to dissipate that heat in infrared out into the vacuum of space. So it's interesting. Philip Johnson was on stage pitching a prize called the Space Cool X Prize. It was something like that. And basically, one of the challenges they still have is radiative cooling.

1:01:28Space is very cold, but there's very little atoms to carry the heat away. So you're focused on infrared radiative cooling, which is a challenge. So I'm so curious, Alex, what do you make of this? Is this the future or is this something that isn't going to happen? Well, I think at the heart of this is what I would argue is one of the most important civilizational questions that we face. We don't know the answer, but the question is, does a mature, intelligent civilization build a Dyson swarm or not? Dyson Swarm, meaning taking apart the planets in our solar system to build lots of computers that orbit the sun.

1:02:11I don't know the answer. I suspect the answer will depend on physics discoveries that haven't happened yet. And just jumping out a few decades, playing this tape forward, as it were, playing the recording forward. I think if humanity ends up being permanently latency constrained, trained, we're probably going to do it. This probably then is the beginning of the construction of a Dyson swarm. On the other hand, if physics make it ergonomic to easily travel to other star systems, presumably with physics that we're not aware of yet, then I could imagine scenarios where actually building a Dyson swarm, turning StarCloud and other orbital computing platforms into a full-on Dyson Swarm probably doesn't make that much sense.

1:03:00One could also imagine other contingencies, maybe the demand as unconscionable as it is right now, that demand for accelerated compute might peak at some point in the future if that ever happens. I could also imagine we don't build the Dyson Swarm. Otherwise, I think just straight shot, this is the beginning of a long-term trend. Mark this point in time. We're at the beginning, unless something changes, of the construction of a Dyson swarm. Yeah, just to clue folks in, Dyson swarm, the terminology comes from Dr. Freeman Dyson, who was at the Institute for Advanced Studies at Princeton, who basically said, as you become an advanced civilization, you're going to want to capture all of the energy coming out of your star.

1:03:44So you'll dismantle your solar system, and you'll basically build a shell around the star that captures all of it. this is the earliest days. So, you know, I just want to point out, and I had this conversation with Philip, you know, we have 8 ,000 times more energy that hits the surface of the earth today than we consume as a species. And the challenge is, can we build the square meterage of solar and dissipation arrays in space? You know, there's going to be a lot of robotics required to do that. And when do we get there? Is it 10 years from now, 20 years from now? We're going to find out. Along these lines, we saw Caruso basically announce that they plan to support this by 2027.

1:04:38And I'm not exactly sure what they mean by supporting it. They're going to put an H-100 up in space. and H-100 in space represents a hundred times more compute than any other satellite has had, but it's a single H-100. It's not a cloud, not a Crusoe cloud. Alex, did you dig into this further? Yeah, I would maybe also just comment on timescales. So putting a single H-100 in low Earth orbit or LEO may not sound like that much now, but if you just, starting from physics, Like if we have this notion that we know, or at least have a prediction that the end state of all of this is taking apart our solar system, you could actually just do a few calculations to figure out the timescale for when that would happen.

1:05:26So one of my favorite statistics, if you ask, like, if we could completely encircle the sun with solar collectors, capture all of its luminosity and channel all of that power to, say, unbinding Jupiter, basically disassembling Jupiter. Jupiter has created its own gravity well, so the term of art would be unbinding it from its own gravity. It would only take approximately two centuries if we captured all the light from the sun to disassemble or unbind Jupiter. So I view one H100 going into space in the next couple of years. This is the first step in potentially a two century journey to deploy compute at scale in our solar system.

1:06:13And I think that's an important step. Exponential growth, double something 30 times, you get a billion fold increase. Dave, what are your thoughts on this? Well, Peter, you said, you know, the sunlight hitting the earth every day is 8 ,000 times more energy than we consume. But have you ever done the math on the fraction of all the sun's energy that hits the earth in the first place? Oh, yeah. It's, you know, far, far less. It's a fraction of 1%. Yeah, I know. I don't know how many decimal points are in there, but it's like, there's a monster amount of energy in that Dyson sphere, Dyson swarm view.

