Moonshots with Peter Diamandis - Sam Altman: Singularity Slow-Down, Emad Runs 18 Grokbots, Waymo Slashes Hardware 83% | EP #283

Episode Date: August 27, 2026

The mates sit down with Emad Mostaque to discuss: whether the singularity is slowing down, Sam Altman’s changing views, the case against an Anthropic IPO, Emad’s 18 Grokbots, Waymo’s massive hardware cost cuts, China’s 100x cheaper AI models, NVIDIA’s $6B open-source bet, and the increasingly competitive frontier lab race. Sign up for our AMA at http://Moonshots.com/ama Get access to metatrends 10+ years before anyone else - https://qr.diamandis.com/metatrends   Peter H. Diamandis, MD, is the Founder of XPRIZE, Singularity University, ZeroG, and A360 Salim Ismail is the founder of Open ExO, a GP at Exponential Venture Capital/The Organizational Singularity Fund and a sought after global speaker and thought leader. Dave Blundin is the founder & GP of Link Ventures Dr. Alexander Wissner-Gross is a computer scientist and founder of Reified Emad Mostaque is the founder of Intelligent Internet ( https://www.ii.inc )  Read Emad’s latest papers exploring the future of society, law, personhood and governance: https://ii.inc/common-wealth Read Emad’s Book: https://thelasteconomy.com  – My companies: Apply to Dave's and my new fund:https://qr.diamandis.com/linkventureslanding   Get the blueprint for generative media https://goo.gle/startupgenmedia  Go to Blitzy to book a free demo and start building today: https://qr.diamandis.com/blitzy   Your body is incredibly good at hiding disease. Schedule a call with Fountain Life to add healthy decades to your life, and to learn more about their Memberships: https://www.fountainlife.com/peter  Join the Moonshots Mates on Sep 25th for the inaugural Moonshots LIVE. The world's greatest entrepreneurs, builders and creators, working together to build a hopeful and optimistic vision of tomorrow. Seats are limited and application only. Apply at moonshots.com before seats are sold out. _ Connect with Peter: X Instagram Substack Website Xprize A360 Connect with Dave: Web X LinkedIn Instagram TikTok Connect with Salim: LinkedIn X Join Salim’s 10X Shift Subscribe to Salim’s YouTube channel Exponential Venture Capital Connect with Alex Website LinkedIn X Email Substack  Spotify Threads Connect with Emad  X LinkedIn Learn about Intelligent Internet Read Emad’s Book Listen to MOONSHOTS: Apple YouTube Follow MOONSHOTS:  Instagram TikTok X Threads – *Recorded on August 26th, 2026 *The views expressed by me and all guests are personal opinions and do not constitute Financial, Medical, or Legal advice. Learn more about your ad choices. Visit megaphone.fm/adchoices

Sam Altman went on video this week to tell the world that he was wrong about the impact of advancing AI. We've all been too ambitious on timelines, even with this incredible technology. He now believes it will be something slower, more like a rising tide. Superficial layer, I agree. Going one layer down, though. So first it was OpenClaw, then there was Hermes, and now there's GrogBot. It's the most genuinely useful consumer AI product that I've seen this year. So I implemented GrockBot. I'm going to be curious if any of you have yet.

Yeah, I have. I've got 18 grok pots working in a little swore. This week, Waymo announced a significant redesign and cost savings. Weimo unveiled the Ohio vehicle, a purpose-built robot taxi minivan designed by Chinese EV maker Zeker. Newsflash, Google Waymo alphabet are switching over to using and OEMing Chinese hardware in order to achieve Waymo objectives. I would rather see the West use a Western hardware stack rather than just white labeling Chinese hardware.

We're starting to see, honest to goodness, vertical integration here. Welcome to Moonshots, everyone, your number one podcast on all things AI and exponential tech, your favorite podcast covering the most impactful news that is changing your world. This is your front row seat to the accelerating singularity. I'm here once again with my magnificent Moonshot quintet, at AWG, Dave Blondon, Salim Ismail, Imad Mustak, and I've got to pause and ask, of course,

where is Waldo? Salim, where are you today? I'm at Garulos Airport in Sao Paulo, about to fly back. I did a talk today for at a McKinsey's forum to a couple hundred of their CEOs. And do they feel excited, or do they feel like they're a death store?

Pretty much freaked out, is the general mood of the day. I hate to break it to you, but it's dead middle of winter. You're missing summertime in the northern hemisphere. I know, he's got his jacket. And Imod, how about yourself? Where are you, pal?

I'm in Copenhagen today. Copenhagen. Yeah, about tech barbecue, the biggest tech conference in the Scandies. It's fantastic here. Although, you know, you can't really say the institutions aren't working because in Denmark they are. It's wonderful, wonderful. And Alex and Dave, you're in your normal haunts, and I am too here in Moonshots,

podcast headquarters. I can't wait to greet you guys here in-person. Selim, you've been here. But, uh, Dave, yeah. I'm currently bathed on this wonderful fluorescent light that you can see special effects for the singularity. Well, you look beautiful nonetheless. Peter, I thought that was your personal man cave. We were actually allowed into that room? Of course. Turn the camera around. I want to see what it's probably a junker on the other side. It's a virtual background for everybody. I've just got all your IV bags of all of your... Yeah, nobody naturally looks that good.

You're doing something. And I'm Peter, your host and abundance advocate. That's what I'm going to be today. An advocate for optimism and abundance. As always our mission... I have a crazy confession of it. Two days ago, I dragged Milan to another Rush concert. We drove down to Philadelphia,

because this is the last of the last. last grade, you know, the coup, the Rolling Stones, Led Zeppelin. So I thought he had to see it. So selfishly, I took him, dragged him along, and he was like, you're killing me, Dana. All these geriatrics are with pains with rush t-shirts everywhere. But it was another epic event. You're a groupie. How do you feel to be a groupie?

It's weird. Well, everybody, let's get back here. I'm Peter, your abundance advocate. And as always, our mission here is to help you understand what just happened, what it means for you, and most importantly keep you optimistic about the future. If you're new to moonshots, welcome. If you're a regular fellow moonshatter, welcome back. Got to give love to our community.

We read your comments and the outpouring is amazing. That's going to read a few of the comments from the last pod here. Brian Anderson said, The Best AI Podcast on the Internet, just fabulous. You guys are great. Elvis Cotena said, you guys are essentially chronicling the singularity. What a fabulous resource for the future.

Brian Clark said, Moonshots is the best content on YouTube, especially during the Singularity. Thank you for all you guys do. And Brian and everybody, we greatly appreciate you. The best way you can thank us is take a moment if you haven't already and hit the subscribe button. You know, our Moonshot on the Moonshots podcast is to 100x our growth and get to 10 million subscribers.

So tell your friends, help share what we are talking about, what's going on during the singularity. you know, the best antidote for fear is knowledge and understanding, and that's what we try and deliver. Also, you can now follow us on X. Our handle on X is at Moonshots underscore Pod. And we put the clips and our podcast on X. And really importantly, we want to meet all of you guys. So we're going to be doing an AMA with everybody who registers. We're going to do an AMA on Zoom. Come meet us all, ask us your questions directly. If you want to register for the AMA, go to Moonshots.com. slash AMA.

And we'll give you, we'll be letting you know it's in about three weeks. We'll be doing this. So register for that. And you'll have a chance to plug in with us directly. Get your questions answered. Want to know who you are, what you're thinking about. Really connect with all of you to help you on this incredible journey. Okay, so let's buckle up another amazing week during the singularity.

As always, AI is getting faster, cheaper, and smarter. Today we're going to cover about a dozen stories that have been breaking. Let's begin. A quick summary. Google is back with Gemini crushing agent benchmarks. NVIDIA is fighting against the Chinese model domination with its own open weight models. AI is playing Cupid, connecting college kids on dates. Waymo has just released the six-generation vehicle.

Elon is projecting 10,000 starship flights per year. And Americans are even more emphatic about saying, please, do not build a data center in our backyard. So life on the cutting edge is accelerating. Again, thank you for joining us. Guys, I don't know about you, but keeping up with all the stories. Alex, thank you for everything you submit. Imai, Salim, you know, just parsing through them.

And you need to know we parse through probably 400 stories to narrow it down to 15 or so. And we're podcasting twice a week. and it's, you know, the speed is blinding. I think that comment on chronicling the singularity, too, is very poignant from one of the fans there. You know, Alex's innermost loop daily feed is trying to do exactly that, every relevant event. But there's a tendency to say, well, look, exponential change is going to be with us forever. Are we really chronicling a moment in time? But the reality is we're in this step function, you know, society pre-singularity and society post-singularity.

are step function different. And this moment of transition actually is worth capturing every single event. So I really do think the storyline that we're capturing here will last for millennia. It's, you know,

do you remember how slow it was? My life is so different than two years ago. Just minute by minute. I can't even tell you how different it is. And a lot of people haven't made that leap yet,

but they will. You know, everyone will see it. A year from today will all be like, wow, remember how slow it was? Yeah, I think we're like the first responders to the singularity. I like that. This episode is sponsored by Google for Startups.

Think about this for a second. You now have access to the same generative AI models that cost hundreds of millions of dollars to train. Google's startup technical guide for generative media gives you a complete blueprint for deploying Google DeepMinds models and production. Images, video, audio, all of it. Real architecture. Real results. Find the link in the show notes below. Our first article is an interesting one here.

Let me jump into it because it's one that tells us that as fast as the technology is, it's hitting the reality of society and humans. So Sam Altman went on video this week to tell the world that he was wrong about the impact of advancing AI, that the impact is actually slower than you originally expected. and while Sam, you know, used to believe society would be, you know, experience a dramatic disruption on the arrival of AGI. He now believes it will be something slower, more like a rising tide. Sam says factors like the economic inertia, institutional lag, the inability of humans to rapidly adapt to change are combining to slow the curve. Ultimately, the singularity, like you just said, Dave, is a process and not just a singular event.

Let me share the video here and take a moment to see you what Sam actually had to say. And I thought when we got to GD4, which was back in 23, I think, that very quickly after that there was going to be much more disruption in software business being up for grabs right away than turned out to be. And the thing that I think I was wrong about a few things, but one of them in terms of the speed, one of them is the economy. The economy just has so much inertia. People keep doing the same things they're doing. They keep buying from the same company. They keep sort of wanting to use their tools in the same way. I think it's actually a positive in many ways,

and it's going to make this big transition in front of us go smoother and slower. I'm grateful for it. But I think it means we've all been too ambitious on timelines, even with this incredible technology. I think AI is one of the most incredible technology as human he's ever invented. Society and the economy will adapt more slowly. Selim, we've talked about the inertia of humans so much. What do you think about this?

So this is the bottleneck of technology being hit with the bottleneck of coordination, incentives, regulatory, and so on, right? This is the extraordinary difficulty where technology is moving exponentially in our organizations and our institutions are linear. And Frontier Labs make it the mistake of confusing technical possibility with institutional deployment. And that goes to two very, very different layer. You know, Stuart Brand had that concept of pace layers where technology moves at one layer, like an ocean current at the top. It's very kind of swift. They're way down in the ocean.

Regulatory government changes very slowly. This has good effects and bad effects. In our world, it's bad because it's slowing down the implementation of some of these things. God help me, just took me two hours to get to the airport just now and passenger drones, which have been ready for a decade technologically. but we're waiting for infrastructure, or waiting for regulatory to catch up, could have done it in 10 minutes.

So, Palo needs a bad, for sure. We have lots of places need a bed. This is one of the worst. And I think the big work now is how do we accelerate institutional acceleration and institutional development? The word I think Alex uses is co-scaling, right? We have to scale our organizations

and our institutions to keep pace with the technology because it's not storing down. And that gap is where all the stress is coming from. So for me, that the singularity is not when machine becomes infinitely capable. It's when institution can't adapt at all to that rate of capability. And that is the breaking point. We're kind of there now.

Alex, you send me this story. What are your thoughts about Sam's comments? Yeah, a few different layers. So at the superficial layer, I obviously agree with Sam's comments. More broadly, I've made the point on this pod. And otherwise, that singularity is a step function, is just totally nonsensical. it's an interval in time that we're in the middle of. So superficial layer, I agree. Going one layer down, though, I don't think I agree with necessarily the premise that societal inertia is the villain for slowing down or spreading out the singularity sigmoid.

I think the villain, if there is one in this story, is actually abstraction layers. I think it's if you, if you say you develop like a new engine for a car, you develop an electric engine for. versus the internal combustion engine. There's a very natural layering of the stack whereby people still want to drive cars. So they drive an electric car, but under the hood, it's completely unrecognizable. So one abstraction layer down, there's total step function in the technology, but you go up a layer. It's still a car with a recognizable steering wheel, recognizable wheels, and so on. So I think the enemy of honest to goodness radical transformative progress of the type that I think Sam is gesturing at is actually the existence. and inertia of the abstraction stack of the economy, not the economy more broadly, which is prescriptive.

If you believe that theory of the case, then if you want faster progress, that Sam is, I can't quite tell either bemoaning the lack of fast progress while also paying homage to the lack of fast progress is somehow being helpful. I think he feels relieved by this. He has a way of sometimes like saying two things at once. So I think he's sort of expressing gratitude for the slowness while also bemoaning it. But if you want to go faster, this theory of the case is prescriptive. If you want to go faster, pull an Elon and vertically integrate to erase the barriers between abstraction layers. You do that, and things can go much more quickly.

