Moonshots with Peter Diamandis - The Latest in AI: Job Loss, Elon & Sam Altman Chip Race & the "AI Bubble" w/ Brian Elliott (Blitzy), Emad Mostaque & Dave Blundin | EP #197

Episode Date: September 26, 2025

Download this week's deck: http://diamandis.com/wtf  Get access to metatrends 10+ years before anyone else - https://qr.diamandis.com/metatrends   Brian Elliott is a serial entrepreneur and Co-founder of Blitzy, an autonomous custom software supercharged by Generative AI. Blitzy's benchmark paper: https://paper.blitzy.com/blitzy_system_2_ai_platform_topping_swe_bench_verified.pdf   Emad Mostaque is the founder of Intelligent Internet ( https://www.ii.inc ) Read Emad’s Book: thelasteconomy.com  Dave Blundin is the founder & GP of Link Ventures – My companies: Reverse the age of my skin using the same cream at https://qr.diamandis.com/oneskinpod   Apply to Dave's and my new fund:https://qr.diamandis.com/linkventureslanding   Go to Blitzy to book a free demo and start building today: https://qr.diamandis.com/blitzy   Join Salim's Workshop to build your ExO https://openexo.com/10x-shift?video=PeterD062625 – Connect with Brian Linkedin  Blitzy on X  Blitzy on LinkedIn Connect with Emad X Linkedin Learn about Intelligent Internet Connect with Peter: X Instagram Connect with Dave: X LinkedIn Listen to MOONSHOTS: Apple YouTube – *Recorded on September 23rd, 2025 *The views expressed by me and all guests are personal opinions and do not constitute Financial, Medical, or Legal advice. Learn more about your ad choices. Visit megaphone.fm/adchoices

AI is useful. People pay for it because it has economic value. AI is not a bubble. Nothing's going to change the world more than what's going on right now. It is definitely not a bubble. It's not even vaguely like a bubble. AI until a few months ago, it was like having a very smart goldfish memory buddy next to you that you had to oversee all the time. Now it's the set it and forget it and it can use millions of tokens, millions of lines of code. Gemini overtakes chat GPT in the US, so this is based on iOS sale. Rock 5 could reach AGI first.

It's going to be a crazy couple of years now with this. And there's just not enough energy, compute, infrastructure, anything. As a CEO and entrepreneur, do you worry about getting access to the compute you need? You really want to be a player where everybody else wins when you win. There will be some kind of a breakthrough on compute. Is it going to be from quantum? Is it going to be from... Now that's the moonshot, ladies and gentlemen.

everybody welcome to moonshots another episode of wTF just happened in tech i'm here with my moonshot mates dave blundon the CEO and head of link exponential ventures imad moustach the head of intelligent internet my dear friend imad you're in where today you're in london yep in london nice and uh brian elliott who you guys met on a previous podcast bryan is the CEO of blitzie so a lot to discuss as always If you are ready to plug in, you guys, start taking notes, start listening. This is the world that is transforming how we live our lives. Before we begin with anything else, I want to talk about the wake-up call for colleges and universities. It's pretty extraordinary.

So this is a chart that's just out about how Americans perceive the value of college. And if you take a look at this graphic, and I'll sort of look at it for everybody here, people who say it's very important have dropped from 75% in 2010 to 35% right the wrong direction if you're a college or university not too important on the other end has gone from 5% up to 24% so for me you know universities have a problem Dave we've been talking about this for a while yeah yeah your thoughts I couldn't believe like I knew this was happening but these numbers blew my mind. I immediately sent it off to David Siegel, the founder of 2 Sigma, because we're going to go meet with Sally Cornbluth, the president of MIT in a few weeks. Like, holy crap, this is a

really, really big deal. And, you know, Peter, you've been saying it for a long time. The cost of tuition goes through the roof. The perceived value of the education has been plummeting, not because it's worth less in any fundamental way, but what you can learn has grown so quickly, and it hasn't made it into the curriculum. And remember, Peter, we had that meeting with the head of, I don't want to name names, one of the top guys at MIT. Yeah, I remember it. We can build a nuclear reactor on campus faster than we will ever change this curriculum. Oh my God. It's like, you know, the problem with you, if you're an accredited university, is you're not iterating your curriculum fast enough. And it just becomes irrelevant before you graduate.

So tuition is up 180% since 2005. You know, room and board in a private university today is a quarter of a million dollars. And you're sad. battled with debt, and you don't make it back because you're not getting the jobs. It's crazy. You know, Brian, you're closer to college than I am right now. How do you think about this? I mean, college has been a credentialing program for a long time, right? And so it was the act of getting into MIT that was actually impressive.

It was less to do with what MIT could specifically teach you because their curriculum is taught all over the world. And so the leading indicator of this. has been dropouts of MIT. Yeah, totally, for free. Yeah, dropouts get funded incredibly fast. And so what's the point of staying for that extra few years, right? And so there's this unbundling right now that's happening between the credentialing that you can get just from getting in or from going to Y Combinator or from having a portfolio

site that's really good. There's other ways to get credential that just weren't possible before. And that's kind of compounded with this big curriculum, like dynamic problem. I'd love to see the graph. of dropout rate in year one, two, three, sort of increasing over time, especially in the last few years. And Imod, I mean, you know, you sort of stopped and started and, you know, finally went and collected the piece of paper. Tell me about how you think about this. Yeah, it took me like 20 years to get my pieces of paper. That was a whole to do. I think that

there were probably two things here. I think the first boom was that tuition expense boom that we saw. I think that's cool in the first part. I think the second part was probably COVID. Like that was a terrible experience for a lot of people in college. Yeah. And also I think it showed things up. And now we're heading towards the AI drop, as it were, whereby we saw that paper by Eric Monofsenson and others that showed early stage graduates starting to lose the ability to get jobs. So that's just going to go. So again, it was into question, what is that? And that's Before we even get into the foreign students and what's going to happen there with the reason changes, et cetera. And this is the second blow. This is the kill shot here. This is a graph that, you know, is titled college educated are unemployed longer.

So it used to be that, you know, you'd go to college to get your job. And we've talked about this on this, on this pod number of times. The only career of the future that really matters, in my opinion, I think in all of our opinion, is being an entrepreneur. It's not marching up the career path. And so this is a graph. between 2000 and 2025, and what we see in terms of unemployment is the college graduates increasing unemployment while everybody else with some college or just high school. In fact, high school college graduates are becoming more employed if they didn't go to college. They go to trade school. Well, yeah.

I love that one pixel there just last summer where the most unemployable people in the world are college graduates. It's just hilarious. This is bad PR for colleges. Bad PR. Well, if you look back 2000, that's what I'm used to hearing, which is, hey, if you go to college and you graduate, you're over twice as likely to get a great job. And that's exactly what you see in the data just 20, 25 years ago.

So this is a pretty rapid shift in society's perception of the value of a degree. Now, keep in mind, within this entire chart, the unemployment rate is extremely low. It's like 4.5%. So, you know, most people are finding jobs. It's not implying that you, well, actually, we can go down that path. Actually, it's very hard for this year's graduating class to find jobs. It's shockingly hard. What does this look like if we stratosphere like the top 10 versus everybody else?

Because I think there's been a sort of a blowing up of people getting college degrees at, I would say, sub-tier institutions. Because it's incredibly profitable for these institutions, even though they maintain a nonprofit status. They're growing the size of their employee base. and their student base as a sort of a way to just fund for education in a way. I do agree with what you said earlier, Brian, which is what really matters out of a college education is the fact that you got accepted by a specific university. You know, when someone says, so, Imod, you went to Oxford or Peter or Dave or Brian, you went to MIT, they don't ask, did you graduate?

They don't ask, what was your GPA? they don't ask you about what you studied. It was like, you know, yeah, I went to MIT. That's all that matters. That's the highest order bit. And it's crazy. So there should be a brand new program that MIT offers where it accepts you, but doesn't expect you to go.

Yeah. All right. If you go to the next slide, it really makes Brian's point. Okay, here's your tuition getting completely out of control, but that top 10, top 15 schools are hugely endowment-driven. In fact, the endowment returns contributing to the budget are over twice as much as all tuition combined. So I want to read this for those who are listening. It says college tuition versus other expenses.

Cumulative percentage price change since 1983, which is when I was at MIT. So it's up almost 900% in tuition over that time. 5.6 increase average annual increase. Yep. Yes, so you've got a handful of schools that, don't even care about the tuition. They'll be fine because their endowments are so big. And then you got this really slippery slope of schools that need the tuition desperately to stay open at a time when people are not really perceiving the value of the degree. So that's where it gets

really ugly, you know, right around school number 40 to 400. If I'm the board member at MIT, Harvard, I'm probably not as worried, but if I'm at a second tier school, I'm, you know, like, holy shit, what do we do? We need to reinvent how we educate. Iman, you know, you and I have talked about the value of education and the fact that the best educator in the world will be AI. What's your thought here? Yeah, I think there's the credentialing part, but, you know, university became something that you just passed by default versus programs like Gauntlet and others where you actually have to work really hard to succeed and get through with high dropout rates. And I think the world we're going to now is one very competitive one where the people that use AI, I mean, there's no nothing you can't master with AI now fast. We've seen Alpha School and others show just in two hours a day of tuition.

They're tipping not 0.5% in the world. Even with academic papers, I think it's going to be similar. And I think there'll be a huge amount of arbitrage because they've just got too expensive. Like, in the UK, Oxford costs $13,000 a year for tuition, or like $60,000 a year if you're foreign. I think that people will go to the networks and they'll go to the places that embrace the technology to actually do what universities are meant to do, which is network. works, knowledge, learn, and more, but we haven't seen the first AI university yet, which I think is going to be really interesting.

