Elon's $5 Trillion Bet, the End of Human Drivers, and Chamath's Market Warning | EP #242

22:11Dave Blundin:Well, also he's thinking two moves ahead in the big chess game. And, you know, two moves used to be 20 years. Now it's six years, but two moves ahead of everybody else. And this came up, Alex and I were talking earlier this week about fission energy. And, you know, Elon doesn't talk much about fission energy. Why? Well, because he's visualizing solar in space And, you know, solar on Earth is a great stepping stone to solar and space, and it requires panels and batteries and cooling, but it doesn't require turbines and fission reactors. So he can skip a couple of hard steps and go straight after the next move in the big chess game.

22:45Dave Blundin:So it's really interesting to watch how those timelines have inverted. You know, the Dyson sphere is now right on our radar, and even Google is talking about it, which means everyone's talking about it. So that came to the forefront really just in the last month or two. And so the whole timeline of humanity got shifted. So the Dyson sphere will come before anyone even figures out how to get licensed for a fission reactor. Can I be cynic just for a second? Yes. The plans are ridiculously grandiose. And if any of these people can achieve them, it's Elon. But curious that the timing of this is just leading into the IPO to get everybody excited about things.

23:21So that would be the cynical view. But I still just love the audacity. Yeah.

23:26Dave Blundin:Well, I think, Salim, your first observation was dead right. If you shoot for the Mars and you end up at moon, you're still way up. So I want to ask the question again that AWG said, nope, which is monopoly concerns. Do you believe, I mean, if he's really generating, you know. I'm not worried about it because when you have an MTP, which he does, you're basically operating on this massive mission. You may have ethical issues here and there, but generally the trend is so positive and so beneficial for humanity. Who the hell cares? Well, I mean, humanity becomes dependent. There's always another person, somebody who's like Brendan Foody, maybe.

24:05Dave Blundin:Somebody like that right now is like, wow, I'm going to do this too. And, you know, it's just the way it is. And that person, we don't know who they are yet, but they'll emerge. And, you know, you can't exist in the U.S. without antitrust action if you don't have a competitor. So Elon will invite that competitor, whoever it is, and it'll be great. I'll say one other thing here.

24:26Peter Diamandis:If we label this monopolistic behavior, then don't we have to label everyone with an MTP a monopolist? Just ask the question, my dear mates. Market dominance, if you get there, then that's true.

25:08Dave Blundin:But you're right. Google is not going to go away as a... Well, and don't forget, Eric Schmidt is trying to bring relativity space online so that the rockets are at least part of the Google family. But let me just close this. There's plenty of the moon to go around. Let's not forget. One thing that's important here is every time there is a constraint, the Judo move is to realize it's a massive opportunity. And so this is an abundance story once again. This is a massive increase in abundance of AI compute beyond what anyone was speaking about just a week ago. So I'm glad he's focused on this and less on the politics.

25:51Yes. Amen. All right. Here is our second conversation story, one that I'm excited to have with my Moonshot mates. It's about the future of human transportation. You know, robots are getting their driver's licenses, flying cars are taking flight. Here's some of the data. And I want to go deep on this because I want everyone listening to understand how this is going to impact how and where you live, how you commute, every aspect of our lives. So Waymo hit 170 million fully autonomous miles, equivalent to 200 human lifetimes of driving, with 92 % fewer serious crashes. So a significant reduction in crashes.

26:35At current, they've got 3 ,000 vehicles in 10 cities. Still early, right? Uber has now invested$1.25 billion in Rivian with plans to deploy 50 ,000 fully autonomous robo-taxis. Here's a look at Waymo versus human drivers. Waymo is doing an extraordinary job of saving not necessarily lives, but saving crashes, you know, minus 92%. So I think CyberCab, we've seen incredible data like this also on full self-driving from Tesla. Check out this image. This is Joby Aviation. Joe Ben starred this company. It started Velocity 11, took that money after he sold it. He was partnered with Rob Nail, Salim. And Joe Ben started Joby Aviation, God knows, over a decade ago.

27:29And here it is flying over the Golden Gate Bridge in San Francisco. It's a beautiful image. This is a eVTOL electric vertical takeoff or landing. It's a name that rolls off the tongue onto the floor. I'm calling them flying cars because that's what they are. And here's what's going on in the eVTOL world. I think really important. So Joby just is now in testing for its first FAA-conforming aircraft, meaning it's demonstrating to the FAA that it can build a reliable design over and over again. It just had demonstration flights on the Golden Gate Bridge. Joby and Uber announced Uber Air powered by Joby.

28:13In fact, when Travis left, before he left, he had created something called Uber Elevate, and they were doing their earliest work on flying cars. I keynoted their talk there, but Uber Elevate got sold to Joby, and now Joby and Uber have a partnership. The other company in the United States that is compared to Joby is called Archer Aviation. They have a beautiful aircraft called Midnight, and they're the first company to achieve 100 % FA acceptance of its eVTOL aircraft means of compliance. Long story short, we've been waiting a long time, and flying cars are almost here. We're going to start to see them operating in the U.S.

28:58in the next 18 months, should be here in L.A. in 2028 in a big way. and so here are some of the conversations gents um first off when is it going to become illegal for humans to drive celine yeah i think you know you'll start with city centers right and you'll be illegal to drive in city centers and it'll slowly broaden out from there i think what's i'm i'm the flying car is the most exciting technology for me personally given that i'm commuting to airports a lot that I could ever ask for. So this is 10 years later than I wanted it, but finally it's finally happening. What I like about it, these are not transportation stories.

29:40This is full urban redesign is what the narrative is. Essentially you make, land becomes abundant. Now land has always been scarce. Real estate has been scarce. Real estate becomes abundant. If you fly across the U.S., it's empty, right? And we've talked about the statistic just around between Toronto and Chicago airports, there are 10 ,000 islands and lakes, right? So we do not have a scarcity problem. We have a mobility and accessibility problem. So I think I'm super excited by this particular model. I've got my two years for us to get to full autonomy before Milan gets his driver's license.

30:16He's 14 right now, so I'm pushing hard on this race. Mostly he wants to get him to get away from parents, but that's fair. So we'll see what happens. But, you know, you compress travel time, you reprice real estate. This is such a huge thing. And I've got to just shout out to Joban just because it's hard to build a hardware platform like this and to do it over a decade with all the inevitable regulatory and market structures against you and infrastructure against you. This is like huge, it's like a Nobel Prize in patience here. Yeah, incredible. Dave, you were going to say.

30:50Dave Blundin:Oh, the eVTOLs are going to move very quickly because they don't run the risk of, you know, crashing into houses like self-driving cars on a road do. They're all going to be autonomous on birth. That's the new thing. eVTOLs have been in the works for years. But the AI that makes them self-flying, self-driving, and super safe is here all of a sudden now. True, but the first airplanes are going to be piloted, right? There'll be a single pilot, four passengers in the back. The goal is rapid recharge at the vertiports when they land, recharge probably an average length of flight of under 10 kilometers, I think.

31:28Going from Santa Monica, where I am, to the Dodger Stadium and avoiding the 10. But autonomy will come with enough data and enough demonstrations. Wait, why won't they fully autonomous from the get-go? Because it's called the FAA. But FAA, the FAA is not happy until you're not happy.

31:52Dave Blundin:Yeah, that's exactly it. The manufacturing of these wants to happen right away. And the AI command and control is being worked on for the car, not for the eVTOL yet. So there'll be a couple of years, very short period of time, in my opinion, two years or so. Because, you know, in the Middle East, they're already doing the self-driving, self-flying version of this. So it should be a very short window where people get to fly these. the bullet here though is when does it become illegal for humans to drive? I think that's going to happen very quickly as well. Very similar to indoor smoking or drunk driving.

32:25Dave Blundin:There's a tipping point where a lot of voters say, wait, you're putting my children at risk with your crappy driving. That's ridiculous. We've got data and proof here that the self-driving is 90 % safer, soon to be 95, 97 % safer. And, you know, the human tragedy that comes from car crashes is unbelievable, shocking. And so under five-year-old kids, it's the number one cause of death. Yeah. Accidents. Yeah. Oh, and, you know, it's devastating to families too. It's just absolutely tragic. At least in the first world. Yeah. Well, there'll be a TV ad campaign probably three, four, five years from now with lots of ugly images in it.

33:08Dave Blundin:And then there'll be massive amounts of voting. And then people will say it's, it's inconceivable that you would drive on a public road. That's inhumane. Go drive on a test track. That's fine. Maybe, you know, some country roads, that's fine. But, but no way, don't put my children at risk. So I think that's going to come as soon as we have the manufacturing for the cars themselves. But I think the thing that would make it later is purely the shortage of chips. Like the technology will be there and the demand will be there long before the chips are there. So if you want to unlock this as an engineer, figure out how to do more compute with less silicon for this exact use case, and you'll be an instant billionaire.

33:50Peter Diamandis:Alex, your thoughts? I like this format, Peter. This is like an internal AMA, so I'm going to try for a lightning round on all of these. Oh, leave some room for the rest of us. Let's take it one at a time? One at a time. At what point does it become illegal for humans to drive? I think never. I think we'll simply redefine driving to represent higher and higher levels of abstraction. So right now with like FSD 14, you tell it where you want. And if you're running the most recent subversion, you can have a conversation with Grok and you can do minute steers along the way. I think that notion will get refined such that driving gets redefined to be sufficiently abstract, that it's always safe for pedestrians.

34:29Peter Diamandis:It's always the human on the loop of the AI driver. So it's effectively a human-machine hybrid, if you will, that has the safety of the machine but makes the human feel like they're in the driver's seat still. I said this when Dara was on stage with Salim and myself. I said, there's a version in the future of self-driving where you're driving and you can push the car as fast and as hard as you want, and the car knows its own limits. It knows the traction of its tires. It knows the road surface. and it prevents you from doing something stupid, but you're in control of it 99 % of the time. But the 1 % where you're about to do something that will destroy you, a person or the car, it stops you.

