← Moonshots with Peter Diamandis
Moonshots with Peter Diamandis
The OpenAI Internet Browser Has Arrived: ChatGPT Atlas w/ Dave Blundin & Alexander Wissner-Gross | EP #203
01:46:10
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- [00:00]
A
OpenAI has launched a full blown browser. The competitive positioning versus Google is basically all out war.
- [00:06]
B
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.
- [00:16]
C
Okay, great. But Google's going to come in and do at least this and, you know, take back any market share they lose.
- [00:25]
D
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 super intelligence. Having a local agent mode I think is potentially transformative.
- [00:37]
A
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.
- [00:44]
C
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, you know, OpenAI or Google. Now that's a moonshot.
- [01:03]
A
Ladies and gentlemen.
- [01:07]
C
Everybody, welcome to Moonshots. Another episode of WTF just happened in tech. I'm here with my moonshot mates, Dave Blunden and AWG Alex Wiesner. Gross. Good morning, gentlemen.
- [01:18]
A
Hey, good morning. And a huge shout out to the team. You know, we were going to shoot this podcast last night and, 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.
- [01:40]
D
Yeah.
- [01:40]
C
Right now, our fourth moonshot mate, Salim, is on an airplane. I just spent the last four days with him here in Calamigos in Malibu for XPRIZE Visioneering 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 who don't know, X Prize 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 Visioneering. 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 xprize, we raised three and a half million dollars of capital last night.
- [02:36]
A
Do that every night. That's a billion dollars a year.
- [02:38]
C
Yeah, that would be awesome. And someday we will.
- [02:43]
A
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'll 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, see what that looks like.
- [03:05]
C
How wired will I be on caffeine? Oh my God, it's great. But you know, we announced yesterday the, 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 like 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 XPRIZE 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 gotta love the name. And it was actually two of our Abundance360 members who proposed this and raise the capital to get this going. So what is the abundance xprize 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 the conversation last night we can talk about this is there's potential for a lot of civil unrest, right? As people start losing jobs, as subgroups start becoming wealthier. And we've talked about this, I'm absolutely clear in the next decade we're going to have extraordinary abundance uplifting everybody. But it's this turbulent period of the next 2, 3, 4, 5 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, the basics of life for 250 bucks a month then they can start to think about okay, how do I use AI? How do I use this technology to be an entrepreneur to create a better life. Any thoughts on that Dave?
- [05:56]
A
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 inside the 250 buck limit. It's just such a great, great idea. But that unlocks your ability to contribute, to make a living, to get educated, all educational. Move to AI so you can have a healthcare is going to move to AI, healthcare, all of that that ties to bandwidth. So it really is a fundamental necessity and I love it.
- [06:27]
C
Yeah. Alex, any thoughts?
- [06:29]
D
Yeah, this sounds a lot like a Universal Basic Services concept. UBS is sort of the symmetric dual to UBI Universal Basic Income. I' 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.
- [06:54]
C
Yeah, no, super excited about that.
- [06:56]
A
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 where you actually get the things you need to survive still encourages you to work and contribute on top of those services. 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.
- [07:18]
C
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 received enough, enough capital to go into development is a Fusion X prize. And so here I am thinking okay, there are 37 venture backed fusion companies, there's been 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 some of the top Faculty one Professor, mit and saying, no, no, we need an X prize to move this forward. We need the public to understand how this important this 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.
- [08:35]
D
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.
- [08:57]
A
Alex, you know what happens after this visioneering 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 then 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 we'll bring back into the podcast on this will be just immense.
- [09:23]
C
You know, it's interesting, the CEO of Commonwealth Fusion, Bob Mumgardner, is going to be with us in Riyadh and he's going to be on stage with me at the Abundance360 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 xprize. I am so excited about that. And so here we have the best funded, most advanced fusion company actually excited about a Fusion X Prize. So I'm excited to dig in further. All right, the third prize is actually something I love. It's called Wall E. We'll have to be, you know, in debate and discussion with, with Disney about this. But here's the prize. Dump a machine into a garbage dump and the machine sorts the trash and generate piles of metals and foods and paper and basically, can we take our current, what do you want to 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 convergence of technologies. It's going to be AI, it's going to be robotics, it could be material sciences. Any thoughts, Dave?
- [10:48]
A
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? I learned a lot about this just studying that company.
- [11:02]
D
Maybe just a broader comment on this space. I think there is such a long tail 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 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 10 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.
- [12:07]
E
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 and AGI and quantum computing to transport, energy, longevity, and more. There's no fluff, only the most important stuff that matters that impacts our lives, our companies, and our careers. If you want me to share these metatrends with you, I write a newsletter twice a week, sending it out as a short 2 minute read via email. And if you want to discover the most important meta trends ten years before anyone else, this report's for you. Readers include founders and CEOs from the world's most disruptive companies and entrepreneurs building the world's most disruptive tech. It's not for you. If you don't want to be informed about what's coming, why it matters, and how you can benefit from it. To subscribe for free, go to dmanandis.com metatrends to gain access to the trends 10 years before anyone else. All right, now back to this episode.
- [13:01]
C
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 in 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 XPRIZE Visioneering. Congratulations to Nusan Shari and the entire leadership team of X Prize. It was an awesome two and a half days and we recorded a podcast which we dropped a couple of days ago. So, you know, we had Imad Mustache and Eric Pulier, Saleem and myself doing 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 awg?
