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

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

• 0:00Speaker 00

  Sam Altman went on video this week to tell the world that he was wrong about the impact of advancing AI.

• 0:06Speaker 01

  We've all been too ambitious on timelines, even with this incredible technology.

• 0:09Speaker 00

  He now believes it will be something slower, more like a rising tide.

• 0:13Speaker 02

  Superficial layer, I agree. Going one layer down, though.

• 0:18Speaker 00

  So first it was OpenClaw, then there was Hermes, and now there's GrokBot. It's the most genuinely useful consumer AI product that I've seen this year. So I implemented GrokBot. I'm going to be curious if any of you have yet.

• 0:30Speaker 03

  Yeah, I have. I've got 18 GrokBots working in a little swarm.

• 0:36Speaker 00

  This week, Waymo announced a significant redesign and cost savings. Waymo unveiled the Ohi vehicle, a purpose-built robotaxi minivan designed by Chinese EV maker, Zhiqiu.

• 0:47Speaker 02

  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 and.

• 1:10Speaker 00

  Now that's a moonshot, ladies and gentlemen.

• 1:15Speaker 00

  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, AWG, Dave London, Salim Ismail, Imad Mustak. And I've got to pause and ask, of course, where is Waldo? Saleem, where are you today?

• 1:42Speaker 04

  I'm at Garolos Airport in Sao Paulo, about to fly back. I did a talk today for Adam McKinsey's forum to a couple hundred of their CEOs.

• 1:52Speaker 00

  And do they feel excited or do they feel like they're at death's door?

• 1:56Speaker 04

  Pretty much freaked out is the general mood of the day.

• 1:59Speaker 05

  I hate to break it to you, but it's dead middle of winter. You're missing summertime in the northern hemisphere.

• 2:06Speaker 04

  That's why I was asked.

• 2:09Speaker 00

  And Imad, how about yourself? Where are you, pal?

• 2:11Speaker 03

  I'm in Copenhagen today.

• 2:13Speaker 00

  Copenhagen.

• 2:14Speaker 03

  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.

• 2:24Speaker 00

  Wonderful, wonderful. Covered. 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. Saleem, you've been here, but Dave, Imad.

• 2:39Speaker 04

  Yeah, I'm currently bathing in this wonderful fluorescent light that you can see. Special effects for the singularity.

• 2:46Speaker 00

  Well, you look beautiful nonetheless.

• 2:48Speaker 05

  Peter, I thought that was your personal man cave. Were we actually allowed into that room?

• 2:52Speaker 00

  Of course.

• 2:54Speaker 05

  Turn the camera around. I want to see what it is. Probably a junkyard on the other side.

• 2:59Speaker 00

  Virtual background for everybody.

• 3:01Speaker 05

  I bet it's got all your IV bags of all of your.

• 3:06Speaker 05

  Yeah, nobody naturally looks that good. You're doing something.

• 3:09Speaker 00

  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.

• 3:19Speaker 04

  I have a crazy confession about it. Two days ago, I dragged Milan to another Rush concert.

• 3:26Speaker 04

  We drove down to Philadelphia because this is the last of the last great, you know, the Who, the Rolling Stones, Led Zeppelin. So I thought he had to see it. So selfishly, I took him and dragged him along and he was like, you're killing me, Dan. All these geriatric songs with aims with Rush t-shirts everywhere, but it was another epic event.

• 3:45Speaker 00

  You're a groupie. How do you feel to be a groupie?

• 3:49Speaker 04

  It's weird.

• 3:49Speaker 00

  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 Moonshooter, welcome back. Got to give love to our community. You know, we read your comments and the outpouring is amazing. I'm just 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."

• 4:31Speaker 00

  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 @moonshots_pod. And we put the clips and our podcasts on X. And really importantly, we want to meet all of you guys.

• 5:15Speaker 00

  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/ama and 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.

• 6:00Speaker 00

  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 sixth 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. Imad, Saleem, you know, just parsing through them.

• 6:42Speaker 00

  And you need to know, we parsed 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.

• 6:56Speaker 05

  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 that the storyline that we're capturing here will last for millennia.

• 7:33Speaker 00

  It's, you know, do you remember how slow it was?

• 7:38Speaker 05

  My life is so different than two years ago. I think 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, we'll all be like, wow, remember how slow it was?

• 7:52Speaker 02

  Yeah, I think we're like the first responders to the singularity.

• 7:57Speaker 00

  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 Tactical Guide for Generative Media gives you a complete blueprint for deploying Google DeepMind's models in production. Images, video, audio, all of it, real architecture, real results. Find the link in the show notes below.

• 8:25Speaker 00

  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

• 9:09Speaker 00

  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 what Sam actually had to say.

• 9:23Speaker 01

  And I thought when we got to GPT-4, which was back in 2023, I think, that very quickly after that, there was going to be much more disruption in software business speed and up for grabs right away than it 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 just has so much inertia. People keep doing the same things they're doing. They keep buying from the same, you know, 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 technologies humanity has ever invented.

• 10:08Speaker 01

  Society and the economy will adapt more slowly.

• 10:10Speaker 00

  Saleem, we've talked about the inertia of humans so much. What do you think about this?

• 10:16Speaker 04

  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 and our organizations and our institutions are linear. And Frontier Labs made the mistake of confusing technical possibility with institutional deployment. And that goes to 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 is very kind of swift, but way down in the ocean, regulatory government changes very slowly. This has good effects and bad effects.

• 11:01Speaker 04

  In our world, it's bad because it's slowing down the implementation of some of these things. God help me, it 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 were waiting for infrastructure, we were waiting for regulatory to catch up, could have done it in 10 minutes.

• 11:17Speaker 00

  Sao Paulo needs it bad, for sure.

• 11:19Speaker 04

  Lots of places need it bad, this is one of the worst. And I think the big work now is how do we accelerate institutional acceleration and institutional development? As the word I think Alex uses is coscaling, right? We have to scale our organizations and our institutions to keep pace with the technology because it's not slowing down and that gap is where all the stress is coming from. So for me, 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 what we, that is the breaking point. We're kind of there now.

• 11:54Speaker 00

  Alex, you sent me this story. What are your thoughts about Sam's comments?

• 11:57Speaker 02

  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 as 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

• 12:38Speaker 02

  an electric engine 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,

• 13:21Speaker 02

  I can't quite tell either bemoaning the lack of fast progress while also paying homage to the lack of fast progress as somehow being helpful.

• 13:29Speaker 00

  I think he's in relief. I think he feels relieved by this.

• 13:31Speaker 02

  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. So, 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.

• 14:15Speaker 02

  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.

• 14:26Speaker 00

  And I think we're seeing a lot of the labs beginning to vertically integrate. I mean, everybody, we'll talk about a story here where Nvidia is beginning to vertically integrate. Ahmad, do you agree with Sam?

• 14:38Speaker 03

  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 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.

• 15:22Speaker 03

  You think about math, O3 was the first model a year or so ago that I could use, small. GPT 5.6 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 iMessage, 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 GPT 4. Can you imagine using GPT 4 in a codebase? You don't remember that? Or even for any institutional process, like it's a good thing there wasn't a diffusion of innovation there because otherwise companies would fall apart. And like, you know, as Alex says, sometimes he says two things at once.

• 16:06Speaker 03

  I think OpenAI 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.

• 16:22Speaker 00

  Dave, your thoughts, please.

• 16:24Speaker 05

  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 starry eyed before the singularity kicked off and then his house got firebombed, you know, with a 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 will last, but as of right now, we're just telling you as it is. But, 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.

• 17:08Speaker 05

  And, 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 OpenAI? 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.