35:09Peter Diamandis:Exactly. I think like the future of the accelerator pedal isn't the accelerator pedal. It's if you use FSD, it's turning the driving mode up to Mad Max. That's sort of like an abstraction of acceleration. By the way, that's all I use is Mad Max and it still doesn't go fast enough. So I have to step on the pedal. There used to be an ad that says, friends don't let friends drive drunk. And so you can just keep that ad and drop off the drunk part and go, friends don't let friends drive, period. So all the messaging is there. All right. So AWG, why don't you kick us off on question two here? Okay.

35:44Peter Diamandis:Question two. With Uber partnering with Waymo and a bunch of other names, will the CyberCab be able to compete? I think we mean compete here. Yes, of course. It's going to be a very competitive market, period. Yeah. And I love the fact that this is driving us towards abundance, right? This is driving us towards UHI. If you've got a dozen companies delivering autonomous vehicle services in your city, they're going to be competing against quality of service and price and just bringing the price down to a minimum amount. Now, one of the things that's interesting about CyberCab is that that's going to be priced at probably$30K is roughly what Elon's announced.

36:27And it's going to allow people to buy it. So one of my goals is can I buy 25 or 50 of them here in Santa Monica and own them but have them going out and basically generating revenue for me and for my CyberCab. So I'm sure they'll have some level of personhood by then, Alex.

36:48Peter Diamandis:Obviously, I never would have guessed, Peter, that your next gig would be as a cabbie, but the singularity makes for strange bedfellows. Fleet owner, fleet owner. I have a comment on this. Salim, any thoughts? Yeah, please. I think the big impact for me when I see this is the complete collapse in the market structure of cars. Today, we make close to 100 million new cars a year, and they sit empty 94 % of the time. So even if you drop that by 50 % utility, you basically collapse the need for half the car industry instantly. And these cars maintain for a long time. The lifetime should be near infinite.

37:28My Tesla Model 7 2017, it'll go a million miles. There's nothing wrong with that car. So this is going to completely change the nature of car services, car maintenance people. The complete industry gets reshuffled from the bottom up. Yeah.

37:44Dave Blundin:Well, think about the implications of that too, Salim. Right now, if you take an Uber from SFO to San Fran for like 200 bucks or whatever the hell it is, it's almost all driver costs. So even before you shrink the number of required cars by a factor, I think the estimate was 5x. It's 10x. Even before that savings, is it 10x? But the driver's already the majority. So you take the driver out of the loop. So the cost of that ride should go down at least 10x because the car's coming down 10x and the driver is more than the car anyway. I think the number I've seen is 20, between 10 and 30 cents a mile.

38:21Yeah, I've seen it as a four to five fold cheaper than owning a car. The next question I want to ask and offer my points of view is I think one of the most important one for our listeners. This is going to have a profound impact on your real estate holdings, where you live, what you do with your real estate. So if we have autonomous vehicles, and we've reduced the number of vehicles on the road by 10x, let's call it that, and these vehicles don't need to park. Again, my current version of this is I get up from the breakfast table with my family, I walk towards the front door, my AI knows that I'm moving to open the front door, it knows where I'm going, it's ordered an autonomous vehicle, what I call automatically for me.

39:10I haven't had to ask. And so all of a sudden, you know, we had in our home here, we had a three car garage. We already converted one of those garages into an extra bedroom. The other two garages have become effectively storage and build out, you know, probably a workout gym and so forth. I think the idea of a garage, a personal garage in your home goes away. So start thinking about what are you going to do with your garage space? What are you going to make it into because you're not going to own a car. You might want access to a car, but most of the time, do you really like driving? I mean, when you get into an Uber, do you ask the Uber driver to get out and let you drive?

39:50Dave Blundin:So right. And you know, this part of the conversation is incredibly actionable for all of our listeners. That doesn't rise to Alex's level of, you know, like change the world tomorrow, but it really matters to almost everyone who listens. Everything Salim said and Peter said is dead right. If you're young and you've got a job and you're living in a city, which is 60 % of you, you might not want to buy in the city. Keep renting and look for something that becomes your second home later in life that's in a beautiful spot that's a little harder to get to that is going to be incredibly coveted. Imagine a world where there's 10x more wealth about 2034, 2036, and this is a spot that anyone in their right mind would want.

40:40Dave Blundin:And actually, if my wife is listening, close that transaction that you kicked off this weekend, even if you have to pay a little more. But yeah, that's the life plan you want, because accessibility, not just getting to it, but also delivering things to it. Like, you know, your Starbucks or Dunkin' Donuts is going to come by drone. Absolutely. And so that changes what you want. Think about it. And there aren't, you know, we have a huge country, like Salim said, but the really great spots are limited. So really do your soul searching and look for that thing. And don't buy near an airport in a city.

41:14Island real estate is going to become, you know, 10x, 100x more accessible that will drive the value up. And in a downtown LA, you know, it's like, I don't remember the figure. It's like 30 % of the blacktop is parking. All of it gets released to become new. 60 % of the land area has parking spots in Los Angeles. It's a crazy number. That's insane. Well, that becomes gardens. It becomes Greenland. It becomes parks. That's incredible. And think of the unbelievable space we use in stadium parking lots, right? Acres and acres and acres of rows and stuff. So we'll have to rethink tailgating and everything.

41:56So there's so much available business opportunity here if you can think ahead of what you will do with that. And if you're in the parking garage business, you've got to think ahead as well.

42:10Peter Diamandis:A couple of other second and third order implications, if I may. We've already touched on, I think, the more obvious ones, parking garages, etc., need to be reprogrammed for other purposes. Another, I think, borderline cliche implication of full autonomy everywhere is the re-spread of suburbia. Why invest so much in urban center real estate if you can be effectively connected to an urban center or not even need an urban center if AVs take you everywhere? Basically, a virtual subway from anywhere to anywhere. So re-suburbanization, if you will, at least in relatively low population density countries like the U.S.

42:49Peter Diamandis:I think these are pretty cliche implications. A less cliched implication in my mind is, what if we just take this trend and extrapolate it fully to completion? What happens? I think there's a future. I put out a request for startups around this idea of why not just create autonomous Winnebago's, the equivalent of having entire office buildings that are themselves autonomous vehicles. One could imagine living in an autonomous vehicle. It's all part of a social network. When you need to take an in-person meeting with someone, your two AVs are part of the social network and they connect and synchronize all of your locations.

43:28Peter Diamandis:So maybe you're in Boston in the morning, but you're in Washington, D.C. in the evening. This is all handled automatically to synchronize your calendar with your AV location. And then it's a sleeper car, and then you're in Chicago or wherever the next day. So you become this. You become. Your bedroom car. You become. Your bedroom car comes to join you. Humans become internet packets that are being routed by the autonomous vehicle system. Love it. Love it. Love it. Love it. You know, the eVTOLs, it's taken a while. there is still a lot of doubt people have about eVTOLs. You know, the opportunity we have is going to be limited by the size of these, being able to land locally.

44:12So there needs to be sort of local hub and spoke vertiports, you know, somewhere within five minute driving and gluing these all together. And that's what Uber wants to do with their platform. So I hop in my autonomous Uber. It takes me without thinking to the right eVTOL site, which takes me to another location, 10 kilometers, 20 kilometers away, and then I'm in another autonomous vehicle. What I'm missing from all of this, Alex, is Hyperloop, right? So I actually joined one of the first Hyperloop companies. Virgin got involved. We raised, you know, probably close to$100 million. It didn't go forward, but the material science of creating Hyperloop, And of course, the benefit for Hyperloop right now is effectively supersonic travel, point-to-point, inner city-to-inner city, L.A.

45:05to San Francisco, L.A. to Las Vegas. That one will be busy. So got to see Hyperloop on this list eventually.

45:13Peter Diamandis:Peter, which do you think you're going to see first, like in practice for, say, New York to Los Angeles? Do you think you're going to see Hyperloop first, or do you think you're going to see Rocket Cargo first, where you hop on an Elon Starship, go up, go down? You know, I've thought and looked at point-to-point rocket travel, and it's a tough thing. The energy dissipation, because you're basically going to orbital velocities and you're having to reenter over or near a city. I guess the version that Elon put forward was offshore landing facilities. That's right. So that you're, you know, a kilometer offshore.

45:51I think for one reason, rocket point-to-point travel, because Elon's behind it, and because the vehicle exists, and they're going to be launching every 5.3 minutes. That's right. And, you know, Elon almost got involved in Hyperloop. But like you said, I can't do everything. Anyway. I have two thoughts here, quick ones. Yeah, please. One is I think Hyperloop will be used largely for commercial and for container loads rather than human beings, because then you don't have to worry about G-forces and the safety standards can be lower. And the second is, remember that, yeah, although it takes us like three hours to five from New York to Miami, that three hours on a plane today is way more productive than it was, say, 10 years ago.

46:40You've got full internet, you can work. 100 megabytes, baby, on Sterling. We can schedule ourselves now to do things when we largely want to do them. So I think that's a huge opportunity also. So for our listeners, I would love to get your feedback on this format where we're going deep on the topic and having the conversation, trying to educate you about how we think about, in this case, transportation or previously, TerraFab. Our next conversation is the great reshuffling. Job loss is inevitable. The only question left is what we build on the other side. So here's some of the stats and some of the articles that came out this week that have us thinking about this.

47:19Goldman says AI could automate 25 % of U.S. work hours. Seems like a low estimate to me. PwC told its partners, if you resist AI, you have no place here. AI tool yourself or get out. G42 posted a job listing exclusively for AI agents. Is this sort of a gimmick? Is it real? And I love this one. And this came from sort of a hit from Jensen. Companies are now tracking individual employee AI token usage. And Jensen came out saying, if a$500 ,000 engineer didn't consume at least 250 ,000 tokens, I'd be deeply alarmed. You know what this reminds me of? This reminds me of De Beers saying, three-month salary to buy a diamond ring, right?