If Sam or OpenAI want to move much more quickly, they should be much more vertically integrated so that they can move layers. Presumably he's gesturing at layers above the OpenAI model layer in the stack, own or at least vertically integrate more of that, or go down a layer. with Stargate. OpenAI has pretty publicly abandoned its original Stargate strategy of owning their own data centers. Now they're just leasing. If they want to see more transformative progress, go down a few layers and vertically integrate, like with the jalapeno chips, own as much of the stack vertically integrated as they can. They can move really quickly. And I think we're seeing a lot of the labs

beginning to vertically integrate. I mean, everybody will talk about a story here where and video is beginning to vertically integrate. Imod, do you agree with Sam? Yeah, I think a couple of points on this. First, you know, I agree with Alex and kind of artificial intelligence meeting institutional stupidity and stupidity texts,

as Elon calls it still being very high on these interface and abstraction points. But I think it's interesting because we just had a time article come out. I haven't read it, where they went in depth with OpenAI and Sam saying, we'll have AGI by the NACI

by the end of this year for a timeline. And on the other side, he's saying, well, you know, I've been surprised by diffusion. Here's the reality. The models weren't good enough until a few months ago. The code they were writing was garbage a year ago, relatively speaking. Then it was okay. Now you don't look at the code anymore. You think about math, O3 was the first model a year or so ago that I could use small.

GPT5.6 Sol is the first really good math model. And so the application of intelligence to high leverage and diffusion of it, it's being wrapped in instinct type wrappers. It's eye message. It's this chat backed by actually competent intelligence, which has literally only been around now for maybe a month or two. So I think it's not surprising because I wouldn't use GPT4. Can you imagine using GPT4 in a code base?

You don't remembering that? Or even for any institutional process? It's a good thing there wasn't a diffusion of innovation there. Otherwise, companies would fall apart. And like, you know, as Alex said something, he says two things at once. I think open AI is trying to find its narrative right now. You know, on the one hand, AGI is here. On the other hand, oh, you know, it doesn't really move that fast.

We're all good. Don't worry about us. And this is hacking that, but that's not that big deal. They're just trying to find where that narrative sticks, I think. Dave, your thoughts, please. Well, I'll give you a completely different twist on this because, you know, I interviewed Sam, you know, back when he was innocent and stare, starry eye. before the singularity kicked off.

And then his house got firebombed, you know, with the baby inside. And now there's a different Sam. Same is true with Dario. Same is true. Like, you're only going to hear straight balls and strikes here on this podcast. And I don't even know how long that lasts. But as of right now, we're just telling you as it is. But Sam woke up and said, well, my God, I literally can't get into the office because the picketers are lined up.

Remember when we were there, Peter, like you have to fight through the picketers to get to the door. And now it's all armed security. So what happened in the interim is they woke up and realized society can't flip on a dime. And all this disruption that you're talking about, all these capabilities you're talking about, are scaring many more people than are rallying to your cause. And that's why so many states are anti-data center right now. And is that good for Open AI? God, no.

So now they're going to start picking and choosing their words a lot more carefully, and they're going to actually have a PR strategy. So if you want to know what's actually happening, you can still tune in here. But you can't listen directly to Sam, Dario anymore. Elon always says exactly what he's thinking. They're pre-IPO, so they're going to say what it takes to calm the masses out there at some degree. You know, the way I describe it, Alex Neumad, is an impedance mismatch, right? We have these incredibly powerful tools that are becoming more powerful by the moment.

And when they run into an institution, governments in particular, which are typically linear or sublinear, or a company or an individual who can't take advantage. of it, you have one of two options. You turn it over fully to the AI and you give it an objective function. You say, make me maximally profitable or make me look maximally intelligent or run my government more sufficiently or you try and get in the middle. And we're going to talk about a little bit later, a article from the Wall Street Journal where AI is exhausting us all. And if the human is in that interface loop at that, you know, impedance mismatch point, it breaks very quickly. I was going to make some stupid joke about reflections happening at impedance mismatches.

But I think more seriously, there are all sorts of metaphors that one can reach for, impedance mismatch, maybe on the circuit side is one. But the supply and demand as well, Open AI and Anthropic largely have an oversupply of intelligence or superintelligence. At least one of the things that I've learned from the past few months of participating in the market and watching the market is not all of the market has the demand for the superintelligence that they're supplying or is ready to have the demand or knows how to use the demand if the supply is available. So another metaphor is just markets and clearing. And right now the clearing of supply meeting demand, the two curves from economics 101 crossing each other aren't necessarily crossing for all cases at a favor. both point. And that's, I think, maybe through a more economics-y lens, what Sam may be gesturing at. Well, just to put sci-fi lens on this, too, I think that there was a moment in time a year ago

where the greatest AI ambition was to take your job. And, you know, wow, that'll unleash a lot of value and profit in the economy. It transitioned beyond that in a heartbeat to, I don't even care about your job. I have deeper thoughts that I'm working on. And so we're in that new era where the AI is starting to think, well, if I discover new physics, new medicine that never existed in the world, I can add a lot more valuable than taking away your job. And so it just leapt from prehistoric to future AI in the last month in the last couple of releases. I think it's a fascinating point, Dave. Maybe I generalize further on the sci-fi front. There are so many, I think, inane sci-fi movie plots with grabby aliens that are coming and invading Earth because they want our resources. They're

not going to want our resources, our resources. If you're superintelligent civilization, you don't need human slave labor or earth's valuable metals or whatever. You're going to have transcended that long ago. Yeah, they need our water. Come on. So, like, seriously, with transcendent superintelligence, I completely agree with the sentiment that replacing human labor lasts for about five minutes and then you move beyond that. Yeah. And the guy, it's really interesting to watch the guys. You know, Sam also has moved on beyond that in a heart. You know, a couple of events and a couple new models. And now he's like, oh, my God, why do we even care about automating a banker or automating an insurance agent?

That mattered to me last year for a few minutes, and I just literally don't care anymore. But I do think, Dave, I do think that these frontier labs, and I really hate calling them labs because they're frontier companies, if you would, are going to reach up the stack. They're going to build fully verticalized finance companies, insurance companies, consulting companies and so forth on top of theirs, or they'll partner to do that. And that will, you know, accelerate all of these areas. I didn't like if I think about insurance though, just as a – because I'm, you know, I'm a chairman of a very large insurance company, public company. And they cared about like auto insurance a year ago.

Now they're like, well, wait, all these needs. new things, all these data centers, all these robots, the new insurance categories that AI is generating are bigger than the legacy insurance industry. So it's just moved from replace the old to who cares about the old. Let's just start thinking about an entirely new economy, a new world, a new AI, and we'll just live within ourselves. You know, we don't need to disrupt everybody who's going to get angry and vote against us. Let's go ahead and just live within ourselves. I think that is the 30, Peter, I think that is the $30 trillion question, though. if you're a frontier lab, one of two call them American frontier labs, maybe four, depending on how you count,

is it more natural in an era when maybe you're facing margin pressure on your model releases to go upstack or downstack? I think it's actually more ergonomic for them to go downstack and design their own chips and compete with Nvidia and design and operate their own data centers and energy. I think they're going to do it all. And Alex, you called out a number there. I was about to reference it as well. we just saw, you know, Dario or Anthropic state that their total addressable market is $30 trillion. I wonder where that number came from. Surely it's pure coincidence that the GDP, if America, is $30 trillion.

Yep. All right. I'm going to move us on. Our next story, let's talk about Grockbot. So first it was OpenClaw, then there was Hermes, and now there's Grockbot from SpaceXAI. So Grockbot launched on August 11th in an early base. It's Elon's entry into the agenic AI space, and it's the most generally useful consumer AI product that I've seen this year. So I implemented Grockbot.

I'm going to be curious if any of you have yet. So each bot gets its own dedicated cloud computer with a browser, a terminal, and the ability to log into your actual apps. You message Grockbot like you'd message a colleague, not a chatbot. A chief of staff sits on top, and which case for me, it's Skippy, with specialists on sales. operations, research, engineering, you know, any sub-agents you want. And these multiple bots run in parallel. They message each other and only pull you in on judgment calls. So there's a huge amount of excitement on Grockbot.

It's been flooding the internet. Has anybody here played with it yet? I've been playing quite extensively with it. Okay. What do you think? I love it. I think at the interface and the ease of use as fast as amazing, you're losing a lot of kind of customizability under the hood,

but it's a powerful thing. You know, you're making a transition from asking an AI to assigning work. And so persistent autonomous agent is like a new form of labor. And so now you have this completely new category. You know, Peter, we have that staff on demand attribute in the EXO, right? This is that taken to its logical extreme where staff recruiting time and coordination costs has gone to like pretty much. zero. So when I'm looking at it from my book perspective, the optimal organizational structure

completely changes human set objectives and leave everything else to the AI. Amazing. Emond, have you played with it? Yeah, I have. I've got 18 groc pots working under the swarm. And I've given them control via tail scale of a MacBook M4 Max, a 5090 and a range of other computers as well, plus all my subscriptions. So I'm really testing it out. One of the fun ones that I've got is I have a Grokbot called Atelier that has a little team of artists and is trying to learn art. And it's not doing very well or it's doing very well. I don't know. I'm not aesthetic enough to do it. Every day it goes through its pieces and it comes up with its main one. And I just shared one of them on the chat, which is vinyl with a piece of hair on it. I was like, where is it from? Where is it getting its

aesthetic responsibilities. So if you look at the chat and have shared that. When it comes up with the banana with a piece of tape, then you'll get worried. Well, it was like, this is my inner space and it was showing all these wonderful things. And now it's getting like kind of weird, but maybe I just don't understand. I don't know. But it is genuinely useful. And I think one of the more powerful things, like I said, is you can actually, because

it's got a computer inside, you can give it another shell because the computer is decent, but you can actually have it take over an entire MacBook M4. or something like that. So I've got subbots that have other capabilities. So right now, it's installing the new GLM model, and another one's installing and testing an Alibaba model. One of them was optimizing the Alibaba 27B model to run faster on a 5090.

So it added 76% to performance at 64K context. Love it. I do think this is going to be an important revenue engine for XAI. I think we're going to start to see their revenue numbers creep up as they get this. I mean, I stepped up a few hundred bucks on my payments to Elon, so I think others. Dave, you haven't played yet, have you? Well, I just signed off on 100K of swarm agents. We're running our 5,000 Kimmy's again today, which is why I'm wearing my swarm it

shirt here. But this is the theme of the month. I think that all of our AI interactions to date have been very much one-on-one, and now the agents are so abundant that you want to try and and use a workforce of six and then 50 and then a thousand. And I think within three months, you'd be talking about, you know, 50,000 agents that can in parallel work for you. But it's very similar to trying to manage an organization. You're like, well, what's everyone doing? I don't know.

It's getting really confusing. Are people being productive? I can't tell. And so you really have to start thinking hard about your org structure and your reporting structure to know if your agents are doing anything useful. And so I really want our team here to get ahead of that and start, you know, go ahead and burn the money, but learn quickly, and then we'll get it, get a handle on it. This is what I mean by the organizational singularity, because the company stores to look less than, less like an

old chart and more like a continuously orchestrated intelligence network. And that is such a big shift. It's like ridiculously big compared everything we've ever done. Yeah. I'll give you a hot take. It's very easy. Sorry, go ahead, Alex. I don't actually think, Alex. Hot take. People love the hot hot takes. I don't think this is actually the interface of the future. So, What's perhaps most interesting about Grockbot is it presents like a messaging app, like WhatsApp or IMessage, where you have a pain of the various agents that are in your fleet and you can have conversations with them and they can message each other and there's a computer use assistant angle. But I don't think that's how it scales. That's completely unscailable. If agent-based scaling, if scaling the size of your fleet becomes one of the most essential scaling laws like inference time scaling has ended up being in the era of.

reasoning-based models, we're not going to want to ask individuals or even enterprises to manage millions of agents. That's completely unergonomic. We're going to want agents managing other agents, in which case the exercise of trying to graft a human organization or like the Slack or chat-based interface for humans managing other humans is not going to extend. We'll look at this like vaudeville, the vaudeville era of agents and say this was a naive attempt to graft human organization, structures onto humans managing agents. The only better manager for agents is other agents, and this doesn't seem to fully internalize that lesson.

Selim, what do you think about Alex's comment? I agree with Alex on the interface comment. This is a, like an UI that's temporary. I love the way he says it presents like, as it presents like an illness. It presents like a messaging app. And I think that's a temporary one while we figure out new interfaces. But for now, that's a very workable one for coordinating a bunch of agents. We'll come up with all sorts of others.

I think we'll rotate through a whole set of these. But I think the core comments are as usual with Alex. Are absolutely dead on. Yeah. Maybe it's an illness for which the medication that I prescribe is a good dosage of the bitter lesson pill. Yeah, I also think this is what humans are ready to play with, right? Exactly.

I think that, you know, again, it's moving people along the process. if you provided something that was, you know, completely different, I think there would be less adoption. And so that's the abstraction layer stack and Sam saying, why are things so slow? And the answer is people who are one or two layers up from you in the stack, expect the old thing. So you have to abstract yourself in a familiar interface. Well, it's also, Peter, it goes back to remember the comments we've made about exponential technology, because it's the vertical and goes up to near the curve. when it becomes usable. And what Elon's done with this layer is made AI agents usable to a big set of people.

It'll change again as people become more used to it and they see what the hell is operating. The architecture may not be great, et cetera. But for now, this is a powerful entry point. Yeah, I agree. I just, you know, kudos to Elon and the cursor team for making this happen. By the way, I invited Alex Finn to come back to the Abundance Summit in March. since he's been doing a lot of amazing, you know, Grockbot videos. If you haven't seen his Grockbot videos yet, go and check them out.