• 17:38Speaker 00

  They're pre-IPO, so they're going to say what it takes to calm the masses out there to some degree. You know, the way I describe it, Alex and Ahmad, 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 nonlinear, 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, and get in the middle.

• 18:19Speaker 00

  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, that interface loop at that, you know, impedance mismatch point, it breaks very quickly.

• 18:37Speaker 02

  I was going to make some stupid joke about reflections happening at impedance mismatches, but I, 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. OpenAI and Anthropic largely have an oversupply of intelligence or superintelligence. And 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.

• 19:19Speaker 02

  And right now, the clearing of supply meeting demand, the, the two curves from economics 101 crossing each other, aren't necessarily crossing for all cases at a favorable point. And that's, I think, maybe through a more economics-y lens, what Sam may be gesturing at.

• 19:35Speaker 05

  Well, just to put sci-fi lens on this too, I think that there, 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, 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.

• 20:12Speaker 02

  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 a 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, with transcendent superintelligence, I completely agree with the sentiment that replacing human labor lasts for about five minutes and then you move beyond that.

• 20:48Speaker 00

  Yeah.

• 20:49Speaker 05

  And the guy is really interesting to watch the guys, you know, Sam also has moved on beyond that in a heartbeat, you know, a couple of events and a couple of 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.

• 21:08Speaker 00

  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, you know, 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.

• 21:34Speaker 05

  Even like if I think about insurance, though, just as a, because I'm, you know, I'm the 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 new things, all these data centers, all these robots, the new insurance categories that AI is generating are bigger than the legacy insurance industry.

• 21:56Speaker 00

  Yeah.

• 21:57Speaker 05

  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.

• 22:12Speaker 02

  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 up stack or down stack? I think it's actually more ergonomic for them to go down stack and design their own chips and compete with Nvidia and design and operate their own data centers and energy.

• 22:39Speaker 00

  I think they're gonna do it all. And Alex, you called out a number there I was about to reference as well. We just saw, you know, Dario or Anthropic state that their total addressable market is $30 trillion.

• 22:51Speaker 02

  I wonder where that number came from. Surely it's pure coincidence that the GDP of America is 30 trillion.

• 22:57Speaker 05

  Yep.

• 22:59Speaker 00

  All right. I'm going to move us on. Our next story, let's talk about Grokbot. So first it was OpenClaw, then there was Hermes, and now there's Grokbot from SpaceX AI. So Grokbot launched on August 11th in an early beta. It's Elon's entry into the agentic AI space, and it's the most genuinely useful consumer AI product that I've seen this year. So I implemented Grokbot. 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 Grokbot like you'd message a colleague, not a chatbot. A chief of staff, you know, sits on top, in which case for me, it's Skippy,

• 23:42Speaker 00

  with specialists on sales, operations, research, engineering, you know, any subagents 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 Grokbot. It's been flooding the internet. Has anybody here played with it yet?

• 24:02Speaker 04

  I've been playing quite extensively with it.

• 24:04Speaker 00

  Okay, what do you think?

• 24:06Speaker 04

  I love it. I think the interface and the ease of use is fast, is 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, it's 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 EXO, right? This is that taken to its logical extreme where staffer, staff recruiting time and coordination costs has gone to like pretty much zero. So the, when I'm looking at it from my book perspective, the optimal organizational structure completely changes. Humans set objectives and leave

• 24:51Speaker 04

  everything else to the AI.

• 24:53Speaker 00

  Amazing. Imad, have you played with it?

• 24:57Speaker 03

  Yeah, I have. I've got 18 Grokbots working in a little 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. So where is that from? Where is it getting its aesthetic responsibilities?

• 25:42Speaker 03

  So if you look at the chat and just share that.

• 25:44Speaker 04

  When it comes up with the banana with a piece of tape, then you'll get worried.

• 25:49Speaker 03

  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's 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 like the new GLM model, and another one's installing and testing Alibaba model. One of them is optimizing the Alibaba 27B model to run faster on a 5090. So added 76% to performance at 64K context.

• 26:32Speaker 00

  Love it. You know, 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?

• 26:50Speaker 05

  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 Swarmit 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 use a workforce of six, and then 50, and then 1,000. 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

• 27:32Speaker 05

  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 a handle on it.

• 27:44Speaker 04

  This is what I mean by the organizational singularity, because the company's structure is less than, less like an org chart, and more like a continuously orchestrated intelligence network. And that is such a big shift. It's like ridiculously big compared to everything we've ever done.

• 28:00Speaker 02

  I'll give you a hot take on this.

• 28:01Speaker 05

  It's very easy. Sorry, go ahead, Alex.

• 28:03Speaker 02

  I don't actually think.

• 28:04Speaker 00

  What's your hot take, Alex?

• 28:05Speaker 02

  Hot take. People love the hot takes. I don't think this is actually the interface of the future. So what's perhaps most interesting about Grokbot is it presents like a messaging app, like WhatsApp or iMessage, where you have a pane 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 unscalable. 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

• 28:49Speaker 02

  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. Well, we'll look at this like Vaudeville, the Vaudeville era of agents, and say, this was a naive attempt to graft human organizational structures onto humans managing agents. The only better manager for agents is other agents, and this doesn't seem to fully internalize that lesson.

• 29:19Speaker 00

  Saleem, what do you think about Alex's comment?

• 29:23Speaker 04

  I think it's a, I agree with Alex on the interface comment. This is a plugin UI that's temporary. I love the way he says it presents like, as if 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 go rotate through a whole set of these. But I think the core comments are as usual with Alex are absolutely dead on.

• 29:52Speaker 05

  Yeah.

• 29:52Speaker 02

  It's maybe it's an illness for which the medication that I prescribe is a good dosage of the bitter lesson pill.

• 30:00Speaker 00

  Yeah, I also think this is what humans are ready to play with. Right?

• 30:04Speaker 04

  Exactly.

• 30:05Speaker 00

  I think that, you know, again, it's moving people along the process. If you provided, if you provided something that was, you know, completely different, I think there would be less adoption. And so it's incremental.

• 30:17Speaker 02

  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.

• 30:31Speaker 04

  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 the 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.

• 30:58Speaker 00

  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, Grokbot videos. If you haven't seen his Grokbot 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 Grokbot is still the hottest thing in March of 2027 at the abundance summit, teach that if it's not, teach whatever's 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 Grokbot and we'll see. Let's move on to our next conversation, which is Google is back.

• 31:39Speaker 00

  So Google's Gemini 3.7 flash just took the top spot on AI, AA 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 on the slide here, Gemini 3.7 flash achieved a 60% pass rate, beating Claude Opus 5 at 54% and Fable 5 at 49%.

• 32:24Speaker 00

  So Alex, you know, many times, you know, you've said, others have said, you know, Gemini is 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, is, 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, with a fast furious punch to try and take the top position. What do you make of this, Alex?

• 33:03Speaker 02

  Do you want me to reassure you that Google still has a chance? Or do you want me to, to give you the, the facts unvarnished?

• 33:09Speaker 05

  Yeah, you got posts there pretty hard. Defend yourself, Alex.

• 33:12Speaker 02

  Okay, so I'll, I'll give you the unvarnished case here. Google's still out of the running for the capability frontier. I was looking at this.

• 33:19Speaker 05

  I didn't expect that. Okay.

• 33:21Speaker 02

  Scratching my head, like Gemini 3.7 flash is nowhere near the, 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.

• 34:03Speaker 02

  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, it, 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, 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 is obviously there are a few other factors. But I think Google, Google deep mind has been under material pressure to optimize their models

• 34:45Speaker 02

  for two things largely owing to Google search. So if we rewind the, 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 at all? And Google's response was to self disrupt by building the Gemini series, or at least some flash variants 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.