1:06:46So yeah, it's, you know, 200 years. Sure. Why not? Um, what's interesting in the short term, this could be a great idea or a terrible idea for Caruso. And it depends entirely on the timeline diffusion, which we're about to talk about. Uh, so that's an interesting factor in all this. It's worth pointing out while the term star cloud sounds like it's got Musk behind it. Uh, Elon is not involved in this. Uh, he did retweet, uh, the star cloud announcement, but, But, you know, I love Elon. He's incredibly brilliant. But at the end of the day, if he were to take this on, he would probably do it on his own.

1:07:26That's my experience. All right. Moving forward. Okay. Now on to Elon here. So Elon says the A15 chip, by some metrics, will be 40 times better than A14. We deleted the legacy GPU. It's basically a GPU. I've poured so much life energy into this personally. It'll be a real winner. So, you know, we've seen this before where Elon goes heads down and focuses on a very specific element, you know, all the way down to the engineers, scientists, the production line. Alex, you've been tracking this. What does the A15 mean for, you know, for Tesla, for optimists, for XAI? So I've spoken on the pod in the past about this notion that superintelligence is not going to stay just bottled up in the data centers.

1:08:19I've argued in the past, it is literally going to walk out the doors of the data centers in humanoid, robotic form, in driverless car form. I think what's most intriguing about the AI5 architecture is it's a unified architecture. This is a single accelerator that is planned for use both in the data center side and in the robotic slash car side. Single check, which is that this is something new that the world hasn't seen before. A single unified architecture for both cloud data center compute and also embodied in robots and cars. And so I think that this is quite literally potentially the embodiment of intelligence walking out the door of the data center into our homes and into our lives.

1:09:06Well, and this ties back to that last story, too. You know, all the big guys now have their own chips. Sam announced in our last podcast that he has his own Broadcom custom design. So Anthropic is the one exception. And so they're going to adopt the Google TPUs that was in that other slide. But that's not a very comfortable place to be. if all the other competitors have their own chip designs and as they're modifying their algorithms, the AI is tweaking the chip design. So once you're in bed with Samsung or TSMC or Intel and you have your whole supply chain going right into your own data centers, you can innovate, redesign the chip and get it back into production very, very quickly.

1:09:45Google's already got that cycle time way down. So it leaves Anthropic in this uncomfortable position where, well, we're buddying up with Google, yeah but you're on their tpus and they're going to give you whatever they want to give you fascinating but all of this comes back to tsmc production capability right in sam in samsung there are basically choke points uh yeah there's no doubt that any one of these companies would be buying tsmc intel or samsung tomorrow if the regulators would let it happen because because that's the choke point and they all know it. So all these really, you know, high level partnerships and relationships are really, really forming.

1:10:27And it's a very competitive playing field. But yeah, we're doing this, you know, week by week, we're seeing the shifting relationships and in capital flow here. All right, this next article comes from Amazon and their new delivery glasses. Let's take a look at the video here and then talk about the implications for this. It's fascinating what this means for labor. Well, check out these nerdy smart glasses. These are smart glasses developed by Amazon for their delivery drivers. So they're just in development now, but basically they use technology to get like a head up display, show you what you need to do.

1:11:05So in this case, instead of using your mobile phone as a driver to scan the parcels, you simply look at them and work out which parcel needs to go where. But then when you head out to deliver, it gives you actual information about the place you're delivering and give you warning about dogs and things and shows you exactly where to leave it and it's all done even the photos are taken and you never need to use the mobile phone so cool technology very much like metas ray-bans or maybe apple vision from amazon okay so this is what i think is going on it's this is put forward as we're going to help our drivers you know we keep them away from you know barking dogs and help them do this with hands-free delivery.

