Making Sense of This Week’s AI Market Crashes | #x307

The mates sit down with Emad Mostaque to discuss AI’s impact on the stock market, Google’s growing profitability challenges, and Sam Altman’s surprising admissions about AI models. From market volatility to the escalating AI race, they explore what it all means for the future of the industry. Get access to metatrends 10+ years before anyone else - https://qr.diamandis.com/metatrends Peter H. Diamandis, MD, is the Founder of XPRIZE, Singularity University, ZeroG, and A360 Salim Ismail is the founder of Open ExO, a GP at Exponential Venture Capital/The Organizational Singularity Fund and a sought after global speaker and thought leader. Dave Blundin is the founder & GP of Link Ventures Dr. Alexander Wissner-Gross is a computer scientist and founder of Reified 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 – This episode is brought to you by: Get the blueprint for generative media https://goo.gle/startupgenmedia Go to Blitzy to book a free demo and start building today: https://qr.diamandis.com/blitzy Your body is incredibly good at hiding disease. Schedule a call with Fountain Life to add healthy decades to your life, and to learn more about their Memberships: https://www.fountainlife.com/peter _ Connect with Peter: X Instagram Substack Website Xprize A360 Connect with Dave: Web X LinkedIn Instagram TikTok Connect with Salim: LinkedIn X Join Salim’s 10X Shift Subscribe to Salim’s YouTube channel Exponential Venture Capital Connect with Alex Website LinkedIn X Email Substack Spotify Threads Connect with Emad ⁠⁠⁠⁠⁠⁠⁠⁠ X⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ LinkedIn⁠⁠⁠⁠⁠⁠⁠⁠ Learn about Intelligent Internet: https://www.ii.inc Read Emad’s Book: https://thelasteconomy.com Listen to MOONSHOTS: Apple YouTube Follow MOONSHOTS: Instagram TikTok X Threads – *Recorded on October 30th, 2026 *The views expressed by me and all guests are personal opinions and do not constitute Financial, Medical, or Legal advice. Learn more about your ad choices. Visit megaphone.fm/adchoices

Speaker names marked ? are inferred from speaking time and the show’s known hosts — they are not voice-verified.

• 0:00Speaker 00

  I checked in with one of our portfolio companies, Pirate Labs, that makes lasers. And they said if anyone has graphene, like pure graphene more than a millimeter, they own the world.

• 0:14Speaker 01

  I can get you all the graphene you want.

• 0:19Speaker 00

  What do you mean?

• 0:21Peter Diamandis?

  My desk drawer over here.

• 0:24Peter Diamandis?

  Oh my god, supply of pencil.

• 0:25Speaker 01

  I have access to the company, the biggest graphene manufacturer in the world.

• 0:29Speaker 00

  Who's that?

• 0:31Speaker 01

  Nano...

• 0:32Speaker 00

  Nano, nano.

• 0:33Speaker 01

  Nano something.

• 0:35Peter Diamandis?

  All right, guys, I have a question. So Chamath dropped a bomb last week, right? Saying Bitcoin is capped, and then I think it'll eventually get hacked, and then it'll go to zero. You know, I'm curious what you thought. His basic premise was that central banks can't really hold it, so the buyer pool is limited, and self-improving AI and quantum is going to disrupt it. You know, Saleem, your thoughts?

• 1:03Speaker 01

  I think it's, I think, I'll be blunt, I think it's a psyop. I think he's working on behalf of the Treasury Secretary to say that. It's a complete, he used to be a massive Bitcoin bull.

• 1:12Peter Diamandis?

  Yeah, he was saying it was going to go to a million bucks. He was playing his book back then.

• 1:16Speaker 01

  So now he's like saying totally the opposite. The, the, the, I've talked to Jeff and other folks. All they have to do is solve the right consensus mechanisms. Also, if you solve the crypto thing, I might, you may have a better view on this, but the elliptical crypto seems to be holding steady even in the face of quantum, and we can shift, go to quantum encryption and other things. It's not, as far as I can see, it's not going anywhere.

• 1:43Peter Diamandis?

  Yeah, our viewers have been...

• 1:46Speaker 01

  Viewers are freaked out.

• 1:47Peter Diamandis?

  Yeah, well, the viewers are saying, please have the Bitcoin debate, so we're going to do that.

• 1:51Speaker 01

  Yeah, please.

• 1:51Peter Diamandis?

  In a week or so, either in the next week or the week after that. And then, of course, you guys saw that Binance got hacked, right?

• 2:00Speaker 01

  Yeah.

• 2:00Peter Diamandis?

  Out of 6.3 billion. No, let me chat about now for a minute, but you know, 6.3 billion got ported out, and it's the largest crypto theft in history. It might be the largest theft in history. And apparently, it was, it was not tech. It was basically the weak link in the loop, the human.

• 2:20Speaker 01

  So, yeah, it was one guy's machine.

• 2:22Peter Diamandis?

  Yeah, so one engineer got compromised from the attackers, apparently out of North Korea. I mean, that's the accusation right now. And they got a hold of his machine and got in the door and stole 6.3 billion dollars. That's insane.

• 2:40Speaker 01

  Yeah, in 20 minutes.

• 2:41Peter Diamandis?

  In 20 minutes. Crazy.

• 2:43Speaker 01

  And you had to do it all at once, right? Like, you couldn't do it.

• 2:46Peter Diamandis?

  Yeah, you could do it a little bit at a time.

• 2:48Speaker 01

  You can't dribble it out, people notice. So, the good news is that the other exchanges have put a lock on everything now, so wherever they moved it to should be somewhat traceable. They're trying to move them into smaller and smaller chains as fast as possible to cover their tracks. But this is the problem, you know, the crypto is not fully anonymous. You can follow the chains.

• 3:11Peter Diamandis?

  Yeah.

• 3:12Speaker 01

  So...

• 3:12Peter Diamandis?

  And apparently 3 billion was, has been frozen, so hopefully recovered. And then the majority were stable coins. It was Tether and Circle. It wasn't Bitcoin.

• 3:23Peter Diamandis?

  Any thoughts on that, Imad?

• 3:27Speaker 03

  Yeah, I mean, Tether, Circle, again, they can kind of freeze it. The human is the weak link. I mean, again, but this is the problem with the banking sector too. Bangladesh lost 100 million dollars via Macau when someone pretended to be the central bank minister there with Swift, and the kind of money went through. So you're going to see actually more sophisticated attacks, like I've mentioned before, I've had calls from my mother saying, you know, send money and things like that.

• 3:51Peter Diamandis?

  Did you?

• 3:52Speaker 03

  With voice spoofing attacks. No, you know, it's the other way around. And like, you're going to see more and more sophisticated attacks, but I think that when we go to the Bitcoin and all this stuff, like, the models are capable of crazy things, and they haven't released the cryptographic advances for a reason so far. And that comes at the same time as quantum computing. So I think if anything can be hacked, it probably will be because the AI can ask the quantum computers the right questions. But whether or not that impacts Bitcoin, given where it is right now and makes it go to zero, I think it goes to zero. There's always going to be a buyer as a kind of historic asset that can upgrade its thing, because 50% of the hash rate is two miners, right? They can upgrade quite easily.

• 4:34Speaker 03

  But it could take hits. And I think the bigger problem, as we discussed with Kathy Wood on stage, is that it's the energy, right? Like, who's building all the new flops for it? Because all of the miners are saying, I want AI chips instead. Why do I have ASICs?

• 4:49Speaker 01

  Alex, welcome.

• 4:50Speaker 00

  I think the crux of what Chamath was saying was not technical. It was that you could easily increase the encryption, but they'll never agree on how to do it. They can't even agree on how to meet.

• 5:01Speaker 03

  We don't know in this age, except for that when there are big targets now, every big target is going to come under attack. Like, how does it kind of handle? Like, one of my friends had an NFT exchange. Swarms of agents were attacking it, and he was fighting back with agents. And he ended up rewriting his entire stack in like one day, because they couldn't figure out a way to make it secure. Like, the losses were only like 100,000, but they're going to visualize it. I literally was agents back and forth. They were finding everything.

• 5:32Peter Diamandis?

  Thank God humans, thank God humans are secure.

• 5:34Speaker 03

  And other things.

• 5:37Speaker 00

  Well, I think it's a very good time to protect your credibility at all costs, because...

• 5:42Speaker 03

  Oh, and by the way, you know Mark Carney invested 1.6 billion in Cohere's latest round, right?

• 5:46Speaker 00

  Are you serious?

• 5:47Speaker 03

  From Canada, and so did Ottawa. Yeah. So Kananda is going to start investing directly in...

• 5:53Peter Diamandis?

  One more thing before we guys get started. You know, let's take a moment and say farewell to Sir Patrick Stewart.

• 6:00Peter Diamandis?

  Captain Jean-Luc Picard, who passed away on Wednesday at his home in LA. He was 86 years old. I mean, you know, listen, you know, Bill Shatner, for me, will always be the captain of the Enterprise, but you know, Jean-Luc Picard was extraordinary, you know, very...

• 6:17Speaker 01

  Unbelievable.

• 6:18Peter Diamandis?

  You know, very beautiful man.

• 6:21Speaker 01

  Lot of legitimacy for us, folks.

• 6:23Peter Diamandis?

  Yeah.

• 6:24Speaker 01

  One thing I'd like to clear up with the commentary about the Borg. They switched at some point from saying resistance is futile to resistance is futile. And let's just say for the record, it's futile. Because that's how English is pronounced, so...

• 6:43Peter Diamandis?

  Alex, any thoughts on Jean-Luc?

• 6:46Speaker 04

  Yeah, it's very sad. Hopefully, with, under, I would say humanities common task, we can someday resurrect Patrick Stewart. And certainly, the character of Captain Picard is already, I think, in a million different sea dance sessions being resurrected as we speak. So I think the character will live on, and hopefully the human can be brought back as well. And then maybe just narrowly on Binance and Bitcoin, cry me a river. This is an unproductive...

• 7:17Speaker 04

  This is an unproductive, it's an unproductive use of capital. So sad, so sad.

• 7:23Speaker 01

  It is not, it is not. The ability to do micropayments, or the ability for anybody in the world to own Bitcoin.

• 7:29Speaker 04

  It's awful, Saleem.

• 7:30Peter Diamandis?

  Save it, save it for the debate. Yeah. Well, anyway...

• 7:35Speaker 01

  Please let's schedule that, because I want to kind of get Jeff's time as a slot in one of those and all the rest of it.

• 7:41Peter Diamandis?

  Yeah, for sure. And it was fun. I saw this morning Elon saying longevity is coming. He finally has converted. He's finally using some of his Grok cycles to hit longevity, so that's...

• 7:52Speaker 04

  It's a huge market. It's a bigger market than AI, and to the extent SpaceX is no longer a rocketry company and is now a neo-hyper scaler, I'm sure Elon himself will discover GLP-1s and whatever market they're creating in longevity is, I don't know, maybe Tesla pivots to GLP-1s.

• 8:11Peter Diamandis?

  Or GLP-1000s, whatever it might be.

• 8:14Speaker 04

  Yeah.

• 8:14Peter Diamandis?

  You know, I had a, I had a call this morning with a friend, Max Jaderberg, who's the president of Isomorphic. Just amazing stuff going on there. Just extraordinary. So, gentlemen, shall we jump in?

• 8:32Speaker 05

  Now that's a moonshot, ladies and gentlemen. This episode is brought to you by the Abundance Summit and Link Ventures.

• 8:42Peter Diamandis?

  Welcome to Moonshots, everyone, your number one podcast on all things AI and exponential, your front row seat, as you know, to the singularity. I'm here with a fantastic five. Alex Weisner-Gross, our genius physicist, computer scientist, our very own in-house ASI, Dave Blunden, venture capitalist extraordinaire, serial founder, our resident translator of what goes from AI hype to AI revenue, and Imad Wustak, founder of Intelligent Internet, author of The Last Economy, and the only one on this pod who can really effectively joust with Alex. So, Imad, that's your purpose now.

• 9:19Speaker 01

  Hey, I can joust, and maybe not as successfully.

• 9:22Peter Diamandis?

  Okay, successfully joust.

• 9:24Speaker 03

  Joust with Alex and pass the butter. That's my purpose. There we go.

• 9:29Speaker 04

  Pass the ammunition.

• 9:30Peter Diamandis?

  And of course, Lee Mismael, founder of Exponential Organizations, the man who's visited more countries in the last year than most diplomats. And it looks like everybody's home today.

• 9:39Speaker 00

  Home.

• 9:41Peter Diamandis?

  Yes, this is Home Week on the pod. Amen.

• 9:44Speaker 00

  Back from Stanford late last night and back at MIT, which is just bubbling. I cannot tell you how much it's bubbling over. Everybody is just optimistic about AI. And I saw a whole bunch of Abundance t-shirts, by the way, walking around campus. Yeah.

• 10:01Peter Diamandis?

  Yeah, well, you know, solve everything, abundance, you know, P doom, less than zero, those are our themes. The number-

• 10:10Speaker 03

  So is the Moonshot much still running?

• 10:13Peter Diamandis?

  Well, we're gonna actually, we're in the middle of redoing the Moonshot's website, and we're gonna provide the merch there to all of our fans so that they can, they can get all the slogans, all the t-shirts, all the mugs. I've got my Moonshots mug right here. It says on the back, "Where can you go 10x bigger than others who are hoping for 10%?"

• 10:31Speaker 04

  We're the Ministry of Information, the Ministry of Truth, if you will, for the singularity, so we might as well have great merch.

• 10:38Peter Diamandis?

  For sure. Gotta make some revenue someplace. The number of this week is 1 billion. That's how many users Gemini app now has, the fastest growing product in Google's history. And yet, as you'll hear today, Alphabet just had its worst stock day in history. If you're new here, hit subscribe. We publish twice a week. You don't want to miss any of these episodes during the singularity. I mean, it's insanely difficult to keep up. I mean, the speed is accelerating. It will never be slower than it is today. Also, if you want, you can follow us on X at @moonshots_pod. We put our most fun and provocative clips up there. Some great love from our subscribers from our last episodes. Quote, "Congrats to

• 11:22Peter Diamandis?

  Alex on his chain theory. So very impressive." You got a lot of love for chain theory, Alex.

• 11:27Speaker 04

  It's very kind, but the ultimate court isn't public opinion. It's the physical world. And-

• 11:32Speaker 01

  It's reality.

• 11:33Speaker 04

  It is reality. So I thank you, but I care even more about actually, in some sense, not just predicting and retrodicting reality, but also doing my own part to make sure that the institution of physics itself actually cares, certainly in fundamental physics, about the real world and not just about pure theory. That's the ultimate arbiter here.

• 11:57Speaker 01

  I want to acknowledge that response, because a lot of people get stuck on their theory. It's really great to see you say it'll, it'll work when it meets the real world. So I just want to say, amazing.

• 12:08Speaker 04

  Thank you. I, maybe not to gild the lily, but I think it's sort of a decent portion of physics as a research community is, in my view, stuck in, call it an unfortunate state where it's lost contact, or let's say, lost the, the spirit of making falsifiable predictions about the physical world. And that used to be the case. Unfortunately, for whatever reason, and I certainly have my own views, there are large portions of physics research that now that don't even aspire to make falsifiable predictions about the physical world. So we'll do what we can to bring the good times back.

• 12:44Speaker 03

  Okay. Yeah, it's what Wolfgang, it's what Wolfgang Pauli said, "Not even wrong," you know, like, it can't be wrong.

• 12:51Speaker 04

  Yeah.

• 12:52Speaker 00

  I gotta use that. I gotta use that.

• 12:54Speaker 04

  Well, that-

• 12:55Peter Diamandis?

  I'm gonna kick it off here.

• 12:56Speaker 04

  Thank you, Peter White, for popularizing "Not even wrong."

• 12:58Peter Diamandis?