• 35:27Speaker 02

  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

• 36:00Speaker 00

  Benchmaxing.

• 36:01Speaker 02

  underperforms. Yeah, it's benchmaxing for basically spreadsheet analysis to be highly reliable.

• 36:06Speaker 00

  Ema, do you agree?

• 36:09Speaker 03

  Um, 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 construct anytime modality of data and flashes are 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 accuse 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.

• 36:53Speaker 03

  Cause 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 you know, 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 LM stuff is continuing to be fantastic. But aside from that, again, they've been falling behind in everything except for Omni modal. And video, they're still actually quite accurate. But given then, the Chinese are coming for their lunch. Like, why not just post train on Chinese models at this point if you're Google?

• 37:29Speaker 02

  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. You think Google has all of the, the compute, the CPUs, the TPUs and the GPUs in the world? It's been widely reported at this point. They, they have internal regular meetings to try to apportion out their scarce compute. And that the three main constituencies in, inside Google that are fighting for, for the flops are, one, Google cloud platform, which is basically fighting on behalf of external users. Two, Google deep mind 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, so my, again, my theory of the case here is there actually is resource starvation inside Google.

• 38:14Speaker 02

  And as a result.

• 38:15Speaker 00

  We've talked about this over and over again. 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.

• 38:29Speaker 02

  Critically, Google has other consumers fighting for their own compute internally besides AI. Whereas if you're OpenAI or Anthropic, no, you don't have any other non-AI users fighting for it.

• 38:41Speaker 00

  Fair enough.

• 38:42Speaker 03

  But Google's landing like 3 million TPUs this year. Like, I think there's relative levels of compute strength. 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 sourced 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 chips. It requires 2 to 4,000.

• 39:24Speaker 05

  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.

• 39:38Speaker 03

  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 GLM 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?

• 39:57Speaker 05

  Well, and then, 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 Kimi, do the rational thing and then tune it. You know, you can't say that because you, 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.

• 40:26Speaker 00

  So guys, who's in the US closed labs, right? Between OpenAI, Anthropic and, and Google and XAI, who's in the best position here? I mean, who has got?

• 40:40Speaker 02

  Now or two years in the future?

• 40:42Speaker 00

  Now.

• 40:44Speaker 05

  Gotta be Anthropic.

• 40:46Speaker 02

  Yeah, right now Anthropic has the strongest, forgetting about price or perform or, you know, time wall clock, Anthropic has the strongest model that's generally available, Fable 5.

• 40:55Speaker 05

  There are hordes and hordes of it.

• 40:57Speaker 00

  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.

• 41:11Speaker 05

  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 like 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 Anthropic and Elon are like, I don't know. It's a really interesting race.

• 41:46Speaker 00

  I just want to give our listeners an understanding of sort of the, you know, sort of the terrain out there. We've got, you know, the US labs competing against each other and the Chinese labs continually pummeling them. And we're going to talk about that in a moment. So, yeah, I mean Anthropic's the most advanced, but their compute, they don't own their compute, which is a problem.

• 42:06Speaker 03

  I would disagree with Anthropic being the most advanced.

• 42:09Speaker 00

  Who do you believe?

• 42:10Speaker 03

  OpenAI. OpenAI, aside from the Chinese labs, own the Pareto frontier. From lunar now being free to everyone, to, again, as a mathematician, GPT-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.

• 42:31Speaker 05

  Yeah, yeah, totally right.

• 42:33Speaker 03

  GPT-5.6 Pro is the only proper frontier model.

• 42:35Speaker 05

  Totally right. Yeah, we switched over to Sol, actually. Everybody over here is like, God, this Fable has lost its mind. But, but, you know, the, the argument there is that, well, inside Anthropic, they have Mythos 2 now. So they're another level ahead and they won't release it to us. Oh, maybe, we can't tell. But for our use case, you know, on hard problems, hard engineering and hard math, yeah, we switched everything over to Sol. So you totally agree, Ahmad.

• 42:58Speaker 03

  Even if it was Mythos 2, again, you would see them releasing low hanging breakthroughs, which the OpenAI have done with Astra. And OpenAI, 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 of 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.

• 43:38Speaker 05

  Yeah, didn't Alex say he actively hates Opus 5?

• 43:41Speaker 03

  I said, I said that.

• 43:43Speaker 05

  Oh, that was you?

• 43:43Speaker 02

  I did say I don't like Opus 5. I prefer Fable 5. But I think the, the truth on the frontier is materially more nuanced. Like, again, if you look, Ahmad, for example, at frontier math tier four, it is the case that Fable 5 outperforms ironically OpenAI's latest solid model, even though OpenAI was the primary sponsor behind Epic developing the frontier math tier four model. So I think the, the truth is a little bit blurry in part because the frontier isn't zero dimensional. It's, 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

• 44:27Speaker 02

  get better performance at a different point on the optimal cost frontier by, say, using Sol.

• 44:33Speaker 00

  I just want to point out to everybody listening, it's not, it's not obvious, right? There, there is a lot going on. And then we're seeing China constantly leapfrog. So, Saleem, you ready to say?

• 44:46Speaker 04

  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 is 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.

• 45:23Speaker 00

  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.

• 45:33Speaker 02

  When frontier labs compete, you win.

• 45:35Speaker 00

  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 US needs a powerful open weight model to contend with what's coming out of China. And this week, Nvidia is stepping up, pouring $6 billion into developing an open source AI model and inference infrastructure, designed to give US developers a domestic alternative to Alibaba, DeepSeek and Kimi. The deal struck between Nvidia and the AI startup Poolside aims to build one of the world's most powerful open weight models. By building its own open weight model, Nvidia is moving up the stack. We've discussed this from silicon to software, positioning itself not just as a chipmaker for AI, but as a

• 46:17Speaker 00

  platform provider for open weight 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. Ahmad, let's go to you first. What are your thoughts on Nvidia and Poolside?

• 46:36Speaker 03

  Yes, I've been talking to some of the investors out here, like this tech barbecue conference who invested in Poolside originally. They tried to raise $2 billion at the end of last year.

• 46:46Speaker 00

  So who is Poolside, first of all?

• 46:48Speaker 03

  Poolside is a company, I believe it was the ex-GitHub.

• 46:52Speaker 05

  Yeah, the former CTO of GitHub.

• 46:54Speaker 03

  Former CTO, Isakant and others. They set up and they wanted to originally create a coding model, then they moved to an open source model and model factory called Laguna, that outperformed Thinking Machine's 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 acqui-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

• 47:39Speaker 03

  did actually was they hired, and I don't think it's been announced yet, Ashish Wyswani'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 and 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 Co here and others won't be building open source models anymore. They'll be building to the Nvidia reference design.

• 48:21Speaker 00

  Alex?

• 48:22Speaker 02

  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 hack acquisition, now they're, they're finally sort of turbocharging their own nematron community. 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, the, my original take on this was this is just an attempt to avoid regulatory scrutiny or antitrust scrutiny. But I've started to see now some

• 49:06Speaker 02

  of the other acquisition targets come back to life, the, 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.

• 49:49Speaker 00

  I mean, there's a lot of pressure for the US to develop top tier open source platforms right now. Dave, what are your, what's your take?

• 49:56Speaker 05

  Yeah, curious, Alex, you said kind of quickly there, you're surprised that acquisitions need to exist in this day and age. But I got calls from both Merkour and from Orin, our good buddy Kush Bhavaria, 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?

