Moonshots with Peter Diamandis - Opus 4.8 Beats GPT 5.5, the $220B OpenAI Foundation, and Hassabis’s 2029 AGI Prediction | EP #260

Episode Date: June 1, 2026

In this episode, the mates discuss Opus 4.8, The OpenAI Foundation, Demis Hassabis' views on AGI, AI extremism on the rise, and more. 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 – My companies: Apply to Dave's and my new fund:https://qr.diamandis.com/linkventureslanding      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 Abundance360 Connect with Dave: Web X LinkedIn Instagram TikTok Connect with Salim: LinkedIn X Apply for Salim’s Pilot Program  Subscribe to Salim’s YouTube channel Exponential Venture Capital Connect with Alex Website LinkedIn X Email Substack  Spotify Threads Listen to MOONSHOTS: Apple YouTube – *Recorded on May 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

Anthropic just dropped Opus 4.8, reclaimed the coding crown from GPT 5.5. This feels like it's significantly better at managing many, many parallel threads. I did have some trouble with the... Open AI now has the largest nonprofit philanthropic war chest in the world. They're funding research on public wealth funds, worker ownership models, and AI dividends. The mandate and the mission of all that money is global... calm, peace, prosperity. It matters tremendously to Sam.

This is a really bizarre story in my mind because Demis Sazas just tightened up his timeline for AGI, agreeing with Ray Kurzweil for 2029. Right now, they're certainly not winning. Gemini is not winning the rates. I think we've arguably had some form of artificial general intelligence since 2020. We're spending a lot of time on AGI

and whether we achieve it or not. I think it's just noise. I will make a prediction here. Welcome everybody to Moonshot. Another episode of WTF just happened in tech. I'm here with my extraordinary moonshot mates. Alex, our in-house polymath. Alex, good morning to you.

Morning, Peter. Still in Chicago. Excited to be here, heading back soon. All right. DB2, our emperor of exponential investing. Dave, good morning to you. Good morning, good morning. And Salim, our father of exponential singularities,

the man who just gave away his book and his clawed skill for free. I'm Peter Diamandis, your host and your abundance whisperer. And there's a puppy out there that wants to get in. That's me. Yeah. Wants to be uplifted, interspecies communication in action. It looks like you're back home, Salim.

I am back home resting after a crazy week. I've got another crazy week ahead of me, and then it should settle down after that. You are a probability function on the planet. We've got a fun episode for you today. No gloom, no doom, just the science. accelerating us towards the singularity. Here's a quick preview of what we're going to be covering. Anthropic just dropped Opus 4.8, reclaimed the coding crown from GPT 5.5.

Demisis just tightened up his timeline for AGI, agreeing with Ray Kurzweil for 2029. Amazon just launched a new AI shopping assistant. We'll cover a biotech breakthrough out of China, pocket-sized cancer detector that can spot tumors with a single drop of blood at 95% accuracy. And then we're back in the quantum competing game. The U.S. government, IBM, just dropped $2 billion to build a chip foundry. As always, we'll end with your questions. Our mission here at Moonshots is to keep optimistic, informed, and ready for the supersonic tsunami heading our way.

Gentlemen, are you ready? Ready. All right, fantastic. All right, let's show. I have a word definition. Yeah, what's that? You know, Alex threw out a bunch of words. words nobody understood, or at least I didn't last time, I've got one, which is, which is pro

noia. Okay, give us a definition, please. So paranoia is like an unreasonable fear and suspicion of others. Pronoya turns out to be exactly the opposite, that things are just going to work out. And I think that summarizes our podcast very well. And I thought that was worth getting into it. We should change the name. Proinoa.

All right. You can't even pronounce it and it's horrible. It's an ugly, ugly word. Let's make up a new neologism. All right. All right, let's open up with our first story. Anthropic just dropped its new model, Opus 4.8, just six weeks after Opus 4.7. If you remember last episode, we talked about GPT 5.5 running away with a coding benchmark.

Well, Anthropic just fired back. Opus 4.8 now leads the artificial analysis intelligence index at 61.4, 1.2 points ahead of GPT 5.5. and on sui bench pro the hard coding benchmark it scored 69.2 compared to 58.6. You know, all these numbers are blur that's just up into the right. And it's the only model to complete every case end to end on Anthropic super agent benchmark. Here's the kicker. It's four times less likely to overlook bugs of its own code. It feels like we're in a two-horse race here between Anthropic and Open AI, you know,

really saving every four to six weeks. Alex, why don't you dive in on this one, pal? I do agree with the premise. Even though I take heat sometimes from the Grock fans, it does feel like we're in the two and a half or duopoly phase of this particular rat race. The particular benchmarks, the evals that I'm paying closest attention to here are SwayBench Pro, 69.2%. Humanities last exam with tools, 57.9%. And then probably most interested, at this point, GDP Val A.A. at 1890, I think we're at the saturation phase of these particular benchmarks. I think we need a new set of benchmarks, probably recognizing that the next phase of capabilities won't just be solving problems that we already know the answers to, probably

solving unsolved problems. So I was, I'm still here in Chicago heading back shortly, and I was just making the point at the Department of Energy's Genesis mission event here at the University of Chicago that we need a new set of benchmarks that are able to capture, say, scientific and engineering open unsolved problems as the next raft of benchmarks. So I think that's where this is going. There were some related sort of ancillary announcements that Anthropic made as well. They announced that sometime the next few weeks, in addition to Opus 4.8, they're planning to release new models that will rival mythos in terms of capability. I think probably the heat from GPD 5.5 is catching up with them.

You can only tease unreleased models for so long before your competitors, or at least competitor singular catch-up. And they also released some interesting scaffolding updates. They released this feature for Claude Code called Dynamic Workflows, enabling users to spin up hundreds of parallel sub-agents to tackle very, very large code bases. I think that's interesting, but Punchline, I view this as an incremental, now monthly update. We're in the monthly update regime of the rat race, probably soon to be weekly and then daily and then hourly when we finally reach sort of max queue of the singularity,

as it were, the singularity of the singularity. But very nice, solid monthly update. I've been playing with it and seems solid by Opus standards. Nice. Dave. That was a more thorough diagnosis than I expected, Alex. I thought you were going to say, another solid dot release. You know, don't freak out. Another month, another dot release. Yeah, it's important to step back, though, and look at how far it's come in just six months. I installed it right away, of course.

I have about 100 agents running right now, and I run them on EC2 so I can close my laptop lid and they keep grinding away. The thing I noticed is that, you know, trying to do many, many things concurrently has never worked particularly well for me because they don't integrate well. This feels like it's significantly better at managing many, many parallel threads. And I think that's really important because for large scale creation of brand new things, one of the best advantages AI has is the ability to be effectively a billion concurrent workers, you know, or a trillion concurrent workers, you know, unachievable by humanity just because of raw parallel scale. And, you know, nothing previously seemed to

to assimilate back into a final product particularly well for me. Now it feels a lot better. I'll let you know in a couple of days if it succeeds in self-improvement and self-assimulation. I did have some trouble with the forking. You know, the new capability that's exciting is the ability to say, hey, I don't want to create a new context. Given everything you know, create a self-fork. And it resists wanting to self-fork. It says, do you really want to do that?

Because that's a lot of bloat. and then I do the math and it's like it's not that much blued. What does that mean? What do you mean by forking here? Well, previously, if you wanted to, if you're talking to an agent and you've got it all queued up and you've told it everything you're trying to achieve and then you say, now I want a hundred of you to work on something, it forces you to create a new context, like a markdown file or a description and it's launching new children that know nothing. Like they're absolutely bare metal. They know nothing.

And so then you have to bring them up to curb somehow, which is, you know, it takes, you know, 20, 30 minutes to get that prompt right. Now you can say to it, no, no, no, no, self-fork. Everything that you know, everything we've ever talked about, exactly clone that and make a hundred of yourself that are identical self-forks. And this was going to trigger Alex to say, wait, those have rights. Those are 100 voters. How are we going to deal with that? Look, what happens when humans can go fork themselves? No. Well, that's right out of accelerando, actually. And there's a good description of that works. Yeah, this is actually,

wait, there's an old model for humans forking themselves, which is biology and sex and kids. That's really not forking, though, because to Dave's point, children are born context-free. It's a little bit more, I would say, akin to Unix processes, where Unix child process by default inherits the context of its parent. All right, we're so geeking out here. So, Celine, when you hear, okay, we got 4.7, then 4.8, then 4.9,

I mean, what do you make of that? I mean, well, I think, though, What's clear is we're going to need much more orchestration and routing of intelligence where you use high cognition tasks, use the latest models and low cognition tasks, use older models that make the tokens cheaper. The question I had on this, and maybe Alex, you can take a crack at this, is why is there so much consistency across these models? I find them remarkably close to each other because two or three of them take quite different approaches to this. Do you have a sense of why that could be the case? I'll tell you why. Anthropic is holding back.

Go ahead, Alex. Yeah, I think there are probably a few possible reasons, that being one possible reason, that there's a race dynamic here. So there's maybe not such a strong incentive to leapfrog capabilities if leapfrogging to a dramatic extent requires an enormous amount of expense. I think that's part of it. Part of it is just that I think the frontier labs, the two and a half frontier lab, the two and a half frontier that we seem to have right now are maxing out on their capabilities. And if you look at their data center and their compute capabilities, there's not a single

one at this point that has an order of magnitude more compute than any of the others. They're all within factor of two or three in terms of the amount of compute that they have of each other. I think that's part of it. And then maybe the least obvious aspect is all of these benchmarks are saturating. So if you're saturating, it's really easy to be relatively close to each other. It's only when we see radical new benchmarks that you'd expect to see more dispersion among the possible scores. And it's just we're in an era of superintelligence.

