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

Episode Date: October 27, 2025

Get access to metatrends 10+ years before anyone else - https://qr.diamandis.com/metatrends   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   Grab dinner with MOONSHOT listeners: https://moonshots.dnnr.io/ _ Connect with Peter: X Instagram Connect with Dave: X LinkedIn Connect with Alex Website LinkedIn X Email Listen to MOONSHOTS: Apple YouTube – *Recorded on October 25th, 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

Open AI has launched a full-blown browser. The competitive positioning versus Google is basically all-out war. Today we're going to launch ChatGPT Atlas. This is an AI-powered web browser built around ChatGPT. We think that AI represents like a rare once-a-decade opportunity to rethink what a browser can be about. Okay, great, but Google is going to come in and do at least this and, you know, take back any market share they lose. I don't think we should think of it as a product. I think we should think of it as a distribution channel.

for OpenAI's superintelligence. Having a local agent mode, I think, is potentially transformative. If Sam wins the data aggregation race, if he falls behind for a month or a year in the AI race, he still has your data. We're going to have an AI that is our personal portal into everything. And I'm not going to care what browser I use.

I'm just going to be able to have a conversation with my AI and it will pull up the data from wherever it is, whether it's using superintelligence from Open AI or Google. Now that's the Moonshot, ladies and gentlemen. Everybody, welcome to Moonshots. Another episode of WTF just happened in tech. I'm here with my Moonshot mate, Dave Blundin and AWG, Alex Weezner Gross. Good morning, gentlemen.

Hey, good morning. And a huge shout out to the team. You know, we were going to shoot this podcast last night. And Alex had so much material that happened in the last three days that we just needed to get in here. I mean, things are changing so quickly. So basically, the team pulled an all-nighter last night to pull together these stories, and it's epic. So thank you, team, behind the scenes.

Yeah, right now, our fourth moonshot mate, Salim is on an airplane. I just spent the last four days with him here in Kalamigos in Malibu for XPRIZE in 2025, which is a story I want to open up with Dave. I wish you were here. Alex, I wish you were here. It was awesome. So for those you don't know, XPRIZE every year gets together our brain trust and our benefactors. And we debate and we discuss what are the problems that aren't being solved that need to be solved or what are the challenges that are too far out and we need to accelerate them and bring them forward.

And that's visionary. It was an amazing two and a half, well, really four days in total, but two and a half days in which we raised, Dave, you're on my board. here at X-Prize. We raised three and a half million dollars of capital last night. So I do that every night? That's a billion dollars a year. Yeah. That would be awesome. And someday we will. Just so the audience knows the sacrifices Peter makes to bring you all of this information. So he's on stage all day yesterday. Tomorrow boards a flight to Riyadh, so we'll be in Saudi. He'd be on stage the day after that with Eric Schmidt kicking off that event. That's 10, time zones away. So watch the footage of him from Riyadh and see what that looks like.

How wired will I be on caffeine? Oh my God. It's great. But, you know, we announced yesterday our impact report for X Prize and the numbers are staggering. We have massive detailed report. And it's we, every dollar invested in a prize, we get a 60x return. So, you know, million dollar prize is driving $60 million of R&D invested by all the teams. They're all optimists. They all think they can win. And they're all sort of a Darwinian evolution to go and solve these problems. So super pumped about that. But I want to report, you know, this is the first group to hear about it on who won X Prize Visioneering. So we enter the two and a half day program with about 20 concepts. We have five different domains, five different

Grand Challenge areas, and we've got four concepts per. We narrowed down to two and then down to one, which leaves us with five that enter the Battle Royale, as we call it. And we go from five to three, and then last night we got down, well, let me just show you the numbers here. So XPRIZE visioneering winners for 2025, we were expecting to just have one of these prizes get funded to go into development. It turned out all three of these got funded to go into development. Let me mention what they are, because I'm very proud of them. The first prize is called abundance, which got to love the name. And it was actually two of our Abundance 360 members who proposed this and raised the capital to get this going. So what is the abundance X-Prize?

it is deliver to a community, food, water, housing, electricity, and bandwidth for $250 a month. That's the goal. So everything that you basically need. And, you know, the conversation last night, we could talk about this, is there's potential for a lot of civil unrest, right? As people start losing jobs, as, you know, subgroups start becoming wealthier. and we've talked about this. I'm absolutely clear in the next decade we're going to have, you know, extraordinary abundance, uplifting everybody. But it's this turbulent period of the next

two, three, four, five years that's concerning. And the idea here is if all of a sudden moms and dads have all of their bases covered, you know, the basics of life for 250 bucks a month, then they can start to think about, okay, how do I? I use AI? How do I use this technology to be an entrepreneur, to create a better life? Any thoughts on that, Dave? Well, especially that last fundamental of food, water, shelter, bandwidth. You know, if you're going to contribute in this global revolution, I love the fact that they added that as a fundamental necessity, you know, inside the 250-buck limit. That's just such a great, great idea. But that unlocks your ability to contribute, to make a living, to get

