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

Sourced by podcast-ingest on 2026-08-28. Auto-transcribed via AssemblyAI (universal-2, en). Speakers identified by AssemblyAI Speaker Identification using the per-podcast host/regulars hints; the resulting label→name mapping is in the frontmatter. Duration: 2h18m. Episode page: (not provided). Audio: https://traffic.megaphone.fm/DVVTS1461313799.mp3.

Show notes (from RSS)

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.

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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

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*Recorded on August 26th, 2026

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Transcript

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

Alex: We've all been too ambitious on timelines. Even with this incredible technology, he now

Peter Diamandis: believes it will be something slower, more like a rising tide.

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

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

Imad: Yeah, I have. I've got 18 Grockbots working in a little swarm.

Peter Diamandis: This week, Waymo announced a significant redesign and cost savings. Waymo unveiled the Ojai vehicle, a purpose built robo taxi minivan designed by Chinese EV maker Zeekr.

Alex: 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

Peter Diamandis: now. That's a moonshot.

Dave Blundin: Ladies and gentlemen,

Peter Diamandis: 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 Blunden, Saleem Ismail, Imad Mustaq, and I've got to pause and ask, of course, where is Waldo? Saleem, where are you today?

Salim Ismail: I'm at Garulos Airport in Sao Paulo, about to fly back. I did a Talk today for Edm McKinsey's forum to a couple hundred of

Peter Diamandis: their CEOs and do they feel excited or do they feel like they're at death's door?

Salim Ismail: Pretty much freaked out is the general mood of the day.

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

Salim Ismail: That's why he's asked.

Peter Diamandis: And imod, how about yourself? Where are you, pal?

Imad: I'm in Copenhagen today. Copenhagen, yeah, but 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.

Alex: Wonderful, wonderful.

Peter Diamandis: 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. Celine, you've been here, but Dave. Yeah.

Salim Ismail: I'm currently bathed in this wonderful fluorescent light that you can see. Special effects for the Singularity.

Peter Diamandis: Well, you look beautiful nonetheless, Peter.

Dave Blundin: I thought that was your personal man cave. Are we actually allowed into that room?

Peter Diamandis: Of course.

Dave Blundin: Turn the camera around. I want to see what it look. It's probably a junkyard on the other side.

Salim Ismail: That's fine.

Peter Diamandis: Virtual background for everybody.

Dave Blundin: I bet it's got all your IV bags of all of your. Yeah, nobody naturally looks that good. You're doing something.

Peter Diamandis: 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. What's that?

Salim Ismail: I have a crazy confession of it. Two days ago, I dragged Milan to another Rush concert. We drove down to Philadelphia because 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, Dana. All these geriatrics on with pains with rushed T shirts everywhere. But it was your excuse event. He was my groupie.

Peter Diamandis: How do you feel to be a groupie?

Salim Ismail: It's weird.

Peter Diamandis: 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 Moonshotter, welcome back. Got to give love to our community. You know, we read your comments and the outpouring is amazing. I was going to read a few of the comments from the last pod here. Brian Anderson said, the best AI podcast on the Internet. Just fabulous. You guys are great. Elvis Cotena said, you guys are essentially chronicling the Singularity. What a fabulous resource for the future. Brian Clark said, Moonshots is the best content on YouTube, especially during the Singularity. Thank you for all you guys do and Brian and everybody, we greatly appreciate you. The best way you can thank us is take a moment if you haven't already and hit the subscribe button. You know our Moonshot on the Moonshots podcast is to 100x our growth and get to 10 million subscribers. So tell your friends, help share what we are talking about. What's going on during the Singularity. You know the best antidote for fear is knowledge and understanding. And that's what we try and deliver. Also, you can now follow us on X. Our handle on X is moonshotspod and we put the clips and our podcasts on X. And really importantly, we wanna meet all of you guys. So we're gonna be doing an AMA with everybody who registers. We're gonna do an AMA on Zoom. Come meet us all. Ask us your questions directly. If you wanna 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. Nvidia is fighting against the Chinese model domination with its own Opwait 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 don't, 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 and you need to know we parse through probably 400 stories to narrow it down to 15 or so. And we're podcasting twice a week and it's, you know, the speed is blinding.

Dave Blundin: I think that comment on chronicling the Singularity too is very poignant from one of, 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 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.

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

Dave Blundin: My life is so different than two years ago. Just minute by minute. I can't even tell you how different it is. And A lot of people haven't made that leap yet, but they will. You know, everyone will see it. A year from today, we'll all be like, wow, remember how slow it was?

Alex: Yeah, I think we're like the first responders to the Singularity.

Peter Diamandis: I like that. This episode is sponsored by Google for Startups. Think about this for a second. You now have access to the same generative AI models that cost hundreds of millions of dollars to train. Google's Startup Technical Guide for Generative Media gives you a complete blueprint for deploying Google DeepMind's models in production. Images, video, audio, all of it. Real architecture, real results. Find the link in the show notes below. Our first article is an interesting one here. Let me jump into it, because it's one that tells us that as fast as the technology is, it's hitting the reality of society and humans. So Sam Altman went on video this week to tell the world that he was wrong about the impact of advancing AI, that the impact is actually slower than he originally expected. And while Sam used to believe society would experience a dramatic disruption on the arrival of AGI, he now believes it will be something slower, more like a rising tide. Sam says factors like the economic inertia, institutional lag, the inability of humans to rapidly adapt to change are combining to slow the curve. Ultimately, the singularity, like you just said, Dave, is a process and not just a singular event. Let me share the video here and take a moment to see what what Sam actually had to say.

Alex: And I thought when we got to GPT4, which was back in 2020, I think that very quickly after that there was going to be much more disruption in software business being up for grabs right away than 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 company, they keep wanting to use their tools in the same way. I think that'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. Society and the economy will adapt more slowly.

Peter Diamandis: Salim, we've talked about the inertia of humans so much. What do you think about this?

Salim Ismail: 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 with two very, very different layers. You know, Stuart Brand had that concept of pace layers, where technology moves at one layer like an ocean current at the top. It's very kind of swift. They're way down in the ocean. Regulatory government changes very slow, slowly. This has good effects and bad effects in our world. It's bad because it's slowing down the implementation of some of these things. God help me. Just took me two hours to get to the airport just now. And passenger drones, which have been ready for a decade technologically, but we're waiting for infrastructure, waiting for regulatory to catch up, could have done it in 10 minutes.

Peter Diamandis: And so Paulo needs it bad for sure.

Salim Ismail: We have lots of places need a 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 co scaling. 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 become. 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. And we're kind of there now.

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

Alex: 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, 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 say you develop a new engine for a car, you develop 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, I can't quite tell either, bemoaning the lack of fast progress while also paying homage to the lack of fast progress.

Peter Diamandis: I think he feels relieved by this.

Alex: He has a way of sometimes like saying two things at once. So I think he's sort of expressing gratitude for the slowness while also bemoaning it. But if you want to go faster, this theory of the case is prescriptive. If you want to go faster, pull an Elon and vertically integrate to erase the barriers between abstraction layers. You do that and things can go much more quickly. If Sam or OpenAI want to move much more quickly, they should be much more vertically integrated so that they can move layers. Presumably he's gesturing at layers above the OpenAI model layer in the stack own, or at least vertically integrate more of that or go down a layer with Stargate. OpenAI has pretty publicly abandoned its original Stargate strategy of owning their own data centers. Now they're just leasing. If they want to see more transformative progress, go down a few layers and vertically integrate. Like with the jalapeno chips, own as much of this stack vertically integrated as they can. They can move really quickly.

Peter Diamandis: And I think we are 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. Imad, do you agree with Sam?

Imad: Yeah, I think a couple of points on this. First, I agree with Alex and kind of artificial intelligence meeting institutional stupidity and the stupidity text, 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. 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 the. This chat backed by actually competent intelligence, which has literally only been around now for maybe a month or two. So I think it's not surprising because I wouldn't use GPT4. Can you imagine using GPT4 in a code base, you know, remembering 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 said something, he says two things at once. I think OpenAI is trying to find its narrative right now. 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.