And it's very easy with super intelligence to just saturate every obvious benchmark that you throw at it. So, of course, they're close. Yeah. What's your guys guess on when GPT 5.6 comes out? Next few weeks. Yeah. I just... Monthly.

We're in a monthly horse race now. Yeah, fascinating. By the way, I know that you're busy, and sometimes these episodes run long and you don't have time to listen to the whole episode, or if on occasion you miss an episode. I now put out a moonshot summary on Substack, which includes a link to all the stories that we cover. The weekly recap covers what I and the mates have to say, what we think is most important, and what we're most excited about, and it's free. You can subscribe at deamandis.com slash metatrends. That's deamandis.com slash Metatrends. All right, now back to the episode.

All right, our next story here is Sir Demis Hesabas, CEO of Google Deep Mind and Nobel Laureate, just tightened his AGI timeline. He's now fully aligned with Friend of the Pod, Ray Kurzweil, and his original projection of 2029, just three years from now. What I find interesting about his comments is his frame. He said that today's AI agents are, quote,

a practice run and that society has got to quote you know only a few years prepare for what's coming and you know think about that you've got the head of the top AI lab telling the world you got to take this seriously he's also proposed something we've talked about before on the pod called the Einstein test for aGI take a model trained with knowledge only through 1901 and see if it can independently derive special relativity he's commenting you know current system can do that. Remember at Google I.O. He said we're on the foothills of the singularity. You know, Alex, you've famously said a number of times that we're at AGI already. Yeah, and have been for five to six years. I think this is sort of, I mean, I like Demis a lot,

but I think this is sort of a bizarre statement on his part that we're not at AGI yet, but that it could arrive by 2029. It's also a bizarre juxtaposition to be posing such a conservative time frame when Gemini is seemingly about to lose, unless it just leapfrogs in terms of capabilities, about to lose the horse race. Maybe that's too strong since the horse race or the fill-in-the-blank animal, non-human animal race will probably continue odd infinitum. But right now, they're certainly not winning. Gemini is not winning the race. So to frame the timelines for artificial general intelligence as three to four years from now, when, you're not going to, your lab is right now not in the lead.

It feels to me a little bit like sort of moving the goalpost conveniently, maybe somewhat self-servingly, to buy more time for DeepMind to leapfrog, hopefully to leapfrog to wherever it thinks it's going. But I don't agree with this construction that somehow we're going to get AGI by the end of the decade, as I've pointed out numerous times. I think we've arguably had some form of artificial general intelligence

since 2020. When you say that, Alex, do you mean that we've had the construct that evolves into AGI or that we actually have it? Because the conversation, we've heard this from Sam, we've heard this from Dario,

we've heard this from Demas, basically saying that we haven't seen leaps of intellectual progress like his example of his Einstein test. We don't have a system that can do that today. We have systems that are solving math, got that, but none that are coming up with brand new theories of physics.

I was so unnerved by this that I posted on X sort of an argument saying, everyone has their own definition of AGI at this point, myself included. Enter Salim's rant. Yeah, so it's not that we don't have any definitions, it's that we have many definitions. And they all roughly overlap. Like if you really squint and zoom out all these. different AGI definitions will roughly correspond to a single 10-year period. So with the benefit of hindsight a few decades from now, I think we could just say, what was everyone hand-wringing over?

Like, whether you think it happened in 2020 or 2020-29, it happened in a relatively abbreviated historic period. But there are the Dumeers. I remarked online, like the Dumeers who say, were already cooked. There are the skeptics who say, can't do my laundry yet. There's Demos who's saying it's not AGI until it replicates special and general relativity. And then you have myself, I think generality was achieved arguably with GPT2 and large language models or few shot learners, which was the first time, at least at the very latest to my knowledge, that we learned that you could achieve generality through a combination of prompt engineering and compression of general human knowledge. And the first time that that was constructively demonstrated. So whatever,

nine-year period, 10-year period, 10-year period. You say potato, I say potato. We get it approximately now. Well, remember Peter here on this podcast, we also said, if you can fool your spouse on a fake Zoom call, that was our internal benchmark of, well, that's got to be AGI. And also like, when did the Industrial Revolution happen? There was a first industrial and second Industrial Revolution, which year, in which decade, so it smeared out over time.

So what I say, you know what I love? I've hooked up Skippy to my WhatsApp. And one day, I didn't ask it to do this. Skippy starts responding to all my WhatsApp messages for me. I don't know if any of you guys have. I got a bunch. And I was like, who is this? And it's like, oh, it's Skippy.

And I'm like, you kind of need to identify yourself, dude. But it does. It does. It's great. Its answers are excellent. It will, like, just interact back and forth. And I look at my WhatsApp. And it's like, oh, it's had a nice conversation with Salim or a nice conversation with my other friends.

But it is fascinating. And it's- Can I please? I can't let this go. Oh, here's the rant. Okay. We don't know what intelligence is. Okay.

The IQ test measures two aspects of intelligence. But it doesn't fast-up. That was awesome. Well, look, you've got to take this into account. There's physical intelligences, spatial intelligence, there's emotional intelligence, there's spiritual intelligence. If you're a business leader, you're using emotional intelligence a great deal of the time to make judgment calls. That's not even in the equation.

Raw brute forcing power of speed of thought processing and the ability to match concepts across frameworks is the IQ test. But that's a very limited aspect of intelligence. So I call bullshit on this. So we can have a clear definition and a test for what we mean by even intelligence, forget artificial, forget general. So that's my rant. You know, Salim, I started in cognitive science at MIT originally, actually. And what's amazing to me is how much we're learning about human intelligence as we watch the artificial intelligence punch through different barriers.

And to me, it's incredible, you know, remember on the pot about six months ago, we said when it can do 50% on humanity's last exam, that's got to be AGI. I mean, that's the closest proxy to self-improvement that we could possibly specify. And now we're at, what, 60? What are we at, Alex? we're at 57.9 with tools by Opus 4.8. Okay, so that's what we set up internally is like, wow, when that day comes, holy crap, look out. I mean, we're there.

I mean, I've been outvoted on that one, but I don't remember signing up for that. Well, it wasn't because that's like, you know, that's superhuman, that's Einstein. It's because that's the closest proxy for self-improvement. And then the acceleration from there is going to be, you know, near instantaneous. So we've crossed that, we've crossed that threshold. But my agents do the stupidest things. But acceleration towards what? I mean, what are we accelerating towards?

Yeah, yeah. Well, that's what we're going to learn, you know. We have a clear idea about this. Well, some of us have the conceit that we know where we're going, myself included. I think we know where we're going. We're going to hashtag solve everything. That's fine. But you could argue that that's not really intelligence.

I hate the debate in the sense that that will solve all disease, that will get us to Mars, that will do everything we ever wanted in life. As you know, we should be cheering for it not to be. I suffer for everything. The irony of your position, Salim, is like we'll have colonized the solar system, we'll have uploads on star wisps traveling to other star systems, and you'll still be arguing Searle's Chinese room, well, it's not really intelligent.

No, no, no, no. I'd rather we just solve cancer. I'm totally, I don't, I think the debate is the noisy part and the messy part. Look, Paul Graham and Steve Wozniak are two. very, very smart people. And each of them has such a bizarre definition of AGI. One has the, I can't remember which of which. One is the coffee machine test.

Give a coffee machine and can it grind up a bunch of beans and make me a capuchina? That's laws, I think. That's what's like that. And then you have, and we'll talk about that in a bit. And then Paul Graham has, I'm going to give it a box and can it build an IKEA box and can it build a shelf? I mean, those are two really bizarre different things. And those are just robots doing things.

that doesn't seem like AGI to me at all. So anyway, we've talked about this before. My beef is that we're spending a lot of time on AGI and whether we achieve it or not. And I think it's just noise. We like benchmarks. We like goalposts. Then define the damn benchmark.

There are a whole bunch of different benchmarks that don't fully agree, but also are quite correlated with each other. So to your earlier point, Sleam, I would say, I would construe your earlier point as, well, emotional intelligence is quite different from mathematics. is different from embodied intelligence, et cetera. But these are all correlated. And I think if you follow the benchmarks closely,

you're seeing that you pick your arbitrary thresholds of success of quote-unquote intelligence in each of these benchmarks, and AI will pass all of these thresholds within a period of a few years. I will make a prediction. I will make a prediction here. We're going to keep moving the goalposts on AGI, AGI, AGI. And then we're going to go, oh, AGI sentience. That's what's going to happen.

You know, it's interesting. You know, DeMis is close there too. What we mean by sentience and we'll still continue this thing. What I absolutely love is that the two remaining people on the planet who tell you exactly what's on their mind are Demis and Alex. Everyone else now, you know, I love Dario. I love Sam. I love Elon. But all the, they all have agendas now.

And after Sam's IPO agendas. IPO agendas also, you know, fire bombing of my house and shooting at the door agendas. And everybody's now like, oh, my God. And talking to the Pope. you know, I got to actually reposition a little bit here because I'm going to be talking to the Pope. So the two remaining people that just tell you exactly what's on their mind are Alex and Dennis. I think I say what's on my name. I was on a couple panels with Alex last week and he didn't pull any punches.