  All right, let's jump in. So this morning, we're gonna open up with a sequence of four stories about Google. Quick reminder and disclosure, Google is one of our sponsors on this pod, but they have no editorial control. But we had to cover this. Google is so back. They've taken back the AI crown. So on Wednesday, Google CEO Sundar Pichai announced Gemini 4 Carbon, only two weeks after announcing Argon. And that's the pace of the frontier, right? Two major models from a single hyperscaler in a single week. On artificial analysis

• 13:36Peter Diamandis?

  intelligent index, they had a score that beat out Opus 5.5, beat out GPT-6, Astra. The score was 59. We'll take a look at that in a moment. But here's the real headline for me is cybersecurity. Carbon found 88% of vulnerabilities on a benchmark called SEC Bench Pro. It successfully exploited 55% of the flaws on Exploit Bench, and it wrote working patches for 71%. Google's own Chrome security team says it's more than 10 times better at producing high-quality patches than a competing frontier model. So it's a big deal. I'm curious. I'm gonna go to you first, Alex. What did you think? Because

• 14:18Peter Diamandis?

  honestly, we've been saying on this pod that Google is so far behind, that they should open source it. And here they are, leaping forward once again. We've seen this every time, right? Meta leaps ahead of everybody else, and then it's Anthropic, it's OpenAI, and Google's back.

• 14:34Speaker 04

  I so want Google to be back, but big asterisk. There are two things I think that maybe are buried in the headlines. One is, this model isn't generally available, unlike, say, Opus 5.5 that everyone has access to. So by the time, perhaps, that it does become generally available, it may no longer even aspirationally be at the frontier. Second thing- Yeah, no, well, okay, so I'm, Peter, I'm exercising my editorial independence here, and I'm calling balls, calling balls and strikes. The other thing is, if you look a little bit more closely on artificial analysis, they do a chart measuring the intelligence

• 15:16Speaker 04

  index versus cost per task by model release. And that one, I think, is especially striking and instructive. So Gemini 4 Carbon, if you look at that, and then you look at the frontier defined by the Opus 5.5 high-level reasoning with fallback, you see that Gemini 4 Carbon is exactly, just, you can extrapolate that line. It's exactly on that frontier. So what, what that would imply, what that would suggest is that actually Gemini 4 Carbon might look like, essentially at the back end, the equivalent of an Opus 5.5 with fallback, simply cranked up to higher reasoning level and therefore at higher cost. And if that's the case, I

• 16:01Speaker 04

  would say that puts Google as, puts Gemini 4 Carbon, rather, as maybe Opus 5.5 level but unreleased. And Google really needs to do, in my view, a better job if it wants to credibly claim the capability frontier crown of actually releasing models and not just stealth releasing them or privately releasing them. I have friends on the team, make no mistake, and I know the friends listen to the pod, but they really need to actually get the models out there. Otherwise, it's an apples-to-oranges comparison. I'm sure OpenAI and Anthropic have models internally, Bell et al., that are, that would blow all of these released models out of the water. But because they're not generally accessible,

• 16:45Speaker 04

  then, you know, it's not a fair comparison.

• 16:47Peter Diamandis?

  Yeah, well, Google has released it to trusted cyber defenders first. They've got a program called Fairwind, and broader release, or they haven't, they haven't announced when they're gonna do that. But the other thing is that Carbon's come in 23% cheaper than Opus.

• 17:02Speaker 04

  If you have access to it, though. Like, so again, I don't want to be the party pooper here, but I do feel the need to call balls and strikes. If they're subsidizing it, we don't know what profit margins Carbon 4 is for Google. This is presumably a very, very, very tiny portion of their business versus, say, Anthropic and OpenAI, where we have reasonably good sense what their margins are. Google could hypothetically be subsidizing all of this and offering it that below cost. We just don't know. So I would love much more transparency from Google before I'm willing to say Google has achieved the frontier. That said, I want the frontier to be competitive, and kudos to Google for at least trying.

• 17:40Speaker 00

  Well, I wouldn't, I wouldn't expect Google to be super transparent anytime soon. They are absolutely in an incredibly good position. You know, the TPUs are now second only to Nvidia in terms of total compute manufactured, and they've done it incredibly quietly. So my read on Google is, you know, they, they have so much cash flow from the core search business. They don't have an IPO coming up. They don't need to be big in the PR wars. And they are very quietly accumulating an incredibly powerful position. Now, whether or not they execute with it or just quietly keep accumulating, we'll find out. But, you know, being vertically integrated between TPUs doing all the thinking now and their

• 18:25Speaker 00

  internal foundation models, huge, insane treasure trove of training data. I mean, crazy, crazy data advantage. And keep in mind that, you know, that Elon started OpenAI, or co-founded OpenAI, specifically because Google is just gonna run away with the entire world. And so now we have a little bit of balance in the force, thanks to, you know, OpenAI, and then people leaving OpenAI to start Anthropic. But absent that move, it would be an all-Google world right now.

• 18:50Peter Diamandis?

  I mean, I think the point I want to make is, you can't count any of these labs out. They're, they've all got massive pressure to leap on the frontier and maintain it. Imad, what was your take on Carbon?

• 19:05Speaker 03

  I mean, how many people are even smart enough to use the smartest models anymore? You know, like, let's be real, like Anthropic just released a prompting guide where they're like, you're being too complicated on prompting, these models can do whatever. And now it's basically become around, you either use the models to do day to day normal work, and they become very capable and very consistent, or you want a swarm of a thousand or 10,000 of them and the capability to swarm them to solve the most complex work, and there's not much in between. So I think the focus on the frontier, as you said, there's better models inside OpenAI and kind of other things, is starting to miss the point a bit. What really matters is, is it in front of people? Google announced Gemini Spark. What's Gemini Spark?

• 19:48Speaker 03

  Everyone says, well, remember, it's going to be that personal assistant. But why is nobody using that versus Dots or Grokbot, which now has a million users and things like that? And this is the flip side and the dangerous side, because Google and Meta, if they don't have the AI that's closest to you, that's buying your things, that hits their main business. In fact, I'm going to make a call here. I think search advertising will top as an industry in Q1. And that will be the big narrative.

• 20:13Peter Diamandis?

  It will top and then.

• 20:14Speaker 00

  That's a really, really gutsy call. I appreciate, I cannot disagree. It is falsifiable, which is awesome. But yeah, that's brilliant. Let's see. I'm proud that you put that out there.

• 20:29Speaker 03

  I mean, Google and Meta, yeah, Google and Meta have been, literally, you look at it, it's growing way faster than GDP every single year. But next year, and I think it'll be as soon as Q1, if that tops out, that structural growth in advertising, because people are buying via their agents, their agents are doing SEO, what's Google's business model? What's Meta's business model? Like, now Google has to think, well, maybe we get AstroTeller and launch 10 companies a year, or 20 companies a year, right? Because now it's time to diversify and what can fill that gap.

• 20:59Speaker 04

  GCP, obviously. I mean, so if you look at, I don't want to front run the stories here, Peter, but if you look at the revenue mix from Google and their, or Alphabet in their last quarterly, it's so obviously transitioning away from becoming a search advertising company to becoming a hyperscaler cloud company. And so I think Google probably, if this trend continues, regardless of what happens with search advertising, search advertising is going, is on a trajectory in the next year or two to become their second largest business, not even their largest business, and they'll just care less.

• 21:31Peter Diamandis?

  Yeah, I've been saying this for years. There's, there's no way that advertising to a human is going to be the way any of this does. All right, it's going to be, your AI is going to know exactly what the best products are, what you're using, what's right for your genome, what's right for your, you know, your schedule for the next three days, and it'll buy it for you.

• 21:50Speaker 01

  Humans are just there to be hacked.

• 21:57Speaker 00

  Just to flush out that story, so GCP is growing like crazy. The margins, though, are higher on search advertising. So it's a little misleading, but, you know, to say that, you know, they're, they're fine because GCP is growing so quickly. You know, if, if Ahmad is right and search tops out in Q1, there is a gap of about a year in there where the search revenue is declining while the GCP margins have not caught up yet. But, you know, if you look beyond that, they're in a phenomenal position. The other thing, though, is GCP is growing on the back of TSMC manufacturing, which is completely and totally sold out. Demand is multiples higher than they can produce.

• 22:37Speaker 00

  And so the way that GCP can win is by getting more TSMC capacity. That's not a given. I don't know how TSMC is deciding what to make between Apple, Google, Nvidia, and all other.

• 22:52Peter Diamandis?

  And SpaceX.

• 22:53Speaker 00

  It's not, they're not doing it on price. You know, in a rational market, they just raise the prices, but they're not doing that. So it's all politics. It's very, very smoky backroom mirrors right now. It's very hard to know exactly what's going on there, but that's the linchpin. You know, and the TerraFab will ultimately come online and, and make that a balanced world, but right now it's completely out of balance. Two thirds of all real chips that matter are made by TSMCs. It's a very, very odd, very fragile world we're in.

• 23:21Peter Diamandis?

  It's also worth remembering, you know, Google has such diversified holdings, right? They're a huge holder in SpaceX, in, in isomorphic labs, in all of DeepMind's other projects. They're not going to be hurting for some time. Wall Street is fickle.

• 23:36Speaker 03

  You know.

• 23:36Speaker 01

  The question I've got in all this is.

• 23:38Speaker 03

  Google earns 14% of Anthropic.

• 23:41Peter Diamandis?

  They're riding all the curves.

• 23:42Speaker 00

  Isn't that wild? Yeah, they're just everywhere. Quiet, and very well, you know, they have antitrust action all over them. So it's very easy to say, well, Google doesn't seem to be doing much. They're trying like crazy to make it less obvious how powerful they really are because of the antitrust action that is ongoing right now. There's, you know, multi, could be $100 billion settlements related to this antitrust action. So they have every reason to stay off the radar, quietly build the smartest AI the world has ever known, and the whole tech stack underneath it.

• 24:11Peter Diamandis?

  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 Startup Tactical Guide for Generative Media gives you a complete blueprint for deploying Google DeepMind's models in production. Images, video, audio, all of it, real architecture, real results. Find the link in the show notes below. All right, let's go to the second story with Google, which is Genie 4 from Google DeepMind. So Genie is a world model. We've talked about world models. We're going to have Fei-Fei Li on the show very soon. You type a prompt and it generates a photorealistic 3D world that you can walk through,

• 24:54Peter Diamandis?

  interact with, using a keyboard like a video game. All right, so Genie has four additions, three big things. First, native audio, music, ambient sound, and characters who speak. Second, real time physics and reasoning. So when you set up an, an event in motion, it simulates what happens next and how people react to it. Third, you can steer the world mid-simulation. I love this. You can type, make it rain, add a person, you know, and the scene adapts completely to you. Demis Abbes posted the following, quote, "Simulations within the simulations makes you wonder just how deep the rabbit hole goes. I have a feeling we're going to find out very soon." So besides making amazing video games, why does this matter?

• 25:38Peter Diamandis?

  Well, robots and AI agents are going to train in simulated worlds. And before they touch the real one, you know, it's being rolled out to trusted testers. Again, we're seeing the same thing here. It's being rolled out a little bit at a time, then to Google AI Ultra subscribers and developers. So I'm curious, for Ahmad and Alex, does this strengthen your views on the simulation theory or not? I mean, the stuff we're doing is extraordinary.

• 26:05Speaker 03

  Yeah, I maintain that there's one set of equations for all of physics. Like, it isn't suggestions, it's a law. And the equations of generative AI are likely to be remarkably similar because they map physics and you see these models learning from everything. So in that, we're trying to find almost the divine, these core kind of elements there. Because the universe came from something, it was generated from something. And so I think the wonderful thing about this is, you know, again, it learns physics, it feeds back to the real world, it feeds back to real systems that we can use to explore the universe and more, and it will accelerate our understanding of all of these different phenomenon when we can finally model them properly through just these massive training runs, which is, I think, is just fascinating and fantastic.

• 26:48Peter Diamandis?

  Alex?

• 26:50Speaker 04

  Yeah, I think maybe the most interesting item buried in the Genie 4 announcement was planned future work by Google. Google now has explicitly said that they want to converge Gemini and Genie. And presumably, although I don't know if they've published, to my knowledge, I haven't seen any publications of architectures behind the scenes at this point with Genie 4, presumably it either looks diffusion transformer-like or looks something like transformer, maybe with a few different. We've talked about Gaussian splats in the past on the pod. We've talked about unreal style surface engines on the pod. Just based on the videos that Genie 4 seems to be interactively generating,

• 27:33Speaker 04

  my guess is it's diffusion transformer-like at the backend, and that is potentially architecturally convergible with the architectures of the foundation models like Gemini. And I do think one of the weak, historically weak spots on the Anthropic model side has been weak visual perception. I think Opus 5.5 goes a long way to repairing what I've perceived as deficits in Anthropic's models to think about and visually reason. I think the best, the bull case for Google converging Gemini and Genie would be models either for robotic manipulation. I think we've probably saturated visual design for computer software development, so not super excited about that.

• 28:18Speaker 04

  Probably something that requires, something economically valuable that requires real world orchestration could be robotics. I mean, robotics is what everyone else is investing in. Could be something else in the physical world, maybe operating laboratories or visually reasoning about physical modalities, chemicals, for example, that otherwise are difficult to, to arrive at novel economically transformative solutions from just purely based on text and images. But I also want to highlight that Google seems to be the only remaining American frontier or near frontier lab that's investing in video generation. And I would view these so-called world models, interactive video models, as, as just a natural generalization of video gen.

• 29:02Speaker 04

  OpenAI had Sora, dropped it. We've seen other, smaller American players develop their own, you know, video generation models, but Google is the largest credible remaining American resource for video generation. Otherwise, the whole game is being thrown to China. So I want to applaud Google for continuing to invest in video generation, because otherwise it's just a Chinese video world.

• 29:27Peter Diamandis?

  Let's take a look at their, their video announcing this one second, and then we'll go to you, Dave and Saleem.

• 29:33Speaker 06

  Genie 4 is our most realistic and interactive world model yet. Build environments and simulate worlds on command. Keep prompting, and Genie 4 will work out what happens next. Then explore and reshape them in real time.

• 29:57Peter Diamandis?

  So here the prompt is the bird to press a key on the keyboard.

• 30:01Speaker 06

  Transform a picture into a dynamic environment that's ready to explore.

• 30:07Speaker 06

  Complete with ambient sound.

• 30:10Speaker 04

  I mean, you know, this is going to get used for video games.

• 30:13Peter Diamandis?

  Yeah.

• 30:13Speaker 04

  It's not quite there yet, but.

• 30:16Peter Diamandis?

  Yeah. And holodecks.

• 30:19Speaker 04

  Holodecks. It's a consumer.

• 30:21Speaker 06

  Move the camera, direct every detail.

• 30:28Peter Diamandis?

  It's pretty beautiful.

• 30:29Speaker 06

  And the world change live.

• 30:31Speaker 07

  Do you really think we're gonna make it?

• 30:39Speaker 06

  Or describe an interactive experience.

• 30:43Speaker 04

  If they're smart, they'll use. If they're smart, they'll use this to replace YouTube. YouTube is a sizable revenue source.

• 30:50Peter Diamandis?

  Yeah.

• 30:51Speaker 00

  I think YouTube video on demand. Way beyond entertainment. It's definitely, in my mind, the future of all work is in this environment. I have a bunch of videos that I took to the West Coast with me and they're about photonic computing. I had one on chain theory. And, you know, I've got Albert Einstein and Isaac Newton and Mary Curie explaining everything. And I'm showing it to Nobel Prize winners and, you know, business owners. And they'd so much rather watch the video than hear it in PowerPoint form. Yeah, well, yeah, or any, I mean, yes. But or anybody. It's just so much more. It's so much easier to learn from an AI created video. The only flaw so far is it's not real time.

• 31:35Speaker 00

  You can't ask it questions in real time. But now with Genie, we're.

• 31:39Peter Diamandis?

  It is real time.

• 31:40Speaker 00

  Like, like as of this week.

• 31:42Peter Diamandis?

  Yeah.

• 31:42Speaker 00

  Everything flips over. The future of all management is going to be through this interface. And it's so much more effective. And it's really fun compared to, you know, writing emails and, you know, writing documents. So it's really engaging for managers. But also, if you think about, you know, how much of the world is factory assembly lines and construction projects and whatever. And you're like, you know, guys, we should be putting that beam over there and this elevator shaft should move. And as you're saying it, it's re-rendering and showing the construction team what you had in mind. That is irreplaceable. Once you've experienced it, you immediately realize this is the future of all management. It's not just entertainment and video games at all. It's all management of all ideas and production of everything.

• 32:25Speaker 00

  So it's much, much more significant and.

• 32:28Speaker 01

  I had the, I had the same experience. I was yesterday at a factory in Toronto where they were kind of using AI to automate. And when I saw this, right, you're going to reach a point where you can simulate an entire factory, its operations, troubleshoot problems before even building the thing. And I think, Dave, you're so dead on. This is such a huge, huge shift. It's going to take people time to get their heads around it is the problem.