Peter Diamandis: Dave, your thoughts please?

Dave Blundin: Well, I'll give you a completely different twist on this because, you know, I interviewed Sam 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 lasts. But as of right now, we're just telling you as it is. But Sam woke up and said, well, my God, I literally can't get into the office because the picketers are lined up. Remember when we were there, Peter? Like you have to fight through the picketers to get to the door and now it's all armed security. So what happened in the interim is they woke up and realized society can't flip on a dime. And all this disruption that you're talking about, all these capabilities you're talking about are scaring many more people than are rallying to your cause. And that's why so many states are anti data center right now. And is that good for 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 saying.

Peter Diamandis: They're pre ipo, so they're going to say what it takes to calm the masses out there to some degree. The way I describe it, Alex, Nimod is an impedance mismatch. We have these incredibly powerful tools that are becoming more powerful by the moment. And when they run into an institution, governments in particular, which are typically linear or sublinear, or a company or an individual who can't take advantage of it, you have one of two options. You turn it over fully to the AI and you give it an objective function. You say, make me maximally profitable or make me look maximally intelligent or run my government more sufficiently, or you try and get in the middle. And we're going to talk about a little bit later, an article from the Wall Street Journal where AI is exhausting us all. And if the human is in that interface loop at that impedance mismatch point, it breaks very quickly.

Alex: I was going to make some stupid joke about reflections happening at impedance mismatches, but I think more seriously, there are all sorts of metaphors that one can reach for. Impedance mismatch, maybe on the circuit side is one, but the supply and demand as well. OpenAI and anthropic largely have an overall 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. And right now, the clearing of supply meeting demand. The. The two curves from economics, one on one, crossing each other, aren't necessarily crossing for all cases at a favorable point. And that's, I think, maybe through a more economic see lens, what Sam may be gesturing at.

Dave Blundin: 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 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.

Alex: I think it's a fascinating point, Dave. Maybe I'd 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 super intelligent civilization, you don't need human slave labor or Earth's valuable metals or whatever. You're going to water.

Dave Blundin: We need your.

Alex: 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.

Dave Blundin: Yeah, and the guy, it's 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 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.

Peter Diamandis: But I do think, Dave, I do think that these Frontier Labs, and I really hate calling them labs because they're their frontier companies, if you would, are going to reach up the stack, they're going to build fully verticalized finance companies, insurance companies, consulting companies and so forth on top of theirs, or they'll partner to do that and that will accelerate all of these areas.

Dave Blundin: If I think about insurance though, just as a cat, because I'm the chairman of a very large insurance company company, public company, and they move 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. 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.

Alex: I think that is the 30, Peter. I think that is the $30 trillion question though. If you're a frontier lab, one of two, call them American frontier labs, maybe four depending on how you count. Is it more natural in an era when maybe you're facing margin pressure on your model releases to go upstack or downstack? I think it's actually more ergonomic for them to go downstack and design their own chips and compete with Nvidia and design and operate data centers and energy.

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

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

Dave Blundin: Yep.

Peter Diamandis: 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 sits on top, in which case, for me, it's SCPI with specialists on sales, operations, research, engineering, any sub agents you want. And these multiple bots run in parallel. They message each other and only pull you in on judgment calls. So there's a huge amount of excitement on Grokbot. It's been flooding the Internet. Has anybody here played with it yet?

Salim Ismail: I've been playing quite extensively with it.

Peter Diamandis: Okay, what do you think?

Salim Ismail: 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're making a transition from asking an AI to assigning work. And so persistent autonomous agent is like a new form of labor. And so now you have this completely new category. You know, Peter, we have that staff on demand attribute in exo. Right, Right. This is that taken to its logical extreme where staff are staff recruiting time and coordination costs has gone to like pretty much zero. So the, the, when I'm looking at it from my book perspective, the optimal organizational structure completely changes human set Objectives and leave everything else to the AI.

Peter Diamandis: Amazing. Imod, have you played with it?

Imad: Yeah, I have. I've got 18 Grockbots working in a little swarm and I've given them control via tailscale 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 more fun ones that I've got is I have a Grockbot 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. Where is that from? Where's it getting its aesthetic kind of responsibilities?

Dave Blundin: So if you look at the chat,

Salim Ismail: I just shared that when it comes up with the. When it comes up with the banana with a piece of tape, then you'll get worried.

Imad: 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 art, I don't know. But it's genuinely useful. And I think one of the more powerful things, like I said, is you can actually, because it's got a computer inside, you can give it another shell because the computer is decent, but you can actually have it take over an entire MacBook M4 or something like that. So I've got subbots that have other capabilities. So right now it's installing, 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.

Peter Diamandis: 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. 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?

Dave Blundin: Well, I just signed off on 100k of swarm agents. We're running our 5000 Kimmies again today, which is why I'm wearing my Swarm IT shirt here. But this is the theme of the month. I think that all of our AI interactions to date have been very much one on one. And now the agents are so abundant that you want to try and use a workforce of six and then 50 and then 1,000. And I think within three months you'd be talking about 50,000 agents that can in parallel work for you. But it's very similar to trying to manage an organization. You're like, well, what's everyone doing? I don't know, it's getting really confusing. Are people being productive? I can't tell. And so you really have to start thinking hard about your org structure and your reporting structure to know if your agents are doing anything useful. And so I really want our team here to get ahead of that and start, you know, go ahead and burn the money, but learn quickly and then we'll get, get a handle on this

Salim Ismail: is what I mean by the organizational singularity. Because the company starts to look 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.

Alex: Yeah, I'll give you a hot take.

Dave Blundin: Sorry, go ahead, Alex.

Peter Diamandis: I don't take Alex.

Alex: 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 with agent based scaling. If scaling the size of your fleet becomes one of the most essential scaling laws like inference time scaling has ended up being in the era of reasoning based models, we're not going to want to ask individuals or even enterprises to manage millions of agents. That's completely unergonomic. We're going to want agents managing other agents. In which case the exercise of trying to graft a human organization, or like the Slack or CHAT based interface for humans, managing other humans is not going to extend. We'll look at this like vaudeville, the vaudeville era of agents, and say this was a naive attempt to graft human 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.

Peter Diamandis: Celine, what do you think about Alex's comment?

Salim Ismail: I think it's a. I agree with Alex on The interface comment. This is like an UI that's temporary. I love the way he says it presents like, as it presents like a Nildus or presents like a, a messaging app. And I think that's a temporary one while we figure out new interfaces. But for now, that's a very workable one for coordinating a bunch of agents. We'll come up with all sorts of others. I think we'll rotate through a whole set of these. But I think its core comments are, as usual with Alex, are absolutely dead on.

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

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

Salim Ismail: Exactly.

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

Alex: And so that's, 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.

Salim Ismail: Well, it's also, Peter, it goes back to. Remember the comments we've made about exponential technology hits the vertical and goes up the knee of 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 how the hell is operating. The architecture may not be great, etcetera, but for now, this is a powerful entry point.

Peter Diamandis: 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 is the latest, hottest thing. But it's, you know, I think people need to be using these agentic systems. I'm still using Hermes and Grokbot and we'll see. Let's move on to our next conversation, which is Google is back. So Google's Gemini 3.7 Flash just took the top spot on AI 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 Tera. 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%. 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 out of the race and they come back. So to me it seems like none of these players are out of the race. They're maybe in stealth mode, they're holding back, but they're coming back with a fast furious punch to try and take the top position. What do you make of this, Alex?

Alex: Do you want me to reassure you that Google still has a chance or do you want me to give you the facts unvarnished?

Dave Blundin: Yeah, you got both there pretty hard. Defend yourself, Alex.

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

Dave Blundin: I expect that.