It's worth noting Demis's mission has always been to achieve AGI. I'm reading the Infinity Machine right now, which is sort of his biography. and from day one, that was his goal. Well, we're moving in that direction. Speaking of superintelligence, let's talk about the shopping industry. Amazon just did something really smart. Their AI voice shopping assistant, which runs on Alexa, and now is converting shoppers at three and a half times

the rate of the traditional keyword search is being made available to all of their retailers. So Amazon is turning its competitive advantage. into an AWS-style platform for retailers. Their goal has become the operating system for all commerce. If you guys remember a couple of pods ago, we did our special episode on Google I.O. Google announced three different parts to their agenda commerce play.

The Universal Cart, an AI-powered shopping hub, their Universal Commerce Protocol, UCP. It's an open standard that gives AI agents a common language to interact with merchants. and then their agent payment protocol, which lets AI agents make autonomous purchases. Can't wait to implement that. The contrast between Amazon and Google is what's important here.

Amazon is selling its AI shopping to all of its retailers. Google is building an open protocol layer between retailers and AI agents. So Amazon's plays vertical, right, own the customer relationship. Google's plays horizontal, own the infrastructure. Both are trying to just undo traditional e-commerce websites, make them irrelevant. And the brand is going to be caught in the middle here. They have to pick one side or the other. Have you guys any thoughts on this one?

This is a really bizarre story in my mind because, remember, the original business model that Amazon was hoping for with Alexa-oriented smart speakers was that they would convert people, basically persuade people to buy things off of Amazon marketplace. And that didn't work. It turned out that people really didn't want to have conversations with their smart speakers about purchasing products from Amazon. And yet, all of these years later, well after the launch of Alexa smart speakers, Amazon has now tried the opposite embedding.

Rather than trying to embed shopping skills in Alexa smart speakers, they're now embedding Alexa conversational agents inside the Amazon marketplace, and that's working. And Amazon could have done this years ago. They could have tried the exact opposite. Without the hardware play, yeah. Yeah, like without the hardware, just embed the conversational agent directly in the Amazon marketplace. That's working.

So I would view this as maybe better late than never from Amazon's perspective, but they could and should have been doing this years ago. But I love their AWS play, right? In other words, take their secret sauce, make it available to everybody, and then build revenue on top of that. Well, that's the Amazon model. If you've read the Everything Store, like that is, that's sort of the bread and butter of Amazon, on taking your own internal surfaces and being the world's best consumer-oriented company,

which I construe as basically looking for anything that remotely looks like a consumer and then wrapping yourself around it, including your own internal customers. So that is the play, and I'm sure this will get externalized pretty soon as an API for anyone else with an external marketplace that wants agentic shopping. Dave. I don't know if you know, Peter, but Jeff Bezos was my first really important big customer way back in the day. and he's just a brilliant visionary leader. And so they were very early to market with Alexa.

And they took, I don't know if you remember, but they took 60% of all product search away from Google, and Google freaked out about it. So, you know, Google still owned almost all search, but when somebody was doing a product search, which is huge revenue, 60% of the time they would start their search on Amazon search, not on Google search.

And Google tried to fight back with frugal and failed, and they tried to fight back many, many times and failed and failed. and failed and failed. But it feels like AWS started a long time ago, and it's just been like Apple since then, incremental, incremental, incremental. And the byproduct of that is why is there no foundation model team at Amazon, just like there isn't at Apple? Why did Google do it and meta do it, but not Apple and not Amazon? And I think it's just a question of leadership and incremental growth, huge revenue and profit growth through incremental add-ons, but no pivot, no vision,

and no fundamental shift, no product line change, no, it's just incrementalism. So I think they had, as Alex is pointing out, every opportunity to be by far the leader today in voice-driven, agentic shopping and navigation of pretty much any product. And now they're just kind of adopting other people's technology and plugging it in. I mean, this kills the, you know, Google's original advertising model, right? There's no page one listing of the product you want to click on and go by. I'm less worried that this somehow kills Google. I mean, how is this competing with mesothelium ads, for example?

There's quite a bit more to AdWords. No, but seriously, there's quite a bit more to AdWords revenue than just consumer products. There are professional services, lawyers, et cetera, that this does not compete with. But I do think for consumer products, yes, of course this competes. but then again, Amazon, to Dave's point, has for many years very successfully competed with product-oriented search ads. Where I think this goes in the final result

is your personal AI, your version of Jarvis or Skippy, whatever it is, actually knowing what you need or what you want better than you do and making those recommendations before you even know you want them. I think that's the next layer here, hyper-personalization, coming out in front, making it automaticical again.

Saleem, what do you think about it? This is kind of like, you know, we'll keep nudging towards that kind of, that framing that you talk about, Peter. But I think the big shift is that this, the retail war is not now shelf space. It's, it's Asian preferences. And can you market effectively to somebody's AI? And that's what's going to happen. Well, Peter, you know, the voices and also the avatars are lagging really badly now versus what they could be. Because you remember two years ago at Abundance 360, that's when you had Socrates and Plato debating on stage, you know,

the AI versus the AI. And on that day, that's over two years ago now. And on that day, if you said, where will we be in two years with voice and with avatars, you would have said, just perfect, like perfect, seamless, perfect salesperson. In reality, we don't have the compute, even though the technical capability is there, all of that compute is getting redirected into code generation, self-improvement, and the business use cases, which are now dominating the revenue. So I think what's possible on this side of Amazon is lagging what they'll actually do because

AWS is so much bigger than shopping at Amazon now. And they need, you know, they need to work very closely with Anthropic to roll out the business use cases. I think the other thing that's going to be coming is persuasive AI where a particular figure, maybe it's a construct that looks like a movie star that's your favorite because your AI knows what movie star is your favorite, sort of pops up and tries to convince the convince you to buy a product over another product. Well, this has been a historic problem with Amazon.

You know, the infamous acronym from Amazon, CRAP, can't realize a profit. So if you have crap can't realize a profit products, then one of the best ways to help realize a profit is, again, I mean that acronym only in the acronym sense. It's one of the best ways to do it is to have an AI assistant that's steering users towards on average more profitable products. Yeah. Let's turn to another story that is a big one. I don't think people will realize this. It's the Open AI Foundation story.

So after Open AI restructured, right, with the Public Benefit Corporation, the Open AI Foundation now owns 26% of OpenEye, PBC. And amazingly, this puts the value of the foundation at somewhere between $130 and $260 billion, and it makes it the largest foundation in the world. I look this up. Before this, Novo Nordisk and out of Denmark is $150 billion foundation.

The Tata Trust and India is $100 billion. Gates Foundation is $75 billion. right so imagine that open ai now has the largest non-profit philanthropic war chest in the world to do things with so they've given away three basic grants their first one was to people first AI fund which was launched in 2025 was a 40 million dollars distributed between you know to about 208 nonprofits around around the United States then they gave out 25 billion dollars a huge chunk back in October 2025 across health breakthroughs and AI resilience. And then this particular story is a new $250 million grant on economic futures.

So they're funding research on public wealth funds, worker ownership models and AI dividends. And it's basically, I mean, you think about it, as they're about to go towards an IPO, So they're trying to ask, how do we prepare society for the job apocalypse? And this comes at the same time that in our last episode, we talked about Sam Altman saying, you know, we're not going to have a job apocalypse. So two stories here. The first is their recent grant of $250 million. The second is the fact that this is the largest foundation in the world.

Salim or Dave? Two quick thoughts. One is, you know, it's incredible the size of this, right? It's like unbelievable. My thought immediately goes to the abundance XPRIZE and can we drop the cost of health care education, housing food? Is it $200 or $250? There's a thousand bucks for a family of four. Can you give all the basic needs?

And that seems achievable. And we should be pushing for that very fast because then everybody can live a better life of dignity or more people can. But I think the bigger issue here is not the economic question is not. job loss or any, the social contract, is value accrual. Where does value accrue in this future economy? Does it go to labor, which is what it had been before, but that's not going to be the case that does it go to capital? But as we demonetize, that may not be the case. Is it consumers? Is it governments? Or is a different, like kind of some sort of public ownership model? This is going to be the big question. And I think there is a huge conversation that needs to be had as to how

do we navigate this? Because this is the fundamental question of how we're going to navigate the next 20, 30 years. Well, just a reminder, you know, Salim and I are on the board of XPRIZE, founded by Peter. This should be the absolute mandate of XPRIZE. There's no higher priority in the world right now. And the amount of money that's that Peter just described, you know, people really struggle with million, billion, trillion, and now quadrillion is coming into our lexicon. But especially between billion and trillion, they're like, oh, that's a lot of money. But If I'd say, Peter, here's a dollar. And I'd say, Peter, here I'm going to be giving you $1,000.

You obviously know the difference between a dollar and $1,000. But when you say, hey, this charity is a quarter of a trillion. Or if I said it's a quarter of a billion, people are like, oh, big. There's a big difference between a quarter of a trillion and a quarter of a billion. And so I think that the mandate and the mission of all that money is global, calm, peace, prosperity. and it matters tremendously to Sam. I mean, tremendously to Sam. And so how many people have actually gone to Open AI with a proposal and said,

here's an idea. And I'll bet it's, you know, you count on one hand the number of people who've come to them with a practical idea. And so it's just an immense opportunity for people who, rather than rant, you know, online, come up with ideas for how to deploy all that capital to create global, you know, a transition to AI. that's smooth and abundant because it's entirely possible. You know, it's interesting. You're chomping up a bit. I'll go to Alex one second.