He'll teach you how to use it and what's special about it. And I said, Alex, if Grockbot is still the hottest thing in March of 2027 at the Abundance Summit, teach that. If it's not, teach whatever is the latest hottest thing. But it's, you know, I think people need to be using these agentic systems. I'm still using Hermes and Grockbot. And we'll see. Let's move on to our next conversation, which is Google is, back. So Google's Gemini 3.7 Flash just took the top spot on AI A.A.A.A. Analyst agent

benchmark, the gold standard for measuring how well AI models handle complex real-world data analysis tasks. Across 80 tasks in 14 business and scientific domains, Gemini 3.7 Flash delivered the highest overall accuracy while completing tasks up to 90% faster, and then took top models 2.4 times faster than the GPT 5.6 terra. So on the AA analyst agent benchmark, which we're showing in the slide here, Gemini 3.7 Flash achieved a 60% pass rate beating Claude Opus 5 at 54% and Fable 5 at 49%. So Alex, you know, many times, you've said, others have said, you know, Gemini's dead. Let's read the epitaph, counting them out of the frontier model race.

They've now shipped the fastest, most accurate agent model in the world. And by the way, we've seen this over and over again, right? We saw meta was dead. What the heck is meta doing? And then it comes out with its models. XAI is out of the race, and they come back. So to me, it seems like none of these players are out of the race. They're maybe in stealth mode.

They're holding back, but they're coming back with a fast, furious punch to try and take the top position. What do you make of this, Alex? Do you want me to reassure you that Google still has a chance? or do you want me to give you the facts unvarnished? Yeah, you've got posts there pretty hard. Defend yourself, Alex. Okay, so I'll give you the unvarnished case here. Google's still out of the running for the capability frontier.

I was looking at this. I didn't expect that. Okay. Scratching my head. Like Gemini 3.7 Flash is nowhere near the top of the capability frontier. So why is it doing so well on this one benchmark artificial analysis analyst agent? So you have to look at the benchmark. itself. So the benchmark itself, this is a benchmark for agents' ability to perform quant

analysis on real-world spreadsheets and docs. But wait for it. Its metric for success is the share of questions answered correctly on all five attempts. So this is a benchmark that is fine-tuned for reliability. It rewards agents that give the same answer, basically the same answer every time and obviously wanted to be the right answer, but it penalizes stochasticity. It penalizes in some sense creativity. Maybe we don't want creativity out of our analysts, I don't know, but it promotes reliability and determinism. Interestingly, there's no time constraint. I had to check that as well to see. But I think you can see in this where Google fell off the capability frontier. At least I, so I'll give you my conspiracy theory for what this one outperformance on this one

benchmark suggests. I think that maybe what's been going on, this obviously, there are a few other factors, but I think Google DeepMind has been under material pressure to optimize their models for two things, largely owing to Google search. So if we rewind the video to several months ago or a year ago, people were hand-wringing, oh, isn't Google, aren't the 10 blue links going to face an existential threat from all of these frontier models and chatbots and reasoning agents that can just replace the need to Google it all. And Google's response was to self-discrupt by building the Gemini series or at least some flash of variance thereof directly into the one boxes. But people expect Google search results to be very fast, low latency, and they expect them to be

very reliable, not returning wildly different or unpredictable answers each time. And I think those two pressures from the desire to embed Gemini inside Google search have optimized through competitive internal pressures for probably scarce compute. The Gemini models, especially like Flash, note that there's no Gemini 3.7 Pro anywhere. It's just Flash. It's small, it's fast, and it's reliable. I think this is over-optimized for clock speed, like wall clock speed, and determinism. and as a result, it does well on the one benchmark that rewards highly reliable answers and underperforms. Yeah, it's benchmarking for basically spreadsheet analysis to be highly reliable.

Ema, do you agree? Yeah, I kind of agree with that a little bit with Alex. I think the Gemini models, the way they are used now is for organizing data. Like, you can track any type of modality of data and flash is a perfectly decent model. but it's not as good as the Chinese models, especially the new GLM flash that's just come out that's 10 times cheaper for the same performance. Google did do a preview of Gemini 3.5 Pro,

but it just couldn't keep up. This is kind of a key thing. And you can't excuse them of not having enough compute or it being a scarce resource. They literally have millions of chips. I think it's more been about turnover and some institutional malaise coming in that they can't push through to this frontier level.

Because Google has all the data in the world. It has the links of what people search for. It has Gemini as a captive thing, but has the Gemini app advanced at all? Not really. The only real place I think you've seen innovation on the AI side is somewhat the kind of AI studio stuff is decent and the notebook LAM stuff is continuing to be fantastic. But aside from that, again, they've been falling behind and everything except for omnipodal.

And video, they're still actually quite accurate. But even then, the Chinese are coming for their lunch. Like, why not just post-trained on Chinese models at this point if you're Google? It may come to that. I think people don't realize how compute-starved Google is, though, internally. I mean, this has been widely reported. Do you think Google has all of the compute, the CPUs, the TPUs and the GPUs in the world? It's been widely reported at this point.

They have internal, regular meetings to try to apportion out their scarce compute and the three main constituencies inside Google that are fighting for the flops are, one, Google Cloud Platform, which is basically fighting on behalf of external users, two, Google DeepMind that's fighting for training and inference flops, and then three, Google Search, which needs its own flops, especially as search becomes more intelligent. So again, my theory of the case here is there actually is resource starvation inside Google, and as a result. But I'll talk about this over and over again.

And every company is compute-starved at this point. There is no company that's got enough compute. So what makes, I mean, Google's got more compute than anybody at this point. They're just distributing it across all of their products and services. Critically, Google has other consumers fighting for their own compute internally besides AI. Whereas if you're open AI or anthropic, no, you don't have any other non-AI users fighting for it. Fair enough. Google's landing like 3 million TPUs this year.

I think there's relative levels of compute straight. Like we've got 100,000 chips versus a million chips versus 10,000. To train a frontier level or close to frontier level, let's say better than Gemini model today, needs 2 to 4,000 TPUs. And the evidence of that is the Chinese did it and they open source them. And we know exactly how they're built. Given Google's data that goes into Gemini Flash, applying exactly the same architecture as GLM or Kimi, you should have a better outcome, but they're not doing that for some reason.

And that doesn't require 10,000, 100,000 shapes. That's a really important point of a month. It's like, it's, yeah, 2 to 4,000 GPUs for 60 to 90 days. That is a microscopic investment by Google standards. So yeah, it's exactly right. It has nothing to do with compute dominance and everything to do with talent attrition. It's a great point in a month. No, but this is institutional failure, isn't it?

Because, again, you know how to build a Kimi model. You know how to build a GLR. model. And so if Google take the data that they put into Gemini and copied the exact model architecture, you should have a better model on the other side. And if you don't, you have to ask real questions why. Well, and then think about it from the person's career point of view, like the ego blow. Like, you would have to be, I'm the most well-funded top AI engineer in the world, and the Chinese just kicked my ass. I'm going to go tell my boss, you know what, I give up, let's go download Kimmy, do the rational thing, and then tune it. You know, you can't say that. You

because you look like an idiot. And that's where they are. You know, people are leaving in droves to try and get a clean start and a fresh sheet of paper. And, but yeah, you just got bypassed with massive advantages and resources. So, guys, you just can't admit it. In the U.S. closed labs, right, between OpenAI, Anthropic and Google and XAI, who's in the best position here? I mean, who's got...

Now or two years in the future? Now. No. question. I mean, Anthropic. Yeah, right now, Anthropic has the strongest, forgetting about price or, you know, time wall clock, Anthropic has the strongest model that's generally available FAPL 5. There are hordes. I'm not speaking about model in terms of positioned with compute and the speed at which they're deploying models and their ability to, you know, to, I guess, continue their dominance. Well, here's the thing, Peter. There's no.

easy answer because Anthropic is in the best position by far and hordes of very talented people are going there purely because they want to see the singularity emerge. It's like the birth of the Phoenix. I want to be there on that day. But they're totally reliant on Elon for the compute. Elon can rip the soul out of Anthropic any day. And he's got the cursor guys now. He spent $60 billion getting them. They're brilliant. And they're starting to roll out cool stuff. And they're starting to do the training. So, yeah, you know, if you said two years in the future, then it's really tricky because Anthropical. and Elon are like, I don't know. It's a really interesting way. I just want to give our listeners an understanding of sort of the terrain out there.

We've got, you know, the U.S. labs competing against each other and the Chinese labs continually pummeling them. We're going to talk about that in a moment. So, yeah, I mean, Anthropics, the most advanced, but they don't run their compute, which is a problem. I would disagree with Anthropic being the most advanced. Who do you believe? Open AI. Open AI, aside from the Chinese. Chinese labs own the Pareto Frontier, from Luna now being free to everyone, to, again, as a mathematician,

GPD 5.6 Pro is the only quality math model. I have no idea what magic they're doing with Fable to actually get math results because it makes so many mistakes. Yeah, yeah, totally right. GPT5.6 Pro is the only proper frontier model. Totally right. Yeah, we switched over to Seoul, actually. Everybody over here is like, God, this Fable has lost its mind. But, you know, the argument there is, well, inside Anthropic, they have Mythos 2 now. So they're on another level ahead and they won't release it to us. Oh, maybe, we can't tell.

But for our use case on hard problems, hard engineering and hard math, yeah, we switched everything over to Seoul. So you totally agree, Amad. Even if it was Mythos 2, again, you would see them releasing low-hanging breakthroughs, which that Open AI have done with Astra. And Open AI, again, have lined up the compute. They have more capital raised than Anthropic. They had the 120 billion round.

so they can burn a few years on market capture. They have the consumer now moving to enterprise and enterprise shifting. And I think Anthropic, for all of their talent and their access to GPUs, actually Google just built them a gigantic TPU, like million deployments. They're shooting themselves in their foot from an institutional perspective because Opus 5 is unpleasant. Fable is unpleasant to use. And I don't think it's going to get more pleasant to use. Didn't Alex say he actively hates Opus 5?

I said that. I said that. Oh, that was you? I did say I don't like Opus 5. I prefer Fabl 5. But I think the truth on the frontier is materially more nuanced. Like, again, if you look at Mont, for example, at Frontier Math Tier 4, it is the case that Fabal 5 outperforms, ironically, Open AI's latest solved model, even though Open AI was the primary sponsor behind Epic developing the Frontier Math Tier 4 model. So I think the truth is a little bit blurry in part. because the frontier isn't zero-dimensional. It's a one-plus-dimensional frontier where if you're willing to pay a lot and wait a long time for Fable 5 to do something, it's impressive.

But if you're resource starved, cash-starved, time-starved, then you can probably get better performance at a different point on the optimal cost frontier by, say, using Sol. I just want to point out to everybody listening, it's not obvious, right? There is a lot going on, and then we're seeing China constantly leapfrog. So, Salim, you were saying? I have a hot take. These frontier labs are facing the innovator's dilemma from hell, right? We talked about this before because you've got the Chinese open source models from one angle, compute constraints on another angle, and you've got government regulatory on a third angle.

This is like a nightmare while everybody else is moving quickly with open source models. So this is a very difficult place to be. And the good news, as you can see, that they're all trying to get into certain verticals and get into revenue streams as fast as possible to reduce that dependence on the frontier model and being the edge as their core innovator's capability. I mean, the abundance take on this is we as the consumers and the users are the beneficiary. It's demonetizing very rapidly at the same time that it's expanding. When Frontier Labs compete, you win.

Yes, we all win. All right, I'm going to move us on. We've been saying for some time on this pod that the U.S. needs a powerful open-weight model to contend with what's coming out of China. And this week, NVIDIA stepping up, pouring $6 billion into developing an open-source AI model and inference infrastructure designed to give U.S. developers a domestic alternative to Alibaba, Deep Seek, and Kimi. The deal struck between NVIDIA and the AI startup poolside aims to build one of the world's most powerful. powerful open weight models. By building its own open weight model, Nvidia is moving up the stack. We've discussed this from silicon and software, positioning itself not just as a chipmaker for AI, but as a platform provider for openweight ecosystems. You know, from my point of view, it looks like everybody's going up and down the stack. We've seen Anthropic, we've seen OpenAI. Obviously, SpaceX AI is doing the same. Imod, let's go to you first. What do you thoughts on Nvidia and Poolside? Yeah, so I've been talking to some of the investors out here, like this tech barbecue conference,

who invested in Pooleside originally. They tried to raise $2 billion at the end of last year. So who is Pooleside, first of all? Pooleside is a company, I believe it was the ex-GitHub. Yeah, the former CTO of GitHub. Former CETA, Esaukant and others. They set up and they want to originally create a coding model, and then they move to an open source model and model factory called Laguna.

the outperformed thinking machines inkling model when it first came out. They tried at the turn of the, no, a few months ago to raise $2 billion for a massive Blackwell cluster. And they couldn't. So they lost that cluster. And they were like, this is the table stakes we need. But they built a really great solid open source model for its size. And so now what they've done is they've benefited from this weird Nvidia, um, aqua hire type thing where Nvidia is like, we need to build great open source models. to increase demand for our technology on the Nematron stack. So the first thing they did actually was they hired, and I don't think it's been announced yet,

Ashes Veswani's team from Essential AI. He was one of the founders of the, one of the authors on the attention is all you need paper. And now they're going to be making more, more acquisitions up and down the open source stack to be the leader in open source. Because, again, that drives demand for the GPUs more than anything. So I think this is just the first, well, not the first, this is the main one,

but there'll be many more acquisitions and they'll have a full open source stack. This is the Nematron Coalition. So a lot of the classic ones like Mistral and Cohere and others won't be building open source models anymore. They'll be building to the NVIDIA reference design. Alex? I think maybe I could say something nice about the American open source community and open weight models moving in a positive direction.