1:11:44I think this is a mechanism by which Amazon uses the drivers to collect a lot of information to train their delivery robots. This is just like Tesla with its cameras training its full self-driving models. Dave, what do you think? Yeah, you're exactly right. And it shows you how the technologies interact too, because the glasses will be profitable instantaneously within their internal use case. They can perfect them and then they can decide later. You remember there was a Kindle phone, Kindle Fire phone. It didn't succeed, but they've tried before to compete with Apple or Android in the device warfare game.

1:12:27So this is a great stepping stone for them to make money and perfect the device while gathering all the data, which will then feed their robotics initiative, but also the consumer glasses initiative, which will come later. So you're exactly right. Yeah. Do you want to add anything, Alex? I'll just add, I think this functionality can generalize well to non-delivery functions as well. I think this is the tip of the iceberg for using wearables to automate. And even before we get to automation, to capture telemetry and training data for the entire services economy. So I think that we're going to see this across many, many other verticals, healthcare, energy, hospitality, expect smart glasses and wearables for building training data sets and post-training data sets across every possible...

1:13:15Also construction. And memory augmentation. You know, we're doing the biggest construction build-out in the history of America and certainly probably the world. And it's all, you know, electricity and plumbing and buildings and everything. But because those are AI-forward projects like, you know, Chase Lockmiller at Caruso and Project Stargate, they're going to be early adopters of exactly the same thing you're talking about for construction so that'll that'll be and construction is a huge fraction of the global economy uh so that'll be a really fun and for me this the most important thing for me uh for a aging population is going to be memory augmentation right using these glasses to remember you know who you're talking to the last conversation you had i mean personally i can't wait i meet so many people and i love being able to you know remember the details but sometimes it's just a challenge.

1:14:07All right, we're going to go into a subject we covered on the last pod with Imad in particular and Eric Gellier, but I cannot wait to hear the take that Alex, you have on this and Dave, you have. Again, this is Google's quantum breakthrough nears real world use. So this is the Willow quantum chip, a friend in Santa Barbara, Hartmut Nevin, who heads the Google quantum team. Congratulations. But at the end of the day, Alex, what does this mean? Well, first, maybe a little bit of the background. So I read the coordinator paper behind this announcement. Very interesting. This was the Google team. By the way, Alex, I have to say, I really appreciate the fact that you dig in on everyone on this podcast to go and read the actual science.

1:14:55Well, it's difficult to comment on it if I haven't read it, but thank you. I understand that. Well, everybody else on the planet is commenting on it without reading it. You're the only one doing it. I've seen these comments on YouTube that Alex is an AI. I've seen him glitch. We want to use this as our cold open? I'm not going to disclose any details, but maybe we'll see you live. Anyway, dive in, please. You read the paper. What does it say? Right. So I read the core nature paper behind this announcement. It's very interesting. The premise is that there's a certain physical quantity. And in the case of this announcement, it's called a second order out of time order correlation.

1:15:47It is basically a measure of quantum chaos. It measures how chaotic a given quantum system is. And the Google and collaborator team showed that it would be very challenging for a classical computer, which is to say a non-quantum computer, to be able to compute it. So I think it's very interesting. It's nice progress in terms of demonstrating quantum speed-ups or quantum advantages versus classical computers. What I'm still waiting for, though, if I got my wish, is a more, call it economically transformative quantum algorithm. What I'm waiting for, what I'm hoping for, is that sometime in the next few years, we will achieve a definitive breakthrough speed up for quantum acceleration of AI.

1:16:31I think applications like this, where there are applications in quantum simulation, quantum chemistry, simulating materials, optimizing molecules, I think it's great. I don't think it is necessarily world-changing. And the world-changing use case for quantum acceleration, if the physics of our universe are so kind as to allow them, would be, I think, something like being able to achieve orders of magnitude speed up in training or inference for a frontier model. I think that would be utterly game-changing. Amazing. The term quantum advantage was coined a few years ago as the point in which a quantum computer demonstrates the ability to do a real-world thing better than any classical computer, right, with ones and zeros.