educated, you know, all educational move to AI so you can have a, you know, the health care is going to move to health care, all of that. That ties to bandwidth. So it really is a fundamental necessity. I love it. Yeah, Alex, any thoughts? Yeah, it sounds a lot like a universal basic services concept. UBS is sort of the symmetric dual to UBI universal basic income. I'm very bullish on universal basic services in general. I think I would expect it's an artifact of a mature economy that the cost of living can be driven down to near zero as part of a sort of lifestyle subscription and Amazon Super Prime, if you will. Yeah, no, I'm super excited about this. There's a lot of studies that say that universal basic income backfires in terms of it causes depression, causes alcoholism, causes drug use. But services, you know, where you actually get the things you need to survive, still encourages you to work and contribute on top of those services.

It's a much better idea. But we learned in our pregame here that Alex doesn't even use caffeine, so I don't know how that's possible. Caffeine is a universal basic service for sure. So this won the most capital last night, and it's going into prize development. I'll report on it. We'll have this team at the Abundance Summit, both of them are abundance members, and we'll talk about it. The second prize, surprisingly, that got top honors and receiving. enough capital to go into development is a Fusion XPRIZ. And so here I am thinking, okay,

there are 37 venture-back fusion companies. There's about $10 billion invest into fusion. What do they need a fusion prize for? And amazingly, and I met with, there were four fusion companies, you know, four, you know, solidly funded ongoing fusion companies, as well as from the top faculty when professor at MIT and saying, no, no, we need an XPRIZ to move this forward. We need the public to understand how this important is and how the government needs to come in and support it. So this one is not fully defined as a prize, but $500,000 was committed to develop the prize and move it forward into potentially a prize. You know, Alex, I think you have some feelings about this one. Yeah, I think fusion is already well capitalized, but I would say ultimately to the extent

that the limits of economic growth are bound by our ability to solve fusion. I think on the margin, it would be more helpful to allocate more capital toward fusion energy sources, and perhaps this helps with that. Alex, you know what happens after this visionary phase is the world's greatest experts on the topic all get together, you know, in the Peterverse, and then they contribute all their ideas. And not all of them get from there to actually being a prize, but you learn so much about the state of what's happening along the way. So I love it when a topic like Fusion gets through this part of the funnel, regardless of how it ends up, because the amount of

information will bring back into the podcast on this. It'll be just immense. You know, it's interesting. The CEO of Commonwealth Fusion, Bob Montgomery Gardner, is going to be with us in Riyadh, and he's going to be on stage with me at the Vundance 360 summit in March. And I was on the phone with him getting ready for what we're going to be doing in Riyadh next week, and he said, listen, I heard that you're talking about a Fusion X Prize. I am so excited about that. And so here we have the best funded, most advanced fusion company actually excited about a Fusion XPRIZ, so I'm excited to dig in further.

The third prize is actually something I love. It's called Wally. We'll have to be in debate and discussion with Disney about this. But here's the prize. Dump a machine into a garbage dump. And the machine sorts the trash and generates piles of metals and foods and paper. And basically, can we take our. current, you know, what do we call them, landfills and actually reutilize them. So I have the way

I would actually win it, but I don't know, I think this is a coincidence of technologies. It's going to be AI, it's could be robotics, could be material sciences. Any thoughts, Dave? Alex brought us, and Alex keeps bringing us deal after deal after deal, and every one of them so far has been a winner. That's really exciting. But Alex, you brought us that rare earth company. You want to talk about that? And I learned a lot about this to studying that company. Maybe just a broader comment on the space. I think there is such a long tale of physical world service jobs that are ripe for automation,

not just limited to repurposing junkyards, as it were. But I think if you look around the world today, I often sort of look out in the street and you can ponder where are all the robots, where we're supposed to be living in the future. why haven't we seen anything that looks facially transformative when you look out in the street? I think in the next five to ten years, we will look out onto the street and we will see an abundance of robots and physical automation that enables communities to be visually transformed aesthetics that would otherwise be out of reach for an economy our size. As the economy starts to grow radically, we'll start to deploy robots everywhere for even

the most minor tasks that would be otherwise economically inaccessible today. So I think this is actually just maybe a special case of a much broader opportunity over the next five to 10 years of just deploying automation everywhere. Every week, my team and I study the top 10 technology metatrends that will transform industries over the decade ahead. I cover trends ranging from humanoid robotics, AGI, and quantum computing to transport, energy, longevity, and more. There's no fluff.