And really important. We're going to have McKinsey Price, the CEO and Joe, the co-founder, who's funded it on a podcast coming up. So those of you who are moms, dads, educators, you're going to get ready for a fun episode on how to reinvent secondary education in high school. All right. Actually, just, I think one final thing. Yeah, please.

Maybe the endowment should be putting big supercomputer class. down because the universities in the U.S. don't have them. That'll probably be the biggest determinant of research quality in universities. How many GPs you have? I totally agree. I love that. I think it's a no-brainer. All right, MIT, listen up here. You put the endowment to use. They want to. There are forces in the school that desperately want to do exactly what I just said. I don't know what the friction is, but we'll work on it. Get J.P. Morgan to fund it. Every week, my team and I study the top 10 technology metatrends that will transform industries over the decade ahead.

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sales, 150 million users. We've seen Gemini go through this viral element. I mean, love nanobanana, V-O-3, and others, and they've jumped into number one position. Any particular thoughts here? I did not believe it. Because ChatGPT had such a huge lead. So I checked the App Store data directly, and it is absolutely true. Now, this is U.S. So, you know, Chad GPT is still miles ahead globally, but, you know, Google can use its massive distribution power to push that. That's how Chrome bypassed Firefox in, and you just push it out. It didn't bypass, it blew it away. It blew it away. Actually, you know, I checked polymarkets on this. Interesting enough,

so I checked on polymarket score, which is really fun to do if our subscribers haven't done that. Look at it. So I first asked, when is Gemini 3 coming out? We've been waiting for Gemini 3 to do an episode on Gemini 3. The current top prediction is 40% by October 31st, so maybe by the end of the next month. But here's the other prediction. Which AI model will be in first place the best by the end of September?

99% it was Google. But what was fascinating was the second best AI model by the end of September, 91% for Alibaba for Quinn. I find that amazing. How do you think about that, Eamon? well i think we've seen the gap closed dramatically between those models um quen is releasing almost daily now today they had six model releases wow and they're just accelerating and i think that it would be difficult for them to have the best model but they just have such reach with the billions

of users that alibaba has the amount of data they have and they've just got a really kick-ass team there and distribution matters so much like i don't know anyone that uses threads at number three there right It has 400 million monthly active users and 115 million daily active users. And I feel that this Gemini chat GPT thing is the same thing, which is why people are going to be doubling down on the distribution. And now that we've got the reinforcement learning really coming through with the models, that's actually how they'll get really good. And I think that's going to be a real differentiator as we go forward. And again, we'll probably see the Quinn models keeping up because they're used so widely now everywhere. And they are closing that gap.

All right. Not to be left out of the conversation. GROC 5. This is a chart that GROC 5 could reach AGI first, and the fact that we've seen it beating all the AGI benchmarks. And in particular here, what we have is GROC 5, you know, reaching top marks on the ARC AGI benchmark, which is the abstract and reasoning corpus. So right now in the ARC5, AGI V2, GROC 4 has hit 15.9%, which is the highest known. Are you tracking these, Eamon? Yeah, I mean, I think that we're continuing to see scales coming through here. And this is going to be the first big mega run that we'll know about. Again, like, opening I might release their verifier runs. All these benchmarks are saturating so fast. I think that, who was the epoch research, predicted that every benchmark in the market

today will be saturated within three years, four years. We need new benchmarks. Just a simple extrapolation. Dave. We need new benchmarks. But the crazy thing. Yeah. Crazy thing is what?

This is V2 though. We already saturated V1, but V2 is crazy hard. If this one saturates, then you're beyond superhuman intelligence. So this one, if this one saturates in three years, we're in another universe, which it probably will. I think more important is the cost per task, right? on the x-axis. Like, it's very, very clear that if you're willing to throw more dollars at this,

you're able to increase performance. And I think that's, I could care less on the last slide of, like, who the consumer user is. It's like, when we throw more dollars at which models, do we increase the quality of performance? And that's going to be who ends up winning. Yeah. Because the one year since I won was announced. That's crazy. That's crazy. Ancient history.

That's funny. And so here we go. Grock for fast reasoning. I love these names, right? just appending on the end of them. GROC for Fast Reasoning ranks number one on the extended New York Times connection benchmark. So what is that?

So this is based on New York Times puzzles where players must group 16 words into four groups, each belonging to a common semantic category. The extended version, the original version, 436 puzzles, the extended version has 759 versions. I mean, these are just, you know, I don't know, these are these vanity benchmarks to sort of brag, get bragging rights? Yeah. Actually, I talked to Alex about this one.

He's off in Europe today, but a lot of benchfacking. Yes, by the way, I should say, Salim is MIA. Selim, where'd you go, buddy? And Alex is on a top secret mission in Europe. I'll leave it at that. This is a really fun benchmark here, though, because You know, if you go to New York Times and you do the connections tests, it's a daily puzzle. It's really fun, actually.

My wife does it every single day with her friends. They made it harder by adding more categories to it, four more categories. And you have to get it right the first time. When you do it on the New York Times website, it gives you three wrong answers before it says, no, you're wrong. But the AI has to get it right the first time. But it really is a good test of general intelligence, shockingly good. but the theory here is that the big foundation model companies are going to benchmax it so they'll train on a bunch of data specific to this puzzle type to try to max it out

and you saw when Brian did the Blitzie announcement on our podcast very careful to say we topped Swaybench but we did not tune or benchmax to that test it just happened this way and here we're almost sure that they're trying to get the PR by benchmark maxing and optimizing toward the problem, but you can't prove it, but it's, it isn't a crazy high score, though, to get in the 90% on this. Amazing. All right. You know, here we go.

This is going to be the Data Center Wars. X-AI's Colossus 2, a gigawatt scale data center, 110,000 GP-200 GPU clusters. I love this, 119 air-cooled chillers and Tesla megapacks. So this is the beginning of Colossus 2. Imod, you're tracking this, I'm sure. Yeah, I think Elon said he's going to be the first two gigawatt, the first to 10 gigawatts and the first two terawatts. Yeah, this is his tweet from today.

Yeah, OpenAI is bragging about their NVIDIA partnership, and here he is saying, just as we were first to bring a gigawatt of coherent training compute online, it will be the first to 10 gigawatts, 100 gigawatts, and one terawatt. Love that. It's basically like as much as a state now. these things will be drawing down. The whole of the Bitcoin energy is about 20 gigawatts, if you look

at it as well. That's about as much as all of Argentina is a 10 gigawatt power center. I think what's going to happen now, though, because you don't have the infrastructure, I think we're going to see massive solar and battery buildouts, and that's going to be super interesting as you scale there. I don't know how else you're going to do it

unless you have these small scale literally nuclear reactors. In fact, Microsoft has co-opted like nuclear power everywhere, so it's going to be power wars. across the U.S. Amazing. Here's our article on NVIDIA investing $100 billion into OpenAI.

It was a great CNBC piece that had Sam Altman and Greg Brockman and Jensen speaking together. And let me just quote what they say. They say, this is Sam saying $100 billion is a small dent in the scale of our plans for 10 gigawatts of compute. This data center will be a multi-square mile

level of infrastructure. the stuff that will come out of this super brain will be remarkable. I love that, right? Multi-square-mile super brain. I mean, tiling the world. And Greg Brockman then comes on and says, we really want everyone to have their own GPUs so agents can do work for you while you're sleeping,

which means that we're talking about on the order of 10 billion GPUs. The deal we're talking about with Nvidia is for millions of GPUs. We're still orders of magnitude off. We're heading towards a future where the entire economy is powered by, compute, and it's a future where it's compute scarce. And then Jensen comes on finally and says,

hey, this project is 10 gigawatts, or roughly 4 to 5 million GPUs. That's approximately putting into one project, what we sold all of last year, and double what we sold the year before, and double what we sold the year before. So just massive increase. Dave, how you think about this? Tie together those last few slides and really open your mind. to the compute scarcity that's coming up. So you've got $100 billion. The U.S. venture industry is about $200 billion a year. And you hear you've got a single investment by a single company

that's half of all a U.S. venture in a year. Where's that going to go? It's going to go into buying chips and building data centers to support the users. Well, how many chips is Jensen going to be able to make this year? It's about $5 million. Yeah. Okay. Five million chips.

This deal buys a lot of the, like, you know, 20, 30% of those by itself. Okay, well, when you looked at the other slide that Brian commented on on the X-axis, wow, this stuff gets more and more intelligent and useful as you throw more hardware at it. How much more hardware? A lot more than we actually have on the planet. Like all these demos you're seeing, all these things you're like these benchmarks, there aren't anywhere near enough chips to deliver that to 7 billion people around the world.

So we talked about, you know, where do you invest? I mean, so ship manufacturers, it's the construction to build out these data centers, it's the power plants to power these. I mean, we're converting electrons into intelligence and into crypto. Imod, how do you think about this? Yeah, I mean, I think who controls this is the marginal producer in the economy, right? If you look at open AI's projection, it gets $200 billion, 80 billion comes from this brand new AI agents line. and then other is another like 20, 30 billion, they're going to be rolling out AI workers that work around the clock.

And then the investment, as you said, is a supply chain. But then it's also the companies that can have the expansion in margins because they have pricing power and they'll be replacing humans with AI. And then downstream, the impact I think is going to be probably actually in the attention economy because it's about the only thing that isn't scarce is human attention. So we're going to look more and more towards media, which might be a bit counterintuitive. Interesting. Brian, as a builder, as a CEO and entrepreneur, do you worry about getting access to the compute you need? You really want to be a player where everybody else wins when you win, right? And so you really want to be sort of model agnostic, you want to be provider agnostic, and you want to lift all ships. So I don't think if you are a sort of healthy player in the ecosystem, it is a huge concern. But I think it's one of it's, you can't be like fifth or sixth, right? You have to be the most important to these folks.