Alex: Okay, scratching my head like Gemini 3.7 flash is nowhere near the top of the capability frontier. So why is it doing so well on this one? Benchmark Artificial Analysis Analyst Agent. So you have to look at the benchmark itself. So the benchmark itself, this is a benchmark for agents ability to perform quant analysis on real world spreadsheets and docs. But wait for it, its metric for success is, is the share of questions answered correctly on all five attempts. So this is a benchmark that is fine tuned for reliability. It rewards agents that give the same answer, basically the same answer every time and obviously want it 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 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. So I'll give you my conspiracy theory for what this one outperformance on this one benchmark suggests. I think that maybe what's been going on, obviously there are a few other factors, but I think Google DeepMind has been under material pressure to optimize their models for two things largely owing to Google search. So if we rewind the video to several months ago or a year ago, people were hand wringing oh, isn't Google. Aren't the 10 blue links going to face an existential threat from all of these frontier models and chatbots and reasoning agents that can just replace the need to Google it all? And Google's response was to self 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. And I think those two pressures from the desire to embed Gemini inside Google search have optimized through competitive internal pressures for probably scarce computer. The Gemini models especially like Flash. Note that there's no Gemini 3.7 Pro anywhere. It's just Flash. It's small, it's fast and it's reliable. I think this is over optimized for clock speed like wall clock speed and determinism and as a result it does well on the one benchmark that rewards highly reliable answers and underperforms. Yeah, it's benchmaxing for basically spreadsheet analysis to be highly reliable.

Peter Diamandis: Imai, do you agree?

Imad: 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 any type of modality of data and Flash is a perfectly decent model but it's not as good as the Chinese models, especially the new GLM Flash that's just come out that's 10 times cheaper for the same performance. Google did do a Preview of Gemini 3.5 Pro but it just couldn't keep up. This is kind of a key thing and you can't accuse them of not having enough compute or being a scarce resource. They literally have millions of chips. I think it's more been about turnover and some institutional malaise coming in that they can't push through to this frontier level because Google has all the data in the world, it has the links of what people search for. It has Gemini as a captive thing but 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 even then the Chinese are coming for their lunch. Like why not just post train on Chinese models at this point if you're

Alex: Google it may come to that. I think people don't realize how compute starved Google is though internally. I mean this has been widely reported. You think Google has all of the compute, the CPUs, the TPUs and the GPUs in the world? It's been widely reported at this point they have internal regular meetings to try to apportion out their scarce compute and the three main constituencies inside Google that are fighting for the flops are one Google Cloud platform which is basically fighting on behalf of external users 2 Google DeepMind, that's fighting for training and inference flops and then 3 Google search at 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 and as a

Peter Diamandis: result 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.

Alex: 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.

Peter Diamandis: Fair enough.

Imad: Google's landing like 3 million TPUs this year. Like I think there's relative levels of compute constraint 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 4000 TPUs and the evidence of that is the Chinese did it and they open source them and we know exactly how they're built. Given Google's data that goes into Gemini Flash applying exactly the same architecture as GLM or Kimi, you should have a better outcome. But they're not doing that for some reason and that doesn't require 10,000 100,000 chips. It requires.

Dave Blundin: That's a really important part. It's like it's yeah, two to 4,000 GPUs for 60 to 90 days that is a microscopic investment by Google standards. So it's exactly right. It has nothing to do with compute dominance and everything to do with talent attrition. It's a great point.

Imad: 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?

Dave Blundin: Well, and then think about it from the person's career point of view. Like the ego blow like you would have to be. I'm the most well funded top AI engineer in the world and the Chinese just kicked my ass. I'm going to go tell my boss, you know what? I give up. Let's go download Kimi, do the rational thing and then tune it. You can't say that because you look like an idiot. And that's where they are. People are leaving in droves to try and get a clean start and a fresh sheet of paper. But yeah, you just got bypassed with massive advantages and resources. So guys, you just can't admit it.

Peter Diamandis: In the US closed labs between OpenAI, Anthropic and Google and Xi, who's in the best position here? I mean who's got or two years

Alex: in the future now?

Dave Blundin: Question.

Alex: 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.

Dave Blundin: Fable 5 There are hordes of model.

Peter Diamandis: 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 I guess continue their dominance. Well, you're.

Dave Blundin: Here's the thing, Peter. There's no easy answer because Anthropic is in the best position by far. And hordes of very talented people are going there purely because they want to see the singularity emerge. It's like the birth of the Phoenix. I want to be there on that day. But they're totally reliant on Elon for the compute. Elon can rip the soul out of Anthropic any day. And he's got the cursor guys now. He spent $60 billion getting them. They're brilliant and they're starting to roll out cool stuff and they're starting to do the training. So yeah, you know, if you said two years in the future then it's really tricky because Anthropic and Elon are like, I don't know, it's a really interesting race.

Peter Diamandis: 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 computer, which is a problem.

Imad: I would disagree with Anthropic being the most advanced.

Peter Diamandis: Who do you believe?

Imad: OpenAI. OpenAI, aside from the Chinese labs, own the Pareto frontier. From Luna 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.

Dave Blundin: Yeah, yeah, totally right.

Imad: GPT 5.6 Pro is the only proper frontier model.

Dave Blundin: Yeah, we switched over to Soul, actually everybody over here is like, God, this Fable has lost its mind. But you know, the argument there is that, well, inside Anthropic, they have Mythos too 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 on hard problems, hard engineering and hard math, yeah, we switched everything over to Sol, so. Totally agree, Imad.

Imad: Even if it was Mythos too, again, you would see them releasing low hanging breakthroughs which 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, 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.

Dave Blundin: Didn't Alex say He actively hates Opus 5?

Imad: I said that.

Dave Blundin: Oh, that was you?

Alex: Oh, no, I did say I don't like Opus 5. I prefer Fable 5. But I think the truth on the frontier is materially more nuanced. Like again, if you look at Mod, for example, at Frontier Math Tier 4, 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 4 model. So I think the truth is a little bit blurry in part because the frontier isn't zero dimensional. It's a one plus dimensional frontier where if you're willing to pay a lot and wait a long time for Fable 5 to do something, it's impressive. But if you're resource starved, cash starved, time starved, then you can probably get better performance at a different point on the optimal cost frontier by say, using sol.

Peter Diamandis: I just want to point out to everybody listening, it's not obvious, right? There is a lot going on and then we're seeing China constantly leapfrog. So Salim, you were gonna say I

Salim Ismail: have a, I have a hot take. These Frontier Labs are facing the innovators 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 in. The good news, as you can see that they're all trying to get into certain verticals and get into revenue streams as fast as possible to reduce that dependence on the Frontier model and being the edge as their core innovators capability.

Peter Diamandis: 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.

Alex: When Frontier Labs compete, you win.

Peter Diamandis: 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 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, Deep Seq and Kimi. The deal struck between Nvidia and the AI startup Poolside aims to build one of the world's most powerful opening models. By building its own opening model, Nvidia is moving up the stack. We've discussed this from silicon to software. Positioning itself not just as a chip maker for AI, but as a platform provider for open weight ecosystems. 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. Imad, let's go to you first. What are Your thoughts on Nvidia and Poolside?

Imad: Yeah, so 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.

Peter Diamandis: So who is Poolside?

Imad: First of all, Poolside is a company I believe is the ex. GitHub.

Alex: Yeah, the former CTO of GitHub, former

Imad: CT, ISO Kant 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 Machines inkling model when it first came out. They tried at the turn of the no. A few months ago to raise $2 billion for a massive Blackwell cluster and they couldn't. So they lost that cluster and they were like, this is the table stakes we need. But they built a really great solid open source model for its size. And so now what they've done is they benefit from this weird Nvidia Aqua higher type thing when video is like, we need to build great open source models to increase demand for our technology on the Nematron stack. So the first thing they did actually was they hired and I don't think it's been announced yet. Ashish Viswani's team from Essential AI, he was one of the founders of the. One of the authors on the Attention Is all youl 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 Cohere and others won't be building open source models anymore. They'll be building to the Nvidia reference design.