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10 years before anyone else. All right, now back to this episode. I just want a robot, you know, just walking up and down the I10 freeway, the 4 or 5, picking up the trash on the side of the road, but the idea that we can actually take our landfills, which are, have so many different problems and everything from methane production to just, you know, disease. And we're sending so much of our trash overseas to Southeast Asia with heavy metals. I mean, the idea that we can actually use it as a feedstock is amazing. So I don't want to belabor the point. Congratulations to the teams that won X-Prize Visioneering. Congratulations to Newsom Sari and the entire leadership team of XPRIZE. It was an awesome two and a half days. And we recorded a podcast, which we dropped a couple

days ago. So, you know, we had Imad Mustak and Eric Poulier, Salim, and myself being a podcast. Hopefully everyone listening has heard that one. We're going to be expanding on some of the ideas because I want to make sure to bring in the, you know, the brilliance and vision of AWG and Dave. All right, let's move on the main course today, AI chips and data centers, as it is every day. All right, do you want to introduce this video, Dave, or at AWG? Yeah, so this is one of the reasons we needed to get together quickly. This just came out. So OpenAI has launched a full-blown browser.

The functionality won't blow you away yet, but the positioning, the competitive positioning versus Google is basically all-out war. So I went back and researched, you know, Google launched Chrome. Chrome was not in the world, you know, people don't remember this. And they leveraged their user base to install it, and now they have two-thirds market share of browsers. And so this is people's point of contact with information goes through Google. They get to see everything you do. Then later on they turned on Chrome sync, so they watch everywhere you navigate. All that information goes back into Google's great AI machine and serves

you ads. Brilliant. And kind of scary. So then Open AI, you know, Sam being the strategic genius that he is, says, okay, this is one of those fundamental Bill Gates-style points of control we absolutely have to play in the browser game. So we're going to love. launch the Atlas browser and what's going to make it better than Chrome is it's going to learn what you like and don't like far, far better and use our AI advantage to serve up better ideas. And the integration of GPT and what you're browsing will be completely seamless. It'll be advising you. It'll be taking you to the next website. It'll be curating your news all through that integrated Atlas AI browser. It'll be taking your data. Yeah, yeah, that too. I mean, that's the key,

right you know let's watch a short video of sam and his team announcing atlas and we'll talk about it we're going to launch chat gpte atlas our new web browser we think that a i represents like a rare once a decade opportunity to rethink what a browser can be about and how to use one and how to sort of most productively and pleasantly use the web and then there's three special core features of atlas that ryan's going to walk you through in a bit the first is chat comes with you anywhere as you go on the web the second big feature is browser memory The third, which we're really excited about, and Justin's going to show this later, is agent, which is in Atlas, Chatchibati now can take actions for you. It can do things.

All right. So my first reaction is, okay, great, but Google's going to come in and do at least this and, you know, take back any market share they lose. I don't know. Do you agree with that? Alex, what are your thoughts? I think there's a misconception that Atlas is a product. I don't think we should think of it as a product. I think we should think of it as a distribution channel for OpenAI's superintelligence. I think all of these products, these discrete products, are just going to dissolve over the next few years into a uniform medium of distribution for superintelligence. So whether it's one browser on the desktop versus another browser competing, I almost think it's the wrong question. I think the right question is what form of back-end superintelligence is being surfaced via which channels?

browsers, one, intelligent code editor environments are another. I think robots and various wearable devices are going to be another over the next few years. And I think it's really the superintelligence at the end of the day. That's the differentiation, less the particular Chrome, if you will, that's just an embodiment of it to deliver it to the user. And I think along those lines, the most interesting for me part of the Atlas launch was the agent mode, less so the other features. Having a local agent mode, I think, is potentially transformative for a number of use cases and feels a little bit more sophisticated than prior agent launches that we've seen from OpenAI, if you remember, operator, or if you remember the cloud-based chat GPT agent,

this one is at least partially local. So you've got the big, big guys with infinite budgets. So you've got Google, you've got Zuck, and you've got Elon. But then you've got the two little startup, you know, super hyper-creative startup guys. So that's Dario and Sam. And so, you know, Sam, Open AI, is playing a very different game from Dario. Dario is relying on exactly what you just said. I'm going to build a more intelligent fundamental machine, and because it's more intelligent, people will navigate to it and will go out through corporate channels. Then Sam is playing the old Bill Gates game where, like, I'm not going to take for granted

that my AI is better than Google's. But right now I have twice as big an installed base as Google does. So what can I add to protect my position that makes me the default choice in the case where the two AIs are on rough parity? So it gets Johnny Ive to build a device. He's building his own data centers with Broadcom, and now he's adding a browser. And so he'll add everything that Bill Gates would have added that's a user point of control or an entry point into the use of AI in order to defend that turf and encourage more of the innovation to come through him rather than work around him through Google. But it's like all that warfare all of a sudden between Google and Open AI, and it's just really fun to watch. Dave and Alex, you know, my favorite model for this is still Jarvis from Iron Man, right?

We're going to have an AI that is our personal compatriot and in our portal into everything. And I'm not going to care what browser I use. I'm just going to be able to have a conversation with my AI and it will pull up the data from wherever it is, whether it's using superintelligence from, you know, open AI. or Google. Well, the only thing I'd add to that is that very, very soon that data will be your personal health data, your personal preferences, your everything about your soul. And then when you have your virtual girlfriend or boyfriend, everything you like and don't like and life will be in there.