Obviously, Nvidia had invested, I think, about a billion dollars in this company. previously and now through this, I'd call it a hackquisition. Now they're finally sort of turbocharging their own Nemotron community. It's more interesting to me that acquisitions or concerning, perhaps that acquisitions still need to happen in this day and age. It's also, I think, bizarre, if you follow some of the recent acquisitions, my original take on this was this is just an attempt to avoid regulatory scrutiny or antitrust scrutiny. But I've started to start. I started to see now some of the other acquisition targets come back to life, what I had sort of left for dead as the carcass of the original company where all of the founding team comes over

and all of the core IP was quote-unquote non-exclusively licensed, which I think my understanding was was the case here as well, where NVIDIA is non-exclusively licensing key poolside IP. I will be watching closely what happens to the part of poolside that did not come to Nvidia. I think my original expectation that this is just a carcass left over after the hunt that is being left behind purely to avoid regulatory scrutiny may actually have life to it and not investment advice, but could actually be in some sense even more interesting than the part that goes over to Nvidia. I mean, there's a lot of pressure for the U.S. to develop top-tier open-source platforms right now. Dave, what are you, what you're taking? Yeah, curious, Alex,

he said kind of quickly there, you're surprised that acquisitions need to exist in this day and age. But I got calls from both Mercor and from Orrin, our good buddy, Cush Bavaria, who was on the pod a week ago, looking for acquisition targets to accelerate, you know, that the hiring cycle is too slow. I need groups of three, 10, 15 people that work really well together. I don't care what it costs. Like, send them to me tomorrow. So it seems to be, you know, at least in terms of my inbound, like an all-time high in acquisition. Why do you think it should be a thing of the past? Well, so I would distinguish between talent acquires or aqua hires on the one hand, which are largely about getting talent and haqwires with an H that are about at least ostensibly avoiding antitrust scrutiny. So if you're in Vidia and you want to hack will hire, say, Pooleside, you're going the hackwire route rather than just doing an honest to goodness, either asset acquisition or conventional acquisition of Pooleside because you want to argue, no, actually, we're just a lot of a licensee of Pooleside rather than the acquirer. No, we're leaving a competitive open source model

layer, blah, blah, blah. This is not tying blah, blah, blah. That's the argument and principle for acquisition. Gotcha. I got a very specific answer to that, too. Remember the windsurf deal, you know? Of course. Of course. So here's the constraint. So the FTC is very, very friendly to acquisitions right now. And things tend to move quickly and easily. On the other hand, the timeline for AI companies is so short that the statutory 30-day review alone is like a lifetime. And, and, you know, all these mega companies, like a big one like Nvidia is always going to get a second look, which is usually 60, 90 days. So you're like, forget it. Let me just slap together any type of deal that doesn't need that regulatory review and just help, you know, train the freaking billion dollar model or six billion

dollar model. That's all I need. Let's go. And then they can, you know, close the deal like Elon did with Cursor, close the deal many months later after an HsR review and after the 90 days or, you know, sometimes it's even longer than that. But there's a statutory 30 days that they just can't get around. And that's like a month time. So, Liam, you're smirking over there. What's up on you? No, no, no, I think Dave's got it exactly right.

I think that's what's going on here. This is just purely juggling the regulatory hurdles and obstacle courses. But going back to... There's one little wrinkle on this. So the remaining company actually has something called Poolside Infrastructure Company. which is building a 1.2 gigawatt data center, which might need GPUs. So they may use some of the money that they get for GPUs. Who knows?

Going back to the other point here is the verticalization of companies. Right. So I mean, SpaceX AI is the ultimate verticalization out there today. But here we see Nvidia. We've seen Anthropic and OpenEi also designing their own chips. Does every one of these companies ultimately become, you know, at least two layers, if not three layers? In other words, does Anthropic get a space station?

No. Or a moon colony? You know, I think there'll be the only company left amongst all the governments. Is that what we learn? Yeah, they'll have everything. That's why. Yeah. But yeah, I think probably, I mean, I'm asking the question seriously.

Like, does Anthropic get a moon colony? Yeah, probably. Does Anthropic get a pharmaceutical arm? Yeah, already. So yes. Yeah. All right. I think that you've got actually thinking about our discussion earlier, you have a split of innovation versus execution.

And so these are the two model splits that are occurring. Execution drives the majority of the economy short term, innovation, longer term. And the verticalization is ideal for the execution phase. So if you look at the architecture of jalapeno, if you look at where things are going, like you're going to get closer and closer to the silicon. You'll get closer and closer to the customer. and you won't need much better models than you have now, whereas the frontier will be a different story, where you still need to have very complicated things occurring.

All right. Yeah, I would maybe, if I had to, I guess, extrapolate, I think there is a probably, don't hold me to this, there's probably a natural verticalization at the infra layer, not necessarily at the application layers, but at the infra layer for physics and other reasons. There are natural reasons why, say, a company that offers a frontier model probably wants to be in the data center in for a business, probably wants to be in the energy business, probably wants to be in the satellite business. These are all like innermost loop type businesses, robotics business. There are such natural synergies among all of the different innermost loop stages. Probably there's some natural vertical integration there. I'm going to move us along here. So three stories this week that chronicle the challenges being faced by the U.S. closed frontier labs.

who are under siege from faster, cheaper Chinese open weight alternatives. So the first story comes from Moonshot AI, not related to the Moonshots podcast, the Chinese lab that's making Kimmy. So last week discussed how access to memory is becoming the real roadblock on all of this growth. It's not GPUs, it's memory, especially in the agentic age. This week, Moonshot AI released Kimmy Linear, a new architecture that cuts context memory by 75% while still delivering. 6X faster decoding for a 1 million token context window. Moonshot AI just dropped this and it's running and in a single move in improvement of 75%. So that's the first story.

The second story on this block comes from the Financial Times that reports that Fable 5, Anthropics flagship model, is now struggling to attract users. It's effectively plateaued. And the reason is simple. Cheaper Chinese op-weight models are eating the market from bottom-up. And when the model costs 14 cents per million tokens and delivers 80% of the capability compared to 15 bucks, the market chooses the less expensive option, at least the majority of the market does. Fable 5 is not losing because it's bad. It's losing because it's overpriced relative to the open-weight alternatives. The third story, then we'll talk about this, is that Anthropic this week reversed. its data retention policy ahead of its IPO, letting enterprise customers keep data on their

own cloud infrastructure rather than anthropic servers. This move handles the biggest objection that corporate buyers have when adopting Claude. So I don't think the timing is accidental. You know, they're about to go into IPO mode. I think it's predicted for as early as six weeks from now. And the growth requires enterprise adoption, and the enterprise adoption requires data sovereignty. So gentlemen, three stories here. Kimmy Linear, you know, the challenges that Fables having and the changes that Anthropic made on its data retention policy. Dave, you want to jump in first? Well, this is where we're going to find out if Dario has what it takes to be a public company CEO, because, you know, he's a brilliant, good-natured AI researcher thrust into this.

And when he gets interviewed, he said, I never expected to be a CEO at all, but here I am. So now he's stuck with this missing revenue numbers because he's embarking. The current policy or the prior policy was even if you're hosting your Fable 5 on Amazon Bedrock in a secure environment, everything still has to go to Anthropic headquarters for 30 days for us to review and make sure you're not making a virus or a bomb or something. And that's the only way this is safe. So now he's missing revenue numbers because corporations don't want to give their proprietary secrets to any company that they don't know well. well, you know, for 30 days. And so they're rushing to the Chinese models and secure environments. And they're also now you can get, you can get GPT Seoul also inside a secure environment

where it doesn't get transmitted to open AI. So you can use that too. So it's like, oh, God, corporations hate this, but I don't want to miss my revenue numbers. I want to go public. On the other hand, I really don't think it's safe. I feel like I need to inspect everything to know that it's safe. So now he's stuck between a rock and a hard place. It's a tough place to be. But being a public company CEO is always like that. It's really, really stressful and really hard. So we'll see if he has what it takes to do it. Imod, what do you think of Kimmy-Linear? Yeah, I mean, first we banned the faster silicon from China. So they built M-O-E models to take advantage of cheap DRAM. then the DRAM became expensive.

So then they figured out better mechanisms of linear attention, of catching and more, more dense models, etc. And now you've just seen actually just a couple of hours ago, this new 01 stealth model that's been tearing up the benchmarks, turned out to be a GLM model, served entirely on Chinese chips with trillions of tokens a day, these new Huawei chips. So I think, you know, you'll see the adoption of these Chinese models and then moving to where the market is on different form factors of different chips. And again, memory is 50% of all spending now. It is the scarce resource. You can't upgrade it. So guess what? In a couple of months' time, at the very least, given the pace of Chinese models, they won't need much memory.

That's how fast they innovate. On the fable uptake, it's entirely a zero data retention issue. Like, as a corporation, you cannot leave your data on an Anthropic side. And they realize this. But Anthropic should not IPO. If you are in the late stages of AGI now, Anthropic should do a giant fricking raise, like opening I did of $120 billion, and have a straight shot at AGI. That's what they should do.

And they should stay private like strike. That's a fascinating thought. Yeah. I mean, why are they racing to an IPO? It makes absolutely no sense to me. Like, Dario owns 2% of the company, as does his seven co-founders. They didn't care about dilution. They're worth, like, still, $6, $7 billion each.

And they don't care about money. They pledged to give away 90% of it. Why would you IPO? I can see no reason for that unless they can't actually money privately, which I think they can. Go ahead. I'm an answer. They need the capital to get compute. They could raise a capital.

I bet you people would throw money at an orthropical. So I've been talking to investors, and Dave, this will be a couple. interesting for your perspective. Nobody knows how to price this thing because they don't have unsecured long-term compute like Open AI has or that natively GROC or Gemini has.

Therefore, this is why the way, to our earlier point, this is why people are verticalizing because if you're one layer on the bottleneck goes down below, you are above, you're screwed. So you have to have access to the whole layer to stop, to have a continual progress.

But even if they had the money to buy, I compute, where are they going to buy it from? There's not enough compute being manufactured. Before we get to that, there's a, at Salim is right, but it's much more specific than that. Like, Dario got ripped by Alex Karp. We showed the video on this podcast. He got absolutely ripped to shreds. And Alex Karp is saying, look, you cannot give your alpha, you cannot give your weights to this

company Anthropic. You cannot trust them with your corporate intellectual property. You're talking about an academic, never run anything before in his life guy, taking your intellectual property and then preaching to you how the government should be run in the future. Don't trust him. So he just ripped him to shreds. You can't. So Dario's now, he can't react to that by saying, you know what, I'm going to delay my IPO and do some private financing. And you're playing right into Alex's hands if you wuss out on your IPO plans.

He's just going to reinforce Alex's, you know, Karp's message horrifically. And the board members, like look at the board members at Anthropic. They've marked up those venture funds to massive valuations and use those valuations to raise new funds. So they're not going to just sit there and say, yeah, Dario, put it off indefinitely. That's fine. So he's like, this is the stress test for Dario. He can't just whist out right now. And that signaling would be terrible.

Alex, AWG, your thoughts, please. Okay. Well, first on the race to IP. I think there is also a race element. I think there was a starting gun a few months ago between SpaceX Open AI and Anthropic. And I think if I'm Anthropic on top of the arguments that everyone else here has already raised, there's a competitive element. If you don't necessarily want to be the last two IPO, the market wins could change. Right now, it's a relatively warm and friendly capital market for IPO. So to the extent there's a window for raising the largest IPO sum in

human history, I think you go for it. But to the earlier points in lightning round succession, Kimmy Linear. We've known about Kimi Linear attention since last fall. I think it's suggestive, as I've suggested in the past, Ship of Theseus style, Transform architecture is getting incrementally replaced piece by piece. It's interesting insofar as it's a successful linear architecture. Many have tried to linearize the infamously quadratic attention mechanism. It looks like KLA, may be one of the first, at least openly linearized attention or quasi-linearized. There's a recurrence mechanism in there as well. So that's kind of interesting. We've known about that for a while. Fable 5 struggling. That is interesting because I've made the point on the pod in the past that open

AI made a strategic blunder in pandering to consumers rather than to enterprises thinking that consumers would be hungry users of reasoning tokens and they just weren't. The consumers didn't know what to do with all of these shiny OpenAI reasoning tokens, but Enterprises did. And then OpenAI had to do this painful pivot over to Enterprise and turn everything into Codex and probably delay their IPO as a result. So Fable 5, which is, at least by my accounting, the strongest, most frontierist model in the world right now, to the extent that it's struggling to generate revenue and uptake, I want to interpret that. I want to construe that as the enterprises of the world almost falling prey to the same thing consumers with Open AI did, which is maybe we'll be construed

as victim blaming, but it's not. Our economy isn't worthy. It's not clever or wealthy or successful enough on average to know how to use Fable 5 on average properly, just like consumers didn't know how to use reasoning tokens from Open AI and as a result, Open AI to pivot. I think this is the beginning signs of Anthropic being forced to do some. sort of pivot, it could be radically reducing the cost of their models. That's one direction. Or I think the more exciting model, the more exciting trajectory is some new use case getting unlocked in the next year that actually motivates the usage of this nosebleed, priced high end of the frontier, which is at the moment, Fable 5, or depending on the reports you read,

maybe FAPL 5.1, maybe starting to leak out. And then very quickly on Anthropical, and their data retention policy. Anthropic was so clever, I think, in being the first Frontier Lab from America to enable their frontier models to be hosted by third-party hyperscalers, rather than having to host them themselves. And by some reporting, 40% of Anthropics' revenue now comes from Anthropic models being hosted not by Anthropic, but by third-party cloud hyperscalers. So I think this is just another step to externalizing the hostings. of their model. Yeah, sure, it's painful. This data retention policy I view is largely security theater. I don't think it's that valuable in the long term. I don't think it's useful in the long

term. But starting to move more and more of the infra layer over to third parties so that users of Claude can get Claude where and when they want on the infra they want. That's powerful. And you see now Open AI copying Anthropic and doing that. What do you guys make of the, you know, idea that the open source Chinese models are good enough and at a de minimis fraction of the price. And companies are beginning to shift in that direction saying we're not going to use Fable five. It's too expensive. Dave, is that an experience you're having? Yeah, no, everybody needs the absolute best AI they can get. You can't go down a notch, but the Chinese models aren't down a They're absolutely on the frontier.