1:17:16And so people have been chasing this idea of a quantum advantage really to rationalize the massive investments and to actually get traction. Now we have a number of public quantum companies and wanting to get revenues. I think one of the other important things to note here is the concept of error rates in quantum computers and how do we get to logical qubits and how to reduce the error rate so we actually have something that's going to be useful. But let me ask you a different question here, Alex. How big is quantum computation as compared to AI? How big a relative? Is it larger, many times larger?

1:18:04What are your thoughts? I want to answer, I want to bisect the question into now slash short term versus long term. At the moment and in the short term, the actual applications are relatively pedestrian, prosaic, not economically transformative. The best applications, I think, that I've seen anywhere close to being useful in the short term are for quantum simulation, leveraging the fact that it's relatively straightforward. As Richard Feynman, who arguably helped to create the entire field of quantum computing, pointed out, you can use one quantum system to simulate another quantum system relatively easily.

1:18:43But these aren't economically transformative, not in the same way as AI that is just turning our service economy, as we were discussing earlier, and just automating it. Quantum doesn't have that capability in the short term. In the long term, I would hope quantum will enable us to build much faster AI systems. So in the long term, holding out hope that quantum in the end, there's almost an angle, you'll forgive me for this, there's almost a redemption arc that I'm hoping for of quantum information systems because so many of the problems right now that AI is solving, grand challenges like protein folding.

1:19:20Do you remember 10, 20 years ago, there was a sizable community that thought protein folding would require quantum computers to solve? That did not happen. We were able to solve it with just AI on top of classical computing. So there's almost a who moved my cheese angle to the sense like the grand challenge is that quantum was supposed to be the great white knight and solve for us. Keep getting devoured by AI instead. I'd love to see a bit of turnaround sometime in the next 10 years. Fascinating. My favorite science fiction books all have digital super intelligent AIs, conscious AIs, doing so on the backs of quantum clusters.

1:20:02There would be certain advantages. Go ahead. So potential advantages like energy efficiency, if we could build a fully reversible AI supercomputer, that would probably have some sort of quantum coherent foundation. That would be transformative. We wouldn't need to build all these SMRs and fission plants and nat gas co-location facilities if we had fully reversible quantum computer-based foundation models everywhere. But we're not there yet. Nice. All right, Dave, let's go to the next article here, and I'd love your thoughts on it, which is that President Trump eyes equity into U.S. quantum firms.

1:20:45So, you know, this is the potential beginning of a sovereign style VC fund for the United States. He's targeted INQ, Rigetti, D-Wave, Quantum Computing Inc., and Atom Computing. I mentioned on the last pod when we talked about this that I had taken D-Wave public through a SPAC. Huge, you know, 8 ,000x return from the earliest, lowest point to where it is today. Dave, thoughts on this? Yeah, well, I love it and I hate it as a precedent, but I still love it because Alex was always pointing out that what we're doing right now is unprecedented, except maybe during the buildup to World War II. and you think about 1939 we're basically flying biplanes in the u.s air force by the end of five years later we have we have jets uh just incredible amount of government investment yeah so that's what's going on right now in ai and it's great it's what we need so now that's moving into quantum too and you've made the point many times peter that our our funk our economy doesn't function well in these areas that require you to think more than five or ten years in the future china works really well, I think in 10, 20, 30 years in the future, but we don't do that well.

1:21:58So the government kickstarting quantum is a great move if you believe in it 5, 10, 15 years in the future. But as a precedent for government involvement in the economy, it's terrible. You know, it's because they're going to make terrible decisions in the long run. These are very good decisions in the short run, but that's because all this incredible talent has gone to Washington for the first time in my lifetime. But you know that's not sustainable. And so I hate it as a president. We see the government investment triggering huge amounts of private investment that follow on, so after the Intel deal, Intel stock doubled between$20 a share before and$40 a share a day or two ago.