So if Sam wins the data aggregation race, if he falls behind for a month or a year in the AI race, he still has your data. And that personalization might create a much more compelling experience, allow him to catch up again. So, you know, the personal data warfare is, like, kicking off in a huge way right now. You mentioned it a second ago, Peter. What's the downside of what we see here at Atlas? I mean, we have the ability of open AI to not only look at the data you have on your browser,

but probably every tab that you have open and everything you have going on in your computer. And they're not promising to keep it confidential. Thoughts on that, Alex? I think we'll see forcing functions for greater forms of confidentiality and privacy. I'm just reminded, do you remember the browser wars? Yeah, of course. Right. And Google One was 70% market share today.

Yeah. Right. So there's sort of a long history of sleepy periods of relatively low innovation separated by Cambrian explosions of functionality. I remember all of the browser wars. And I think a browser war today over competing among other factors on whose browser is most private while also being AI agentic, I think that's a valid front for competition, and I welcome the competition. Amazing. Alex, would you introduce this next slide here? You built a chess game, but before I play it, explain what you built here. Yeah. With computer use assistance, CUAs, of which arguably this new chat GPT Atlas agent mode is one example, I have my own e-vails. One of my favorite evils for testing these CUAs is to see whether they can win at simple and or complicated single player web games. So a favorite easy example is to see whether I turn Atlas losing.

on a single-player, not double-player, a single-player game of web chess and see whether it can win. I've used this e-val against historically operator from OpenAI. What we're seeing here is a time lapse of it just being asked. I turned it loose on a web chess single-player, asked it to win. And interestingly, this is the best performance I've seen to date from a web-based CUA turned loose on chess. Sometimes I'll turn it loose on a game of web civilization, if folks are familiar with the civilization franchise. But in this case, intriguingly, it asked for hints, which I've never seen before. So it used the helpline built into the web game to ask for hints and was winning at the end of the day.

I think this is a preview in short. Did it ask you for hints or did it ask some other LLO for hits? It asked the website for hints. Once it discovered, which it did pretty quickly that it could ask for hints, it asked. for Hintz and use that to win the game. And I think this is a preview of CUAs for everything, not just winning easy games of chess. Amazing. Amazing.

I'm going to jump into Anthropic. And this is a conversation between Jonah Kuhl, who's the head of Life Science Partnership and Development, and Eric Catterer Abrams, who's the head of biology and life sciences research. You know, in January at the World Economic Forum, We heard Dario Amadeh, the CEO of Anthropic, talk about one of his passions, which is the ability of AI to accelerate biology and longevity.

And very famously, he said, you know, if we're able to hit the targets we have for AI, we could see the doubling of the human lifespan in the next to five to ten years, which perked everybody's ears up, including mine. You know, are we going to see longevity escape velocity within this decade? increasingly, the answer is yes. Let's take a listen to Jonah and Eric have this conversation. I'll start with why are we focused on the life sciences. When we talk about the beneficial use cases of AI

and all the amazing things that we can do in the world with the frontier AI that we're developing, actually the number one place that we anthropic are excited about applying it is within biology and the life sciences. If you read our foundational material, that's the primary area where we're really focused. on delivering the beneficial impact. We did Claude to be conversant with all of the tools

that scientists are using every day, right? And so there's a whole ecosystem of important tools and partners out there that we are integrating with, right? So we talk about benchling on the, you know, experiment administration, lab notebook side of things, TEDx Genomics with Cell Rager, right? Incredibly important platform for analyzing single cell experiments

and then PubMed, for example, for being able to query the literature, right? And so these are just three of three incredibly important partners in a much larger ecosystem. And so that base level is we need to make sure that Claude can talk to all the major sources that scientists are using throughout their daily. We want to bring Claude to performing at the level of a superhuman research assistant that can assist you as a scientist throughout all stages of your project. Alex. I speak from time to time on this pod about super intelligence, solve. math, science, engineering, medicine. I think this is likely how biology gets solved. I think

I was talking a moment ago about computer use assistance, CUAs. I think we're entering the era of CUAs for biology, where we have baby superintelligences that are completely fluent and well-versed in the tools of computational biology and are able to read PubMed fluently and then go and perform experiments even. I think this is what solving biology with AI looks like. Yeah. You know, there's a company I just recently invested in that I'm very excited about. It's called Lila, L-I-L-A.