- [14:17]
A
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 Google launched Chrome. Chrome was not in the world. People don't remember this and they leveraged their user base to install it and now they have 2/3 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 OpenAI, Sam, being the strategic genius that he is, says, okay, this is one of those fundamental Bill Gates style pilots points of control. We absolutely have to play in the browser game. So we're going to 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 eyebrows.
- [15:35]
C
It'll be taking your data.
- [15:37]
A
Yeah, yeah, that too. I mean that's, that's the key, right?
- [15:39]
C
You know, let's watch a short video of Sam and his team announcing Atlas and then we'll talk about it.
- [15:46]
B
We're going to launch ChatGPT Atlas, our new web browser. We think that AI 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. ChatGPT now can take actions for you. It can do things.
- [16:18]
C
All right, so my first reaction is, okay, great, but Google is going to come in and do at least this and take back any market share they lose. I don't know. Do you agree with that? Alex, what are your thoughts?
- [16:33]
D
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 backend superintelligence is being surfaced via which channels. Browser is 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 is that 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, the other features. Having a local agent mode I think is potentially transformative for, 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 ChatGPT agent, this one is at least partially local.
- [17:55]
A
So you've got you' 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, super hyper creative startup guys. So that's Dario and Sam. And so Sam OpenAI 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 we'll go out through corporate channels. Then Sam is playing the old Bill Gates game, where 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. 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. It gets Jony I've 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 OpenAI and it's just really fun to watch.
- [19:09]
C
Dave and Alex, 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, OpenAI or Google.
- [19:35]
A
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 SO and 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 the personal data warfare is kicking off in a huge way right now. You mentioned it a second ago, Peter.
- [20:07]
C
What'S the downside of what we see here with Atlas? I mean, we have the ability of OpenAI 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?
- [20:29]
D
I think we'll see forcing functions for greater forms of confidentiality and privacy. But I'm just reminded, do you remember the browser wars?
- [20:38]
C
Yeah, of course.
- [20:39]
D
Right.
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C
And Google won with 70% market share today.
- [20:43]
A
Yeah.
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D
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.
- [21:11]
C
Amazing. Alex, would you introduce this next slide here? You built a chess game, but before I play it, explain what you built here.
- [21:22]
D
Yeah, with computer use assistance, CUAS of which arguably this new ChatGPT Atlas agent mode is one example. I have my own evals. One of my favorite evals for testing these CUAs is to see whether they can win at simple and or complicated single player web games. So favorite easy example is to see whether I turn atlas loose on single player, not double player, a single player game of web chess and see whether it can win. I've used this eval 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 sort of 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.
- [22:43]
C
Did it ask you for hints or did it ask some other ll it.
- [22:47]
D
Asked the website for hints. Once it discovered, which it did pretty quickly, that it could ask for hints. It asked for hints 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.
- [23:00]
C
Amazing. Amazing. I'm going to jump into Anthropic and this is a conversation between Jonah Cool, who's the head of Life Science Partnership and Development, and Eric Cauter Abrams, who's the head of Biology and Life Sciences research. You know, in January at the World Economic Forum, we heard Daria Amade, 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, if we're able to Hit the targets we have for AI, we could see the doubling of the human lifespan the next five to 10 years, which perked everybody's ears up, including mine. 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.
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F
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 at Anthropic are excited about applying it is within biology in 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 need Claude to be conversant with all of the tools that scientists are using every day.
- [24:24]
A
Right.
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F
And so there's a whole ecosystem of important tools and partners out there that we are integrating with.
- [24:30]
D
Right.
- [24:30]
F
So we talk about benchling on the, you know, experiment administration, lab, notebook side of things. TEDx, genomics with cellranger.
- [24:38]
D
Right.
- [24:39]
F
Incredibly important platform for analyzing single cell experiments. And then PubMed, for example, for being able to query the literature.
- [24:47]
D
Right.
- [24:47]
F
And so these are just three of three incredibly important partners in a much ecosystem. And so that that base level is we need to make sure that Claude can, can talk to all the major sources that scientists are using throughout, you know, their, their daily. We want to bring Claude to performing at the level of a, a superhuman research assistant that can assist you as, as a scientist throughout all stages of your project.
- [25:10]
D
Alex, I, I, I speak from time to time on this pod about superintelligence solving, math, science, engineering, medicine. I, I think this is likely how biolo. 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.
- [25:52]
C
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 Molten 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 super intelligence model they're building. And these, these science data factories are basically 24, seven, 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, gather the data, bring it back, check their, 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, cat 5 to 10 chemical, 10, 5 to 10 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.
- [27:21]
D
I think that it as I think Peter, you might know, Jeff was a lab mate of mine when we were undergrads at mit and I'm a huge evangelist for dark labs. I would like to see dark labs for everything.
- [27:34]
A
Well, and Jeffrey Von Maltzen, I know it's a harder name to find on the Internet than Jonas Kuhl or Jonah Kuhl, but definitely look him up. The guy is going to be huge. You can see it coming. 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 got to slow down AI, we 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 that, that's not going to happen. So that's why the AI labs are talking about this use case so much, because it's life, it's preserving lives.