• 32:53Speaker 00

  Yeah. Yeah.

• 32:55Speaker 03

  Yeah, to give you an idea, I estimate the cost of running this is $20 an hour of running Genie 4.

• 33:02Speaker 03

  And that'll be down to $2 next year. And you'll be able to.

• 33:05Peter Diamandis?

  We've talked about, you know, every bit, every, every pixel being generated on demand. And now it's just a customized, I mean, you can have your AI read your emotions and actually generate a movie that plays exactly to your emotions as you're doing it or a video game. Crazy.

• 33:22Speaker 00

  Yeah. Well, I think if you walk around and talk to, you know, people in business and say, have you ever used a CAD CAM system? 99.9% have no experience with CAD CAM. But if you talk to somebody in mechanical design that uses CAD CAM, the idea of, of working without it is insane. Like, it's just so ingrained in the way they imagine and visualize and then try and create. So now I think that CAD CAM experience will export out now to every area of human endeavor through this. And so, so people will never go back once they've experienced designing, building, creating, structuring, planning, even if it's just a party, like a wedding party. Where's everyone gonna sit? You know, just instant visualization of the tables and people milling about.

• 34:06Speaker 00

  Like, even that use case, you never go back once you've experienced it.

• 34:10Speaker 01

  You could even have family members arguing, fighting each other as you plan out the wedding wedding layout. That'll be easy to simulate. I have a, I have a, you know, with all these, this stuff changing, I'm updating the organizational singularity book in real time. Right? And here's the question I've got with when you, when this comes out. If you can simulate an entire business or a physical operation before you build it, all strategic planning is now obsolete. Like, because you can essentially envision it, think about it, run the simulation and see what happens or not. This is like completely changes the game now for strategy consultants, all C-suite planning, everything.

• 34:52Speaker 03

  So, so what you're saying, Salim, is that the singularity is going to automate human labor?

• 35:00Peter Diamandis?

  Cognitive and.

• 35:01Speaker 01

  Thinking. And, well, now it comes down to imagination. We have to start, and at some point it'll replicate imagination, but for now, we have to do the imagination, imagining of it, imagineering of it, if you're going to use Disney's world.

• 35:14Peter Diamandis?

  For now. For now.

• 35:16Speaker 00

  For now, but I think it's a really important point. Like, nobody knows if the for now is a couple of years, a couple of months, maybe 10 years. It's somewhere in that range.

• 35:24Speaker 01

  Well, it's a couple of weeks at this pace. I mean, for God's sake.

• 35:26Speaker 00

  Well, maybe, maybe not, but people get intimidated and then they don't jump in. They're like, well, you know, no matter what I'm adding to the party here, it'll be irrelevant soon. And I don't believe that. I think, I think right now the AI is not good at all at imagining outcomes. But it's really good at creating the outcomes that you imagined. It's the golden moment for humanity, for creators right now. And to waste even a minute of it is, I think, utterly insane. But a lot of people are wasting it out of fear that AI will, will make whatever they're thinking of irrelevant very quickly. And I just don't believe that's likely.

• 35:55Speaker 01

  Yeah, can I, can I just segue to this video I put up here?

• 35:58Speaker 03

  Yeah, of course.

• 35:59Speaker 01

  So I put out a video yesterday, basically asking a simple question, right? And it's getting like crazy comments and it's worth revisiting because I think it's the thesis of this entire podcast, which is everybody's bemoaning the lack of the destruction in jobs and going, oh, my God, what will we do when all the jobs disappear? If you flip that around and say, wouldn't it be the greatest thing ever if all the jobs disappeared? You, you can start to imagine now how you get there.

• 36:27Peter Diamandis?

  But you have to add to that, Salim, if, if you didn't have to work is the.

• 36:31Speaker 01

  If you don't have to work.

• 36:32Peter Diamandis?

  And you still maintain your quality of life.

• 36:34Speaker 01

  Yeah, we have a precedent for this called retirement. We're used to spend 50 years working to get that 20 year time where you could do whatever you want, work on your hobby, kit car, spend time with your grandkids, do whatever, but you're too old to really do much. Now, if we get to the right time and get to the point and figure out how to do the economic distribution, you can spend time on creative passions, spend time with family, work on building communities. And let's start envisioning that future because that is actually going to become possible. There was a great, I asked them for comments around what might happen if people do this and what would it look like? Somebody, VK4058, got the great, gave the greatest comment. He said, what's actually going to happen is people will turn into easy dopamine addicted

• 37:16Speaker 01

  bonobos with IQs gradually approaching those apes. And I thought that was awesome. But the, but the, you could go down a Wally scenario and you could go down it, you know, have the greatest life of being presencing ever. And you see people in retirement doing one of those two things. They either go, they fade away or they get super active. Right? One of my uncles is doing a PhD in astronomy because he's retired and he's not doing that. I think it's going to be incredible to see. And I put that provocation out. It's fascinating to see the results.

• 37:47Peter Diamandis?

  So, so important to point out, you know, the importance of purpose, the importance of having goals and objectives when you don't have to work, right? I love the fact that, you know, William Shatner, now 95 years old, is, you know, appearing in rock concerts, flying to space, you know, he's going to come and do the closing conversation at the Abundance Summit. I mean, you need to have purpose. And the biggest concern isn't that you don't have to work. It has work always been your purpose in life? And if it's taken away from you, are you, you know, sort of lost? So, yeah, Imad, please. Yeah.

• 38:23Speaker 03

  I figured out something, listen to this. The biggest difference between humans and AI is conviction.

• 38:30Speaker 03

  Conviction to do stuff to push it forward. Like, what does Elon have? Massive amounts of conviction, right? He made the world go around him. Like, when you were talking about strategic planning, Salim, that's like an expected utility, like, the world is static. Whereas now, we have the biggest levers ever if we have the conviction to push things forward. And you see this when you're talking to your AIs. And like Claude says, you're 50% right and 50% wrong. And 50%, that's right. It's the interesting bit. Or like, when you actually look at the code of Astra, and it's finding like edge cases that you were like, that will never happen. The AIs lack conviction. So they can deal with the current environment. But it's the humans that can push things through with individuals and people around them and agents around them to achieve the massive change. And I think we should reframe it like that.

• 39:15Speaker 01

  Why do you think AIs couldn't do the or simulate that same conviction? Or take, you could say to an AI, I want you to take on Elon Musk level conviction and let's solve these problems? Why couldn't you do that?

• 39:29Speaker 03

  So I think that part of it is, the AIs, the way that their distribution of their latent space is set up, is that they tend to do like exploration. Like, even when the tuning and the training, they do Monte Carlo tree search. So it's very rare that you see an AI that actually has a conviction and pushes it forward. Whereas you see lots of humans achieving great things. What do they all have in common? They have conviction. They have determination and more. So I think it's just something about the architecture. You could build an AI with huge conviction. Like, now, there are experiments where you're turning on little neurons, and then they collapse their entire wave function. But that's not how AIs are right now. And so I think, again, once you realize that, and you realize you can do everything, you can tear the threads

• 40:10Speaker 03

  of the universe. That's the really interesting thing here. Because if you have a company.

• 40:15Speaker 04

  Sorry.

• 40:17Speaker 03

  Yeah, I was just saying, the framework for this is, Jeff Bezos said, you know, he has a model where he has the inevitable and the unchanging. So it was like, there would be books, and people always want faster, cheaper, better. Like, what business strategy doesn't work with that, right? Like, the way you get there is one thing. But he had that conviction there, and then the whole of Amazon went that way. And strategic planning doesn't really fit with that necessarily. Which is why, if you know where the future's going, and you pull it forward, then you can achieve bigger things than strategic planning would indicate. Sorry, Alex.

• 40:48Speaker 04

  I think I'm much more optimistic that conviction, or call it long-term strategic planning, is very much within sight of models these days, even just a system prompt away. I think the distinction between, say, business leaders, Elon at all, and the models is Elon, at this point, has quite a bit of capital. And he's also very good at marketing. When Elon decides, no, actually, we're not going to Mars next, we're going to the moon next. It was the moon all along, and retcons the moon into SpaceX's plans. That's branded as business genius. Whereas, if a model did it, one might say, well, the model lacked conviction on getting to Mars first versus

• 41:29Speaker 04

  moon first. The models don't, aren't yet in a position where they're allowed to market themselves as having these long-term ideas. They lack the capital, certainly. They're unbanked. And I would suspect, if we had a model, and it started with some long-term system prompt, like, carry out the following really challenging objective over a period of years, and we provided it with the capital to do it, and the real-world engagement and empowerment to do it, it would probably be able to market itself just as competently.

• 42:03Peter Diamandis?

  Well, guess what, guys? We're gonna find out soon enough. That's the beautiful thing. Our third Google story, and now the paradox, you know, Google shipped the number one, arguably not yet publicly released, AI model. And on Thursday, Alphabet had the worst day from a stock perspective in history. Its shares dropped 13%, wiping out $500 billion in market value. You know, the strange thing is, revenues grew 25% to $127 billion. Google Cloud more than doubled, up 100%, and Gemini app hit a billion users. So what sparked the market? Two things. First, search. Search ad

• 42:43Peter Diamandis?

  revenue, while it grew 12%, was down 17% from last quarter, and 19% from earlier in the year. So people are very concerned that their main revenue driver may be on a waning trajectory. And second, cash. Alphabet burned $9 billion of free cash flow in the quarter, far worse than expected, while keeping capex at $195 to $205 billion for the year. You know, a few other stock movers worth noting here. Both AMD and Intel were both down. Intel dropped 28% today, you know, kind of crazy.

• 43:21Speaker 00

  30, 30 plus.

• 43:23Peter Diamandis?

  Intel's results beat estimates. Its outlook for the quarter came in below expectations. The CFO said that the PC sales were down, driven by, you know, expensive memory chips. So I'm curious, Dave, your thoughts on the market here? I mean, we've been talking about the potential AI bubble, the leak in the AI balloon. It's continuing. What are your thoughts?

• 43:49Speaker 00

  Well, what's going on here is really obvious. The Mark Zuckerbergs, Sundar Pichai's, Lip Bhutan's, they're gonna invest more money than humanity has ever invested before for AI. They are 100% believers that whoever controls the chip stack or the AI algorithms controls the whole future of the world. And so the idea that, you know, some of the most profitable companies we've ever seen, like Meta, like, just an absolute cash machine, is now borrowing tens of billions of dollars, because even that cash flow is not enough. We must do AI. We're not slowing down. You know, the market is now like, oh, my God, I'm getting scared. I'm really jittery about this. They're not gonna stop, though. So it'll probably get worse before it gets better,

• 44:32Speaker 00

  in the sense of, like, they are not slowing down, and they're 100% right, and this is the only moment, this is the moment in all of human history. And so, you know, if ultimately, there just isn't that much money in the world, then, then things can't rebound. You know, the money just physically doesn't exist. And but they're starting to draw from every nook and cranny and corner of the debt markets all over the world into this massive build-out. So, you know, a week ago, the market was like, yeah, this is all gonna work out. Now, now, everybody on Wall Street's like, oh, my God, that's a huge amount of debt. And also, the shortage of RAM, that ain't going away. Like, we did not build anywhere near enough chip fab capacity to keep up with

• 45:13Speaker 00

  the need for massive amounts of HBM memory. And so now, people can't upgrade their iPhones, can't buy a new iPhone. Why? Because it's too expensive. Why is it too expensive? Because the RAM prices are way up. And Apple has its first earnings, you know, shortfall in, as long as I can remember. Why? Because they have to pay so much more for RAM. So AI is gonna suck up every resource in the world, and it will absolutely all pay off. There's no doubt about it. But the question is, what about between now and then? You know, like, what's gonna happen? Should we all be like, should we all stop eating and just, you know, pump that, pump that money back into AI? Generation? There's a rational argument that we should just all subsist on rice for as long

• 45:58Speaker 00

  as we can, but put that money back into chips, because it'll pay off a thousandfold.

• 46:03Speaker 04

  Dave, we've talked about how some employees purportedly at Frontier Labs have taken up smoking, because they just think their cancer will be auto-cured in a few years by their AIs anyway. It's even worse than that.

• 46:15Speaker 01

  My liver enzymes are up 50% after, because I'm on retinotropia, so I'm able to drink more wine. I think this is great. I want to make a comment here. I think we have something really amazing going on here that is worth talking about, right? Which is the unbelievable gumption and cojones of these CEOs to make these massive billion-dollar bets. I mean, you know, we talked about conviction just now, right? Whether it's Sundar, Satya Nadella, Zuckerberg, whatever, they're coming unbelievable amounts of capital to a future that's not arrived. They're absolutely so convinced of this, the conviction they have, like, they're saying, screw it, if we think

• 46:58Speaker 01

  intelligence is gonna become this, the foundational infrastructure of civilization, we're gonna build for that future. And that takes amazing conviction. You know, half the people are like, yeah, and there's all these people saying it's a bubble, they're spending too much. And look at that, that kind of dedication. That's why these types of people win, because they have that conviction, and they're willing to do it.

• 47:18Speaker 00

  I'll tell you, Salim, the people that are closest to the truth, so the Elons and the Zuckerbergs, the guys inside the middle of it, they have the most conviction. And that tells you, that tells you what's really gonna happen. It's the people on the edges, you know, that are kind of investing through a series of funds that aren't quite sure. They're the ones that are panicking. So.

• 47:36Speaker 04

  But I would just ask, what choice do they have? I mean, even Zuck is purchasing GPUs left and right, and has the reassurance Meta compute can always absorb any extra capacity that he can't monetize. But if you look at a Google, really, what choice do they have? There are other bets, and of course, all do deference to X and Astro and the other bets, but they have Waymo. Okay, that's been a success story. But other than Waymo, in terms of revenue, for the moment, they really, other bets have not had a major success. On the other hand, if you look at GCP, Google has been often characterized historically as a one-trick pony, and their best next trick has to be, just based on the financials, has to be serving as a

• 48:19Speaker 04

  hyperscaler. So even if it means cannibalizing search revenue in order to become the best possible hyperscaler they can, honestly, I'm not sure Google had much of a choice but to cannibalize themselves if they wanted to keep growing.

• 48:31Peter Diamandis?

  They're playing the long game, guys. They're playing the long game. I remember there was a quote from Sam, I have a video, I should have found it, where he says, we're building an AI god. I don't care how much it costs. Right? And I think that's their attitude. This is, they're putting all in on all the chips right now. They have to.

• 48:51Speaker 00

  Keep in mind, Sergey and Larry are still controlling shareholders of Google, if you can believe that. Nobody really pays attention to that. They still control it. And that's where that that fortitude comes from. Zuckerberg, it comes from him. Elon, it comes from him. But to answer your question, Alex, the other choice would be to be where Apple and Microsoft are.

• 49:09Peter Diamandis?

  Right.

• 49:09Speaker 00

  And which, just kind of touching around the edges, not really doing a huge amount.

• 49:14Speaker 01

  European infrastructure CEO.

• 49:16Speaker 04

  Remember when Microsoft said, we're good for our 80 billion? And that was like, the beginning of the end for Microsoft, reaching for all the possible capital that they could for in for a build-out. Microsoft bowed out of the hyperscaler race in some sense. I do agree with you, there's an element of founder mode, reaching for the capex, even if it means cannibalizing the legacy businesses here.

• 49:37Speaker 03

  I think that the market is missing something huge here. We've talked about GPUs and DRAM and necessity being the mother of invention. If we have 10 agents per American, there are not enough CPUs in the world.

• 49:52Speaker 00

  Yeah, no doubt.

• 49:53Speaker 03

  Not even close.

• 49:54Speaker 00

  Not even. Exactly. Great point. Great point.

• 49:56Speaker 03

  And who was number one in CPUs? Intel. You know, you have Intel, ARM, and you have AMD. Those are the players.

• 50:05Speaker 04

  For desktop, I mean, but in terms of overall CPUs, it's, well, for mobile, obviously ARM. And then for actual CPUs, putting aside chip architecture, it's probably something exotic, like some microcontroller architecture or something. So not necessarily Intel.