Alex: Alex, I think maybe I could say something nice about the American open source community and open weight models moving in a positive direction. Obviously Nvidia had invested, I think about a billion dollars in this company previously and now through this, I'd call it a hack. Now they're finally sort of turbocharging their own Nemotron community. It's more interesting to me that acquisitions were concerning perhaps that acquisitions still need to happen in this day and age. It's also, I think, bizarre if you follow some of the recent acquisitions. My original take on this was this is Just an attempt to avoid regulatory scrutiny or antitrust scrutiny. But I've started to see now some of the other acquisition targets come back to life. What I had sort of left for dead as the carcass of the original company where all of the founding team comes over and all of the core IP was non exclusively licensed, which I think my understanding 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 leftover 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.

Peter Diamandis: There's a lot of pressure for the US to develop top tier open source platforms right now. Dave, what's your take?

Dave Blundin: 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 Mercour and from Oren, our good buddy Kush Bavaria who was on the pod a week ago looking for acquisition targets to accelerate the hiring cycle is too slow. I need groups of 3, 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, 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?

Alex: Well, so I would distinguish between talent acquirers or acqui hires on the one hand, which are largely about getting talent and hackwires with an H that are about at least ostensibly avoiding antitrust scrutiny. So if you're Nvidia and you want to hackwire, say poolside, you're going the hack will 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 in principle for a hackwell acquisition.

Dave Blundin: Gotcha. I got a very specific answer to that too. Remember the Windsurf deal? Of course, of course. So here's the, 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 close the deal like Elon did with Cursor, close the deal many months later after an HSR review and after the 90 days or you know, sometimes it's even longer than that, but There's a statutory 30 days that they just can't get around.

Peter Diamandis: And that's smirking over there. What's up on you?

Salim Ismail: No, no, I think Dave's got it exactly right. I think that's what's going on here. This is just purely juggling the regulatory hurdles and obstacle courses.

Imad: But going back, 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?

Peter Diamandis: The other point here is the verticalization of companies. 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?

Alex: In other words, does Anthropic get a space station?

Imad: No.

Alex: Or a moon colony?

Peter Diamandis: You know, I think they'll be the only company left amongst all the governments. Is that what we learned?

Imad: Yeah, there'll be American gdp, that's why.

Alex: 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.

Peter Diamandis: Yeah. All right.

Imad: I think that you've got actually thinking about our discussion earlier. You have a split of innovation versus execution. And so these are the two model splits that are occurring. Execution drives the majority of the economy, short term, innovation, longer term. And the verticalization is ideal for the execution phase. So if you look at the architecture of Jalapeno, if you look at where things are going, you're going to get closer and closer to the silica, 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.

Alex: All right, yeah, 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.

Peter Diamandis: I'm going to move us along here so three stories this week that chronicle the challenges being faced by the US Closed Frontier Lab 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 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 opweight models are eating the market from bottom up. And when the model costs $0.14 per million tokens compared and delivers 80% of the capability compared to 15 bucks, the market chooses the less expensive option. At least the majority of the market does. Fable 5 is not losing because it's bad. It's losing because it's overpriced relative to the open weight alternatives. The third story, then we'll talk about this is that Anthropic this week reversed its data retention policy ahead of its ipo, letting enterprise customers keep data on their own cloud infrastructure rather than anthropic servers. This move handles the biggest objection that corporate buyers have when adopting Claude. So I don't think the timing is accidental. They're about to go into IPO mode. I think it's predicted for as early as six weeks from now. And the growth requires enterprise adoption and the enterprise adoption requires data sovereignty. So, gentlemen, three stories here. Kimilinear. 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?

Dave Blundin: 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, 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 embargoing the current policy or the prior policy was even if you're hosting your Fable 5 on Amazon Bedrock in a secure environment, everything still has to go to anthropic headquarters for 30 days for us to review and make sure you're not making a virus or a bomb or something. And that's the only way this is safe. So now he's missing revenue numbers because corporations don't want to give their proprietary secrets to any company that they don't know well, 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 gptsol also inside a secure environment where it doesn't get transmitted to OpenAI, so you can use that too. So it's like, oh God, corporations hate this. But I don't want to miss my revenue numbers. I want to go public. On the other hand, I really don't think it's safe. I feel like I need to inspect everything to know that it's safe. So now he's stuck between a rock and a hard place. It's a tough place to be, but being a public company CEO is always like that. It's really, really stressful and really hard. So we'll see if he has what it takes to do it.

Peter Diamandis: Imod, what do you think of Kimilinear?

Imad: 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, etc. 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 new Huawei chips. So I think, you know, you'll see the adoption of these Chinese models and them moving to where the market is on different form factors of different chips. And Again, memory is 50% of all spending now. It is the scarce resource. You can't upgrade it. So guess what? In a couple of months time at the very least, given the pace of Chinese models, they won't need much memory. That's how fast they innovate on the fabled uptake. It's entirely a zero data retention issue. Like as a corporation you cannot leave your data on 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.

Peter Diamandis: That's a fascinating thought. Yeah, I mean why. Why are they racing to an ipo?

Imad: 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 pledge to give away 90% of it. It. Why would you IPO? I can see no reason for that. Unless they can't have an answer privately, which I think they can.

Peter Diamandis: Yeah, go ahead.

Salim Ismail: I have an answer. They need the capital to get compute.

Peter Diamandis: They could raise the capital. I bet you people would throw money at it.

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

Dave Blundin: Yeah.

Salim Ismail: So that's.

Peter Diamandis: 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.

Dave Blundin: 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. So Dario's. Now, he can't react to that by saying, you know what? I'm going to delay my IPO and do some private financing. And you're playing right into Alex's hands. If you wuss out on your IPO plans, he's just going to reinforce Alex's, you know, Karp's message, horrifically. And the board members, like, look at the board members at Anthropic. They've marked up those venture funds to massive valuations and use those valuations to raise new funds. So they're not going to just sit there and say, yeah, Dario, 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.

Salim Ismail: Interesting.

Dave Blundin: That signaling would be terrible.

Peter Diamandis: Alex, awg your thoughts, please.

Alex: 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 wins. Could change. Right now, it's a relatively warm and friendly capital market for ipo. So to the extent there's a window for raising the largest IPO sum in human history, I think you go for it. But to the earlier points in lightning round succession. Kimilinear. We've known about Kimilinear attention since last fall. I think it's suggestive. As I've suggested in the past, Ship of Theseus style transform architecture is getting incrementally replaced piece by piece. It's interesting insofar as it's a successful linear architecture. Many have tried to linearize the graphics. Infamously quadratic attention mechanism. It looks like KLA may be one of the first, at least openly linearized attention or quasi linearized. There's a recurrence mechanism in there as well. So that's kind of interesting. We've known about that for a while. Fable 5 struggling. That is interesting because I've made the point on the POD in the past that 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. That the consumers didn't know what to do with all of these shiny OpenAI reasoning tokens, but enterprises did. And then OpenAI had to do this painful pivot over to enterprise and turn everything into Codex and probably delay their IPO as a result. So Fable 5, which is at least by my accounting, the strongest most frontier model in the world right now, is 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 this maybe will be construed as victim blaming, but it's not. Our economy isn't worthy, it's not clever or wealthy or successful enough on average to know how to use Fable 5 on average properly. Just like consumers didn't know how to use reasoning tokens from 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 cost of their models. That's one direction. Or I think the more exciting model, the more exciting trajectory is some new use case getting unlocked in the next year that actually motivates the usage of this nosebleed priced high end of the frontier, which is at the moment Fable 5. Or depending on the reports you read, maybe 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 report, 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 think it's useful in the long term, but starting to move more and more of the infra layer over to third parties so that users of Claude can get Claude where and when they want on the infra they want. That's powerful. And you see now OpenAI copying anthropic and doing that.

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

Dave Blundin: 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 and now they're all good enough to improve themselves too. So if you start a group within your company that's using these models, you can start improving it inside your company if you get the talent. And so that's like a runaway train, you know, I think that's what's really going on. It's not compromising to save a few pennies. It's like, wow, we can control our own destiny and be on the frontier at the same time.

Imad: 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 100 times cheaper.