- [28:22]
C
And by the way, Jeffrey Von Moulton and Lila will be at the Abundance Summit. Super excited for him to present our theme in March of 26 at the summit is Super Intelligence and the rise of Humanoid 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 Grokopedia to come online. Alex, what are your thoughts here?
- [29:00]
D
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, I think AI generated knowledge is right around the corner.
- [29:40]
C
Okay, Dave, I'm going to go ahead and then I have a rant on this.
- [29:43]
A
All right, well, this is right in my wheelhouse, so I need to wax poetic for a minute on this topic. So 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. Traffic, 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, is well known. Now, 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 got to pay Google, you got to pay Facebook. And if you do that concurrently with putting your content out there, then they'll give you the traffic. Also, you need to reformat your content so it's easily readable, interpretable by the AI. Hence geo@ the bottom of this 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 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 happening.
- [31:10]
C
My rant on this. I've been trying to update my Wikipedia page for literally two years. I hired consultants to update my Wikipedia page and every time it's updated, they bring it back to what it was. It's like so stuck 20 years ago. And you know, I don't know. I 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 Grakopedia will be a solution here. Or in fact, any AI that just has, you know, spin up a page on Dave Blunden, I can send somebody. That's going to be awesome.
- [31:52]
A
I'll give you one other, you know, pro tip. Get, get a similar web account, SimilarWeb.com, get a similar web account and you can see exactly where that user went. The, 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.
- [32:10]
C
Amazing. All right, next article here is GPT5 rediscovers long forgotten math connections. This has Alex Wiesner Gross written all over it. Dr. Gross, please tell us.
- [32:24]
D
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 GPT5 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 water level of intelligence is rising day by day. And some of the earliest math problems, open math problems to be solved, I think will be math problems where the solutions were known to a subset of humanity, but not to all of humanity. And we're going to wring our hands collectively as a civilization quite a bit over, well, was this open problem in math really open, or was it solved, or was it half open where some people knew how to solve it and other people didn't know that it had even been solved? That's the fog of war phase that we're in. So there was a lot of discussion over the past week. Was this a real accomplishment, a real discovery in math by AI, one of the Erdish problems, number 1043, for example. But there was, I think, ultimately a lot of really revealing discussion and commentary on this particular problem and also other Erdish problems that actually this is just a phase right now, like early days, 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.
- [34:13]
C
Yeah, you mean solved, right? You mean solved.
- [34:16]
D
Open means unsolved, closed means solved.
- [34:20]
A
I think this is also a great little case study in how the academia world is like, well, this proves that it didn't really solve it. It looked up an ancient. When you're trying to do something, you don't care a wit how it solved it. It came back with the right answer. This is a lot like ThinkStruct in our lab. It's a company that does academic research and now patent research using AI. So Nikki Abate and Julius Heitcutter. 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.
- [35:10]
C
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 were 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. I said, well, why don't you just ask? And so what I, what I showed her said, okay, here's 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.
- [35:57]
A
All right, anyone who's a real fan of this podcast by now has to have read Accelerando because Alex Wisner Gross says it's the best piece of writing in the history of humanity. If you, 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. With AI generated patent filing.
- [36:18]
C
Yes, consistently. Then give it away. Anyway, let's not go there. All right, Our next article here is Uber tests Microwork for drivers to train AI. So Uber is paying between 50 cents to a dollar per task that can take two to three minutes and get processed within 24 hours. So is this sort of a digital task? Rabbit? What is this? Dave.
- [36:44]
A
This is really, really cool because Mercur is almost closing in on a billion of revenue Going all over the world, grabbing expertise and getting it into a format where the AI can assimilate it and then the AI can be an expert in that topic too. Well, you got all these Uber drivers driving around, they're sitting around a lot of the time. Do they have knowledge that may be a contributor back into the great AI machine? Because a lot of what's missing is physical motion, common sense, just all this information. So why not use that same platform? You've already got to be another Merkor type AI data gathering machine.
- [37:21]
C
Alex, your thoughts on this?
- [37:22]
D
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.
- [37:49]
C
Yeah. So fascinating that Uber turned this way. You know, 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.
- [38:05]
A
Well, you know, during COVID you know, Lyft got annihilated and Uber did fine because they had launched Uber Eats. So they're, you know, they're very, very thoughtful about this. You know, in fact, when, when, I don't know if you remember Travis Kalanick when Uber was going public, but he got on stage and he said, uber is not a ride sharing, hailing cab company. We're an Internet fabric. It was some, like, really ethereal, but now they're actually doing it. It makes sense in hindsight. So they don't view their platform as being about cars and rides. They view it about.
- [38:39]
C
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 had 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 Joby 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'll be fun. All right, Alex, I'm going to turn to you on this one. Deep Seek is packing text into images. Talk about this, pal. This isn't a significant transformation, isn't it?
- [39:26]
D
Yeah, this is a major advance from Deep seq. So a new model that Deep SEQ announced Deep SEQ ocr. So maybe a bit of background first. Foundation models, frontier models like GPT aren't thought to perceive text in the way that humans perceive text. Humans look at text on a page and we see text visually. The frontier models, 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 SEQ ocr, which is again, if you squint at the model architecture, it's sort of an autoencoder that does optical character recognition after a fashion, but in a really interesting way. 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, 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.