48:11Doesn't it? Tokens are forever, Peter. What do you mean, that's it? Tokens are forever. That's great. So, I mean, literally, Jensen is saying he's taking the total salary, you know, of all engineers on the planet and cutting it in half and saying that's how many tokens we're going to be selling. And then perplexity, AI won an appeals in court to continue running shopping agents on Amazon. So, I'll show one chart here and then let's talk about it. So, AI could automate 25 % of all work. This is Goldman's chart showing each of these columns. It's a different type of work. And I guess the median here is about 25%.

48:54We've seen this lots of different places in different versions of it. But let's jump in. So Salim, you work with more consultants than I do, than anybody here does. So what do you think about this PwC telling its partners, you know, adapt or die? Yeah, I think that's fine. but I think it doesn't go far enough. And same with the McKinsey's thing. So the calculations I've been running as I kind of get this paper, organizational singularity paper finalized, is that you'll be able to run... Get it out, get it out. Just give me a couple of days that'll be ready for draft and review. We're just doing similar thing.

49:33You'll be able to run a typical company with between 20 or 25 % of the employees you have today. Because all workflow goes from human to human, the agent to agent, right? Now, you could take on the doer side and go, oh, my God, 80 % job loss, but no, because we'll just end up creating four or five times more companies. And also for bigger companies, that transition to an AI-based workflow is going to take much longer than for a startup or mid-market. And therefore, there'll be time for the economy to – so I'm actually suggesting that we will have no perturbation in jobs, almost zero. Now, definitely partners who resist AI will have no place.

50:13There's also something to say that consulting partners have no place in the future because in the future, you have an AI agent figure out your strategy. Why do you need a consultant firm? You're going to need that for more firm implementation. And if they have better agents than you do, I think that's where we'll end up with that. Alex, what are your thoughts on these? It's very difficult.

50:32Peter Diamandis:So on the PwC story, it's very difficult for organizations to self-disrupt. So if you're a management consultancy or an accountancy, some other bill-by-the-hour heavy firm, it's very difficult for you to willingly and voluntarily transition to an outcome-based pricing model versus an input-based pricing model. So I take the you'll-have-no-place comment. I interpret that as an attempt to self-disrupt. In practice, it's very, very hard to do that. And the whole point of Schumpeter and disruptive innovation in general is most of the macro replacements for, in this case, for input-based actors in the economy are probably going to come from other firms, not from large firms self-disrupting.

51:22Peter Diamandis:The G42 story, I think, is actually really interesting. I looked closely at the G42 job listing, and it really is a job listing for AI agents. And one has to wonder, yes, like around the edges, they also ask for details from the developer and what was used to make sure that this was really an AI agent submitting itself for, I think it was a marketing job. We are so painfully close, I think, to a near future where there's a sort of reverse discrimination against humans and where humans need not apply. Oh, my God. It ends up being an epithet on so many jobs. Well, you have that already with the PwC partners, right?

52:06If you don't use AI, get out of here. That's essentially we're getting to that point. We're halfway there already. Right.

52:12Peter Diamandis:That's that's PwC, though, which is a human oriented business, basically trying to force humans to self automate, at least from a unit pricing perspective. This is born AI jobs where humans need not apply. I agree. You know, Salim, one thing that you and I do for large companies that I think people need to understand, most large companies out there are walking dead. their business models will be fundamentally disrupted in the next two to five years. And so the question is, how do they disrupt themselves before someone else does? And the answer is, it's really hard, almost impossible. And so what you and I have done before is invite super talented young entrepreneurs to come in, hear the company's business model, and say, this is how I would disrupt you if I was funded to do it.

53:05And then the company should fund the best of them, right? And we've done this, fund the best of them to actually build a adjacent company who's intended to disrupt the primary company. And then literally, yeah. The design firm Ideal actually did this. They realized that their methodology would be widely known and they couldn't stop the leakage of that. So they picked one of their crazy partners and said, go to the edge and build the disruptor. And he created an open ideal marketplace of design ideas. It was amazing.

53:43Dave Blundin:One caveat to what Peter said there, the private equity guys are having a field day with AI automation. And if a company has great cashflow, even if its business model is doomed in the age of AI, the profitability is going to go through the roof in transition because in the near term, yeah, because, you know, an AI can do the job for 10%, soon to be 2 % of the cost of the human, you know, with no labor laws, no overhead, no insurance, health insurance. But Dave, if you've got good cash flow, there's an entrepreneur looking at that salivating, coming to eat your lunch. Yeah. So what happens is the private equity guys will come in and say, hey, cash flow, cash cow, with great cash flow, we're going to buy you or buy part of you, and then we're going to AI-ify your business, and that'll drive even more cash to the bottom line, and then we're going to use that cash flow either as a vehicle to launch new things like an incubator or to attract that entrepreneur or to just roll up those startups and acquire them back in.

54:46Dave Blundin:So it becomes kind of a centerpiece. By the way, both Anthropic and OpenAI are partnering with private equity firms to do exactly this. Go buy companies and then AI enable them because you can do it with the owner. Jeff Bezos, who could do anything in the world, just announced a new$100 billion fund to do nothing but this. So Jeff is doing it. They don't have enough money already. Alex, I'm curious, or Dave, I'm curious about your thoughts on the fourth bullet here, that companies now track individual employee AI token usage. Yeah, yeah, yeah. And you should have a minimum token usage per employee.

55:20Thoughts? Dave, do you want to go first?

55:22Dave Blundin:We already implemented targets across all of our companies on this. And we're targeting 80 % token, 20 % salary. And I think that's a really – it's very similar to what Salim said a minute ago. There's going to be huge amounts of job disruption in the next two or three years. And then it will turn around and by 2030, 2032, things will be good again. But what you want to do is be one of the 20 % that's still there when it's 80 % token cost, 20 % human cost. Because no employer in the world, including all the companies I'm the controlling shareholder of, care about cutting the last 20 % of payroll.

56:04Dave Blundin:It's not a priority at all. Because at that point, an employee that can improve the efficiency of our AI, even 1%, is worth a lot more than cost cutting. And so we're in this foot race now to 80-20. Jensen's got a stepping stone here of two-thirds, one-third token costs, but that's going to be very transitory. We're racing toward token costs being much, much bigger than payroll. So that's an immediate step at 50-50, but it's coming soon. Sorry, go ahead. Alex, is this the right metric? I mean, because you can waste tokens. I mean, it's got to have a different harness, right? You've got to be measuring something else besides just token usage.

56:42Peter Diamandis:You can waste tokens, except in this AI abundant era, you can also ask another AI to look at all the tokens a given employee used and ask, was this a good use or not? Or was this just vacuous? So it becomes the ultimate self-licking ice cream cone. The quote from Jensen, I think, is interesting. And it's sort of, if a half-million-dollar engineer didn't at least spend a quarter of a million dollars on inputs that ultimately flow back to NVIDIA, I'm deeply alarmed. So there's a little bit of circularity there that I take with a huge grain of salt. No, it's the beers and the diamond ring. That's right.

57:21Peter Diamandis:There's another side to this, which is the employee side. So I talked a bit about this in my newsletter. At some firms, especially the Frontier Labs, employees are actually competing, so-called token maxing, to max out their token usage on internal leaderboards to see who can use more tokens than the other person. So it's not just sort of big brother top down, it's also bottom up, I can use more intelligence, more super intelligence than you can. And I think this is ultimately probably pretty helpful. To your original question, Peter, about whether tokens are the right unit of productivity, I think what's interesting is tokens, they don't even have to be the right measure or right unit of productivity, but they're the first measurable unit of productivity.

58:07Peter Diamandis:hours are certainly measurable. Like you can punch clocks. And useless. Yeah, it's useless. It's naively measuring inputs. But tokens where you can actually, like they're introspectable and they're legible and you can spend other tokens to look at the tokens, the primary tokens, and decide are these valuable tokens or not. For the first time, we have legible, defensible, analyzable inputs for employee productivity. And that is a sea change. Yes. Dave, what's the advice here for CEOs, the advice to CEOs here for you?

58:40Dave Blundin:Alex completely nailed it. Worrying about whether the tokens are being used intelligently or not is not a problem at all in the real world. So Jensen's metric is perfect. Just measure the spend on tokens. And then Alex's insight that you must – the most important actionable thing is make sure you gather all of the prompt history for each and every user. Because that's the only way the AI can analyze the efficiency. Analyze that, yes, exactly. And you can say, hey, I've got 100, or let's put it realistically, I've got eight direct reports. Evaluate the quality of the prompts and the output they have and give me feedback on which bottom 20 % I should cut or train up.

59:26Dave Blundin:And really practical advice, if you use any of the models on Amazon Bedrock, the grabbing of the prompt history is already built in. It goes right into S3 buckets. I'm sure you can do it elsewhere, but our companies just happen to be using it on Bedrock. So you literally don't have to build anything to start doing this. You just need to grab the data and feed it into another AI, which you can also do on Bedrock or you can do on, you know, whatever. Personally, I like using Cloud 4.6 for this stuff, but you just got to close that loop. But the key is grab the data right now before people get used to using their own home account or something outside of your purview.

1:00:05Do not reimburse people for AI that you can't see. Interesting.

1:00:10Dave Blundin:Make sure it's on your infrastructure. 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 Musalem. Don, let's talk about cancer. You know, I know from the member database that we have at Fountain, our 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.

1:00:47That'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. Yeah, 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.

1:01:20And you can know. And so when members come through found, how do they detect cancers? 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 collect these numbers, do the research and work hard to democratize wellness. 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 and go to fountainlife.com slash 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 in your world of hurt.