And so this is like economies of scale, we're going to matter a lot here. Here's a chart reinforcing this. Lab compute has 3xed in just one year. We see a graph showing Open AI, XAI, meta, and Anthropic. OpenA. at the top, XAI coming on strong. We don't see Google on this or alphabet, which is interesting. I don't know if any comments on this. I'm going to couple it with the next slide here, which is that data center capacity is

expected to go up fourfold by 2030, going from 44 gigawatts to 156 gigawatts. 44 gigawatts today, 156 gigawatts by 2030. And from what I'm hearing, that seems like a lowball estimate as well. McKinsey always low balls in numbers. So demand, I think somewhere else in here, we have demand is going up 10x year every year. Supply is going up very quickly, but nowhere near as fast as demand. So what does that mean? What you see with all the model providers, they're trying to offer fast or

smart or whatever, but what it's really doing is rerouting your query to the smallest model they can answer the question to try and save some compute. Meanwhile, they're all working on internal self-improvement, so that's eating up a lot of compute at the same time. So you're starting to see the cracks in the supply demand curve here. Your question for Brian was a really, really good one. It's like, do you worry at all about getting access? And I think that a lot of the use cases that'll be deprived access are like the virtual girlfriend and the, you know, doing your English homework because, you know, Brian can overpay, you know, 100 X or a thousand X over those use cases. So he won't get cut off. But there is going to be a huge supply shortage for

sure. Oh, yeah, it's about the marginal dollar rate. Costs are going to go up dramatically, I believe. At the same time, costs are depreciating from the actual cost basis to the chip, but the model providers are going to be able to increase cost if they're number one. And we're willing to pay that. We're willing to really pay anything because it's much more valuable what we're able to provide than these consumer type services. economic value per flop is just going up dramatically because you're at this inflection point AI until a few months ago most people were using GPT40 it was like having a very smart goldfish memory buddy next to you that you had to oversee all the time now it's the

set it and forget it and it can use millions of tokens millions of lines of code and then be proactive and as you know Brian and Dave said it'll be the marginal dollar going up but if we look at the previous one like just put it in context we had our launch party at stability i think three years ago the exploratorium and i had a slide go up saying you know we're the 10th fastest cluster in the world at 4,000 chips and now people are talking about 114,000 million chip deployments the reason for that is literally just because of this economic thing the amount of we think the world of economic labor that you can do the i i can do it's gone from maybe i think one or 2% now to in the next few months it'll probably be 50% in the next year actually and so this is

all complete this isn't a bubble this is like all very reasonable because your tam has gone up your total has gone up so much yeah it's going to be a crazy couple of years now with this and there's just not enough energy compute infrastructure anything amazing uh this is uh Greg Brockman on that very subject I think part of the 2030 outlook is we will be in a world of material abundance, right? I think that AI is going to make it much easier than you could almost imagine to create anything you want, right? And that will probably be true in the physical world in addition to the digital world in ways that are hard to predict. But I think it will be a world of absolute compute scarcity. And we've seen a little bit of what this is like within Open AI, right?

the way that different research projects fight over compute or that the success of the research program is determined by the compute allocation. And so one thing we think about a lot is how do we increase the supply of compute in the world, right? We want to increase the intelligence, but also the availability of that intelligence. And fundamentally, it is a physical infrastructure problem, not just a software problem. Could you imagine the ongoing conversations inside of open AI and sort of the arguments about, no, I need the compute to do this project.

You know, everybody's sort of vying for their own special crazy. I don't know if you remember, Peter, but when we were at Open AIA headquarters a few weeks ago, talking to Kevin Wheel. Yeah. We asked, or I asked him anyway, about the division of labor between him and Mark Chen and Sam and Greg Brockman. And he said, well, Brockman's out there just getting compute. Like, we need compute like you. So he's just out there finding it. So, yeah.

You know, I kind of missed the days when Greg and Sam. Sam used to do these things together. You know, Sam is on the road constantly now, so Greg has got to be in the house finding the compute. But he used to do a lot more podcasting. It was really nice when they were a two-person team. But I don't know, everything he said is exactly what you were just saying. The theme of today, abundance everywhere, except compute scarcity.

You know, there will be some kind of a breakthrough on compute, right? And, Imad, what's your bet on where we might get some sort of new breakthroughs at 10x efficiency or power use or, you know, is it going to be from quantum? Is it going to be from thermodynamic compute? What do you think? I think it's probably a data story right now. Like, if you look at the Tongue model by the Alibaba Quinn, it's their AGI lab next to their Quinn Lab, they managed to score, I think, 22% on Humanity's last exam with 3 billion active parameters. with a self-reinforcing continuous learning model. That runs on a smartphone, and they did it through improved data.

Again, this thing David said about better RL, better kind of thing. I think there's a data hybrid reasoning and other things coming together to optimize for specific tasks of the economy. Again, that 50% of tasks. That's how you could route this down to be highly efficient. And we don't know where the lower bound is on that because we could have more breakthroughs. we could have improved chip performance. Again, we're going up like five, ten times a year on chip performance. And it's just very hard to extrapolate this.

The only reason you can say it's going to reach this crunch point is simply because the amount of work that can be done in the global context is so large at this inflection point. There's no way that we'll be able to get them efficient enough. That's the only way we can kind of look at that. And if I could just riff on that for any of the entrepreneurs out there, What Imad just said is a really good barrier to entry if you work on it within your domain. So if you said, hey, there's all this technology and research related to transfer learning and distillation that allows me to get the exact same quality of result with 1% of the parameters and therefore 1% of the compute,

well, then by all means do it. Right now, we're all used to, oh, I can just get an AWS account tomorrow and I can just sign up and pay and it'll be there for me forever. It's like a utility. You know, that whole cloud computing era, they tried to convince us it's all a utility. It will always be there. Well, lo and behold, nope, it's a scarce resource. Greg just said it. He's always right. It's not a utility.

Have a plan. Like, you need a plan today because, you know, Bill Gross was saying every mountain with a lake next to it has already been bought, you know, for pumped hydro power storage. You miss the opportunity to buy your mountain. don't miss your opportunity to reserve your compute because it's now or never because these things get locked up very early you know this is a it's a competitive world Dave said a hundred times literally if you have task specific data sets distillation and you have the right verifier it is a hundred times difference in the cost of executing a particular task yeah this is a perfectly viable business plan this is what happened with storage if you business that drop box got so big right they were the first folks to use S3 and not have to store have their own data centers and they were storage there was a hundred other

storage companies they were just the next year than everybody else and they scaled off of that and built a very powerful company same thing applies to models looks like open AI may get the shackles pulled off it so open AI reaches a deal with Microsoft to allow restructuring from a non-profit to a for-profit so there you know open AI is targeting a 500 billion dollar valuation as part of that and And I know what it's like to flip a for-profit or nonprofit into a for-profit. I did it with Singularity University many years ago. And you need to leave a certain amount of capital and capabilities inside the nonprofit. I won't go through the machinations of how you do it.

But as they do this, Open AI's nonprofit will be left with about $100 billion in capital. It will be the largest nonprofit, you know, endowment out there, which is amazing. amazing what they'll do with it. You know, you remember, Dave, we met with, I won't mention who it is at OpenAI, and they likely will be in charge in the nonprofit, and they have incredible vision for what they want to do to go and solve humanity's biggest problems with it.

So if you guys remember, Microsoft invested a billion dollars in 2019, another $10 billion in 2023, and they're estimated today to own about 30% of Open AI that's unconfirmed, but that's what the estimate is. And this sets them up basically to be able to, you know, become a multi-trillion dollar company. Microsoft can't lose. Microsoft can't lose. For context on the earlier part of the conversation, OpenAI is twice the size of Harvard's

Endowment Fund, which is, you know, for the longest time and the largest endowment fund of all time. So from a nonprofit status, Open AI in just a couple of years, double-a-I. in just a couple of years, doubling the size of the endowment fund. By the way, can you imagine the relationship between Open AI and Microsoft right now? So, for example, when the NVIDIA,

Open AI deal was struck, Microsoft was notified the day before. Right? So, you know, OpenAI used to get all of its compute from Microsoft, and now they've been sort of kicked to the side, and they're just growing, you know, unshackled, fascinating. I remember when Michelle Sison

kind of had that commitment for $100 billion to Open AI and then someone asked sat here about it. He said, well, I'm good for my 90 billion. I think that Jensen is definitely good for his 100 billion. And, you know, like now

these are all crazy numbers, right? They are insane. When Microsoft invested 10 billion or a billion, we were like, we're like, that's big. Now it's like only 100 billion for the nonprofit. It's the second largest. And we don't even blink at $100 billion being invested in them. Yeah.

Because literally they will spend, they will have a trillion dollars of buildout. And I think Elon Musk said something again recently. It was like, someone's like, what about Anthropic? He was like, they never had a chance. Because really, who can scale now to compete? XAI, Google, open AI, and probably meta, you know? Yeah. Speaking about that, anthropic.

This goes to our next slide. And the title here is Zuckerberg says, Better to Lose Billions than be late to Super Intelligence. So he's committed to invest $600 billion in U.S. data centers by 2028. Why? Because I don't want to be second to superintelligence. Crazy. It's just staggering.

The sheer size is staggering. But also the lives these guys are living is completely unprecedented in the world. I mean, Zuck was just at the White House a week ago, having dinner with like look at the table look at these people and then they're all you know the president is saying how much you're going to pump into the u.s economy and zuck is like 600 billion this has not existed ever in the world before and i don't know this next couple of years it's like nothing in human energy sounds like inflation to me because the economy is dependent on its capital stock you know like we build our universities our factories and everything but basically all this is

is it's the investment for the new economy. The economy, five, ten years from now, is run by AI. It's powered by AI. So it makes sense that you'll spend trillions of dollars on this. And these guys want to get it. First from an economic point of view, but then there's more than that. Like, do you remember the story of how opening I got going with Larry, Larry Page from Google and Elon Musk?