- [41:25]
C
Interesting. And we're going to be seeing an article later about Amazon getting into the AR Glass marketplace and we're going to see from Meta and Google and probably OpenAI and all of them we're transforming from a phone as the medium of interface to glasses at this medium interface. So I'm assuming that this kind of technology is going to help your Glass effectively translate everything you're seeing into something that can be understood, read and responded to.
- [42:00]
D
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 quite transformative.
- [42:11]
C
Dave, you want to comment on this?
- [42:13]
A
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.
- [42:52]
C
Do you expect, Alex, that we're going to see this type of OCR come into all the models next?
- [42:57]
D
Yeah, I think we're moving towards a near future with universal tokens, tokens that span modalities. And I've long thought, wouldn't it 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.
- [43:23]
A
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.
- [43:56]
G
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- [45:00]
C
All right, let's jump into our next article here. This is OpenAI hires bankers to automate junior work. So OpenAI has hired over 100 bankers, paying them 150 bucks an hour to train AIs on M&A LBOs, IPOs. Effectively, these bankers are in one sort of the way, traders helping to eliminate jobs of fellow bankers. So I don't know, my first take on this is OpenAI 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 OpenAI going to do this for every field? You know, get rid of white collar work across the board and.
- [45:47]
A
Well, the answer to that is absolute yes, they are going to do this for every field and they're going to do it quickly. And I just had this conversation with two of our companies. Make sure that you're the guy that Sam calls. And they're, 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 Y Combinator who haven't even gotten to market yet. So if you're somewhere between those two things, you just need to position yourself like Brendan Foody did at Merkor, get into the building and be the person that solves that problem for OpenAI. But yes is the answer. He'll do this in absolutely every category of human endeavor.
- [46:33]
C
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 were up with Kevin, Kevin wheel that is OpenAI going to be moving into and eliminating all the entrepreneurial vertical channels. I find this fascinating.
- [46:57]
A
Yeah, go ahead, Malik.
- [46:59]
D
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 service 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.
- [48:08]
C
So bottom line here is that this effort by OpenAI could eliminate between a quarter and half of the junior headcount across Wall street within two years. All right, moving on. I love this article. So Google is prepping Genie 3 for public experiments. So Genie 3 is going to let users create interactive worlds with text prompts. We talked about this. Extraordinarily powerful. This is, 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 of different areas. Alex, do you want to jump in?
- [48:55]
D
First of all, you have to admire that the user interface which we're now seeing previews of, looks identical almost to the grid of the holodeck in Star Trek.
- [49:03]
C
Yes, I love that.
- [49:06]
D
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.
- [49:52]
C
It's the democratic modernization of interactive content creation right at a level of reality and resolution that is shocking just to hit on some of the ideas right. For the individual. If you're thinking about this, how would I use it? You can build personalized gaming. It's creative storytelling. It's customized education for companies. I think a lot of companies that could 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.
- [50:55]
A
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 Nvidia box, you're not going to be able to get the speed you want.
- [51:28]
C
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?
- [51:45]
A
Yeah, absolutely. Mark Zuckerberg has taken every penny of cash flow from one of the biggest tech companies on the planet, from Meta, Facebook, and pumped it all into this AI initiative. And now is borrowing going to the next level. And the stock market loves it. So what does that tell you as a CEO? If you are a true AI company and on a true AI mission, you can invest like crazy from your public capital or from your, 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.
- [52:34]
C
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.
- [52:43]
D
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 credit 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 infrastack.
- [53:21]
C
The implications of this though is capital from public equities, from sovereigns, from debt, all flowing into AI at the exclusion of so many other technology areas.
- [53:32]
A
Well, one of our best partners, Kush Bavaria, phenomenal guy. I just co founded a company called Orn O R N N. Yeah, check it out. But my point in this is that people that are kind of technical and engineering wouldn't normally get into the finance side of things, but kind of like Chase Lockmiller, they're getting drawn into this in a big way. And it's a very, very good strategic move. If you have any interest in finance whatsoever and you understand GPUs, chips, data centers, or just math, it's a great direction to go. It's just a huge amount of capital redirecting into this direction and making it move intelligently. The right investments, the right locations, 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.
- [54:18]
C
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. Is ADAFlop here? Is Adaflop there?
- [54:41]
A
All right, I'm going to feed Alex on this one. I can't wait to hear what he has to say. But 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 superintelligent. Register it with the government type, type thing. That's 1E26. A Zeta flop is what? 1E21. So that's per second, though. That's, you know, that's that many flops per second.
- [55:08]
C
So we're talking about exponent of. Yes, good.
- [55:13]
D
Yeah.
- [55:13]
A
So, so to get from, you know, 10 to the 16th to 10 to 21, you need, you need five more ooms. So that's a hundred thousand.
- [55:20]
C
So every hundred thousand are orders of magnitude just to translate five more ooms.
- [55:26]
A
Five more. So 100,000 x. So every 100,000 seconds a one Zeta flop computer can create a foundation frontier level AI model every 100,000 seconds. So 100,000 seconds is 1.1 days, as it turns out. So every day you get a new foundation and that's at one zetta flop. This is 16 zetta 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'm doing.