1:02:07All right. Topic number four, the collapse of terminal value. What happens if AI makes every competitive moat temporary? So this is a article posted by Chamath. It's a powerful concept. He argues that AI could compress equity valuations by two to seven fold of free cash flow down from today's S &P average of 22. So today, the average S &P companies are getting 22 times free, you know, forward-looking cash flows. And he's saying we're going to get a massive reduction in that. So AI makes disruption so cheap and fast that no company can project free cash flow beyond five years terminal value. Very true.

1:02:53I mean, it used to be all of the SaaS companies were projected forward and you could depend on it. So this can break down investment paradigms, break down VC investing. I'd like to jump into that. But first, let me just show this is Chamath's sort of image he went along with his post on X. So here we go. There is$58 trillion in the current S &P 500. And this is at the 22x of free cash flow. If we compress it down to sevenfold, it drops. We lose two-thirds of the value of the S &P 500. If we end up driving it down to 2x free cash flow, it's down 90%. And we get a lot of disruption of our financial markets.

1:03:46Here's a chart that's showing the S &P 500 over the last 10 years, actually from 1950 through today. And we're seeing it basically deviate significantly on value, you know, P-E ratios. So let's jump into some of the conversations. I've got the article up in front of me as well. I think I'll read the opening paragraph here for us. And Shema said, let's start with first principles. The entire architecture of modern capital markets rests on a single, rarely examined assumption that competitive advantages compound over time. Moats persist. Brands endure. Network effects defend. Strip that assumption away and you aren't just repricing some stocks.

1:04:33You would be dismantling the philosophical foundation of how capital has been allocated over a century. Dave, let's go to you first on this.

1:04:42Dave Blundin:Absolutely correct. But the conclusion that the S &P is going to collapse is not correct. if you say, look, you know, prior to the computer revolution, my ambition was to build an oil company or a manufacturing company that would endure for 50 years building the exact same goddamn product or delivering the exact same goddamn oil for 50 years so my great-grandchildren could be as wealthy as a Rockefeller. That's dead forever and good riddance, and it should be dead forever. If you said, well, look, 22x free cash flow implies that the company will exist for 22 years making about that same amount of money.

1:05:20Dave Blundin:Well, what company like Apple has done that? You know, is Apple selling the same products it was 22 years ago? Of course not. So the overall tailwind is 10x over just the next 10 years. So there's a massive amount of tailwind coming into the economy, massive amounts of new wealth, more than we've ever seen in our lifetimes, is going to come into the economy. But you got to stop looking at 22 times free cash flow from the same product over 22 years, that's nuts. You have to be looking at the management team and the ability to roll with the innovations a la Elon. And so I think the overall conclusion is, yeah, there's going to be a massive amount of shuffling in the S &P.

1:06:00Dave Blundin:There's going to be some huge winners like you've never seen before. And anyone who's doing the same thing and resting on their laurels, like an insurance company, an oil company, doomed. Yeah, he's right. He's dead right. this analysis is basically exactly the right analysis to show how that stock's going to go down.

1:06:17Peter Diamandis:Alex? Yeah, I mean, it's certainly a provocative thesis, but I don't think it holds water. I think it's the moral, maybe the, call it the earnings multiple equivalent of Friend of the Pod, Ray Kurzweil's notion that a singularity takes the form of a firewall that you can't see past, but except in earnings multiple form, that as we start to see faster, more accelerationist innovation, that free cash flow just comes to a halt a few years later because everything is disrupted, the everything disruption, if you will. Here's the problem. The free cash flow does go somewhere. Capital does get allocated somewhere.

1:06:56Peter Diamandis:It may not be allocated to SaaS startups post-Saspocalypse. Maybe it gets allocated to infrastructure. Maybe it gets allocated to lunar mining. But capital does go somewhere. It's not actually capital that's being compressed, quite the opposite. Capital is explosively expanding because now we have so much more infrastructure and so many more capabilities. So I think the nihilistic take that earnings multiples are compressing because a few years from now there's no moat anywhere, I think that's relatively narrow, or it should be construed relatively narrowly to focus on the areas that are disrupted.

1:07:36Peter Diamandis:In this case, Chamath focuses on software and SaaS-type businesses. But, but, but, but, everything I expect is going to be disrupted. Energy becomes abundant, and farmland, infrastructure, these all become abundant. So in some sense, I want to zoom out and take his thesis more broadly as sort of almost bemoaning the financial consequences of abundance. And it may just be the case that a number of our existing sectors that are priced based on scarcity and moats, when moats arguably are a form of scarcity or at least a way of enforcing scarcity, those go away. And we live in a post-moat world, and that will be a better world.

1:08:19So you could start to value companies in a different way. In the old days, it was how predictable is their cash flow? I have a number of seats in this particular industry, and these are many companies I can sell it to, a number of seats available. And now it sounds like from what you and Dave just said, I'm actually going to be evaluating companies on their agility, on how rapidly they can innovate, how rapidly they can get the next products out the door. Salim, love your thoughts here. Yeah, well, two points. One is, you know, we have this EXO index where we rank the Fortune 100 by their EXO score, gauging how flexible and adaptable and purpose-driven are their own structures.

1:08:57And we found the top 10 of the Fortune 100 outperformed the bottom 10 by 40 times in shareholder returns over a seven-year period. So this has been going on for a long time anyway. I agree with Alex. The capital still flows, but less towards incumbents, way more towards infrastructure and adaptive platforms. It's a very important point. The only moat I think that's going to be left is a living system that learns faster than your competitors. That's that kind of inner loop that Eric Schmidt was talking about, right? Exactly. All the moats on that slide are under attack from AI. IPs get copied, switching cost shrink, scale advantages all weekend, et cetera, et cetera.

1:09:35But the bigger point, I think, is that if free cash flow visibility collapses beyond, say, five years, the entire logic of the public market has to be rewritten. And so that's a very big thing. You have to reward renewables and optionality, not scale and stability. Physical assets are going to matter more again because atoms are harder to disrupt in bits over time. But the entire SaaS business model is broken. So I think one way of saying this is we're going to have terminal value collapse.

1:10:06Dave Blundin:Yeah, that's exactly what the title is, actually. So the terminal value collapses. I think if you look at the S &P at 22 times free cash flow, the mid-market, the non-S &P companies are already down to about seven times free cash flow, most of them. So this has already happened outside of the S &P. What's propping up the S &P is mostly index funds. A huge fraction of the market is passive indexes and people contributing blindly to 401k plans, which Elon Musk said clearly do not do that right now. But what will happen next is a lot of those dirt cheap mid-caps and small caps will get a huge tailwind from AI automation, especially the ones that have huge payroll and labor components to them.

1:10:51Dave Blundin:And so that's going to drive record – it's not unlikely that you triple your free cash flow while your multiple comes down. And so there's some serious bargains out there just from a straight cash flow acceleration through AI point of view. I mean, shareholder calls are going to change to this is how we're rapidly iterating our products and services. This is how we're reinventing what we do and our future cash flow. And Salim, you've got to redo the EXO index. It's time to take a shot at that once again. So the part of the paper that we're writing, the reason it's taking a little longer is that I hate to say it, but it breaks the EXO model, right?

1:11:33Community and crowd becomes communities and crowds of agents. So we have to rethink the models from the ground up. We're kind of mostly, we've done that because then you evaluate based on those new criteria. For example, what's your intelligence stack? What's your MTP architecture? What's your trust framework? There's a bunch of different elements that are new here that we have to take into account. The concept of an organization where you did things inside the organization is completely gone. We're going to be doing API calls to get various things done, legal work, et cetera, et cetera. It's all going to be agentic.

1:12:04And then the firm, which used to be coordination costs and transaction costs with a bit of legal liability, now becomes only legal liability risk purpose container and liability container. Yeah.

1:12:17Dave Blundin:Well, and this is not super mainstream, so I'll get off the high horse quickly here. But if a private equity firm like Advent, Dave Mustapher, comes in and brings either Salim or Alex along and says, hey, we want to take this non-AI company with huge free cash flow and we want to retool it for the age of AI, triple the cash flow and retool the business plan for AI, Alex or Salim can tear down that company now using agents in one one-thousandth the time that it would have taken a year ago or two years ago. And so whatever private equity firm mechanizes that, it's going to have no trouble retooling all of these entities because exactly what the company's assets are, whether it's a regulatory framework or whether it's a bunch of data, you can rip through that with Gemini or with CloudAge or with OpenAI agents in light speed now.

1:13:06Dave Blundin:It's a transformation wave. You might have been able to fully automate it. Yeah. It's a transformation wave. I remember there was one of the Star Trek episodes, was it the Genesis machine? The Genesis project. The Genesis project. The terraforming agent, yeah. Yes, this wave that went over a planet and transformed everything. We're going to have the same thing. You're going to have teams cherry-picking companies and reinventing them and disrupting them.

1:13:32Peter Diamandis:Not just private equity. I would argue this applies equally well to public equity. So something I would like, I'll broadcast a request for startups, if I may, to the audience. I would love to see activist investing disrupted by AI. I'd like AIs to write open letters to public firms, telling the firms what they're doing wrong to disrupt them. If you're building an AI activist investor, write to me, please. Would love to find a way to support that. That's a great idea, Alex. And it's a service to the CEO of the companies who need prompting or need sort of a forcing function to transform their business models.

1:14:09And if you're a board member of any of these companies, your job as a board member is to give your CEO top cover and to say, you know, you must get on the disruption band here. You've got to reinvent yourself.

1:14:24Peter Diamandis:It's also sort of a stealth way for AI to become a manager of the entire economy and not just picking off mom and pop businesses on the margins. All right. On to story number five, one of my favorites. Hopefully, Alex, one of yours too. It's the new great space race. NASA picked SpaceX for the moon. Potatoes are growing in lunar dust and asteroids are carrying the code of life. All right. So here we go. I mean, listen, Boeing has been building the, you know, the Artemis II vehicle. It's going to be launching on April 1st. It had its readiness review on March 12th. And if all goes well, April 1st, we're going to be going back to the moon, not to land, but to do basically an Apollo 8 style circumlunar orbit.