Dave Blundin: Yeah, which I think is really important because 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 a thousand. Or this is why the swarm is such a big deal. You can afford 5 or 10,000 concurrent Chinese operators instead of one anthropic.

Imad: 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. Yeah, well, 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. Oh, the right questions.

Salim Ismail: Right.

Dave Blundin: 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.

Alex: I'm not sure how sustainable this, this situation is. I almost want to analogize it now to US importing generic drugs from Canada. The drugs get invented in the US they get manufactured cheaply in Canada. And then at least historically, it's been the case that you could get American drugs more cheaply from Canada by importing on or off label than you could from American drugs. I think the situation may be somewhat analogous here where these are 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 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 front to your 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.

Salim Ismail: 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.

Alex: Yeah, it held until about a year ago.

Peter Diamandis: 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 7pm 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 app. It's already produced 80,000 dates. The app does what Tinder and Hinge refuse to do. It removes choice. The entire dating industry is built on the premise that more options are better But Ditto believes that too many options lead to, you know, decision fatigue, analysis, paralysis, and then AI is the cure. The app does not ask you for a choice, it chooses for you. You know, this is sort of the old style matchmaker agent, you know, a yenta, if you would. And it seems to be working. Celine, 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?

Salim Ismail: 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 interactions and so on. But this makes the searching unnecessary. And I think that's really a powerful user interface experience where people are going to go, let the figure it out and then I'll do the connection and see if there's chemistry there or not. Which you have to do anyway, by the way. Let's note as a scarcity to abundance paradigm, when we were all growing up, sex had a scarcity paradigm. With Tinder, sex became abundant. Where the hell was that in our 20s is the obvious question. But you have to deal with that abundance in a different way. So this is the, the really fascinating thing. I'll watch this. Very careful to see where this goes.

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

Dave Blundin: 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.

Salim Ismail: Bingo.

Dave Blundin: Which I think is going to be, if it's done right, it's going to be one of the greatest boons to mental health in world history. If it's left to manipulate you, it's going to be horrible because it's such a great salesperson. So there's a good, a good test case. You know, are we going to manage it? Well, it's 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?

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

Imad: 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 2 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 loving grace. And we've got to be quite careful about that because, you know, it does take away a little bit from your intrinsic humanity if you outsource your cognition and connection in that way. But, you know, again, you're kind of feeling it already, like with how much of your stuff you offload to these things. And I'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 like, this is human.

Salim Ismail: 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 could 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.

Imad: Apply to that world exponential organization. Salim, come on.

Salim Ismail: I guess you would, Alex.

Peter Diamandis: I should be the only one amongst us not married. So, you know, would you try this out?

Alex: No. I think this is why we can't have nice things. I think this is why. Have you seen the Ditto Body Count Detector? Do you even know what I'm talking about?

Peter Diamandis: No, Tell me.

Alex: 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. Seriously. It's called the Ditto AI Body Count Detector. Folks can check it out. This is, I view as a suboptimal use of reasoning tokens when we could be, as you and I wrote, Peter, we could be solving everything. Yes, we solving everything. And instead we're doing body count detection, so this one gets a thumbs down for me.

Peter Diamandis: All right, well, you know, the reality is that most people on these dating apps are looking at, you know, simply the external parameters of the individual. Are they handsome? Are they beautiful? I think part of it is how honest are you on the questionnaire. And, you know, matchmaking does work, you know, throughout time and culture and across all cultures, some of the longest lasting marriages come from being matched because it's going beyond just your initial hormonal response to the individual. And I think there's something there. Whether or not it has sufficient data to actually align two people accurately is a different thing, but I think there's something there. But I do agree, Dave, that this applies to so many different areas. And Saleem, I know at the Abundance Summit we have 600 CEOs and we're, by the way, I think we're now 90% full for Abundance. 20, 27, if you're interested, you can go to Abundance. 360. 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 a value proposition to be had there.

Alex: Social discovery, I do think is quite valuable if it's for socially productive or economically productive purposes. Social discovery for body count detection. I mean, again, this reminds me of Hot or Not back in the early Facebook days. I just think we could be aiming so much higher as a civilization than AI for this.

Peter Diamandis: Listen, the divorce rate in the United States is 50%, which is crazy. And I think 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.

Dave Blundin: I'd love to know. Alex, how you reconcile. This is a waste of tokens. We should be solving a disease.

Alex: Not a waste. A suboptimal use.

Dave Blundin: Okay, okay. Because one of the terms you've coined in this great revolution is patriot. What's that thing?

Alex: Patricia Musa.

Dave Blundin: Yeah. You can't even say it.

Salim Ismail: No, no, that is

Alex: Patricia Musa.

Dave Blundin: Okay.

Peter Diamandis: Alex loves neologisms. If you haven't seen it, he's publishing new terminology for the Singularity almost every day. Go ahead.

Dave Blundin: You do need a token budget for. For that concept, you know. So how do you recognize. Reconcile those two?

Alex: That's what happens once we have a leisure class that can afford tokens too cheap to meter, which we don't yet have. So maybe the way I reconcile to make you happy, Dave, is I'd say save the body count detection until after we've solved everything. At that point, do as much body count detection as you like.

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

Alex: All right, the line of the song is that once the day had been solved, the day hasn't yet been solved.

Peter Diamandis: Okay, all right, guys, I'm going to move us on, but it's a fascinating concept and I hope ditto works. And there are many happy relationships that come out of it.

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

Salim Ismail: This is Jeffin'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, you 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, 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 in machine speed and requiring a human approval on, on that. So I'm actually facing this. From all the stuff I'm going to do today, you may be seeing the same thing with Skippy. So we need the better next breakthroughs needing to be better delegation, permission escalations crash. 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' requiring a whole new threshold of escalation, thresholds governance, etc. Etc. Because companies need to decide what the machines may decide autonomously and what they want to manage later, what gets audited, what genuinely needs a human. Otherwise we're creating a totally crazy huge future where AI is going to be working like 247 and humans are going to be obligated to work 247 to navigate them. Keep pace of that, right? So more capability, but more capability doesn't mean more freedom. But I'm actually, I'm burning the candle is 16 ends right now. I'm loving it, but I'm not sure how long it lasts at this pace. And you guys aren't helping, I will

Peter Diamandis: say so can I just ask for, you know, Dave, you know Imad and Alex, is it the same for all of you, working harder than ever?

Dave Blundin: God, yeah, absolutely. And then I'll tell you what, you got to savor the moment because you know, Imad and Alex will tell you it's not going to last forever. And you know what's really frustrating to me is actually been recruiting some incredibly talented people for Quantum AI and we lost an MIT Core 6. One 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 Ms. The singularity? Like, no, of course not. But it's frustrating to watch that happen because this moment we're in right now, you can master A thousand 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, you know, don't need you anymore.

Peter Diamandis: Get out of the way.

Dave Blundin: 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 AIs is genuinely fun too. It's not like I'm moving boxes around or grinding it out in a cornfield. You know, this is like, really, really fun, actually discovering the future.

Salim Ismail: It is fun.

Peter Diamandis: It's a blast.

Alex: 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.

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

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

Dave Blundin: I mean, if nothing else motivates you, every year millions of people die needlessly. And if we just get three months shaved off that timeline by working our asses off, millions of people will exist forever. That otherwise wouldn't exist exist.

Peter Diamandis: Beautifully said.

Dave Blundin: 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. So what are your thoughts on this?

Imad: No, I mean, like, the amount of leverage you can do per unit of your attention now is more than has ever been. Another thing, as Alex said, it probably ever will be like, you're approaching the last human discoveries. You're approaching the last point of being able to deploy and control these things. And I think, again, like, you have a limited, focused attention budget. That's why you're getting tired. Maybe to try and coin neurological. Maybe it's cognithology, you know, cognitive lethargy that we're facing here. From my own side, you know, I've written like two books in the last year. I've 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. So we're doing like a big funding round. We're launching lots of new things. We'll be releasing all the research finally. And I turned off my agents that were doing all the research. Like, I've set them onto auto mode. No more mad stuff. And they're coming up with things still. But, like, I can only read it once a week. I've actually made it, so I can't do it. And I think you can shift between these modes of work because you can't be on all the time, because it does burn you out. But at the same time, if you get in the right flow, then you can do more than you've ever done before. And I said, I can't imagine. Like I would say on this podcast, just 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.