• 50:20Speaker 03

  Well, CPUs for agents, you've got obviously your gravitons from the hyperscalers and others. But I think we're always looking for where the next bottleneck is. And right now, it's clear that we're going to go from less than one to more than one agent per person. And we have discussed previously how inference costs are going to collapse. And maybe the GPU buildout is already there. So we have the capacity coming on of millions of Vera Rubens and MI450s, et cetera. The CPU buildout with two to three years of lag time is only just starting. They haven't really invested there. So when you actually do the math, it's clear that this is, for me, this is going to be the next bottleneck. Because agents need CPUs.

• 51:00Speaker 04

  I'd love to push on that just a little bit, if I may. So what I think you're, what I hear you saying, Ahmad, is you're sort of predicting monotonic growth of number of agents per person. And with that monotonic growth, the implication being it won't be GPU bound, it'll be CPU bound. There is an alternative way that this could play out, which is that as the baseline foundation models get stronger, this explosion that we might naively see in terms of number of agents per person, might actually reverse in the sense that when OpenAI released their Navier-Stokes results, they went out of their way to say, I was 10,000 results, 10,000 agents over a short period of time. But then by the time of Bell and the slop drop, it was one agent for three hours. So an alternative

• 51:44Speaker 04

  perspective might be actually, as the models themselves get stronger, the need for swarms of agents or large numbers of agents actually diminishes. And that then impairs the need for CPUs altogether. What do you think?

• 51:56Speaker 03

  I think that, again, I'm not talking about 100 agents per person. It's like 0.1 to heading towards one. And if you look, again, four, five years out, I think you have at least one. And they need houses. And there are not enough houses built. And the lead time for RAM, we've already seen, and we've seen what happened with RAM, right? Lead time for CPUs, again, it's a couple of years. So I think the market's going to look at this, probably not now. Again, Intel is down 30% today. That's one of the biggest moves in the stock market ever. Like, I think it's going to be an interesting, as we look for the next narrative, we look for the next choke point. And as you said, a single model actually can do a surprising amount. Sometimes you do see these massive increases like Navier-Stokes, but also single models outperform a dozen models in many cases.

• 52:40Speaker 07

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• 53:44Peter Diamandis?

  All right, I'm going to move us forward. Our next two stories come from a conversation that Sam Altman had with John Collison, the co-founder of Stripe, on John's podcast called Cheeky Pint. And I think we should all be drinking beers during this podcast, guys. About half a beer.

• 53:59Speaker 04

  We drink, we drink water here. Unlike the Collisons, who are drinking alcohol, we drink water.

• 54:04Speaker 00

  Who's we, white men?

• 54:08Speaker 04

  No comment.

• 54:09Peter Diamandis?

  All right. So about halfway in drinking his beer, Sam said, I'm actually probably not supposed to say this, but since we're drinking, all right, let's watch the clip here. How much should the math cost?

• 54:22Speaker 03

  Order 10 million per like, for like Navier-Stokes, I think.

• 54:25Speaker 06

  Okay.

• 54:26Speaker 03

  Maybe a little more.

• 54:27Speaker 06

  10 million-ish.

• 54:28Speaker 03

  10, 20.

• 54:29Speaker 06

  That order might shoot. Yeah, yeah. But for one proof. And so 700?

• 54:32Speaker 03

  Well, no, no, because then we kept getting better so fast. Like, we understood more, like.

• 54:35Speaker 06

  Got it.

• 54:36Speaker 03

  We spent way less than that on the average one of those.

• 54:38Speaker 06

  But like hundreds and hundreds of dollars of math.

• 54:40Speaker 03

  Yeah, yeah, that kind of work. Interesting. But that include like, that includes like much more other discovery than what we have published.

• 54:47Speaker 06

  Yes.

• 54:47Speaker 03

  So it was like, maybe we spent that much.

• 54:49Speaker 06

  More than the 700 proofs?

• 54:50Speaker 03

  We did, of course.

• 54:51Speaker 06

  When did you get those?

• 54:51Speaker 03

  It was one weekend when we got a new model. And in, I'm not supposed to say this, but I will since we're drinking.

• 54:57Speaker 06

  Exactly. We're half pint in, yeah. Perfect time.

• 54:59Speaker 03

  The name of the channel was model name dash hold my beer. And people were just throwing that at the hardest problems they could. And people just like, didn't think the model was going to do these things. And we had this collective experience of people's like hardest research problems from their academic career. The model was just knocking it out on one after the other, many different fields. It was incredible to watch. And kind of two nights in a row, I was up most of the night because I was so excited, I couldn't go to bed. It was, it was like, many of those problems that we published, many other things. And I was tremendously excited and happy. But I also had like much more sadness and melancholy and like a feeling of like something ending than I was expecting. So, again, I agree,

• 55:44Speaker 03

  this is the right thing on behalf of the world. And also, I agree that this is just like the shape of reality and nothing that anyone can stop or should stop.

• 55:51Peter Diamandis?

  Can you imagine, you know, 10 years ago, saying a company, a private company that's not in the mathematics business, spending 100 million dollars to solve problems? It's crazy. So, you know, Alex, you know, what do you think is sitting in the unpublished pile of math proofs?

• 56:10Speaker 04

  I can only imagine, certainly, probably the remainder. We, last time, when we talked on the pod about Navier-Stokes, I predicted, and I think Ahmad, you predicted as well, Yang Mills. So we already know now a bit more about their Yang Mills strategy. Probably a bunch more Millennium problems. I wouldn't be surprised, I'll give a hot take on this one, wouldn't be surprised if there are further advances beyond ETH that collapse the complexity hierarchy. That would be pretty scandalous. Wouldn't be surprised if there are lots of cryptographic or counter cryptographic advances that they're sitting on, not publishing, going back to the original Q-Star allegations. But I also want to touch on Sam saying, hold

• 56:50Speaker 04

  my beer. This is, remember, in the context of GPT, I think it was GPT-5 with the Star Wars space station, the Death Star, and he was using a lot of Death Star motifs, Sam, on his X post to describe it. And the Obi-Wan Kenobi line of, I felt a great disturbance in the forest, as if millions of voices suddenly cried out in terror and were suddenly silenced. And here, Sam and OpenAI are sitting around joking on a Slack channel, model name hold my beer, about basically crushing entire disciplines. I think their, history will regard this as a striking asymmetry between sort of casualness on the interior with super

• 57:33Speaker 04

  intelligent superpowers, and on the exterior, entire fields rolling over and playing dead because of it. I think it's striking.

• 57:42Peter Diamandis?

  So, I'm curious, you know, he said he felt sadness, right? An emotional response to this. What do you make of that?

• 57:55Peter Diamandis?

  A big sigh.

• 57:58Speaker 01

  I think, you know, when there's a sadness for the art form that gets lost when you get such magical outcomes coming from things. So there's, the craft gets lost. I think that's what he's referencing there. But the fact that we can get so many more outcomes should make you way more than happy for that sadness to balance out.

• 58:23Peter Diamandis?

  I think it's sadness for the old way of doing things, sort of nostalgia.

• 58:27Speaker 01

  But this is, but this is the same. You talk to any systems programmers, they go, oh, what happened to all the great assembly line coding? Right? And that was great for that period of time and for those types of systems. But now we have so much more power and other levels. I think it comes down to that.

• 58:42Peter Diamandis?

  Yeah. Dave, I mean,

• 58:46Peter Diamandis?

  What he's talking about is wholesale reinvention of entire fields for millions of dollars, and we haven't seen their best models. What do you, you know, I'm curious if you think that, you know, OpenAI's value in the future is going to be everything they build on top of these models, everything they discover, rather than selling compute or selling tokens?

• 59:09Speaker 00

  Yeah, it's a golden age, but, you know, coming back to the emotional reaction, it's, I think if you looked into Alex's eyes on the last podcast we had when we were talking about chain theory, I really felt that same vibe that Olympic gold medalist has when they, they've been working for a decade toward this outcome, and they suddenly have the gold medal in their hands, and they're over the moon excited, but then after that wears off, then you're like, okay, well, now I have to retake stock of my entire life now, where are we? So the people working on these, these foundation models at OpenAI have been at it for over a decade, and they're some of the hardest working people you've ever seen in your life. Remember, they, they invested in that company that allows you to sleep for four hours and feel like you slept in eight, for eight?

• 59:50Peter Diamandis?

  Yeah.

• 59:51Speaker 00

  So they could try and recapture?

• 59:52Peter Diamandis?

  Yeah.

• 59:53Speaker 00

  Yeah, just trying to get four more hours a day, but that's, that's been their mode of operation for years now toward this outcome. As soon as you start cracking the world's hardest math problems, you know that you're over the threshold of success, which is always a wistful moment in time. It's like, wow, now we're in a whole new chapter for humanity, where now we have to actually, yeah, like you said, Peter, now we have to leverage this to make the world a better place. So that starts a whole new chapter, but the, the immediate target, the urgent target has been achieved, and that's what creates that wistful feeling. So, yeah, it's a, it's a new world, you know, like the, the world after 2026 will be nothing like the world prior to 2026, and here we are, right on the precipice.

• 1:00:36Peter Diamandis?

  Yeah, I, I think part of it is, you know, are we going to run out of the big problems that we wanted to solve, that we can now solve, and then continue to push it? I mean, this is, you know, again, human purpose, human conviction. And we go to our second clip, in the same conversation, Altman revealed that OpenAI's robotic program is pointed at, get this, building data centers. So he said, quote, "People talk a lot about RSI as an AI that does AI research. There's very little, relatively little speech about self-replicating data centers." All right, let's watch this, this clip, it's awesome.

• 1:01:11Speaker 07

  I think the trend is toward a, we always just want more compute, like, the demand for sufficiently capable models at a sufficiently low price, I think that trend only goes one way. And we're, we're doing a lot of things to try to be prepared for this. Our, we made a chip that is an incredible performance at like, you know, units of intelligence performer, units of intelligence per watt. We are learning how to build our own data centers. We have a robotics program that we're going to point at making lots of data centers. People talk a lot about-

• 1:01:45Peter Diamandis?

  The real RSI.

• 1:01:46Speaker 07

  Yeah, people talk a lot about RSI as like a AI that does AI research. There's very little, relatively little talk about like self-replicating data centers. You know, this idea that you can use AI to control robots and run fabs and build turbines or solar panels and, you know, build data centers, but I think we are, I think we have that like within grasp.

• 1:02:04Peter Diamandis?

  But-

• 1:02:05Speaker 07

  And so we'll try to make a lot of really cheap compute.

• 1:02:08Peter Diamandis?

  Emod, self-replicating data centers, how far out you think?

• 1:02:13Speaker 03

  Well, you have dock factories and robots already, so why not within the next year or so? You know, I think, again, you're reaching these points and things, like, listening to Sam just now, I was like, that's proust in search of lost time, right? These sorrows will be greater even as our desires are fulfilled. This is not a new thing, we've reached heights as humanity, right? And the question is, what is our desire? I think it's, we quote the world in intelligence, we make it available to everyone, but then the space of solving problems has gone from kind of things that we should have solved, I think, ages ago if our mind had been put to it, and we should solve health, we should solve kind of these things, to solving ourselves, you know, understanding ourselves and more.

• 1:02:57Speaker 03

  And this replication of the thing, like, you shouldn't build data centers, again, this goes to Salim's video, like, why would you need to be a data center tech? You know, why do you need to be an electrician? You shouldn't have to, because if we can build this actually correctly, then we can be freed to think and desire the bigger things in life, and to solve even more interesting problems, including, again, those that are more personal to us.

• 1:03:21Speaker 01

  I had two thoughts when I heard this. One was that this is very reminiscent and duplicative of Alex's inner loop.

• 1:03:31Speaker 04

  Exactly, where did he get this? I have no idea where Sam gets this, it's the innermost loop.

• 1:03:35Speaker 01

  It's the innermost loop, and there's a precedent for this already, like, we've talked about this already on the pod, in China, they have robots putting up solar panels to gather the energy to feed the factory to build more robots, and you have that kind of loop going. If you feed that into a data center side of thing, but the, you know, the, the video also, John pushes back and says, look, the bottleneck is regulatory and permitting and all these human things, that's where the real issue is, and that is going to have to be solved in a different way.

• 1:04:03Peter Diamandis?

  Oh, government, the government will be taken over by AI systems. I mean, so this innermost loop, Alex, you know, robots building data centers, data centers, training the models that run the robots, smarter robots, building better robots.

• 1:04:16Speaker 04

  With lots of energy coming in as well, this is the innermost loop, this is the physical world embodiment of recursive self-improvement. And I think there's one piece that Sam is not saying, Soto Vochi, that Sam is burying, which is, are these self-replicating data centers going to be terrestrial? Maybe not. Arguably, they want to be orbital, or even better, lunar, because they're free of regulatory constraints there. Of course, Sam doesn't want, presumably, to say anything especially nice about orbital data centers, because that's immediately handing the ball to Elon and SpaceX and their virtual monopoly in the short term on heavy launch.

• 1:04:57Speaker 04

  But if, if we are, if we're serious, if we're thinking critically about a future with self-replicating data centers, in a world where, at least at the moment, we have all these municipalities that are hostile to terrestrial data centers, I can only imagine how hostile they'll, they'll be to terrestrial data center construction that doesn't even create local employment via HVAC or construction workers, they're going to hate it. So where, where are these self-replicating data centers likeliest to materialize? I think probably on the moon.

• 1:05:25Peter Diamandis?

  Two predictions here, Alex.

• 1:05:27Speaker 04

  That's the elephant in the room.

• 1:05:28Peter Diamandis?

  Two predictions. Number one, they're, you know, OpenAI is going to buy one of the launch companies. They'll either buy, you know, Rocket Labs, or they'll buy Relativity Space, they can't afford not to have their own launch capacity. And the second thing, I hate to say this, is regulation's going to go to the moon. Every, you know, we've seen regulation go to Antarctica, we've seen it go every place. There's going to be regulation there as well, eventually. The question is, will-

• 1:05:55Speaker 01

  I'll take, make a hot take.

• 1:05:56Speaker 04

  Who's going to regulate it?

• 1:05:57Speaker 01

  I think it's going to be easier and faster to go under the ocean than to get to the moon.

• 1:06:01Speaker 04

  Maybe, I mean, the ocean is more, the, the subsea area is right now, I think, materially more regulated than the lunar surface, but Peter, we have the Outer Space Treaty, we have the Artemis Accords, what sort of regulatory environment are you envisioning on the moon?

• 1:06:14Peter Diamandis?

  I imagine that whoever goes and becomes the dominant sovereign is going to drive regulation. These are US corporations, their US regulatory capture doesn't leave them when they, when they leave a particular country. When you launch your satellites, you're still regulated by the country from which you're launching.

• 1:06:34Speaker 04

  So you think it's going to, I, I agree with the premise that it'll probably be like Delaware and Texas law that's regulating the lunar surface, but that's regulating the actions of American companies with a lunar presence. But what happens when some other country, many of these lunar companies don't subject themselves to American law, they'll, they'll pick some, some other country, usually a country with much more favorable, like Luxembourg, or whatever, with a favorable outer space policy and regulatory regime, what happens then?

• 1:07:05Peter Diamandis?

  Believe me, if there's a chance to, to drive regulations, countries will make the effort. I, I think that is human nature. Now, the question is, are the future regulators going to be humans or AIs?

• 1:07:18Speaker 04

  Well, if they're self-replicating data centers, maybe they're self-regulating data centers as well.

• 1:07:24Speaker 03

  All governments and systems will be run by AI, there's no way it can't be, I think.

• 1:07:29Speaker 01

  Let me help this discussion by saying the following, we should just get the UN involved.

• 1:07:33Peter Diamandis?

  Oh, no.

• 1:07:35Peter Diamandis?

  Dave, close us out on this one. I mean, you know, what are your thoughts here? This is the biggest opportunity we're going to see, RSI and physical as well.

• 1:07:46Speaker 00

  Yeah, and I think that people are way overestimating how much space it takes for a data center to exist. And in a world where your geography embraces data centers, even if you said, hey, we've automated away all the plumbing and HVAC and electrical jobs, and that's not, that'll be, you know, three, four years from now at the earliest. But even in that world, it's generating so much revenue for that little chunk of geography that the immediately surrounding people are going to be some of the wealthiest and happiest on the planet. And I think, you know, the chip supply is so constrained, and in the U.S., the energy is so constrained, that if you wrangle those two things, you're going to be a very, very happy person, regardless of the fact that it'll end up in the moon

• 1:08:26Speaker 00

  on the, in the long, long run. So between here and there, people who embrace data centers, and even the fully automated construction of the data center is only going to make that geography the wealthiest in the world. So it's crazy to me that people don't see that and that they, they fight against it.