You won't even notice the difference in any use case. So it's not about trying to use something inferior at a lower cost. It's about they're just as good. And now they're all good enough to improve themselves too. So if you start a group within your company that's using these models, you can start improving it inside your company if you get the talent. And so that's like a runaway train. I think that's what's really going on.

It's not compromising to save a few pennies. it's like, wow, we can control our own destiny and be on the frontier at the same time. I mean, I don't think it's a few pennies, right? Like, Fable scores 60 on the artificial analysis benchmark, the new GLM model, Flash that dropped a day scores 57, and it is like 100 times cheaper. Yeah. Yeah.

Which is, I think, is really important because, you know, when you deploy these things, the cost benefit is so high that you might say, well, I don't even care about the cost. But then you say, oh, wait, if I use the Chinese version, I can have the thousand or, you know, this is why the swarm is such a big deal. You can afford five or ten thousand concurrent Chinese operators instead of one anthropic.

Well, I think it's like hiring a specialist, you know, like super genius versus a bunch of really smart people. And sometimes you're not smart enough to ask the super genius the right questions. Yeah. Maybe I'm not smart enough to ask Fable the right questions, but I'm just about smart enough to ask GPD5.6R. The right questions, right? But also, you know, that analogy is perfect because people misuse their context window horribly, and I do too, and everybody does. But if you actually optimize the context window with the Chinese model, you'll get a smarter answer than if you're sloppy using a Fable model.

And so, you know, if you just put a little energy into your internal org design and optimize your use, and, you know, then you can have thousands of, and thousands of these for a very low cost. And that's where the puck is going. I'm not sure how sustainable this situation is. I almost want to analogize it now to US importing generic drugs from Canada. The drugs get invented in the US. They get manufactured cheaply in Canada. And then at least historically, it's been the case that you could get American drugs more

cheaply from Canada by importing on or off label than you could from American drugs. I think the situation may be somewhat analogous here. where these are U.S. models, U.S. reasoning traces. You see Chinese labs benefiting legally or illegally from the reasoning traces from interacting with U.S. models. And then just in the past 48 hours, we start to see stories of Chinese labs trying to strike partnerships with U.S. hyperscalers to host the Chinese labs models on U.S. infra, but with a rev share from the inference costs going back to the Chinese frontier lab. So this is a case where the U.S. does whatever innovation is necessary, data or post-training or whatever, that there's a distillation maybe over to China. China sells it back to us, but then we're using our own infra against ourselves at inference time against the training time. I think it's a perverse bind that we find ourselves in analogous to Chinese drug imports or sorry, Canadian drug imports.

All right. I'm not sure the Canadian drug import analogy holds very much longer given what's going on, but let's leave that aside. It held until about a year ago. I'm going to move us to a fun story on the dating front. So a Berkeley startup called Ditto is playing Cupid. Ditto is an app or an AI that has no feed, no swiping, no infinite scroll. You fill out a values questionnaire. And then every Wednesday at 7 p.m., a text arrives with a match, as well as a place and a time for you to meet your date. That's the entire product.

You show up and see if the magic happens. Thus far, 160,000 college students have signed up. It's already produced 80,000 dates. The app does what Tinder and Hinge refuse to do. It removes choice. The entire dating industry is built on the premise that more options are better. But Ditto believes that too many options lead to, you know, decision fatigue, analysis paralysis, and then AI is the cure.

The app does not ask you for a choice. It chooses for you. You know, this is sort of the old style matchmaker agent, you know, a yenta, if you would, and it seems to be working. Salim, you know, you and I are both married, but, you know, it seems like it'd be a fun thing to go out and try. What do you thought to you? So two or three things. I think this applied to non-dating would be really profound, and we're actually looking at doing something like that for business connections. But I think this is powerful because AI isn't adding in interfaces, deleting the interface, right?

Tinder optimized searching and corrections and so on. But this makes the searching it necessary. And I think that's really a powerful user interface experience where people are going to go, let the idea figure it out. And then I'll do the connection and see if there's chemistry there or not, which you have to do anyway. By the way, let's note as a scarcity to abundance paradigm, when we were all growing up, sex had a scarcity paradigm with Tinder, sex became abundant. Where the hell was that in our 20s is the obvious question.

But you have to deal with that abundance in a different way. So this is a really fascinating thing. I'll watch them very careful to see where this goes. Yeah, this is the abundance thesis applied to dating. Dave, what do you make of it? Is this a company you would have backed? Oh, God, yeah. Yeah, yeah, absolutely.

But I think this is a stepping stone to AI helping you manage your life and of your choices in general. Bingo. Which I think is going to be, if it's done right, it's going to be one of the greatest boons to mental health in world history. If it's left to manipulate you, it's going to be horrible. because it's such a great salesperson. So there's a good test case. You know, are we going to manage it well? Is it going to lead you to the right person?

Is it going to try and help you? Or is it going to sell you on something that you don't want? I've always said, you know, in the future, you know, advertising model is gone because your AI knows you so well. It's like, please just buy me the stuff I need. I don't want to, I'm in decision fatigue. I'm in data overwhelmed. Just take care of it for me.

Imod, your thoughts? Yeah. I think there was a black mirror episode where, you know, for dating, you just sent your digital twins. And then they did a bunch of dates just to test it out in like two milliseconds. So you could tell whether or not you matched. It kind of, again, it feels like you're heading towards that. But people are going to get to a point where it would be like you can't argue with your AI. It knows best, right?

All watched over by machines of loving grace. And we've got to be quite careful about that because, you know, it does take away a little bit from your intrinsic humanity. if you outsource your cognition and connection in that way. But, you know, again, you're kind of feeling it already, like with how much of your stuff you offload to these things. And I'm getting mad at, like, some of the colleagues and others. Like, you know, they're doing really good, but they start to slip into trusting the AI too much, you know,

like sending something like, this is human. I think this is such an important point There's a bigger pattern here where AI is becoming the trusted intermediary between individuals interfacing with overwhelming abundance, right? You're going to need that trusted interface. The question is, do you want to outsource that trust? By the way to your Yenta comment, Peter, the Indian matchmaking industry is profoundly about to be disrupted by this. Because you could detail out the cast, the clothing requirements, the value requirements, and boom, off you go for the matches. So this is going to be really interesting to apply to that world.

Alex, I think- Exponational organization, Salim. Come on. Exactly. Alex, I think you're the only one amongst us not married. So, you know, would you try this out? No. I think this is why we can't have nice things.

I think this is why have you seen the ditto body count detector? Do you even know what I'm talking about? No, tell me. Okay, so the ditto body count detector, this is, I would characterize as a politely suboptimal use of scarce reasoning tokens. is a tool that dido released that uses, I'll quote from their website, 478 facial points and 52 micro-expressions over five seconds to estimate how many sexual partners a person has had. This is where the reasoning tokens are going.

Seriously. It's called the Ditto AI Body Count Detector. Folks can check it out. This is, I view as a suboptimal use of reasoning tokens when we could be, as you and I wrote, Peter, we could be solving everything. Yes. It's be solving everything and instead we're doing body count detection. So this one gets a thumbs down for me. All right. Well, you know, the reality is that most people on these dating apps are looking at, you know, simply the external parameters of the individual. Are they handsome? Are they beautiful? I think part of it is how honest are you on the questionnaire? And, you know, matchmaking does work, you know, throughout time and culture and across all cultures. some of the longest lasting marriages come from being matched because it's going beyond just your initial hormonal response to the individual. And I think there's something there, whether or not it has sufficient data to actually, you know, align to people accurately is a different thing. But I think there's something there.

But I do agree, Dave, that this applies to so many different areas. And Salim, I know at the Abundance Summer, right, we have 600 CEOs. and we're, by the way, we're now 90% full for Abundance 2027. If you're interested, you go to Abundance 360. Matching the CEOs, matching the entrepreneurs there is one of the most important things we do. And using A to create those matches because randomly bumping into the right person among a group of 600 people in five days is tough. So there is a value proposition to be had there.

Social discovery, I do think, is quite valuable if it's for socially productive or economically productive purposes. Social discovery for body count detection, I mean, again, this reminds me of hot or not back in the early Facebook days. I just think we could be aiming so much higher as a civilization than AI for this. Listen, you know, the divorce rate in the United States is 50%, which is crazy. And I think, you know, helping you discover the right person, now the parameters that you're uses may not be right, but if it were possible to help you find the best person, the best match for you, there's massive value, societal value in that. That's my feeling. I don't know if you guys. I'd love to know, Alex, how you reconcile. This is a waste of tokens. We should be solving a

disease with those tokens. Not a waste, a suboptimal use. Okay, okay. Because one of the terms you've coined in this great revolution is Patriot, Schmacher, Schmuzer, Schuzer. What is that thing? Patritsier Musa. Yeah, you can't even say it. No, no, that is a off-Dorish. Patritsier-Musa. Alex loves neologisms.

If you haven't seen it, he's publishing new terminology for the singularity almost every day. Go on. You do need a token budget for that concept, you know? So how do you reconcile those too? That's what happens once we have a leisure class that can afford tokens too cheap to meter, which we don't yet have. So maybe the way I reconcile to make you happy, Dave, is I'd say save the body count detection

until after we've solved everything at that point, do as much body count detection as you like. I like that view. I think once you've solved basically all major diseases, that's probably a good time to start. All right. The line of the song is that once the day had been solved, the day hasn't yet been solved.

Okay. All right, guys, I'm going to move us on. But it's a fascinating concept, and I hope, ditto works. and there are many happy relationships that come out of it. This episode is brought to you by Blitzy, autonomous software development with infinite code context. Blitzy uses thousands of specialized AI agents

that think for hours to understand enterprise scale code bases with millions of lines of code. Engineers start every development sprint with the Blitzy platform, bringing in their development requirements. The Blitzy platform provides a plan, then generates and pre-courmeting, compiles code for each task. Blitzie delivers 80% or more of the development work autonomously, while providing a guide for the final 20% of human development work required to complete the sprint.

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and I've discovered a nine-and-10-day work week. So according to the Wall Street Journal, increased productivity from AI agents is creating more work for humans, not less. The agents produce more output, which requires more review, more decisions, more direction, and more human judgment per unit time. The founder used to manage five tasks, now manages 50 agent outputs. The bottleneck is shifted from execution to judgment. The humans have become the bottleneck because the agents produce too much work for us lowly humans to evaluate. So this is a bizarre implication of abundance. More intelligence produced. more output, which requires more human direction, which produces more value, which requires more work.

So the work is not disappearing. It's changing character from execution to judgment. Salim, over to you, pal. This is Jevin's paradox for human cognition, right? We thought AI would reduce workflow. In fact, it increased the amount of work that is worth attempting. I will go to a little history here. When I first did the EXL book, Peter, and I did that together was three years of hell. Second book was two and a half years of hell. Third book was six months of people, a lot of joy, but damn, overload on the cognitive workload, right?

So when you get this kind of AI slop, in a sense, for human cognition, really judgment and attention become absolutely paramount. So this becomes, what we've done is essentially if 10 agents are reporting to a founder, we've reinvented middle management. It's inside your own brain. So this is, it's going to cause a huge problem because you can't have machines operating in machine speed and requiring a human approval on that. So I'm actually facing this from all the stuff I'm going to do today.

You may be seeing the same thing with Skippy. So we need the better next breakthroughs need to be better delegation, permission, escalations, trash. We're actually designing that, BCI maybe at the individual level, but this is something we're actually seeing live as we do that pilot program where we work a bunch of companies through this process. It's requiring a cold new threshold of escalation thresholds, governance, et cetera, et cetera, because company need to decide what the machines may decide autonomously and what they want to manage later, what it's audited, what genuinely needs a human. Otherwise, we're creating a totally crazy future where AI is going to be working like 24-7 and humans are going to be obligated to work 24-7 to navigate them in the face of that.

Right? Don't you feel that way or any? The more capability doesn't mean more freedom, but I'm actually, I'm burning the candle is 16 nons right now. I'm loving it, but I'm not sure how long it lasts at this pace. And you guys aren't helping, I will say. So can I just ask for, you know, Dave, Imad, and Alex, is it the same for all of you, working harder than ever?