Larry Ellison, yeah. Larry Page from Google. So they're having a discussion. I was there for that argument. Yeah. And we're, you know, Elon, or Larry called Elon a specious. Yes, and Peter, do you want to tell the story there? Oh, no, go ahead, go ahead. I mean, it's because they were discussing intelligence, and Larry Page was like, you know,

digital intelligence, he was like, can overtake humanity, and that's fine. And he was like, no, humans. Yeah, like, Larry Page is on record, not on record, but there again have been reports that he said, he's willing to make Google bankrupt to get to superintelligence. first. They weren't because they make so much money, but this is big stakes now. Yeah, I think it's worth just stepping back and comparing a day in the life of Mark Zuckerberg to Sam Altman. Sam has literally getting attacked constantly from every side, especially by Elon, while needing to beg for money from any sorts he can get it, traveling all over the world, trying to hold this together while

taking a non-profit to make it into a for-profit, which is a logistical nightmare. He's dealing with all of that. Zuck just needs to call his CFO and say, you know what, go ahead and divert that money back into data science. And I'm going to go have a Mai Tai. They're printing money on my ship in the Caribbean. The market of a reward for it too. It's an unreal existence. Dave, you said it right. I mean, I don't know how you remain grounded as a CEO of one of these companies when you're speaking about literally trillion-dollar deals that you're in. I mean, it's crazy. Yeah, that's a good concern, too.

I kind of trust the people that struggle have either struggled before in their lives or struggling right now, but you do worry a little bit about, you know, just the scale of power in a few people's hands and, you know, and what decision they might make tomorrow. But we are, just to remind everybody, we are in a war footing. Going back to what you said a few minutes ago, Imad, you know, we're in a war footing getting ready for the next economy, just like we came out of World War II with a brand new, you know, interstate highways in the United States, and you, in aerospace

and automobiles, we're gearing up for a new economy, which will displace the old economy, and it'll be, you know, tens of trillions of dollars include robotics and will be close to, you know, $100 trillion over the course of a decade. This episode is brought to you by Blitzy, autonomous software development with infinite code context. Blitzy uses thousands of specialized AI agents that think for hours to understand enterprise scale code bases with millions of lines of code.

Engineers start every development sprint 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 blitzie.com to schedule a demo and start building with Blitzy today. All right, let's look at what comes up next here. Dario Amadei on Claude designing Claude. This is a quote from Dario. He says, Claude is playing a very active role in designing the next Claude. We can't fully close the loop, but the ability to use the models to design the next models is not yet going super fast, but it's definitely started.

How long before it's going super fast, Eamad? It's the takeoff point right now. There was a recent interview with Tree Dow, who is like the man for writing Kuda kernels on Nvidia. So he's at Together AI, and he came up with flash attention that literally increased performance 30%. And he's like, I use Claude code and I'm at least 50% better. and this guy is the cream of the cream of that

and we've seen that from top people already that self-recursive loop it's coming inevitably we're already seeing TPUs being designed by AI and Sam Altman recently said again fantastic CEO fantastic capitalized but he said his plan is to get one gigawatt of new compute on every week with a fully integrated system

that could also be training its own models so I think we're moving full stack vertically integrated like chip silicon 2 model feedback loops. And there's no way that won't speed things up even more. Can you feel the acceleration? Oh, my God. I spent about six years of my life just purely building neural network

and researching neural network algorithms and code. And it's very similar to discovering math, which Alex is always talking about. So Alex, Alex was in a gross on this pod as predicting. I think it was 18 months. will be solving all math I mean you've been on this you've been on this bandwagon as well right

the AI is I mean look at winning the gold medals and the ICPC and the math Olympiads and things like that you parallelize it like we've been running 1,000 lean proofers in parallel analyzing things you know like next week we're releasing a full stack of economic proofs that you just can't argue with for everything these AI is like once you actually apply them it's not it's not like you have one like one genius is enough but Dario said data centers of geniuses checking each other's work in

parallel obviously you're going to get that next step up from that and we've seen things like Terence Tao was formalizing some various proofs and they only got like 20 30% the way in parallelizing that I believe it was morph labs that they did that they I actually do the full proofs in like two days. So, yeah, I think it's a good chance. I have no idea what the implications of that is. Well, also remember, Noam Brown over at Open Eye when we were there, was saying that their progress in core AI research is gated by compute now and not by researchers.

Yeah. They have a backlog of ideas. They just don't have enough compute to try them all. So pretty soon, the AI will also be generating the ideas, and then the backlog is purely compute. So that's where Elon is saying, well, I'll have the most servers, therefore I'll win the race. But it'll all be compute constrained. You know, there's a window of a year or two here where it's also idea constrained. So lots of opportunity for people to think really hard during

this window. But very soon it'll switch to AI generated ideas. You know, 10 billion here, 100 billion there, pretty soon you're talking about trillions. So Alphabet becomes the fourth company. I like to call it to reach the four comma club. This is to reach $3 trillion market cap, joins Apple, Microsoft, and Nvidia in this $3 trillion market cap club. Stock is up 33% in 2025 and 55% over the past year. I was talking about last time, you know, for me, Google has been an extraordinary bet. Any comments here? I mean, I think the prediction market still hold Google an alphabet to be the long-term winner.

Imad, do you buy that still? I mean, they're fully integrated with thousands of amazing talents, Demis, at the head of deep mind, and they've got the reach, right? So you started to see AI search results. It's not quite good enough because they're doing the crappy models, but when Gemini kind of three flash is better than Gemini 2.5 Pro, the directionality of where things are going, again, they've got the full stack. They don't need to pay the Nvidia tax. They can build everything themselves, and they have Metis Cash. So why wouldn't they be up in the lead there? Yeah, and just add one thing to that, too, we announced or we spoke about OpenAI doing their own ships with Broadcom, but they just started.

Google's been working on their TPUs for years, so they're years ahead in that vertically integrated solution. They've been their own customer for a long time because they run the Google on the TPUs. TPUs are probably five times more power efficient than Nvidia chips, and they have better interconnect for large context models as well. so they're pretty much ideal for what's coming through now. Nice. How do you know that, by the way? I thought that that's impressive knowledge.

We use thousands of TPUs. We were down there when they didn't have jacks. Oh, at stability? You had hands-on access? Oh, no way. Yeah, because they pulled them from the market effect because they're using them all internally now. So it's kind of hard to get performance specs.

That's really useful information. Well, they might actually start selling them soon. We'll see. We'll see if they can, yeah. I'm betting. I'll put a little money on no. They won't be able to make enough of them. They'll eat them all themselves.

Yeah. There was a little video clip put out by Mustafa Sullivan, the CEO of Microsoft AI, which I found somewhat compelling. Let's take a listen to it. At the moment, these models are still one-shot prediction engines. You know, you ask a question and you get an answer. You know, it produces a single correct prediction at time step T.

And not, they can't lay out a plan over time. And the way that you decide to go home this evening is that, you know, you know first to get up from your chair and then open the door and then get in your car and da-da-da. And that is just a computational limitation. And just as today, there's a kind of super intelligence that is in our pocket that can answer any question on the spot. Like we dismiss how incredible it is right now. Is magic in your pocket? Now, imagine when it's able to not just answer any question about poetry or some random physics. thing, but it can actually take actions over infinitely long time horizon. Just that capability

alone. I think that we basically have that by the end of next year. So I found that compelling. Imaud, Dave, what do you think? Well, I love the core point that, look, this is absolute magic, and it came into the world so quickly. And there's so many ways to take advantage of it that we've only begun to scratch the surface. I do disagree that the planning ability, I don't know when this was recorded, but the planning ability has gotten pretty damn good, pretty damn quickly. So this might have been like three weeks ago, but it's not, but today is different. Ancient history. Well, I mean, look, look, do you think a Tesla can self-drive from one side of America to the other?

100%. Yes, yes. That's planning. That's crazy, yeah. And then just think, you hook that up with a vision model, so it's making notes and it's writing the great American novel as it drives. Like, again, we actually have all the tools there. And, in fact, Brian, you're the expert in this, right?

Like, what have you seen in terms of massive long-term stuff? You can achieve AGI type effects at the application layer, right? This long-term horizon of planning can't be done extremely well at the model level. But from a user or consumer, who cares, right? It's about what I experience, which is a long horizon plan given to me from a set of models. So I would say we are in this reality today for a size. number of domains, including software engineering. Nice.

We had the CEO of Repplet on the pod recently, and I loved this quote about how to use agents. Let's take a listen. I'm one with true unique domain expertise. Let's say I'm a lawyer who is top in the world at solving certain

cases that are very rare. And so I have this domain expertise that I'm not going to share in the open source. I'm not going to sell to scale AI so that they can sell to Open AI or Google, all those. I'm just going to keep this resource to myself. But the way I would monetize it, instead of myself going and selling my services directly,

I would like imbue this knowledge into an agent that becomes this very specialized agent in this very specialized domain, and then I can scale myself. So I like that. You know, one of the questions that we've had asked in the comments on this pod, and we do read the comments from all of you listening or watching on YouTube, is, okay, you talk about what you should do if you're 18, 19, 21. What should you do if you're in mid-career? How should you be thinking about AI?

This sounds like a pretty good example. Dave, how would you answer that? someone mid-career. Yeah, that's a tough one. Maybe I'll bounce that over to you, big brains on, like, the concept I totally get. Like, I've got domain knowledge. I'm a lawyer. I'm a doctor. You know, there's very, very specific domain knowledge all over the world. And I know the RLHF companies, like, you know, Invisible and Mercor are killing it, wrangling all that technology and getting it into the models. So the question then becomes, okay, I want to monetize that. But once it's ripped off my brain, they may pay me a lot for a month or two, but then what?