1:22:42And we're seeing this again, a 10 % to 15 % increase in these quantum stocks after this this story got leaked. I wonder where they're going to go next. I think the government's going into rare earth metals. We've seen some of that conversation. Where else might they be making sort of strategic investments? Well, I hope they take Alex's World War II analogy and stay focused on the things we need in this very specific race to AGI and ASI. So rare earths would fit for sure, and energy would fit for sure. Quantum may or may not. I'm kind of shocked that the government hasn't made a move to get into the fusion companies or the SMR companies really to help accelerate that.

1:23:25Because I think that one thing would bring a lot more capital. I mean, Commonwealth Fusion is probably the best funded. You know, I was talking to some of the fusion companies here at Visioneering and talking about Helion. Interestingly, they said, you know, Helion is so closed lip, we have actually no idea what they're doing and how far they're along. You know, there's public disclosure to some information. They're claiming 2028, Microsoft, but we don't actually know. And these were from some of the top Fusion experts. Commonwealth Fusion, you know, targeting 2030, but they still have a lot more development.

1:24:05Alex, do you have any thoughts on that? Yeah, I'm not going to second guess the Commerce Department or the executive, but there is some reporting that there may have been some money left over from the CHIPS Act. And quantum firms might be interested, certainly would be interested in either obtaining equity investments or my guess is more likely loans or warrants or some other financial structure. But I think the question of how strategically important quantum is as a technology when you compare it with more obvious feedstocks like rare earths or energy or compute or fabs, I think that's to be decided.

1:24:45I don't know. Well, I will say I can't add anything to Alex's insights on this at all. But I will say I talked to Frank Wilczek about it. He's a Nobel Prize winner in physics and famous and spent his whole career in quantum physics. And he said almost exactly the same thing Alex said. So there's two data points. All right, let's jump into energy. A few different articles here. This one's interesting. In particular, there's a chart showing us the increasing price for U.S. construction of nuclear reactors versus China. And here's the quote. construction costs for nuclear reactors in the United States have risen roughly a thousand percent since 1970s, while China's costs have steadily declined.

1:25:33That's not good news. Alex, do you want to weigh in on this? I think there is an alternative history where the U.S. never basically stopped building nuclear plants in the late 1970s. And if you're familiar with all of the microeconomics around experience curves, unit costs tend to collapse the more you make of a given item. And as a country, the US basically stopped making nuclear power plants decades ago. And I think if we're going to feed the voracious energy appetite of these AI data centers, we need as a country to relearn how to build lots of next generation nuclear plants. And And the good news is the demand signal is being sent by the AI data center companies.

1:26:21But I think there will be all of these knock-on benefits, not just for AI data centers, but for everyday life if we live, again, in a truly power-rich society. Well, Alex, it's worse than that sounds, too, because it's not just about unit costs. If you look at the actual construction of a nuclear facility in the U.S., it's mostly overhead, regulatory, political garbage, bullshit costs. It's regulation, it's litigation, it's loss of manufacturing expertise, all of these things. And we've done it to ourselves. All right. Next article here is fascinating. U.S. is offering nuclear energy companies access to weapons-grade plutonium.

1:27:00So this comes out of Energy Secretary Chris Wright. The U.S. Department of Energy will let private firms use 19 tons of plutonium from old warheads to fuel their next generation reactors. the move is boosting domestic nuclear supply, reducing reliance on Russian uranium. I find this is a fascinating move. I mean, talk about, you know, sort of removing the shackles and giving entrepreneurs access to feedstock. Who wants to take it? Well, everybody probably knows this, but the cost of the fuel in a nuclear reactor is tiny. It's a rounding error. Everyone's been buying their fuel from Russia for a long time.