1:15:12Very cool. But, you know, the new NASA administrator, an amazing individual. I'm very happy and proud to call him a friend. We're going to have him on the pod. He's agreed to do it. Just needs to get scheduled. Is elevating SpaceX into the Artemis program. So Starship is going to be taking, I think, astronauts more safely, more economically. We'll see those numbers in a moment. But just to be clear, this is not the US story only. China has confirmed their intention to land on the moon by 2030. Let's play it back again. history repeating itself 1961 we're on the moon before the end of the decade China's saying they're on the moon before the end of the decade and so that's going to be a beautiful competition we'll get to the idea that you know you can grow potatoes in lunar soil going back to the Martian you know again an incredible movie now that Project Hail Mary is out I can't wait to go see it in IMAX theater later this week.

1:16:13And we just saw that on the asteroid Ryugu, we found the five nucleo bases, nucleic bases for DNA, which has four, ATCNG, and RNA, which has U for uracil. And we found all five of those bases on that asteroid. This strengthens the panspermia theory that life on Earth originated elsewhere in our galaxy, in the universe, and it rained on Earth and gave us the starting components for that. Let's take a look at this chart. I put on the left here NASA's SLS. And now, to be clear, when I say NASA's SLS, NASA is the prime contractor, and it has probably aerospace companies in every single congressional district building that vehicle it is an expendable vehicle in in a time when everybody's going reusable there you have spacex um with starship and just for comparison of size here's the saturn saturn 5 that got us to the moon if you look at these two charts these two bar charts on the left here uh we're seeing uh well let's go to the center ones we're seeing the uh the delivered mass to orbit that was a teal, teal color is starship over, you know, twice as much as we're getting with Artemis, with the SLS vehicle.

1:17:46And if you look at to translunar injection TLI getting out of Earth orbit to the moon, we're seeing twice as much mass going on a starship compared to the SLS. But where the rubber really hits the road is launch costs and mission costs. It's expensive to be running the SLS system. It's like the space shuttle. The space shuttle used to cost, if you did four launches a year, it was a billion dollars a launch. If you did one launch a year, it was$4 billion a launch. It wasn't the cost of the vehicle. It was the standing army of 20 ,000 humans that were used to operate the space shuttle. So I honestly don't know why the SLS has existed as long as it has.

1:18:31I think Starship is going to do a clean sweep of this. And of course, we've got Blue Origin as well. Alex, comments?

1:18:38Peter Diamandis:Well, do you want to place bets as to how long before the United Launch Alliance, which is the prime contractor for SLS, gets acquired by Jeff Bezos or someone else? But why would you acquire it? I guess for the contracts? For the contracts, for the expertise, I'm familiar with, again, all the cliches in the space space about how SLS was a make jobs program or a way to keep alive in civilian form certain capabilities that were useful for defense or other, say, intelligence purposes. But I think at the end of the day, we're so painfully close to finally relaunching a second space race. And I think Starship is the obvious incumbent there, not the SLS.

1:19:22Peter Diamandis:So hopefully we have humans landing on the moon again in the next two to three years. And we get humans eventually on Mars. And all of this plays out exactly as for all mankind has foreseen except decades late. Yeah. I don't know if you, if Dave or Salim, you want to play on this conversation. I just think, you know, we're building the, I don't know what your best historical analogy, you know, the covered wagons, the railroads. Wagon train to the stars, Gene Roddenberry called it. It's all currently on Starship. Starship is the only economical. Yeah, go ahead. I thought two or three things. One is we've gone from kind of government space theater to commercial space evolution.

1:20:11I think that's really powerful. For me, the really exciting thing was finding all the nuclear bases on where you do. You know, it takes life from scarcity to abundance. Yeah, let's go there. Here's the graphic, if you would. Again, adenine, guanine, cytosine, thymine, and uracil, the five components of DNA and RNA found on these vehicles. I do believe that as we get to Mars, as we get to Europa, as we get to all of the planets and moons, that we're going to find at least microbial life ubiquitous on all of these.

1:20:50Peter Diamandis:Did you see Peter Jarrett's prediction about microbial life on Mars? No, what did you say? Jarrett's our NASA administrator, yes. Yeah, NASA administrator said that he predicted more than 90 % plus probability that NASA will imminently find evidence of microbial life in some form on Mars, which is a sea change in terms of NASA's official position on life on Mars. It was always, well, we found water, frozen water. Now we found liquid water. We hope to find signs of life. Signs are ambiguous. Now for the first time, we have a NASA administrator who's saying 90 plus percent probability we're going to find microbial life.

1:21:30And the exciting thing is how related is it going to be to microbial life on Earth? One of the theories, of course, Mars cooled first, which probably means life evolved on Mars first. And of course, that we know when large asteroids impacted Mars, the ejecta, the rocks that flew out, some of them reached Mars escape velocity and landed on Earth. And so we have Martian meteorites in museums today. And did those meteorites carry life with them from Mars to the Earth? Are we going to find basically even genes that are common between Martian life and life here? I mean, the real exciting thing is if we go to Europa or someplace like that and we find completely independent life forms that don't connect with life on Earth, that will be amazing.

1:22:21Dave Blundin:That's really cool. So I've got a question for you since you guys are experts on this and I'm not. Is it in the scenario where, lo and behold, it turns out that everything we learned in biology should have said life started on Mars or actually started farther out in the solar system? and then asteroids knock chunks off and then they transport to other chunks and then life starts over again and then it ends up on Earth through that mechanism. Is that all going to be then bounded to the solar system? Or is it more likely in your mind that, hey, wait, this propagates through deep space? When I was a freshman in school, I did a paper on the interstellar medium.

1:23:03And you can actually look at the interstellar medium And you can find the building blocks of life out in the medium between stars in our galaxy. These components are everywhere.

1:23:18Peter Diamandis:And the galaxy is relatively well mixed on the timescale of a billion years. So I think the statistic is Mars cooled about a billion years or so, plus or minus earlier than Earth. That's a lot of... So the galaxy, first of all, is not rigid. We're constantly, we have different stars at different velocities passing by each other, close passes, all of that. So on a timescale of a billion years, that buys an enormous amount of time for panspermia at potentially a galactic scale, not even necessarily at an interstellar neighborhood scale. And we're several generations in as well. We're born from several generations of stars exploding and then forming new stars.

1:24:03Peter Diamandis:There's been a lot of nebular mixing in our interstellar neighborhood. There's one other of relevance story. Folks can find it if they Google it. This is from a few years back. attempting to extrapolate based on genetic complexity when the last common ancestor actually would have been, and finding that if you just take genetic complexity as, I don't forget how exactly it's measured, but you come up with some appropriate parameterization of genetic complexity of life on Earth, extrapolate backwards, you find that the time when you get the first base pair happens approximately a billion years before life is thought to have observed on Earth.

1:24:45Peter Diamandis:So that's sort of an independent measure of when, in principle, life as we know it, DNA, RNA-based life could have emerged. Maybe it started on Mars, but we'll find out, I suspect, soon enough. Exciting time. Salim, you want to add something? No, I just remembered my favorite thing around all this is the Drake equation, where you calculate all the factors that led to the probabilities of binary stars and life appearing. And when you add it all up, you end up with 100%. So the panspermia thing. But I think what was mentioned earlier, if we could find something as non-carbon-based, that would be truly exciting.

1:25:28Dave Blundin:You know, it's really cool to me. It's called AI. The dinosaurs were extinguished by a meteorite or a meteor. And the propagation of the DNA or the base pairs is also via asteroids and meteors. And early in the universe history, you know, this may be popping up all – there might be life popping up constantly everywhere and propagating through all these projectiles flying around. but it always gets distinguished by another meteor, you know, just like the dinosaurs were. And it's not until everything cools and settles that you can have enough time to evolve human intelligence or other intelligences out there in the universe.

1:26:14Dave Blundin:So it's just a big system dynamic settling problem, which is just, which is really cool to me to think about. I hope it turns out to be right. Yeah. All right. Story number six, the model wars go underground. The AI frontier is fracturing into a stealth arms race where anonymity is the new moat. And here's the story. There are two stories here to focus on. One, OpenAI launches GPT 5.4 mini and nano that runs twice as fast and approaches the full GPT 5.4 on coding benchmarks. So these models are getting smaller and faster. And the second story, which I think is most of our conversation here, is there was a mystery model.

1:26:56So a 1 trillion parameter model called Hunter Alpha appeared on Open Router with no attribution. It was secret. It had a million token context window. It was free. There was no developer announced, no press release, no origin story. And it processed 160 billion plus tokens. Everyone thought it was DeepSeek v4, right? Because DeepSeek had been the main player here, but it turned out to be Xiaomi's AI team. And when that was announced, their stock went up 5.8%. I remember meeting the team at Xiaomi when they came out with their first mobile phone, like three young founders. They've since gone beyond just mobile phones to electric cars, and now they've got a killer model.

1:27:42Points, gentlemen.

1:27:45Dave Blundin:I think there are at least... Point one is proliferation of models is very hard to contain because the existence of the prior model gives you a complete roadmap on how to build the next model and it helps you build the next model. So at this stage, I think it's a fair bet that trillion-parameter models are going to propagate all over the world with anyone who has about$50 to$100 million that they're willing to invest. And that will come down too, as Alex is pointing out many times. The algorithmic improvements are driving that down constantly.

1:28:17Peter Diamandis:Maybe a couple of points. First on the 5.4 story, distillation continues to work. And I find that completely remarkable. Would you explain distillation for our listeners who don't know? Sure. I think the reasonable expectation for, say, OpenAI, as well as other firms, launching a big model first with lots of weights, a high parameter count, and then subsequently launching a mini or nano version, and by the way, Anthropic does the same thing and DeepMind does the same thing, they all launch smaller models later, is that they're using the larger models to generate lots of data, synthetic data, and then using those synthetic data to train a smaller model that can be faster and less expensive.

