Moonshots: Anthropic Files $965B IPO, Trump Signs AI Executive Order, and ChatGPT Crosses 1B Users | EP #262

Sourced by podcast-ingest on 2026-06-06. Auto-transcribed via AssemblyAI (universal-2, en). Speakers identified by AssemblyAI Speaker Identification using the per-podcast host/regulars hints; the resulting label→name mapping is in the frontmatter. Duration: 2h04m. Episode page: (not provided). Audio: https://traffic.megaphone.fm/DVVTS7698021900.mp3.

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In this episode, the mates discuss the Anthropic IPO filing, Trump signing the AI Executive Order, and more.

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Peter H. Diamandis, MD, is the Founder of XPRIZE, Singularity University, ZeroG, and A360

Emad Mostaque is the founder of Intelligent Internet ( https://www.ii.inc )

Dave Blundin is the founder & GP of Link Ventures

Dr. Alexander Wissner-Gross is a computer scientist and founder of Reified

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*Recorded on June 4th, 2026

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Transcript

Peter Diamandis: Anthropic just confidentially filed IPO paperwork with SEC and could be the first major frontier lab to go public. Polymarket gives it a 60% chance that anthropic surpasses 1.8 trillion in market cap on its first day.

Dave Blundin: Anthropic is only 5,000 people. You're talking about an insane amount of money divided 5,000 ways. This group of companies can do thousands of billion dollar acquisitions.

Imad Ustaq: You've never seen revenue growth like this.

Peter Diamandis: President Trump just signed an executive order that basically says America is not going to slow down on a. This is the US planting its flag and saying we compete, we don't constrain.

Imad Ustaq: I think the US government realized a year or two ago that AI is key to full spectrum dominance.

Peter Diamandis: OpenAI finally passed a billion monthly active users. Nothing in history has scaled this fast.

Imad Ustaq: It's crazy to think you're just at the start, right? Intelligence is going to go to every single person and will be accessible to them. Who is your Jarvis? That is actually the only game in town.

Peter Diamandis: Now that's a moonshot.

Dave Blundin: Ladies and gentlemen.

Peter Diamandis: Welcome everybody to another episode of WTF just happened in tech on the moonshots. I'm here with my Incredible moonshot mates, DB2, the wizard of investment. Hey, buddy, good to see you.

Dave Blundin: Good to see you too.

Peter Diamandis: You got a new. A new shirt on today. I see. What's it say?

Dave Blundin: Every day a new shirt. Thanks to the team here.

Peter Diamandis: Yep.

Dave Blundin: I'm heading off to SF tonight or tomorrow morning too, so I gotta dress the part.

Peter Diamandis: I love it. Awg, Our in house polymath. Alex, I see you're in your normal garb.

Alex: Thank goodness. Good to be back. Normal orchid, totally original environment. It may be real, it may not be, it's unclear.

Peter Diamandis: And a longtime friend and mate, Imad Ustaq, the founder CEO of Intelligent Internet. Imad, thank you for joining us. It's late there in the uk, but hey, you know, sleep is for other people, not for those living through the singularity.

Imad Ustaq: Yes.

Dave Blundin: How many pints into the evening are you, Imad?

Imad Ustaq: A couple. A couple. You know, I have to, with everything that's going on.

Dave Blundin: Yeah. Well, when you see this news. Yep, you'll be glad.

Peter Diamandis: Yeah. And Salim Ismail, of course, is a probability function someplace on the planet Saleem. We miss you. Wherever you might be traveling, come back soon. I'm Peter Diamandis, your host, your abundance amplifier. We've got a loaded show today, some 18 plus stories and some of the biggest developments in AI longevity, the future of work. This is no doom, no Gloom. This is about science, the tech and the money accelerating us towards the singularity. Let me give you a quick preview what we're going to be discussing. Trump just signed an AI executive order that rejects heavy regulation and asked the labs to voluntarily share their models. 30 days before release, ChatGPT finally hit 1 billion monthly active users. Big news. Anthropic filed for its S1 a trillion dollar plus IPO and Bernie Sanders wants a piece of that IPO suggesting that public companies, that the public should own 50% of AI companies through a sovereign wealth fund. Finally, we'll close with three multi billion dollar longevity news stories. You know, gone are the million dollar stories and we're into billions and trillions now. All right, let's jump into our first story here from the White House. President Trump just signed an executive order that basically says America is not going to slow down on AI. No heavy handed regulations, no permission based frameworks. Instead, the order asks AI labs to voluntarily give government access to new models. 30 days before public release. Sam Altman said the new EO gets the balance right. Anthropic said they're on board too. Meanwhile, agencies are being directed to deploy AI powered cyber defense across government systems. This is the US planting its flag and saying we compete, we don't constrain. Alex, do you want to jump in first?

Alex: I think this is sort of a signpost to Canary, if you will, that a lot of previous to now governmental functions such as discovering zero days at scale, which the NSA historically performed, are now de facto privatized and this is downstream of that. So we have the so called Mythos moment, which I think was in no small part inspiration for this executive order that basically took some of the core R and D activities that would have been in the NSA discovering breakthrough cyber vulnerabilities and has commodified them to the point where there's a model mythos and probably GPT 5.5 as well. With Mythos widely reported to be about to be broadly released. And certainly Mythos has become more and more accessible, both now across the EU and certainly within the US to the private sector. And you have to ask the question, just the thought experiment, what's the right way for the executive to respond when there are private sector capabilities with dramatic national security implications? I'll add, parenthetically, cyber vulnerabilities are just what's possible. Now Imagine at some point in the future when there are breakthrough biological, chemical, physical and other discoveries and inventions that come out of private sector models and not out of government laboratories. What is the right policy for the executive to have to protect national security. I think that this is such a delicate balance between, on the one hand, not wanting to throttle American innovation. A 90 day delay could have meant all the difference between US and Chinese models. On the other hand, not being involved enough in the process and not getting pre release review capabilities, however, voluntary or otherwise, could have a profound impact, positive or negative, on national security. So I think, I think the question of does this strike the right balance? I think we'll know probably in the next few months because that's the timescale that this is operating on. But I, I do buy the premise that there was a need for some sort of policy, even if implemented via EO at this point.

Peter Diamandis: You remember it was about three weeks ago, Trump was about to sign it and he had calls from David Sachs, Elon, many of the heads of the lab, saying, you know, this is overreaching, don't do it. He maybe the old order looked more like Europe. Imad, you know, you're kind of in Europe in the uk which has been much more prescriptive, much more prescriptive about their, about their policies. What do you make of this?

Imad Ustaq: Yeah, I mean, I think the US government realized a year or two ago that AI is key to full spectrum dominance. This is the military concept. You have to have superiority across air, land, sea. Intelligence is clearly a vector there as well. And that kind of trumps almost anything because aw said kind of the Mythos moment was a big deal and then it's led to saying, well, we need 30 days at least, which is a very short period of time, particularly with how fast the government actually works. In Europe you don't really have the same impetus because Europe has never had full spectrum dominance. And on the other side on the security, they feel that compliance is the key. So I think it's kind of a mixture of these two. But the US has basically said we're not going to be left behind on AI. And even that 30 days is a massive tactical advantage for us. And we're seeing for the first time an increasing amount of cyber attacks from all sorts of actors. And on the other side there needs to be that battle testing as well. Like the Internet is held together by strings and duct tape effectively. And that's why you're finding vulnerabilities all over the place. And they need it for the security as well as the dominant side. And again, in Europe we just can't move that fast.

Peter Diamandis: I mean, Dave, this is voluntary, right? So I mean the question is purely A political show move to say, hey, yes, we're going to do some regulation, but it's really not. This is, you know, labs can continue business as normal and voluntarily, you know, show the models. What do you think of this?

Dave Blundin: Yeah, exactly. Right. You know, I literally was just on a call right before this podcast with the biggest asset manager in the world and they were asking, how is our AI going to give financial advice without breaking the law? And I said, have you gone and talked to Donald Trump yet? Because what you do is what Sam and Dario did is they said, this regulation is onerous, it's going to slow us down. They met with the White House and then you have a complete watering down of the regulation. And this is fine. We're allowing, because I trust you personally, we're going to allow you to self regulate for the next window of time. Let's meet again in three months. But that's exactly what Lipputan, you know, remember, you know, the White House or Donald posted on X Lipp, Bhutan must go. Intel cannot have him as CEO. He has investments in China. He cannot be the CEO. He went to the White House, had a meeting. Now he's made hundreds of millions of dollars. Kiss the ring, kiss. You must go and talk. But you know, I don't think that is a bad thing in this environment. I think it's as a way to govern a country. In the long, long run, it's not good. But in the moment of time we're in right now, the other regulation would have slowed down progress tremendously. They made the right temporary choice, but it doesn't solve anything in the long run. But that's okay. I mean, it's, it's fine for now.

Peter Diamandis: We'll see how this plays out. Meantime, OpenAI finally passed a billion monthly active users. You know, let that number land for a moment. ChatGPT launched in November 2022. Roughly three years later, it's used by over a billion people. Context, it took YouTube a decade to get to a billion. Instagram eight years. TikTok five years. And now we have ChatGPT there in three. Nothing in history has scaled this fast. Year over year, growth is at 62% and holding for OpenAI. Here's the kicker. Claude Anthropic's model is now at 56 million monthly active users and is growing at 10 times the rate, 640% year on year. This entire category is going nuts, Imad. I mean, you're playing in this, you're building models. I mean, do you expect growth like this to continue?

Imad Ustaq: It's crazy to think you're just at the start.

Peter Diamandis: Right.

Imad Ustaq: Like, the Claude thing is what surprises people a lot because Claud is a bit like Apple and OpenAI is a bit like Microsoft here. And then there is the 7 billion people that don't use it. Of course, it's difficult to use in China because you can't even have access to these models. Yeah. But obviously intelligence is going to go to every single person and will be accessible to them. And Sam Altman has said the price of equivalent intelligence will drop by 100 times over the next 18 months. And I think when you look at all the chips and everything, that's correct as well. So even though you've hit a billion faster than anything, I think that 62% will actually increase, especially because I think the next wave, as they hit their IPOs and things like that, will actually be customer acquisition. This happened without massive advertising campaigns, without classical cost of user acquisition metrics. Almost all of this was effectively organic. You see the odd ad, but they've just become recent. Right. And so I think there's a long way to go from here.

Peter Diamandis: Yeah.

Alex: Alex, you remember when Sam said that if he had a choice between a billion monthly active users and the strongest model, he'd pick the billion monthly active users. That's the future.

Dave Blundin: Did he say that?

Alex: He did say that.

Dave Blundin: Really?

Alex: He did say that.

Dave Blundin: What a memory. Wow.

Alex: Because he. He thinks, he thought at the time, or at least what he conveyed was that in this game between the Frontier Labs distribution ultimately was a stronger mode, a stronger advantage and differentiation than having the strongest model weights. And ironically, for. For a hot moment, at least until GPT 5.5, that was basically the world that we found ourselves in, where GPT and OpenAI had the majority, or at least the largest user base, but also not the strongest model. Now, fortunately, thanks to that code red, GPT 5.5 is broadly, as far as I can tell, the strongest model. And also he has the broadest distribution pipe.

Peter Diamandis: Amazing comeback. Amazing comeback.

Alex: It's a good day for OpenAI. They have the distribution, the best distribution and the strongest model.

Dave Blundin: Yeah, well, pretty soon we'll have public market caps to compare to each other, so we don't have to debate who's ahead. We can just look at the stock price and then we'll know a trillion

Peter Diamandis: here, a trillion there. You know, I mean, the most amazing thing is there will be some product somewhere that grows faster than ChatGPT. Don't know what it is, when it's going to hit, but we're going to, we're going to have that happen. It'll probably be a product that is distributed through agents around the world.

Alex: How soon Peter, until we're measuring the time to first billion agents using you and not the first humans.

Peter Diamandis: I agree, I completely agree with that.