1:27:44Opening up the U.S. supply doesn't really change anything. It's a rounding error in the overall costs anyway. But if you're going to buy it from Russia anyway, what's the harm in using our surplus plutonium? It's not changing the math one iota. I'd also comment maybe even more broadly on nuclear engineering as a vibrant discipline. There was maybe a bit of a hot take, but there was a period of time for a few decades when nuclear engineering, unless it was for, say, some biomedical application, was positively unfashionable to study. And I think that I don't want to call it a nuclear winter for obvious reasons, but there was a I think that period of time we're coming out of that now.

1:28:34And as a society, speaking particularly of the U.S., but the West in general, is entering an era when we need to refamiliarize ourselves with the nuclear fuel cycle and get comfortable with nuclear fuel cycles in general. It's part of the future. Particularly part of the future is fusion. And so the U.S. has put forward a new roadmap for fusion energy. The DOE roadmap touts commercial fusion by the mid-2030s. actual aim for public infrastructure in the 2030s to scale up. Interestingly, this has$0 of federal funding behind it and$9 billion of private investment. Alex, you found this particular timeline.

1:29:21Talk to us about it. What does it mean? Yeah, no, I enjoyed reading the roadmap. I thought it was delightful in some respects. So the roadmap calls for three stages of advancement in fusion energy in the U.S. The first stage, call it the short term over the next two to three years, calls for early stage price demonstrations. So that takes us through 2027, 2028. The second stage, medium term, calls for early stage fusion pilot plants between 2028 and 2030. And the third, quote unquote, long term, calls for actual operation at production of generation power plants between 2030 and 2035. So this is actually a very, I think some would say it's a very ambitious timeline, at least by historic standards, where fusion was always 30 to 50 years out.

1:30:14Now it's basically in our short term. And it also, I think, aligns with some of the public announcements that Helion, on the one hand, and Commonwealth Fusion, on the other hand, have made regarding actual test facilities being in operation between 2028 and 2030. So I think in short, this roadmap is more a reflection, or at least I interpret it as more a reflection of some of the most ambitious private sector players and their actual plans. Yeah, Dave, we're going to be having a dinner with Bob Mumgard on Wednesday night in Riyadh. We have our abundance dinner that we're co-hosting with Amjad from Replit and Link Ventures.

1:30:57A lot of incredible people are going to be there. So I look forward to asking him more about this. Yeah, me too. I mean, the head of Commonwealth Fusion, he's done extraordinary work. I'm excited to see where they're going to go. All right, continuing on the energy theme. Amazon bets big on next-gen nuclear. So this is the state of SMR, small modular reactors. This one is with X-Energy. We've talked about X-Energy before. It's initial 320 megawatt output that can scale to nearly a gigawatt, which can power data centers, obviously carbon-free. I love SMRs, and I love the Gen 4 nuclear reactors.

1:31:43you know we unfortunately shut and we talked about this we've shut down our ability to manufacture these and so this has become an entrepreneurial effort but one of the things that i find fascinating is while we have the designs we have permissions the timelines for getting these smrs out um they're not like 26 27 28 they're 2030s um which is concerning Why can't we get these going faster? No, the timelines are really interesting to track, and it'll come up at FII next week in a big way. But a gigawatt, Eric Schmidt said we need 100 gigawatts by 2030, and that's just a fact. You can't go up or down because that's the number of GPUs we'll be making.

1:32:29They're going to go into production one way or another. And so you need to find 100 gigawatts by 2030. That's only about a 10 % expansion of the U.S. power supply. It's not insurmountable. But then 2031, 2032, the new fabs will be online and the GPU production will go way up in 2031, 2032. And so then you need some massive, you know, the 100 gigawatts is a stepping stone to something much bigger just a few years later. So if the fusion comes online in 2029, 2030, it's massively important. But if it's just five years late, we're like, where's that power going to come from? Then suddenly you're launching them into space.