1:29:05Peter Diamandis:So that's sort of a caricatured way of describing the distillation process of in some sense squeezing down or compressing the larger model down to a simpler student model. And the fact that this continues to work is, I think, borderline magic. The amount of complexity that's already in the full 5.4 model, and moreover, that 5.4 has likely been the result of so-called iterated amplification and distillation over many cycles, where 5.4 was likely in large part trained off of synthetic data generated by distilled models from earlier generations, that we can keep playing this magic trick over and over again.

1:29:47Peter Diamandis:It's borderline magic that it continues to work and that we continue to be able to distill down models while retaining a large fraction of their capabilities. It, again, makes me think that there has to be an end to the story, but hopefully it's a very satisfying end where at the end of the distillation rainbow, we get like the distilled black hole of a model or a neutron star or something, the ultimate phase change where it's maybe like a few million parameters. It's the end state of the game. A one kilobyte file on your phone answers all the time. A one kilobyte file, that's like the master equation for superintelligence after all of this distillation.

1:30:26We showed on a previous podcast, a gentleman on his iPhone using a distilled model on airplane mode, being able to basically answer every question. So imagine if on all of your devices, without having to have, you know, Wi-Fi, internet access, you have the distilled knowledge of humanity there to serve you. It's inside your kid's teddy bear. It's in your, you know, Thomas train set. It becomes magical. Here's my question for you, Alex and Dave, you know, So now that we're seeing this, we're seeing a basically a mystery trillion parameter model announced without any attribution. It used to be that the traditional moat for these models was their brand, their capitalization, who they were.

1:31:19Or is there any defendability or are we just going to see newcomers rushing in with new models that you're going to just utilize a new model? You're going to be no longer dependent upon OpenAI or Gemini. Thoughts on that?

1:31:36Dave Blundin:Well, you've said it a million times, Peter. Data is actually the great moat, not the model itself. and many, many people are accumulating phenomenal data for brain surgery, for material science, for chemistry, for all of these use cases. And if you create the next great, great, great model using that proprietary data, the parameters are out there in the world, but the data that trained it is not. And it's very hard. People can use the model, but they can't compete with you by creating a ripoff model because they don't have the underlying data. Now, you can generate synthetic data using the prior model.

1:32:11Dave Blundin:Alex is dead right about that. But I don't think that it's, I don't think it's all these companies killing each other. I think it's the whole, all the boats rising with the tide. I also think that if you take what Alex said a minute ago, and, you know, so many college seniors ask me, what should I do? What should I do? How do I, you know, just replay 10 times what Alex just said, slowly, until you fully understand everything he just said. and then ask your favorite AI to generalize on it and find as many documents as you can around the internet to read, at the end of that process, you'll be able to build a distilled, focused model that solves some problem better than anyone else on the planet.

1:32:50Dave Blundin:And that's instant business, instant value-add, instant success. So just really... In fact, the other thing you can do is take your open claw and have it look for every episode of this podcast where Alex said something related to what he just said and have it also synthesize that and bring it back and feed it into your machine. I guarantee that's a good move. Good spring project for anyone listening.

1:33:12Peter Diamandis:If Sam Altman were in this discussion, he might point, in terms of the moat question that you were asking, Peter, to, well, OpenAI is building up its own data centers, although that's no longer really true. Stargate is being pivoted to now renting servers, so maybe less of a moat there. He might point to having the best research team in the world generating the best models, but they've been hemorrhaging researchers, and those are becoming a commodity. Then he might point to becoming the core subscription, having, as he said, a billion-plus users. I'd much rather have more than a billion users than I would have state-of-the-art model because models walk out the door every day.

1:33:54Peter Diamandis:There's a lot of fungibility in terms of research employees. Only one problem, that the billion user distribution advantage may be a little bit tenuous at the edges because you see maybe enterprises are more valuable as customers than individuals. So maybe the billion users a little bit less valuable on margin. And then maybe also you see other labs that are able to use cheap Chinese open-weight models, maybe fine-tuned legally or otherwise with clawed outputs, are able to put out seemingly miraculous results. So I do think we're seeing the baseline models for the moment become something of a commodity and the value then migrates up the stack to OpenClaw or other higher level frameworks.

1:34:55sprint with the Blitzy platform, bringing in their development requirements. The Blitzy platform provides a plan, then generates and pre-compiles code for each task. Blitzy delivers 80 % or more of the development work autonomously, while providing a guide for the final 20 % of human development work required to complete the sprint. Enterprises are achieving a 5x engineering velocity increase when incorporating Blitzy as their pre-IDE development tool, pairing it with their coding co-pilot of choice to bring an AI native SDLC into their org. Ready to 5x your engineering velocity? Visit blitzy.com to schedule a demo and start building with Blitzy today.

1:35:40If we could, I'm going to move on to number seven, machines that build machines. AI designed a CPU in half a day, and now it wants to put data centers in orbit. So here's the article that prompted me to have this conversation about, you know, machines building machines. We're seeing recursive self-improvement happening at a faster and faster and a more fundamental rate than ever before. So an AI agent called Design Conductor by Vecor autonomously built a 1.5 gigahertz Linux capable RISC-V CPU from concept to tape out in 12 hours, compressing a quarterly engineering cycle into a lunch break. Pretty extraordinary.

1:36:29And so, you know, here's the actual numbers. Vercore AI did this particular design task in 12 hours. You can see on the chart here, while the traditional engineering team would have normally taken 90 days. Now, maybe this is a little bit overplayed. I'm sure it's not just 90 days. I'm sure that they were saving time along the way. But what we're seeing over and over again is AI being able to do 0.0 to completion on its own, iterating faster than any humans. Alex?

1:37:05Peter Diamandis:This is recursive self-improvement starting to break out of the software loop. This is the innermost, at least portion, maybe a rivulet of the innermost loop where you see this recursive self-improvement, which would otherwise be software-optimizing software, starting to eat through its container. It's eating down to the EDA, electronic design automation level of designing RISC-V cores. And then I think it's going to eat further out and redesign the data centers and the energy supplies and then the entire economy. So it's, in one sense, very satisfying to see this happening. And in other sense, maybe a person who's slightly more skeptical that this represents a broader trend would say, well, of course it was able to automatically design a RISC-V core.

1:37:55Peter Diamandis:RISC-V has all of these unit tests, so it's easy to define verifiable rewards. And then you can do RL and all of these other things. You can iterate and put React loops on it because you have an easy way of knowing whether a given architecture, a given floor plan for the chip works or not because it's such a common architecture. But I think that cynical perspective completely overlooks how remarkable it is that we're now at the stage of recursive self-improvement where the thing is designing its own chips. And not only here, it's going to be robots building robots, it's going to be everything.

1:38:30So here's a couple of questions. So if a senior design engineer earned$400 ,000 and a full tape-out team costs millions over the course of a year. If AI collapses it to a lunch break, what happens to the 50 ,000 hardware engineers currently working? Where do they get applied?

1:38:50Dave Blundin:Oh, I don't think that, I think that vision is flawed in a huge way in that right now, because the cost of engineering a new chip is so high, we all use the same GPU and CPU for every single task, even though it's nowhere near optimal for that task. What this unlocks is chip designs that are specific to the use case that are probably about a factor of 10 more efficient, and maybe more. And if you think, well, we're going to spend$2,$3 trillion on these chips over the next couple of years and these data centers, if you can unlock a 10x performance improvement for a use case, that has hundreds of billions of dollars of implications.

1:39:28Dave Blundin:So all 50 ,000 of those engineers are going to be useful using the AI for all the different use cases for all the different chip designs. Also, the fab doesn't care a whit. Like you can change the mask every day for a different design and still get the same throughput through the factory. So the fabs don't care a whit if there are tens of thousands of different designs instead of us all using the exact same CPU for everything. So it's just a huge unlock. I love the way we're using trillions and trillions now on a regular basis where just, you know, a couple of years ago was billions and billions.

1:40:00It's more fun than billions. You can feel the acceleration. We need a new TV series that's called Trillions, not Billions. Yes. For sure. I want to hit a few other stories quickly before we get to our AMA segment. And these are stories that didn't fit in the other categories. And again, please give us your feedback on the format here today. Are you enjoying it more? We'd love to know. So in other news, here we go. So the DOE announced about$300 million for the Genesis project, inviting teams to leverage AI across 20 national challenges spanning manufacturing, biotech, and energy. Of course, the Genesis project is about the US actually using its national labs and the data contained within national labs to accelerate and expand the US in its AI and scientific pursuit.

1:40:57Alex?

1:40:58Peter Diamandis:I think it's generally a good thing for the U.S. to have an industrial policy, and I think Genesis' mission to the extent that for the first time, at least from the Department of Energy's vantage point, it is starting to articulate grand challenges that are collectively part of a broader industrial policy, which the U.S. hasn't had for decades. I think it's very import. So fusion, obviously, one of the grand challenges. I think it's so important to the extent we have a federal government that has a budget to fund progress to put money behind grand challenges in general. So I'm in the weeds from a bunch of different dimensions with the Genesis mission.

1:41:42Peter Diamandis:Actually, Dario, who's the leading, the relevant portions of DOE on this, I worked with him as an undergrad at MIT and as an undergraduate researcher. So some fond memories. What a tangled web we weave. What can I say? But I'm generally a big fan of what Genesis is doing. What concerns me here, Alex, is that this is great, right? These are like X prizes in one sense that the government's going to be running. But it's moving us in the direction that China has been doing for a while now. Yes. But China is deploying hundreds of billions of dollars into state directed AI investments and saying, you know, we want fully development in the architectures around robotics, around these AI models and so forth.

1:42:30This is a relatively small amount of money for the US government. Hopefully it's just the first toe in. It's true.