• 50:28Speaker 02

  Well, so I would distinguish between talent acquires or acquihires on the one hand, which are largely about getting talent and hackwell hires with an H that are about, at least ostensibly, avoiding antitrust scrutiny. So if you're Nvidia and you want to hackwell hire, say, Poolside, you're going the hackwell hire route rather than just doing an honest to goodness either asset acquisition or conventional acquisition of Poolside because you want to argue, no, actually, we're just a licensee of Poolside 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.

• 51:09Speaker 05

  Okay, okay. Gotcha. I got a very specific answer to that, too. Remember the Wind Surf deal, you know?

• 51:13Speaker 02

  Of course.

• 51:14Speaker 05

  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 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 frickin' billion-dollar model or $6 billion model. That's all I need. Let's go. And then they can, you know, close the deal like Elon did with Cursor, close

• 51:55Speaker 05

  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.

• 52:04Speaker 00

  Salim, you're smirking over there. What's up on you?

• 52:06Speaker 04

  I don't know. 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 the obstacle courses.

• 52:16Speaker 00

  But going back to the-

• 52:18Speaker 03

  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?

• 52:31Speaker 00

  Going back to the other point here is the verticalization of companies, right? So, I mean, XAI, SpaceX AI is the ultimate verticalization out there today. But here we see Nvidia, we've seen Anthropic and OpenAI also designing their own chips. Does every one of these companies ultimately become at least two layers, if not three layers?

• 52:55Speaker 02

  In other words, does Anthropic get a space station?

• 52:59Speaker 00

  No.

• 53:00Speaker 02

  Or a moon colony?

• 53:01Speaker 00

  You know, I think they'll be the only company left amongst all the governments. Is that what we learned? Yeah, they'll have everything.

• 53:09Speaker 03

  That's why they'll be American GDP, that's why.

• 53:10Speaker 00

  Yeah.

• 53:11Speaker 02

  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.

• 53:23Speaker 00

  Yeah. All right.

• 53:25Speaker 03

  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 Halapenio, 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.

• 54:01Speaker 02

  All right. Yeah, I 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 infra 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.

• 54:44Speaker 00

  I'm going to move us along here. So three stories this week that chronicle the challenges being faced by the US 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 Kimi. 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 Kimi Linear, a new architecture that cuts context memory by 75% while still delivering 6X faster

• 55:22Speaker 00

  decoding for a 1 million token context window. Moonshot AI just dropped this and it's running and in a single move, an 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, Anthropic's flagship model, is now struggling to attract users. It's effectively plateaued. And the reason is simple. Cheaper Chinese open weight models are eating the market from bottom up. And when the model costs 14 cents per million tokens compared and delivers 80% of the capability compared to 15 bucks, the market chooses the less expensive option, at least in the

• 56:06Speaker 00

  jari 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

• 56:50Speaker 00

  here. Kimi Linear, you know, the challenges that Fable is having, and the changes that Anthropic made on its data retention policy. Dave, you want to jump in first?

• 57:02Speaker 05

  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 embarguing, like, 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

• 57:44Speaker 05

  any company that they don't know 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 Soul also inside a secure environment where it doesn't get transmitted to OpenAI. So you can, 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 need, I feel like I need to inspect everything to know that it's safe. So now he's, 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, if he has what it takes to do it.

• 58:27Speaker 00

  Ahmad, what do you think of Kimi Linear?

• 58:30Speaker 03

  Yeah, I mean, first, we banned the faster silicon from China. So they built MOE models to take advantage of cheap DRAM. Then the DRAM became expensive. So then they figured out better mechanisms of linear attention, of caching and more, more dense models, et cetera. And now you've just seen, actually, just a couple of hours ago, this new O1 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 Huawei chips. So I think, you know, you'll see the adoption of these Chinese models and then moving to where the market

• 59:14Speaker 03

  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 OpenAI did of 120 billion, and have a straight shot at AGI. That's what they should do. And they should stay private like Stripe.

• 59:58Speaker 00

  That's a fascinating thought. Yeah, I mean, why, why are they racing to an IPO?

• 1:00:04Speaker 03

  It makes absolutely no sense to me. Like, Dario owns 2% of the company, as does his seven co-founders. They don'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 access money privately, which I think they can.

• 1:00:23Speaker 00

  I have an answer.

• 1:00:24Speaker 04

  They need the capital to get compute.

• 1:00:27Speaker 00

  They could raise the capital. I bet you people would throw money at Anthropic.

• 1:00:32Speaker 04

  So I've been talking, I've been talking to investors, and Dave, this will be interesting from your perspective. Nobody knows how to price this thing because they don't have a secure long-term compute like OpenAI has, or that natively Croc or Gemini has. Therefore, this is why, to our earlier point, this is why people are verticalizing. Because if you're one layer and the bottleneck goes down below you or above you, you're screwed. So you have to have access to the whole layer to stop, to have a continual progress.

• 1:01:03Speaker 00

  Yeah, but even if they had the money to buy compute, where are they going to buy it from? There's not enough compute being manufactured.

• 1:01:11Speaker 05

  Before we get to that, there's a, 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

• 1:01:56Speaker 05

  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, go do, you know, put it off indefinitely. That's, that's fine. So he's, like, this is the stress test for Dario. He can't, he can't just wuss out right now. And that signaling would be terrible. Alex, AWG, your thoughts, please?

• 1:02:30Speaker 02

  Okay, well, first on, on the race to IPO, I think there is also a race element. I think there was a starting gun a few months ago between SpaceX, OpenAI, 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 to IPO, the market winds 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, Kimi linear. We've known about Kimi linear attention since last fall. I think it's, it's suggestive, as I've suggested in the past, ship of Theseus style, transformer

• 1:03:15Speaker 02

  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. 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 OpenAI 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

• 1:03:57Speaker 02

  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 frontieriest 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 OpenAI 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

• 1:04:41Speaker 02

  on average to know how to use Fable 5 on average properly, just like consumers didn't know how to use reasoning tokens from OpenAI. And as a result, OpenAI had 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, 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

• 1:05:22Speaker 02

  you read, maybe Fable 5.1 may be starting to leak out. And then very quickly on Anthropic 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 Anthropic's 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 hosting 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

• 1:06:06Speaker 02

  think it's useful in the long term. But starting to move more and more of the, 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 OpenAI copying Anthropic and doing that.

• 1:06:24Speaker 00

  What do you guys make of the, you know, the idea that the open source Chinese models are good enough and at a, you know, de minimis fraction of the price, and companies are beginning to shift in that direction, saying, we're not going to use Fable 5, it's too expensive. Dave, is that an experience you're having?

• 1:06:42Speaker 05

  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 notch. 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. So, and, 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, and so that's like a runaway train, you know? I, I think that's what's really going on. It's not, 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.

• 1:07:22Speaker 03

  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 today, scores 57, and it is like 100 times cheaper.

• 1:07:38Speaker 05

  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 1,000 or, you know, this is why the swarm is such a big deal. You can afford 5,000 or 10,000 concurrent Chinese operators instead of one Anthropic.

• 1:08:02Speaker 03

  Well, I think it's like, 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. Because maybe I'm not smart enough to ask Fable the right questions, but I'm just about smart enough to ask GPT-5.6 all the right questions.

• 1:08:23Speaker 05

  But also, you know, that analogy is perfect because people misuse their context window horribly. And I do, too. 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 and thousands of these for, you know, a very low cost. And that's, that's where the puck is going.