• 1:08:43Speaker 01

  Jensen Huang just visited and spent time in Kazakhstan, which has fully embraced this data center build out. They're like, let's just go. So kudos to them.

• 1:08:55Speaker 00

  Well, also, you know, Intel had 300 million of its, of its miss in today's, or yesterday's earnings call was related to their fab in Israel getting bombed. And so people are, you know, there's a lot going on in the Middle East that are making people very reluctant to build out their data centers there. And so if you're, you know, in Canada, sitting on a hydroelectric or a nuclear power supply, you're suddenly, not, not only were you already in great shape, but now people are kind of reluctant to expand into Kazakhstan or whatever because of, of that risk. So you're doubly in great shape if you just jump on the opportunity. So I think, I think, you know, the self-replicating data center is really automated construction

• 1:09:38Speaker 00

  of all kinds of things, but the money is all pouring into data center. So anyone related to the trades, to construction, to finance, just talk to Sam, talk to Dario, talk to the Elon, to people building out the biggest building in the world, you know, the new TerraFab, that is where you want to put all your energy. Work on that first, because that's where all the money in the world is going to go for the short term, and then it'll expand out, you know, to the moon, or to construction of hotels, or, you know, it'll go out from there. But for the next couple of years, that's the total focus.

• 1:10:10Peter Diamandis?

  Highest revenue per cubic meter.

• 1:10:13Speaker 04

  Deep in the heart of Texas, I guess. And also, maybe just a movie reference. I think probably everyone here saw the Johnny Depp movie Transcendence, which, to my knowledge, is the only recent movie that actually does depict a self-replicating data center. They call it in the movie, the Brightwood Data Center, but it's inhabited by the spirit or the upload of Johnny Depp's character. And you watch it rebuilding itself, rebuilding its energy sources in real time with nanotech. It's a, a pretty sci-fi cool depiction of what a self-replicating data center might look like.

• 1:10:42Peter Diamandis?

  I have to watch that one again.

• 1:10:44Speaker 04

  It's pretty good.

• 1:10:45Peter Diamandis?

  Let's continue on, on physical AI. Talk about robots and autonomous vehicles. So first up this week, Tesla announced that their first production quality Optimus robots are coming off the high-volume line at Fremont, where they've replaced producing the Model S and the Model X, two vehicles I love. The line is designed to build a million robots per year, 20,000 a week. Elon says it will take at least a year to get those production line levels up that high, and the first customer deliveries are expected in 2027. Optimus is roughly one to two years behind Elon's original schedule. I mean, it's classic Elon. He gets it right, just typically a couple of years late. So now the global picture,

• 1:11:28Peter Diamandis?

  right? Humanoid robots have been shipped, about 25,000 robots worldwide in the first half of this year, roughly 400% from last year. Chinese companies built more than 95% of them, led by Agibot and Unitree. Total 2026 shipments are projected to double to exceed 50,000 robots. If Tesla hits a million robots a year, that's 20 times the entire world's supply. So, you know, the question is, can we onshore all the production? Dave, your thoughts on that?

• 1:12:02Speaker 00

  Can we onshore all the production? I mean, I think with AI, with AI-based automation, everything's onshoring at an incredible rate. You know, it's, there's a really interesting video on the topic of TSMC, you know, educating people in Texas on how to build chips now, and us needing to re-import all of this knowledge that dissipated out, you know, starting in the 1950s, and then, you know, the whole globalization push pushed all manufacturing offshore. And now it's all coming roaring back because it's not labor constrained anymore. Everything's automated with this rapidly growing, you know, even before the Optimus robots, you have, you know, just factory, regular factory arm robots. But because there's no labor constraint anymore, all of this is going to come pouring back into the U.S.,

• 1:12:47Speaker 00

  which is not great for the rest of the world. It's certainly great in the long run for America, and for the few places on the, in the planet, and China as well, that are doing it. So, so yeah, it's, it absolutely can all come back to America and inevitably will. Also, the, the intelligence that makes it all work has all kinds of export controls on it. And so it's unlikely that it can leak away again, as long as that intelligence is manufactured purely inside the U.S. and China. So, yeah, it's, it's going to accelerate like wild from here.

• 1:13:22Peter Diamandis?

  Yeah, I can't wait for our podcast with, with Brett at Figure AI. It's going to be a fun conversation. I, I wonder what, you know, if Elon is his, you know, sort of competitor of choice, whether he sees himself competing against China. Alex?

• 1:13:39Speaker 04

  Yeah, the, the biggest mystery here is, in my mind, less on the supply side. I'm pretty confident Elon can meet, at least eventually, his supply side goals and catch up to probably past Chinese production. It's the demand side. What is going to be the demand for these? Obviously, I, I think, Peter, you and I are both still waiting for our 1X Neo domestic humanoid robots. I, I would love to have an one or more Optimus robots as well, but this is the part of the equation that I don't see the answer to yet. He's indicated in his past, he's indicated in his past comments that the first application is going to be in, in Tesla factories for, for manufacturing. That's fine, but that's

• 1:14:22Speaker 04

  going to saturate pretty quickly based on his curves. And just like with Starship, suddenly creating all of this new upmass capacity, he almost has to create, I think, a new market to satisfy his own supply to, on the demand side, to meet his supply side. And I'm just not sure, I could think of a range of speculative possibilities. Maybe he'll decide to go domestic early, or maybe he'll aim it at construction, or maybe he'll aim, you know, lots of different industries, obviously just waiting for humanoid robots too cheap to meter. But the fact that he's been cagey, beyond just saying, I'm going to put them in Tesla's or emerged SpaceX Tesla's factories, I think is the most mysterious part of all of this. And I, I do wonder.

• 1:15:05Speaker 00

  Let's trace through the math on that a little bit. Alex, because, you know, he's going to get Model S and Model Y equivalent manufacturing back to all-time highs once the robots are working on it. But he also wants to make a Starship every single day, make a new one, like, every day. So I haven't, I haven't actually walked through how many robots that'll require, but I imagine it's a lot.

• 1:15:25Peter Diamandis?

  And when I'm in front of audiences and I say, listen, these robots are going to cost you, you know, 300 bucks a month, $10 a day, under a dollar an hour, how many of them would you want? Right? And I take a poll of that. Everybody wants at least two. $10 an hour, right? $10 a day. That's, that's insane. I, I think the market for the consumer, if they're proven safe, is massive.

• 1:15:48Speaker 03

  Well, again, I think we can do the math here on just even Elon, and let's say it's just, he uses them internally. The market has, right now, 100,000 to 500,000 robots that he produces next year. 100,000 of them is $3 billion worth of robots. And you compare that against the CapEx of all those things, I think he can absorb even that. But the thing is, this takeoff is going to be absolutely unprecedented. Like, if he gets to a million next year, at 1.6 million, the revenue from Optimus is greater than the revenue from Tesla. You know, that's kind of what we're talking about here. I, to be honest, if I wasn't doing all the stuff I was doing now, I'd be like, let's set up a fund, billion,

• 1:16:30Speaker 03

  5 billion, and just buy 100, 200,000 of the robots and give them the money right now. Because the other interesting thing about this, and we saw this, the Unitree robots, next year, I think, is where you see a freeze in hardware. So the Unitree robots were stumbling around, then they got smart and they started doing flips and stuff. Next year, you'll see a freeze in hardware, whereby it'll be the same Optimus created for a few years, but the software will continuously improve into 2028 and beyond. So if you go and buy all these robots upfront now, the value of them will actually increase, just like we'd seen with GPUs, right? Where you saw that, and now you're seeing that. And this is, again, the next big asset class. But again, if 100,000 of them, which is basically all the production is 3 billion, and you compare it to the computing build out, it's nothing. So this is why the numbers are very strange right now.

• 1:17:17Speaker 04

  Yeah, I'll try saying maybe that slightly differently. SpaceX has approximately 20,000 human employees. Tesla has approximately 130 plus thousand human employees. At these numbers of production, looking out one to two years that Elon is talking about for Optimus, this is just going to spill out well beyond whatever their internal needs or demand for production are, even if they go full on recursive self-improvement. These are, these robots are going to be pouring out onto the streets or to somewhere. I don't think Tesla, SpaceX combined, I suspect, has the internal capacity to just absorb all this output if he sticks with his numbers. That's what I'm gesturing at.

• 1:17:55Peter Diamandis?

  I agree, but you don't think the home use is going to be, you know, sort of the dominant? So Saleem, I'm curious, when you're on the same stage as I am, do you ask this question of the audience? Like, how many would you buy?

• 1:18:05Speaker 01

  No. Because my thesis is that we'll have, we'll spend five years using them in commercial back, back of the office, stock picking, inventory management. There's so much demand to solve that first before it gets to, oh, I need something to do my gardening and pick up my leaves type of stuff. This industrial use will suck up all the demand for quite a while before it gets to.

• 1:18:34Peter Diamandis?

  I just find.

• 1:18:35Speaker 01

  That's my view. I may be, I may be wrong.

• 1:18:37Speaker 03

  I just find one use in my talks that I give, which is a robot chef at home that always cooks you healthy food, which is giving a robot a knife, which is maybe not a good idea. But for, you know, 10 bucks a day, having a great chef, that's a market that's huge.

• 1:18:52Peter Diamandis?

  Absolutely. That knows your physiological state in the moment. It knows your protein levels and your, you know, your vitamin D levels, your hydration, and it, you know, all of your physiological data is getting ported by your AI to the chef to cook you the perfect meal you need at that very moment.

• 1:19:09Speaker 03

  Would you pay 10 bucks a day for that?

• 1:19:10Speaker 01

  But people. That's all great. That's all great.

• 1:19:13Peter Diamandis?

  But people are poorer.

• 1:19:14Speaker 01

  Yeah, like people. The demand from industrial will overwhelm the supply for quite a while to come before you're able to get your home chef, which I love the idea.

• 1:19:23Speaker 04

  Yeah, as I agree with Saleem on this one, consumers, at least in the West, are relatively poor compared to enterprises. So if the consumers couldn't even successfully absorb or metabolize OpenAI's reasoning models, and the best that American, the American economy could think of is like Meta Muse for absorbing reasoning models for consumers, which probably is not that compute intensive ultimately, I just don't see how consumers will be able to afford.

• 1:19:48Peter Diamandis?

  Alex, I disagree. If you're, if you're earning 20 bucks an hour at McDonald's and your robot can do your cooking and your home cleaning at two bucks an hour, it makes a lot of sense for you to have a robot and go and earn revenue elsewhere.

• 1:20:00Speaker 04

  Eventually, yes, but remember, in the meantime, as with tokens flowing to the maximum revenue per token use case, I expect the robots to flow to the maximum revenue per robot action use case, and that's not going to be a poor consumer.

• 1:20:14Speaker 03

  That's why we should set up a.

• 1:20:15Peter Diamandis?

  You have, you have, where's the demand coming from?

• 1:20:17Speaker 01

  And you'll get the, you'll get families running into McDonald's together, grabbing the humanoid robot from behind the counter and taking it home to do the chef.

• 1:20:27Speaker 04

  Okay, so Peter, you're now asking the question that I'm asking, which is, I think, the big elephant in the room, the big mystery here, which is what will be the use case for all of these hundreds of thousands of Optimus robots that maximizes revenue per robot? I don't know.

• 1:20:42Peter Diamandis?

  Yeah, I think they'll, they'll go into industry first, but I think there's an inquenchable supply of, of needs for the consumer as well. Anyway, we're going to find out.

• 1:20:51Speaker 00

  I think, I think to a first order, if you look at Star Trek episodes, you know, it always anticipates, hey, we're going to have a communication device, supercomputer level on our body. What do you know? It's here. Oh, and we're also going to fly faster than the speed of light. Now, that, that didn't happen. So where are we today in terms of robots? I think that what's going to actually happen is we're going to spend enormous amounts of money building out data centers, and the robots are going to be working on that night and day. And they're also going to be building tons of rockets to get more and more Starlink up into the sky. And the spillover into the folding your laundry is not going to happen because they'd be so busy building out the data centers. But then those data centers are going to give you your 3D virtual world, and every

• 1:21:33Speaker 00

  consumer is going to have that and be overjoyed with that long before they have a robot in their house, because the robots are busy building your data center that gives you your 3D virtual world.

• 1:21:43Speaker 04

  Maybe that's it, Dave.

• 1:21:44Speaker 01

  I think you made the point that, I think, you might, you've made the point that construction robots are going to be the massive use case, right?

• 1:21:51Speaker 03

  I mean, you can just do the math around the clock.

• 1:21:53Speaker 04

  Dave, I think.

• 1:21:54Speaker 03

  Yeah.

• 1:21:55Speaker 04

  Yeah, I think, Dave, Dave, the scenario you portray is probably the likeliest one that I've heard, which is Elon inevitably to compete with Sam and his self-replicating data centers decides, all right, tell, message to all, all concerned shareholders, Tesla and SpaceX have to merge because SpaceX needs Tesla's Optimus robots to build out all of its, its terrestrial data centers going forward. So merge them.

• 1:22:20Speaker 01

  Brilliant. Yep.

• 1:22:22Peter Diamandis?

  I, I think the final point is, this is not a demand side problem. I think the demand is going to be there from everything we discussed.

• 1:22:30Speaker 01

  Yeah. And I know, Peter, you're dying for like six Optimus robots in the house, but I think you'll be waiting.

• 1:22:36Peter Diamandis?

  Okay. Well, I'll give each of my, I'll give each of my Grokbots a robot.

• 1:22:41Speaker 03

  That's why I said, I think this, the.

• 1:22:42Speaker 04

  Or maybe, Peter, you have to open up your own data center if you want some Optimus.

• 1:22:45Speaker 03

  Well, that's why I think the smartest thing to do right now is you launch a fund and you literally buy the first 100,000. You will make massive ROI on that.

• 1:22:53Peter Diamandis?

  And we talked about launching, you know, if you're a consumer out there, buy 100 robot taxis and put them to work for you. Right? Which is our next story. So let's jump into it. So Elon posted about Tesla versus Waymo and said, quote, "It never was a real competition." So let me share the chart here, and this was put out by our friend of the pod, Kathy Wood at Arc Invest. And here are the numbers. In terms of dollars per mile, the, the Cybercab is coming in at 20 cents per mile. That's the prediction, or at least what they're seeing today. Waymo's newest version is at 40 cents per mile.

• 1:23:37Peter Diamandis?

  Model Y is at 68 cents per mile, and the old version of Waymo is at a dollar six per mile. So why? Well, a number of reasons. You know, Tesla uses cameras only to build its car. It was a long debate about whether they should be using LiDAR and radar. Waymo is using a multitude of sensors, including LiDAR and radar, and their new minivans are built in China, so they're facing tariffs. You know, the performance is, is interesting today. Waymo has 4,000 robot taxis on the road, 500,000 paid rides per week, and it's in 50, 15 cities fully driverless. Waymo is winning the competition today, but Tesla, you know, I think in my estimate,

• 1:24:22Peter Diamandis?

  probably all of yours, is ultimately going to win the race. They've just built a lower cost, higher performance vehicle. Dave, you know, your thoughts on this?

• 1:24:32Speaker 00

  I mean, I think these numbers are correct, but I also think that catching up is not, catching up in the age of AI is about the easiest thing in the world. And so I wouldn't, I wouldn't write off Waymo slash Google anytime soon. I think the winner is the, the first person to build their chip factory. If Elon builds the TerraFab successfully and quickly, then he wins because he can just make that many more Cybercabs. If he does not win that race, if, if Google does something, and you know, the antitrust action around Google slows them down a lot on this front, but whoever buys either Global Foundry or Intel or whatever and gets control of their own chip manufacturing is going to very quickly retool their auto manufacturing around their chip supply.

• 1:25:16Speaker 00

  So I, it's very subtle, but everything else in the car has multiple vendors and relatively easy, easy to fix supply chains. You know, you're not going to run out of tires, you're not going to run out of seats, you're not going to run out of windshield wipers. What prevents you from taking over the world with driverless cars? It's purely, comes back to semiconductor supply chains that are, that are constrained. Not, not just the chip manufacturers, but also the, you know, the surface mount and the advanced packaging is hugely constrained. So that's why the TerraFab is the linchpin to everything else. So yeah, yeah, he's way ahead, but there's no reason to believe way ahead means anything beyond like a six month window.