- [55:55]
D
I need to double check, but it sounds approximately right, I would add. So Oracle is. This is all in the public reporting. Oracle is both financing and operating Stargate Abilene. And Stargate Abilene is, I think, together with this 16 ZetaFlop super cluster. It is emblematic of a new form factor for computing. The personal computer was a major new form factor. The smartphone was arguably a major new form factor. These superclusters with Approximately a million GPUs and tens of Zeta flops, this is a fundamentally new form factor for computing with high speed interconnect, which we're not talking about, but which is arguably just as important as the raw compute power being a key architectural innovation. 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.
- [57:06]
C
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 is sort of the little brother there and they're growing closer and closer. Alex, what do you make of this?
- [57:32]
D
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 infrastack. So we're seeing Nvidia GPUs up against Google, TPUs, up against Amazon Trainiums 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 now 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.
- [58:36]
C
Alex, for those who don't know the difference between TPUs and GPUs, would you give us a 101 here?
- [58:43]
D
GPUs? This is branding that was popularized by Nvidia. So graphics processing unit. This was originally conceived and went to market for accelerating video games, where Nvidia was the arguably the chief actor for accelerating compute, specifically for video game purposes and professional graphics as well. Then eventually it found its way to Bitcoin and other crypto minings and then fortunately the need and the thirst for accelerated compute for AI arrived just in time to sort of recover from a bit of a mini crypto winter and step in 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 operation that they need to perform in support of AI and machine learning is taking large matrices which if generalized, become tensors, sort of high dimensional matrices of numbers and multiplying and adding them. So that's sort of to oversimplify, that is the core operation of of accelerated compute for machine learning, just taking matrices of numbers and multiplying them.
- [60:05]
A
That's a great point.
- [60:08]
C
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 Star Cloud 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.
- [60:40]
H
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, 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.
- [61:11]
C
So it's interesting Philip Johnson was On stage pitching a prize called, you know, the space, let's see the space. Cool X Prize. It was something like that. It 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?
- [61:49]
D
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. Just jumping out a few decades, playing this tape forward, as it were, playing the recording forward. I think if humanity ends up being permanently latency constrained, 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, that we're not aware of yet, then I could imagine scenarios where actually building a Dyson swarm, turning star cloud 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 swarm.
- [63:28]
C
Yeah, just to clue folks in, Dyson swarm, the terminology comes from Dr. Freeman Dyson, who was at the Institute for Advanced Studies at Princeton, who basically said as you become an advanced civilization, you're going to want to capture all of the energy coming out of your star. 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 day. 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? There's going to be a lot of robotics required to do that. And when do we get there? Is it 10 years from now? 20 years from now? We're going to find out along these lines. We saw Caruso basically announce that they plan to Support this by 2027. And I'm not exactly sure what they mean by supporting it. They're going to put an H100 up in space. And H100 in space represents 100 times more compute than any other satellite has had. But It's a single H100. It's not a cloud, not a Crusoe cloud. Alex, did you dig into this further?
- [64:59]
D
Yeah, I would maybe also just comment on timescales. So putting a single H100 in Low Earth Orbiter LE NOT sound like that much now. But if you just starting from physics, like if we have this notion that we know, or at least have a prediction that the end state of all of this is taking apart our solar system, you could actually just do a few calculations to figure out the timescale for when that would happen. 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's 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 viewed, you know, 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 that's important.
- [66:14]
C
That's exponential growth. Double something 30 times, you get a billion fold increase. Dave, what are your thoughts on this?
- [66:21]
A
Well, Peter, you said, you know, the sunlight hitting the Earth every day is 8,000 times more energy than we consume. But have you ever done the math on the, the fraction of all the sun's energy that hits the Earth in the first place?
- [66:31]
C
Oh yeah, far less. It's a fraction of 1%.
- [66:37]
A
Yeah, I know. I don't know how many decimal points are in there, but it's like there's a monster amount of energy in that Dyson sphere, Dyson swarm view. So yeah, it's 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.
- [67:03]
C
It's worth pointing out, while the term star cloud sounds like it's got musk behind it, Elon is not involved in this. He did retweet the star cloud 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 life energy into this personally, it'll be a real winner. So, you know, we've seen this before where Elon goes heads down and 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 A15 mean for, you know, for Tesla, for Optimus, for Xai?
- [68:10]
D
So I've spoken in the pod, on the pod in the past about this notion that superintelligence is not going to stay just. Just bottled up in the data centers. 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 AI 5 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 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 that this is quite literally, potentially the embodiment of intelligence walking out the door of the data center into our homes and into our lives.
- [69:06]
A
Well, and this ties back to one last story too. All the big guys now have their own chips, as Sam announced in our last podcast that, 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 TSMC or intel and you have your whole supply chain going right into your own data centers, you can innovate, redesign the chip and get it back into production very, very quickly. You know, Google's already got that cycle down, cycle time, way down. So it leaves anthropic in kind of this uncomfortable position where. Well, we're buddying up with Google. Yeah, but you're on their TPUs, they're going to give you whatever they want to give you.
- [70:01]
C
Fascinating. But all of this comes back to TCMC production capability. Right. In Samsung there are basically choke points.
- [70:10]
A
Yeah, there's no doubt that any one of these companies would be buying tsmc, intel or Samsung tomorrow if the regulators would let it happen. Because, because that's the choke point and they all know it. So all these really, you know, high level partnerships and relationships are really, really forming and it's a very competitive playing field but everyone's going to have their.