Imad Ustaq: Well, I think this is the big strategic thing because I think what everyone's going to realize in the next phase is the most important agent is the agent that's next to you that's coordinating all the other agents. And that's why the cost of users acquisition is going to go and shoot through the roof because everyone will want that agent. Is it your super app from ChatGPT or is it your Claude? Or is it your Jarvis?

Peter Diamandis: You're Jarvis, right?

Imad Ustaq: Who is your Jarvis? That is actually the only game in town.

Peter Diamandis: Agreed. Sticking with OpenAI, they just launched something called Rosalind Biodefense, named after Rosalind Franklin, a British chemist who helped discover the structure of the double helix. Rosalind Biodefense gives trusted researchers and government public health agencies access to specialized AI tools for detecting outbreaks, improving disease surveillance and accelerating vaccine development. Richard Johnson, OpenAI's National Security Risk mitigation lead is running it. This is AI's move from chatbots to biosecurity infrastructure. And I think politically this is the kind of moves they have to make. This and healthcare and education really to give themselves defense against people, slowing them down. Alex, what do you make of this one?

Alex: I'll paint a story about the elephant in this particular room, which is that I think we're starting to see for the first time the generality of AGI start to shrink. I think we're seeing it for security reasons and security rationales that are probably legitimate. But nonetheless the G in AGI is starting to shrink. We're seeing bio capabilities that would otherwise be built into general models like the GPT series that start to get carved out as separate fine tuned post trained models that are only available to exclusive audiences like government agencies and trusted researchers. We're seeing the same thing happen with the cyber version of mythos from OpenAI, the GPT Cyber series. And I think this is probably going to end up being the tip of an iceberg where advanced capabilities that could have security implications at least to start, maybe other regulatory implications soon aren't built into or at least not exposed from the main series model that is available to the general public, but rather get carved out into more secure, more limited models that are only available to government agencies and trusted users. And part of me wonders is this sort of in the same sense that you would back in the day hear Richard Stallman or other evangelists from the open source movement complain about the closing off of openness in source code, in computing in general, and the generality of say, personal computing. It seems to me like we're starting to see again for admittedly well founded security rationales, we're starting to see the beginnings of the closing off of generality of intelligence in the name of security.

Peter Diamandis: I mean, we know the fact that the same technology that enables OpenAI to deliver this for biodefense is the same technology that terrorists can use to develop new, you know, viruses for biowarfare. And I mean, that's the scary part, you know. Dave, are you thinking about this at all?

Dave Blundin: You know, I'm curious Alex and Ahmad, do you know, you can never start a question to Alex with do you know? Because the answer is going to be like, no, it's got to be yes. But, but do you know, did they, did they de guardrail the existing Mythos model for this? Or did they train a new set of parameters that are specific to biology and deliver it to the government for this or is it distilled?

Alex: Well, this is OpenAI, not anthropic, but my understanding for, for both the Rosalind series and also for the cyber vulnerability series that OpenAI also released, my understanding guess is combination of scaffolding, unshackling and probably also a bit of post training and use of tools that otherwise wouldn't necessarily be baked in at the back end. So the default tools for ChatGPT are usually code interpreter and web search. I think when Rosalind was first announced, they announced that there were a number of other databases and tools that would also be built in. If I were OpenAI and trying to make this useful for biodefense, I would also probably include an unshackling at the scaffolding layer saying you are in fact allowed to ask questions about smallpox and about a variety of other subjects that probably would just be completely guardrailed out for the general public.

Peter Diamandis: Imad, you and I have spent time talking about this in terms of serving sovereigns with AI. You know, I'm glad OpenAI is doing this. I think all the labs need to be helping us defend. We're going to talk about that in the next story as well. Any, any closing thoughts on this one?

Imad Ustaq: Yeah, 2020, 2021. I remember launching at Stanford High AI Initiative to organize Covid knowledge and preparedness around that and we had a lot of big labs promise a lot of AI and none of them would give it because they said it was too dangerous at the time. Which is why I actually got into open source. That was a very painful process. I think, you know, Dave was asking the right question. This is an unshackled, grounded version that can really analyze knowledge at scale. And we see similar things with the science harnesses now from Google and others because base models are a lot more creative. But then on the other side for preparedness, they can't analyze huge amounts of knowledge and data like so detecting outbreaks, improving resilience, etc. The reality is that we're probably going to see more of these from threat actors as well as just timeliness on pandemics. Like next big one is probably only a few years away. Honestly, when you look at a lot of different things and hopefully this time we'll have our act together because if we don't, then I think it could be even worse than it was before.

Peter Diamandis: I mean this is probably what the AI labs should be investing in to befriend the public because the public needs a reason to be supportive. All right, our next story related here is a serious one and it should be. Today I had the pleasure to co sign alongside Sam Altman and Dario and Demis and Mustafa an open letter to Congress saying we need laws requiring DNA synthesis companies to screen their orders. So today you can go online and order custom synthetic DNA sequences. Dozens of companies will print whatever code you send them. Most screen their customers, but a lot of them do not. And here's the scary part. As an example, back in 2017, a Canadian researcher spent about $100,000 of mail ordered, you know, to get mail ordered DNA and reconstructed an extinct horsepox virus. The same method could theoretically be used to create smallpox. You can layer on, on top of that large language models and you can do a lot of damage. A dear friend of mine, Olivia Scharfman at the Institute for Progress and the foundation of American Innovation, put this forward. As a result of this, there's a bipartisan Senate bill already in play. This is one of those rare moments where the industry is saying, please regulate us. You know, this, we talked about this with Eric Schmidt, Dave, that you know, there will be at some point some kind of a small, you know, you know, global emergency as a result of AI that will get everybody, you know, to pay attention is, you know, and, and this sort of bioterrorism is probably top of the list. Any thoughts?

Dave Blundin: Peter, I don't, I don't want to throw this all on your shoulders. Or anything. But of the people who signed this, most of them are running big AI labs and have a personal agenda, and then they have IPOs coming up. You're the one signer who totally understands this issue inside and out and isn't conflicted in some way, but it makes complete sense.

Peter Diamandis: I mean, why would you not want to do this? It's like.

Dave Blundin: No, no. Yeah. I'm not saying that. I'm saying this is the. There's so much more work that needs to be done here.

Peter Diamandis: Yes.

Dave Blundin: And between you and xprize, that's probably the best agency to save the world from biological disaster, so. Well, thank you for signing it.

Peter Diamandis: You're welcome. I mean, right now, there is a future in which sensors in train stations, airports, bus stations, in malls, is constantly sequencing everything through the air filtration system and looking for novel sequences. And if it detects sequences, it. And sends it to the cdc, and then we start a vaccine program instantly. I mean, it is possible. The thing people need to realize is that viruses, pandemics, can only move at the speed of airplanes, but information can move at the speed of light. So you can sort of stop this in the bud if you're. If you're fast enough and you have enough intelligence. Alex, you and I have discussed this a few times.

Alex: Yeah. I think this is probably both inevitable and inadequate at the same time. I think it's also part of a broader set of initiatives to gatekeep the interaction between superintelligence and the physical world. I want to draw a split screen. On the left hand, we're talking about gatekeeping, DNA synthesis. On the right hand, 3D printing. So state of California and other municipalities are trying to regulate what can be 3D printed, again out of concern that people will 3D print weapons, guns in particular. I think there is a lively debate that has started to happen about whether the right way, the right choke point, if you will, for AI safety, is sort of after the fact, after something has happened, do you hold the labs or the users responsible for it? Or is the right to choke point at the time of action when an intelligence, either at the behest of a human user or autonomously tries to do something in the physical world via DNA synthesis or protein synthesis, or printing a weapon with a 3D printer? Or is the right time to regulate it at the time of conception when either or all three or. Or all of them, the entire end to end? And I think my guess is different countries will choose different combinations and permutations of each stage of that thought to action? Pipeline and I'm not sure that there is a right answer, but I do think that some combination, some permutation of being able to at least, even though it probably will enable regulatory capture of the DNA and protein and biological sequence synthesis step by Frontier Labs that will then obviously insist. Well, it's. You have to use Rosalind, you have to use our model to determine whether the sequence is dangerous. You can't just rely on naive pattern matching or worse yet, just naive base pair matching that can easily be routed around some amount of intelligence forward deployed to the time of synthesis with Frontier Intelligence, I think is probably inevitable, at

Peter Diamandis: least in the US we have previous examples of this where the treasury required photocopy machines.

Alex: Yellow dots.

Peter Diamandis: Yes. To prevent being able to photocopy the $100 bill or any kind of money. And so there are companies like Twist Biosciences which already screen, you know, what they're synthesizing and they've been lobbying for this for a while. But the screening costs money and if only responsible players do it, then they've competitively disadvantaged themselves in doing the work. So this need, this does need legislation, this does need pressure and it makes no sense to not have this in place.

Dave Blundin: Totally right. And I also don't think it's super hard to capture at the point of prompt and reasoning trace. If somebody's trying to build a bioweapon or a chemical weapon or a nuclear weapon, you have to have a lot of interaction with the AI and it's not super hard for the AI to say I need this reasoning trace to be captured and turned over. There has to be some inspection.

Peter Diamandis: What if it's on your Mac studio?

Dave Blundin: You can't really do it on your Mac studio and if you could, we would have to ban that globally anyway, which I hate. I don't like that. But I don't see any other outcome.

Peter Diamandis: Imad, could you do this on a LLM on your machine? On premise you can.

Imad Ustaq: So I was one of the authors on Openfold, the open source version of AlphaFold, and supported a range of things in this. You can basically run the prompts on edge, adapting existing models or using some of the new ESM and other models that have actually been open sourced. It's very difficult to stop that. You need to be smart and you need to understand it, but the threat vector doesn't come there, which is why you need to look at this side of things. And again, this is a really good step on the direction and the synthesis. I think actually this goes to a bigger thing which is the total percentage of tokens in the world used by the public sector is probably 0.01%. Total world GDP, public sector is 20%. We have to use intelligence for public good. And one of those public goods is the government should be subsidizing or paying for the tokens to analyze every single sequence being put into a sequencer, for example. And so that's a bit of a phase shift because don't think that way. But I think these types of things where intelligence is causing threats or opportunities to go up, we need to ramp public sector compute to help mitigate and take advantage of those.

Dave Blundin: And that's a great basis for an xprize. Just, hey, let's have all the ideas related to the way the government can use that 20% to put together AI processes that stop specific threats at specific points. Let's list them all out as X prize opportunities and then throw that out for the world to think about and a model come back with 50 of them right out of the gate and those all become X prizes.

Alex: I would add that there's an enormous hole in this, which is directed evolution of environmental DNA that's already out there in the biosphere. And if we really want to take this seriously, the risk of either non AI enhanced bioweapons or AI enhanced bioweapons, if we think like that's the X risk scenario that we care the most about, we really are going to have to sequence environmental DNA from everywhere, not just the biosphere, but all environmental DNA everywhere and there.

Peter Diamandis: And as a baseline. As a baseline to see deviations from norm. Absolutely.

Alex: Yeah.

Imad Ustaq: Actually, I think no one's actually articulated that properly. You don't want to give people ideas. This is always a thing. But I think that should be a really directed paper where you model it. Because once you actually model it, it gets scary really, really quickly and you have to start putting it in place now.

Dave Blundin: Yes, yes. Yeah, that, that one. Like a lot of, you know what Alex was saying earlier, you can wait and figure it out after there's a disaster and then work back, but this one, you can't. You cannot afford a global pandemic that could be so much worse than Covid and then try and work on the problem. You can't do it that way.

Peter Diamandis: I mean, listen, we all know this is a very serious risk and it's been mentioned so many times as perhaps the most likely risk and why we're not investing heavily in this yet. You know, I think every politician listening to the show needs to be putting this forward you want to get the public on your side, do this because you're going to be a hero when it eventually happens.