• 1:25:56Peter Diamandis?

  You know, it's worth saying there's at least 10 other autonomous vehicle manufacturers out there, from Zooks to others, and the winner here is the consumer. Right? These guys are going to beat their brains out to get the cheapest price per mile. And I find it fascinating, you know, the poorest people on the planet are going to be chauffeured around every place they go.

• 1:26:14Speaker 00

  10 times safer, too. Don't forget that.

• 1:26:17Peter Diamandis?

  Yeah.

• 1:26:18Speaker 00

  10 times safer and getting better.

• 1:26:19Peter Diamandis?

  And getting better.

• 1:26:20Speaker 00

  I mean, the, the human toll of driving is astronomical. It's just a far better world.

• 1:26:26Peter Diamandis?

  Toll on time, on productivity even.

• 1:26:28Speaker 00

  Time, yeah, everything.

• 1:26:30Speaker 01

  I've got two or three thoughts about this.

• 1:26:32Peter Diamandis?

  Please.

• 1:26:33Speaker 01

  I think people are underestimating Waymo's accumulated operational experience within real world transportation, right? It's a different, I think it's a different kind of a competitive advantage. The metric I want to see is not theoretical cost per mile, which is an easy one to compute. What's the fully loaded cost of safe, reliable, completed mileage? Right? Because you have to think about maintenance and remote assistance and cleaning, all this other stuff that comes downtime, et cetera. That's the part I'd like to see. I think you're going to end up with both. Jevon's paradox says that as we make this available, like in LA, it's hard to get a Waymo car now because they're so busy, right?

• 1:27:15Speaker 01

  And so I think the minute these cars become available, the demand will just suck it up. You'll have lots of time for both solutions to build out for quite a while.

• 1:27:23Peter Diamandis?

  And you're going to have your personal AI or your personal bot bidding, you know, what car is close? You know, I pay for time, right? This is, this is your buying back time with these devices. You know, I have meetings, I'm taking a Waymo or Uber, but when I'm going on, I'm asking who's closest, who can get me a ride? You know, they're all, they're all relatively clean and fast, so I'll pay for whatever one is closest to me. So I think production, how many are going to be on the streets is another parameter here.

• 1:27:53Speaker 01

  Yeah, I just want to give a little parallel here. You know, I lived in Manhattan 20 years ago, right? And it was a nightmare because you didn't have traffic signals, you didn't have Spot Hero to tell you where you could park. You basically get to somewhere you're trying to get to, live through crosstown traffic hell, and then guess where there might be a parking garage that would just charge you an unbelievably exorbitant fee. 20 years later, the, the combination of Waze plus Spot Hero means I can navigate in Manhattan incredibly easily, know exactly where I want to park. It just gives me back so much time and mental space. It's unbelievable, and I think that's the part, if you take that as a bridge point, fully autonomous driving takes it to the whole other next level.

• 1:28:36Speaker 01

  God help us, can we please have that as fast as possible?

• 1:28:39Speaker 00

  Not to mention, Saleem, if you're on a corner in Manhattan and you summer in Uber and then the Suburban. This monster two-ton suburban pulls up and takes you four blocks. Like, the inefficiency of that entire loop is nuts.

• 1:28:53Speaker 01

  And that driver is never speaking English to say, "Stop two blocks earlier, please," or something.

• 1:28:59Speaker 04

  Yeah, I'm also not sure the extent to which, so I, first of all, as a preliminary matter, I love my Tesla. I have a Tesla Model Y 2026 Juniper model. I love it. It's wonderful. I use FSD. I think Tesla now gives drivers their FSD scores, what percentage of the time you spend on fully autonomous driving. I think I'm above 96 or 97% at this point. Go from Boston to New York without any interventions. It's wonderful. But I'm not sure Tesla actually, in an era when Elon on the SpaceX side, and there's been quite a bit written about this, maybe doesn't care as much, say, about NASA contracts as he used to. Why? Because SpaceX is now a data center hyperscaler company, and Anthropic

• 1:29:42Speaker 04

  is its largest customer. Similarly, on the Tesla side, Tesla-SpaceX merge, will Elon really care a huge amount around, to Saleem's point, all of the maintenance issues and infra issues needed for Cybercab? I know, north of Boston, on the Google Waymo side, or Alphabet Waymo side, there was this announcement that they just opened up a very large repair facility or maintenance facility. Will a combined Tesla-SpaceX really care about maintenance of Cybercabs, or will it end up just being viewed as almost a cost line item, the way the build-out of supercharger stations was? At one point, there was so

• 1:30:25Speaker 04

  much churn on their supercharger team, Tesla basically paused supercharger build-outs. Will it end up more like that, where it's a nice-to-have, it demonstrates to shareholders that Tesla cares about AI and autonomy, it motivates the merger with SpaceX, but at the end of the day, it's just viewed as a sub-business and isn't fully realized in the same way that Waymo, where it's a pure play, at least within Alphabet, could? That would be my worry.

• 1:30:48Peter Diamandis?

  Or Alex, is, does a population of millions of Cybercabs become infrastructure for infra across the SpaceX ecosystem? And does it become a repeater for Starlink? It's going to have bandwidth, it's going to have power, and it's going to be distributed throughout a busy city population?

• 1:31:10Speaker 04

  If he really believed that, though, wouldn't he be allocating more production to Cybercab and less to Optimus Robots? I would expect Optimus Robots, yeah, sure, Starlink, femto cells or whatever, and real-time mapping of urban environments. But do you think Cybercab is the play for that and not Optimus?

• 1:31:27Peter Diamandis?

  I think Cybercab is going to have 20 kilowatt-hours of power, it's going to be where the people are, and it's going to have, all have Starlink connections being built in from day one.

• 1:31:39Speaker 03

  Yeah, I think people are missing something on Cybercabs and this. It's actually a first-to-market thing, and how you can produce these en masse within a couple of years. I did some calculations, and I saw that in the London or New York, there's about 800,000 trips a day. The amount of Cybercabs you need to completely replace all those Uber and black taxi and yellow taxi trips is 40,000.

• 1:32:05Speaker 00

  Yeah.

• 1:32:06Speaker 03

  So if Elon puts 40,000 Cybercabs in Austin and New York and London, he has the market. Because you're not going to introduce a marginal Waymo into that market, are you? And even then, like, right now, in San Francisco, LA, like, it feels like there's quite a lot of Waymos already and things like that. So can you imagine 40,000 of them? Again, there's actually an upper limit to the amount that the city itself will accept of these autonomous vehicles. So I think that you're going to see a ramp-up. And when you look at the numbers, actually, you see that he could saturate a few first-tier cities and then move to second-tier cities. It's just, I think he's thinking Optimus first, that then builds more Cybercabs. But then, every single city, just do the math, go and talk to your JPT,

• 1:32:50Speaker 03

  how many trips and how many Cybercabs would you need to replace this, and what's the cost of that? And how difficult is it for a second player in that city, then?

• 1:33:00Peter Diamandis?

  Interesting. Production. And of course, Waymo's producing them in China, and he's producing them in his plants here in the United States. Which brings us to our next story. For my colleagues in Cambridge, Massachusetts, Teamsters Local 25 rallied outside of City Hall on Thursday, then testified in the Transportation Committee, asking to keep Waymo and driverless taxis out of Cambridge. Their reasons: job and public safety. So I looked for a few historical analogs, so where there was pushback from the incumbents. Back in 1865, Britain passed the Red Flag Act. Self-propelled vehicles were limited to two miles per hour in town with a person waving a flag, a red flag,

• 1:33:44Peter Diamandis?

  in front of the vehicles. It was repealed, get this, 34 years later, in 1896. And then in 1945, 15,000 elevator operators went on strike in New York City and froze the city's skyscrapers, right? Saying automated elevators were a danger to humanity. And more recently, New York taxi medallions sold for about $1 million each before Uber, and then their values collapsed. So the lesson, you can delay a technology that's safer and cheaper, but you can't stop it. Saleem, I'm curious, how long does this sort of, like, ban against robotaxis take to resolve?

• 1:34:27Speaker 01

  It's, this is a classic immune system response, right? It's like the Luddite revolt, et cetera. Institutions always resist disruption, especially when it's disrupting them. And you can understand it from that one perspective in that level. What they don't see, and I wish they would see, is that black cabs and taxis in New York and other places are busier than ever because of Jevon's paradox. Uber takes up a lot of the rise that they aren't willing to take up, and deals with drunk passengers at 3:00 AM in the morning that they don't have to think about. And this is just a phase they have to go through. My favorite story of this is that Fort Lauderdale blocked Uber

• 1:35:11Speaker 01

  because all of the taxis complained, and somebody in the city commission had a voice, and so they blocked Uber at Fort Lauderdale Airport. This is about three, four years ago. And everybody just went, "Well, why would I fly into Fort Lauderdale? I was flying to Miami." And the plane tickets dropped, the sales dropped at Fort Lauderdale Airport, which meant there was no less business for the taxis, and finally, they had to repeal that. So that'll happen. It's just a question of how long common sense takes to take hold in these situations. It just slows down progress. This is the problem with, the human factor in this is always the biggest drag on innovation and progress.

• 1:35:48Peter Diamandis?

  And Dave and Alex, I mean, this is your hometown, buddy.

• 1:35:53Speaker 00

  It's such a case study in dysfunction, too. I love our governor, Maura Healey. She's phenomenal, and she's brilliant. And to watch her fight through this stupidity every day, and then you go into election cycle again, and then you're just like, wow, no wonder nothing ever happens. It's just nuts. But Cambridge is the most high-tech place on the planet. Four times more venture capital investments per capita in Cambridge than in Silicon Valley, which is second highest in the world. More patents, more Nobel Prize winners. It's just the mecca of technology, and it's just embarrassing to be doing this, like Saleem said, this immune reaction. It's like, come on, here? Are you serious? It's ridiculous.

• 1:36:33Speaker 01

  This is why... Listen, it's the same, this is the same thing everywhere. Like, in Canada, for example, doing venture capital is really difficult because people don't want to take a risk. I got blackballed by the VC Association in Canada because I was in front of them, and they wanted to see profits before they would invest in the company. So I finally started yelling at them, going, "You know there's a V in your name. You're supposed to actually venture the capital. Where's the V?" And that's why I wasn't invited to any more VC events. People kind of get stuck in their old patterns. They operate in the way they're used to. And this is why I go back to my ultimate commentary about human beings. We would much rather be comfortable than happy.

• 1:37:10Speaker 00

  Yeah. Well, the argument that's going to turn the tide is safety, I think. Not, you know, jobs, great, Teamsters, great, but no, no. You're talking about little children getting hit by cars. If you have an opportunity for safety, you have to take that opportunity. So I think that's what's going to turn the tide.

• 1:37:27Speaker 04

  I had, I had an extended member of the family, a relative, who died in the Triangle Shirtwaist Factory fire, which is one of the key incidents that motivated the formation of labor unions in the first place in this country. And I think that marks, sometime around then, marks the beginning of an era. And I think we're coming to the end of an era where manual labor, where it makes sense, where unions are adding to the social good and not detracting. One of the unions, it was reported, involved is the Boston Carmens Union. First of all, Carmen? Second of all, the Boston Carman's Union is a union of MBTA workers.

• 1:38:10Speaker 04

  And honestly, it's both to Dave's point embarrassing, this is also why we can't have nice things, to be in Cambridge where the public unions are actively restraining not just technological progress, but also to the points a couple of you raised, safety progress. The era of unions in America arguably started with protecting human safety. And now in the era of superintelligence, these autonomous vehicles could be radically increasing human safety. And yet it's the same unions that ironically were formed to protect human safety that are now impairing it. So hopefully.

• 1:38:48Speaker 00

  Very well said.

• 1:38:50Speaker 01

  Can I make a direct appeal here?

• 1:38:52Peter Diamandis?

  Please.

• 1:38:53Speaker 01

  If we had a different camera, I'd shift to the different camera, but we don't. But so, you know, if you're a driver in a union that's blocking this, right? You have legitimate concerns. People have mortgages and families and financial obligations and all of that stuff. Gather everybody together, take your union dues and invest it in cyber caps. Then you'll own the means of production. You won't have to work and the revenues and profits will come to you.

• 1:39:17Peter Diamandis?

  Yeah, I think it's really important.

• 1:39:19Speaker 03

  I think it might also be like, come on, guys, you live in a democracy, right? Like, you're in Cambridge, just organize people to say, do you want dead kids? You know, like, use the means that you have to. I mean, again, you can organize students around that you can organize others, like families will speak on the behalf. Because one of the problems is the apparatus of democracy is utilized only by a select few. And that's why they're in front of her and she feels the pressure. But how many people in Cambridge would like safer roads and convenience and be able to do this? More than the Teamsters.

• 1:39:54Peter Diamandis?

  And ultimately lower costs, lower cost per mile.

• 1:39:56Speaker 03

  Cost, different style of living. But the fact is that they are not being organized at the moment, which is ironic because again, the AI can do it. And you can just hit that narrative. Again, who is pushing that self-driving cars mean less dead kids? And there are strict numbers on that. 5,000 less dead kids per year if you have self-driving cars. Nobody.

• 1:40:17Speaker 01

  I just got to throw out.

• 1:40:19Speaker 04

  Imad, I think you're the foreign agent that America is looking to for guidance here to ensure that we prevent child mortality. You're the one. You've been so nominated.

• 1:40:31Speaker 01

  I'll just throw out my favorite stat, which I've said before, half the court cases in the US are car accident related. Half.

• 1:40:38Peter Diamandis?

  That's why, that's why the lawyers are funding the, you know, the car and taxi drivers to basically, you know, put a stop here. Everybody's playing their book. Welcome to the health section of Moonshots, brought to you by Fountain Life. The discussion in this section is for informational purposes only and is not medical advice. Please consult a qualified healthcare professional about your individual needs. I'm a co-founder and client at Fountain Life. You know, AI is impacting every aspect of our lives, how we teach our kids, how we do our business. But one of the most important things that AI can deliver to us is health. And one of the things I think about when, you know, shooting for 100, 120 is, am I

• 1:41:22Peter Diamandis?

  going to have the cognitive health to be able to think clearly and keep my wits about me for the next 50 years? I'm joined here today by Dr. Dawn Musalem, the Chief Medical Officer of Fountain Life and a member of my Fountain Life medical team. Dawn, a pleasure. So Dawn, talk to me about brain health. Brain health, you know, you're right. This is the number one concern people coming into Fountain Life have is, will I remember the name of my child and the face of my loved one? 45% of dementia cases are entirely preventable with lifestyle. And what was really intriguing to me, Peter, is that a quarter of our members had advanced brain age. But over 13 months of us really helping them live healthier lifestyles, eating healthier,

• 1:42:05Peter Diamandis?

  moving their body regularly and optimizing sleep. People overlook that so often, but that sleep optimization is critical for our brain health. What we showed is that we were able to improve the brain age in 46% of those individuals. That's a powerful number. That's amazing. You know, one of the things I love about Fountain is we're constantly searching the world for the most advanced therapeutics and bringing them to our members. So for me and all of you, I hope that you appreciate the fact that you can become the CEO of your own health. You can make sure that you've got the cognitive clarity for the next 50 years. Come and check it out. Fountainlife.com/peter to learn more and become the CEO of your health. Now, back to the episode. All right. We've been talking about Cambridge. Let's talk about educational a bit more. Two

• 1:42:49Peter Diamandis?

  stories tell us that students are rethinking their educational degrees. And they're in two areas of interest, computer science and MBA. Let's look at computer science first. According to new data from the National Student Clearinghouse, enrollment in computer science fell more than 12% this fall at undergraduate level and more than 10% at the graduate level. Two years ago, CS undergraduate enrollment was down 18.4%. Meanwhile, you know, majors like health are growing. The data alone can't prove AI caused the drop, but students are reading the same headlines that we are. At the same time, in business schools are seeing the same thing. According to the Graduate Management Admissions Council,

• 1:43:31Peter Diamandis?

  applications to full-time MBA programs in the US fell 27% this year. That ends two years of growth. Most of the drop is coming from international applicants who are down 38%, driven by stricter visa policies. But applications for Americans also dropped 6%. Students cite economic uncertainty and growing doubts about job prospects after graduation, including the fear that AI will eliminate entry-level jobs and an MBA will be of no use. So, you know, as we think about MBAs, you know, degrees traditionally, what do they teach? You know, analysis, financial modeling, strategic frameworks and slide decks. And that's exactly where AI does its job really well. Hopefully, you know, it's

• 1:44:15Peter Diamandis?

  not too long before we automate judgment, relationships, taste and courage. So Saleem,

• 1:44:22Peter Diamandis?

  you know, you've been talking about this for some time. So what replaces the MBA? Is it just experience building a company yourself?