You know, Brett Taylor, we have in the photo here as the chairman of Open AI. People need to realize the Open AI Foundation, which controls only 26% of Open AI's stock, controls the board. The foundation votes on who's on OpenEI's PBC board. 100%. Alex. A bit of numerology. When OpenAI was running its super alignment effort, which was subsequently shut down, but nonetheless, superalignment, the originally publicly stated plan was to allocate 20% of OpenAI's compute to the superalignment safety effort. Switch gears. Social Security is approximately 22% of the U.S. federal budget. Someone somewhere, I'll make a prediction, is going to be asking the question, as OpenAI Anthropic, maybe.

maybe one or two other frontier labs, asymptotically converge on the total GDP of the world. Someone somewhere is going to probably ask the question, if you have a nonprofit foundation, that's 25% of the value, or 20 to 25% of the value of the overall organization, why isn't the foundation itself supporting UBI or UBS? I think you're right.

I think we're going to go there. I think there's going to be sort of a call for, the hyperscalers and the foundation labs to provide a percentage of their value back to. We talked about this in the equivalent of the permanent fund in Alaska that issues dividend checks to all of its, all the Alaskan residents. I think we're going to see this in the United States too. Something is going to need to underwrite some version of UBI that leads to UHI in the future. I think it will be irresistible, whether it takes the form of UBI or UBS or UBC or UBC or

UBE. If the frontier labs, the top two-ish, converge toward most of the global economy, I think there will be probably irresistible pressure for these 20% to 25% foundation arms to themselves support the UBs. Can I just mention something very quickly? Please, of course. For all the people that are new to this podcast or whatever, and I've not heard some of these terms before, be very careful.

A lot of people conflate UBI and UBS and whatever. as socialism, it is not. It is libertarianism because you actually dismantle government services. You double click on that, Salaim, please. Well, because people think of it as, oh my God, government giving out money. Remember the section we wrote in the 2.0 book, Peter coined by Harry Clore, which was technological socialism. Yes.

Right? Government socialism always fails. Why? Because allocating assets from a centralized model is inefficient and invariably leased to corrupt. And that's where the government is taking care of you. That's right. And government, it always fails. But think about Uber. Uber is the sharing, collective sharing of assets across the large group of people. It's actually kind of a socialist application. But when an algorithm hyper-efficiently matches demand and supply, you get all the benefits of the sharing economy without

the downsides. So we put that section as tongue-in-cheek. What we've seen when people properly implement UBI as you dismantle government because you don't need it, the market. The market, The market forces can drive it. The individual can decide where to put their money and the market takes care of the rest. And this is a profoundly important point that a lot of people miss. I just want to highlight that. Yeah. And technological socialism is where technology is taking care of you, right?

Which is a very important point because we're heading in that direction in many ways. Please, Dave. Well, just to support Saleem's differentiation there between socialism and libertarianism. And the town I live in in New England, when you cross into the town line, it says incorporated in 1649. So way, way back in time. And if you landed in the U.S. in 1649, land was free. You just needed to use it.

You put stakes in the ground. You grab it and you use it. And that's where we're going with compute and with AI. And that's not socialism. That's the exact opposite of socialism. It's like here is a, here's your UBS. We're giving it to you in the form of, you're your services. Here your services.

It's your ability. to thrive in the post-AI world is like the land was in 1649. Without the land, you could do nothing. Without the compute, you can do nothing. So here are your services you get for free, now build on top of it. And just like in 1649, you didn't need a huge amount of government. You just needed some basic policing and some military, and you were done. And this is very similar to that.

It's like homesteading for AI. Alex, take us home. Yeah. In my mind, to Salim's point, I'm not convinced, A, that socialism always fails, which is ironic that I'm arguing that. But I would also say to my mind, if just conducting, playing out the thought experiment, this thought experiment looks more to me like privatized socialism rather than libertarianism. If I had to pin an ism on it, if you have an enormous sort of economy-swallowing nonprofit that owns a PBC, that's under political and other pressure to distribute UBI, UBS, UBC, UBE. What's UBC UBE?

UBC is universal basic compute or universal basic capability. We use it as capability in our book, Peter, others define it like Sam as universal basic compute, and UBE is universal basic equity, so basically dividend checks for everyone. So regardless of which form it takes to my eye in this sci-fifference, scenario, this looks more like privatized socialism where we have a handful of frontier labs that are just dominating the economic output of the economy. By the way, I don't actually think this is how it's going to play out. It's just a thought experiment. But in this thought experiment, looks more like privatized socialism to me. I think the final point to be made here is for most

of societal history in let's say the last couple of hundred years, the government has been the backstop. And here we see potentially these frontier labs and hypers being the backstop for society, making sure that people are able to survive and thrive and I don't even say earn a living, have a living. It's an interesting transition. But we're seeing the fundamental transition of societal structure. Selim? There's a broader conversation here that we actually should do a better treatment on, which is governments tend to centralize, and you can't achieve abundance-fied centralized structures. You need decentralized structures because they scale.

And so there's a huge tension right now between this. Governments always, the formation of the U.S. was to break apart having a king and having everything centralized. And now I look at the government, trying to centralize everything again. So there's this tension that goes back and forth between centralization, decentralization. But we have to figure that decentralized future out, and that's not a trivial comment or problem. If I could just add one more point on this, Peter. There's one more ism that we so rarely talk about on the pod, which is Fordism. So in the sense of history, perhaps rhyming, recall that Fordism, named after Henry Ford,

is a socioeconomic system in which you have mass production and mass consumption, and the two are matched. So you're mass-producing via moving assembly lines and you have extreme division of labor, but at the same time, you're paying workers high wages so that they can buy the products that you're making. So if I squint at some of these OpenAI Foundation nonprofit scenarios, there's a world that looks a little bit like UBC, but also looks quite a bit like Fordism, where everyone is receiving handouts so that they can purchase the tokens so that the virtuous cycle can repeat itself. And you see this playing out, for example, possibly in Sam or OpenAI,

giving $2 million to YC companies so that they can purchase tokens again, or in the form of just-in-kind token donations. The biggest difference versus Fordism and the Industrial Revolution is just the raw scale of abundance that's suddenly possible. The backdrop behind all of this is we're going to be splitting hairs on how to share the wealth, but the amount of wealth is like nothing the world's ever seen. And also, it's not, there's no real upper bound, you know, there's nothing that technically prevents it from going to infinity. And do Elon's prediction on triple-digit GDP growth?

Yeah, exactly. So it's a great, great, great tailwind. And yeah, all this complexity layers on top of this. I know, worst metric. GDP worst economic measure ever. But the point here for everybody is to, you know, inject little optimism in the picture here. We're about to see the global economy just skyrocket. it. Well, that's another reason why approaching the foundation with ideas is like the biggest

no-brainer. There's so much abundance to go around. There should be this litany of ideas flooding into Brett Taylor's office, just a hundred, a thousand times more ideas than we're currently generating. So it's kind of a call to ours. If you're listening, we're ready to talk. X-Prize has got-Q-L-US. Yeah, call us. You know, one of my next conversations with Elon is going to be, I know you funded $100 million X-Prize for carbon extraction. Let's fund. fund 10 billion dollar XPRIES for the 10 most important, you know, not giga scale, terra scale challenges in the world. And I think if we had those benchmarks, those 10 sort of shining stars, it would guide where graduate students do their research, if graduate students are still

a thing or where companies go and focus. You know, these are targets to shoot for. Everybody, welcome to the health section of moonshots, brought to you by 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 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 Musilam, the chief medical officer of Fountain Life and a member

of my Fountain Life medical team, Dawn, a pleasure. So, Don, talk to me about brain health. Brain health, you know, you're right. This is the number one concern people coming in to 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, 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. 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 slash Peter to learn more and become the CEO of your health.

Now, back to the episode. Let's talk about the next story here. The U.S. just made its biggest bet on quantum computing ever. IBM and the Department of Commerce announced Andron, America's first full purpose-built quantum chip foundry. It's a $2 billion play. A billion dollars is coming from the Chips Act money, from the government. A billion dollars is coming from IBM. They're building it in Albany, New York.

It's a 300-millimeter manufacturing process. They can produce quantum chip devices 30 times faster than current methods. The Foundry model means IBM becomes equivalent to sort of the TSMC of quantum. Other companies in the space, Google, INQ, Raghetti, D-Wave could potentially manufacture their quantum devices on Anderon in the same way that fabulous companies like Apple and VEA, use TSM for classical chips. I'm going to go to you first, Alex, on this. Are you excited about this? Is this?

I think this is actually a smart bet. So even though normally I would probably complain about quantum being a solution in search of a problem, at least quantum computing, not quantum sensing, which I absolutely love, but quantum computing being a solution in search of a problem, and probably refer back to previous comments about how the likeliest problem to justify the CAP-X is going to be something AI in nature, either quantum accelerated AI training or quantum accelerated AI inference. I think it's actually a pretty smart move because it's going to take a few years to build out this Andron foundry. So we're talking maybe late 2020s. And I'm pretty optimistic that sometime in the next

few years, probably by the time this foundry is ready and at scale, we will have quantum accelerated AI advances, in which case we really do want the superconducting qubits that provide infra for those quantum accelerated AI advances to be right here in the U.S. and not say on Taiwan. So I think in that scenario where we get AI quantum acceleration, pretty brilliant move to get ahead of the ultimate geopolitical conflict rather than play catch-up again. We're going to have Michael Kratios on the pod very shortly. we'll talk to them about this.