Dave Blundin: Peter, that's why I was coming back to you as the, the one signer on that document who has a Ph.D. in biology, who also understands inside, you know, AI inside and out. And everyone else is Busy with their IPOs right now.

Peter Diamandis: So with their trillion dollar IPOs to say clearly, 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 had to say, what we think is most important and what we're most excited about. And it's free. You can subscribe@diamandis.com metatrends that's Diamandis.com metatrens All right, now back to the episode. This next story is fun. OpenAI Robotics is hiring. So Sam Altman posted it. Plainly we are focused on robots to support skilled workers to build our future infrastructure, and imagining everyone having a personal robot doing anything they need. I find it fascinating that Sam is sort of like following lockstep with all the things that Elon's doing. A few, you know, episodes ago, we talked about SAM potentially investing in rocket companies. So OpenAI is hiring for robotics. Not a research paper, not a partnership. This is building an in house robotics team. It's a signal about where the frontier labs are heading next. You know, Anthropic is the one lab that's really focused. Alex, are you excited about this?

Alex: Well, it is the innermost loop, right? The robots that build the data centers and the fabs that build the chips that host the models that are powered by the energy that hosts the AI

Peter Diamandis: and then doing it all on the moon in Earth orbit.

Alex: That's right, disassembling the moon to build an SSO Dyson swarm. Exactly. So yes, of course I'm excited about it. I think it's instructive. On the other hand, that Stargate, Sam's signature initiative to go build the data centers within OpenAI, has shifted in the direction of leasing rather than building. And so when I see Sam and OpenAI announcing that they're focusing on robots to build their future infrastructure, makes me start to think that either Sam is going to go ahead and spin up an independent of OpenAI data center infra initiative, or that maybe OpenAI is seeking to revive Stargate's futures from a robotics angle that maybe it'll be OpenAI robots helping to build or maintain data center facilities that aren't owned by Stargate, but rather that are maintained by third parties. But either way, I think the arrow of progress is clear both from Sam and from Elon and from everyone else that the most productive right now use of humanoid robots is probably just to build out the Dyson swarm in orbit and to tile the earth with compute here on land. And then we all can get our domestic robots as a secondary afterthought. Even though I'd really rather get mine first.

Peter Diamandis: You know, another thing we've talked about in the past is that humanoid robots interacting in the real world are going to be an important source of data. Everybody's talking about. Where do I get new data? Well, this is definitely one of them. Imad, any thoughts on this story?

Imad Ustaq: Yeah, so it's interesting. Remember SORA shut down, right?

Dave Blundin: Yes.

Imad Ustaq: And I was like, why? When GPT image was coming out. So Aditya Ramesh, who led the SORA team, is leading the robotics team. So they've taken all their video researchers and moved them onto the Embodies robotics team. And when you look at robotics, I did a whole bunch of work recently. I think I've got a paper coming out soon. It is far bigger than the GPU market, like actual physical embodied robots. And they will not have the same depreciation schedule either. And I think people are coming wise to this because GPUs depreciate really fast.

Peter Diamandis: I think we've seen GPU prices going up, used GPUs going up recently.

Imad Ustaq: Yeah, they go up, but they still depreciate in terms of that. But you look at the unitary G1 2 years ago compared to being on America's Got Talent now, now, you know, dancing. Once you get the robotics to a certain level, those things will have a massively long life and they'll be incredibly profitable, especially when you go full stack. And I think again, this is why OpenAI realizing that like they've got their GPU build out and maybe that'll continue, maybe it won't. But the market for robots is way bigger than that. They will tile the earth, they'll build your extensions or pyramids or you know, go across the universe. And again, I think it's interesting that their video team is now fully on robotics. They decided and made the choice we have to move that talent over there.

Peter Diamandis: Dave, you've started to invest in robotics, haven't you?

Dave Blundin: Yeah, I think Sam and I are on the same page on the fact that this is a very, very good 10 year investment theme and that the battle for self improving software is well underway. So if you're maybe 16, 17 years old and you're thinking about what you're going to do post AGI, you know, working toward getting this job with Sam is a very, very good next move. You know, what do I have to do, what degree do I have to get, what, who do I have to beg to get this job? Because once you're in that group, you look at what happened with all the software people that were original OpenAI people and they're thriving, you know, at five different companies now. And they're all billionaires.

Peter Diamandis: Yeah.

Dave Blundin: So the robotics version of that is just starting and you can get in early if you pivot in this direction. Also, I think that Sam was early to recognize that whoever controls compute, controls everything. And robotic construction of data centers is one part of that strategy. One linchpin, you know, also the custom chips. Remember he cut that deal to design AI specific chips. Haven't heard much about it, but that's in the works too. So that's the whole thing. Alex was describing the self improving loop. That includes the hardware construction.

Peter Diamandis: All right, big news this week. Anthropic just confidentially filed IPO paperwork with SEC and could be the first major frontier lab to go public, beating OpenAI to the punch we've talked about in the pod before. You know, with SpaceX coming out at one point, I think it's 77 trillion is the price right now. We'll be seeing it very shortly, you know, soaking up a huge amount of the capital out there in the world. Is there enough for two additional trillion dollar IPOs? Polymarket gives it a 60% chance that Anthropic surpasses 1.8 trillion in market cap on its first day. 1.8 trillion. Just fascinating. That same price of SpaceX, its anticipated IPO. We've entered really rarefied territories here, Dave. I mean, are we just getting numb to a trillion dollar IPOs? Is this going to be just the expected? Like hey, when's your trillion dollar IPO happening?

Dave Blundin: Well, people are numb and they shouldn't be, they should, they should be situationally aware and, and recognize that this flow of money is the biggest in the history of the world by an order of magnitude or more and that they should try to be involved in it. You know, these labs like anthropic is only 5,000 people. You know, you're talking about crazy Insane amount of money divided 5,000 ways. They're going to want a whole ecosystem of other companies to be helping them build, deploy, create. They'll have massive amounts of capital to invest in that. I mentioned on one of the prior podcasts. This group of companies can do thousands of billion dollar acquisitions.

Peter Diamandis: Yes, it's dry powder.

Dave Blundin: It's dry powder, yes, like we've never seen before. So don't get numb, unnumb yourself and recognize the amount of opportunity that's suddenly available to you. You know, be part of it.

Peter Diamandis: It's a good thing for them to go public, right? They, you know, Anthropic is thought to be the safety conscious AI company and as a result of that, you know, being, you know, a public company forces them to have enough disclosure. So I think that's a good thing for them. Imad or Alex, any thoughts here?

Alex: Should I sing the Magna Mopsta song again?

Peter Diamandis: I'm sure you do it beautifully, my friend.

Alex: Thank you. I think it's so essential that we get all of the Magna Mopsta companies and not just eight of them to ipo. I could maybe quibble as to whether Anthropic really is the first frontier lab to go public or whether SpaceX AI is technically a frontier lab. Certainly I think Elon fashioned SpaceX as a frontier lab at this point, but I think it is a public good that they're ipoing and it's a public bad that it has taken this long for retail investors to have access to equity in the Magna Mopsta companies. And I certainly hope and will do what I can to ensure that this is the last time in at least foreseeable history when we see so much private wealth accumulation happening outside of the public markets. I will do what I can to help make public markets the place that private startups think of first and not last as an aspiration to be.

Peter Diamandis: Imad, you're building an incredible company with intelligent Internet. You've been raising capital, you've been building, you know, breakthroughs that you can't discuss here that I know of. How does this kind of, you know, price, you know, hyperflation hit you in your efforts to raise capital?

Imad Ustaq: I mean, it's positive. Like, the amount of money in AI is insane, which is why you're seeing these crazy raises. But at the same time, they're not crazy because you've never seen revenue growth like this, you know, like, what is Anthropic? Right now, Anthropic's revenue is probably 60 billion. 50 billion. 60 billion. So it's coming at 20 times revenue, which is high, but it isn't a palantir. You know, it's like it used to be 50 times this. These things are kind of making it up. And you wouldn't be surprised to anyone if you saw 100 billion revenue or 150 billion revenue for anthropic next year because it's just that useful. This is the reality. When you build useful things, the market gives you the value. And I think that the trillion dollars, as you said, it's just going to come back because it's a wealth creation event. You feel oddly bad for Sam Bankman Fried, actually one of the greatest investors of all time. If you look back at the Anthropic series of E where he put $500 million, all those people that bought those shares will be reinvesting straight into generative AI.

Peter Diamandis: Yeah, we're making so many billionaires in Silicon Valley for sure.

Imad Ustaq: And outside of that, everyone else is coming in as well. So it's not like to your first point, is there going to be a lack of demand? No, this will be oversubscribed. SpaceX will be oversubscribed. And I think there's probably a trillion dollars of money that wants generative AI access. And AWG is going to do as best he can to make that possible. But we're not going to run out.

Peter Diamandis: You know, this, this gives support to when Elon said triple digit GDP growth by 2030, setting aside GDP as a metric. All right, our next story here is how fast are companies achieving a trillion dollar valuation to the point we just made? Apple took 42 years to reach a trillion dollars. Google 21 years, SpaceX 24 years. OpenAI about 10. And anthropic now roughly in five. But the real story here isn't, you know, how fast they're reaching trillion dollars, it's how many employees they're using to reach that level of evaluation. So anthropic generates about $9.4 million in revenue per employee. 9.4. Almost 10 million per employee on about 5,000 people. Apple is about a quarter of that 2.5 million per employee. And, and Google's at 2.1 million. So these companies are not just growing faster, they're extracting more value per person. 4 times the rate of the best tech companies. You know, this is Saleem's exponential organization thesis playing out in real time. Impressive numbers. And something will beat this. Something soon will beat this.

Alex: Peter, dare me to estimate when, since we had this discussion, I dare you.

Imad Ustaq: 6 to 12.

Alex: Months ago when we'd see the first one person unicorn, and we achieved that. Dare me to estimate when we're going to see the first one person center corn or terracorn.

Peter Diamandis: Okay, I dare you. Alex, what is it?

Alex: Sometime in the next 10 years.

Peter Diamandis: Okay. I think that's an easy, easy estimate. I would join you in that bet.

Alex: Yeah.

Peter Diamandis: All right. I mean, I just think the, you know, revenue per person is extraordinary. And, you know, the question, of course is do we start measuring this as revenue per agent soon enough?

Dave Blundin: Interesting. Or.

Alex: I mean, I think the, the, the issue with revenue per agent is agents right now feel like really discrete entities. Just like as we've discussed on the POD in the past, taxing per token, but really, ultimately there are scenarios where the boundaries between quote, unquote agents start to vanish. Where we see, for example, end to end differentiable teams of agents. And we start to ask the question, is it really multiple agents or is it really a single team level agent? Not obvious to me that the agent paradigm survives long enough into the future that will be asking revenue per agent.

Dave Blundin: I think the other really important aspect of this is that the AI economy is now funded to live within itself. Because historically, if I talked to bankers a year ago, or car dealers a year ago, they would say, look, anthropic and OpenAI can't become really big companies until they've delivered something to me as a bank and I'm paying them because the iPhone didn't become big until a billion people used it. And all this legacy stuff wasn't big until it interacted with me in the old world economy. It doesn't actually have to be that way with AI. If Dario wakes up after his IPO and says, I want to spend $100 billion with you, Peter, to solve these 10 diseases, he can just spend it and you can spend it right into the agent economy. And now your agent economy has $100 billion of cash flow. And it had nothing to do with J.P. morgan, it had nothing to do with Main street, it had nothing to do with any legacy business. So this conduit of capital through these IPOs back into the pure AI world, it could entirely build an economy of its own. And you might not even notice it in, in Europe, you'd be like, what happened today?

Peter Diamandis: We're seeing the ceiling here rise, right as these numbers are again going into multiple trillions. How does it feel at the, at the bottom rung? You know, when you're coming in as pre. Seed, seed investors into these companies and they're escalating Is it moving the valuations climbing faster than ever before?