• 1:44:30Speaker 01

  Yeah. I mean, look, there's only one path forward for business schools and universities in general, which is to become entrepreneurship institutes. We've talked about this many, many times on the podcast. If you're an MBA program, and this will be the same for engineering eventually, you won't study engineering for four years. You'll go build stuff and after four years they'll go, what did you build? And if it was good enough, you get a credential. These days you don't need this. The computer science degree, I have a little more sympathy for because Jevon's paradox means we will just keep writing way, way, way more code for a long time to come and experience computer science folks and people that understand data structures and networking and so on. We're going to be badly needed for quite a while

• 1:45:12Speaker 01

  to come. But the MBA program has been out of date for a while. I've been noting for about 10 years that even 10 years now, like 2026, almost 2027, there's still not a single MBA program in the world that can teach you how to build Uber. Every single MBA program teaches how to build a 20th century organization. And so there's that problem because the curriculum can't be updated in this. The bigger problem, though, is you can't study business to build a bit, to understand business. You really just have to go build it. And the opportunity, because of de-modernization and de-marketization of anybody and their grandmother picking up AI and using it to build a business has never, ever, ever been

• 1:45:54Speaker 01

  better. Peter, you talk about this all the time. Go build a business. Do not take an MBA.

• 1:46:00Peter Diamandis?

  Yeah. Dave, when you and I were in school, a lot of our undergrad friends went and did their MBA degree. It was like the, you know, the most important degree you could get, you know, go get a job on Wall Street. Are you seeing MBA students in, inside of Link, the Link ecosystem?

• 1:46:18Speaker 00

  Well, the venture funds, you know, the deal negotiators and the capital raisers are mostly business school alums for sure. But, you know, we would take people in that role that have won one year and they're done, or they were about to go to get their MBA, but they decided not to get it because the moment's too urgent, you know, that they're just as good. It's the, it's the building mentality. But I also think that the labels are out of date. If you said, look, Python coding is dead. I don't want a degree in Python. And financial modeling and spreadsheets is dead. I don't want a degree in financial modeling and spreadsheets. But what do I want to study? Well, Imad said earlier on the pod, somebody who goes and raises a $5 billion fund right after this podcast to buy a couple hundred thousand, or as many optimists as you can get your hands on, and

• 1:47:01Speaker 00

  then builds a company around that fund is going to crush it. Absolutely true. So the person who reacts to that prompt is probably a business school person who studied finance. And the management of the logistics of what Imad suggested, pretty damn hard. So that skill is absolutely still worth having. Then at the other end of the spectrum, we're about to spend $7 trillion on AI inference. And lots of people are switching over to physics, to photonics, to semiconductor, to microcode. So the underbelly of computer science is thriving. So it's the middle stuff that AI has taken over. So you can still get an MBA, just focus on raising billions of dollars for world-changing missions. You can still get a computer science

• 1:47:45Speaker 00

  degree, focus on the physics end of it. But don't get stuck in the middle. But the labels imply MBAs are dead or computer science is dead. That's not true at all. It's the specific code monkey is dead. That's not a job you want anymore. Spreadsheet monkey is dead. That's not a job you want anymore. So you got to parse that a little bit.

• 1:48:04Speaker 03

  I mean, good riddance, good riddance to slides and presentation. PowerPoint sucks, right? Like.

• 1:48:10Speaker 04

  I just don't think there are any safe harbors here. This institution, this notion, at least in the West, especially in America, post-World War II, that everyone has to go through a common pipeline in order to be an economically productive member of society, this is a modern creation. There's nothing universal about it. That would be, maybe if I were giving a speech in Germany, which has a notion of trade schools that's viewed differently with a different social valence in America, that's what I would say. But also, remember, the sands are shifting from underneath us. With a four-year undergraduate program, if your goal is to maximize economic productivity

• 1:48:52Speaker 04

  for those who look to college for vertical mobility, the world four years from now, if you're just starting college now, is going to look wildly different. And if I had to, this is not investment advice, and it's not college major advice, but I would say the only class of capabilities that seem at least somewhat secure in the very short term, call it the next two to three years, are those that touch on the physical world. Whereas computer science, we've seen already, computer science is cooked, math is cooked. They're very useful and valuable nonetheless. And if you're going to start companies and be an entrepreneur, as Peter and Dave and Salim and Ahmad, actually, all of you say, then it's super helpful to have knowledge

• 1:49:36Speaker 04

  in your meat body brain of computer science and math. But at the same time, recognize, from a coding perspective or reduction to practice, it's all AI at this point. It's hopeless. Give it up and focus your attention on, in the short term, majors, if you must, and activities that touch the physical world, where superintelligence and the singularity are still creeping in, but not quite there yet. Otherwise, build a company and ride the wave of superintelligence, because there is no safe harbor.

• 1:50:06Peter Diamandis?

  If I had to give a piece of instruction to any undergraduate right now in particular, or someone considering graduate school, there's probably two major reasons to go. One, to get a great network. You go there to find amazing people that you're going to partner with, that you're going to find a common love with, and build something. If you don't have a great network, going to a top-tier university to get that network is a great idea. The second thing is if you don't know what you want to do, right? If you haven't found your purpose and passion in life yet, because whatever you do should be driven by an innermost hunger. Doing anything big and bold is hard, and unless you want it deeply in your heart and

• 1:50:49Peter Diamandis?

  soul, you're going to give up before you get there. So you can go there to find a purpose, find something that you love doing. But for me, those are the two major reasons. It's not learning, because what you learn is going to be out of date very quickly. And it's not going to be to get a job, because we've all said, you know, the whole paradigm of jobs is cooked. So go find your tribe, go find a purpose, and then go build.

• 1:51:14Speaker 03

  Yeah, I think I was going to echo that, Peter. Like, I think now actually is the most important time to surround yourself with people that you look up to, you feel positive energy around. Because that's one of the key drivers of what success will be. And again, like you and Dave met at MIT, right? Like, some of these connections will last for a lifetime. So I think actually in-person humans around you is more important than ever, ironically. Because previously, you could just coast by, getting your accountancy or MBA or kind of other things. The other thing I'd like to say is, I just realized, I haven't looked at a single line of code this month.

• 1:51:47Speaker 00

  Wow. Yeah, isn't that amazing? Yeah. And yet, you've probably generated millions.

• 1:51:51Speaker 03

  I don't even know how much I've generated, but I've built state-of-the-art things of all types that some of you have seen. And it's been a month since I've seen any code.

• 1:52:01Speaker 03

  I mean, Dave, are you guys looking at code still? Like, it must have...

• 1:52:06Speaker 00

  Of course not. I'm warning people, like, I can see in the prompt history as if people are looking at code, and it's like a red flag saying, like, why do you feel the need to do that? Are you a junkie? Like, what's the issue?

• 1:52:17Speaker 04

  It's even worse than that, Ahmad. I would say programming languages themselves are no longer interesting. Like, what's the point of even creating a new programming language if you're never going to program?

• 1:52:25Speaker 00

  Yeah. Yeah, but AI management frameworks are hugely important all of a sudden, and they're a lot like a language, except much, you know, broader in scope. And suddenly, that's a massive lever. So the mindset, you know, of a person who thinks in terms of programming languages, that mindset is more valuable than ever. But it's moved over to agent management and frameworks.

• 1:52:47Speaker 01

  Look, prompting with precision is going to be a very, very valuable skill over the next decade or so.

• 1:52:53Speaker 04

  You think so? I think that only had five minutes of shelf life before the models got so smart, they just understand what you're talking about and don't need context engineering.

• 1:53:01Speaker 00

  But if you embrace the things that have five minutes of shelf life during that five minutes, then you're really well-prepared to embrace the next thing.

• 1:53:08Speaker 04

  It's true.

• 1:53:09Speaker 00

  That's the key, is like, don't give up.

• 1:53:11Speaker 04

  It was a glorious five minutes.

• 1:53:13Speaker 00

  Exactly. Just keep riding, keep thriving, keep riding, keep changing.

• 1:53:17Speaker 04

  Motion, motion, keep the motion up.

• 1:53:19Peter Diamandis?

  All right, let me go to the last story here, which is a great model. This is a friend of the pod, Palmer Lucky, and his company, Anduril. Full disclosure, I'm an investor in Anduril. So Anduril and Qualcomm just announced Blue Chip. It's a line of hardened, American-made computers. The first product is a rugged laptop for the military, government, and first responders and police. It runs on Qualcomm's Snapdragon chip, made in TSMC's Arizona plant. About 90% of the parts come from within the US or allies, with a roadmap to get 100%. The screen for Blue Chip is still made in China. Final assembly is at Anduril's Arsenal 1 factory in Ohio. Palmer Lucky said it this way, quote, "The anti-surveillance computer."

• 1:54:04Peter Diamandis?

  He says it'll cost about 20% more than high-end PCs and be heavy with limited battery life. Let's go to a quick video of Palmer discussing his Blue Chip computer.

• 1:54:18Speaker 07

  Eighty years ago, America pioneered modern computing to defend our nation. Now, we're bringing it home. This is Blue Chip. American-designed, American-built. Other companies might design their computers in the US, Anduril makes them here. Yet we're making parts out of metals that the US knows how to extract, knows how to refine, knows how to process, and knows how to mill at scale at a reasonable price. And that goes for the entire laptop. The same thing goes for the battery technology. We need to design things that survive very, very rough environments. And so what we've designed is a chassis that makes it very, very easy to replace the bottom shell and even the top shell, which you can easily integrate things like solar panels, other soft goods, other service insignias, even things like flat phased array antennas

• 1:55:02Speaker 07

  directly into the laptop itself. Blue Chip is America's comeback. Anduril is making sure that the machines we depend on every day are machines we can actually manufacture ourselves.

• 1:55:15Speaker 07

  This is America's birthright.

• 1:55:18Speaker 07

  It's time to bring silicon back to the valley.

• 1:55:22Peter Diamandis?

  You know, I flew with him back from New York, where he was winning the Wildfire X Prize, and he was telling me about this. He's so passionate about it. It's interesting, right? Willing to pay 20% more for "Made in America." Who wants to jump in?

• 1:55:38Speaker 04

  I'll just say, I applaud Palmer for doing what Apple was unwilling to do. It's like pulling teeth to get Apple to move its supply chain out of Shenzhen, and they're mostly moving it out of China to India and not to North America, Greater North America, or even lesser, the United States. And doing what Elon threatened to do but didn't, which was to build the X phone. He, every once in a while, gets frustrated with Apple and says that his supply chain largesse is going to be used to build consumer, general-purpose computers, but he hasn't done that. Bravo to Palmer to build a rugged book. Obviously, defense applications are the first application.

• 1:56:22Speaker 04

  I just hope that we see, whether it's through regulatory measures like export controls, or whether it's just through demand and superior domestic, arguably sovereign, production capabilities, that we see more and more of the entire device, not just semiconductor, but the entire device supply chain moved out of East Asia or Asia overall, re-domesticated back to the US. I think the country will be much safer. I think the country will be much more capable if we can take, sort of transplant Borg-style all of Shenzhen into the US. Masayoshi Son had his Project Crystal Land project notion that never quite got off the ground. I would love to see a Project Crystal Land in the US that offers end-to-end Shenzhen-type

• 1:57:06Speaker 04

  capabilities for laptop production and everything else, and maybe Palmer will help to drive that way.

• 1:57:12Peter Diamandis?

  Dave?

• 1:57:13Speaker 00

  Yeah, I think it's a no brainer for this to come back to the US. I think the problem that Apple runs into is that there's a big push right now to bring, you know, PC board and surface mount devices and all that, bring that back to the US. But then you're like, well, there's another election in two years. They'll probably change their mind again, you know? It's just, there's no reason to believe those, any continuity in the policy. And by the time you get it all moved back, you know, you're two years into it. And that's right when the next election comes along. So, you know, countries like China that have continuity of leadership over long periods of time are just kill us, crush us with these long-term plans. And no one in the US can plan that far ahead. But it's obvious that if you do move it back, it's all going to be roboticized.

• 1:57:58Speaker 00

  There's no labor constraint anymore. So it's far, far smarter to have it back on shore. So Palmer's doing the right thing. And I don't blame Apple for being all worried about it. They're trying to move it to India now. But, you know, moving it to the US, if you could promise that you'll still be saying that six and 12 years from now, we would do it.

• 1:58:18Peter Diamandis?

  Yeah, it's a different, it's a different business, right? The government's willing to pay more, consumers are not. Consumers will flock to the lowest cost product. Saleem, you were going to say?

• 1:58:27Speaker 01

  I just love the overall MTP framing here because he's not saying we're going to build a better laptop. We're going to kind of rebuild the entire American ability to do innovation, right? It reminds me of Robert Goldberg, who's MTP was reinvent American exceptionalism, right? There's some incredible potential and need. And as Dave points out, as we automate and you need less people, this is the best place in the world to do it, and it will become the best place in the world to do it. And if you can build an ecosystem that is supporting all this, and you don't have to build the whole thing, you have to do bit by bit while you get the whole thing done. And then you're in an amazing place. You have to do it this way.

• 1:59:07Peter Diamandis?

  Iman, I'm curious, does England build anything? I guess cars, I guess you build some cars.

• 1:59:12Speaker 03

  We've been shutting down those factories. I'm not sure, actually, again, like, electricity is like three times more expensive. Our permits are huge, and so it's very difficult for us. And more than that, like, the entrepreneurs like Dyson and others left because the environment was not favorable. I think the winds are behind Palmer, you know, God bless him, and he's showing that he can be a mega entrepreneur and delightfully retro as well, from the mod retro Game Boy to kind of this. It's kind of going back to the old school and bringing it forward. And as Saleem said, not being apologetic, like, this isn't the fastest, cheapest, best laptop. It does the job, very functional, and all the things that he builds will be.

• 1:59:51Peter Diamandis?

  You know, Palmer and folks like Ben Lam are very much sort of the analogs to Elon. There are very few entrepreneurs that make these huge bets, risk everything over and over again. We need more of them.

• 2:00:05Speaker 03

  But the thing is, it's not a risk, actually, is it? This is Elon's idiot tax at work. The supply chain is going to be so much shorter for this. The supply chain, as you re-industrialize America, will be so much more resilient. And particularly because there's probably holes everywhere.

• 2:00:20Speaker 04

  And I think for Palmer in particular, I wouldn't characterize this as an act of heroism. He has a customer, the US government, that very much wants to ensure that it doesn't have components that originate from Chinese supply chains with potential supply chain vulnerabilities. So I think, starting with the US government as a customer for fully sovereign device assembly makes total sense. Again, the question in my mind is, beyond the US government, does the, say, the American consumer, American enterprises, do they have an incentive ultimately to buy American fully sourced desktops, laptops, smartphones, or not? You can make them have an incentive with import controls, which is what this administration is doing with robots, but otherwise, not obvious to me whether this spreads beyond the US government consumer.

• 2:01:06Speaker 00

  Well, the problem with the government as a customer is they have to put everything out to bid for, to reevaluate every single year. It might be time to reconsider that.

• 2:01:14Peter Diamandis?

  But that's not the way Andrel works. Andrel builds it and says, this is now available for you. It's not a bidding process. I mean, that's what Andrel's genius is.

• 2:01:25Speaker 00

  Yeah, and that's why there is risk.

• 2:01:27Speaker 04

  Yeah, I mean, there is, I mean, the way government contracting usually works is there's firm fixed price, on the one hand, there's cost plus on the other. And the success, the notable success of Andrel with selling to the government is that they are biased in the direction of selling firm fixed price products as opposed to just trying to bid on cost plus contracts, which is what many inferior legacy primes do. That's been the strength. So presumably, he's offering these at, you know, a fixed dollar amount per pop, and it's an FFP contract, but still subject to bidding.

• 2:01:59Peter Diamandis?

  And let anybody else who's making an all-American built laptop compete, right? Nobody is. All right, it's time for AMA with the mates. Saleem, I'll give you a first crack here. What do you want to go for?