People can look it up. It's out of MIT and Harvard. George Church is the chief scientist. Jeffrey von Moulton is the CEO. And what they're doing in a similar fashion, but I think more advanced is they've set up these science data factories, right? So they have a superintelligence model their building, and these science data factories are basically 24-7 lights out robotic, you know, robotic farms looking for information

out of nature. So if you imagine the superintelligence will come up with a scientific theorem or, you know, a proposed research, they'll program the robots to go do the research at night, gathered the data, bring it back, check their theory, iterate, put the next experiment forward, and running on this 24-7 cycle to sort of mine data out of science itself and focusing on biology first and foremost, but chemistry and material sciences. And I love this as we're searching for new data out there in the world to help us understand what's going on in our 40 billion cells, you know, it's five to ten chemical, five to ten billion chemical reactions per second per cell. We need to, we need to be able to reach in and get the data out to build our

models even better. I think that it, as I think Peter, you might know, Jeff was a labmate of mine when we were undergrad at MIT. And I'm a huge evangelist for dark labs. I would like to see dark labs for everything. Yeah. Well, and Jeffrey, Von Maltz, and I know, it's a harder name to find on the internet than Jonas Cool or Jonah Cool, but definitely look him up. The guy is going to be huge. You know, you can see it coming on, and Alex will reaffirm this, but he will be one of the key figures cracking life sciences. And I'll tell you what else. We'll see later in the pod. There are some people saying, look, we've got to slow down AI, we've got to stop. It's not going to actually happen. We're going to move full throttle,

and there are two reasons. One is China. The other one is this. People are not going to sit and let people die unnecessarily from illnesses if AI can discover solutions to it. That's not going to happen. And so that's why the AI labs are talking about this use case so much because it's life. It's preserving lives. Yeah. And by the way, Jeff, Jeffrey by Maltin and Lila will be at the Abundance Summit. Super excited from to present. Our theme in March of 26th at the summit is superintelligence and the rise of human or robots. So he said, okay, 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 Grockapedia to come online. Alex, what are your thoughts here? Yeah, 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. I have a, okay, Dave, I'm going to go ahead and then I have a ramp on this. All right. Well, this is right in my wheelhouse. So I need to wax poetic for a minute on this topic. So, you know, 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 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, but you also have to pay the man. You've got to pay Google. You've 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 and 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's 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 we're factual it doesn't matter you're going away and so that's what's my 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 i 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 think maybe Grogoppedia will be a solution here,

or in fact, any AI that just says, you know, spin up a page on Dave Blundon, I can send somebody. That's going to be awesome. I'll give you one other, you know, pro tip. Get a similar web account. Similar web.com. Get a similar web account. And you can see exactly where. that user went. The 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 GPT5. Rediscover's long-forgotten math connections. This has Alex Weezer 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. And I think this story sort of beautifully encapsulates the fog of war we're in right now. the level, the water level of intelligence is rising day by day. And some of the earliest math problems, open math problems to be solved are, I think will be math problems that where the solutions were known to a subset of humanity, but not to all of humanity. And we're going to ring 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 other people didn't know that it had even been solved.

That's the fog of war phase that we're in. So 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 Erdush Problems, number 143, for example? But there was, I think, ultimately, a lot of really revealing discussion and commentary on this particular problem and also other Erdish problems that actually, this is just a phase right now but early days where we're still

cleaning up 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.

Yeah I think it's also... You mean solved, right? You mean solved by open. Open means unsolved, closed means solved. I think there's also a great little case study and how the action 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 wit how it solved it. It came back with the right answer. There's a lot like, you know, a think-struct in our lab. You know, it's a

company that does academic research and now patent research using AI. So Nikki Abate and Julius height cutter. 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 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. But one of my favorite applications of AIs and patents with 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, 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 Wiesner Gross says it's the best piece of writing in the history of humanity. If 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 give it away. Anyway, let's not go there. All right, our next article here is Uber tests micro work 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? This is really, really cool because, you know, Mercor is almost, you know, closing it 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. Well, you've 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? You know, because a lot of what's missing is physical motion, common sense, you know, just all this information. So, you know, why not use that same platform you've already got to be another another, another. Merckor-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.

I think this points toward a near future where training robots to perform service economy tasks, is the new de facto gig economy. Yeah, so it's 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, 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 collinick when uber was going public but he got on stage and he said uber is not a ride sharing hailing cab company we're a internet fabric it was some like really ethereal but now they're actually doing it it it makes sense in in hindsight so they don't view their platform as being about cars and rides they view it about like dave 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 long-standing relationship with DARA. We'll talk about what he's doing 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, you know, they're hooking up, I think, with Jobie on the, you know, flying cars, let's call it that for the moment. So Uber's been an incredible platform for experimentation and sort of integration of various exponential technologies. So that would be fun. All right. 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 DeepSeek. So a new model that DeepSeek announced, DeepSeek OCR. So maybe a bit of background first. Foundation models, frontier models like GPT, are thought to perceive text in the way that humans perceive text. Humans look at text on a page and we see text visually. The 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 deep seek OCR, which is, again, if you squint at the model architecture, it's sort of an auto encoder that does optical character recognition after a fashion. But in a really interesting way, it 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. 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. I 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 Open AI, 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 it can be understood, read, and responded to. I think that that's table stakes. So, 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. So it'll be a big advantage in multimodal. But what works already is just mind-blowing to me.