1:33:08And so these completely different ideas in the modular reactors here, they're fission. So that's the third option, plus renewable is the fourth. So all those things are racing against this 2030 clock. I have to imagine by 2030, we're going to figure it out more energy efficient compute, 10x or 100x more efficient. And Alex, I'd love to hear your thoughts on that. The intelligence of the AI between here and there is going to be like... But also, I have to invoke Jevons' paradox. We're going to have, presumably, much more demand for it as well, even though cost per computer algorithmic advances are going to 5x to 10x every year, maybe optimistically the amount of energy reduction that we need in any given year.

1:33:56So I don't know when or if there will be a turning point where we need less energy. I will point out, though, with the SMRs, I think it's striking. No cooling towers. This is a totally new form factor. Decades of acculturation, people being trained to look for those iconic cylindrical cooling towers. No cooling towers. These can be put in so many more locations. They are compact. They can be put into novel sites that otherwise might never have been on the table for some of the first generation nuclear parasites. So even if there is a sequencing issue and even if the first boatloads of SMRs start arriving circa 2030, I do think they're very likely to end up being an important part of the overall power mix for AI data centers and otherwise.

1:34:47Yeah, and keep in mind, the vast majority of the data centers don't need to be near population centers. And that's a big difference. Those iconic cooling towers that Alex was mentioning, people hate them when they're on the beach in front of your house. But these SMRs can be Wyoming and Texas and Nevada in the middle of very unpopulated areas. And that's a great place to put some of these really large-scale data centers. So this will happen. They look like normal buildings. That's what's most striking to me. You would never, at least with the eyes of 2025 today, look at the building that you're sharing and say, that's obviously a fission site.

1:35:25It looks like a normal building. Amazing. So, you know, we're going to see a continued mix. I sure hope that the government does start backing solar and backing SMRs and backing fusion more. We need to accelerate our energy production beyond just natural gas and coal and other areas. I'm going to end this with what I'm going to call a weird science article. So let's end on something that doesn't normally enter our conversation in the exponential world. Alex, you found this one. It's called Butt Breathing, a Real Medical Option. Do you want to? Sure, Peter. I'll take the hit for ending on a low note.

1:36:12So, but in all seriousness, this is a transformative breakthrough, or at least the beginnings of a transformative breakthrough for people suffering from severe respiratory failure who can't breathe through their lungs. And if folks have seen The Abyss, the science fiction movie where there's a famous scene where a character is consuming oxygenated or I should say an oxygen substitute liquid. So breathing liquid, basically, deep underwater. They'll have some familiarity with novel forms of respiration and blood oxygenation. This was also the subject of last year's egg Nobel prize for discovering that non-human animals could oxygenate their blood supply by consuming oxygen via the other end.

1:37:06As it were, only so many euphemisms I can use here. Well, the intestines are a very blood-rich, large surface area part of your body. And so if you're able to put sort of a hyperoxygenated fluid enema, let's call it that, then you can perhaps oxygenate your blood supply and get enough of your red blood cells oxygenated to get to your brain. I guess you're really taking this seriously.

1:37:37But to elevate just a little bit. We just lost our entire audience on this particular article. The only reason I like this story and I wanted it in the podcast is because every time Salim says something in the future, we have the option to say, oh, he's butt breathing. Oh, no. Maybe just to try to elevate a little bit, there's been interest over the decades in nanorobots that would help with oxygenating the blood, so-called rispirocytes. And to the extent that it's possible, and I should add also parenthetically, sci-fi scenarios like enabling humans to be able to hold their breath underwater for hours on end.

1:38:17So there's been persistent sci-fi pressure to discover new ways to oxygenate the blood in environments that are, call them, less than hospitable. You're really, really reinforcing the theory that you're an AI. So, you know, all of this materializes on the backside of nanotechnology. And one of these times, you know, I really want to dive into not wet nanotechnology where we're using DNA origami, but, you know, Drexlerian assemblers. That just opens up everything. And risperocytes are fantastic, you know, literally BCI enabled through nanobots in the brain. I can't wait. So, you know, I'm going to get Ray Kurzweil on our podcast so we can have the conversations with him.