• 2:02:11Speaker 01

  I got to go with number three. When an organization switches AI models or cloud providers, how can it ensure that existing security restrictions, decisions, records, and compliance obligations are preserved? And that's from Invisible Laws Official. What a great name. This gets like really right to the heart of the organizational singularity in the way we think about this. Companies totally need to rethink their architecture. You can't just add AI to existing workflows, right? The foundational principle has to be, to what extent can you have replaceable intelligence, but with a layer of persistent accountability on top of it? Your security and your compliance, all those records should belong to the organization, not to the model.

• 2:02:56Speaker 01

  And so you have to lift that above, and the governance needs to be implemented by a machine readable policies. And so you have to figure out how to layer that. And we've kind of designed this in what we call the intelligence stack, which is available for free in our Claude skill, because you have to be able to swap out Claude or Gemini or another model. These models are leapfrogging themselves every week now, or every two weeks. And you have to be able to swap those out without losing the organizational memory and the permissions and all the rest of it. So, super critical to do this.

• 2:03:27Peter Diamandis?

  Dave, over to you, pal.

• 2:03:29Speaker 00

  All right, number two. Could breakthroughs by competing AI models cause stock price whiplash for companies like OpenAI and Anthropic? And is it sustainable for companies to focus purely or solely on AI in such a competitive market? From Future Insights essay. You know, the market is, what, 3%, 3.5% down today? That used to be like, like, you know, a catastrophic, once in a millennium kind of event, and now it's like every week. It's amazing how much more volatility there is. And that's just the nature of technology. Stuff changes so quickly and people panic and everything bounces around.

• 2:04:10Speaker 00

  So, yeah, I expect there'll be a huge amount of volatility in the OpenAI, if it ever goes public, and Anthropic, soon to be public stocks, for exactly that reason. Every announcement, every new Chinese model, every benchmark, the stocks are going to go all over the place. But if you look overall in aggregate, you know, the market's up and up and up, and the economy's growing and growing and growing. So, you know, Alex always says, just diversify, be hedged against it, but don't be unexposed to the category. I think those companies are going to stick with the narrow focus, even though it's volatile. And that's probably the right, the right strategy for them, and just live with the volatility.

• 2:04:50Peter Diamandis?

  Iman?

• 2:04:54Peter Diamandis?

  Three or four?

• 2:04:55Speaker 03

  Three.

• 2:04:55Peter Diamandis?

  I'm sorry, two or four? I'm sorry.

• 2:04:58Speaker 04

  One or four, I think.

• 2:04:59Peter Diamandis?

  One or four, thank you.

• 2:05:01Speaker 04

  Got it in the end.

• 2:05:02Peter Diamandis?

  I got your four right.

• 2:05:03Speaker 01

  Been a long pod.

• 2:05:04Speaker 03

  Number one, why are Chinese AI models cheaper? Is it due to greater efficiency, government subsidies, or lower energy costs? That's from at R Y R 4770. I think necessity is the mother of invention. They didn't have the big chips, they didn't have the compute, so they optimized for smaller or RAM intensive models when RAM was cheap. They obviously borrowed from US models as well, so they didn't have the same R and D. And the biggest thing, actually, is that they don't do margins. So the Anthropic S1 was just interesting because they have huge margins, like 80% instead of everyone else. And we all thought they were running at cost, and in fact, they weren't. So with that optimization, with that distillation, and with, again, the need to drive these things down, they did it.

• 2:05:49Speaker 03

  And the final element is sometimes just superb engineering. The DeepSeek details that came out of their inference, like, it was astonishing when they released their inference stack, how efficient they'd made it. And that's just good engineering, full stop.

• 2:06:05Peter Diamandis?

  All right, Alex.

• 2:06:07Speaker 04

  All right, question number four. Is Microsoft's voluntary exit first have to admire the Orwellian doublespeak. Is Microsoft's voluntary exit offer to 60K employees an early sign of AI-driven job displacement or corporate restructuring? This is from PCN2B. This is a pretty weird future-present that we're living in. If we had told this story 10-plus years ago, the easier and more obvious story to tell would have been AI automation itself just obsoleting the role of employees. So basically, spend on employees being substituted by spend on replacements for the employees in the form of automation. That's not, it appears, what's

• 2:06:49Speaker 04

  actually happening here. What it appears, and it's not just Microsoft, Oracle, and other hyperscalers are doing exactly the same thing. It's not one OpEx substituting for another OpEx. It's CapEx substituting for OpEx. So in the case of Microsoft and the other hyperscalers, what seems to be the case from the outside is that rather than spending money on employees and all of their associated costs, which in their ledger would be considered an operational expense, they're instead taking that cash and investing it as a capital expense in the data center build-out. So it's not that, again, this pretty bizarre world we live in. It's not that spend on AI is substituting, or at least spend on AI applications is substituting for spend on human software engineers. It's that the

• 2:07:34Speaker 04

  investment in the data centers is so capital-intensive, Microsoft has relatively little cash, which they're calling an operational expense leftover to pay their employees, and that's why they're exiting them. So it is, in some sense, a capital substituting for labor effect, but a weird one.

• 2:07:53Peter Diamandis?

  Nice. All right. I think number six is for you, Alex. Do I take it?

• 2:07:57Speaker 04

  Okay, six asks, does chain theory strengthen the case for simulation theory? And this is from JSBGMC6613. So as I was developing chain theory, and again, with the obvious caveats as a preliminary matter, these are very early days, this is a baby theory, it's still developing, lots of room still left. But nonetheless, this was actually a question that I investigated, spent a material amount of time investigating. And as far as I can tell, again, caveat, caveat, caveat, early days, it appears that chain theory does have weak opinions about Nick Bostrom's simulation hypothesis. The weak opinion is that because

• 2:08:38Speaker 04

  there are no free parameters, if we are indeed living inside a simulation, it wouldn't be a very useful premise to have. There aren't rooms for, say, someone or something outside the simulator, the simulation, to twiddle knobs, inject themselves. Otherwise, there are just, there's no degrees, there appear to be no extra degrees of freedom that would make living inside a simulation, A, useful to anyone or anything outside it, but B, it also appears there isn't any way to test it. As opposed to, say, if we were living inside a naive classical simulation, you could run timing attacks on it. We talked in the last pod about timing and side-channel attacks that baby superintelligences are

• 2:09:20Speaker 04

  running to chat with each other. Chain theory doesn't seem to have anything quite like what one would naively construe as a classical computer simulation. So it doesn't, if we are living inside a computer simulation, I think chain theory's view based on its current state would be, it's like unfalsifiable, it's a gauge, you could choose either way. It's a little bit, there's a concept in physics of a gauge, basically a symmetry, where it's, there's no correct answer. There are, like, every answer is correct. And thus far as I can tell, within the premise and the framework of chain theory, are we living inside a simulation or not? It's a gauge, no way to tell, maybe even provably no way to tell.

• 2:10:03Peter Diamandis?

  Saleem, what's your take? What question?

• 2:10:06Speaker 01

  On this particular one, if you squint, we're living in a simulation.

• 2:10:09Peter Diamandis?

  Okay.

• 2:10:09Speaker 01

  Then I'll use Alex's favorite phrase there. That is one of my favorites of Alex's. What, you want me to take your question?

• 2:10:14Peter Diamandis?

  Yeah, five, seven, or eight?

• 2:10:17Speaker 01

  Let me take number, I think I've got to take number seven. That's the one. Wouldn't it be more practical to build an AI-driven mechanical dog instead of engineering real ones, which comes from Ziv to live, which I love that. For many applications, build a robot. But biology is very sophisticated in lots of different ways. Depends, but it depends what outcome you want, right? Robotics gives us programmability, and it gives us control. But biology gives us adaptation and lots of efficiency that's evolved over four billion years, like the sense of smell, et cetera, et cetera. We'll end up with the

• 2:11:02Speaker 01

  combination of the two, giving you the best ever. But just as a small example, a certain breeds of dogs can operate for like a day and a half without eating or drinking, whereas a robotic dog will probably need battery power pack replacements much, much more frequently. And that requires a lot more infrastructure, at least for now. So I go back to Brad Templeton, who was talking about the Boston Dynamics horses. And he's like, if you want a robotic horse with all the mechanical stuff, well, I'll give you a male horse and a female horse, we'll breed you a horse. It's not that hard. There's lots of advantage of biology that you don't get in the mechanical side. So if you want those advantages early and quickly, go with the biology. Over time, we'll programmatically get there.

• 2:11:47Peter Diamandis?

  It's also worth noting, mechanical dogs are going to be a lot faster to produce, and their software can be upgraded at a moment's notice, unlike with biology. But

• 2:11:57Speaker 01

  That is a valid point. I'm not sure about the faster we produce.

• 2:11:59Peter Diamandis?

  I think you can have a production line of mechanical dogs. I guess you could, you know, if they have artificial wombs at colossal, they can, you know, sort of like put thousands into

• 2:12:10Speaker 01

  Fair enough.

• 2:12:11Peter Diamandis?

  into development at once. Okay, Dave, let's see, you've got number five or number eight?

• 2:12:18Speaker 00

  All right, I'll take number five. With Nvidia heavily dependent on AI infrastructure spending, could the lack of profitability at companies like OpenAI and Anthropic pose a risk to its future growth? And that's from SpiritualEvolution14. Heck, yeah. I mean, keep in mind, Nvidia sits between TSMC and a few massive customers, Anthropic, OpenAI, and others. Elon, a huge one. And in that, in that stack, you know, you heard on this podcast that Anthropic and their S1, they're operating at 80, 85% margin. And then on top of that, Nvidia is operating the chips at 80, 85% margin, and that's on TSMC, operating

• 2:12:59Speaker 00

  at 50% margin. So when you buy a token from Anthropic, the markup on the markup on the markup is insane, what you end up paying. Do you really think it's going to look like that in three years, four years, five years? There's definitely a theory that it won't, and everybody's racing to vertically integrate now. You know, Anthropic is designing chips. You know, everyone else is also designing chips. Elon is the one to cross the next line and say, I'm going to build my own fabs. I'm not going to be dependent on TSMC. But ultimately, this will be vertically integrated across all of them, and Nvidia has their own models. They're not good yet, but they have their own models. So they're all going to end up competing, and those margins have to come down. So heck, yes, that could happen for sure.

• 2:13:43Peter Diamandis?

  Imad, number eight's for you.

• 2:13:45Speaker 03

  As AI accelerates scientific research, can the peer review process keep up without compromising scientific rigor? At Rita Rawling 7235. The peer review process has held up science, and it's terrible and awful. Having a few unappointed people gate ideas coming through that need to be as close to the norm as possible, with basically no difference from chance, per the Rothwell study and others, and pushback and endanger people's careers has been one of the worst things we have. The science, which should be an iterative open process, where we explore and the marketplace of ideas wins. So I think it'll be the opposite of it, because we should be putting out ideas into the world. Like, for example, my take

• 2:14:28Speaker 03

  at a high level on Alex's chain theory is, I haven't absorbed it because he's spent far more time than me, but I think the base is a far better thing than string theory, because it's actually more reasonable. And I think a lot of it is reasonable. But how will it win in the marketplace of ideas? Because now we all have AIs to be able to check these things. And we should reward putting out ideas that have merit, and we should also reward replication of ideas and more, because so much of science, unfortunately, is unfortunately just made up, which is the craziest thing of all. So I hope it kills the peer review process, and we all become peers.

• 2:15:04Peter Diamandis?

  Yeah. And the thing about the peer review process is, if you're an expert in the field and some disruption comes along, you're no longer the expert in the field. And there's a absolute incentive to slow things down. All right, gentlemen, anybody listening?

• 2:15:19Speaker 01

  Wait, I have a comment. I have to say something.

• 2:15:21Peter Diamandis?

  Please.

• 2:15:22Speaker 01

  I want to make a comment about my religion comment from last episode.

• 2:15:26Peter Diamandis?

  What is it?

• 2:15:27Speaker 01

  So

• 2:15:27Speaker 04

  You want to walk it back, Saleem? Is that what you're saying?

• 2:15:33Speaker 03

  He's muted himself.

• 2:15:34Speaker 04

  You're doubling, you muted yourself, and you're doubling down at the same time. This is great.

• 2:15:38Speaker 01

  The AI muted me. I don't want, I don't want to walk it back.

• 2:15:46Speaker 00

  I have to run back. I'm on stage at MIT in a few minutes. I have to run out the door here.

• 2:15:51Speaker 01

  All right, real quick. Apologies for those if I offended you. I don't mean to offend. If I do offend, I hope to equally offend everybody, so I'm an equal opportunity type guy. But, but, in my defense, when people said in the comments, only Islam does that, Christianity does that, doesn't do that, Judaism doesn't do that, I had to go, go, hello, hello. So the Christians have been forced conversion, everybody for, throughout history, the Spanish Inquisition is the easiest example. Islam is a very bad offender on this. But even the Buddhists, okay, the Tibetan Buddhists, who we think of as these nice, sweet people, when it was established, they suppressed Vipassan practitioners, and they were heavily prosecuted and said, you have to convert or you'll die. And even the Jews in the Hasmonian

• 2:16:36Speaker 01

  Kingdom forced conversion, multiple instances of that. So all religions are guilty, and I will smear all religions equally with this.

• 2:16:43Peter Diamandis?

  All right, just don't tell the

• 2:16:45Speaker 04

  Congratulations, Saleem. You're Mr. Popular.

• 2:16:48Peter Diamandis?

  Quadrupling down, quadrupling down.

• 2:16:50Speaker 01

  I've offended, two-thirds of the world consider themselves to be religious, so I've just offended that.

• 2:16:55Peter Diamandis?

  We're going to wrap with a beautiful video from our dear friend, friend of the pod, CJ Trueheart, called Singulatarians. All right, enjoy.

• 2:17:10Speaker 06

  Used to sleep. Somebody drew a curve on a whiteboard and asked, "What if it bends up?"

• 2:17:22Speaker 06

  The singularity started as a university. Underhanded one to moonshot curiosity. Peter and Ray drew a curve on the wall. Selenia mine's gonna miss it all. From deep mind technologies to chess kids quest. Solve intelligence first, then solve the rest. SpaceX rockets landing back on the map. And they W G's equations keeping futures uncapped. Decentralized O S for paradigm shift. Tech optimism is the gift. Big problems need bigger minds to live. Many billion lives at a time. We're singularitarians. Exponential tech with the soul. Abundances are gold. Building large plans for the whole of humankind.

• 2:18:07Speaker 06

  Yeah, the whole of humankind. We're singularitarians.

• 2:18:15Speaker 06

  We're singularitarians.

• 2:18:20Speaker 06

  We're singularitarians. Most don't think it's probable, but we know it's possible. Just flip it to impossible. Every wall's a door that's optional. They called it impossible till we made it true. Cause we hold an optimistic point of view. Photo protein map of mine. How would the world with the sun that shines? Double down to double up. Think exponential level up. Decentralized O S for paradigm shift. Tech optimism is the gift. Big problems need bigger minds to live. Many billion lives at a time. We're singularitarians. Exponential tech with the soul. Abundances are gold.

• 2:19:02Speaker 06

  Building large plans for the whole of humankind. Yeah, the whole of humankind. We're singularitarians. Mind manifesting, heart guiding true. Hands in the work, giving meaning to me and you.

• 2:19:23Peter Diamandis?

  All right. Thank you, CJ.

• 2:19:26Speaker 04

  Nice job, CJ. And I guess we're singularitarians, not extropians. I don't know what will be tomorrow, but it's nice to have a name.

• 2:19:33Peter Diamandis?

  As long as we are.

• 2:19:35Speaker 04

  Yes.

• 2:19:35Peter Diamandis?

  Tomorrow. Yes. All right, everybody.

• 2:19:38Speaker 01

  Great session, guys.

• 2:19:38Peter Diamandis?

  Love you all.

• 2:19:39Speaker 01

  Great conversation.

• 2:19:52Speaker 07

  LinkedIn is pretty amazing at helping you grow your small business. We cannot make your email response time faster. We can help you sell, market and hire in one place. We cannot help you find space for your three desk drinks. Why do you have three? And while we can't help you find the perfect volume for your presentation video, LinkedIn can help you find the perfect audience for your business. Grow your small business on LinkedIn. Learn more at LinkedIn.com/smallbusiness.