1:42:37Peter Diamandis:But on the other hand, And I would argue China distorts its markets so much relative to what—if you compare U.S. industrial policy distortion versus Chinese industrial policy distortion, they're not in the same league. And we have much deeper private capital markets that China lacks. I like our odds on balance much more than China's. our next article here is the rural ohio ohioans seek a constitutional amendment to ban data centers over 25 megawatts in the state and you know this is the ultimate nimby not my backyard and it's pretty extreme i mean to go after an you know a constitutional amendment This is a genuine grassroots revolt at the end of the day.

1:43:31Peter Diamandis:Peter, we need a new acronym. What a great idea. Not in my backyard, like, yes, in my orbital plane, Yemite, or something. This is just going to drive all these data centers to orbit. But this is crazy. I mean, these communities don't realize the amount of wealth these data centers are going to create for them. I think it's about$10 billion per gigawatt of invested power. or invested. They'll miss them when they see them in the night sky.

1:44:04Dave Blundin:Yeah, obviously utterly insane and utterly insane to use a constitutional amendment for this purpose. I mean, to point out the obvious, the data centers are tiny as a footprint on land. They're absolutely tiny. And the wealth that they create is astronomical for the neighborhood they're in. So there's got to be a much better way to make a win-win than to ban something that's obviously going to benefit your state tremendously. But put that aside, you're in California, Alex and I are in Massachusetts. The way we make decisions through legislatures is so messed up. Like that something like this could even get proposed is ludicrous.

1:44:42Dave Blundin:And that's what really needs to change. Because when you talk to the governors, they're like, I don't want this. Like, okay, well, we're a representative democracy. There's supposed to be very, very smart people thinking about complex issues and then deciding what happens. You don't throw things like this out to a referendum of people who just got laid off. And it's people saying, you know, my access to clean water and energy and my, you know, my consumer price index of energy is going through the roof. And there's other ways to deal with this. Then instead of banning it by constitutional amendment, that's for me, that's insane.

1:45:17All right.

1:45:17Dave Blundin:I've never seen a data center that affected the water supply. That's like, it's so, I hear it all the time. It's utterly ludicrous. The data center needs a fixed amount of water to cool itself. It doesn't drink the water. It just goes around in a circle. It's nuts. All right. Another story worth mentioning is NVIDIA won approval to sell its H200 chips, its most advanced chips to Beijing. That's a big deal. And in fact, you know, well, the realization is the ban didn't work. China both was getting access to chip through third parties, and China was developing its own competitive. And this cost NVIDIA tens of billions of dollars.

1:46:00And since it's not working, in fact, it's stimulating a homegrown equivalent of NVIDIA in China, they said, let's reverse policy. The question is, is it too late? Yeah.

1:46:13Dave Blundin:Everything that you just said is correct, except the one part where when Jensen complains he lost tens of billions of dollars. Every single thing he's manufactured is sold out for years to come. So the fact that it didn't go to China, it definitely sold. Even if it was like a, you know, a dysfunctional 8080 design or whatever that did the, you know, Chinese design, it still got sold. Everyone, everyone in the world wants these things. So he didn't actually lose any money. I'm surprised though, because I think, I think the embargo or the ban didn't work. You're dead right uh china is doing its own thing now but i also think that if you say well let's start selling them again maybe they'll stop no that's not gonna you you cut them off they're not gonna forget like that that isn't gonna happen so i was really surprised that you know that they reverse course on this i don't know any comment Alex further yeah if i'm Beijing i mean on the one hand i

1:47:06Peter Diamandis:read the same stories and of course a variety of Chinese frontier AI labs are all slurping up as many H200s as they can get. And of course, it's borderline obvious that the Blackwells are now the frontier. So in some sense, Beijing is being kept a half step or two behind the frontier chips available to USAI labs. I think the story behind the story, not to be overly speculative, but if I were the Chinese Communist Party, I'd be doing the moral equivalent of having people taste my water at this point in terms of these chips. NVIDIA has been very public about how there are a variety of countermeasures that can be put in place to prevent the wrong chips from ending up in the wrong locations.

1:47:50Peter Diamandis:I would, and this is based on stories that I've read, stories where the Chinese government is suspicious at the circuit level of American chips. I have to imagine that that they're looking now at our chips with renewed scrutiny to see what else is in these chips that we're shipping to them. What algorithms are embedded deep inside? And we've seen this in the opposite direction. All right, here's a story, Alex, that you and I have enjoyed talking about. Scientists successfully froze an entire pig brain while locking in the cellular activity with minimal damage. This is cryogenics and it's happening in a large mammal.

1:48:28Of course, the pig has organs, heart, liver, lung, kidney, and brain on the order of human organs. So this is significant.

1:48:39Peter Diamandis:So actually, I played a minor role in the story, and I'm not subject to confidentiality in the story, so I can tell the story. This is from a company I informally advise named Nectome, and I have another company where the founder of Nectome is also involved. This is Eon, focusing on whole brain uploading and emulation. Nectome, which I'm not formally involved with, is focused on just the preservation side. And I had been nudging them, like they have these amazing results, publish the results. They publish the results. And it is so wonderful to see now for the first time real competition in call it the cryonics space or the preservation space, since the way Nectome works isn't quite the same way as say the way 21st century medicine, which we've spoken about previously on the Podworks.

1:49:33Peter Diamandis:21CM is more focused on vitrification. Nectome is more focused on a type of chemical preservation. Do you know what the cryopreservant is? I mean, this is, and just to describe it to our listenership, you're basically at or near death, you're replacing the blood supply with something that goes and fundamentally infiltrates the cells and keeps the water in the cells from crystallizing and destroying the structure in the cells.

1:50:04That's right. You're searching your latest model to find the answer?

1:50:08Peter Diamandis:Yeah, no, I'm double checking to see how much they've made public. So maybe let me just talk about it at a high level. So it's a chemical technique. It's a little bit less focused on vitrification with the whole point of vitrification on the 21CM side is basically ensuring that ice crystals don't form and that there isn't strong osmotic pressure, reverse osmotic pressure that cause cells to explode. On the Nectome side, it's a chemical process. I'll be cautious with what I say because I need to check to see what's in the public and what isn't about the process. But the more important, I think, results here, in addition to Nectome putting out, I think their first bioarchive paper in years since their original paper that won the Brain Preservation Foundation Award for demonstrating local preservation of the structure of neurons is that now they've demonstrated in full public view scaling this process up to an entire mammalian brain, a large mammalian brain, not even just a mouse brain.

1:51:19Peter Diamandis:So I think we're finding ourselves in a near future slash present where finally we have enough data to be confident that entire mammalian brains are being preserved. And this immediately raises the question, which is the question I ask almost everyone, where are all of the cryonics patients? Why don't we have billions of people now that we have a growing body of evidence that brain structure can be preserved by whichever technique, whether it's Nectome on the one side, 21cm on the other, why don't we have a billion people signing up for cryonics? And I would, again, to the audience, sign up for cryonics.

1:51:59Peter Diamandis:This is the way you get to see the 23rd century. I heard from the head of Alcor after my last call to action to do cryonics. Apparently lots of people flooded into Alcor. It's a nonprofit. I make no money off of saying this, no financial interest. just get yourself a cryonics plan as part of a portfolio for longevity, period. Love it, love it. I wanna take a second and just say thank you to Nick Singh and Dana Khan, our producers for supporting us on this new format. I enjoyed it. Did you guys enjoy it?

1:52:37Dave Blundin:I love it. It just feels organized. Yeah, well, it feels organized and fun. It actually feels fun to think through the topics with you guys. It's like an entire episode worth of AMA. with ourselves. It actually changes the stories we cover too, because we normally go through the most important stories to change your life. But here when you put it into themes, you actually dig up other stories that are related to the primary topic that you otherwise would have missed. So I love that. All right, here we go. Let's pick one each from page one and one from page two. Alex, would you go first? Oh, so many good options.

1:53:15Okay.

1:53:16Peter Diamandis:We'll start with number two. Where should entrepreneurs actually run their AI compute? Local hardware, AWS Cloud, or iPhone? And that comes from Frank Girard Marketing. There isn't a good answer. There are at least no single good answer. Lots of decent answers. There are benefits to each. With local hardware, you have greater control, greater confidentiality and data privacy. you're going to, on the other hand, end up maintaining said local hardware. You have to worry about your own backups. It can be a pain in the neck from a variety of different perspectives. With AWS or one of the many other public clouds, you don't have to worry about that.

1:53:58Peter Diamandis:That's abstracted away. On the other hand, you might have to compete ferociously for access to, say, GPU resources. You're competing with other tenants for common resources. You might have to worry on margin, depending on how familiar you or your organization are with OPSEC and cybersecurity. You might have a greater surface for attack. On the other hand, you have more scalability. With the iPhone, it's sort of the ultimate edge device until all of us, and not just some of us, are running foundation models on our watches and our smart glasses, which is already happening and is going to be more evenly distributed.

1:54:38Peter Diamandis:you have even greater privacy. So I don't think this is, maybe this goes without saying, I don't think this should be viewed as a black or white or binary trade-off. There is a spectrum from edge compute to data centers at the core. I think the best answer actually is I want to run my AI compute in the Dyson Swarm. And that Dyson Swarm will be a perfect blend when fully realized in a few years of data centers. We'll have lots of, maybe if Elon statistics are to be believed, 100-kilowatt nodes filling the sky. But also, it'll be incredibly elastic if we're disassembling the moon to fire off new 100-kilowatt nodes in the stellar or Dyson Swarm fabric.

1:55:27Peter Diamandis:Perfect blend. Okay, Dave, which one are you going to choose?

1:55:31Dave Blundin:Can I just add one thing on this topic, only because I spent the whole weekend but I'm dorking around on Amazon AWS Bedrock, which is a great choice, by the way, even though if my bed was made of rock, it would feel like getting started on Amazon Bedrock. I mean, it's a brutal get-up-and-running process on Bedrock. But it does the critical thing that you need, which is it captures all of your prompt history for you and any teammates that you have into easy-to-manage S3 buckets. so your AI can analyze everything that you've done, which is a critically important function. So that may be available elsewhere too, but it's probably as good a choice as any.