Peter Diamandis: Well, not to do college degrees, let

Imad: alone, I would say, you're not even do a college degree. Like, what will you get out of it right now? You will go and you will learn a very specific thing when you should be learning agency, like a THEO fellowship. And the type of people do that will go way bigger than they've ever gone before. You know, parents might kind of complain and things, but show them what you create. Gather people, humans and agents.

Alex: A skeptic would say, all right, Maud, 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 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.

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

Salim Ismail: It was a different time. It was a different time.

Dave Blundin: That just makes you more credible in what you're saying than I would actually say.

Imad: I think undergraduate's still a lot of fun and you don't really have to.

Peter Diamandis: Elon said this. It's a social experience, but it's adult daycare.

Imad: It's adult daycare. So it's actually great for using massive amounts of agents. PhDs though, I don't get, you know, especially like, I feel sorry for. I talked to a bunch of my buddies who are math PhDs and a couple of them had like problems solved in the recent batch. Like they don't even know what they're gonna do. Every verifiable domain PhD now is under massive threat. Why would you even do it or even consider it?

Alex: Like, I agree.

Salim Ismail: Speaking.

Alex: 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, 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, A double think, as it were, before you just go and follow some zombie pattern.

Dave Blundin: Well, I think this is the most important conversation we've had. We've had yet I spooked them.

Alex: I spooked the heck out of them.

Peter Diamandis: 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 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.

Dave Blundin: Well, or actually in a lot of cases, about five years ago, before anyone knew the singularity was coming, they started working their ass off toward that. And you've been working so hard inertia for so long and then you get in and it's like, I got in. But the idea that suddenly it's irrelevant or you shouldn't be doing it is so hard to take after you work so hard to get there. But you gotta pivot. You gotta just recognize, like Elon did.

Peter Diamandis: Get into your Stanford PhD and say, okay, I checked that box and now I'm gonna jump into a company. Oh, well, it's important for people to realize the world is very different than it was before. All right, I'm going to move us forward. This is A conversation we've had before. Two stories on the data center debacle. The first story is about public sentiment. So a year ago, and then again this month a year later, Heat Map News polled Americans about data centers. A year ago, Americans were split 43 to 42 on whether they opposed data centers being built near them. Today, the opposition has risen to 75%, with 61% saying they are strongly opposed. Also this week, Senator Bernie Sanders once again called for a nationwide moratorium. The second story is about a post on X that went viral about data center water myth. We've talked about this on the pod before. Here's the data on people against data centers. It's been increasing, you know, almost. I guess it's a linear increase, but it's going to asymptote near 100%. And the post on the water center, on 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, three times as much, or power plants at 133 billion. Or growing cattle at 137 billion. The fact of the matter is the tech industry is a trust problem. 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. We're going to put education programs in the schools. We're going to make the cost of energy in your community lower than it is today. And we're going to make these data centers not look like ugly boxes. We're going to make them look like cathedrals. I mean, spending an extra 10%. I don't know why that's not going on right now. Honestly, don't.

Alex: My worry is that that wouldn't help. My fear is that this isn't because people think data centers are unsightly or unaesthetic. My concern is that. 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 buildout. We talk about at least one of them all the time on this pod. So my concern would be that we look back in a year or two and see that some quantum of this opposition to data center construction is actually the result of popular sentiment being stoked by foreign adversaries.

Peter Diamandis: Okay, agreed, Alex, but why isn't that, you know, you can Countervail that. When I was on with Michael Karatios, I said, why isn't the White House getting out in front of this? And, you know, because it's an issue that is gaining steam. People can see this. The second thing is you can counter that by saying, listen, like this is what Zuck said in this video last week, right? We're going to, you know, give you better schools, we're going to give you better access to jobs. We're going to be a positive contributor to the community. You know, you can get to a point where having a data center is such an advantage to your community that people are going to say, I don't, you know, that's false news. Here's the facts. Cheaper energy, right? More jobs.

Alex: Here's the problem. The problem, though, is that 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, okay, the east is going to be responsible for data, the west is going to be responsible for compute and energy, and we're going to build this national scale grid for combining compute, data and energy together. And poof, you're the CCP and you get to centrally command the whole economy. In the 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.

Peter Diamandis: But this is false data. This is an outrage cycle in social media.

Alex: This is people shocked, shocked that foreign interference would leverage false data. Shock.

Salim Ismail: Wait, let me, let me say a couple things about this. Can I. Yeah, please. Okay, so we have a problem where our information systems reward compelling narratives over evidence. And this data center thing is the heart of that. And it's a problem that's been building up over decades with the use of social media. We are not evidentiary based in the US at all. This is really a big challenge because we're totally narrative driven and not evidently driven at all. We decide what the story is and then we go looking for facts that support it. Okay, Data centers are a great hobby horse 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. And therefore, and that's amplified radically with social media because nuance has no viral Coefficient. There's like this. This just doesn't aptly 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 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

Dave Blundin: the US Something really, really cool. Yeah, I don't know if you ever met Rob Fisher. He was the president of Lynx 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.

Peter Diamandis: There you go.

Dave Blundin: It's so cool. So, you know, it's like it's doing its own carbon capture using waste heat, you know, running off nuclear power mostly from Seabrook, New Hampshire. And it captures more carbon than the entire loop produces. And they said, oh, you know what, we can actually use just the humidity accumulating because of the temperature gradient to create more water than we consume and just use our own dripping water, then nobody can complain. We're not. We're actually water negative and carbon negative. So it's really. It's really cool.

Peter Diamandis: And I think I saw that it

Dave Blundin: shows you how little water they actually use.

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

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

Peter Diamandis: Yeah. I mean, how, how intelligent was Elon's move prophetic?

Alex: 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 and the Dyson Swarm because he read the tea leaves.

Peter Diamandis: Amazing.

Salim Ismail: 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 evidence evidentiary foundation in our culture. Otherwise every new technology is going to be strangled by the narratives that go viral before the evidence can spread. This is the fundamental foundational problem we have with civilization. As Alex said, this is why we can't have nice things.

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

Salim Ismail: You know, change the narrative.

Peter Diamandis: It's got a branding problem.

Imad: The branding problem. Again, this is not a factual thing. I have a better one I saw recently.

Salim Ismail: I have a better one. AI Churches.

Imad: A computer says, well, beats AI Church. Come on.

Salim Ismail: Fine. Sorry I interrupted you. Go ahead.

Peter Diamandis: 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 cybercap. This week, Waymo announced a significant redesign and cost savings. They announced details around their custom 5 nanometer chip that processes camera, lidar and radar data in real time. I love this. At 1, quadrillion operations per second, we've gone past trillions. We're at quadrillions already. Helping/ their sixth generation autonomous driving hardware costs from 115,000 to 20,000. At the same time, Waymo unveiled the Ojai vehicle, a purpose built robotaxi minivan designed by Chinese EV maker Zeekr. The Ojai 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. Remember, Elon made the point years ago that if a human driver can drive with just one eye, you should be able to do all the driving with just visual sensors. Also in related news, Nvidia this week gave permission for Tesla, Uber and Waymo to simultaneously begin operations in Las Vegas. So let's watch a quick video about the new Waymo. I had a chance to ride in it yesterday. It's a pretty cool vehicle, kind of not as sexy as the Gold Cyber Cab. But take a look for what Wavo

Alex: calls its sixth generation driver, the hardware and software system that actually does the driving.

Dave Blundin: Combine that lower cost Chinese hardware with this new interior tech, which the company

Alex: says was designed to cut sensor costs

Peter Diamandis: while improving performance, and the math starts

Alex: to move in Waymo's favor in a way that it hadn't previously.