• 1:08:50Speaker 02

  I'm not sure how sustainable this, this situation is. I, I almost want to analogize it now to US importing generic drugs from Canada. The, the drugs get invented in the US, they get manufactured cheaply in Canada. And then, at least historically, it's been the case that, that you could get American drugs more cheaply from Canada by, by importing on or off label than you could from American drugs. I, I think the situation may be somewhat analogous here where these are US models, US reasoning traces. You see Chinese labs benefiting legally or illegally from the reasoning traces from interacting with US models. And then just in the past 48 hours, we start to see stories of Chinese labs trying

• 1:09:31Speaker 02

  to strike partnerships with US hyperscalers to host the Chinese labs, models on US infra, but with a rev share from the inference costs going back to the Chinese frontier lab. So this is a case where US 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, it's a perverse bind that we find ourselves in, analogous to Chinese drug imports, or sorry, Canadian drug imports.

• 1:10:08Speaker 04

  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.

• 1:10:14Speaker 05

  Yeah, it held until about a year ago.

• 1:10:15Speaker 00

  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 a AI that has no feed, no swiping, no infinite scroll. You fill out a values questionnaire and then every Wednesday at 7:00 PM, 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

• 1:10:58Speaker 00

  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. Saleem, 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 are your thoughts here?

• 1:11:25Speaker 04

  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 an interface, it's deleting the interface. Right? Tinder optimized searching and captions and so on, but this makes the searching a necessary, and I think that's really a powerful user interface experience where people are going to go, let the app 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 twenties is the obvious question. But you have to deal with that abundance in a different way.

• 1:12:09Speaker 04

  So this is the, this is the really fascinating thing. I'll watch this very carefully to see where this goes.

• 1:12:14Speaker 00

  Yeah, this is the abundance thesis applied to dating. Dave, what do you make of it? Is this a company you would have backed?

• 1:12:20Speaker 05

  Oh, God, yeah. Yeah, yeah, absolutely. But I think this is a stepping stone to AI helping you manage your life and your choices in general.

• 1:12:28Speaker 04

  Bingo.

• 1:12:29Speaker 05

  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.

• 1:12:39Speaker 00

  Yeah.

• 1:12:40Speaker 05

  Because it's such a great salesperson. So this is a good, 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? So.

• 1:12:52Speaker 00

  Yeah, I've always said, you know, in the future, advertising model is gone because your AI knows you so well. It's like, like, please just buy me the stuff I need. I don't want to, I'm in decision fatigue. I'm in data overwhelm. Just take care of it for me. Imad, your thoughts?

• 1:13:07Speaker 03

  Yeah, I, 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'd be like, you can't argue with your AI. It knows best, right? All watched over by machines of love and 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.

• 1:13:49Speaker 03

  And I've been 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 where you're like, this is human.

• 1:14:02Speaker 04

  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, and 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 can detail the cast, the clothing requirements, the salary requirements, and boom, off you go for the matches. So this is going to be really interesting to apply to that world.

• 1:14:34Speaker 03

  You have to have an exponential organization, Saleem. Come on.

• 1:14:38Speaker 04

  Dying desk, you would.

• 1:14:40Speaker 00

  Alex, I think you're the only one amongst us not married, so, you know, would you try this out?

• 1:14:45Speaker 02

  No. I, 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?

• 1:14:54Speaker 00

  No, tell me.

• 1:14:55Speaker 02

  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 Ditto 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.

• 1:15:20Speaker 00

  Seriously.

• 1:15:21Speaker 02

  This is low, 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.

• 1:15:33Speaker 00

  Yes.

• 1:15:34Speaker 02

  Could be solving everything, and instead we're doing body count detection. So this one gets a thumbs down for me.

• 1:15:38Speaker 00

  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, 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, in, 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 two people accurately is a different thing. But I think there's something there.

• 1:16:22Speaker 00

  But I do agree, Dave, that this applies to so many different areas. And Saleem, I know at the Abundance Summit, right, we have 600 CEOs, and we're, by the way, we're now 90% full for Abundance 2027. If you're interested, you can go to abundance360. Matching the CEOs, matching the entrepreneurs there is one of the most important things we do, and using AI 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, there is a value proposition to be had there.

• 1:16:56Speaker 02

  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, the early Facebook days. I just think we could be aiming so much higher as a civilization than AI for this.

• 1:17:15Speaker 00

  Yeah, listen, you know, the divorce rate in the United States is 50%, which is, which is crazy. And I think, you know, helping you discover the right person, now, the parameters it 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.

• 1:17:40Speaker 05

  Yeah, I'd love to know, Alex, how you reconcile, this is a waste of tokens, we should be solving a disease with those tokens.

• 1:17:46Speaker 02

  Not a waste, a suboptimal use.

• 1:17:48Speaker 05

  Okay, okay. Because, because one of the terms you've coined in this great revolution is patrio schmarker schmuser schuser. What is, what is that thing?

• 1:17:58Speaker 02

  Patrizier Musa.

• 1:17:59Speaker 05

  Yeah, you can't even say it.

• 1:18:01Speaker 02

  No, no, that is off, off, off, off. Patrizier Musa.

• 1:18:06Speaker 00

  Alex loves neo-Logisms. If you haven't seen it, he's publishing new terminology for the singularity almost every day. Yeah.

• 1:18:16Speaker 05

  You do need a token budget for, for that concept, you know? So how do, how do you reconcile those two?

• 1:18:20Speaker 02

  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 may, 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.

• 1:18:37Speaker 05

  I like the, I like that view. I think when, once you've solved basically all major diseases, that's probably a good time to start.

• 1:18:43Speaker 02

  The line of the song is that once the day had been solved, the day hasn't yet been solved.

• 1:18:48Speaker 00

  Okay. All right, guys, I'm, I'm going to move us on. But it's a, it's a fascinating concept, and I, I hope Ditto works, and there are many happy relationships that come out of it.

• 1:18:57Speaker 06

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• 1:20:02Speaker 00

  One more AI story before we move on to robotics. And it's a Wall Street Journal article that confirms what all of us are feeling, that AI is making us work harder at a level like never before. I joke, people are talking about a three and four day work week, 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. And the founder used to manage five tasks, now manages 50 agent outputs. The bottleneck has shifted from execution to judgment.

• 1:20:43Speaker 00

  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 produces 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. Saleem, over to you, pal.

• 1:21:08Speaker 04

  This is Jevon'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 EXO book, Peter and I did that together, it was three years of hell. Second book was two and a half years of hell. Third book was six months of 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,

• 1:21:51Speaker 04

  we've reinvented middle management, it's inside your own brain. Right? So this is, this is, it's going to cause a huge problem because you can't have machines operating at machine speed and requiring a human approval on that. So I'm actually facing this from all the stuff I'm trying 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, escalation thresholds. We're actually designing that. BCI maybe at the individual level, but where, you know, 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 whole new threshold of escalation thresholds, governance, et cetera, et cetera. Because companies need to decide what the machines may decide autonomously and what

• 1:22:36Speaker 04

  they want to manage later, what gets 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 that pace of that, right? So more capability, more, the more capability doesn't mean more freedom, but I'm actually, I'm burning, the candle is 16 men's right now. I'm loving it, but I'm not sure how long I can last at this pace. And you guys aren't helping, I will say.

• 1:23:07Speaker 00

  So can I just ask, you know, Dave, you know, Ahmad and Alex, is it the same for all of you, working harder than ever?

• 1:23:13Speaker 05

  Gotcha, 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 forever. And you know what's really frustrating to me is actually I've been recruiting some incredibly talented people for Quantum AI, and we lost an MIT Core 61 guy who just decided he's going to go to the Princeton PhD 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

• 1:23:52Speaker 05

  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.

• 1:24:09Speaker 00

  Get out of the way.

• 1:24:10Speaker 05

  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 every minute of it. And I tell you, working with the AIs 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.

• 1:24:33Speaker 04

  It is fun.

• 1:24:34Speaker 00

  It's a blast.