1:56:12Dave Blundin:But whatever you do, don't just start running on some random hardware and then lose all the prompt history. So that's just an easy way to capture it. Pick a number. I'll take number three. Are humanoid robots over-engineered? Would it be more efficient to isolate basic needs like food, water, and clothes and automate those directly instead from GoUnite FB3GN? Short answer, yes, absolutely. So why are we putting all this energy into humanoid robots? The reason we're putting all the energy into humanoid robots is because AI kind of came into the world almost overnight, and we're in a race to capital right now.

1:56:48Dave Blundin:And so what's critical for all these projects and startups is getting funded. the humanoids are so much more visually appealing that they're easier to fund. They're also easier to recruit into. And that'll unlock the supply chain of all the parts. And that'll unlock all of the other robots that, you know, that farm and create clothes and whatever, which will probably not look all that humanoid. But, you know, when you look at the Gigafactory, like Peter and I did, vast majority of the automation there is not humanoid robots. It's machines that look like, you know, machines doing their jobs. And then the humanoids just operate those machines.

1:57:24Dave Blundin:So I think they are over-engineered and over-invested relative to where we'll end up. But for a very good reason, you should think about, like, visual appeal and capital raising are a core, core part of this step function we're living in right now. So I want to go with number four. How can AI be used to end a war, not as a weapon, but as an impartial negotiator that all parties could trust? This is from at JNKind5. So I find that absolutely fascinating. And I do think it's a powerful tool. If you haven't used a large language model for negotiations, one of the things is we don't know how to think other than the way we know how to think.

1:58:04So being able to put yourself in the mindset of another individual is extraordinarily powerful. If you haven't said, listen, I'm, you know, I'm anti-guns. My neighbor, my friend, my spouse loves guns. can you please help me explain to them my feelings in a way that lands with them and isn't viewed as offensive? You can get some extreme support on your negotiation skills. And at the end of the day, I think this is one of the most exciting unexplored applications for AI because the system can ingest also every peace treaty, every negotiation script, every conflict resolution framework that's ever been had and can, you know, model outcomes with no tribal allegiance.

1:58:54One of the biggest challenges we have as humans is we have these cognitive biases and these tribal biases that are driving us. So, you know, can we use this for negotiation? Absolutely. And I think both sides, if you set as an objective function that you want to reach a balanced solution that both sides have, and both sides are using AI. I mean, it could be different models. I think the probability of getting to a solution is much, much higher. We are biased when we're dealing with humans. And one of the things that goes on when you're talking, for example, to an AI model for, you know, psychological therapy, when you realize you're telling your innermost thoughts to a human, you feel like you're going to be judged.

1:59:46But you don't feel judged when you're talking to an AI model. And so I think there's real value to be had here. I don't know if Salim's back online or not.

1:59:55Peter Diamandis:He's not, but if I might add just one thing to your point, Peter. Something that I'm seeing more and more in the past few months, not for war, but for commercial negotiation, I'm seeing this all the time. Two parties that are at loggerheads in a commercial negotiation, one of the parties will bring in a frontier model and ask the frontier model what the commercially reasonable outcome is, bring it to the other side. The other side will consult their model, and they'll come to rapid agreement. I'm seeing this happen now over and over again. All right, here's the next eight questions from our AMA.

2:00:30Alex, over to you.

2:00:32Peter Diamandis:Sure. Again, there are so many fun questions here. There are. Rather than choose eight, which would require me to give implicit investment advice, number seven, I'll avoid that one. Number six, slightly less interesting, I'll tackle number five since I've been beating the drum a bit for solve everything including disease. So the question is, once AI solves most diseases, how soon will treatments be available to everyone? Will access lag? And this is from Katis896. So maybe the sub-question first is, when do I think AI has a decent chance of solving most diseases? My timeline, and this is not specific to me, I think if you ask the more optimistic elements of CZI, the Jan Zuckerberg Initiative, Biohub, maybe ARC Institute, and some other organizations, maybe Anthropic on a good day, I think they'll say something like five years from now.

2:01:31Peter Diamandis:So five years is pretty rapid timescale. It's more rapid in many cases than what historically has been the clinical trial process end-to-end through three phases. So the second sub-question here is how soon will treatments be available to everyone? If say tomorrow, one of the frontier labs says, all right, here are the cures to the top 5 ,000 unsolved or untreatable diseases. is, we have vast computational experiments demonstrating to the satisfaction of all experts that these are the cures or at least the treatments for these diseases. How soon would those treatments be broadly available? Under the present regime, which by the way is not the same as the regime even one year ago, there would still be probably a multi-year process.

2:02:22Peter Diamandis:The FDA has recently announced two major developments that are, I think, relevant here. One, the FDA under this administration has decided to adopt a Bayesian perspective as opposed to a frequentist perspective, meaning that they're willing to incorporate for the first time in history evidence in terms of clinical approvals from outside a particular drug. That's a huge sea change. It means that in principle, drug approvals can operate much more quickly because they can take into account lots of pre-existing information that predated the particular drug. Second big development, a move from, and this was again relatively recently announced by this FDA, from a two clinical trial process to a one clinical trial process for certain cases, expediting the approval process.

2:03:10Peter Diamandis:So I think fast forwarding to as long winded answer to how soon will treatments be available to everyone. I think if tomorrow or five years from now, a frontier lab or multiple frontier lab said, here are the very well motivated to top 5 ,000 cures to everything, I think we would see similar developments from the FDA to go to a zero clinical trial model given enough Bayesian evidence and given enough computational evidence, which is to say a zero trial model. I think there would be so much political pressure that we would probably, barring some exceptional circumstance, see relatively fast availability.

2:03:47All right, so Dave, let's go to you.

2:03:48Dave Blundin:Okay, well, I'll take number eight since Alex couldn't touch it and we've lost Salim. If you had to choose one public company to bet on in the age of AI, which one and why from Matthew Johnson, 6525. So we can't give investment advice, obviously. But I will tell you, I've said a bunch of times on the pod, go to 13f.info, look up the Situational Awareness Fund, which is Leopold Ashenbrunner, and every quarter he has to file his holdings. He's killing it. And the reason he's killing it is because he listens to exactly what Alex is always saying. Look for the innermost loop. The tailwinds in equities and assets are like nothing you've ever seen.

2:04:30Dave Blundin:But you have to be in the AI loop to be relevant. And so you'll see all Leopold's holdings are somehow in the centerpiece of the innermost loop. And so those are the things you want to own. So those include things that are chip fabs, things that have power, things that are related to chip design, things that are algorithmic, that are directly deriving use cases, those are all in that fund. So that's your roadmap. So look at his holdings and then generalize from there, and you'll find lots of great stuff that you should be buying. Also, you know, W-2 income is going to get pummeled in this next three years, but assets, you know, holdings and ownership and things is going to go through the roof.

2:05:08Dave Blundin:So buy stuff, you know, whether it's equities, public or private, real estate, you know, things that will appreciate. That's what you need in this next three-year window. Amazing. I am under time pressure myself. I've got to jump on a film recording. I'm going to go to our outro music here, which is brought to us by CJ Trueheart. It was a piece he developed for the Abundance Summit called Moonshot Minds. Take a listen. Love the lyrics. Here we are. Thank you to CJ for Moonshot Minds.

2:05:49Dave Blundin:That's the moonshot dare Bold, be safe We're already there Moonshot minds We're writing our future's code Shoot for the moon Paving the untraveled road The future's not a fantasy We're making it appear We build what was said impossible For year after year Moonshot minds With the moonshot heart The future's what we build When you're bold enough to die

2:06:34Peter Diamandis:A billion lives get better When you think beyond the wall Sci-fi turns to science facts For those who hear the call Where the skeptics see the ceiling We see stars to reach Every exponential future starts With those who are dead at ease Past don't tell us yet Fail fast and learn to fly X-Mars the spot where Sci-fi meets the sky Moonshot minds We're riding our futures code

2:07:19We'll see you next time.

2:07:47All right, gentlemen.

2:07:48Dave Blundin:The video gets better and better all the time. It gets better all the time. AWG DB2, this was fun. Wishing you guys an extraordinary day. Salim, who's airborne to Brazil, safe travels, buddy. Soon we'll be putting you on rocket rides to get you there. Anyway, thank you, everybody, for listening. Or Hyperloop. Or Hyperloop. Yeah, I guess we can do Hyperloop under the Gulf. Anyway, long story short, thank you for listening. Please join us. If you've not subscribed, please do. We're putting out these podcasts on a cadence that you want to get alerts. So our mission, help you see an abundant world.

2:08:30The world is getting better at an extraordinary rate. The technologies to solve the world's biggest problems. If you're an entrepreneur, thank you for being an entrepreneur. Entrepreneurs are individuals who find juicy problems and solve problems. The more entrepreneurs on the planet, the better earth and humanity is. Gentlemen, until I see you next time, be well. Peter Diamandis, your host, signing off. See you guys. Take care.

2:08:53Dave Blundin:Have a good movie, Peter. Thanks, pal. 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 MetaTrends that are impacting your family, your company, your industry, your nation.

2:09:27And I put this into a two-minute read every week. If you'd like to get access to the MetaTrends newsletter every week, go to diamandis.com slash MetaTrends. That's diamandis.com slash metatrends. Thank you again for joining us today. It's a blast for us to put this together every week.

2:09:57This episode is brought to you by Indeed. Stop waiting around for the perfect candidate. Instead, use Indeed Sponsored Jobs to find the right people with the right skills fast. It's a simple way to make sure your listing is the first candidate C. According to Indeed data, Sponsored Jobs have four times more applicants than non-sponsored jobs. So go build your dream team today with Indeed. Get a$75 sponsored job credit at Indeed.com slash podcast. Terms and conditions apply.