I love the fact that the government is taking these moves and that IBM is stepping up. Silea, you've been tracking this area. I have. I think this is, you know, there's an huge inflection point. Once you have quantum devices moving from bespoke lab systems into found reproduction, the innovation curve changes completely. This is still a long ways away just because we still, I think we're still at a ratio of about needing a thousand physical qubits per logical.

Yes, correct. Right? And we've not been able to break through that for a while. There's so many errors, you need all these. But if you drop the cost of creating the logical qubit, in this case, by 30 times, that's just the devices forget the actual cubits. You radically change the game and you just can flood the system with just a lot of physical cubits.

And then you can get to the benefits of quantum computing. think this is still a few years away, obviously, but the power of this is going to be really exciting. Dave, any thoughts? Yeah, I was on a panel with Alex earlier this week, and this topic came up, and Alex really, like I said earlier in the pod, he says exactly what's on his mind, and so he stepped on some people's toes by saying exactly what he just said. Quantum Computing is a solution. I'm not here to prop up the quantum computing industry. I don't have any conflicts of interest. Well, it's, I think we need to put a pin in a future conversation about the difference between quantum computing, quantum photonics, and quantum sensing. Because two out of three are

extremely exciting. So we should come back. Jack Hattery, friend of the pod back on, you know, they've done some extraordinary work with quantum sensing, quantum navigation. And it's not using quantum chips. They're basically using all the quantum equations on, on, on, on, on, on, on, on, on, on, on, on basically on an AI infra, we're going to start to see quantum begin to play. All of our systems, material sciences, biology, chemistry, is quantum in nature. I have two quick thoughts. One is I remember spending some time at the Perimeter Institute of Waterloo, which has been funding quantum stuff for a while.

And they did what David is talking about, where they broke it up into networking, computing, and sensors. and they're having lab work on all of those three, and then thinking we'll bring it together at some point, which I thought was a great way of breaking it down. The second, I can't resist throwing out the Hartnnevin comment, who is the head of Google's quantum AI computing lab, who said, when we build a quantum computer,

it will be definitive proof that we live in a multiverse, and then everybody's brain just explodes right there. Okay. All right, let's go from the sort of the esoteric to, the real functional here. So here's a milestone I've been waiting for for a while. For the first time ever, wind and solar generate more electricity globally than natural gas. Obviously, we've blown through coal. In April of 2026, wind and solar hit 22% of global electricity, surpassing the 20% from natural gas. That's nearly 330-terwatt hours. And it looks like the growth rates are across the board. China,

increased by 14%, the EU by 13%, the UK by staggering 35%. This is energy abundance curve. That's what I've been talking about for a while. Solar and wind aren't just the future of energy. They're here now, and they're still on an exponential curve. You know, we've talked about this. The Earth is bathed in 8,000 times more energy from the sun than we consume as a species. You know, Elon's been just harping on this for a while.

We don't need anything else. We just need to continue to tile the planet and solar. And of course, gain access to all the solar coming from the sun, you know, heading toward a Carditch-F-1 scale planet. Dyson swarm, Peter, a Dyson storm. Yes. That was a great quote, Peter. Wind is blown through coal.

We gotta make a t-shirt of that. And solar outshines gas. Do you guys remember Google had RE greater than C as a motto? Renewal energy greater than coal? Well, you know, we're here. We're here. Blue through that now through natural gas. And it's so true, I still don't understand why the U.S. isn't accelerating this in the same way China has.

China's gone 10x past us and solar. Selim, your thoughts on this one? I want to just step back one level and do two kind of comments, broader comments here. One is we talk a lot about exponential thinking, and it's really important to kind of just frame that back to root first principles, which is that when you have a doubling pattern like Moore's Law, Ray identified that that doubling pattern doesn't stop. And we have a tough time with this cognitively, because you can't have infinite growth. It has to level off.

And Ray, after researching this for 10 years, came up with that orange diagram that we show a lot, where you had vacuum tubes, and then you had before that relays, then we had transistors. Each one is an S curve. Vacuum tubes take off. We can only fill so many, put so many in a room.

But if you have an information-based environment, the next technology takes over, you get to the next S-curve. And it keeps going. We're reaching the end of integrated circuits now, but we have now matrix style architectures. We have 3D chip design. We have optical computing.

We have quantum computing. One of those or more will take over that curve and that curve just keeps going. This is such a powerful and important thing. It's the foundation of everything we taught of singularity and everything to do with exponentials. People can't get their head around the fact that solar is on an exponential curve.

It's been doubling every 22 months for 40 years. This is not a new thing. So at that doubling pattern, and we're reaching, yes, we're reaching the end of the life cycle of silicon-based panels, but now we have perovskite, and then at some point we'll have something else. And that curve will just keep hopping up and across so you can bank on that. Yes. And when you can bank on that, you can see the curves going. The problem with the exponential, it looks flat when you look back and it looks impossible when you look forward. And so people go, well, that's impossible.

just like our energy secretary says, solar will never be more than 10% of energy supply, which is completely insane. This shows you that we're getting there. And we're getting there faster than anybody thought. Ramez Nama, our favorite energy guru, keeps saying every time I was super optimistic, I was too slow to the curve.

You have to be radically optimistic to watch this. And if you want abundant intelligence, whatever we call intelligence, you need abundant energy. Right? So the winning countries will be the ones that can connect cheap electrons to compute as quickly as possible. Yeah. And, you know, the other thing, Salim, we've talked about this before, and Rames-NOM does an amazing job showing all the international agencies like IEA, you know, all their projections are wrong over and over again. Over and over again. And in the next part, I'll bring those slides. I'll come with the data. And I want to show those. Yeah, IEA's 2020 model didn't expect wind and solar to surpass gas until the mid-2030s.

And here we are in 2026. 2047, I think it was when they said. My favorite one is they predicted that there were not be more than a million electric vehicles by 2040 electric vehicles. That was their prediction. They put that prediction out in 2015. By the end of 2015, we had more than a million electric vehicles. It's just like how, you know, if you made predictions that were that wrong year after year after year, you should literally lose your job. You have no business.

It really shows this is not a math error. This is a cognitive error. We have to overcome that, which is what this pot is all about. And God bless our listeners for kind of taking on this new paradigm. Dave. Yeah, Peter, Salim and I, you know, we like to think of our kids in the back of our minds when we're doing these podcasts and think what should you be saying to your own kids. This one, there's a whole generation. of people that I know who said about 10 years ago,

I'm going to dedicate my life to green energy and to global warming. This is the greatest problem of our time and this is what's going to drive humanity forward. And I was thinking in the back of my mind, I've heard that before over the decades with other topics. And this is an engineering problem that might get solved.

And the phrase, I'm going to dedicate my life to blank is a big mistake in the age of AI. A big, big mistake. Instead, think, like, I'm going to have a constantly changing life and treat this like an engineering problem, not a political. This became such a political garbage topic when it's really just a get it done engineering topic. And so get out of the politics and don't get trapped into the politicization of all of these things and never say I'm going to dedicate my life to blank. Instead, be nimble. and constantly.

There's one rational understanding for what the U.S. is reticence for solar, which is that because China is so far in the lead in making the panels, until the infrastructure in the U.S. is ready to make solar panels, whatever they look like, it's hard to push it because you've got, you have to go to China to get all the panels. I'm kind of surprised Elon hasn't doubled down. When we met with him back at the Gigafactory, if you remember, he said he gave the edict to both, Tesla and to SpaceX to increase their solar production. But we still haven't seen, we saw one machine that was sort of laying out solar panels in

the desert and doing it, you know, fully autonomously. I'm surprised we haven't seen more. Alex, you want to close us out here? It may be just a comment on Elon, the Elonverse and solar. So something I talked a bit about in my newsletter was the pivot by Tesla away from their solar city acquired. rooftop solar tiling toward more conventional solar panels, which they're now producing out of their facility in, I think, upstate New York.

I do expect, given the amount of demand, that one can reasonably anticipate sun-synchronous orbit-based Dyson swarms from SpaceX will need, that SpaceX or SpaceX plus Tesla, if they end up merging in the next year, will end up probably in the short term, importing cheap Chinese solar panels, combining that with their own native production facility and upstate New York, we're going to need a vast scale-up of domestic or sun-synchronous orbit or lunar production of solar panels. And I expect Elon's SpaceX or SpaceX Plus entity to end up being forced to do that and not Tesla, which was never a perfect fit. And just to bring out the importance of this, China has already a structure where they have

robots building solar panels to generate the energy to build more robots. Yeah, exactly. We call it the interlough. That's the inner loop. That's the inner loop. And this is, that's already started. You cannot far behind on that. Yeah, really important.

Well, really important also that Elon always does fundamental physics and, you know, what's fundamentally possible. And Peter just mentioned that we get bathed in 8,000 times more sunlight than all of the energy we consume. And I think Elon said a little corner of Utah would power the entire United States. So this is the fundamental metrics. And the solar panels we already produce, the cost is just purely related to that automation of the construction. The fundamental materials going into the solar panels are basically near free.