Do you expect, Alex, are we 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 spend 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, if we just had maybe like a single universal maybe video style modality

that everything else flowed through, it might have certain benefits. You 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.

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Ready to 5X your engineering velocity, visit blitzie.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 Open AI is hired over 100 bankers, paying them $150 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 ag going to do this for every field? You know, get rid of white collar work across the board. Well, the answer to that is absolutely, yes. They're 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.

And they're like, well, Sam's. not going to, 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 Ycombinator who haven't even gotten to market yet. So if you're somewhere between those two things, you're just need to position yourself like Brendan Foodie did at Merckor, get into the building and be the person that solves that problem for open AI. But yes, it's the answer.

He'll do this in absolutely every category of human endeavor. So I would imagine this kind of a vertical would be something that 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 Will that is open AI going to be moving into and eliminating all the entrepreneurial vertical channels. I find this fascinating. Yeah, I think they go ahead, Mel. I think 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 surface economy, each manifestation of it, gets digested and turned into AI automation. But 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 subverticles. 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. We'll have, I think, a completely heterogeneous economy indefinitely into the future. So bottom line here is that this effort by Open AI 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. Alex, 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 and Star Trek. Yes, I love that. Have to admire that we're catching up with the future. It's very exciting. A level deeper, though, I do think world models, so-called right now, are going to merge with the foundation models. 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. 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? At a level of reality resolution, that is shocking.

Just a hit on something 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 you 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, but 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.

It's entirely... Or GPUs. More GPUs, man. Keep tiling because people are going to love it. It's incredible. And unless you buy your own Invidia 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 in the planet, you know, from meta, Facebook, and pumped it all into this AI initiative. And now is borrowing, you know, going to the next level and the market, 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. It'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 infrastack 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 infrastructure. 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. Well, one of our best partners, Kush Bavaria, a phenomenal guy, just co-founded a company

called Orne-O-R-N-N. Yeah, check it out. But my point in And this is that people that are kind of technical and 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, you know, redirecting into this direction. And, you know, making it move intelligently, the right investments, the right locations.

That'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 Zeta flop here or Zeta flop 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 10 E26 models. So the E26, that's the regulatory definition of a AGI super intelligent, register it with the government type thing. So that's 1E26.

A Zeta flop is, what, 1E21. 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, you know, 10 to the 16th to 10 to 21, you need five more ooms. So that's 100,000. So every 100,000 seconds. And for those, ums are orders of magnitude just to translate. Five more ooms. Five more. So 100,000 X. So every 100,000 seconds, a one Zetaflop 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 Zetaflop. This is 16 Zeta Flops. So 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, think together with this 16 Zeta Flop supercluster, 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 superclusters with approximately a million GPUs and tens of Zetaflops, 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. And 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 a little brother there and they're going closer and closer. Alex, what do you make of this? Well, 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 infrastact. So we're seeing Nvidia GPUs, up against Google TPUs, up against Amazon traniums, up against ASICs, including Frontier Lab 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 no actually we're seeing heterogeneous architectural combinations at multiple

levels of the stack. The 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 from 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 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-mining's, 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.

Meanwhile, 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 to oversimplify, that is the core operation of accelerated compute for machine learning, just taking matrices of matrices of numbers. in multiplying them. That's a great promise. 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 Star Cloud, 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 so 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 and infrared out into the vacuum of space. So it's interesting. Philip Johnson was on stage pitching a prize called, you know, the space cool XPRIZE. It was something like that. And basically, one of the challenges they still have is radiative cooling. Space is very cold, but there's no, there's very little, you know, 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. I 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 I were, playing the recording forward. I think if humanity ends up being permanently latency constrained, 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, you know, turning StarCloud and other orbital computing platforms into a full-on Dyson swarm probably doesn't make that much sense. One 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's form. Yeah, just to clue folks in Dyson's form, the terminology comes from Dr. Freeman Dyson, who is at 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. So 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, you know, basically announce that they plan to support this by 2027. And 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 100 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 orbiter, 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, If all of this is taking apart our solar system, you could actually just do a few calculations to figure out the time scale for when that would happen. So 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 1H100 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. And I think it's important.

Exponential growth, double something 30 times. you get a billion-fold increase. Dave, what are your thoughts on this? Well, Peter, you said 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 a, you know, far less. It's a fraction of 1%. Yeah, no, 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. So, yeah, it's, you know, 200 years, sure, why not? What's interesting in the short term, this could be a great idea or a terrible idea for Crusoe, and it depends entirely on the timeline diffusion, which we're about to talk about.