- [70:31]
C
Own, you know, week by week we're seeing the shifting relationships and in capital flow here. 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, for labor.
- [70:51]
I
Well check out these nerdy smart glasses. These are smart glasses developed by Amazon for their delivery drivers. So they're just in development now but basically they use technology to like a head up display, show you what you need to do, 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 Meta's Ray Bans or maybe Apple Vision from Amazon.
- [71:31]
C
Okay, so this is what I think is going on. It's, this is put forward as we're going to help our drivers, you know, 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 self driving models. Dave, what do you think?
- [72:04]
A
Yeah, you're exactly right. And it shows you how the technologies interact too. Because the glasses will be profitable instantaneously within their internal use case. They can perfect them and then they can decide later. You remember there was a Kindle phone, Kindle Fire phone. It didn't succeed, but they've tried before to compete with Apple or Android in the device warfare game. 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.
- [72:40]
C
Yeah. Do you want to add anything, Alex?
- [72:43]
D
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 this, we're going to see this across many, many other verticals. Healthcare, energy, hospitality, expect smart glasses and wearables for building training data sets and post training data sets across every possible.
- [73:15]
A
Also construction, memory over construction. You know, we're doing the biggest construction build out in the history of America and certainly probably the world. And it's all, you know, electricity and plumbing and buildings and everything. But because those are AI forward projects like you know, Chase Lockmiller at 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, that'll be. Construction is a huge fraction of the global economy. So that'll be a really fun.
- [73:43]
C
And for me this, the most important thing for me for a aging population is going to be memory augmentation. Right. Using these glasses to remember you know who you're talking to. The last conversation you had. I mean personally I can't wait. I meet so many people and I love being able to, you know, remember the details but sometimes it's just a challenge. All right, we're going to go into a subject we covered on the last pod with IMOD in particular and Eric Pilier. But I cannot wait to hear the take that Alex you have on this. Dave, you have it again. This is Google's quantum breakthrough nears real world use. So this is the Willow Quantum chip. A friend in Santa Barbara, Hartmut Nevin, who heads the Google Quantum team. Congratulations. But at the end of the day, Alex, what does this mean?
- [74:37]
D
Well first maybe a little bit of the background. So I read the coordinator paper behind this announcement. Very interesting. This was the Google, by the way.
- [74:46]
C
Alex, I have to say I really appreciate the fact that you dig in on everyone these podcasts to go and read the actual science, you know.
- [74:56]
D
Well, it's difficult to comment on it if I haven't read it, but thank.
- [74:58]
C
You, I understand that.
- [74:59]
A
Well everybody else on the planet is commenting on it without reading it. You're the only one doing it.
- [75:04]
C
And I've heard, I've seen these, I've seen these, these comments in on YouTube that Alex is an AI. I've seen him glitch, you know, God.
- [75:16]
D
Knows we want to use this as our cold open.
- [75:21]
C
I'm not going to disclose any details but maybe we'll see you live. Anyway, dive in please. You read the paper, what does it say?
- [75:31]
D
Right. So I read the coordinator paper behind this announcement. It's very interesting. The premise is that there's a certain physical quantity and in the case of this announcement it's called a second order out of time order correlation. 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 was to say a non quantum computer, to be able to compute it. So I think it's very interesting. It's nice progress in terms of demonstrating quantum speed ups or quantum advantages versus classical computers. What I'm still waiting for though, if I got my wish, is a more call it economically transformative quantum algorithm. What I'm waiting for, what I'm hoping for is that sometime in the next few years we will achieve a definitive breakthrough speed up for quantum acceleration of AI. 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.
- [77:04]
C
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 do we 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, you know, relative. Is it larger? Many times larger. What are your thoughts?
- [78:07]
D
I want to bisect the question into now short term versus long term. @ 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 out 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 the sense like the grand challenge is that quantum was supposed to be the great white knight and solve for us. Keep getting devoured by AI instead. I'd love to see a bit of turnaround sometime in the next 10 years.
- [79:50]
C
Fascinating. My favorite science fiction books all have digital superintelligence. AI's conscious AI's doing so on the backs of quantum clusters.
- [80:02]
D
So there would be certain advantages like.
- [80:05]
C
Yeah, go ahead.
- [80:07]
D
So potential advantages like energy efficiency. If we could build a fully reversible AI supercomputer that would probably have some sort of quantum coherent foundation that would be transformative. We wouldn't need to build all these SMRs and, and fission plants and natgas colocation facilities if we had fully reversible quantum computer based foundation models everywhere. But we're not there yet.
- [80:34]
C
Nice. Dave, let's go to the next article here and I'd love your thoughts on it, which is that President Trump eyes equity into US Quantum firms. So this is the potential beginning of a sovereign style VC fund for the United States. He's targeted imq, Rigetti, D Wave, Quantum Computing Inc. And Atom Computing. I mentioned on the last pod when we talked about this that I had taken D Wave public through a SPAC. Huge, you know, 8000x return from the earliest, lowest point to where it is today. Dave, thoughts on this?