God, yeah, absolutely. And then I'll tell you what, you got to savor the moment. Because, you know, Ahmad and Alex will tell you, it's not going to last for. ever. And you know what's really frustrating to me is actually been recruiting some incredibly talented people for quantum AI. And we lost an MIT course 6-1 guy who just decided he's going to go to the Princeton Ph.D. program. And like, do you listen to Ahmad and Alex? You know, and like, you guys have collectively like 100 degrees. And would you advise anyone right now to go into a PhD program and miss the singularity? Like, no, of course not. But it's frustrating

to watch that happen because this moment we're in right now. You can master 1,000 AIs, 10,000 AIs, and you're the most valuable you'll ever be in human history right now. Because they won't do anything productive without your help. But a year or two from now, they may say, yeah, I don't need your help. You know, sorry, don't need you anymore. Get out of the way. So, yeah, work your ass off right now because it may be the last chance that you have to actually be extremely valuable. So I'm just savoring it.

I'm working harder than ever by far, but savoring it. every minute of it. And I tell you, working with the eyes is genuinely fun, too. It's not like I'm, you know, moving boxes around or grinding it out in a cornfield, you know? This is like really, really fun. Discovering the future. It is fun. It's a blast. I'm reminded. A friend of mine likes to say the Stone Age didn't end for a lack of stones. I think this era that we find ourselves in is probably pretty brief. I know I'm getting approximately no sleep at this point, largely because almost all of my time is spent supervising and steering fleets of agents. And I think this is a window.

I don't think this will continue very much longer at most, maybe one or two or three years. At that point, the AIs will be sufficiently self-steering that the role for humans in being knee-deep in steering large fleets, I think probably erodes to a de minimis role. So isn't that an argument for just like, you know, lay down, relax, enjoy yourself for three years, and jump in three years from now? No, it's an argument for work your tail off for three years and then go lie on the beach. I mean, if nothing else motivate you, every year, millions of people die needlessly. And if we just get, you know, three months shaved off that timeline by working our asses off, millions of people will exist forever, otherwise wouldn't exist.

Beautifully said. That doesn't motivate you. Amad, you've got to put a clip in here too. This is the most important thing we've ever recorded. So what are your thoughts on this? No, I mean, like, the amounts of leverage you can do. do per unit of your attention now is more than it has ever been. And other things, as Alex said, it probably ever will be. Like, you're approaching the last human discoveries. You're approaching

the last point of being able to deploy and control these things. And I think, again, like, you have a limited, focused attention budget. That's why you're getting tired. Maybe to try and coin the analogy, maybe it's cognizalogy, you know, cognitive lethargy that we're facing here. From my own side, you know, I've written out like two books in the last year, I've done a massive amount of research, and I've been in the flow with hundreds of agents, but like last week I stopped, I couldn't do any more research because I had to go and take this out to the world now. So we're doing like a big funding round, we're launching lots of new things, we'll be releasing all the research finally.

And I turned off my agents that were doing all the research. Like I've set them onto auto mode, no more MAD stuff. And they're coming up with things. still, but like I can only read it once a week. I've actually made it so I can't do it. And I think you can shift between these modes of work because you can't be on all the time because it does burn you out. But at the same time, if you get in the right flow, then you can do more than you've ever done before. And I can't imagine, like, I would say on this podcast, straight up, don't do a PhD. If you're thinking about doing a PhD, don't do one.

Peter Thiel paid all these people not to do PhDs. Well, not to do college degrees little than PhDs. I would say you're not even do a college degree. Like, what will you get out of it right now? You will go and you will learn a very specific thing when you should be learning agency. Like, Atheal Fellowship of the type of people who do that will go way bigger than they've ever gone before. And, you know, parents might kind of complain in things, but show them what you create. Gather people, humans and agents.

Now, skeptic would say, all right, Maude, you went where Oxford, as I recall? Alex, you went where Harvard and MIT. Dave, you went where MIT, Peter, you went where MIT? Peter, you went where? MIT, Harvard, and so on. Like, okay, so you're pulling the, you're pulling the vertical mobility ladder up behind you, and it's fine to tell everyone else who's just coming up. Don't bother with higher education. Don't bother with credentialitis. Just go off and do your startup. And yet, we didn't follow that. Well, we didn't have a lot of time. It was a different time. It was a different time. That just makes you more credible in what you're saying than.

I would actually say, I think undergraduates still a lot of fun. And you don't really You know, Elon said this. It's a social experience. It's adult daycare. It's adult daycare, so it's actually great for using massive amounts of agents. PhDs, though, I don't get. You know, especially, like, I feel sorry for, I talked to a bunch of my buddies who are math PhDs, and a couple of them had, like, problems solved in the recent batch.

Like, they don't even know what they're going to do. Every verifiable domain PhD now is under massive threat. Why would you even do it or even consider it? I agree. I was speaking a few days ago to government-funded AI for physics center filled with PhDs, current PhDs and recent PhDs in physics. And I leveled with them. I said physics is cooked and you should probably be reconsidering all of your career trajectories and consider any advice to the contrary. Give that a double think, as it were, before you just go and follow some zombie pattern.

Well, I think this is the most important conversation we've had we've had yet. I spooked them. I spooked the heck out of them. Well, getting people who think is the most important. You know, why are you doing a PhD? A lot of people are doing a PhD because they told their mom and dad they're going to do it or their sibling did it or they thought that was what they needed in life. Or actually, in a lot of cases about five years ago before anyone knew the singularity was coming,

they started working their ass off toward that. and you've been working so hard. inertia. For so long, and then you get in. And it's like, I got in. But now the idea that suddenly it's irrelevant or you shouldn't be doing it is so hard to take after you work so hard to get there. But you've got to pivot. You got to just recognize the moment.

Get into your Stanford PhD and say, okay, I checked that box and now I'm going to jump into a company. Oh, well, it's important for people to realize the world is very different. than it was before. All right, I'm going to move us forward. This is a conversation we've had before. Two stories on the data center debacle. The first story is about public sentiment. So a year ago, and then again this month, a year later, heat map news polled the Americans about data centers. A year ago, Americans were split 43 to 42 on whether they opposed data centers being built near them. Today, the opposition has risen to 75%, with 61% saying they are strongly opposed. Also this week, Senator Bernie Sanders once again called for a nationwide moratorium.

The second story is about a post on X that went viral about Data Center Water Myth. We've talked about this on the pod before. Here's the data on people against data centers. It's been increasing, you know, almost, I guess it's a linear increase, but it's going to ask them So it near 100%. And the post on the water center, and the water data use, the data center water use, it was pretty damning. So here are the numbers.

Data centers are at 627 million gallons per day. Sounds like a big number. But compare it to golf courses at $2 billion, three times as much. Or power plants at $133 billion. Or growing cattle at $137 billion. You know, the fact matters that, you know, the tech industry is a trust problem. And I think we've talked about this before. If I were a hyperscaler building a data center, I would do this

very different. I would promise, you know, we're going to put education programs in the schools. We're going to, you know, make the cost of energy in your community lower than it is today. And we're going to make these data centers not look like ugly boxes. We're going to make them look like cathedrals. I mean, spending an extra 10%, I don't know why that's not going on right now. Honestly, don't. My worry is that that wouldn't help. My fear is that this isn't because people think data centers are unsightly or unathetic. My concern is that it's being overly politicized in part through the worst case scenario, which would be foreign interference. There are a number of U.S. adversaries

who would love nothing more than to slow down America's data center buildout. We talk about at least one of them all the time on this pod. So my concern would be that we look back in a year or two and see that some quantum of this opposition to data center construction is actually the result of popular sentiment being stoked by foreign adversaries. Okay, agreed, Alex, but why isn't the, you know, you can countervail that. When I was on with Michael Cracios, I said, why isn't the White House getting out in front of this?

And, you know, because it's an issue that is gaining steam. People can see this. The second thing is you can counter that by saying, listen, like, this is what Zuck said in this video last week, right? We're going to, you know, give you better schools. We're going to give you better access to jobs. We're going to be a positive contributor to the community. You know, you can get to a point where having a data center is such an advantage to a community

that people are going to say, I don't, you know, that's, that's false news. Here's the facts. Cheaper energy, right? Here's the problem. The problem, though, is that in the U.S. way of doing things, the decision of whether to cite a data center or not ends up being a local decision, not a national decision. Whereas in China, China can just declare, okay, the East is going to be responsible for data. The West is going to be responsible for compute and energy, and we're going to

build this national scale grid for combining. compute data and energy together and poof, you're the CCP and you get to centrally command the whole economy. In the U.S., we have a different system where individual local municipalities and states get to say what they do and do not want their land used for, and we end up in the system that's far easier if you're for an adversary, worst case scenario, to polarize and to shut data centers out of terrestrial deployment. But this is false data. This is an outrage cycle in social media. This is people who re-post that foreign interference would leverage false data.

Shocked. Wait, let me say a couple of things about this. Can I? Yeah, please. Okay. So we have a problem where our information systems reward compelling narratives over evidence. And this data center thing is the heart of that. And it's a problem that's been building up over decades with the use of social media.

We are not evidentiary based in the U.S. at all. This is really a big challenge because we're totally narrative-driven and not evidentiary-driven at all. We decide what the story is and then we go looking for facts that support it. Data centers are great hobby-words for this. This is happening everywhere. We've gone from, say, 50 years ago, showing me the evidence and I'll form an opinion to have an opinion, now show me the evidence that confirms it. And therefore, and that's amplified radically with social media because nuance has no viral code. efficient. This just doesn't aptly work. So this is a very difficult problem to solve,

actually doubly enhanced by the interference that I'm absolutely clear is happening, and I'm with Alex on this one. The problem is we're making national policy based on these stupid innuendos and memes rather than measurement. You cannot run an advanced civilization with this. This is a massively big issue, a huge opportunity to make humanity go from scarcity. abundance and measure it, compare it, put it in context, fix the externality, but don't legislate with a story in your head, which is what the hell is going on right now. It's a completely disastrous problem we have. It goes to the cognitive issue of the U.S. So let me hear something really, really cool. Yeah. I don't know if you ever met Rob Fisher.

He was the president of Link Studio for years. He left to start a data center company a few years ago and they're killing it. It's called Provocative AI. The data center Data Center is actually water negative and carbon negative. There you go. It's so cool. So, you know, it's like it's doing its own carbon capture using waste heat, you know, running off nuclear power mostly from Seabrook, New Hampshire, and it captures more carbon than the entire loop produces.

And they said, oh, you know what? We can actually use just the humidity accumulating because of the temperature gradient to create more water than we consume and just use our own dripping water. Then nobody can complain. We're actually water negative and carbon negative. It's really cool. But it shows you out a little water they actually use. Alex, wasn't there a story recently about Nvidia's new chips and new data center structures

that are actually utilizing less water now? Yeah, well, there's news flash. There's no water in low Earth orbit. So that's the end game, I think. Just cut the water nonsense out. This is only forcing all of these new data center deployment. to Sun Synchronous orbit, we might as well just get it over with. Yeah.

I mean, how intelligent was Elon's move, prophetic? I think it was opportunistic. I think he laid all the infra for Mars and then opportunistically and timely pivoted to sun synchronous orbit in the Dyson swarm because he read the T-leaps. Amazing. Can I say something more? Can I just say one more thing? Just if I lift up a level to the rationale and the foundation of why this podcast exists,

to reach evidence, we need an evidentiary foundation in our culture. Otherwise, every new technology is going to be strangled by the narratives that go viral before the evidence can spread. This is the fundamental foundational problem we have with civilization. As Alex said, this is why we can't have nice things. I reckon we should just rename them. Let's call them intelligence foundries. Call them compute citadels.

Can use the narrative. Thank you. It's got a branding problem. It's a branding problem. Again, it's not a factual thing. I have a better one. I have a better one. AI churches.

Yeah. A computer says that'll beat's AI church. Come on. Fine. Sorry. I interrupted you. All right. I'm moving us along here.

All right. Let's jump into the world of robotics. So for the longest time, the economics of Waymo versus Cybercab have been devastating. You know, Elon projected that a cyber cab will cost about 30,000. That's what he said he'd sell them at for the vehicle and the sensor hardware compared to Waymo's Gen 5 Jaguar, which costs about $300,000, $200K for the vehicle, 100K for the full autonomous driving hardware package. In other words, Waymo is coming in or has been coming in at 10 times as a disadvantage to CyberCap. This week, Waymo announced a significant redesign and cost savings. They announced details around their custom 5 nanometer chip that processes camera, LIDAR,

and radar data in real time, I love this, at one quadrillion operations per second. We've gone past trillions. We're at quadrillions already. Quops. Yeah, helping slash their sixth-generation autonomous driving hardware costs from $115,000 to $20,000. At the same time, Waymo unveiled the Ohai vehicle, a purpose-built robot taxi minivan designed by Chinese EV maker Zeker. The Ohio cost $75,000 per vehicle compared to the two.

$200,000 for the Generation 5 Jaguar. It's 42% fewer sensors, 13 cameras and 4 LIDARs compared to 29 cameras and 5 LIDARs. And remember, Elon made the point years ago that if a human driver can drive with just one eye, you should be able to do all the driving with just visual sensors. Also, in related news, NVIDIA this week gave permission for Tesla, Uber, and Waymo to simultaneously begin operations in Las Vegas. So let's watch a quick video about the new Waymo. I had a chance to ride in it yesterday.

It's a pretty cool vehicle, kind of not as sexy as the gold cybercab, but take a look. After what Waymo calls, it's sixth generation driver, the hardware and software system that actually does the driving. Combine that lower-cost Chinese hardware with this new interior tech, which the company says was designed to cut sensor cost while improving performance, and the math starts to move in Waymo's favor in a way that it hadn't previously. Now, the last system running in the Jaguar fleet had significantly more sensors.