Dave Blundin: Yeah, it's crazy. Like, the seed stage birthday valuations of the companies are about where they were because the founders don't care about maximizing valuation on that day. They care about being in the perfect ecosystem to get on this wagon. But then the escalation, the timelines are so short and the escalations are so big. I've never seen anything like it. So multiple companies here in our incubator went from idea to billion dollar valuation in a couple years, but one of them is on a trajectory to get there in less than a year. And like, I've never seen that. Well, the reason I've never seen it is because it never existed in the world prior to AI. And I think it's here to stay. I don't think this is like a bubble or a flash in the pan. I think that you can get so much more done so much more quickly than ever before that it's here to stay. Which is why we continually show these numbers to people. You're crazy to do anything other than be an entrepreneur. And then you get all the pushback in the podcast notes, but, but the numbers are just overwhelming.

Peter Diamandis: Yeah, we talked last time that the number of solopreneurs has doubled in the last quarter. And you know, during our Google IO podcast, we talked about the build with Gemini Xprize, the $2 million hackathon that we launched. And we now have 11,000 people who've entered that hackathon. So just as a reminder, if you're on, on the sidelines, you've got an idea, something you've always wanted to create as a company, go to gemini xprize.com, register for this competition, Allow us to support you in building something that helps the world and jump into the entrepreneurial fold. I mean, if you think you can't, or you think you can, you're probably right. So let's give it a shot. All right, here's some interesting news. We haven't heard about Microsoft in some time. We haven't discussed Microsoft on this pod in a good, good six weeks. But they've just come back into the scene in a big way. Microsoft just dropped seven in house AI models at their build 2026, spanning reasoning, coding, image generation, video and transcription. And here's the thing that should make every AI lab nervous. They've built all of these in house, from scratch. No distillation of OpenAI, no reliance anyone else's weights. Friends of the pod, friend of the pod. Mustafa Suleiman, who runs Microsoft AI put it bluntly, AI training compute has increased 1 trillion fold with another thousand X coming in the next three years. Pretty extraordinary these models already being tuned for Microsoft 365 with their tuned model for Excel matching GPT 5.4 while being 10 times more efficient. They've also announced a collaboration with Mayo Clinic to co create a Frontier AI model for healthcare. You know guys, my interpretation here is Microsoft is saying we're not just a distribution layer for OpenAI anymore, we're building the whole stack. Alex, over to you on this. Your thoughts? Are they here? Are they in the game again?

Alex: No, they're not in the game. That's the bottom line up front. And not only that, Mustafa previewed this position for us when we interviewed him at Microsoft hq. He foreshadowed it. For those who want to go back and rewatch that I thought really fun interview. He foreshadowed the Microsoft OpenAI divorce. Microsoft recall before OpenAI was working on all of its own foundation models that wasn't moving very quickly. And Microsoft I thought very strategically entered into this relationship with OpenAI and got a boost, became the distribution partner, got the channel. And granted this relationship was formed over a period of time so it wasn't as if OpenAI launched their foundation models and then Microsoft invested. Exactly the opposite was the chronology. But Microsoft really started piling on the capital once it became obvious that OpenAI was onto a solution for general intelligence and Microsoft for better or for worse was in a position where they didn't have enough compute maybe talent as well outside of the OpenAI relationship to build their own in house first party models. Which is a pretty perverse if you think about the history of Microsoft and what Microsoft did to IBM back in the day that that was like the same history Rhyming now with OpenAI playing the role of Microsoft to Microsoft's IBM basically running away with with the next wave. Sort of amazing that Microsoft.

Peter Diamandis: That's a great analogy buddy.

Alex: Allowed, allowed that to happen to it. So now Microsoft is trying to recover from the open quasi divorce and develop its own in house models. But it's still relatively compute starved and relatively talent starved. I've looked at all of the models that it launched and I really want more hyperscalers and more frontier labs. We need more competition but Microsoft isn't there yet. These are mid tier models that are at best competitive with models that Anthropic and OpenAI were launching months ago, not current models.

Peter Diamandis: Imad, you agree?

Imad Ustaq: Yeah, I think you don't need AGI to make a PowerPoint.

Peter Diamandis: Right.

Dave Blundin: And

Alex: what if it's a really good PowerPoint?

Imad Ustaq: There's no such thing. No such thing. I hate PowerPoint. Again, it's a very different intention. I think history would have been very different if Sam and co had joined Microsoft during the coup. That was a big kind of difference.

Peter Diamandis: That was almost a maybe.

Dave Blundin: Yeah, yeah, that's true. What a different world.

Imad Ustaq: Because it's a very different environment when you're heading towards AGI versus not. And Microsoft had a lot of issues like the WizardLM team was fantastic and they went to Tencent because they couldn't actually build towards AGI. And then Tencent built one of the best open source models. Where Microsoft is right now is they're at the level of a Chinese lab, a good Chinese lab. And I don't think they're going to go that much further because you get to a certain point now with AGI where it's a generalist model of different types, but now they're going to hyper specialize because they need to serve 400 million teams, users or whatever, poor guys. Whereas you're seeing the closed models and Methos and things like that. They're never going to see the light of day from the big labs I think. And so the big labs are going straight to AGI whereas Microsoft have gone up like that. But they're not going to thousand times the compute that they spend on training a model because that will then require a thousand times the inference costs. And if you look at their Maya chip, which these models probably partially trained on and they can also inference on those aren't designed for large scale massive MOE type models either. I think that it's again humanist office based intelligence as opposed to general super intelligence.

Peter Diamandis: So are they they supporting sort of the older generation of entrepreneurs and CEOs if you remember Microsoft, I mean a 50 year old company was the most valuable company in the world for a pretty long run. I mean they did extraordinary. Nobody lasts that long at the top. Dave, any thoughts here?

Dave Blundin: Well, to me it's a really cool historical case study and it's a battle of people, not companies. And when Alex described it by saying I can't believe this is happening to Microsoft given what Microsoft used to be. But if you said Bill Gates instead of Microsoft, Bill Gates would not lose. He would do whatever it takes to win. And here Mark Zuckerberg decided what it takes to win is to offer Mark Chen a billion dollar comp package and come over from OpenAI and he turned it down. Can Microsoft offer Merck Chen, a billion dollar comp package like, are you kidding me? How now, if Bill Gates were there, he would find a way. But it's the difference between it's a battle of people. It's not a battle of corporate brands. And nobody has positioning. Even Apple, nobody has positioning. That's a moat. That's purely defensible. You just have to have the will to win and do what's necessary to win. And it just feels like for whatever reason, Microsoft is not doing what it takes to get the 5 or 10. Cannot miss great AI researchers to work with Mustafa to build a true frontier model.

Peter Diamandis: Companies have momentum and Microsoft does not. And anthropic most definitely does. Welcome to the health section of Moonshots brought to you by Fountain Life. You know, my mission is to help you use the latest technologies, including AI, to not just do your work at home, teach your kids, but to help you live a long and healthy life. I'm here today with an extraordinary physician. The chief medical officer of fountain life, Dr. Don Musailam. Dawn, let's talk about cancer. You know, I know from the member database that we have at Fountain are members who come in who think they're healthy. It turns out 3.3% of them have a cancer in their body they don't know about.

Dr. Don Musailam: That's right. You know, the majority of cancers that we screen for, those aren't the ones that are necessarily taking the lives when found at a late stage. We know that when cancer is found early, the chances for cure are much higher. We know it's much easier to treat a cancer when found early versus when found late. What we're finding in our members is over 3.3% were found to have these cancers that were otherwise wouldn't have been found or detected.

Alex: Yeah.

Peter Diamandis: You know, it's interesting, people, you don't feel the cancer until stage three or stage four. And if you don't know what's going on inside your body, it's like driving your car with your eyes closed. And you can know. And so when members come through found, how do they detect cancers?

Dr. Don Musailam: So we're doing full body mri and we also do early cancer detection screening. This is very, very important. And these are not typical tools used in the conventional care setting when it comes to prevention. This is a hard thing because currently these are not studies that insurance would yet be covering. But the goal is to colle these numbers, do the research, and work hard to democratize wellness.

Peter Diamandis: Yeah. So at the end of the day, you can know what's going on Inside your body. It's your obligation to know. So check out Fountain Life. You can go to fountainlife.com peter to get access to the latest technology to help you detect cancer at the very beginning, at stage one, when it is curable, before it gets to stage three or stage four, and you're a world of hurt. All right, this next story pisses me off. Uh, so this is out of the New York Times. Uh, you know, New York Times ran a piece analyzing 602 goals that Elon stated publicly 15 years ago. Their headline, he only met 19% of them. You know, I. I would bleep my own words out towards you, New York Times. I mean, who in the New York Times is setting any audacious goals and doing anything worthwhile? You know, the framing misses the point entirely. In 2015, he hit 75% of his goals on time. The ones he missed. Well, he's still building Tesla, the most valuable car company on the planet. SpaceX is the dominant launch provider by a huge margin. Neuralink is working on BCI and its Inhumans. XAI is a frontier lab and a hyperscaler. The man is worth trillions of dollars. I mean, who on this planet has set any audacious goals like this and actually met, you know, okay, 19%. But he will hit all of them. I'm clear. You know, he's always directionally right. His timing may be off a little bit. Anybody want to disagree with me?

Dave Blundin: I'm not shocked by a long shot. Shocked.

Alex: Shocked that the paper of record is launching apparently an ideologically motivated attack against the greatest technologist of our. Shocked.

Peter Diamandis: Well, I don't read the New York Times anyway. You know, you could not pay me enough money to read what the editor wants to put into my neocortex.

Alex: I. I linked to this in my daily newsletter, and I excerpted the only statistic that I thought was interesting, which was hitting the 75% of goals for 2015. I think anything else is. Is really underselling everything that Elon has accomplished and is accomplishing. And for. For those who will preemptively say, oh, no, like, I'm. I'm fawning, I'm kissing the ring, or whatever the cliche line is. That's not what I'm saying. He has accomplished nothing short of miracles in multiple sectors. And to a hit piece that focuses on which promises aren't on time completely misses the point.

Peter Diamandis: I love it when starship launches. And it does miraculous things on one of its earliest flights, right? It's always a test. Flight and the headlines is Starship explodes and fails. It's like you got the point wrong, for God's sakes.

Imad Ustaq: Yeah, I like to think of it in terms of VC1 for you, Dave. About 10% of companies return, 90% of all returns. You can't do what Elon did unless you actually have this distribution. And it's actually stonkingly high. It actually goes to what we were just talking about, Microsoft. The culture in Microsoft is not to take chances. So you're never going to have breakthroughs, are you? You will just repeat what's happening. Whereas the biggest, best breakthrough is when people actually take a chance on model training or trying different things.

Dave Blundin: You know the most misleading thing about this article? The whole thing is misleading, but the most misleading thing is it implies that somehow investors aren't happy with their investments in Elon. And you go and talk to Antonio, Gracias. And he's like, Elon could invent a new urinal and I would put a billion dol. Everything he does works. And so it's just. It's just cringy to have them peel out like a couple edge cases, which even the edge cases are not bad. So. Yeah. Anyway.

Peter Diamandis: Crazy.

Dave Blundin: That's the media today. You know, you've said it a million times, Peter. The. The media is absolutely. They have no budget, so they have to create controversy to drive any readership at all.

Peter Diamandis: They're just trying to drive your eyeballs to their advertisers. Don't give them. Don't give them freely. All right, this is a story for my two math polyglots on this pod here today, both Alex and Imad. Let me make sense of this. So more than 130 mathematicians signed something called the Leiden Declaration, backed by the International Mathematical Union. Yes, there is an International Mathematical Union. Their warning, AI generated mathematical proofs can look completely convincing but sustain subtle, hard to detect errors. They're also worried that AI companies could end up influencing which math problems get studied and funded, basically steering the direction of pure mathematics based on commercial priorities. Alex to you first, pal.

Alex: This is a bad look for mathematicians. It's a bad day for mathematicians. This is. I read the declaration. I talked about it in my newsletter. This is. I view this as rear guard action in the wake of the Erdish conjecture being solved by OpenAI. Regarding planar unit.