Then I've just completely dumped my knowledge into the AI. Do I have any value? So I don't have a good answer off the top of my head for how to capture that. You know, I would say there's no barrier to starting a company. You don't have to be 21 to start a company. You absolutely, there's so much greenfield opportunity out there. And I do love these companies that have a regulatory barrier or a vertical domain, deep knowledge barrier, just start a company using AI in that category.

That's how you might then say, okay, now it's sustainable and I can make a career out of it. So that's always a good choice. But you've got to leave your day job and go do it. I would translate that to find a good problem that you understand deeply, that no one is yet solved and go build around that problem. It's never been a better time for these domain experts. I'm more bullish than Dave is on this 45-year-old audience. And if you think about software's never been easier to build, that is true, but software is just two things.

One, it's sort of like, I'll say the technical design and build of it, but you're imbueing a business process and a set of flows and decisions that you need a user to make. These insurance folks, these financial services folks, like they're world class at understanding how to do that portion of pricing products dynamically to the market. And that has very little to do with technology selection. So we can empower these folks with platforms like, let's see, to build large-scale systems, enterprise systems that are purpose-built for that 45-year-old insurance underwriter or financial product person. And this is never before been possible. Yeah. I've been thinking a lot about this. And, you know, Nasim Taleb, the Black Swan guy, has this great thing, concept called intellectual yet idiot about very well-credentialed people who just don't have any skin in the game so they don't give a damn, right?

That's a flaw of many of our systems. AI models are intellectually idiot. They don't give a damn. One of the most important things is actually giving a dam about the context about when these are implemented. And if you think about the long tail of these implementations to solve problems, if you actually give a dam and you can communicate it and be that intersection,

that's where you get the most leverage. You actually need to understand the consumer and how they operate today. You need to actually have some skin in the game in the way that you do that. And I think people underestimate that because we just assume the technology will suit because people do these analyses and they understand the way we do. No, there needs to be that translation layer and you need to actually be able to communicate and show that you give a damn. So your advice, Ima, to that, you know, 40, 45, 50 year old individual who's like, how do I apply AI to do something significant in my life?

I think that when you look at the problem, there is the intellectual part. Hey, I've got cognitive surplus now from the. these tools. But the next part is getting to understand the organization that you're in, if you're within your organization, trying to improve it. The real like things and balances and who you need to communicate these things to in the appropriate way. And then if you're servicing someone, having that really high touch consumer aspects of it where you're helping them through something that's very scary and has huge potential will pay a massive amount of dividends. And again, you can use the AI to help you communicate and things like that as well.

That human touch, I think, is underestimated, particularly as we, again, diffuse from just the early adopters to the vast middle of this industry. Yeah, we're just at the beginning of this game. Well, Peter, that video was Zamjad Masad. Do you want to tell the story about how easy it is to build software from, maybe from... So, you know, I was flying from Santa Monica to up to San Francisco to Stanford. Dave was already there, and we were interviewing, and Salim was there.

were interviewing I'm Jod about about Replit and you know I had downloaded Replit but I'd never really used it and so like damn if I'm not going to give it a try so I you know have Starlink on my my SR 22 turbo my airplane so I'm flying the airplane on autopilot I've got the Starlink antenna on the front and I plug into Replit and I coded up a mindset app on the flight there and it was fantastic right so it was like that was that was so easy easy, you know, zero requirements. I just needed to know the single most important thing, again, if you're new to this, if you're just a fan of this, if you haven't played at all, right? Repplet's amazing. There are other platforms lovable and others. It's critical for you.

Just try and play. And, you know, bring a curiosity mindset, your playful mindset. And if you know what you want to exist, the AI systems will help you get that into. existence. And it's only going to get easier. It's only like your domain knowledge will be extremely important and the product creation, you know, use Blitzie, it'll be easy, easy, easy. So before I drop, before I move past the conversation about Replit and vibe coding, Brian, you're taking this level of coding to a brand new level. How do you apply this to industries, to entrepreneurs? What are your thoughts? There's two classes of software, right? There's this disposable widget-based software that, Peter, you built with Starlink on your plane, right? And this is the idea of getting this

concept into a prototype. And then there's two enterprise scale software. I'm going to have thousands or hundreds of thousands of users. I'm going to have concurrency. I'm going to have good caching, right? And that's the part of the system where Blitzy fits in. And so everyone's having this Peter experience, right, where I can create something quickly. And then they're getting to the enterprise scale, and they're getting none of those gains, right? And so we've brought the vibe coding speed to the enterprise scale. And we can do that for the new entrepreneur, building the insurance product, or we can do it for the existing enterprise. That's doing large-scale development. But the idea is, like, velocity from an engineering perspective, is dramatically

higher than it's ever been. So it's never been a better time to build. Do you interface with mid-level managers and companies, or is this got to be a top-down for people who want to use Blitsey to, you know, sort of improve their product and capabilities. Yeah, anyone that leads a large engineering team comes and works with us. So lots of times, CTOs and CIOs will come meet me directly. But you also have, you know, VPs of engineering that say, like, I'm going to make my company go faster and I'm going to weigh in and I'm going to bring Blitzie in and be the first to do it.

And we love those folks, too. Got it. Got it. Great. Here's our next one comes from Andy Jassy, CEO of Amazon. He's like, wait, wait, wait, wait. You know, we're going to build glasses, too. Meta is not going to lead the way here.

There's got to be someone else. So Amazon is developing their own AI glasses to challenge meta. And what I found fascinating is that these glasses are going to be, there's a consumer version, but importantly, there is a version that's going to be used by their drivers. And the drivers are going to be recording everything. And for what use, it's to train the future robots. So this is codenamed Jayhawk, expected to launch in late 2026 or early 27. And today, the company plans to pilot 100,000 units by Q2 for its workforce of 390,000 drivers.

So, Eamon, I think you said something about this earlier, right? This is how we're going to get the data to train up new systems. Yeah, I mean, it's kind of obvious. you're going to have seamless data to train up the robots of the future from these kind of fleets just as to replace the workers of the future it will just scan all your slack messages and code commits and create a virtual version of you yeah but the reason is the technology is good you know it's been 11 years since google glass i think it was 2014 wow you remember that they look stupid at the time i remember now the new metaglass yeah they work and they are useful and they are light

So how can you do your job now without being augmented? I think this is going to be the next part. And it just feeds back because the glasses and the guidance will just improve until it's perfect almost. I love it when Ahmad says it's kind of obvious. It's just like when Alex answers those like Humanity's last exam questions. Like, oh, it's four, of course. Well, you know, competition is great.

You know, we've seen there are a number of companies creating glasses. There's X-Real and others, but it's really to productize these and make them so cheap and so consumer-friendly that they become, you know, I still remember the first time I saw someone walking down the street with an earpiece talking to themselves. And I was like, is that person crazy or what's going on? I don't know if you remember that experience the first time you ever saw somebody with the equivalent of what is now an AirPods. And we're going to start to see people walking around with glasses. We talked about this in the last pod. You know, are you going to be comfortable with everybody recording you all the time? I think in the beginning, you will not be comfortable, but then it'll just be assumed.

You're always being recorded. The idea that privacy exists is going to be a long, lost concept. I don't know if you guys disagree with me. Well, I think it's interesting. No, no, no, it's definitely, yeah. It's a long conversation. But what's really interesting to me is that of the Mag 7 today, you have three secondhand CEOs, Andy Jassy being one of them.

Now, Amazon is the best managed company, I believe, in the history of the world. And we teach all of our executives and our teams, the OP1 planning process that Jeff Bezos and Andy Jassy invented. Incredible company. But you've got three legacy CEOs, Andy Jassy. So you've got Apple, Microsoft, and Amazon. And then the other four are founder-led CEOs. Well, no, I mean, you've got the CEO of Alphabet, right?

Oh, Sundar Pichai, yeah. So you've got four, okay, so four second-hands and three founder-C-Eas. You're right, you're absolutely right. So it is interesting because here you're like, hey, we're going to do glasses too. Or Apple's like, oh, we're going to add AI to our products too. It's like, okay, that's not exactly. I mean, listen, you know, founder-led, Outer-led companies are able to make much more dramatic right-hand turns and say to the shareholders,

listen, I've made money for you before. Just believe me, this is what I'm doing, like it or not. Elon does that every single day. We're seeing meta do that. Anyway, all right, on to our next subject. Albania points the world's first AI-made minister. So I find this fascinating. I think we're going to have more of these in the world. the goal of this AI minister is to tackle corruption in public tenders through fast, efficient, impartial decisions. Imad, you know, you and I have talked about this a lot. Both of us are part of the, in fact, in Dave is you as well, part of what's going on in Riyadh and Saudi at FII.

We're going to be meeting with ministers talking about how to use AI to run their policies and their governments more efficiently. How do you think about this, Iman? well I don't think anyone thinks is there anyone listening in here which thinks that she won't do a work she won't do a better job than the existing ministers I mean like this is kind of the bar I think again this is inevitability the AI will incorporate more and more of our decision-making systems and be representative of us until it makes those decisions because it will do a better job and the question is just how and why will that happen I have to say though in the launch video there was a bit of creepiness because she said, I'm very disappointed at how people have perceived this. Now, it's either a person telling her to say that,

which is one thing, or the AI itself is disappointed, which is another kind of words. Yeah, so the real question, of course, is if you've programmed or you've stood up in AI minister, what data have you provided to it, him or her? And is there a bias in that data? Does the person who controls, you know, the data center control what the minister is going to do?