Peter Diamandis: Now, the last system running in the

Alex: Jaguar fleet had significantly more sensors. The new one uses 13 cameras, four LiDAR and and six radars, and Waymo says it performs better. The company switched to 17 megapixel cameras, a major jump from the previous specs. Higher resolution means the system can see more with fewer cameras. They slashed the total sensor count by

Dave Blundin: more than 40%, so cost is down

Alex: 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.

Peter Diamandis: 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.

Alex: Okay, so venting some pain here. So Jaguar owned by an Indian company now, but was doing its manufacturing in the uk. Yeah, but was doing its manufacturing largely for Jaguars in the uk. Look behind the headline. Careful what we wish for. With whoever here is suggesting that Google should just switch over to fine tuning Chinese models. Newsflash, Google. Waymo, Alphabet are switching over to using and oem' ing Chinese hardware in order to achieve Waymo objectives. I would rather see the west use a Western hardware stack rather than just white labeling Chinese hardware. That's somewhat disappointing. It's also kind of interesting if you look underneath at the overall chip supply chain that they're using. It seems like they're moving away from Broadcom. They're vertically integrating, which is I think a theme that we were speaking about here earlier. Waymo is maybe Waymo wants its own space station at this point. Waymo is getting its own chips. It's OEM'ing Chinese hardware at the hardware layer. Maybe it's playing footsie with Uber for the moment for distribution, but probably wants to own its own distribution in the long term. I know whenever I use Waymo I'm not using or engaging with Waymo via some aggregator app. I interact directly with Waymo. So I think we're starting to see honest to goodness vertical integration here. And wouldn't also be surprised as Alphabet Waymo is starting to drive costs down in this case, I guess by white labeling Chinese hardware. There's an Interesting historic rhyme with Tesla which started with high end 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 doesn't make sense to sell cheaper cars. It makes more sense to just get out of car sales entirely and offer hosted autonomy platform. I think we're going to start to see Waymo at some point. In order to drive the cost down, they'll just ditch all third party vendors and they turn into a white label, sort of a Dell for Chinese hardware or maybe American hardware. And their focus is entirely on software.

Dave Blundin: Again, 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 Magnum obstacle 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 they're just doing the entire stack.

Peter Diamandis: And robots next they're all going to

Alex: build robots and meanwhile TSMC is a sitting duck. TSMC is waiting to be verticalized.

Dave Blundin: Isn't that amazing? It's like the, the linchpin to this entire thing and it's sitting there not

Alex: doing anything right across the Strait of Taiwan, ready to start World War III at a moment's notice.

Dave Blundin: Yeah, yeah.

Peter Diamandis: Imad, you ever see these vehicles coming to Europe?

Imad: Yeah, we're starting to see Waymos in London and I think the regulation might, should be largely positive for them. But I was having dinner today with Jens Wiese, Deep Tech VC at Leitmotif 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 jobs gone. And I was like, well actually why wouldn't you have specialist robot drivers? You know, like you don't need to retrofit all these cars because you think about a humanoid robot that's walking around in the real world versus one that sits in a cockpit driving a car. It's so much simpler. And I did a bill of materials. I'm like, that's like $6,000 with the actuators and everything. And so I was like, oh, crap, this could actually happen a lot quicker.

Peter Diamandis: Yeah.

Imad: The other side of it 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 virtually integrate if you have fully dark factory. So I kind of feel like there are these kind of two things that are coming, but I really got thinking about this humanoid driver robot.

Salim Ismail: 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 I will yield to you, sir.

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

Alex: It's vaudevillian, 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. Salim.

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

Peter Diamandis: All right, I'm going to move on to the next story.

Salim Ismail: I just want to respond, 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, Selim, that why the self loathing? It was so funny. So I just love that. So I just want to reflect back

Alex: on the human we love. We love our humanoid form factors.

Peter Diamandis: 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 2 miles per hour. I love this product. Let's take a look at the quick video here. And it's like, wow. Best use of a drone I've seen. Pretty amazing, guys.

Salim Ismail: 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. With this type of use case, these applications are going to do new air for public sector acceptance of AI than any, like, chatbot benchmark. Whatever. It's such a great use case. I love this.

Peter Diamandis: Yeah, Alex.

Alex: Yeah. So another one of my neologisms was the broken Waymos theory. People who haven't seen this may remember from the 90s the broken windows theory most famously associated with Rudy Giuliani and the purported rehabilitation of the streets of New York City. The idea was at the time that if there were broken windows, that was either a proxy for or even causally related with broader crime issues. And that you could almost run this causal relationship in reverse, that if you made sure that there were no broken windows, you could make sure that crime overall was down. Or at least that was the thinking at the time in sub quadrants in New York city in the 90s and the early 2000s. Similarly, maybe hopefully slightly better founded. I. I've tried to push the notion of a broken Waymos theory. The idea being that if a city or a nation can't deploy autonomous robots, then they're not prepared for the singularity. And I see videos like this drone life preserver aircraft coming out of China. And I shake my head a bit because here in Boston we can't even get Waymos. And I raised the subject, or attempted to raise the subject with Mayor Wu a couple weeks ago. De minimis progress. I just think, like, we're getting lapped by China at this point.

Peter Diamandis: This is what Sam said. This is institutional inertia. This is the existing players blocking their disruption. This is not a surprise.

Alex: Not a surprise, but definitely a disappointment.

Dave Blundin: Yeah, but I think the AI labs were very late to address PR and realize they need priority. And now they're on it, and we'll see where it goes from here. But, you know, the government reacts to voters. The voters are anti everything, anti data center, anti AI disruption, anti job loss. And that's because the foundation labs, who are now writing Documents like machines of loving grace. You know, this is the roadmap for how the whole world should be governed in the age post AI. Well okay, but get ahead of your pr. You can't have every voter hating you while you try to roll out that roadmap. So get ahead of your priority. In China the news is controlled by the central government, so they just dictate the pr. I mean it's a much easier problem in the closed world than in the free world. But at least the AI labs are aware of it now and hopefully they'll get on it and we'll start like the lifeguard is such a no brainer.

Peter Diamandis: 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 and 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 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.

Imad: I mean I think you do, 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.

Peter Diamandis: Things.

Imad: 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, ubiquitously 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.

Peter Diamandis: This is what you're right and I

Dave Blundin: 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 U.S. so you talk about the water in the, 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.

Peter Diamandis: Dave, this is what Alvin said on the 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.

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

Dave Blundin: 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. Catch that. And that skews the voters tremendously. Alvin explicitly talked about that too. They just, they're just more statistically accurate in the Chinese press.

Peter Diamandis: Yeah. And if it bleeds,

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

Imad: 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.

Peter Diamandis: 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.

Imad: 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?

Alex: All right, we are the Ministry of Superintelligence Truth for the west,

Peter Diamandis: everybody. Welcome to the health section of Moonshots, brought to you by Fountain Life. You know, we talk about AI on the 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. Dawn Musallem, the chief medical officer of Fountain Life and a part of my medical team. Dawn, a pleasure. Great to be here. 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?

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Dave Blundin: And you're right. At Fountain Life, our members, the number

Imad: one thing people are most concerned about

Dave Blundin: is losing their brain health. Forgetting the name of their child, forgetting

Alex: the face of their loved one.

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Alex: dementia, the conservative estimates are that 45% are entirely preventable.

Dave Blundin: What was amazing is with the advanced testing we're doing At Fountain Life, 1/4

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Peter Diamandis: Wow.

Dave Blundin: But what was really awesome is again,

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Alex: This gives me chills.

Dave Blundin: 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.

Peter Diamandis: 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. Dave, 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 Starmine and you know, 100 gigawatts of solar powered AI in orbit and that's 10,000 Starship launches per year to deliver a million tons of data center payload. So he's sticking with those numbers, I guess, starting in 2028, starting launching StarMind and hopefully to 10,000 launches per year. That's crazy. I mean, can you imagine just sitting outside the launch port and watching them pop off every like 50 minutes? It's going to be awesome.

Dave Blundin: And it's amazing that the numbers work as things are, you know, there's going to be a 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.