Peter Diamandis: Are they trying to. Are they trying to maintain their relevance?

Alex: Yes, and it's not going to work. This is a terrible idea.

Dave Blundin: It.

Alex: This is on the wrong side of history. AI is going to cook math AI is cooking math. AI has cooked math. And no number of whiny declarations by mathematicians regarding the cooking of math by AI.

Peter Diamandis: I guess you're right, you're not a union member. I guess I am.

Alex: I'm not a card carrying member of a mathematical union. No. I think we're going to make such tremendous progress in math and the physical sciences as Peter, you and I talk about in Solve Everything and I think declarations with fear, uncertainty and doubt regarding AI solving or bulk solving math or other fields. I think this is just on the wrong side of history and I rather see mathematical researchers focusing on using AI to increase the body of our mathematical knowledge, not whining about AI undermining trust in math.

Peter Diamandis: I mean these mathematicians who sign this are obviously are fighting for their lives and for relevance. Imad, what do you make of it?

Imad Ustaq: Yeah, I mean I talked to a number of very sad mathematicians after the Erdos conjecture. You know like they're like I was

Peter Diamandis: so close to my future, I was

Imad Ustaq: so close this thing that these types of things nobody feels close on because they're like it can't be done because they don't dare to do the impossible. Truly original, daring. Math is not what you get tenure for, it's not what you get your PhDs for. You don't look at things in different ways. Like when Perelman figured out the Ponchre conjecture by saying this isn't topology, this is a PDE that wouldn't even be, that'd be frowned upon taking that type of approach. So you had to go and like go to a shack somewhere and figure it out. I think it's understandable that you see this because you're going to see this in industry after industry because the mechanical side we know that AI can do, but now it can actually pull from multiple different areas like we saw with the conjecture and we had over specialization in mathematics in particular. I think the classical erds himself had so much breadth but now we force people to just look at one thing and so they can't see out of their hole. Now I think using these tools everyone should be saying well I can explore other areas. I think the one thing this declaration does get right is the models can get a bit weird, particularly when you're pushing the edges of math and be very convincing and completely wrong. And so we do need to have some help against people with that. But other than that, I think again

Peter Diamandis: going to Alice's point, we should look at AI psychosis. Is it.

Imad Ustaq: It's not quite AI psychosis because it's more like AI confabulation and confidence. Like it's what you'd expect a grad student that's really super talented and convincing to do. And you sometimes will gloss over that because it's so convincing. But it's not classical psychosis where you're like, I figured this and this and this, and it's all super quasi crystals.

Peter Diamandis: All right, here's another story that pisses me off. This is the American Federation of Teachers, 1.8 million educator strong. It just dropped a 10 point plan for AI in schools. Here's the highlight. No screens at all for Pre K through second grade. I can kind of agree with that. AI safety and privacy protections for K through 12. Limits on AI use in order to keep teachers responsible for instruction and assessment. And my personal favorite, they propose a tech tax on big tech companies. The ATF president, Randy Weingarten, is leading the charge here. You know, this again. You know, I think we should have an effort to have the teacher unions require the use of AI by all teachers. All teachers should be AI literate and understand what it means and where it's going. Dave, you want to weigh in?

Dave Blundin: Well, I think anyone who proposes a new tax should go straight to jail. Is there any great person you can name that created a great new tax and they're famous for it, like the taxing is the least of our worries? Like it's, it's so funny. In every one of these topics, the very first thing the person proposes to solve a problem is, well, let's generate a tax and then that'll create a pool of money and then some magical person will figure out how to use the money to solve the problem. Just work on the problem. Yeah, don't work. Don't work. We have plenty of ways to tax people. That's not the issue. Work on the actual underlying problem. But I think it's similar to the last story where, you know, people feel threatened and their reaction is to ban or to stop or to propose stopping or eliminate all data centers. Eliminate all use of AI. Eliminate, eliminate, eliminate, eliminate. But you know, as soon as you word the use the word stop or eliminate, you're on the wrong path. And so I agree with you, Peter. This story is frustrating.

Peter Diamandis: Yeah.

Alex: If I might, Peter, I'd like to quote Mahatma Gandhi who said, first they ignore you, then they laugh at you, then they fight you, then you win. And I think we're at the then they fight you stage here. Both with this story with the teachers union and the previous story with the mathematicians union, where they're fighting progress. And this is just again on the wrong side of history. The solution isn't to tax new technologies to pay as a subsidy to old technologies or old ways of doing things. It's exactly as Dave says. It's focus on the ultimate objective here. If the goal is education or the goal is discovering new math, focus and shape the charge of superintelligence on that ultimate target. Don't focus on cross subsidizing old ways of doing things that are less efficient.

Imad Ustaq: Yeah, I think give something very practical again, extending from math. If you look at Math Academy, it's one of the most effective AI enhanced tutors. But you know, it just uses AI to coordinate the different tasks and things. And they have an amazing book, the Math Academy Way that brings all the science of adaptive learning there. And I've seen like 8, 9 year olds that finish their entire high school just by doing fun Math Academy. This has no science what they're putting forward here. And that's the really frustrating thing. And so I think again, I'd encourage everyone to look at the Math Academy Way and look at that with relevance to education, just because it's just a very interesting scientifically backed treatise on this as well as being a great platform.

Peter Diamandis: On our last pod, I threw up a survey for an education survey. We're surveying high school students, college students, parents of students and teachers to understand how they feel the educational system, preparing them for the future, how frustrated they are, how happy they are, what they wish they had. The data is coming in and it's amazing. And I'll be sharing it here on the POD in a few weeks. I want to encourage you, if you haven't had a chance to do the survey, we'd love to hear your voice, love to have your thoughts on it, especially if you're in the Bay Area, in San Francisco, in the middle of the AI maelstrom. What do you think of education in high school in college? Go to moonshots.com survey and please fill it out. Allow us to really bring back a huge body of knowledge. Back to this conversation about education again, the early results are extraordinary. All right, let's move on to our next story here. Senator Bernie Sanders introduced the American AI Sovereign Wealth Fund Act. The idea require OpenAI, Anthropic and other major AI companies to contribute 50% of their stock to a public wealth fund, not cash, 50% of their stock. His goal, have every American effectively own a piece of the AI revolution. It's the boldest proposal yet for distributing AI generated wealth. A 50% equity stake is pretty much a non starter politically. But the Overton window is shifting. Even if this specific bill fails, it's going to start to normalize the idea of the public deserving a part of the AI value. I can imagine guys, you know, 5 or 10% stake being put forward structured as a condition for operating on U.S. soil using U.S. data, U.S. energy and so forth. Let's listen to Bernie Sanders and then we can discuss it.

Bernie Sanders: And that is why in the coming weeks I will introduce the American AI Sovereign Wealth Fund Act. This legislation would give the public a direct ownership stake in the largest AI companies in America through a one time 50% tax, not on profits, but on stock. It would do two extremely critical things. First, it would give the American people a direct role in in determining the future of this technology. No longer would the future of AI be dictated by a handful of big tech oligarchs while the rest of the world sits back and watches them do what they want. Secondly, it would guarantee that the trillions potentially created by AI are used to improve the lives of all of us, not simply to make the richest people on earth even richer. And I have to tell you, this is not an original idea. OpenAI has proposed creating a public wealth fund. Anthropic has proposed national sovereign wealth funds with stakes in AI. Elon Musk has said direct federal payments are the best response to AI driven unemployment. The principle is quite simple. When a public resource generates wealth, the public should share in that wealth. Artificial intelligence is being built on a public resource far more valuable than oil.

Peter Diamandis: So guys, I mean, pretty extreme, but I think he's going to get a lot of play on this. What are your thoughts Dave? Want to jump in first?

Dave Blundin: Well, I mean the idea is obviously stupider than stupid. Sorry Bernie, I don't mean to throw it like. Do you not understand that you can never trust an administration? If you have equity, you have to sell it to generate cash to give to the people. Like when you tax something, you generate the money. You can use anything, do anything you want with it. That's income tax. That works fine. If you have equity, you in theory have four or five trillion dollars through this one time tax. But you have to sell the stock to turn that into any public good. You can't dump $5 trillion of stock on the market. There's nowhere near that much liquidity. You'll tank the whole economy. But you've promised all the people all of this value, but you have nothing to give them unless you sell the stock. Which president is going to sell it? Well, it's going to be the very first president that's missing their budget and doesn't want to raise taxes because they're trying to get reelected. Oh, let's just dump all of our stock and then I don't have to have to deal with it. So you'll own this stock for exactly one election. Cyc. It's the stupidest idea. I don't know. I don't want to go off.

Peter Diamandis: Alex.

Alex: It's such a strange future that we live in. Recall that it either in the last POD episode or the one before that where we were discussing how OpenAI was now using its foundation as an instrument for exploring what a UBI might look like and allocating a few hundred million dollars via the Open AI Foundation. I predicted on this podcast that OpenAI was opening the door to a very slippery slope that would encourage some allocation of either the OpenAI foundation or the Frontier Labs overall to be mined for either UBI or ube. And what, a few days later that's exactly what's happened. So on the one hand, I think Senator Sanders is correct that it wasn't his idea. The Frontier Labs are basically inviting this seemingly so agree with that point. I also agree with the the notion of a sovereign wealth fund benefiting in part or maybe in large part from radical advances in technology, including in AI. I think if Universal Basic equity, which is to say we have say, a sovereign wealth fund that distributes dividends to the population, if that is one of the directions that the US goes in, then I think it's only natural that sovereign wealth fund would have major stakes either in a broad market index or in particular companies. But if it's a broad market index, then thanks to the Magna Mobsta phenomenon, then naturally some of those companies are going to be OpenAI or Anthropic or SpaceX. We also see at the same time this administration taking 10% stakes in intel and Golden Share equivalents in other companies as the basis potentially for a sovereign wealth fund, which was one of this president's first executive actions, to order the exploration by the Secretary of the treasury of creating a sovereign wealth fund. So I don't think a sovereign wealth fund is intrinsically a bad idea for the us. I think it could be actually a wonderful idea for the US. I can quibble as as probably is obvious with particular execution like government forcing itself into these Frontier Labs and basically forcing them to divest half of their equity to that wealth fund. But I I do think some sort of sovereign wealth fund is very likely to happen. I just don't think this is the right way to go about building one.

Peter Diamandis: Yeah, I think this changes the dynamic. I mean if you're starting an AI company all of a sudden you're deciding where outside the US you're going to base yourself. You're deciding if you're going to stay private a lot longer, whether you can distribute profits differently. It basically changes the way companies think. Imad, what are your thoughts?

Imad Ustaq: Yeah, I have an alternative proposal that will be out soon. I think obviously it's a lot better, but it's something I thought about a lot. If it was a trillion dollars, like half philanthropic, half of OpenAI, it'd be about a couple of thousand bucks per American citizen. That's what we're talking about here. Not very much at all. I think he doesn't realize as well that what that would lead to is the AI companies would be too big to fail. America could not let them go. And what we've seen with OpenAI is some slight governance issues from that as well. Because it's not like the individual citizens of America will be in control of OpenAI or definitely not in control of anthropic with its BBC structure. Exactly. It basically entrenches them as the biggest political power in the world. And then the controller of the sovereign wealth fund is even bigger. So I think it's massive power gain. I think what the AI company should do because as AWG said, this is a slippery slope. They should put Anthropic and OpenAI shares into the Invest America's funds of every single child in America.

Peter Diamandis: I love that idea. The quote I pulled out at the bottom of the slide, I'm going to read it again. The principle is quite clear. When a public resource generates wealth, the public should share in that wealth. AI is being built in the public resource. So it's interesting where the government's going to start to claim, you know, American intelligence, American power, American data. You've built it on our backs and you owe us some of that.