Can you inject it? I mean, there will be a lot of debate about the impartiality of these ministers. Like it or not, we are humans. I spent my early childhood in Iran and Brian spent a fair amount of time overseas too. And, you know, the global standard is corruption. You know, areas that are not corrupt are extremely rare on a global scale. albana being one of the worst or among the worst and this is just going to be nothing but good even if it's not perfect in terms of its UI it doesn't matter it's not going to deliberately take

your money or ask you for a kickback or a bribe and that that's just such a global game changer so sorry Brian that you were going to say similar like the hurdle rate for success is so incredibly low so I think the AI can be right 80% of the time and it would be better than the current status quo. And it would sort of be randomly messing up as opposed to sort of purposely driving money to a family member. And so it's only going to get better. So I think this is really a great thing for Albania. Yeah. All right. Our next segment in our WTF episode today is energy robots and transport. Here we go. Listen up to our U.S. Secretary of Energy. I don't agree what he has to say, but let's hear it. So Elon Musk has it completely wrong. He, he has.

has a wildly exaggerated view of where solar and batteries will go. And if we could make a bet 50 years out, I'll make a bet solar never gets to 10% of global energy. Okay, let me give you some, let me drop some knowledge on you. So today in the United States, there's 18 gigawatts of solar capacity installed in the first half of 2025. Solar accounts for 50% of new electricity generating capacity in the first half of 25 and 69% in the first quarter of 2025. Solar is made up 10.2% of the total U.S. installed utility scale generated capacity in 24, surpassing nuclear and hydropower. It's now the fourth largest electricity source after natural gas, coal, and wind.

Gentlemen, I'll mention one other the thing. NRL, which is the National Renewable Energy Laboratory, which is under the Department of Energy, projects solar could power 40% or more of U.S. electricity demands by 2035. So I think he needs to talk to some of his labs. Yeah, the historic problem, the historic challenge with solar has always been storage, right, which no one's better at that than anyone and when he's built at Tesla. Right. And so solar is intermittent source. And so you'd store it over time and there'd be some depreciation on that storage. But it's essentially a solved or nailer your salt.

solved problem. And so, yeah, Chris is, I don't want to pick any, solar is a big deal. Storing solar is getting easier and easier. And the DOE is absolutely correct on this. You know, the other thing I would say, if he's right about solar, then, go on, go ahead. If he's right about solar, there's no way the U.S. can keep up with China. Yeah. Solar is basically the U.S.'s best shot at keeping up with China. The hard party mod is our solar supply chain is completely tied to China. So it's not about just solar work or is storage going to get better and better. It's getting better

every single year, and Elon's driving that. It's, can we have a U.S. driven solar supply chain or we're not reliant on an outsource partner for what's going to be one of the most important ways for us to capture energy? I think that's a great point. Exactly it. What, you know, we do need to realize

the world is about to change on the back of ASI, right? We're going to have better manufacturing processes. We're going to have new materials. We're going to have all kinds of capabilities that did not exist, you know, today but will exist in three or four years. Can we scale it quickly enough? We'll see. But China has run circles around us. I mean, the numbers are pretty staggering. China leads with 880 gigawatts of solar capacity in 2024 growing at 45.6 percent annually. That's insane. The U.S.

is 177 gigawatts growing at 27 percent. So they're basically lapping us, constantly. You're so right, Peter. We have a fundamental structural problem because, you know, look at all the companies that we've built, you know, Ahmad, Brian, all of all four of us. They're all like, you know, I need three, four, five hundred grand of seed money. Then I need a couple million bucks. And then if all goes well, it's going to be worth billions of dollars. Like, that's pretty damn compelling from an investor point of view. But when you start talking about industries, like real industries like automotive or solar or energy, we're just not making the investments. We have a fundamental structural problem in the country that prevents us from making those investments. And the $200 billion a year venture community is never going to do it and isn't even nearly big enough to do it anyway. And so what happens every time with, you know, 80% of the world's cars were made in Detroit, 80%. Every part of those cars was invented in America. Yet we lost the entire industry. It almost died completely. Obama had to save it from absolute collapse. And now it's kind of coming back. But why? How does that happen? And it happened with LCD TVs. It happens

everything. It's all invented here, cloned elsewhere. They make the investment to do it at scale, to get the cost down, and then they bring it back into the U.S., back into Europe at low prices. With a large tariff. It's just a fundamentally broken machine in the U.S. that's per—well, tariffs are part of that. Well, who pays the tariffs, right? It's a consumer. I think that when China gets its robot supply chain going, it's only going to widen, because those robots are going to build those factories. Yeah, they have a huge lead there. There's a big focus area for David Siegel, you know, the two Sigma founder. So if we want a pod with him, he'd love to riff on this topic.

But he has some ideas on how to fundamentally fix them. Yeah. So we reported last pod about Brett Adcox, you know, figure raising a billion dollars at a $39 billion evaluation. I mistakenly said it was a $93 billion valuation. Sorry to triple your valuation there, Brett. But it was $1 billion. He's under water. Just give it a few weeks.

Exactly. It's $1 billion on top at a $39 billion valuation. Pretty amazing. And Brett is an incredible entrepreneur, you know, who was in the E.V.Tal with Archer Aviation before and has brought his engineering expertise to the table. They've also announced a strategic partnership with Brookfield, and Brookfield is giving them access to 100,000 homes, 500 million square feet of offices in logistics space. So there is a concept right now, and we learned about this when we were visiting Burnt at 1X Technologies. These companies believe they need embodiment of AI to really get to AGI and beyond.

They need to be in different places. And what Burt was saying, remember Dave, was if you're in the factory, building automobiles or distributing packages, you're seeing the same thing over and over and over again. You're not getting diversity. So we need to be in the home, in the office, like a toddler crawling around and getting you data all the time. Thoughts? Yeah, it's totally right. I don't believe that you need that to get to AGI. I heard Burt say it.

I think you can have AGI without that But if it wants to understand your daily life What it means to trip over the kids blocks and bump your head It needs this data to be empathetic and understand that part of life But you can have AGI without that Nevertheless this is exactly right you need all that that kinematic telematic data To build the true motion AI foundation model Yeah and it's these models are inferring physics based on video data

And so it's incredibly hard when you're face with the real world. And so when Brent shifted off of his Open AI partnership, you know, 18 months ago, he made this very, very assessment, which is we have to build our own foundation models that are focused on our own data from rural world simulation because, you know, inferring physics is insufficient for an LLM. And not to be left behind in the robot world, Open AI is ramping up their robot work. It's like, wait, wait, wait, no, we need robots too. So Open AI was in the robot space back in 2021, but they basically paused all of that to focus on chat GPT. And today they have listed a number of postings for jobs on teleoperation, simulation, mechanical engineering.

So if you're listening to this pod and you want to build robots, go check out OpenAIs OpenRoles. And of course, this is a multi-trillion dollar marketplace. Here's the interesting thing. Morgan Stanley, you know, always looking at these reports. And all the reports by these banks are so conservative. They're saying it's a $5 trillion market by 2050. But, you know, when I'm looking at the numbers, you know, Vinod Koslow was on stage last year at the Abundance Summit.

And then we had Brett. And, you know, the low end of this is a billion robots by 2040. The high end, and Elon makes a convincing argument. So does Brett that we're at 10 billion robots by 2040? So if we're just at a billion robots and they're 25K each, That's a $25 trillion marketplace by 2040. I don't know why these guys are low-bowling these numbers. I'll tell you one thing.

When you read the way they analyze this, they use the old business school kind of just project it forward garbage without any concept of either self-improvement for software or self-manufacturing for robotics. But that feedback loop dominates the math in the real world. And that's why they're way, way off in their projections. For sure. It's the classic like Uber's market size.

being the same as taxis. It's so flawed. Great point, Brian, for sure. Hey, everybody. There's not a week that goes by when I don't get the strangest of compliments. Someone will stop me and say, Peter, you've got such nice skin. Honestly, I never thought, especially at age 64, I'd be hearing anyone say that I have great skin. And honestly, I can't take any credit. I use an amazing product called One Skin OS01 twice a day, every day. The company was built by four brilliant Ph.D. women who have identified a 10 amino acid peptide that effectively reverses the age of your skin. I love it and like I say, I use it every day twice a day. There you have it. That's my secret. You go to Oneskin.com and write Peter at checkout for a discount on the same product I use.

Okay, now back to the episode. All right. I want to jump into the economy and Imad love having you here on this and excited when you announce your economic treatise. I'm still predicting Nobel Prize for you, buddy. That's my goal. Nothing less, Nobel Prize in economics. And then we'll do a Nobel Prize and something else for you as well. So here's the slide. It says AI is not a bubble.

Dave, do you want to lead this description here? It's not a bubble. Look at the slide. It's clearly not a bubble. God, I'm not. I really want you to rip on this. But look, I was there. I was alive.

I was actually building companies during the bubble That's changed the course of my life. The dot-com bubble to be specific. And then the market crashing also did. Oh, yeah. Yeah, not the tulip bulbs back in 17. All right. So 16, whatever.