So that's an interesting factor in all this. It's worth pointing out, while the term StarCloud sounds like it's got Musk behind it, Elon is not involved in this. He did retweet the StarCloud announcement. 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. That'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 poured so much light. energy into this personally, it'll be a real winner. So, you know, we've seen this before where Elon goes, heads down and focus 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 A-15 mean for, you know, for Tesla, for optimists, for X-A-I? So I've spoken in the pod, on the pod in the past about this notion that superintelligence is not going to stay just bottled up in the data centers. It is, I've argued in 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 chip, 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 this is quite literally potentially the embodiment of intelligence walking out the door of the data center into our homes and into our lives. lives. Well, and this time back to that last story, too, you know, all the big guys now have

their own chips, as Sam announced in our last podcast, that he has his own broadcom custom designs. 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, they're tweaking, the AI is tweaking the chip design. So once you're in bed with Samsung or TSM or Intel and you have your whole supply chain going right into your own data centers, you can innovate, innovate, redesign the chip and get it back into production very, very quickly.

You know, Google's already got that cycle time way down. So it leaves Anthropic in kind of this uncomfortable position where, well, we're budding up with Google. Yeah, but you're on their TPUs. They're going to give you whatever they want to give you. Fascinating. But all of this comes back to TCMC production capability, right? In Samsung, there are basically choke points. Yeah, there's no doubt that any one of these companies would be buying TSM Intel or Samsung tomorrow

if the regulators would let it happen 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. And 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. Basically, they use technology to get it like a head-up display, show you what you need to do. So 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. It'll 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, Raybans or maybe Apple Vision from Amazon.

Okay, so this is what I think is going on. This is put forward as we're going to help our drivers, you know, keep them away from, you know, barking dogs and help them, you know, do this with hands-free delivery. I 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, you know, 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 and Android in the device warfare, you know, game. So 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, health care, energy, hospitality, expect smart glasses and wearables for building training data sets and post-training data sets across every possible. Also construction. And don't forget construction. You know, we're doing the biggest construction buildout in the history of America and certainly,

probably the world. and it's all electricity and plumbing and buildings and everything. But because those are AI forward projects like Chase Lockmiller at Crusoe and Project Stargate, they're going to be early adopters of exactly the same thing you're talking about for construction. So that'll be, construction is a huge fraction of the global economy. So that'll be a really fun doing. And for me, the most important thing for me for an 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 all right we're going to go into a subject we covered on the last pod with emod in particular and eric lear but i cannot wait to hear the take that Alex, you have on this, and Dave, you have it. Again, this is Google's quantum breakthrough near's 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 read. really appreciate the fact that you dig in on everyone these podcasts to go and read the actual science, you know.

Well, 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. You're the only one doing it. And I've heard, I've seen these, I've seen these, uh, these comments in, uh, on YouTube that Alex is an AI. I've seen him glitch, uh, you know, God knows me. We want to use this as our cold open?

I'm not going to disclose any details, but maybe we'll see you in live. Anyway, dive in, please. You read the paper. What does it say? Right. So I read the coordinator paper behind this announcement. It's very interesting. The premise is that there's a certain physical quantity.

In the case of this announcement, it's called a second order, out-of-time order correlation. This 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 speedups 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. I 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. And 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, you know, 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? What 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. But 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. Do 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, 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 the next 10 years. Fascinating. My favorite science fiction books all have digital superintelligent

AI's conscious AI's doing so on the backs of quantum clusters. There would be certain advantages. Like, yeah. Go ahead. 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 Natgas co-location facilities if we had fully reversible quantum computer-based foundation models everywhere, but we're not there yet. Nice. Dave, let's go to the next article here.

of your thoughts on it, which is that President Trump eyes equity into U.S. quantum firms. So, you know, this is the potential beginning of a sovereign-style VC fund for the United States. He's targeted IMQ, Raghetti, D-Wave, Quantum Computing, and Adam 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, 8,000 X 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, you know, 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 jets. Yeah. So just incredible amount of government in that. 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 two. And you've made the point many times, Peter, that 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, thinking 10, 20, 30 years in the future, but we don't do that well. So the government kickstarting quantum is a great move. If you believe in it, five, 10, 15 years in the future. But as a precedent for government involvement in the economy, it's terrible. You know, 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 hated as president. And we see the government investment triggering huge amounts of private investment that follow on, right? So after the Intel deal, you know, Intel stock doubled between $20. a share before and 40 bucks a share, you know, a day or two ago. And we're seeing this again,

a 10 to 15 percent increase in these quantum stocks after this story got leaked. I wonder where they're going to go next. I think the government's been 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 that, you know, 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. Because 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 some of the fusion companies here at Visioneering and talking about Helion. Interestingly, they said, you know, Helion is so close-li-li-li-lip, we have actually no idea what they're doing and how far they're along. You know, there's public disclosures of 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. Alex, do you have any thoughts on that? 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 that's to be decided. I 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 talk to Frank Wilczek about it. He's a Nobel Prize winner in physics and, you know, 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 as 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 1,000 percent since 1970s, while China's costs have steadily declined. That'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, units costs, unit costs tend to collapse the more you make of a given item. And as a country, the U.S. basically stopped making nuclear power plants decades ago. And we're going to, I think, if we're going to, if we're going to, 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 the good news is the demand signal is being sent by the AI data center companies. But 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, it's worse than that. It's worse than that sounds, too, because it's not just about unit cost. 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, its 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. So 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 as 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 a tiny. It's a rounding error. And so everyone's been buying their fuel from Russia for a long time.