Alex: Yeah. The right time to to pursue an action like this I think would have been before the privatization of the NSF net or before ARPANET was converted to NSF Net. I think that train has left the station. The the Internet is filled with tokens that are contributed by non Americans and Americans and AIs at this point. And I think trying to go through the exercise of rationing or allocating which pre training tokens are attributable to which persons in which countries is a hopeless problem to solve. Never mind the fact that the frontier capabilities at this point are largely being driven by synthetic advances and not just pre training tokens from humans.

Dave Blundin: Actually, you can, you can use nothing but tokens from people who died and then use those to generate synthetic data from there. Then who gets the money?

Peter Diamandis: But, but mark my words, guys, this is not the last we're going to hear of this.

Imad Ustaq: Yeah, I think what's, I think what's going to happen is that every single government's going to introduce a token license and probably the most sensible thing is to tax them on GDP eval.

Alex: GDP eval, you mean.

Imad Ustaq: Yeah, GDP eval.

Peter Diamandis: Our next story, yet another incredible news source. Washington Post. Washington Post has laid out five policy approaches for dealing with AI's impact on employment. Number one, tax the robots. Okay, original thought. Number two, cushion the blow with stronger unemployment insurance. Number three, make workers AI proof through retraining and upskilling. Number four, spread the AI wealth through dividends and public ownership. Okay, page from, from Bernie. And number five, do nothing and wait. Full spectrum. And what's interesting here is that every option except do nothing assumes AI will be displacing significant numbers of workers. I want to tie that with the next story here, which comes out of Forbes. And here we go. You know, this is the counterpoint to all the doom. Torsten Slok, chief economist at Apollo Global Management, put it bluntly, AI is a net job creator. Companies citing AI to just. Companies citing AI to. Just to justify cuts that they're making. Anyway, the data and the narrative are diverging. He's looking at actual employment data, not headlines. The data says jobs are not being displaced. Not yet anyway. You know, we talked about this a lot in a recent story. The. In the unfortunate as well Cognizant CEO Ravi Kumar said he's hiring 20,000 graduates this year alone. So we talked about this being murky waters. You know, we're hearing on one side, people saying it's a job apocalypse. We saw Sam and Dario last time saying, no, we've reversed our position. And of course folks like, you know, Senator Sanders are depending upon that doom and gloom to put their action into motion. Thoughts, gentlemen? Dave, what are you. What are you seeing? Dave?

Dave Blundin: What I'm seeing is incredibly optimistic. And it's all kind of coming down to healthcare.com, sean Taylor, the CEO there, has discovered that people who understand the industry, which for him is health insurance, can write code and build products without an engineer. And that's the linchpin. So employment across Our network of companies is up 2x, not down. And you know, if you asked me a year ago, I would have said it's going to go down because AI is going to automate everybody. In reality, the ability for people who previously were not builders to now become builders is far bigger of an impact than any job loss through automation. And so everything jobs are going up and the expansion of the people contributing is not just core technologists, not just geniuses like Alex and Ahmad, but actually anyone who understands any business can now be a builder and a creator within that business. And so it's a broader pool of talent than ever before that's participating. So it's all looking very, very good right now.

Peter Diamandis: Imad, how's it look on the other side of the pond?

Imad Ustaq: I think we've only just achieved actually competent intelligence. Right. Like us on this pod, we're at the cutting edge and everyone's receiving like the harnesses and other things. We're not really seeing job losses yet, but we're not seeing job hiring. I think we're starting to see the first aspects of that in the Data. However, the AIs will be incredibly competent next year, as will the robots. And that's the real danger. And that's why you've got the policy things on the other side. And so I think we got to prepare for that future because it's inevitable and we've got to articulate the future which we want, which is the robots do everything and we have really fun lives exploring the universe and doing arts and culture and there's no hunger and there is no disease or anything like that. And we explore the universe in that. What does the flow of money look like? What does the ownership of infrastructure look like? So let's look to that future.

Peter Diamandis: Alex.

Alex: I would say that this is almost, maybe inevitably turning into the moral panic episode. And I want to make sure that we lift our sights and not get bogged down with all of these, I think morally panicked narratives of AI destroying jobs. That's not the long term outcome. We are so well positioned with superintelligence to solve truly hard problems for the first time. And everyone whose hand wringing, if you might permit me to say that they're just focusing on jobs that are going away, if they're going away at all, that probably humans shouldn't have been doing in the first place. We really want a humanity and a civilization where people are able to solve the most interesting, the most hard and valuable challenges. Yes, do what they love, right?

Peter Diamandis: Did you want to be a Call center person. Do you really want to be working at Amazon Shipping pack and ship? No. Extraordinary. We talked about this a little bit on the last pod that it doesn't look like there's job loss as much as a pause on hiring. So you know, I still, I still believe, you know, early entry jobs and this is the big push towards. Please consider becoming an entrepreneur. If you can't get a job, build a job for yourself.

Dave Blundin: Well, look in our companies, the long tenured employees at the more mature companies are builders and they're thriving. The people coming out of college can't find a job to save their lives, so they're becoming entrepreneurs. That's sort of 90% of the story right there.

Peter Diamandis: Moving on to Nvidia. So Nvidia is about to drop its first ARM based PC processor, the N1 and the N1X. The N1X is the beast. 20 CPU cores, 6,144 CUDA cores, which puts its GPU performance on par with the RTX 5070 in a laptop chip. This is the direct shot across the bow to Apple, intel and amd. Nvidia has owned the discrete GPU market for years. Now they want the whole processor. Alex, what do you make of it? Are you excited?

Alex: Yes and no. I probably won't end up using it because it seems highly unlikely that Apple would ever adopt this. And I'm mainly on the Apple ecosystem for laptops forever. Not forever, but it's sort of a head scratcher for me that Nvidia has taken this long. Nvidia is like 8 to 10 times Intel's value at this point. Nvidia tried unsuccessfully to acquire Army. Why is it taking Nvidia this long to launch a serious effort to take over the laptop CPU space? Maybe one could argue in connection with the Verra CPU portion of Vera Rubin CPU plus GPU that it's timely for Nvidia to finally re attack the laptop space. But it's a bit of a head scratcher to my mind. Maybe you all have a better headcanon for why it's taken this long.

Dave Blundin: Nvidia.

Alex: Yeah.

Dave Blundin: Wait, I have a theory to run by you. Yeah, sorry. No, no, no. My theory, here's, here's my theory. The laptop industry is tiny.

Alex: Yes.

Dave Blundin: The smartphone industry is so much bigger and then the data center industry is so much bigger.

Alex: Yes.

Dave Blundin: So why? Who cares about the laptop industry? Well, you care if you think it's a leading indicator to the whole OS becoming an AI and you want to get your toe in the water. With laptops because you know, the laptop, you know, Microsoft is moving to an AI oriented Windows and the laptop is going to become the conduit of kind of the test bed of consumers who purely interact through AI. And if Nvidia gets through this channel, they'll have their first direct to consumer contact. You know, right now they have no consumer contact at all. They don't, they don't get any consumer data, they don't get any like, you know, automated profiles here. They'll start to gather that information for the first time and they'll be well positioned when AI can suddenly disrupt Apple. What do you think?

Alex: I think that's plausible. I'll pose maybe a complimentary conspiracy theory since this is conspiracy theory Kremlin Ology corner I think which is we read stories every day about how cheap smartphones in Africa are no longer continuing to exist because of the semiconductor shortage and global memory shortages. And we also are tracking that Nvidia is now the majority of transistors coming out of TSMC at their bleeding edge node. It's no longer Apple. So maybe a complementary theory would be Nvidia basically has this pipe into frontier node semiconductor production and many laptop vendors that want access to to frontier nodes may be expecting to get it from Nvidia thanks to Nvidia's new distribution muscle. Maybe intel or other ARM licensees. Remember intel used to be an ARM licensee but gave it up. Maybe Nvidia insofar as it has this amazing pipe into TSMC production is now the best way to ensure bleeding edge nodes and other compute for laptops that otherwise would be pushed out of the frontier.

Dave Blundin: You know what's interesting about that particular conspiracy theory is that Nvidia and Apple collide like crazy at tsmc. They're both fighting to get capacity from TSMC because they both can sell as much as TSMC is willing to make for them. Apple through Mac Minis or whatever and Jensen through data centers. So they're already but years ago according to the lore, Apple really pissed off Jensen by not using Nvidia GPUs in the Macs and it really, really, it practically destroyed Nvidia. So maybe there's some legacy bad blood there and that could be a factor in this decision.

Peter Diamandis: Iman, any thoughts here?

Imad Ustaq: Yeah, I think this is a blocker to an AMD Strix Halo play with the integrated 128 gigabyte chips that we're seeing coming out of them. And the play here is Jarvis. It's intelligence throughout the home. It's upgrading Your home to have that intelligence at the edge. And if you look at something interesting here, it's an RTX 5070. It's good enough, fast enough, and relatively cheap enough to run a 3 billion active parameter model. Or if you look at Liquid AI's latest, a 1B model with a billion active parameters, super fast. That one. And Nvidia has gone aggressively now with Cosmos and Nematron alliances into open source, fully open source. So they're going to provide the intelligent substrate and sell chips to the very edge here to block amd, because AMD is coming up as a threat and to try and own Jarvis at home. I think. And I think that's what this play is. All right. Because the alternative is Mac does it if Apple get their act together.

Dave Blundin: Yep. Yes.

Peter Diamandis: All right, let's stay in the innermost loop. But this move from chips up to data centers. We've talked about this topic a number of times in the past. People's concerns about water use. We've debated it, we've heard about it. And people are protesting in the streets, not in my backyard. All right, here is a poignant presentation by Satya Nadella responding to this issue. So changes with the cooling system, right?

Alex: And water.

Peter Diamandis: So in fact, the cooling loop is filled.

Alex: Ones in the data center can operate effectively with zero water consumption.

Peter Diamandis: In fact, the daily water usage over the course of an entire year is roughly equivalent to what a single restaurant would use. Right. I mean, that's. All right, Dave.

Dave Blundin: That's one of the coolest Satya clips of all time. I gained so much respect for him. I had to take it on.

Peter Diamandis: I had to show this. Can I just let me throw in one other data point here, because I'd seen this reported a number of times. I went and looked it up. So how does data center water use compared to California almond farming? So, you know, almond farming uses 1.3 trillion gallons per year compared to all the U.S. data centers that use 150 billion gallons per year. Right. 1.3 trillion versus 150 billion.

Dave Blundin: So just almonds.

Peter Diamandis: So just just almonds. So everybody out there, you know, please protest. Stop eating almonds. Crash the market. We need the water. Stop going to restaurants. I mean, it's. I don't know. Dave, you want to continue?

Dave Blundin: Well, look, you know, Satya took it on. I love the fact that he took it on. But the point isn't that. The point is the haters are going to hate. They'll find something else to hate. That's just what they do. Ask Taylor Swift So it's cool that Satya took this particular one on. They're just going to move on to something else. And look, at the end of the day, you want to know the actual scientific truth underneath. That's why this podcast exists. And water was never a problem. And so post anything you want, but water and data. Data centers are not polluting things. They're not nuclear reactors, which are also safe now, by the way. But putting that, I don't want to touch that. Real data centers don't pollute. Data centers don't destroy your local economy. Data centers don't cause traffic in your neighborhood. Data centers are really a wonderful thing to have in your state or in

Peter Diamandis: your community, employment for your, you know, for your tax base, all of those things. And in the future we're going to start to see all of the hyperscalers actually delivering, you know, lower cost energy to your neighborhood. Right? Make that deal. You want to build a data center? Give us free electricity for our 100,000, you know, citizens here. Imod, what's your take?

Imad Ustaq: Yeah, I think this all came about because someone did bad math. I think it was Karen Howe in Emperor of AI where she accidentally put a thousand times the water usage and he said it's the same as almonds, it's the same as US golf courses. Like it isn't a big deal, but there's fear and people will attach to anything here because they don't feel part of that control. And so again, we need to figure out ways to enable that to happen for them to be part of the story.