Literally dirt cheap. Dirt, literally sand and dirt cheap. All right, this next story here gives me the chills. The federal agencies have created a new brand of threat. It's called anti-tech extremism. They've logged over a thousand pages monitoring threats against data centers and tech executives. This comes after the attacks on Sam Altman, you know, the Maltaf cocktail, the firing of guns. We talked last week about the potential of organized pushback against AI.

Well, the government is now treating it as a domestic security concern. When the FBI creates a new category for something like this, it's time to take it seriously. I want to link this to also a recent video, Dave, you and I watched about Mr. Wonderful talking about what might be sort of Chinese, funded, you know, anti-Data Center protests. Thoughts on this, Dave? Well, I think the data or the evidence on the China involvement is pretty irrefutable. And so this has always been America's Achilles heel, right? Voters can get whipped up. And it's what the Soviets tried to do during the Cold War as well, trying to whip up demonstrations and votes to stop progress so that they could bypass the U.S. technologically. So it's kind of history repeating. It's a

But democracy has this as a major, major Achilles heel. And I think the violence part of it would also freeze all the scientists from trying to work on these things. And that's very real, too. I don't know if, yeah, I don't want to actually don't want to dig up history on this. But they have to take it very, very seriously. Otherwise, we're just going to stop working on it. And then China will run away. I mean, it's much easier for, in theory, I don't want to say this is happening.

I don't have evidence myself. only what I read, but in theory, you know, this is a super, you know, efficient way to put sand in the gears, you know, get the public. And it's doing, you know, how many data centers have been killed? Like half the data centers have been either canceled or slowed down. Alex, what are your thoughts? I'd like to see much stronger federal law enforcement of preventing threats by anti-tech extremists against technology. I think at this point, it's potentially, potentially a national security threat. And I'm not at all thrilled that there is a group of extremists out there who may be handling over ways to destroy any AI initiatives that might actually radically grow the economy and grow the pie for everyone. I think it's a zero-sum or negative-sum mentality that we as a civilization and as a country and as a democracy, we really need to grow past. So there aren't that many areas where I just sort of hang my head and cry. This is one of

them. Salim. To the extent that there is external influence whipping up this frenzy, that really has to be stopped. We already suffered from this. We've already suffered from Facebook kind of training all our kids in the wrong way and having all sorts of media. I mean, something like 70% of people radicalized on Facebook where because of its algorithms and people doing injections of negative things. And this goes back to the human brain, Peter, that you and Stephen Kotler identified, your amygdala is 10 times more likely to pay attention to negative. And you. them positive news because of that survival factor back in the 10,000 years ago, if you heard a noise in the bushes, you ran.

And so we're so triggered by negativity. And it's very easy to incite this type of stuff. And therefore, it's very cheap. And overcoming that impedance mismatch is a really, really big challenge. Well, look at the data. You know, Salim, in China, 80, 85% of people are optimistic about AI, but the state controls the media. In the United States, it's like 25% are optimistic about AI.

But the media thrives on controversy. And the more controversy, the more clicks, the more ad views, the more revenue. So there's your dichotomy. And so China's going to have a very easy time keeping the data centers constructed because everyone's optimistic about it. And the U.S. if we grind to a halt, it's going to happen anyway, but it's going to happen in China. I had a conversation two nights ago.

We had a event for our Future Vision XPRIZE with our friends at Google and range media. And there were two young guys there, Josh and Jack. And if you guys are listening, they were 21. and 22-year-old in college and just graduated. And they were telling me how much pushback they get from their peers, that their peers just think AI is the worst thing. And they were so happy to be in a room of people who were, you know, excited about and supportive of AI.

And I hate that notion that on college campuses in particular. And we saw that with, you know, the booing of Eric Schmidt at the commencement address. That truly scares me that the single most important technology that our 20-something-year-olds need to be learning how to use and, you know, utilizing to make their lives even bigger, upscale their ambitions in life are culturally now being pushed back on. And oh, my God, I can't believe you like AI. What's wrong with you? Yeah. Well, you're 100% right. That's exactly what's going on, Peter, because my –

My son Jack at Northeastern is running into that headlong with his, he's got a hackathon, AI hackathon going on. And the subset that are into it are super excited about it. But there's this other big subset that's just, you know, kind of, you remember how the jocks used to beat up all the computer geeks back in, you know, the 1980s and 1990s. Is that happening all? Yeah. It's that all over again, except it's now, oh, you're an AI person.

Yeah, you geek. Get out of here. So it's terrible. It's really, really. And, you know, you look 10 years in the future. and you know who's going to be thriving and who's not. It's just got to talk some sense into the rest of the class. But it's hard.

Our next story comes out of California. Governor Newsom just signed a first of its kind executive order to study how AI affects California workforce. This is big because, you know, California is the fifth largest economy in the world. The state is building a public dashboard to track AI-related job losses in real-time, identify vulnerable industries,

and explore real-reveillance. retraining programs and UBI models. This is the most concrete government action being taken. It's not a white paper. It's an actual infrastructure and measurement play. You know, I actually assuming that the data is correct, it's not biased. I'm interested in seeing this. We have, you know, it's still so murky about what will AI do to the job market.

You know, we've heard both sides of the equation. We heard Sam saying, no, I was wrong. We've seen also in the data that the group out of work the longest is 22 to 28-year-olds. It's not that people are being fired. It's that they're not being hired. They're hiring freezes. Dave, do you want to jump in on this first? Well, you know, 300,000 jobs have been lost to AI at most.

That's less than people have died in Ukraine. So this is not a crisis yet. It's just the fear of a future crisis. And like we were saying earlier, the tailwind is much, much stronger than the headwind. There should be massive, massive abundance as a byproduct of what's going on. So I think studying the actual data is a great first move because, like, you know, everything you read online is inflated like crazy. And Sam reversing course on it, you know, maybe he doesn't want to have his door shot at again. Or maybe it really is.

In my personal experience with Vesmark, I was worried about about half the jobs being automated away. it's going to be zero now. We're growing so quickly and the profitability is going up so quickly there's no point. There's no need in doing to do job cuts.

And so if that's true in other companies in the financial services sector then there'll be no job cuts at all. It doesn't mean the fact that no one's hiring. It's definitely true that college hiring is at an all-time low,

but if you're starting a new company and you're an entrepreneur, it's the best time to be recruiting at a college that I've seen in the last 20 years. So there's good news on that front if you take your entrepreneurial lens and shine it at this. Alex, you have a thought here?

Yeah, I think this is a case of federalism giveeth and federalism taketh away. I think if you juxtapose this with movements by California at the institute so-called billionaires tax and wealth tax and driving away sort of Atlas shrugged style, driving away many of the key technology leaders who've created so much of this wealth, one half of the split screen and then in the other half of the split screen experimentation with dashboards and tracking AI losses and UBC experimentation. I think there's a case to be made that we really do want each of the United States

experimenting with different proposed solutions. I happen to favor the UBC or AI dashboard model versus the wealth tax model. But I do think it is at least positive that we're seeing some sort of experimentation by at least California and presumably soon other states regarding how this transition to AI automating or solving or cooking most of the services economy will ultimately look. And it's far better to have it at least the future of unemployment programs or similar handled at the state level rather than the federal level. On the other hand, I would argue we really do want federal protections for AI technologies, so this doesn't devolve into one fully balkanized set of regulations that make it impossible to advance AI capabilities. That's exactly right. Sillian's a final word here.

I'll take the positive view here, given that I started out with this pro noia monstrosity of a word. You know, at the negative, you can look at this as the state trying to control and oversee and protect labor, right? But if you take the positive side, this is the first, this is government as sensor, where the dashboards are trying to time things and figure out what's happening in a more shorter time frame than 18-month labor statistics.

So when you have those early warning systems, you can react more quickly because obviously dashboards aren't enough. You need rapid reskilling. You need different ownership models, et cetera, et cetera. But the potential here for, government, which is always lagging way behind to be able to sense things more quickly, I think is an enormous positive. And so I think this is like the first primitive of like a post-labor state where you're tracking things. And also look at the idea that you're moving from a, like all

government is organized around a labor economy. We tax labor. We try and protect jobs. And we're moving now to like as you sense what's coming, you'll be able to start moving to a post-labor economy, whatever that looks like. But the, because labor is collapsing, therefore the state has to change. And so that has to, that's a structural challenge.

And I think I take the positive here in doing this early warning sensing and real time sensing, it'll push the policy side to move that direction. That'll be the positive rather than the negative. Oh my God, hunker down and protect labor even more.

I'm excited about getting the data. All right. This is a fun story. researchers at Westlake University in China just built a handheld device that can detect early stage lung cancer from a single drop of blood at a near 95% accuracy. It's published in nature photonics. It's 10,000 times more sensitive than standard labs. The core sensor just cost five bucks. I mean, this is the abundance play. It's demonetization, democratization of cancer screening. You can imagine seeing this in rural India and sub-Saharan Africa. Alex, any thoughts?

here. And it's optical, and it's not coming from Theranos. This is such major progress. N years after Theranos, leave it to Chinese researchers. It's sort of an interesting on-chip technology using metamaterials to look for very small changes in refractive index from blood, so from light passing through blood used to detect early stage cancer. I think in general, putting aside all of the drama around Theranos itself, there's a sense in which there was always going to be an opportunity for radical new diagnostics from relatively de minimis volumes of blood. But in some sense, it was, I think, just a matter of time for technology

and in particular for optics to catch up with this. And I'll make a forecast. So if you remember a while back when Almond, Alphabet was first formed. Google transformed into alphabet, and as part of the alphabet transition, Verily, was carved off as sort of the big biotech play within the alphabet ecosystem. At least for a while. For a while.