- [81:16]
A
Yeah, well, I love it it and I hate it as a precedent, but I still love it because Alex was always pointing out that what we're doing right now is unprecedented, except maybe during the build up 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. Just incredible amount of government investment. Yeah. So that's what's going on right now in AI and it's great. It's what we need. So now that's moving into Quantum 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. 5, 10, 15 years in the future. But as a precedent for government involvement in the economy, it's terrible. You know, it's because. 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 it.
- [82:27]
C
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 a day or two ago. And we're seeing this again, a 10 to 15% 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 strategic investments?
- [83:01]
A
Well, I hope they take Alex's World War II analogy and stay focused on the things we need in that this very specific race to AGI and asi. So rare Earths would fit for sure and, and energy would fit for sure. Quantum may or may not.
- [83:17]
C
You know, kind of. 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 to some of the fusion companies here at Visioneering and talking about Helion. Interestingly, they said, you know, Helion is so close lipped, we have actually no idea what they're doing and how far they're they're along. You know, there's public disclosures, 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 targeting 2030, but they still have a lot more development. Alex, do you have any thoughts on that?
- [84:08]
D
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, or warrants or some other financial structure. But I think that the question of how strategically important quantum is as a technology, when you compare it with more obvious feedstocks like rare earths or energy or compute or fabs, I think that's to be decided. I don't know.
- [84:46]
A
Well, I will say I can't add anything to Alex's insights on this at all. But I will say I talked to Frank Wilczek about it. He's a Nobel Prize winner in physics and 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.
- [85:05]
C
All right, let's jump into energy. A few different articles here. This one's interesting in particular is a chart showing us the increasing price for US 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% since 1970s, while China's costs have steadily declined. That's not good news. Alex, do you want to weigh in on this?
- [85:37]
D
I think there is an alternative history where the US never basically stopped building nuclear plants in the late 1970s. And if you're familiar with all of the microeconomics around, experience curves costs, unit costs tend to collapse the more you make of a given item. And, and as a country, the US basically stopped making nuclear power plants decades ago. And we're going to, I think if we're going to feed the voracious energy appetite of these AI data centers, we need as a country to relearn how to build lots of next generation nuclear plants. And 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, a truly power rich society.
- [86:32]
A
Well, Alex, it's worse than that sounds too, because it's not just about unit costs. If you look the actual construction of a nuclear facility in the US it's mostly overhead, regulatory, political garbage, bullshit costs.
- [86:45]
C
Regulation, it's litigation, it's loss of manufacturing expertise, all of these things and we've done it to ourselves. All right, next article here is fascinating. US 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 sort of removing the shackles and giving entrepreneurs access to feedstock. Who wants to take it?
- [87:34]
A
Well, everybody probably knows this, but the cost of the fuel in a nuclear reactor is tiny. It's a rounding error. And so everyone's been buying their fuel from Russia for a long time. Opening up the US 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, it's not changing the math one iota.
- [88:02]
C
Alex.
- [88:04]
D
I'd also comment maybe even more broadly on nuclear engineering as a vibrant discipline. There was maybe a bit of a hot take, but there was a period of time for a few decades when nuclear engineering, unless it was for say some biomedical application, was positively unfashionable to study. And I think that, I don't want to call it a nuclear winter for obvious reasons, but there was a, I think that period of time. We're coming out of that now and as a society, speaking particularly of the US but the west in general is entering an era when we need to refamiliarize ourselves with, with the nuclear fuel cycle and get comfortable with nuclear fuel cycles in general. It's part of the future.
- [88:52]
C
In particular, part of the future is fusion. And so The US has put forward a new roadmap for Fusion Energy. The DOE roadmap touts commercial fusion by the mid-2030s. Actual aim to for public infrastructure in the 2000-30s to scale up. Interestingly, this has $0 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?
- [89:23]
D
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 us. 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 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 in operation between 2028 and 2030. So I think in short, this roadma is more a reflection, or at least I interpret it as more a reflection of some of the most ambitious private sector players and their actual plans.
- [90:43]
C
Dave, we're going to be having dinner with Bob Mumgaard 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.
- [91:04]
A
Yeah, me too.
- [91:06]
C
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, of SMR small modular reactors. This one is with X Energy. We've talked about X Energy before. Its 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. You know we unfortunately shut and we talked about this, we've shut down our ability to manufacture these and so this has become an entrepreneurial effort. But one of the things that I find fascinating is while we have the designs, we have permissions, the timelines for getting these SMRs out, they're not like 26, 27, 28, they're 2000 and 30s, which is concerning. Why can't we get these going faster?
- [92:12]
A
No, the timelines are really interesting to track and it'll come up at FII next week in a big way. But a gigawatt. Eric Schmidt said we need 100 gigawatts by 2030 and that's just a fact. It 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 US 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. The 100 gigawatts is a stepping stone to something much bigger just a few years later, later. So if the fusion comes online in 2029, 2030, it's massively important. But if it's just five years late, we're like, where's that power going to come from? Then suddenly you're launching them into space. And so these completely different ideas and 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.
- [93:21]
C
I have to imagine by 2030 we're going to have figured out more energy efficient computer compute, 10x or 100x more efficient. And you know, Alex, I'd love to hear your thoughts on that.
- [93:32]
A
The intelligence between here and there is going to be like, yeah, but also.