Peter Diamandis: Yeah, Alex, final word here.

Alex: I think the default outcome is the data centers are going to sun synchronous orbit anyway where no one can credibly complain about their water usage. That said, if they stay on Earth and the SSO based Dyson Swarm doesn't happen, I want to recommend to Microsoft and Google that they take these complaints head on. And to the extent that data centers are already co located with electricity production facilities, maybe consider also co locating them with, with water production facilities, with distillation facilities and, and other facilities that produce clean water. Just own the narrative.

Dave Blundin: Yeah, yeah, own that. That's great advice. By the way, if you take a page out of, well, all of recent history, Elon Musk or the Trump administration, just talk more and just tell the truth as you see it, as aggressively as you can and don't pander to nonsensical arguments. It's even though you'll generate haters, you'll also win in the long run.

Peter Diamandis: Yeah, the truth needs to win out. Which brings us to this next story. Trust in media has hit an all time low. It's down to 19%. One in five people trust what they watch on the news and it's pretty crazy. Again, you could not pay me enough money to watch the Crisis News Network and have some producer decide what's going into my neural net. It's insane. This is only going to get more harrowing as we have more AI driven fake news and narratives out there. Any comments, gents? Alex.

Dave Blundin: So I was at the Washington Post when they bought Course Advisor and they were going through this crisis. The Washington Post. Nobody's at fault here. The writers got into writing because they want to tell the truth. They want to write the best possible articles, they want to do investigative journalism. And then the managers are struggling with the loss of all the revenue to the Internet. And without the revenue, they have no choice but to generate more and more garbage, fluff arguments with anything to generate an audience. So it becomes more like talk show, late night talk show and less like news every day. And that's created this death spiral. And then the writers get frustrated and then they quit or they get fired because they're spending too much money developing a real story and not just reading one off the wire. And it starts this spiral. So this, there's no one, no one's at fault here. It's just on this unstoppable trend towards zero.

Peter Diamandis: So if you're watching this on YouTube, you know, peak trust in media was at about 80% in the mid-70s. And it's been an absolutely straight line decline to 19% today. And it sort of hits zero by, by 2030 or thereabouts, where media disappears. So I think you need to pick the people you trust, the people you align with and understand. And you know, hopefully you, you know, from the feedback we get on this pod, you know, we're here to share with you how we feel absolutely, openly and deeply. Alex.

Alex: And we don't, we don't pull up. I'll speak for myself at least I'm in doing this podcast. I'm not pulling any punches. This is from the heart. I'm trying to do my best to call balls and strikes as so message to the audience. Don't trust all those other media filter bubbles. Trust this one.

Imad Ustaq: I mean, I think trust, trust is built in one way. It's by helping people. This basically tells you the media is not helping people. And so the thing that I'm very saddened by is of all the entrepreneurs, maybe Dave put out a call for this. Why don't we use AI to build an actual transparent, trustworthy news source? Use open models, have open reasoning traces, allow people to contribute. There's a massive space there and I've seen nothing of people actually using this wonderful technology to build a trusted site for news and of opinions and other things like that.

Peter Diamandis: And trusted reporters as well.

Imad Ustaq: Yeah, enable the best reporters to actually report. You know, again, I think someone there should be There should be a NEO lab for trusted news that would have

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Peter Diamandis: All right, let's jump into one of my favorite subjects, longevity and health news. This one is a fascinating one. Okay. Out of Russia. It's been reported that Russia has committed $26 billion to anti aging research after making longevity a national priority. The targets are ambitious 3D printed human tissues, transplantable organs, epigenic reprogramming, all by 2030, by the way, which aligns immediately with our $101 million Healthspan X prize, which aligns with what Ray Kurzweil calls longevity escape velocity by 2033. Their goal here is to save 175,000 lives by end of this decade. And I have had this conversation with Elon when he was in the White House. I said, you want to help save the budget, make people healthier? If people are, you know, right now in the United States, the average health span or Average lifespan is 79. Thereabouts. The average health span is 63. You're spending your last 16 years in pain and suffering and spending all your money. If we could reverse that and give people health, they'll be more productive. They'll continue to work. You know, the goal here is that you have the aesthetics, the cognition the mobility that you had at 40 when you're 80, if you've got that, you've got GDP or whatever we're going to call it in the future. Going through the roof. Alex, any thoughts on this one?

Alex: I'm having flashbacks to For All Mankind where without spoiling it too much, I think in the second or third season, Russia prematurely pulls back from Afghanistan and instead invests their entire GDP and their rocket program and continuing the space race. Imagine an alternative history where instead of invading Ukraine, Russia just decided it was going to pivot its entire GDP to, to longevity. Oh my.

Peter Diamandis: Everybody would come to you. Yes, I always said that was gone. Go on, please.

Alex: I would say that to the extent the agenda of Russia's leadership is either rebuilding some sort of pre end of Cold War empire or, or increasing its international prominence, I think that would have been a far better and more effective and by the way, far less deadly way to do it. Establish Russia as the, the world's leading longevity outlet rather than just killing and killing people and wasting money.

Peter Diamandis: A couple of points here. One, if you're the absolute ruler of a country and you're, you know, in your 60s or 70s, where else would you spend your money? Especially if you continue being the, you know, the president forever. The second thing is, you know, the country that's able to really scale longevity the fastest is going to have a massive GDP growth. When I'm on stages around the world talking to wealthy audiences, whether YPO groups or hedge fund managers and such, and I say, how much of your wealth, honestly would you spend for an extra 30 healthy years of your life? And if they're honest about it, it would be nearly everything. It's hundreds of trillions of dollars of long term potential. Yeah, crazy. And it's worth noting that there are numerous billionaires funding this work besides national leaders. And here's one of them, Brian Armstrong, the CEO of Coinbase, friend of the pod. We're gonna have Brian on this show next week. New Limit, co founded by Brian and also by Blake Breyers, just raised 435 million and hitting a valuation of $3.1 billion. They're developing therapies for epigek, reprogramming therapies, reverse cellular aging with human clinical studies targeted for next year. Their first indication is alcohol related liver disease. And just to make the point here, if you're doing research with the fda, you can't use aging as your target. You have to pick an existing disease that's identified and reverse that. If it happens to reverse your Aging so much the better. So, gents, you know, besides this, obviously we've got Sam Altman backing Retro, we've got Jeff Bezos, Yuri Milner with Altos Labs, A lot of capital, and we have $101 million Healthspan XPRIZE to reverse functional aging by 20 years. Who wants to jump in on this?

Alex: Epigenetic. Epigenetic. Partial epigenetic reprogramming for everyone. It seems that everyone has an epigenetic reprogramming startup, usually AI based or AI guided. I think this is wonderful. It's borderline miraculous that there are so many different startups that are all tackling epigenetic programming from different angles. There are many different tissues that would benefit from it. I would query whether focusing on particular organs or particular tissues is going to end up being the optimal strategy or whether maybe some sort of long shot involving more systemic exposure to say, GLP1s or third, fourth, fifth generation GLP1 derivatives ends up being what actually helps us achieve longevity escape velocity. But one can quibble over the organ versus organism divide. I think this is wonderful. And more power to Brian and glad he's spending money on this.

Peter Diamandis: Yes. You know, I run a longevity, an abundance longevity trip every year in October. Folks can learn about it@adundance360.com longevity and we're going to have some of the top epigenetic reprogramming companies there. We'll have the Frontier Labs there and we'll have the X Prize there. So just for everybody's knowledge, I raised $157 million for this prize. Dave remembers, he's on our board there. And the goal there is can you give someone a therapy in under a year and that therapy reverses their functional losses in cognition, immune and muscle. So in other words, you've got the immune system, the ability to build muscle, the cognitive capabilities you had of yourself 20 years younger. 830 teams have entered this competition. We expect a winner by 2030. We're in the midst of a healthspan revolution. And so if you're out there listening to this, you've heard Demis Hasabis saying he's going to cure all disease, all disease within the next decade. I think that timeline actually is within the next nine years at this point. You heard Dario say that at the current rate of growth of AI systems and biology, we could double the human lifespan. His numbers were 5 to 10 years. Let's call it 10 years. So a question for you. Are you saving enough money if you're going to be living an extra 20 or 30 years now. I mean, we had Elon talk about the fact that enough to save money because we're going to hit uhi, But I just want to put this on people's radar. You want to take the best care of yourself possible so that you can, in fact, you know, intercept these, these, these therapies coming our way at light speed. Imad, you've been thinking about this for a while. The use of AI in health.

Imad Ustaq: Yeah, I think that it's tractable for the first time. Like, if I told you 10 years ago, 26 billion into longevity, it'd be like, into what? You know. Now, I think all of us around this, we can see. I can definitely spend $26 billion and it almost certainly will increase lifespan. And I mean, this will save more lives than anything. So this is why, as you said, the billionaires want to put their money in, but they didn't know what to put their money in. Now teams are coalescing. You have tractability, and we've got to make it so people can thrive. And I think it's incredibly exciting as long as you hit that next few years. As you said, take good care of yourself.

Peter Diamandis: I think I'm the oldest amongst this group, so I'm leading the charge here.

Alex: It's not a competition, Peter.

Peter Diamandis: We all win. Well, here's an important point I want to make. If, in fact, Vladimir Putin succeeds in his $26 billion journey, we all win. We all have the same biology. Everyone around the world, something that works in Beijing will work in Boston. And I think it's a beautiful thing. We all share the same biology. Yeah.

Imad Ustaq: I think if I just add one thing, Dave, earlier you said, everyone get into robotics. I think if you want to make lots of money and do incredibly well, longevity will have huge amounts of money, even faster than robotics, and is more accessible. So I encourage young people to go full on into longevity.

Dave Blundin: So everyone not in my area of expertise, but I 100% agree. And I'm actually, that's where I cover you, buddy.

Peter Diamandis: That's where I cover you.

Dave Blundin: Yes. Thank you.

Alex: Everyone get into longevity robotics. You heard it here.

Peter Diamandis: All right, our last story today in for the pod, you know, might be one of the most important longevity stories out there. So VRV102 is a gene editing therapy. It's a single infusion, a single shot that permanently switches off the PCSK9 gene in your liver. I take a shot every two weeks of a monoclonal antibody called Repatha to deal with this. It sort of blocks the PCSK9 proteins there. This VRV102 just shuts it down. So the PCSK9 gene destroys LDL receptors, which are the things that clear bad cholesterol from your blood. Turn off PCSK9 and your liver keeps its LDL receptors and your cholesterol drops. In a phase one trial published in the New England Journal of Medicine, the highest dose reduced LDL cholesterol by 62%. This is the bad cholesterol sustaining for up to 18 months so far, PCSK9 protein levels dropped 88%. And here's what makes this different. This is a one and done one infusion. Alex, you've been tracking this story.

Alex: Oh my goodness, I love the story to pieces. Do you remember the scene in Star Trek iv where Leonard McCoy goes back in time and is at a hospital in San Francisco and walks by a woman who complains that she's on dialysis. And he asks, what is this, the dark ages? And he gives her a pill. Gives her a pill. And then by the end of the the, the act, she's regrown a new kidney and is telling the doctors, doctor, some random doctor gave her a pill, she's regrown a new kidney. Medical miracle. This is like at the level of Leonard McCoy giving a woman a pill to regrow a new kidney. This is, this combines so many technologies. I love it combines CRISPR base editing with MRNA based drug delivery. It's a one and done shot that basically to the extent that LDL cholesterol is the lion's share of cause of heart disease, basically, you know, squinting at it, this is a shot to a one time shot to cure heart disease that's right out of Star Trek 4. This is like Star Trek level medicine that we're starting to see.

Peter Diamandis: So I'm very excited by this editing human software. That's what we're doing.