Yeah. No, the, you look, I was on the board of MicroStrategy. Check its history. You know, strategy.com got up to like a $14 billion valuation, I think with no revenue, or certainly near no revenue. This is not like that at all. Look at the red line on the right. So just to describe it for our listeners, this is a graphic.

of Cisco showing its stock price, going from 100 bucks up to you around 700 bucks. But at the same time, its stock price is peaking. It's 12-month-forward earnings per share is pretty flat. So that's by definition a bubble. It's a hype bubble. On the other side of this image, we see NVIDIA. And what we see is that the price of NVIDIA is going up, and it's going up lockstep with the 12-month forward earnings per se.

share. It's generating real revenue, real profits. So, Imad, smack us with some knowledge here, buddy. Yeah, I mean, I think stock market is a bit of a voting mechanism in the short term and calculating mechanism in the long term. What we see with these bubbles is it can be disconnect to the fundamentals. But the real thing here is AI is useful. People pay for it because it has economic value. That's why even when you look at the $100 billion of NVIDIA money going into open AI, that feels like back in the dot-com bubble, we had this round-shipping of revenue, but it never created economic value. Every single GPU that Open AI uses will be booked out because it can do so many

things economically. And that's why this is not a bubble. It's a transition from one type of economy to another type of economy. And I think that's what a lot of people just haven't figured out. And this is before we see that inflection point of what Mustafa talked about earlier, what Brian's working on, of this incredibly long-term kind of planning agent capability that can do really complicated stuff. So I think this will just continue. There will be some weirdness. And when your kind of taxi driver starts talking about generative AI digital assets, that's when you probably know that it's going to be above all. Yeah, when your mom starts talking about, should I invest in this in this company? That's crazy.

Well, just some numbers, you know, just because it was a part of our lives or part of my life. You know, the hottest company in the world by far was Yahoo back in the internet bubble. And, you know, it's hard to imagine that now, but Yahoo was the dream of all dreams. And it went public at a $300 million evaluation, laughable. And then on day one, it got to a billion dollars. It was trading at a billion. The press went like crazy. like this, that's insane. It has less than 100 employees. How can be worth a billion dollars? That's nuts. So then after that, they got super acquisitive, bought a whole bunch of assets, got all the way up to about 110, $120 billion valuation at the peak of the market there. And then the capital got cut off almost overnight. And then 9-11 happened. And the market imploded. So it went down 95%. And then, you know, pretty quickly after 9-11 recovered again and settled around asset values, so around $50 billion.

Okay, so then, you know, not much happened after that, eventually got acquired, whatever, gone. So Jensen now is on top of the world. He's investing $100 billion into Open AI, buying everything, which diversifies that value, you know, $4.5 trillion dollar valuation. So, you know, not only are the revenues and the earnings very real at NVIDIA, but they're also diversifying and aggregating power and equity stakes at an incredible clip. So, you know, it is price to perfection. That's also true, too. But the foundation here is very real. Nothing's going to change the world more than what's going on right now.

It is definitely not a bubble. It's not even vaguely like a bubble. The one way you can tell a bubble, and that's when people come up with brand new statistics, like Yahoo's valued per eyeball. So if Nvidia's value a transistor, then we know there's an issue. Brian? I think people miss the latency between. the KAPX involved in creating the internet and the value that came out of the internet, right?

The dot-com bubble, like by any means, a few dollar cost average in the year 2000, even the height of the bubble and then waited 10 years, you had fantastic outcomes, right? But the latency between KAPX right now and earnings is almost immediate, right? Because they're able to translate that. All of the advertising engines are able to translate almost immediately into additional earnings. So this is just a timing, and the timing for AI basically payback is, is immediate. By the way, I want to debil down on what Brian just said,

because I thought I was the only guy on the planet saying this. There was no bubble. The Internet changed our lives more than anything in prior technology. What it was is a catastrophic loss of confidence in our own investment community, and then 9-11 happened right in the middle of it. And we just lost faith in what turned out to be the best investment. And that's when Google was born, right in the bottom of that. Yeah, Amazon.

Yeah. Yeah. To Eamon's point, it's a voting mechanism, right? Let me remind our subscribers. These charts that we're going after, going over, these slides are available to you. If you go to DeAmandis.com slash WTF, go there, download them. As I said before, you know, have a conversation with your favorite AI, you know, large language model about this. Dive in.

This is the fun stuff. This is what Dave and I do all the time. Eamon just knows all this stuff cold. and I'm sure Brian does too, so. I got the two-minute heads-up on this podcast, but hey, it's been so fun. Yeah, well, you got two-minute heads up, and E-Mod got 30 seconds, so there you go. All right, but I love having brilliant people around us that we can have these conversations with. Yeah, I put in a good 20 hours.

All right, I want to have a conversation about this, maybe a little bit of a debate here. So, Eric Juan, the CEO of Zoom, said, we're heading towards a three-day work. week. That will come on the heels of AI. Let me give you a few other quotes here. So Bill Gates, his quote, is a reduced work week to two to three days will happen within a decade. Jensen has said a four-day work week may become the standard. Jamie Diamond from J.P. Morgan has said future generations may work 3.5 days weekly. I like the 0.5. You know, they don't want to say three, don't want to say four, 3.5. Thoughts on this. I mean, you know, day. Dave, you and I are talking about 9-97.

I don't know about you, but I am working. Actually, I get up about 5 a.m. So I'm more like 6 a.m. to 8 p.m. Yeah, seven days a week. It's exciting. I don't want to let a day go. It's like this is fun. Three days a week.

Yeah, I totally agree. I mean, it's just hard not to work constantly because it is fun, like you said. But there's so much. I mean, just keeping up with everything going on consumes a full week. work week. And then you have to produce on top of that. So I'm seeing a lot of divergence here. You've got all these people that I know around here that are working 996, 997, just crazy. And then we're predicting that workloads will go down for everybody outside the building, apparently. But it's not clear to me how that works. Like if I'm doing something and then AI can do it

better, why would I be doing it three days a week? You know, what does that achieve? So I don't know. Yeah. If a human is providing like economic value that's driving up the value of the company and it has some relation to the amount of input that they put in, they're probably going to work as much as the company will force them to work, right? Like five days, six, day, seven days, because they're ultimately competing with some other firm. So either they don't need the human at all or they can have somebody for five, six, seven days a week. And so the in-between doesn't really make sense because we're competing against other folks that aren't going to make similar decisions. Imad, what's your thought? They're all going to get government jobs. I mean, so seriously, like, again, humans will have negative value in cognitive labor in a few years. So you've said that, I want you to double down on that conversation. It's a really important concept where humans have negative value in the equation.

What does that mean? You're working on a team, and you're the dumbest person on the team, you drag it down. You're working on a team with AI The AI's are smarter, more capable than you They never sleep, they learn perfectly from all their mistakes And they can take in 10 million tokens or words at one point You're not going to be able to keep up So what does that look like?

Okay, we might create new jobs No one's really been able to articulate what they are You know, apart from entertainment and a few other things So you look at the 1929 emergence You have jobs programs, you have an expansion of the public sector And more Maybe we figure out taxation But I think when you look at a three to four day work week,

your job is your identity, it's structure, and it's more. You can't just have people unemployed. So I think they will have jobs, programs, and others with a three, four day work week, giving some sort of social security net. And that's what it kind of looks like, because if you're in a job where your role is to beat other people, as in private sector competitive jobs, particularly in knowledge work, you're not going to beat an AI.

And then in a few years, your muscles aren't going to outcompetitive. or your skillet plumbing isn't going to outcompete a robot. So just to give two examples on this idea that humans drag down the average and have a negative impact on value, this is where, for example, if you have self-driving fleets and a human enters that and drives, that human is likely to have more accidents in the self-driving fleets. A stat from about six months ago, there was a study done out of Harvard and Stanford in the medical space. And it looked at physicians diagnosing versus physicians with GPT4 versus

GPT4 on its own. The numbers were insane. So a physician diagnosed 74% of the time successfully on their own in this particular study. A physician using GPT4 bumped up two points to 76%. But GPT4 on its own was getting it right 92% of the time. So the human in the loop was actually doing damage. We're biased. We're not able to have pure thought and decision making there. Actually, I think you're going to start here. If all cars were driven at Waymo level, we'd save 40,000 lives a year and a trillion dollars in societal costs.

Amazing. Yeah. Amazing. This sort of, this staff from Eric, this is the organizational point about just having fewer people. So I think we're going to see, there's this number called the Dunbar number, which is like 150 people is sort of the max amount that you can have in a network in your head without having lost all the folks. So it's likely we're going to have a bunch of organizations of about 150 people because the 150 first is actually negative in a cost of communication no matter what. So you max that out, use all the AI you can and sort of like get the jobs to be done. thrown into the economy through your organization.

Yeah. So curious about this one, we talked about Deolingo a few pods ago, especially because of the breakthroughs coming out of both OpenAI and Google. So Duolingo CEO says AI made employees four to five times more productive, no layoffs. We reported no full-time layoffs since the company went AI first, and AI has sped up lesson creation in languages, math, and music. and Duolingo raised revenue forecast to $1.02 billion from $996 million. Dave, what do you think about this?

Well, one thing I can say for sure, just based on these last two slides, if you look at podcasts and interviews from maybe three or four months ago, they're very, very honest about job displacement and job loss. All of the big wigs now are switching to, oh, it's going to be great. There'll be a three-day work week. You'll be, you know, it'll be fine. And, you know, here, hey, we used AI everywhere, but we didn't have any layoffs. I think that everyone is now worried about wholesale panic and, you know, pitchforks in the streets.

Yes. And so they're not being particularly honest about the way they see it. Now, that being said, there's going to be massive amounts of abundance. There's more than enough success and happiness to go around. But there is no mechanism right now for distributing it. It's going to land in like five or ten or twenty hands or, you know, maybe a few more than that. but a very concentrated subset if things just evolve with no change. And that's just the reality of how things were evolving.

And, yeah, occasionally a company will grow so quickly that there are no layoffs, but many, many other companies are going to say, wow, half the headcount can go because I AI'd it. So, you know, I'm just seeing a lot less honesty in these interviews. Your Lingo is growing 30, 40% a year. It should be growing its employee based 3040. if it's on to yet. Yeah. Interesting point.