• 1:24:35Speaker 02

  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.

• 1:25:12Speaker 00

  So isn't that an argument for just like, you know, lay down, relax, enjoy yourself for three years, and then jump in three years from now?

• 1:25:19Speaker 02

  No, it's an argument for work your tail off for three years and then go lie on the beach.

• 1:25:25Speaker 05

  I mean, if nothing else motivates 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 that otherwise wouldn't exist.

• 1:25:36Speaker 00

  Beautifully said.

• 1:25:37Speaker 05

  If that doesn't motivate you, Ahmad, you got to put a clip in here, too. This is the most important thing we've ever recorded. What are your thoughts on this?

• 1:25:44Speaker 03

  No, I mean, like, the amount of leverage you can do per unit of your attention now is more than has ever been, and other things 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 cognitology, 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, done a massive amount of research, and I've been in a 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.

• 1:26:29Speaker 03

  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 M-Ad 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. But 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 said, 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.

• 1:27:08Speaker 00

  Well, not to do college degrees, little, not PhDs.

• 1:27:11Speaker 03

  I would say you 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, a Thiel 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 and things, but show them what you create. Gather people, humans and agents.

• 1:27:32Speaker 02

  A skeptic would say, all right, Ahmad, you went where, Oxford, as I recall? Alex, you went where, Harvard and MIT? Dave, 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.

• 1:27:59Speaker 03

  Yeah, we didn't have AI at the time.

• 1:28:01Speaker 00

  It was a different time. It was a different time.

• 1:28:04Speaker 05

  That just makes you more credible in what you're saying than...

• 1:28:07Speaker 03

  I would actually say, I think undergraduate's still a lot of fun, and you don't really have to work that hard.

• 1:28:12Speaker 00

  Elon said this, it's a social experience. It's adult daycare.

• 1:28:16Speaker 03

  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 were math PhDs, and a couple of them had like, problems solved in 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, even consider it?

• 1:28:39Speaker 02

  I agree, I was speaking, I was speaking a few days ago to a 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.

• 1:29:08Speaker 05

  Well, I think this is the most important conversation we've had we've had yet.

• 1:29:11Speaker 02

  I spooked them.

• 1:29:12Speaker 05

  Flip this and circulate it right away.

• 1:29:13Speaker 02

  I spooked the heck out of them.

• 1:29:14Speaker 00

  Well, getting people to think is the most important. You know, why are you doing a PhD? A lot of people are doing a PhD because they're 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.

• 1:29:27Speaker 05

  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.

• 1:29:36Speaker 00

  Inertia.

• 1:29:37Speaker 05

  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 worked so hard to get there. But you got to pivot. You got to you got to just recognize the moment.

• 1:29:52Speaker 00

  Get into your Stanford PhD and say, OK, I checked that box, and now I'm going to jump into a company.

• 1:30:00Speaker 00

  Oh, well, it's 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.

• 1:30:41Speaker 00

  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 on people against data centers. It's been increasing, you know, almost, I guess it's a linear increase, but it's going to asymptotically 100%. And the post on water sender 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, you know, golf courses at $2 billion,

• 1:31:21Speaker 00

  three times as much, or power plants at $133 billion, or growing cattle at $137 billion. You know, the fact of the matter is 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.

• 1:32:05Speaker 02

  My worry is that that wouldn't help. My fear is that this isn't because people think data centers are unsightly or unesthetic. 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 US adversaries who would love nothing more than to slow down America's data center build out. 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.

• 1:32:45Speaker 00

  OK, agreed, Alex. But why isn't the, you know, you can counterveil that. When I was on with with Michael Kratzios, 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 his video last week, right? We're going to, you know, give you better schools. We're going to give you better access to 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 your 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?

• 1:33:31Speaker 00

  More job.

• 1:33:32Speaker 02

  The problem, though, is that in in the US way of doing things, the decision of whether to site a data center or not ends up being a local decision, not a national decision. Whereas in China, China can just declare, OK, 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 US, 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 a foreign adversary, worst case scenario, to polarize and to shut data centers out of terrestrial deployment.

• 1:34:18Speaker 00

  But this is false data. There's this is an outrage cycle in social media. This is people reposting.

• 1:34:25Speaker 02

  Shocked that foreign interference would leverage false data. Shocked.

• 1:34:29Speaker 04

  Wait, let me let me say a couple of things about this. Can I?

• 1:34:33Speaker 00

  Yeah, please.

• 1:34:35Speaker 04

  OK.

• 1:34:35Speaker 00

  Give us your wisdom.

• 1:34:36Speaker 04

  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 US 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. OK? Data centers are great hobbyists for this. This is happening everywhere. We've gone from, say, 50 years ago, show me the evidence and I'll form an opinion, to I have an opinion, now show me the evidence that confirms it.

• 1:35:17Speaker 04

  And therefore, and that's amplified radically with social media, because nuance has no viral coefficient. Because like this, this just doesn't actually work. So this is a very difficult problem solved, 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 to abundance, and measure it, compare it, put it in context, fix the externality, but don't legislate

• 1:36:00Speaker 04

  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 US.

• 1:36:10Speaker 05

  So then you want to hear something really, really cool?

• 1:36:12Speaker 04

  Yeah.

• 1:36:14Speaker 05

  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 is actually water negative and carbon negative.

• 1:36:27Speaker 00

  There you go.

• 1:36:28Speaker 05

  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 could 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 not, we're actually water negative and carbon negative. That's really, it's really cool.

• 1:36:56Speaker 00

  And I think I saw.

• 1:36:57Speaker 05

  But it shows you how little water they actually use.

• 1:36:59Speaker 00

  Alex, wasn't there a story recently about Nvidia's new chips and new data center structures that are actually utilizing less water now?

• 1:37:08Speaker 02

  Yeah, well, there's there's, news flash, there's no water in low Earth orbit. So that's the end game, I think. Just cut the the water nonsense out. This is only forcing all of these new data center deployments to sun synchronous orbit. We might as well just get it over with.

• 1:37:25Speaker 00

  Yeah, I mean, how? How intelligent was Elon's move? Prophetic.

• 1:37:31Speaker 02

  I think it was opportunistic. I think he 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 tea leaves.

• 1:37:41Speaker 00

  Amazing.

• 1:37:42Speaker 04

  Can I say something more? Can I just say one more thing? Just if I lift up a level to the to the rationale and the foundation of why this podcast exists, to reach evidence, we need to reach abundance, 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.

• 1:38:07Speaker 04

  And this is the fundamental foundational problem we have with civilization. As Alex said, this is why we can't have nice things.

• 1:38:13Speaker 03

  I reckon we should just rename them. Let's call them intelligence foundries, or call them compute citadels.

• 1:38:19Speaker 04

  Change the narrative. Thank you.

• 1:38:21Speaker 00

  It's got a branding problem.

• 1:38:22Speaker 03

  It's a branding problem. Again, this is not a factual thing.

• 1:38:25Speaker 04

  I have a better one.

• 1:38:26Speaker 03

  One of the funniest tweets I saw recently.

• 1:38:28Speaker 04

  I have a better one. AI churches.

• 1:38:32Speaker 03

  A computer's a little bit say I chat, come on.

• 1:38:34Speaker 00

  Fine, I'm sorry.

• 1:38:37Speaker 00

  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 Cybercab 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 Cybercab. This week, Waymo announced a significant redesign and cost savings. They announced details around their custom 5 nanometer chip

• 1:39:18Speaker 00

  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 Ohi vehicle, a purpose-built robotaxi minivan designed by Chinese EV maker, Zhiker. The Ohi costs $75,000 per vehicle compared to the $200,000 for the Generation 5 Jaguar. It's 42% fewer sensors, 13 cameras and four LiDARs compared to 29 cameras and five LiDARs.