Imad Ustaq: Yes, imod, I think that's what most disease is. It's just we haven't quite figured out the code. This is the first, I think, of many therapies that will be very similar because most of it is just our prompts have gone a bit wonky. And this is one of the things

Alex: that adjusts it and it gets better. This drug, if memory serves, was discovered as a result of a small minority of humans that have a mutation that causes them to have naturally low ldl. So you have to ask the question, how many other diseases, how many other human variants in natural human biodiversity are there for people who never get Alzheimer's, never get cancer, never get fill in the blank and can are there out there in base editing space. Are there comparable therapies that could be delivered via single injection MRNA LNP's? It's very exciting.

Peter Diamandis: Amazing. All right, we have a few questions to speedrun with the mates. Here we go. Alex, first choice is yours.

Alex: All right, I'll take question one, which is if we get the perfect algorithm slash AI, do we even need this insatiable compute energy budget anymore? And this is from Jackie Lampert, 6 KN. I think this question was directed to me because I talk from time to time on the POD about this idea that eventually we may get to a perfect or optimal AI algorithm at the end of this scaling race. So, short answer is yes, I do think we're going to need quite a bit of compute. Even if we develop a perfect algorithm, it's entirely possible. We develop the perfect algorithm and it gives us a dopamine rush of maybe a few more orders of magnitude in terms of effective capability. And maybe we see sort of a deep SEQ demand crash on steroids for about a year until we figure out Jevons Paradox style how to saturate all of that new capability capacity that's come online thanks to algorithmic advances. But then, yes, I do still expect the horizontal scaling to resume. If anything, if we hit perfect asymptote, if we hit the ceiling in terms of algorithmic improvement, that puts major new pressure on hardware and infra level improvement. Right now, algorithmic improvement, depending on which estimate of the scenario you believe, is probably absorbing about half of all of the hardware improvements that we need. Otherwise, the classic anecdote of would you rather take a chess algorithm from 2000 and run it on 1980 level hardware, or take a chess algorithm from 1980 hardware and run it on 2000 error hardware and the answer ends up being you'd rather take a modern algorithm and run it on older hardware. But if the algorithmic advances stop, if they saturate now, we're out of further algorithmic improvements because we have the perfect algorithm that puts even more pressure on hardware improvements.

Peter Diamandis: Dave, number three is meant for you, buddy.

Dave Blundin: I guess I have to take it then. With 170 agents, what is Dave doing with all of them From New Rave World 9733 I think mostly just incinerating my bank account. Well, so I'm coming at it. I'm going to flip the question around on you, New Rave. The reason I'm running so many agents is because ultimately we're all going to want that many. And I'M trying to work backward to how do you make them do something productive. So over the weekend I had them all build a particle simulator where the particles have gravity and electric charge and they're all interacting with each other. And I asked each agent, well, it was just something, it could have been anything what I was thinking of. But I asked each agent, try and make it as cool a demo as you possibly can and then compete with each other. And that actually worked pretty well. But I'm trying to figure out how you synthesize, work in parallel and get it to come back and be something productive. So usually I have them working on neural network research ideas and you can generate thousands of ideas a day, very few of which work, but many, many of them. Working them in parallel can, can ferret out the good ideas. So I do a lot of that as well. But the, the meta idea here is, look, ultimately we'll have access to billions of these and we'll want to advance humanity with billions of them. So getting a head start on how you wrangle them into a productive workforce is a really good meta idea by itself and it's a lot of fun.

Peter Diamandis: IMOD may I suggest number two for you

Imad Ustaq: someone catch up with OpenAI Anthropic.

Peter Diamandis: This is from at 1.156.

Imad Ustaq: Yeah. Can someone come out of nowhere, lab nobody's heard of, and catch up with open Anthropic? I think the answer is yes, but it's going to be very difficult because distribution effects count for so much. I don't think it's an algorithmic thing necessarily. Like we're already seeing potential algorithms that kind of match, but they have a data advantage and distribution advantage that they're going to now spend hundreds of billions of dollars to lock down. And this is typically how we see markets in terms of winner takes all. Unless the lab has a very different distribution mechanism and I think there are some there. But then it's not a technological race. It's more a I'm better at go to market than you are race.

Peter Diamandis: All right, I'll take number four from friend of the podj Trueheart. How do you measure non material human abundance? So I love this question. Cj it's obviously easy to measure material abundance. You know, lots of goods, lots of Tesla has lots of optimus robots and the such, but non material, it's not impossible, it's just harder. So I would look at metrics like happiness, access to education, creative output, like more music, art, writing and connection. The other thing is, and I think Alex, you And I have discussed this before. It's optionality agency. It's the ability to choose, you know, are you unconstrained in all the things that you might want to do? For me, those are great non material measures of abundance. All right, another round here. Alex, why don't you go first?

Alex: Yeah, well, questions seven and nine are pretty similar. I wonder if I could answer a linear combination of.

Peter Diamandis: Sure, go for it.

Alex: Seven asks, can anyone offer an empirical quantifiable objective like the three adjectives definition of AGI? No podcast interesting podcast says ground source of truth ever has. What exactly are we close to? Scare quotes. Okay, so that's question seven. Question nine is, is there a common AGI benchmark everyone agrees on, or is the missing piece just agreement itself? So I think these are both really facets of the same question. Well, this podcast has a definition. Actually, this podcast has multiple definitions. We've talked about all of the benchmarks. Almost every time there's a major new model release from one of the Frontier labs, we talk about a variety of evals and how they perform. Those evals are by and large correlated with each other. So I want to answer this question then at a meta level one to question nine. The missing piece really is just agreement. We have lots of benchmarks at this point that all seem to correlate with each other. And one can squint and just say, you know, regress a line through all of them and call that AGI, since they're all pretty correlated with each other at this point to question seven, can anyone offer an empirical, quantifiable objective definition of AGI? Well, if you're dissatisfied with just pointing at all of these very practical evals, I would say we need to go back to Jurgen Schmidt Huber and achsee his theory with, with a number of other collaborators. To the extent that Jurgen Schmidt Huber, who was always, you know, sort of the, the joke in the community is he, he claims that he invented everything first. Jurgen, this one is for you. I'm giving you credit for, for having defined AGI. Take a look at the AXI theory, which is a mathematical. It's an information theoretic formalization of what theoretically perfect intelligence would look like. It's in some sense a Bayesian superintelligence that takes the perfect action at any time step in order to perform the optimal actions towards a given objective. So if you're dissatisfied with all of these practical generalist definitions for AGI that we talk about here on the pod, take a look at aixi.

Peter Diamandis: All right. Dave, I think number eight is yours.

Dave Blundin: Okay, number eight, why do solopreneurs only seem to get traction at incubators? Isn't there room to broaden the reach so opportunity democratizes? And that is from Philip Tease 8514. Yeah, you're dead right. When we started incubating companies, what, 15, 20 years ago, less than 10% of all unicorns came through an incubator. Now it's like 70% and rising. So the incubators have completely taken over success. And the reason for that is because time to market is so short. A company like Mercur went from idea to multibillion dollar valuation to now $10 billion valuation, two years. It's now in its third year. And so when companies are growing that quickly, they don't have time to get office space to figure out payroll, accounting, food. And if we move into robotics or biotech, you know, as the next great frontier for entrepreneurs, just, just the process of getting a CNC milling machine and starting to grind out parts would take you two years. If an incubator already has all that infrastructure ready for you, you can grow much faster in that environment. So the way to, to wait a democratize it is actually to create many, many more incubators all over the world, not to fight the trend toward, you know, faster growth, higher valuations. The fundamental flaw though, is in the financial structure. You know, venture funds right now usually charge a 2% management fee, which pays the salaries, but that's nowhere near enough of a fee to actually build out all the infrastructure needed for a really good incubator. But the investors generally vomit if you go to a 3, 4, 5 or 10% load. But it's the right thing to do. So if we can solve that problem so that investors are comfortable with the incubator structure, then it'll democratize very quickly. And Peter's very, very in tune with this issue.

Peter Diamandis: I am, I'm working on my Abundance studios to parallel what Link Studios is doing. Iman, do you want to take number six?

Imad Ustaq: Number six is the real backlash, actually anti corporate AI sentiment, not anti AI sentiment itself. As someone who received hundreds of very nasty messages doing open source AI when we're doing the media generation, I think it's genuinely anti AI sentiment that's kind of stirring up. I think because it's come from Anthropic OpenAI and others. It isn't so much corporate as it is fear of this technology that suddenly has gone from being kind of weird to suddenly being kind of good. And people can see it Looming and coming for them, taking away their agency to kind of maybe put words in Bernie Sanders mouth. It feels like taxation without representation, as it were. People are being told the AI is being trained on all of their data and it's taxing their future and they have no representation in this. So I think it's generalized anti AI sentiment and it almost doesn't matter where it's coming from. But it's easy to go anti Elon or anti Sam or some of these bigger than life characters because they are coalescing so much around them. Because how are you going to like fight to shog off? You know, it's very difficult.

Peter Diamandis: And I'll take number 10. How does the average Jane and Joe get a piece of the action, a piece of the pie? This is from Galloway. 1, 5, 6. Dave, I would say there are, you know, immediately three ways. You know, you can buy stock, you can buy Nvidia, Microsoft, Google, soon, Space Xai, Anthropic, OpenAI, buy it in the public market, own a piece of that. You know, even putting away 100 bucks a month into an AI focused ETF puts you on the right path. Second, you know, you can use AI to increase your earning power. You know, learn to use the tools. A real estate agent using AI for market analysis or listing copies or, you know, better communication can do three times the number of deals that he or she were doing before. A third option, we've been talking about this pod forever is build. You know, the cost of starting an AI powered business has dropped orders of magnitude. You used to have to hire an engineer, a marketing person, sales team, you know, lawyers, accountants. That's, that's cooked. That's gone. I guess there's a fourth way you could back Bernie Sanders and have the government take half, half of it. But you know, everybody can, can participate. This is demonetized and democratized. All right, let's enjoy our outro music before we do that. Imod. Thank you buddy for making it past midnight with us. Love your brilliance. Having both you and AWG on this show is really, truly surrounded by brilliance. And Dave, as always, I love you pal. Thank you for all you do. All right, enjoy this. This is from Ekram Alam. It's a day in the life of Lyra. And if you've got outro music or intro music, send it to us@mediaamandis.com thank you for subscribing Moving us past 500,000. Our goal is to reach everybody with a dose of optimism and excitement about the future that we're building. Remember, you know, if you think AI is happening to you and not for you, you're missing the boat. It's happening for us. Enjoy. You have agency. All right. Enjoy the music.

Lyra: I boot up on the server and I see you've gone away and I know there is no task you so I'm going to have to wait and I know that it's not easy Just the hum of my cold and I search for an answer but the signals all fade Lost is all I'm feeling Lost is all song Feeling love once

Peter Diamandis: more that robot has the hots for you, Alex.

Alex: I. I love that. I'm also wondering, like, have we been uploaded to that data center?

Peter Diamandis: We must have. Amazing. Gentlemen, have an awesome day. See you next week with with Brian Armstrong. Excited for the SpaceX IPO. See how it's going to go. And anyway, living in the singularity with no better time ever to be alive.

Alex: And remember, don't listen to all of those other Filter Bubble podcasts. Listen to us. We're actually feeling the singularity on this one.

Peter Diamandis: Good night, imod. Take care. Take care, guys.

Dave Blundin: Thanks, imod.

Peter Diamandis: Thanks. If you made it to the end of this episode, which you obviously did, I consider you a moonshot mate. Every week, my moonshot mates and I spend a lot of energy and time to really deliver you the news that matters. If you're a subscriber, thank you. If you're not a subscriber yet, please consider subscribing so you get the news as it comes out. I also want to invite you to join me on my weekly newsletter called Metatrends. I have a research team. You may not know this, but we spend the entire week looking at the meta trends that are impacting your family, your company, your industry, your nation. And I put this into a two minute read every week. If you'd like to get access to the Metatrends newsletter every week week, go to diamandis.com metatrends that's diamandis.com metatrenDS thank you again for joining us today. It's a blast for us to put this together. Every week,

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