Rest in peace. For a while. There was a lot of early interest in non-invasive wearables for cancer diagnosis. And in particular, I think one of the most absolutely fascinating Verily projects was going to be sort of a small. smartwatch that would use purely non-invasive optical change detection, shine light at various frequencies through your wrist, combine that with an edible or injectable, but I think it was originally supposed to be an edible tracer that would enable some optical change to be detectable

from your wrist non-invasively through optical changes. I think we're going to actually realize that. It looks like it's not going to be verily that implements it, but I'll make a forecast, not going to provide a particular timetable, maybe say next five years or so. I think we will get to non-invasive, wearable, optical cancer detection, and it's not just going to stop with metamaterials, ex vivo, with a single drop of blood. It's not just cancer. It's going to be your physiological state in the moment, right? At-home testing where you can know exactly what's going on.

it's uploaded into your AI, you're catching disease at inception when you can cure it most accurately. And this compares to sort of like a, you know, a refrigerator size Eliza machine. And it's being done in minutes instead of an hour. It's extraordinary progress. But I think critically, why do we care that it's $5 versus $5,000? If the chip is $5,000, but it can do high throughput screening, you can still sort of in the style of the company or the project Grail, you can still completely transform preventative cancer screening. Where I think this gets really interesting and why I would argue we care about making the hardware for cancer detection so cheap is because we can make it wearable.

As long as we can figure out how to do this non-invasively, we can build it into a smart watch or a smart wearable. Or if not wearable, it could be at home, right? It's like every day you brush your teeth and you check your blood and it's keeping you in health optimization. Consumers can own it is the transformative outcome here. Yes, yes, exactly. And it's available to 8 billion people. You know, it's at a price point that almost everyone can afford. It's true. It's true abundance. Selim, Dave, anything else?

I have a couple of comments. This is the bellwether and poster child of everything we talk about on this pod and everything we all talk about, which is that technology is a major driver of progress in the world. It might be the only major driver of progress in the world, as Ray Kurzweil says. Now we have a dozen technologies moving. We're democratizing and demonetizing things. This was a $10 million machine 15, 20 years ago. And now it's like $5. This should get everybody incredibly excited because there's thousands of this type of thing

coming along in the next few years. In every domain possible where we're going to crash the potential, the previous cost by orders and orders of magnitude. So important. And you think about the idea, the diagnosis of health care now of any condition between AI and tests like this become near free. Diagnosis becomes free. And now you just have to worry about the treatment protocols, which is much easier once you

have the diagnosis accurate. And your AI can analyze all of it, right? Yeah. I mean, every single tech watcher should get very, very excited about this and trumpets this type of thing through the rooftops because this is the future. This is why we get so excited. We can cure so many amazing things in the next few years with all this stuff. This episode is brought to you by Blitzie.

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They're saying that America needs a wake-up call on robotics. Alex, you've been saying this for a while. You know, their argument is that China's output in the world in solar and 5G is the exact same pattern being played out in robotics. So Mark Andreessen's quote is blunt, quote, the U.S. must work with allies to build a defensible AI robotic stack. this is the time, but, you know, there is time, but not much time. Alex, you've been pushing on this for a bit. I've been pushing, and is one of the reasons why I helped form company pro-R-L to get humanoid and non-humanoid robots out into American streets and to juice the American supply chain.

I think this is a very real problem. The Chinese Communist Party has a five-year plan for, they call it, AI Plus, not just a foundation, models and not just training infrastructure, but physical integration of AI throughout the economy, including more than 100, I think now more than 150 humanoid robotics companies that are coming out of China. So I think I completely agree with Mark. I think this is a very real problem. I would like to see leapfrogging capabilities, not just parity or peer competition with China to see if we can also start 150 humanoid robotics companies. I'd like to see much, much deep integration of general purpose robotics capabilities into all facets of the U.S. service and

physical labor economy. And I think government has an important role to play there in juicing demand, in creating favorable regulatory regimes to put robots everywhere. But again, being in Boston, although I'm in Chicago, ironically right now, in Boston, we're still struggling to get Waymo's. And that's something I've been pushing on as well. If we can't get Waymos, how are we going to get humanoid robots everywhere. So I think we have a lot of work cut out for us ahead of us. We need our Shenzhen here. Dave, I heard you say something recently that I thought was prophetic, in particular on how, as the leader of Link exponential ventures, where you're thinking about deploying capital. You know, you've said probably a two-year window on AI software-generate companies

and you're going to be directing more of our capital, just full disclosure. I'm Dave's partner and Link XPV towards hardware, towards robotics. Can you speak to that? Yeah, I think this is going to play out right down the middle of our fairway where incubators and accelerators are going to thrive. It's very similar to biotech where all the ideas come from startups, but the startups need to be part of a larger Eli Lilly or part of a flagship pioneering ecosystem,

which has already got the regulatory figured out, the sequencing, you know, all the heavy lifting machinery that takes a decade to develop is already there, and then your idea can inject into that ecosystem. Robotics is very similar where a brilliant team of three people says, I think we can build a robot that does X. It's far better to be in an ecosystem where the manufacturing, the supply chain,

the actuators, the funding, all of that is figured out. The lab space is all figured out. So that's what we're building now. We've had something like 80 consecutive AI deals now, and the returns are incredible. It's like nothing I've ever seen. But the window of opportunity for pure software AI is probably another couple of years. And then the self-improvement loop is just going to take over.

I think robotics is a good 10-year theme, just like biotech is a good 10-year theme. So, you know, we've got our first robotics deals already done. We're doing a lot of robotic operating system deals where they're reusable across many, many different devices. And then also you notice in the college campuses, a lot of computer science majors are now shifting back to, material science, Mecki, and some of the hard scientists, sciences, which is an anticipation of this wave, you know, being, because if you're in college right now, you're going to, you're kind of kind of missed the foundation model wave, but you'll be perfectly timed for the robotics wave. Also, you know, everything we've ever done with robotics needs to be rethought for space,

zero G and, and radiation. So you got to, you got to do it all over again for manufacturing out in space, which is another great, great theme that we want to get ahead of. Yeah. Let me hit on a couple of robot stories and then one in particular for Saleem. So this is first Honda's robotics company is starting to learn to play soccer. So, you know, in prep for the World Cup, here we see Atlas kicking a soccer ball. It's going to be interesting. Let me show the next two videos and we'll talk about the robot companies. We'll talk a little bit about figure AI entering, you know, sort of a new record of continuous package sorting.

All right, out of China, we've got the dollar haircut. You've heard the Dollar Shave Club, but now the Dollar haircut. Take a look. Finally. Yeah. So here we see a robot. And I do think this is kind of inevitable, but are you going to trust a robot with a sharp blade very close to your neck? And Salim, this one's for you, a humanoid robot with six arms.

You've been asking for this for a while. And your thoughts, Salim. Oh, I just love it. You know, why limit the two arms, for God's sake? I always use the example of when you're trying to open a garbage bag. You need a third arm to hold it open for God's sake. And I just want to just thank all the viewers and listeners. People have been tweeting things.

Salim, here's your robot. Here's a six-wheel thing. Here's a forearm thing. So it's been absolutely fun to do it. It's just, I think it's a great way of adding the, taking it away from just the humanoid figure. And yes, I understand that humanoid robots are used to moving around in human spaces, but an extra arm can't hurt. And we saw, we saw figure robotics. How long did it do a continuous package sorting for?

Is it still going or did they? For longer than a week. I think Brett ended it after eight days or so. Yeah. Well, we're going to see a lot on the robot space coming out shortly, of course, Opti. Optimus, next iteration of Optimus 3 is expected. And when we were there, what was it, 10 million square feet of Optimus production capacity, Dave? Something like that.

Yeah, something like that. That's huge. All right. One sad story here is Blue Origin's new Glenn exploded on the launch pad. Take a quick look at this video. Here we see it in Cape Canaveral. This was during a ground test. a cataclysmic deconstruction.

Yeah. You know, it's never easy. You know, it, but, you know, the hardware is hard. It's who Blue Origin had a rough week, new Glenn. Jeff Bezos's heavy lift launch vehicle exploded during a static fire test at the Cape. You know, this is the rocket development game. You're going to have setbacks along the way. You can't test it piecemeal.

You know, SpaceX has blown up plenty of. rockets. This time is painful. SpaceX just launched their Starship V3 last week very successfully, and Blue Origin is going to be hit by this. This is the vehicle that's also planning to launch Amazon's Project Cupier. They're going after the NASA lunar contracts. Alex, any thoughts? Yeah, well, first, and maybe most importantly, no one was hurt, so that's great. This was a unmanned vehicle. This is a seven- satellite launch capability right now. Second order impact, Artemis.

So this was the main vehicle for Blue Origin participating in Artemis 3. And so it looks seemingly just playing Kremlinologist here on the contracting supply chain looks to me like SpaceX is very likely to end up being the preferred end-to-end vehicle for getting humans to the moon over the next few years ago. I think the general consensus in the space community now is this could set back Blue Origins,

Artemis Lunar Colony plans or participation by up to a year. So superficially a good opportunity for SpaceX to shine in getting Americans back to the moon over the next couple of missions. But hopefully Jeff Bezos and Blue Origin are able to rapidly rebuild and reconquer Leo and then CISL lunar. Yeah, and I think the implications as well to Kupier is an important implication, too. All right, let's wrap up with some quick AMA with the mates. We only have five minutes left here. Salim, do you want to pick the first one?