Opening up the U.S. supply doesn't really change anything. It's a rounding error in the overall costs anyway. But, you know, if you're going to buy it from Russia anyway, what's the harm in using our surplus plutonium? So 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 There was a, I think that period of time, we're coming out of that now. And 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. And particularly part of the future is fusion. And so the U.S. has put forward a new roadmap for fusion energy. DoE Roadmap touts commercial fusion by the mid-2030s, actual aim for public infrastructure

in the 2030s to scale up. Interestingly, this has $0.00 of federal funding behind it and $9 billion of private investment. Alex, you found this particular timeline. Talk 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 and 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. Now 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 an operation between 2028 and 2030. So I think in short, this roadmap is more a reflection, or at least I interpreted, as more a reflection of some of the most ambitious private sector players and their actual plans.

Dave, we're going to be having a dinner with Bob Mungard on Wednesday night in Riyadh. We have our abundance dinner that we're co-hosting with Amjad from Replit. and Link Ventures, a 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 and 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. You know, I love SMRs and I love the Gen 4 nuclear reactors. 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,

they're not like 26, 27, 28, they're 2030s, which is concerning. Why can't we get these guys going faster? No, the timelines are really interesting to track, and it'll come up at FII next week in a big way, but, you know, a gigawatt, you know, Eric Schmidt said we need 100 gigawatts by 2030, and that's just a fact, you know. You can't go up or down because that's the number of GPUs we'll be making. They'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. So 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, where's that power going to come from? Then suddenly you're launching them into space. And so these completely different ideas, you know, in the modular reactors here, they're fission. So that's the third option, plus renewable is a fourth. So all those

things are racing against this 2030 clock. I'd have to imagine by 2030 we're going to figure it out more efficient compute, 10x or 100x more efficient. And, you know, Alex, I'd love to hear your thoughts on that. The intelligence of the AI between here and there is going to be like, yeah, but also like I have to invoke Jevin's 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, that the amount of energy, the energy reduction that we need in any given year. So 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 at 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. Yeah, I don't keep in mind. The vast majority of the data centers don't need to. to be near population centers. And that's a big difference. You know, 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, you know, Wyoming and Texas and Nevada in the middle of, you know, 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, ah, that's obviously an efficient site. It

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. So, 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 the 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. of respiration and blood oxygenation. This was also the subject of last year's Ig Nobel Prize for discovering that non-human animals could oxygenate their blood supply by consuming oxygen via the other end. As 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 put sort of a hyper-oxygenated fluid enema, let's call it that, then you can perhaps oxygenate your blood supply and get enough of your red blood cells oxygenate to get your brain. I mean, you know, it's like it.

But to elevate just a little bit, I mean, we've just lost our entire audience on this particular art. 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 respirocytes. 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. So there's been persistent sci-fi pressure to discover new ways to oxygenate the blood in environments that are, call them, less than hospitable.

So to the extent that... 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, you know, assemblers, that just opens up everything. And respirocytes are fantastic, you know, literally BCI enabled through nanobots and 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. Ray'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 233, and that's going to unlock, you know, high band with 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 sub-seular 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 do that for sure.

And again, to all of our friends listening, I hope you've enjoyed this episode of WTF. If you're not a subscriber, please join us. We'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, you know, we're living this extraordinary time where we can solve any grand challenge. Congratulations to the Visioneering X-Prize 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. Dave, I'm heading to the airport in, I think, two hours to head to Saudi. Crazy. It's going to be fun.

I'll see you and Emad and Selim 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. meetings you're looking forward to Dave well you know you're kicking it off with the the big shots so you know you've got Eric Schmidt Larry Fank just like the big big money people and the big vision people so that's the 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 so I'll be backstage the whole time it's yeah it's going to be wild so thanks and interestingly enough uh 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'd share their AI activities. 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 Mida 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 do they put in place. How do they, you know, what do they do best for their nation state, for their citizenry? And so we're going to be announcing a program called sovereign AI government. engine. We'll talk about what that means, but it's really to help people around the world

deal with disruptive change and disruptive opportunity at the speed of AI versus the speed of governments and PDFs. It's going to be good. And 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. And so that'll be a huge bellwether for Western democracies because it'll happen there long before it happens in the U.S. 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 mean, I've had people telling me, you know, faculty at UCLA and others saying, I've assigned this to all of my students to listen to that podcast. Yeah. No, it's 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.

It's the Moot Shopmates at their best. Love you guys. See you on the other side of the pond, Dave. Alex. See you in the week when we're back. All right. Sounds great. All right.

Take care all. Thank you. Thank you.