Peter Diamandis: The second story this week came out of the White House when they released the Golden Age of Space Transportation report outlining the administration's agenda to streamline FAA launch licensing, expand spaceport infrastructure infrastructure, accelerate commercial lunar programs and set a target of a thousand 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. 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 non. So what this means is the incumbents, viasat, Eutelsat, Gogo are going to get crushed out of existence. Thoughts on this, gentleman?

Alex: 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

Peter Diamandis: Starbase Louisiana Next pod, but let's cover it now.

Alex: 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 star bases, seems to be localizing. While at the same time going back, Peter, to your comment on the White House announcement, buried in that announcement was an executive order to the Secretary of the Interior to start appropriating federal land for federal spaceports. And so if you pull the string a bit and ask where are we 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, any takers?

Peter Diamandis: Let's see,

Alex: where's all the federal land?

Peter Diamandis: In Nevada.

Alex: Yeah, 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 spaceport. So I think we get, in the American Southwest we get federal space bases or star bases, and on the Gulf coast we, we get private starbases, as it were, and that's how we get to this like 30,000 per unit time launch capability.

Peter Diamandis: You know, the reason historically all the launches were taking place out of Florida is you were dropping stages along the way. Right.

Alex: You want to be near the water and you want to be near the equator.

Peter Diamandis: Yeah, near the equator.

Dave Blundin: You have to go east. Right, you have to go to the east.

Peter Diamandis: Well, if you want to use the spin of the Earth to assist your launch master. But when you're dropping one, two and three stages out east of you, you don't want to be dropping unpopulated 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.

Alex: We're going to get landlocked starbases. Exactly, yeah.

Peter Diamandis: And except for Israel, that launches west for obvious geographic regions.

Alex: Which way does California launch?

Peter Diamandis: North.

Alex: North.

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

Salim Ismail: I think every day on this podcast we used to talk about, you know, I've never thought about launching north or south. I thought you launched up.

Alex: I mean, up for those of us in the Northern hemisphere, perhaps. But I think, Peter, also you make a super interesting point and 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.

Peter Diamandis: A lot of suborbital vehicles, which just went straight up into the ionosphere and beyond stratosphere and came back down, were being launched from 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 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,

Alex: Same cheers.

Peter Diamandis: Same cheers. Yeah. Pretty crazy. You know, interestingly enough, you know, SpaceX does all of their testing in public. They, you know, describe all of their failures, they open source a lot of their information and China is being able to catch up in the reusable rocket category by taking advantage of it.

Alex: 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.

Peter Diamandis: I think he wants as much launch, as much chips, as much all of this as possible. He's been pretty vocal about that.

Salim Ismail: So, anyway, I'm more optimistic than most on this because what you've got in SpaceX was a compounding learning loop and that's hard to break, that's hard to beat.

Peter Diamandis: 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 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 mediaamandis.com we want more of your creative genius. You guys open for a few AMAs?

Salim Ismail: Just a few minutes or two before I have to rush to my boarding.

Peter Diamandis: Okay, we'll give you a first crack at this. Saleem. Pick your first one.

Salim Ismail: 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 Bujan 545 5. Oh wow. You know this goes to what we talked about earlier, right? You're 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. This look at the benefit of on on X of people checking with GROK whether something's real or not. It's creating a really viable, 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 another agent's claim. But you're going to have to program that in to have that cognitive critical thinking in there term. 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 bad model or from the same original point. So I think we're gonna 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.

Peter Diamandis: 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 XPRIZES with a clear objective function. The first person to do this I think honestly the AI labs from the work that Demis Hasabis 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.

Dave Blundin: 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 Plumadon 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 LIPU 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. 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.

Peter Diamandis: There you go. All right. Imod, you want to take number three?

Imad: 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 5 CD? So there has been advances in this with AI designed ligands to increase enamel production and have stronger teeth on the other side. We've seen AI in dentistry from analyzing kind of the mouth and the various kind of elements of that. But I think kind of getting these amelo blasts up and running will be really useful, useful in repairing teeth, but I don't think anyone's actually figured out how to crack regrowing them fully.

Peter Diamandis: Alexa layer on top.

Alex: I feel like I have to take another bite at this question. So there is a drug out of spinoff from Kyoto University called TRH035 that is targeting 2, 3 growth. Honest to goodness, 2, 3 growth with general availability by 2030. And I don't think there's that much AI involved with it. Again, it's blocking a particular, I think protein pathway that is normally associated with blocking. So it's a double blocker blocking the blocker for tooth regrowth. I think the primary focus in their clinical trials is infants that suffer from a disease that causes impaired tooth growth. But the plan is to get it out to general availability by the end of this decade.

Peter Diamandis: Nice. I'm always going to layer on top, but you got it all right, Dave.

Dave Blundin: 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.

Peter Diamandis: All right Imad,

Imad: 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 Hood? Harmon03 I think that's the point. You're not gonna have a say in super intelligence. I think anthropic think that's far too dangerous and there is no good democratic way to do that under their rubric and kind of approach. So you have to assume that it will be a close controlled company and ultimately comes down to a few people like Ben Bernanke to decide the future of the light cone potentially.

Peter Diamandis: All right Alex, how about number five?

Dave Blundin: Oh really?

Alex: Don't you want me answering number six?

Peter Diamandis: I'll take number six.

Alex: Oh really? All right, okay fine.

Peter Diamandis: I'm steering the conversation clearly.

Alex: So 5 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 licking 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 economic gain. You, you can only get so far improving AI for its own sake before ultimately you have to start driving real economic gains. Which AI if it just lives in a pure bottle and never interacts with the outside world, there's no real economic gain there. It has to start talking to the outside world at some point. And that's what non AI R D is. So in short, no.

Peter Diamandis: All right. And number six, when will an AI bot become a member of the Moonshots panel from what makes you think John, that we're not already AI bots?

Alex: That's my answer, Peter.

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

Alex: Approximately a year ago.

Peter Diamandis: 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 Parish.

Alex: Optimism to the max with moonshots mates 4 months 4 takes honest debate the singularity is now and just accelerates no

Peter Diamandis: dystopia here we build and create

Salim Ismail: a

Alex: whippy rhythm that the moonshots makes like how we're all bobbleheads at this point.

Peter Diamandis: Peter the prophet of abundance 28 hour

Alex: days moonshot after moonshot lighting the flame exponential oracle in the dawning new age

Peter Diamandis: he's always ready to blow his mind

Alex: away Ley lay I impresario he's the allocator in the markets in the lab Sharp as an alligator 30 years in

Dave Blundin: the game so he says it straight

Peter Diamandis: up on the cutting edge Pure accelerator

Alex: optimism to the max with moonshots mates

Peter Diamandis: 4 minus 4 takes honest debate the

Alex: singularity is now and just acceleration no

Peter Diamandis: dystopia here we build, we create moon

Dave Blundin: shots made what the moon shots maze

Alex: founded exo in the MTP system thinking Salem sing fundamental transformation is what he sings Efficiency maxing with the models he brings globetrotting cause there's no contained in

Dave Blundin: this thing Intelligence wants to be free

Peter Diamandis: A WG in house as I voice for digital entities right.

Alex: He's got his mind on the truth and the truth on his mind Data move them in a way we can't describe Dyson spheres filling his dreams at

Dave Blundin: night drags him to the max with

Peter Diamandis: moonshots mates 4 minds for singularity is how and just accelerates no dystopia here we build, we create with the money. All right, for all your outro video creators again, send us@mediadmanis.com we have to start including EMOD into those videos. And gentlemen, I guess we're going to be recording in 48 hours from now. You know, no time to sleep.

Alex: Good thing nothing ever happens.

Imad: Yeah, I think another full docket already for that one, eh?

Peter Diamandis: We do. We do. Amazing. Really, so so much.

Imad: You have to check out Nvidia results.

Peter Diamandis: Man, I love you guys.

Salim Ismail: Be well.

Alex: Thanks, Peter.

Dave Blundin: Likewise.