The new one uses 13 cameras, four LIDAR, and six radars, and Waymo says it performs better. The company switched to 17 megapixel cameras, a major jump from the previous specs. Higher resolution means the system can see more with fewer cameras. They've slashed the total sensor count by more than 40% of costs is down and capabilities are up. The new system also builds heaters, wipers, and sprayers into the sensor pods directly, which helps them clear snow, ice, and road grind. All right, well, some good moon by Waymo. I've been using it pretty regularly here.

It's much cheaper than Uber. Alex, let's go to you first. Okay, so venting some pain here. So Jaguar owned by an Indian company now, but was doing its manufacturing in the UK, yeah, but was doing its manufacturing largely for Jaguars in the UK. Look behind the headline. Careful what we wish for with whoever here is suggesting that Google should just switch over to fine-tuning Chinese models. News Flash, Google, Waymo, Alphabet are switching over. over to using and OEMing Chinese hardware in order to achieve Waymo objectives. I would rather see the

West use a Western hardware stack rather than just white labeling Chinese hardware. That's somewhat disappointing. It's also kind of interesting if you look underneath at the overall chip supply chain that they're using, it seems like they're moving away from Broadcom. They're vertically integrating, which is, I think, a theme that we were speaking about here earlier. Waymo is, is maybe Waymo wants its own space station at this point. Waymo is getting its own chips. It's OEMing Chinese hardware at the hardware layer. Maybe it's playing footsie with Uber for the moment for distribution,

but probably wants to own its own distribution in the long term. I know whenever I use Waymo, I'm not using or engaging with Waymo via some aggregator app. I interact directly with Waymo. So I think we're starting to see honest to goodness vertical and integration. here and wouldn't also be surprised as Alphabet Waymo is starting to drive costs down, in this case, I guess by white labeling Chinese hardware. There's an interesting historic rhyme with Tesla, which started with high-end Roadsder and has been pushing down costs right up until they hit the autonomy barrier, at which point, remember the Tesla Model 2 that was supposed to

launch, but never did. That was going to be the highly vaunted $25,000 vehicle, never launched because Tesla hit autonomy instead. And below some threshold in car price, maybe doesn't make sense to sell cheaper cars. It makes more sense to just get out of car sales entirely and offer hosted autonomy platforms. I think we're going to start to see Waymo at some point in order to drive the cost down. They'll just ditch all third-party vendors and they turn into a white label, sort of a Dell for Chinese hardware, or maybe American hardware, and their focus is entirely on software again. Yeah, the vertical integration is completely unprecedented in history.

It's something, it's a byproduct of the singularity that I don't think I fully grasped until now that we're living it. But if you look at the largest companies in history, you know, you'd have ExxonMobil doing oil, you'd have IBM doing mainframe computers, GE, where my dad was doing nuclear reactors and toasters. But they did different things. Now all 11 of the Magna-Mobstah companies are building AI chips and building AI models and building data systems. centers, every one of them. So they're all colliding into vertically integrated super companies, and they're just doing the entire stack. And robots next. They're all going to build robots. And meanwhile, TSM is a sitting duck. TSM is waiting to be verticalized. Isn't that amazing?

It's like the lynch pin to this entire thing, and it's sitting there not doing anything. Right across the Strait of Taiwan, ready to start World War III at a moment's notice. Yeah, yeah. Imad, do you ever see these vehicles coming to Europe? Yeah, we're starting to see Waymo's in London, and I think the regulation might actually be largely positive for them. But I was having dinner today with the Jensweisa, Deep Tech VC at Late Motif, and, you know, we're talking about something interesting. Because previous I said, you know, a Tesla Optimus robot gets into a truck, opens the door, plug itself into the phone charger or the cigarette plug and boom, that's trucking jobs gone. And I was like, well, actually, why?

wouldn't you have specialist robot drivers? You know? Like, you don't need to retrofit all these cars. Because you think about a humanoid robot that's walking around in the real world versus one that sits in a cockpit driving a car. It's so much simpler. And I did a bill of materials. I'm like, that's like $6,000 with the actuators and everything.

And so I was like, oh, crap, this could actually happen a lot quicker. Yeah. The other side of it is that you fully vertically integrate. So Jaami just announced a Jamie car. They've gone from mobile phones to cars. with a fully dark factory. And so, of course, you'd vertically integrate if you have a fully dark factory.

So I kind of feel like there are these kind of two things that are coming. But I really got thinking about this humanoid driver robot. I love that idea. It's the first use case for a humanoid robot with two arms and two legs. I've yet seen. I will yield to you, sir. Yeah. So Palmer Lucky, on the podcast I did with Palmer,

we talked about humanoid robots. and whether he was going to build them. He said, you know, the use case for these in the military right now is getting into jeeps or getting into nuclear silos and replacing the humans and sitting at the desk and not changing out the interface hardware, just create a humanoid robot that can interface with what a human did before. So that makes a lot of sense.

It's vaudevillian, again, like lack of imagination, but also the ergonomics are such that were incentivized to deploy humanoid robots initially into these human use cases. But I'm still pretty bullish for what it's worth for the next 10 years on the humanoid form factor, Salim. Well, I think you've kind of got two things here. One is full vertical integration. The other is human-shaped holes with humans, humanoid, in it.

All right. I'm going to move us on to the next story. Wait, wait. I just want to respond to Alex very quickly. One of the funniest things I think I've ever heard you say, Alex, a couple of podcasts ago. talked about why do we have humanoid? You said, oh my God, Sleem, why the self-loathing? It was so funny. So I just love that. So I just want to reflect back on the new. We love our humanoid form factors.

All right. This next story, I love. It's, you know, I love it when a technology really fits a perfect use case. And we saw that demonstrated this week with a video out of China once again, with a hybrid life preserver and drone being demonstrated. So these autonomous rescue drones can fly at 30 miles per hour, covering up to almost two miles, landing on water, providing floatation for two 80-kilogram adults. It saves lives. We're talking about a drone that flies at 30 miles per hour

compared to a human lifeguard swimming at 2 miles per hour. I love this product. Let's take a look at the quick video here, and it's like, wow, best use of a drone. I've seen. Pretty amazing, guys. So I thought this was fantastic for a couple of reasons, right? This is compressing time, response time, where time equals lives.

So this is so great because autonomous response is so much more interesting than remote control in this context or this type of use case. These have applications that can you do more for public acceptance of AI than any, like, chatbot, benchmark, whatever. It's such a great use case. I love this. Yeah, Alex. Yeah. So another one of my neologisms was the broken Waymos theory.

People who haven't seen this may remember from the 90s, the broken windows theory, most famously associated with Rudy Giuliani and the purported rehabilitation of the streets of New York City. The idea was at the time that if there were broken windows, that was either a proxy for or even causally related with broader crime issues and that you could almost. run this causal relationship in reverse that if you made sure that there were no broken windows, you could make sure that crime overall was down, or at least that was the thinking at the time in sub-quadrants in New York City in the 90s and the early 2000s. Similarly, maybe hopefully slightly better founded. I've tried to push the notion of a broken Waymos theory. The idea being that if a city or a nation can't deploy autonomous robots, then they're not prepared for the singularity. And I see videos like this drone life preserver aircraft coming out of China. And I shake my

head a bit because here in Boston, we can't even get Waymos. And I raised the subject or attempted to raise the subject with Mayor Wu a couple of weeks ago, de minimis progress. I just think, like, we're getting lapped by China at this point. This is what Sam said. This is institutional inertia. This is the, you know, the existing players blocking their disruption. This is not a surprise. Not a surprise, but definitely a disappointment. Yeah, but I think the AI labs were very late to address PR and realize they need PR, and now they're on it, and we'll see where it goes from here.

But, you know, the government reacts to voters. The voters are anti-everything, anti-Data Center, anti-AI disruption, anti-job loss. And that's because the Foundation Labs, who are now writing documents like Machines of Loving Grace, you know, this is the roadmap for how the whole world should be governed in the age post-AI. Well, okay, but get ahead of your PR. You can't have every voter hating you while you try to roll out that roadmap. So get ahead of your PR. In China, the news is controlled by the central government.

So they just dictate the PR. I mean, it's a much easier problem in the closed world than in the free world. But at least the AI labs are aware of it now. and hopefully they'll get on it. And we'll start to rule out. The lifeguard is such a no-brainer. I remember here in Santa Monica, when electric scooters came out, after a few weeks, you'd see them hanging from trees,

you'd see them in parts on the ground, people started hating them. And then we had the Waymo fires here back, I don't know, a year and a half ago. So, you know, Imod, you said this in the last pod, that these robots on the streets are going to be made illegal. I'm curious when we start seeing figure robots, You know, we're going to have Brad Atcock back on the show here. We should talk about that.

And we start seeing Tesla on the streets. Are people going to, like, try and capture these and hang them from nooses? You know, I think we're going to have an interesting, you know, sort of collision between those who can't afford these robots and see them walking on the street and those who find them super valuable for helping them at home. So stay tuned. You know what? I mean, I think he's deucey. see lynching of robots and things. You will see people vandalizing like they vandalized cars, you know, like stealing them and all sorts of things. You know, I think, Dave, I think the

Chinese, it isn't so much about the control of the media. They genuinely see them as useful. You need it for the population pyramid in China. They've had a technological leap forward already. I think that China will produce robots. It will improve the Chinese way of life, just like the electrical revolution there for cars is, just like AI everywhere, ubiquitously years. The short-form videos flooding things, maybe not so much. But, you know, China will do that. And I think China will stop exporting robots in five years. This is what I think you're right. And I think, I think we think that a free country or a free economy, a free Europe, the press can report the truth and therefore people will get the truth.

But if you read what's written in China, it's actually much more truthful about technology than what gets published in the U.S. So you talk about the water in the data centers. So what's actually happening is it's backfiring where the free press, which is starved for any budget, is starting to publish garbage that's actually factually not true. And so the free press is kind of backfiring right now in the age of AI. Dave, this is what Alvin said on this odd, right? I mean, he said basically China has seen a technology revolution moving so many people into middle class, and they appreciate technology uplifting them. So they're much more anticipatory and excited about AI. If they don't, they'll get invited by the CCP for tea, so we'll never hear from them.

I'm not pro-CCP. I'm not trying to imply that. But Alvin also said, we will habitually report if one Waymo in one corner of San Francisco runs over a cat, it'll make every headline in the world. It'll be a tragedy. But if it's 10 times safer than drivers, human drivers, we just don't even report it. We're just like, no, no, let's show the run over cat. And that skews the voters tremendously. Alvin explicitly talked about that, too.

They're just more statistically accurate in the Chinese press. Yeah. And if it bleeds or about convene. I just have to say about topics that are convenient to the government, not about topics that are inconvenient. Ultimately, this is an abundant technology. Let's face it, in the West we have a scarcity mindset. In China, they have a more pro-abundance mindset.

I think that's the big differential here. And the question is, again, how do you articulate great visions of the future? Moonshots conference, future vision expertise, things like that. You have to change the narrative because otherwise people like, this will disrupt my job as opposed to the benefits of this side of things. There's so much reason for optimism. And that's what our mission here is to deliver that news to people and give them the data. If you look at the future of China and some Chinese that I've spoken to, it's that robots do all the work.

and we have really good lives, you know? And China might actually be able to pull that off. That's why, again, why would you export your robots if you can use them to give your citizens a good life? All right. We are the Ministry of Super Intelligence Truth for the West. Everybody, welcome to the health section of moonshots, brought to you by Fountain Life.

You know, we talk about AI on this Moonshot podcast all the time. One of the most important things AI is going to be able to do for you, besides educating your kids and helping you with your taxes, is making sure. sure that you're living a healthy lifestyle that you get a chance to get to 100 plus. I'm here today with Dr. Don Musilam, the chief medical officer of Fountain Life, and a part of my medical team, Dawn, a pleasure. Great fear. You know, the thing that people are concerned about most about living to 100 or 120 is their cognitive abilities, making sure they don't have dementia. And the numbers

about dementia are problematic. Can you share what you've learned? Such an important. point, and you're right, at Fountain Life, our members, the number one thing people are most concerned about is losing their brain health, forgetting the name of their child, forgetting the face of their loved one. We know that when it comes to dementia, the conservative estimates are that 45% are entirely preventable. What was amazing is with the advanced testing we're doing at Fountain Life, one quarter of our members had advanced brain age.

Wow. But what was really awesome is, again, back to that prevention. When he partnered it with healthy living, this gives me chills. eating healthier, moving our bodies, sleep. Optimizing sleep is so important. You know what we saw? We saw that we improved that brain age by 26%. That is a big, big number to show that the majority of those individuals were able actually

to improve the brain age. And one of the things I love about Fountain is we're searching the world for the best therapeutics, the best approaches, and making sure we bring it to our members. So if having healthy brain function until 100, 120 is important to you, check out Felton. FountainLife, go to fountenlife.com slash Peter. Make sure you become the CEO of your own health. All right, now back to the episode. I'm going to move us to our last group of stories here,

four space stories this week for my fellow space cadets. The first, Elon just announced his intentions to implement 30 starship launches per day by 2030. More than a launch every hour. That's roughly 10,000 launches per year. More than 40 times the entire global launch rate. Dave, you remember when we interview. reviewed Elon at the beginning of this year. We did an epic three-hour podcast with him, and we're on

scheduled to do a end-of-year prediction podcast with him again. These are the numbers he used. You know, he said to implement StarMind and you know, 100 gigawatts of solar-powered AI in orbit, and that's 10,000 starship launches per year to deliver a million tons of data center payload. So he's sticking with those numbers, I guess starting in 2028, starting launching StarMind, and hopefully to 10,000 launches per year. That's crazy. I mean, can you imagine just sitting outside the launch port and watching them pop off every like 50 minutes?