• 1:40:02Speaker 00

  Yeah, and remember, you know, Elon made the point years ago that if a human driver can drive with just one eye, you know, 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, it's a pretty cool vehicle. Kind of not as sexy as the gold Cybercab, but take a look.

• 1:40:36Speaker 07

  After what Waymo calls its 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 costs 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.

• 1:41:19Speaker 07

  They've slashed the total sensor count by more than 40%, so 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 grime.

• 1:41:34Speaker 00

  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.

• 1:41:43Speaker 02

  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, that we, careful what we wish for with whoever here is suggesting that Google should just switch over to fine tuning Chinese models. 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.

• 1:42:25Speaker 02

  That's somewhat disappointing. It's also kind of interesting if you look underneath at the, 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, maybe Waymo wants its own space station at this point. Waymo is, is getting its own chips. It's OEMing Chinese hardware at the hardware layer. Maybe it's, 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.

• 1:43:08Speaker 02

  So I think we're starting to see honest to goodness, vertical 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 the high-end Roadster 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 it 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.

• 1:43:53Speaker 02

  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, for Chinese hardware or maybe American hardware, and their focus is entirely on software again.

• 1:44:10Speaker 05

  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 Mobsta companies are building AI chips and building AI models and building data centers. Every one of them. So they're all colliding into vertically integrated super companies. And, and they're just doing the entire stack.

• 1:44:47Speaker 00

  And robots next. They're all going to build robots.

• 1:44:50Speaker 02

  And meanwhile, TSMC is a sitting duck. TSMC is waiting to be verticalized.

• 1:44:56Speaker 05

  Isn't that amazing? It's like the, the linchpin to this entire thing and it's sitting there not doing anything.

• 1:45:02Speaker 02

  Right across the Strait of Taiwan, ready to start World War III at a moment's notice.

• 1:45:07Speaker 00

  Yeah. Imad, do you ever see these vehicles coming to Europe?

• 1:45:11Speaker 03

  Yeah, we're starting to see Waymo's in London and I think the regulation should be largely positive for them. But I was having dinner today with the Anzui's deep tech VC at Late Motif. And, you know, we're talking about something interesting like, because previous I said, you know, Tesla Optimus robot gets into a truck, opens the door, plugs itself into the phone chart, into the phone charger or the cigarette plug and boom, that's trucking job's gone. And I was like, well, actually, why wouldn't you have specialist robot drivers?

• 1:45:40Speaker 03

  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. The other side of that is that you fully vertically integrate. So Xiaomi just announced a Xiaomi 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 they're these kind of two things that are coming. But actually, I really got thinking about this humanoid driver robot.

• 1:46:20Speaker 04

  I love that idea. It's the first use case for a humanoid robot with two arms and two legs I've yet seen, so.

• 1:46:28Speaker 04

  I will, I will kneel to you, sir.

• 1:46:31Speaker 00

  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, 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, makes a lot of sense.

• 1:47:00Speaker 02

  It's vaudeville again, again, like lack of imagination, but also the ergonomics are such that we're 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, Saleem.

• 1:47:15Speaker 03

  Well, I think you've kind of got two things here. Like, so one is full vertical integration. The other is human shaped holes with humans, humanoids in it.

• 1:47:25Speaker 00

  All right, I'm going to move us on to the next story.

• 1:47:29Speaker 04

  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 when I talked about, why do we have humor? You said, oh my God, Saleem, that why the self-loathing? It was so funny. So I just love that. So I just want to reflect back on that.

• 1:47:45Speaker 02

  We love, we love our humanoid form factors.

• 1:47:49Speaker 00

  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, you know, up to almost two miles, landing on water, providing flotation 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 two 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.

• 1:48:47Speaker 00

  Pretty amazing, guys.

• 1:48:48Speaker 04

  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 applications are going to do more for public acceptance of AI than any like chat bot benchmark, whatever. It's such a great use case. I love this.

• 1:49:16Speaker 00

  Yeah. Alex?

• 1:49:18Speaker 02

  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.

• 1:49:58Speaker 02

  Similarly, maybe hopefully slightly better founded, I 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. Deminimus progress. I just think like we're getting lapped by China at this point.

• 1:50:40Speaker 00

  This is what Tam said. This is institutional inertia. This is the, you know, the existing players blocking their disruption. This is not a surprise.

• 1:50:54Speaker 02

  Not a surprise, but definitely a disappointment.

• 1:50:56Speaker 05

  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 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.

• 1:51:39Speaker 05

  But at least the AI labs are aware of it now and that hopefully they'll get on it. And we'll start to roll out like the lifeguard is such a no brainer.

• 1:51:46Speaker 00

  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, Imad, 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 Adcock 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 sort of collision between those

• 1:52:29Speaker 00

  who can 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.

• 1:52:39Speaker 03

  I mean, I think you will see lynching of robots and things. You will see people vandalizing like they vandalize cars, you know, like stealing them and all sorts of things. Yeah, 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 ubiquitous is. 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.

• 1:53:20Speaker 05

  This is what Alvin said. And I think, I think we, 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 US. 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.

• 1:53:53Speaker 00

  Dave, this is what Alvin said on that pod, 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.

• 1:54:08Speaker 02

  And we said, if they don't, they'll get invited by the CCP for tea. So we'll never hear from them.

• 1:54:14Speaker 05

  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 and it'll be a tragedy. But if we save, 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.

• 1:54:45Speaker 00

  Yeah. And if it bleeds, it bleeds.

• 1:54:48Speaker 02

  About, I just have to say about topics that are convenient to the government, not about topics that are inconvenient.

• 1:54:55Speaker 03

  Yeah, but I mean, 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 X Prize, things like that. You have to change the narrative because otherwise people are like, this will disrupt my job as opposed to the benefits of this side of things.

• 1:55:21Speaker 00

  There's so much reason for optimism. And we, I mean, that's what our mission here is to deliver that news to people and give them the data.

• 1:55:29Speaker 03

  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?

• 1:55:44Speaker 02

  All right. We are the Ministry of Superintelligence Truth for the West.

• 1:55:51Speaker 00

  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 that you're living a healthy lifestyle, that you get a chance to get to 100 plus. I'm here today with Dr. Don Musalem, the Chief Medical Officer of Fountain Life and a part of my medical team. Don, a pleasure.

• 1:56:17Speaker 08

  Great to be here.

• 1:56:18Speaker 00

  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?

• 1:56:33Speaker 08

  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.

• 1:56:58Speaker 00

  Wow.

• 1:56:58Speaker 08

  But what was really awesome is again, back to that prevention, when we 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.

• 1:57:20Speaker 00

  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 till 100, 120 is important to you, check out Fountain Life, go to fountainlife.com/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.

• 1:58:03Speaker 00

  Dave, you remember when we interviewed Elon at the beginning of this year, we did an epic three hour podcast with him and we're on schedule to do a end of year prediction podcast with him again. These are the numbers he used. You know, he said to implement Star Mind, you need 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 Star Mind 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 15 minutes? It's going to be awesome.

• 1:58:44Speaker 05

  And it's amazing that the numbers work as things are. You know, there's going to be huge innovation in 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.

• 1:59:02Speaker 00

  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 FA launch licensing, expand spaceport 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, getting those done, making sure that the wrong free, you know, 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.

• 1:59:45Speaker 00

  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 airline over none. So what this means is the incumbents, you know, VSAT, UTELSAT, Gogo, are going to get crushed out of existence. Thoughts on this, gentlemen?