Yeah. So it's standing still. Well, this is what Mark Benioff talked about as well. You know, we're growing, but we're not growing the number of engineers with agent force there. I thought this was important for us to talk about. NASDAQ pushes to launch trading of tokenized securities. And so the U.S. to become the first exchange to move with this initiative. And, you know, it's not.

enough for us to trade five days a week, you know, eight hours a day. We want to go to 24 hours a day, five days a week, and then it'll be 24-7. So if approved, we'll see the first tokenized trades rollout by late 2026. As a reminder, Robin Hood, at least their EU version in June and July, started, launched with tokenized stock tokens for 200 U.S. stocks. They've been trading 24-5. Robin Hood also, on their EU platform, rolled out stock tokens for private companies, OpenAI and SpaceX. So I found that pretty fascinating. It hasn't come to the U.S. yet, but it most likely will. Thoughts about this, Dave?

You've just been trading successfully on the... Actually, there's another one this week, Better Mortgage out of nowhere. You guys can look it up, BETR and check it out. What is Better Mortgage? Well, so Better Mortgage is one of many companies, including GoHealth and one I'm involved with as chairman, that if they implement AI correctly and their workflows have a huge instantaneous lift. And Better Mortgage is a great case study. So Better Mortgage is an online marketplace for mortgages. They swapped in AI workflows and AI voices. It works really well. Nobody's paying attention to these microcaps. So they trade very cheaply with virtually no liquidity. No mutual fund can touch them because there isn't enough float. Anyway, it's AI-fied at some time. I'm writing it down.

Better. Write it down. Just make the trade live, Peter. Good on Robbett. Yeah, I get that. One second, I'll be right there. Yeah. Okay.

There's a whole theme there, though. You could probably query them up relatively quickly. So all you want to do is look for companies that have huge amounts of consumers passing through their pipes, any type will do. and then look at the management team and say, is this management team going to AI this or are they going to miss the window? And if it looks like people that will AI and they already have lots of consumers.

This is not investment advice. I'm supposed to say that every time we mention it. No, yes. That was an investment advice. It's just a thought. But I'm curious about this idea of tokenized securities. I mean, we're heading towards a world where everything's tokenized

and our agents are going to be trading them for us. We desperately need this, too, because, you know, going public is very, very onerous and getting more onerous all the time. Oh, my God, yeah. But companies are getting created and growing faster than ever before. There needs to be an easier, shorter, closer liquidity pathway, and some kind of reliable, trustworthy, token-based pseudo-IPO

would completely open up the economy. It would solve a lot of the problems we talked about earlier in the podcast, actually. So this could be the structural change we really, really need, to bridge the gap between, you know, early-stage venture and then IPO, which is only accessible above, you know, $20, $100 billion now. I mean, U.S. monetary velocity is not really recovered since COVID. It's still below the decade below COVID. Crypto is legal in the U.S.

Apparently GDP is going on the blockchain, the Treasury Secretary should have said, whatever that means. Like, if you want to see what a bubble looks like, just look for the next three years in digital assets. That will show you completely what a bubble looks like. Genentebeye is the proper thing. This one will be insane. I think you'll be able to trade stocks on X by next year. You know, everything is a go. In fact, you'll see blockchains from Stripe to Amazon to Google.

Everyone is launching their own blockchains now, because finally it's legal. Totally right. And not to get too technical, we can cut it out of the podcast if it gets too technical. But historically, the reason the IPO market exists is because it's massively regulated by the SEC and you have all these gap accounting standards. and you have to do you want to prevent you know widows and orphans from losing money in

in deals? Yeah, yeah, and so now all of that all of that can be done by AI. And you want to employ enough lawyers. And you want to employ enough lawyers and, yeah, and accountants. It's the biggest accounting lot of thing in the world. But the AI can do all of that now.

So you can have a perfectly fair and valid reporting system that is on the blockchain that is far better than what the SEC currently does and what your 10Q reports currently do. In fact, your 10Qs are so full of legal garbage. They're almost unintelligible without AI anyway. So why not make this all seamless? Move it to the blockchain. It goes all right into ETFs anyway. So there very much is a solution in there. It's really a good idea. All right. Let's move. Go ahead, Brian. Yeah, right this up here.

The top desal private companies are larger than a huge portion of the public markets. And so the IPO market has gotten so onerous right now that private investors get access to all of the best deals in perpetuity. Companies like straight, the data bricks. And so if you want to solve that, there needs to be a structural shift. Yeah. All right. We'll move into our final segment here on health. And here's a piece. Apple Watch hypertension alert receives FDA clearance. So listen, hypertension is a silent killer. 1.5 billion adults, 30 to 45 percent of the population, 60%, if you're over 60, is affected by hypertension. It's a systolic of 130 or greater and a diastolic of greater than 80.

And the challenge is that 46% of people with hypertension goes undiagnosed, and only 21% is controlled. So if you can, in fact, get it handled by your Apple Watch, give you a heads up. But this is the beginning of basically wearables and sightables becoming part of our daily life. So, you know, I'm wearing a continuous glucose monitor. I've got my aura ring, my Apple Watch, and I'm dribbling data actually into my AI, my Zori AI that I have had found. And all of that data allows me to ask critical questions about my health. You know, has my deep sleep varied or my CGM levels varied with any. particular medicine I'm taking or any particular supplement I'm taking. So it becomes really

incredibly powerful. But what I really find exciting in this space is this announcement from Demis. DeepMind CEO says AI could shorten drug discovery to months. So Imod, you've been thinking about this a lot, the impact of AI on drug discovery and on health. What are your thoughts here? Yeah, I mean, healthcare had to assume this ergodicity thing, like, we're all the same, we're all statistics. Everyone gets 500 milligrams of paracetamol, for example, which, you know, the whole ASD thing. Actually, paracetamol can impact you a bit more if you have a cytocrine P450 abnormality, which causes metabolism. But how do you know that unless you've done tests like phantom life, right? Yeah.

There's two parts of this. One is the ability to take all that data and think about everything formful. first principles, how all your systems interact. Then there are things like isomorphic labs, which, you know, Demis leads, one of the spinouts there. The whole drug discovery thing, we can understand how compounds affect every part of our system, and then that can accelerate these elements as long as they don't, again, get caught up by FDA and other red tape that's unnecessary. Similarly, even as we do the trials, right now we just take down such little data. We can ask people how they feel and get massively rich data that comes in.

that allows us to extrapolate because data is data, knowledge is knowledge, and we know how to compress and analyze that. I think you will find brand new drugs, like again the first AI design drug for my somorphic and clinical trials, and we're seeing that elsewhere. But even repurposing of existing drugs, I think will have a massive impact because, again, you have all this annex data that's out there.

We have a whole bunch of compounds and we'll finally be able to analyze the masses of papers and trials properly to actually solve things. here's some of the numbers so the first AI design drug comes from a friend Alex Severankoff my bold venture capital fund is a investor in in silica medicine just for full disclosure but they've designed a drug for idiopathic pulmonary fibrosis that's in human trials right now and then there's a drug called DSP 1181 I love the names of these drugs and it's for obsessive-compulsive disease.

And in particular, it went from design to human trials in 12 months. Normally it takes four to five years. Here are some additional numbers. 150 small molecule drugs were discovered via AI first in 2025 alone. And at least 21 drugs have completed phase one successfully with a success rate of 80 to 90 percent, which is stunning. You know, we've talked about this, Imad, that health and education are going to be two of the biggest areas fundamentally disrupted by AI, and it really uplifts humanity. Yeah, I think it's just super exciting, and I think what will be really interesting is, I reckon in the next five years, you might actually have part of the FDA process. what is the in-silico, as it were, predictions of these drug trials and other things like that.

And again, every part of that process, I think we can just shrink down and we can cure so many diseases as well as improve our own. Dave, closing thoughts for today. I don't know how we're going to keep up. There's just so much every single week. You know, it's funny, we were just riffing, what, for an hour, hour and a half, and I don't know, whatever it was. But we had a whole other agenda we were going to talk about today, too. We're going to have to reschedule that. But hey, this is the way it's going to be for the rest of our lives.

Or at least for the next five years, the pace of acceleration is just crazy. And you've got to be in a full sprint mode, at least for this time period. I think, Ryan, it was great that you could join us today because your insight on now is the best time. There will never be a better time. There never has been a better time. Maybe tomorrow. I love the fact that we pulled down the – well, the windows come and the windows go. So it's great to have your insights today.

Yeah. Yeah, good to be here. And Brian, I just thank you for the support you're giving this pod. A pleasure to have you and excited for those of our listeners, subscribers who have reached out to Blitzy. Super cool. Yeah, and Imad, excited. We're going to have you back on the pod in about a month when you come out to X-Prize Visioneering. We're going to do a live WTF episode.

at XPRIZE Visioneering, which will be a lot of fun. And you and I will be talking a lot before we get to Saudi Arabia right after visioneering. Anything you want to tell us about intelligent internet right now? Yeah, now release the new book on The New Economy, The Last Economy.com, and we'll be releasing brand new math on how to think about the economy as we'll be forward when humans aren't the marginal innovator. It's a crazy time, and we've got to think about this really carefully. really is rewriting fundamental economic theory, period.

Yeah. Brian, we stole you away from some meetings. What's your lineup for the rest of the day? You're just building furiously or engaging with customers? Yeah, I'm going to hang out with customers. I like to hang out with the West Coast clients between 6 p.m. and 9 p.m. because it's still work time in their time. Amazing.

All right, everybody. Thank you for another great episode of WTF. Please check out the slides at deamandis.com slash WTF. Join us as a subscriber. Tell your friends about what we do. Our mission is to share sort of this extraordinary acceleration that we're feeling with you, educate you along the way, have fun, but get you ready for the new economy that Imaud is writing about, get you ready for the extraordinary future coming our way. I hope you'll trade an hour on the crisis news network for an hour with us instead. Everybody have an amazing day and night and week.

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