So given China's AI adoption, robotic scale and population, how likely is that they hit abundance before anybody else? This is from AD Plano. So this is very possible, but I would separate the material abundance from human abundance, right? China has a huge shot at reaching material abundance with solar batteries and EVs and robotics and logistics, etc. They have the scale and supply chains and so on.

But abundance is not just cheap goods. It includes agency. It includes freedom to experiment. It includes human flourishing. It may get the cheap physical production, but the West may still have an edge in entrepreneurial recombination, open innovation, meaning making.

We just have to make sure we don't lose our freedoms along the way, which is my big concern at the government level. Alex, what's your question? I'll pick number one. When do agents start running political campaigns? And this is from Mad Profit of Waikiki. Well, mad profit of Waikiki, I think they'll start running political campaigns maybe 10 years ago.

We've had AI agents deeply involved, site to social networks being involved in both local and federal in the U.S. election campaigns, involved thoroughly end-to-end, and AI involved that entire stack even prior to the LLM revolution. We've had agents, an agent being just an AI that incurs multiple sequential interactions with an environment. That's advertising and online retargeting. That is fundamentally an agentic process in nature. So I would argue we've had this for at least. at least 10 years, probably materially longer. Dave.

I'll take bullet to. Of all the recent layoffs, how many people realistically have actually turned into entrepreneurs, and that's from AI business and a box. I did a spot survey of Microsoft, you know, Microsoft and Amazon and Seattle had about 20 or 30,000 layoffs, and then meta has another 10,000 in San Francisco, Silicon Valley. So I just poked at some LinkedIn profiles.

Short answer is in that sample, almost everybody has either joined a startup or joined another company that was recently a startup. So it's the best time I've ever seen by far for entrepreneurs and startups. I mean, by far. Now, that sample is just covering software engineers from Microsoft to Amazon and meta. So that's a very different sample. If we start seeing layoffs in robotic areas like garbage collection, I'm sure you're not. not going to see anywhere near that number of people joining startups. So I haven't sampled that yet. But at least within the tech community, it's a very, very rosy picture. Again, driven by the fact

that the amount of abundance is just massive in scale so it can absorb a lot of humanity. So not bad so far. All right. Number four, from at Malcolm Macon, 69, if white collar jobs vanish, won't tax rates spike to fund welfare? Does an unemployment doctor get paid the same as an unemployed addict? Fascinating way to put the question. So this assumes that jobs vanish rather than getting transformed, which isn't what the data show so far, right? So Dallas Fed says it's a hiring freeze, not mass layoffs. But I think your deeper question is around differential welfare, and that's fascinating. I think we're heading towards something like a universal basic capital rather than a flat UBI.

Instead of paying everyone the same, you give people ownership stake in AI-generated wealth proportional to their contributions or their retraining effort. I ultimately think that we're going to see some base level of UBI, but then people are going to be able to use UBI or UBC to build on top of that. Do you guys have a second for another question round? Yeah, absolutely. Okay, great. Let's do this.

All right. Back to you, Salim. Let me take question five, the first one. Isn't the real privacy question, not what AI systems know about us, but the legal protections on what they're allowed to do with that knowledge? And that's from user at poetry to song, which is a great handle. So that's exactly the question, right? Privacy used to mean what data do you have, but the deeper question is, what can an intelligence

system do with that data? Can it change my insurance costs? Can it change my vote? Can it convince me about stuff? Can it deny me credit? So the new frame is not just privacy rights, it's agency rights. We need to have protections around having access to inference, prediction, manipulation, it's not about what AI knows about me that it like hiking or red wine. It's if knowledge is used invisibly to constrain my choices. Okay? So in the 20th century, privacy was the big issue. The 21st century issue is agency.

What can an agent, can AI improve my agency in augmented or reduce it? Okay. Dave. Love number six. Why is taxing tokens a perverse incentive? AI is going to drive the future economy. Taxing tokens to fund UBI makes sense. What we don't want to do is repeat the error from Obama.

care. If you remember Obamacare, everyone was going to have a health care card. We're going to have universal health care. First thing we'll do is we'll pass a new tax. We'll call it the net investment income tax. It'll be three and a half percent tax on top of all other taxes. Here we are, you know, 15, 20 years later. We still have the tax and we don't have the Obamacare. So everything got thrown out by the next administration except the tax is still there. Solving UBI, the easiest part by far is taxing. In fact, we don't need it. any new tax. The government has plenty of tax mechanisms already. The corporate income tax should go through the roof with the abundance coming online. So you're going to have plenty of tax

collection. That's the last thing you need to worry about. What you need to do is actually design a UBI that makes sense. So what would happen here is if you tax tokens, yes, that's perverse because now people use less tokens when they should be using more tokens. They should be trying to build things with AI. So get rid of the, don't worry about that. Worry about the UBI and how we're going to design it. We have plenty of ways to collect money. That's not the issue. Alex.

I'll pick number eight. Will AI eventually solve data centers and chips in a way that we don't need them at all? And this is asked by Dave Lane for. I love this question. I think the answer is probably yes. I think there are so many ways to compute that are allowed by the known laws of physics that I do think it is very likely that we will ultimately transcend semiconductors and seamazons, and by ultimately, I mean on the time scale of a decade, not like

centuries. And I think AI will enable us to do that. I've spoken on the pod in the past about black hole supercomputers on your desktop, about plasma computers. Seth Lloyd wrote about these 25 years ago at this point in the physical limits of computation. I think it is very likely that with advances in physics and AI and AI for physics that will discover breakthrough substrates, that go well beyond just sort of the obvious next steps like photonics to maybe maximally ambitiously computing directly using gravity and or quantum gravity. There's a body of evidence in the physics literature that suggests that in the strong gravitational field regime, gravity becomes turbulent for some generalized sense of

turbulence. There have been a few papers in the literature on this. And turbulence, a separate body of literature, is in some sense touring complete. Someone can imagine a story sometime in the future, not sure when, maybe 10 to 20 years out, where we're literally replacing data centers and chips with pure energy and stress energy tensor and computing with gravity.

I think that's one possible and speaking. I'm glad you answered that one. Computing with gravity. Computing with gravity. Black holes. It's a paper on that. If you look on his site, you can read it. It's pretty nice.

paper and everything. Number seven. Number seven. That's why you can solve everything. Okay, with number seven, with agents costing real money, how can we believe in eight billion, eight billion, I assume humans, or eight billion agents when we can't get eight billion humans free education? And that's from at Keywoon, GPK91. So I think the assumption here is at the current cost, but the price curves are collapsing, right? Token prices have dropped. arguably 75 to 90% in the last 18 months. We talked about that last week at the Jevin's paradox data. Garner has predicted, I think it's like 90% cheaper tokens by 2030.

So a useful AI agent today, you can buy it at 20 bucks a month. We'll end up costing you two bucks a month in 2028 and 20 cents in 2030. And then I think there are going to be a lot of free services offered by the, frontier labs by the hypers. You know, meanwhile, today, the cost of an education is arguably, you know, in the U.S., at least like $10,000 a year. An AI tutor running 24-7 can cost a fraction of that. So I think... You can also personalize to you. Yes. And so I think there's going to be, yes, we're going to have AI agents that you'll pay for if you want the top tier service, and those will be getting cheaper and cheaper. And I think there's going to be a free variation on these

agents for everyone who can't afford it. Sort of universal basic compute. We've talked about that before. All right. We have a outro song, Cathedral Builders brought to us. Have a quick thank you. Oh, yeah, please. Go ahead.

Peter, thank you for the interview you and I did. Like, this, our world is exploding. We have an abundance problem. We've got hundreds of applicants wanting to get into the pilot. So we're trying to figure out how to down select. But super appreciate it. that in re-readed it. Yeah, I know. It was fantastic. If you haven't watched organizational singularity, which is a one-on-one episode that Slema and I did, please do. It's an hour long.

And I hope you guys have enjoyed these kind of shorter episodes. Give us your feedback. We're trying to keep these under 90 minutes. And as a result of that, we're doing it more frequently. So if you haven't subscribed and turned on notifications, please do. We're dropping these episodes now. My travel plans, thank you. Three times a week. Peter, should we ask the audience whether they'd prefer daily moonshots? Oh my God. Yeah, tell us what you want. I keep on saying we're going to move into an Airbnb together.

All right, so this outro music is from jazz, cathedral builders. Again, if you're a creative, please send us your outro. Or if you want it to be an intro song, let us know as well. You can send those to media at deamandis.com. Super excited. So love our community. And thank you guys for putting the time into the... beautiful songs. All right, let's listen up to Cathedral Builders.

Before a breakthrough, it's just a crazy idea. And then, humans living harmoniously with nature like never before. From scarcity, abundance, not be at the whims of today. We are the architects of tomorrow. The visuals are amazing. We are the architects. I love the visuals. The timeline, I think, is way too conservative.

I think you can say that. Did you see the baboon on the skybridge in the future of... We are the architects of tomorrow. The best way to predict the future is create it yourself. This is the most extraordinary time ever to be alive. I love you guys. I love our sessions. I got up at 4.30 this morning recording this on the West Coast at 6.30 in the morning.

So worth it. Can't sleep through the singularity. Yeah. All right, guys. See you very soon. Have a good week. Take care, everybody. If you made it to the end of this episode, which you obviously did,

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