• 2:00:20Speaker 02

  Few thoughts, maybe just starting with what I perceive to be the regionalization of spaceflight and space launch. So buried under, I think, the SpaceX story is Starbase Louisiana, the announcement of Starbase Louisiana.

• 2:00:36Speaker 00

  I was going to cover that in our next pod, but let's cover it now.

• 2:00:39Speaker 02

  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 starbase 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 starbases, 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

• 2:01:20Speaker 02

  start appropriating federal land for federal spaceports. And so if you pull the string a bit and ask, where are we likely to get federally owned land for spaceports? I don't know if folks want to guess what the likeliest candidates are. I think we're going to get a few of them. Any takers?

• 2:01:39Speaker 00

  Let's see.

• 2:01:41Speaker 02

  Where's all the federal land?

• 2:01:46Speaker 05

  Nevada.

• 2:01:47Speaker 00

  Nevada, yeah.

• 2:01:48Speaker 02

  Exactly. 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 spaceports. So I think we get in the American Southwest, we get federal spacebases or starbases, and on the Gulf Coast, we get private starbases, as it were. And that's how we get to this, like, 30,000 per unit time launch capability.

• 2:02:24Speaker 00

  You know, the reason historically all the launches were taking place out of Florida is you were dropping stages along the way, right?

• 2:02:31Speaker 02

  You want to be near the water, and you want to be near the equator.

• 2:02:34Speaker 00

  Yeah.

• 2:02:35Speaker 05

  And you have to go east, right? You have to go to the east.

• 2:02:38Speaker 00

  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 in populated areas. And of course, Starship is reused. 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 in a landlocked area.

• 2:03:00Speaker 02

  We're going to get landlocked starbases. Exactly.

• 2:03:03Speaker 00

  Yeah, and except for Israel that launches west for obvious geographic regions.

• 2:03:07Speaker 02

  Which way does California launch?

• 2:03:10Speaker 00

  North.

• 2:03:11Speaker 02

  North, interesting.

• 2:03:12Speaker 00

  Yeah, so you're basically...

• 2:03:14Speaker 02

  For polar orbits.

• 2:03:15Speaker 00

  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.

• 2:03:46Speaker 04

  We learned something every day on this podcast. We used to talk about, you know, I've never thought about launching north or south. That's how you launch up.

• 2:03:54Speaker 02

  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 reusability, we're about to have. And then any landlocked country, I mean, I guess you could probably talk our ear off about the former Soviet Union and how it located its particular launch sites, but with reusability, landlocked launch becomes a lot easier.

• 2:04:29Speaker 00

  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.

• 2:05:12Speaker 02

  Same cheers?

• 2:05:29Speaker 00

  Same cheers, yeah. Pretty crazy. You know, interestingly enough, 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 reusable rocket category by taking advantage of it.

• 2:05:50Speaker 02

  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 portfolios. Not sure whether he cares, but if he cares, maybe he wants to revisit that policy.

• 2:06:06Speaker 00

  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.

• 2:06:15Speaker 04

  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.

• 2:06:25Speaker 00

  Yeah, I don't think anybody's going to come close to beating them. We've also got the capital markets that enable SpaceX to really, you know, design and develop. And now that Grok, or the next version of Grok, 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 [email protected]. We want more of your creative genius. You guys open for a few AMAs?

• 2:06:56Speaker 04

  Just a few minutes before I have to rush to my boarding.

• 2:07:00Speaker 00

  Okay, we'll give you a first crack at this. Saleem, pick your first one.

• 2:07:03Speaker 04

  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 Boojin5455? 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 propagate through millions of agents almost instantly. But it also gives us a defensive capability, because we can cross-check this.

• 2:07:43Speaker 04

  Look at the benefit on X of people checking with Grok, whether something's wrong or not. It's creating a really viable conversational architecture where truth, maximally 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, AI with a bad meme. It's billions of AI sharing the same bad meme, because they all came from the same

• 2:08:26Speaker 04

  bad model or from the same original point. So 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 defensive co-scaling.

• 2:08:38Speaker 00

  I'll take number two. Is there an X Prize 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 X Prizes with a clear objective function, the first person to do this. I think honestly, the AI labs from, you know, the work that Demis Hassabis is doing and Dario is doing are working on this. I don't think an X Prize would accelerate it. So we don't want to get into the middle of something that's already in the process of being solved, we're looking for problems that are stuck. All right, Dave, over to you, pal.

• 2:09:14Speaker 05

  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 Plama Don 67637. I was just talking to a senior exec from Intel, asking almost exactly that same question. So I happen to know the answer. So Litbu has the company making a ungodly fortune on Xeons 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 just raised another 20 billion to build more fabs. The idea being get that capacity up and compete with TSMC as a general purpose fab company.

• 2:09:59Speaker 05

  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 TSMC competitive business to massive scale. So that's their strategy.

• 2:10:19Speaker 00

  There you go. All right, Emad, do we take number three?

• 2:10:23Speaker 03

  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 5CD? So there has to be 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 amyloid blasts up and running will be really useful in repairing teeth. But I don't think anyone's actually figured out a crack regrowing them fully.

• 2:10:59Speaker 00

  Alex, you want to layer on top?

• 2:11:01Speaker 02

  I feel like I have to take another bite at this question.

• 2:11:03Speaker 00

  Ha ha.

• 2:11:04Speaker 02

  Ha ha. So there is a drug out of a spinoff from Kyoto University called TRH035 that is targeting tooth regrowth, honest to goodness, tooth regrowth 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 this decade.

• 2:11:48Speaker 00

  Nice. I was gonna layer on top, but you got it. All right, Dave?

• 2:11:53Speaker 05

  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 Demis Hassabis. 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.

• 2:12:36Speaker 00

  All right, Emad?

• 2:12:38Speaker 03

  Let's see, if Dario wants super voting shares and control and ends up with a trust nobody elected, how does anyone actually get that power back at Dave Huth Harmon 03? I think that's the point. You're not gonna 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, it comes down to a few people like Ben Bernanke to decide the future of the lycan, potentially.

• 2:13:18Speaker 00

  All right, Alex, how about number five?

• 2:13:21Speaker 02

  Oh, really? Don't you want me answering number six?

• 2:13:24Speaker 00

  I'll take number six.

• 2:13:26Speaker 02

  Oh, really? All right. Okay, fine.

• 2:13:29Speaker 00

  I'm steering the conversation.

• 2:13:32Speaker 02

  Clearly. So Five asks, are we worried that non-AI research and development gets 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-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.

• 2:14:17Speaker 02

  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.

• 2:14:24Speaker 00

  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?

• 2:14:38Speaker 02

  That was my answer, Peter.

• 2:14:40Speaker 00

  Yes, I know it is. What makes you think Alex is a real human? I mean, listen.

• 2:14:45Speaker 02

  Approximately a year ago.

• 2:14:47Speaker 00

  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.

• 2:16:46Speaker 00

  All right, for all your outro video creators, again, send us at [email protected]. We have to start including Emad into those videos. Gentlemen, I guess we're gonna be recording in 48 hours from now. You know, no time to sleep.

• 2:17:00Speaker 02

  Good thing nothing ever happens.

• 2:17:02Speaker 00

  Yeah.

• 2:17:03Speaker 03

  I think I love a full document already for that one, eh?

• 2:17:06Speaker 00

  We do, we do. Amazing.

• 2:17:08Speaker 05

  Really?

• 2:17:08Speaker 00

  So much.

• 2:17:10Speaker 03

  You have to check out Nvidia results, man.

• 2:17:12Speaker 00

  Love you, guys. Be well.

• 2:17:15Speaker 05

  Thanks, Peter.