1:39:10Ray's been a dear friend and a mentor for so many years. At the end of the day, you know, his prediction is nanobots by the early mid 2030s. So 2033, and that's going to unlock, you know, high bandwidth BCI, but unlocks basically longevity escape philosophy. Or I don't like using the term immortality because it sort of hits so many different negative buttons. but if you can repair on a cellular and subcellular level all parts of your body that is an incredible future well if you can get ray and alex on the same podcast that podcast could also be immortal that would be something i would kill to see well we'll we'll do that uh for sure and uh again to all of our friends listening i hope you've enjoyed this episode of wtf uh if you're not a subscriber please join us.

1:40:02We'll let you know. It's interesting. We're putting out news as it breaks. So while we try and do this once a week, sometimes it comes out twice a week and you'll get a notice of that. We hope that other than butt breathing, that this helps you understand how fast the world is changing and that we're living this extraordinary time where we can solve any grand challenge. Congratulations to the Visioneering XPRIZE teams for winning visioneering and to the entire XPRIZE organization for really accelerating these grand challenges. I'd love to know in the notes here, if you have an XPRIZE that you'd love to see in the future, let us know what it is.

1:40:42Dave, I'm heading to the airport in, I think, two hours to head to Saudi. Crazy, crazy. It's going to be fun. I'll see you and Imad and Salim there. Alex, we will miss you. You'll be there either digitally or in spirit. But we have quite the week lined up, meeting with the top CEOs from all the AI and tech companies. It's going to be fun. Any favorite meetings you're looking forward to, Dave? Well, you're kicking it off with the big shots. So you've got Eric Schmidt, Larry Fink, just like the big, big money people and the big vision people. So that's going to be such a fast start. But then backstage, it's like, God, it's just like a who's who of incredible people.

1:41:27So I'll be backstage the whole time. It's, yeah, it's going to be wild. So thanks. And interestingly enough, yeah, no, a pleasure. I chair FII is out of Saudi. It's the Future Investment Initiative. And I'm on the board there and I chair their AI activities. You know, one of the things that's going to be interesting this year is we have, I think, 20 something heads of state. And I'm going to be co-chairing a conclave with Imad and Anj Mita from A16Z. And we're going to be talking about how to use AI to accelerate governance for countries. You know, one of the biggest challenges we have, we'll talk about this when we come back, is that the speed of change is so extraordinary and so disruptive in terms of AI and humanoid robots and longevity that countries out there are having a difficult time trying to understand what policies they put in place.

1:42:22What do they do best for their nation state, for their citizenry? And so we're going to be announcing a program called Sovereign AI Governance Engine. We'll talk about what that means, but it's really to help people around the world deal with the disruptive change and disruptive opportunity at the speed of AI versus the speed of governments and PDFs. It's going to be good. The reason that's coming out in Saudi Arabia in Riyadh is because the deployment rate of ideas like that can be very, very, very fast in those countries because they make decisions kind of in a very tight-knit, little, very, very fast-moving group.

1:43:06And so that'll be a huge bellwether for Western democracies because it'll happen there long before it happens in the US and Europe. Alex, what's the week like for you, buddy? It's in some sense, the same as every week for me, which is trying to accelerate and smooth out the gentle singularity. Yes, I love that. By the way, our episode on the singularity is now has just done incredibly well. I've had people telling me, faculty at UCLA and others saying, I've assigned this to all of my students to listen to that podcast. Yeah, no, extraordinary. It's really done. It's gone viral. So if you haven't heard that episode, The Singularity Is Now, go listen to it.

1:43:51It's the Moonshot Mates at their best. Love you guys. See you on the other side of the pond, Dave, Alex. See you in a week when we're back. All right. That's great. All right. Take care all.

1:44:08Thank you.

1:44:38Thank you.

1:45:08Thank you.