- [93:36]
D
Like I, I, I, I have to invoke Jevons Paradox. We're, we're going to have presumably much more demand for it as well, even though cost per computer, algorithmic advances are going to, 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 been, might never have been on the table for, for some of the first generation nuclear power sites. So even if there is a sequencing issue and even if the first boatloads of SMRs start arriving circa 2030, I do think they're very likely to end up being an important part of the overall power mix for AI data centers and otherwise.
- [94:47]
A
Yeah. Keep in mind the vast majority of the data centers don't need to be near population centers, and that's a big difference. Those iconic cooling towers that Alex was mentioning, people hate them when they're on the beach in front of your house. But these SMRs can be Wyoming and Texas and Nevada in the middle of very unpopulated areas. And that's a great place to put some of these really large scale data centers. So this will happen.
- [95:14]
D
They look like normal buildings. That's what's most striking to me. Me you would never, at least with the eyes of 2025 today, look at the building that you're sharing and say, aha, that's obviously a fission site. It looks like a normal building.
- [95:28]
C
Amazing. So 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. 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.
- [96:09]
D
Sure, sure, Peter. I'll take the hit for ending on a loan note. But in all seriousness, this is a transformative breakthrough, or at least the beginnings of a transformative breakthrough for people suffering from severe respiratory failure who can't breathe through their lungs. And if folks have seen the Abyss, the science fiction movie where there's a famous scene where a character is consuming the oxygenated, or I should say an oxygen substitute. Liquid. Liquid. So breathing liquid. Basically deep underwater they'll have some familiarity with novel forms of respiration and blood oxygenation. This was also the subject of last year's 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.
- [97:12]
C
Well, the intestines are a very blood rich, large surface area part of your body. And so if you're able to put sort of a hyperoxygenated fluid enema, let's call it that, then you can perhaps oxygenate your blood supply and get enough, enough of your red blood cells oxygenated.
- [97:38]
D
But to elevate just a little bit.
- [97:39]
C
We've lost our entire audience on this particular art.
- [97:42]
A
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.
- [97:54]
D
Maybe just to try to elevate a little bit. There's been interest over the decades in, 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, in environments that are, call them less than hospitable. So to the extent you're really, really.
- [98:32]
A
Reinforcing the theory that you're an AI.
- [98:36]
C
So, you know, all of this, 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, we're using DNA origami, but, you know, drexlerian assembler that just opens up everything. And respiracytes are fantastic. You know, literally BCI enabled through nanobots in the brain. I can't wait. So, you know, I'm going to get Ray Kurzweil on our podcast so we can have the conversations with him. 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 2033. And that's going to unlock, you know, high bandwidth BCI, but unlocks basically longevity, escape velocity, or I don't like using the term immortality because it sort of hits so many different negative buttons. But if you can repair on a cellular and subcellular level all parts of your body, that is an incredible future.
- [99:42]
A
Well, I think we'll get Ray and Alex on the same podcast. That podcast could also be a more portal. That would be something I would kill to see.
- [99:50]
C
Well, we'll, 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 XPRIZE teams for winning Visioneering and to the entire XPRIZE organization for really accelerating these grand challenges. I'd love to know in, in the notes here if you have an X prize 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.
- [100:49]
A
Crazy.
- [100:51]
C
It's going to be fun. I'll see you and IMOD and Salim there. Alex, we will miss you. You'll be there either digitally or in spirit. But we have quite the week lined up. Meeting with the top CEOs from all the AI and tech companies. It's going to be fun. Any favorite meetings you're looking forward to? Dave?
- [101:12]
A
Well, you know, you're kicking it off with the, the big shots. So you know, you've got Eric Schmidt, Larry Fink, 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.
- [101:35]
C
Yeah, no, a pleasure. I chair FII is out of Saudi. It's the Future Investment Initiative and I'm on the board there and I chair their AI activities. You know, one of the things that's going to be interesting this year is we have I think 20 something heads of state and I'm going to be co chairing a conclave with IMOD and ANA from A16Z and we're going to be talking about how to use AI to accelerate great 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, for their nation state, for their citizenry and so we're going to be announcing a program called Sovereign AI Governance Engine. We'll talk about what that means, but it's really to help people around the world deal with disruptive change and disruptive opportunity at the speed of AI versus the speed of governments and PDFs. It's going to be good.
- [102:51]
A
And the reason that's coming out in Saudi Arabia at Riyadh and Riyadh is because the deployment rate of ideas like that can be very, very fast at in those countries because they make decisions kind of in a very tight knit, little, 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 US And Europe.
- [103:15]
C
Alex, what's the week like for you, buddy?
- [103:17]
D
It's in some sense the same as every week for me, which is trying to accelerate and smooth out the gentle Singularity.
- [103:25]
C
Yes, I love that. By the way, our episode on the Singularity is Now has just done incredibly well. People. I mean, I've had people telling me, faculty at UCLA and others saying, I've assigned this to all of my students to listen to that podcast. Yeah, no, extraordinary. It's really done. It's gone viral. So if you haven't heard that episode, the Singularity is now, go listen to it. It's the Moonshot Mates at their best. Love you guys. See you on the other side of the pond. Dave, Alex, see you in a week when we're back.
- [103:59]
D
Back.
- [104:00]
C
All right, sounds great. All right, take care. All.
- [104:25]
D
Right, Sam.