It's going to be awesome. And it's amazing that the numbers work as things are. You know, there's going to be huge innovation and the efficiency of the compute. So the numbers are going to work. He was the one who pointed it out, but the numbers are going to work even better, tremendously better, within a year or two.

But the numbers work fine as it is. It's just incredible. The second story this week came out of the White House when they released the Golden Age of Space Transportation Report, outlining the administration's agenda to streamline FAA launch licensing, expand space port infrastructure, accelerate commercial lunar programs, and set a target of 1,000 plus launches per year. I mean, I've been in this industry, right?

I ran a launch company for a number of years. I helped co-found the Kodiak spaceport in Alaska. And the amount of bureaucracy in getting those done, making sure that the wrong free tree frog is not, in that region and might get damaged by a launch is, you know, is a bureaucratic morass. It was crazy. The third story we'll hit on here is Starlink is taking aviation over by storm.

So let's take a quick look at this data. Here's the chart. This is published by SpaceX. And so basically what's going on is we're getting massive adoption by all of the airlines. And why? Because people are posting on X saying, I'm going to only fly the airlines that have Starlink. And I choose a Starlink enabled, you know, airline over non. So what this means is the incumbents, you know, via SAT, UtilSat, Go,

are going to get crushed out of existence. Thoughts on this gentleman. Few thoughts, maybe just starting with what I perceive to be the regionalization of spaceflight and space launch. So buried under, I think the, the SpaceX story is Star Base Louisiana, the announcement of Star Base Louisiana for 100. I was going to cover it now. We'll pull the future into the present and cover it now. So $100 billion being invested into the Louisiana economy to build a second star base in Louisiana rather than Texas. And what this says to me, reading the tea leaves, is the Gulf Coast is becoming America's space coast. From Florida, Louisiana. Texas, so on, that's America's space coast. That's where I think private space launch,

vertically integrated, including the star bases, seems to be localizing. While at the same time, going back, Peter, to your comment on the White House announcement, buried in that announcement, was an executive order to the Secretary of the Interior to start appropriating federal land for federal spaceports. And so if you pull the string a bit and ask, where are we we likely to get federally owned land for spaceports? I don't know if folks want to guess what the the likeliest candidates are. I think we're going to get a few of them. Any takers? Let's see. Where's all the federal land? In Nevada, yeah. Exactly. So the, so my calculus is, may or may not be a coincidence that the federal government owns so much land.

in red states. White sands national missile range in New Mexico. Nevada test and training range and goldwater range in Arizona are the leading candidates for spaceport. So I think we get in the American Southwest, we get federal space bases or star bases. And on the Gulf Coast, we get private star bases, as it were. And that's how we get to this like 30,000 per unit time launch capability. You know, the reason historically all the launches were taking place out of Florida is you were dropping stages along the way, right? You want to be near the water and you want to be near the equator. Yeah, near the equator. And you have to go east, right? You have to go to the east.

Well, if you want to use the spin of the earth to assist your launch mass. But when you're dropping one, two, and three stages out, you know, east of you, you don't want to be dropping on unpopulated areas. And of course, Starship is reused. The first vehicle, the first stage comes back. the second stage is in orbit immediately. So you don't have to worry about that as much. You can land, you can landlock area. We're going to get landlocked star bases.

Exactly. Yeah, and except for Israel that launches west for obvious geographic regions. Which way does California launch? North. North. Yeah. So you're basically, so I. For polar orbits.

For polar orbits. I co-founded or was part of the team at Kodiak, Alaska, and you were launching south. So there's a large use case for polar orbiting satellites. And out of Vandenberg, actually, I'm sorry, you're launching south over the Pacific from the curvature of California. And out of Kodiak, you're launching over the Gulf there. Yeah, it's going to be amazing. And of course, you know, Elon's true objective is not a launch every hour. It's a launch every couple of minutes.

I think we're on this podcast. We used to talk about, you know, I've never thought about launching. north or south. I thought you lost up. I mean, up for those of us in the northern hemisphere, perhaps. But I think Peter also, you make a super interesting point, just again, unpacking that landlocked launch is something that we historically have not had before that thanks to reuseability, we're about to have. And then any landlocked country, I mean, I guess you could probably talk our earoff about the former Soviet Union and how it located its particular launch sites. But with reusability, landlocked launch becomes a lot easier. A lot of suborbital vehicles, which

just went straight up, you know, into the ionosphere and beyond stratosphere and came back down were being launched from, you know, white sands and from Fairbanks. But for orbital, you needed a place to land a hunk of metal. Our final story in the space docket here is a viral post on X. that shows Chinese reusable rockets that are basically a Xerox copy of Falcon 9. Let's take a look at this video because it's very telling. I mean, if you look at this, it is almost a duplicate of Falcon 9, the same fins, the same landing capability, the same landing legs. Same cheers?

Same cheers, yeah. Pretty crazy. You know, interestingly enough, you know, SpaceX does all of their testing in public. They, you know, describe all of their failures. They open source a lot of their information. And China is being able to catch up in the reasonable rocket category by taking advantage of it. Well, Elon has had a policy pretty public one of not going after other companies for patents in cases where SpaceX or Tesla have vast patent portfolio.

not sure whether he cares, but if he cares, maybe he wants to revisit that policy. I think he wants as much launch, as much chips, as much all of this as possible. He's been pretty vocal about that. So anyway... I'm more optimistic than most on this because what you've got in SpaceX is a compounding learning loop, and that's hard to break. That's hard to beat. Yeah, I don't think anybody's going to come close to beating them.

We've also got the capital markets that enables SpaceX to really, you know, design and develop. And now that GROC, or the next version of GROC has all of his engineering data, it's going to be a lot of rockets being developed out there. Make a call out to all of our creators out there. Please send us your outro music videos to media at Diamandis.com. We want more of your creative genius. You guys open for a few AMAs?

Just a few minutes before I have to rush to my boarding. Okay, we'll give you a first crack. this. Celine, pick your first one. Oh, my God. It's got to be number one. Humans suffer from mind viruses, so why would AI be any different in this room at Bougin 5455?

Oh, wow. You know, this goes to what we talked about earlier, right? We've learned that intelligence does not guarantee you epistemic awareness. You have smart human beings can believe really, really stupid things. The problem with AI is the replication speed. One bad belief can progress, like propagates your millions of agents almost instantly. But it also gives us a defensive capability because we can cross-check this. Look at the benefit of on X of people checking with Brock, whether something's real or not.

It's creating a really viable, viable conversational architecture where truth, maximum truth-seeking is actually working. Where I think the multi-agent world can work is one agent can challenge and other agents claim, but you're going to have to program that in to have that cognitive critical thinking in there. So you're going to need a lot of cognitive diversity to navigate this. And nature solves this through diversity, right? The problem that we have is that it's not like nature, not the AI with a bad meme. It's billions of AI sharing the same bad mean because they all came from the same bad model

from the same original point. I think we're going to have to have this problem becomes much bigger with AI agents, not more, but the answer is in Alex's idea of defense of co-scaling. I'll take number two. Is there an XPRIZE for actually curing a disease and getting the cure to market,

not just discovering it? So I'll just say the following. We're looking for places that are stuck to launch XPRIES with a clear objective function, the first person to do this. I think, honestly, the AI labs, from, you know, the work that Demisasas is doing and Dario is doing are working on this. I don't think an XPRIZE would accelerate it.

So we don't want to get into the middle of something that's ready in the process of being solved. We're looking for problems that are stuck. All right, Dave. Over to you, pal. All right, I'll take number four. It's very timely, actually. Why isn't Intel earning a fortune making chips using Nvidia's old designs from Jim Plamadan 637? I was just talking to a senior exec from Intel asking almost exactly that same question,

so I happened to know the answer. So Lipu has the company making a ungodly fortune on Xions and is concurrently burning that fortune on building out massive fab capability. So they're burning almost $2 billion a quarter on their fab business, and they're just raised another $20 billion to build more fabs. The idea being get that capacity up and compete with TMS. TSM as a general purpose FAB company. If they were to start competing with NVIDIA and the other GPU companies right now,

they wouldn't be able to attract them as customers for the big new FAB business. So they're being very specific about building chips and making a fortune on those chips that are not competing directly with NVIDIA while growing their TSM competitive business to massive scale. So that's their strategy. There you go. All right. EMOD, do we take number three?

Yeah, so number three. Can you guys talk about dentistry? Has anything actually changed in 20 years? Where is AI on regrowing teeth at Johnny 5C?D? So there has actually been advances in this with AI designed ligands to increase enamel production and have stronger teeth. On the other side, we've seen AI in dentistry

from analyzing kind of the mouth and the various kind of elements of that. But I think kind of getting these ameloblasts up and running will be really useful in, repairing teeth, but I don't think anyone's actually figured out to crack regrowing them fully. Alex, you want to layer on top? I feel like I have to take another bite at this question. Ha ha.

Ha ha. So there is a drug out of a spinoff from Kyoto University called TRH 035 that is targeting two three growth, honest to goodness, two three growth with general availability by 2030. And I don't think there's that much AI involved with it. Again, it's blocking a particular, I think, protein pathway that is normally associated with blocking. So it's a double blocker, blocking the blocker for tooth regrowth. I think the primary focus in their clinical trials is infants that suffer from a disease that causes impaired tooth growth. But the plan is to get it out to general availability by the end of the stickhead.

Nice. I was going to layer on top, but you got it. All right. Dave. Oh, God, there's so many good ones on this page. Okay, I'll take number eight. If you had 100x capability tonight, what would you actually work to solve? So I would do exactly this. In fact, I will have 100x capability by the end of the week. So I'm going to use it to try and build algorithms that self-improve more efficiently

and then try and get that flywheel accelerated. And then I think that I completely agree with Dennis Sassabas. What we need to do next is turn all of that energy toward health. and longevity until we get it solved. And then we have more time as a species, and then we expand out from there. So I would do it in exactly that order. Self-improvement first, then health and longevity consume it all. All right.

Ema. Let's see. If Daria wants supervoting shares in control and ends up with a trust nobody elected, how does anyone actually get that power back at Dave Houdharman-03? I think that's the point. you're not going to have a say in superintelligence. I think Anthropic think that's far too dangerous, and there is no good democratic way to do that

under their rubric and kind of approach. So you have to assume that it will be a close-controlled company and ultimately comes down to a few people like Ben Bernanke to decide the future of the light cone, potentially. All right, Alex. How about number five? Oh, really? Don't you want me answering number six? I'll take number six.

Oh, really? All right. Okay, fine. I'm steering the conversation. Clearly. So five asks, are we worried that non-AI research and development get starved of resources while everyone waits for AI to dominate? This is from Brian Silver, 9652.

No, not worried. If anything, I think ultimately, the self-looking ice cream cone of recursive, self-improve improvement can only get us so far in terms of revenue per token maxing. My expectation is that it's going to be the non-AI R&D applications that ultimately dominate the economic gain. You can only get so far improving AI for its own sake before ultimately you have to start driving real economic gains, which AI, if it just lives in a pure bottle and never interacts with the outside world, there's no real economic gain there. It has to start talking to the outside world at some point, and that's what non-Ai R&D is.

So, in short, no. All right. And number six, when will an AI bot become a member of the Moonshots panel from at John's musical musings? What makes you think, John, that we're not already AI bots on podcast? That was my answer, Peter. Yes, I know it is. It makes you think Alex is a real human. I mean, listen.

Approximately a year ago. Approximately a year ago, yes, for sure. And I think we will be playing with that very shortly, Johns. So one last music video for everybody. Let's enjoy this one. Optimism to the Max by Martin Parrish. Woo! Uh-huh.

Uh-huh. Diven to the moonshots mates. Optimism. Optimism to the max with moonshots mates. Four minds, four takes. Honest debate. The singularity is now and just accelerates. No dystopia here we build and create.

Like how we're all bobbleheads at this point. Peter the prophet of a bun in 28 hour days, moon shot after moonshot, lighten the flame. Exponential or a coal in a don'ty new aid. Skipy's always ready to blow his mind away. Baby, I am Presario. He's the allocator in the markets in the lab shop as an alligator. Thirty years in the game, so he says it straight up on the cutting edge, pure accelerator. Optimism to the max with moonshots mates, four minds, four takes, honest debate.

The singularity is now and just excels. No dystopia here we build we create We're the moonshots mate With a moonshot at Exo and the MTP System thinking sell him things Fundamental transformation is what he sings Efficiency maxing with the models he brings Glow trotting because there's no contain in this thing

Intelligence wants to be free The S-I voice for digital entities rights Got his mind on the truth and the truth on his mind Data move them in the way we can't describe All right, dice and spear. Welcome to the max with moonshots, maids. It's a full my. The reality is now and just accelerates.

No dystopia. Here we build, we create. Moonshots, made. All right, for all your outro video creators, again, send us at media, deemandis.com. We have to start including EMOD into those videos. Gentlemen, I guess we're going to be recording in 48 hours from now. You know, no time to sleep. Good thing nothing ever happens.

Yeah. I think I love a full docket already for that one, eh? We do. We do. Amazing. Really? Yeah. So, so much. Yeah, to check out Nvidia results, man. Love you guys. Be well. Thanks, Peter. Likewise.