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 bomb. >> 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 sales. GR 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 a moonshot, ladies and gentlemen.
[00:01:00] >> Hey everybody, welcome to Moonshots. Another episode of WTF Just Happened in Tech. I’m here with my Moonshot mates, uh, Dave Blondon, the CEO and head of Link Exponential Ventures. Immad Mustach, the head of intelligent internet, a dear friend. Immad, you’re in where today? You’re in London. >> Yep, in London. Nice. And uh Brian Elliot who you guys met on a previous podcast. Brian is the CEO of Blitzy. So a lot to discuss as always. Uh if you are ready to plug in guys, start taking notes, start listening. Uh this is the world that is transforming how we live our lives. Before we begin with anything else, I want to talk about the wakeup 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 uh at this graphic, and I’ll, you know, sort of look at it for everybody here, uh people
[00:02:00] who say it’s very important have dropped from 75% in 2010 to 35%. Right? The wrong direction if you’re a college university. Um 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. That Yeah. Your thoughts? >> I I I couldn’t believe like I I knew this was happening, but these numbers blew my mind. I immediately sent it off to David Seagull, you know, the founder of Two Sigma. >> Yeah. >> Uh because we’re going to go meet with Sally Cornbluth, the president of MIT in a few weeks. I’m 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 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
[00:03:01] the top guys at MIT. 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 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, Rman Board in a private university today is a quarter of a million dollars and you’re saddled with debt and you don’t make it back because you’re not getting the jobs. Uh it’s crazy. You know, uh Brian, uh you’re closer to college than I was than I am right now. How do you think about this? >> I mean, it’s college has been a credentiing 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 indicator of this has been dropouts of MIT. Yeah, totally. For free. Yeah. Dropouts get funded uh
[00:04:01] 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 credentiing 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 >> I’d love to see the problem of >> I’d love to see the graph of of dropout rate in year 1 2 3 sort of increasing over time especially in the last few years and and I mean you know you sort of stopped and started and you know finally went and collected the piece of paper uh tell me about how you think about this >> yeah it took me like 20 years to get my pieces of paper um from Oxford. That was a hole to do. I think that there were probably two things here. I think the first boom was that uh tuition expense boom that we saw. I think that’s caught in the first part. I think the second part was probably co >> like that was a terrible experience for a lot of people in college.
[00:05:00] >> 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 Mloffson and others >> that showed early stage uh 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 visa changes etc. >> 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 uh 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. Uh while everybody else
[00:06:02] with some college or just high school, in fact, high school college graduates are 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 unemploy unemployable people in the world are college graduates. Uh it’s just hilarious. But it’s bad VR for colleges. bad PR. >> Yeah. >> Well, if you look back uh, you know, 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, you know, 20 25 years ago. Uh, so this is a pretty rapid shift in society’s perception uh of the value of a degree. Um, now now keep in mind within this entire chart, the ent the unemployment rate is extremely low. It’s like four and a half%. So, you know, most people are finding jobs. It’s not implying that you Well, actually, we can go 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
[00:07:00] 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 subtier institutions. Uh 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 as a as a sort of a way to just fund uh fund poor education in a way. >> Yeah, 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 you got accepted by a specific university. You know, when someone says, “So, Emod, you went to Oxford or 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 what you studied. It was like, you know, yeah, I went to MIT. That’s all that matters. That’s the highest order bit. >> Uh, 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.
[00:08:00] >> Yeah. >> All right. If you if you go to the next slide, it really makes Brian’s point. Okay. Here’s here’s your 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. Uh so it’s up almost 900% in tuition over that time. 5.6 increase average uh average annual increase. >> Yep. >> Yeah. So you 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 uh 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
[00:09:01] 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 what do we do? Uh, we need to reinvent how we educate. Uh, 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 credentiing 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 faster. We’ve seen Alpha School and others show just in two hours a day of tuition, they’re ting 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 cuz it just got too expensive. Like in the UK, Oxford costs $13,000 a year for
[00:10:02] 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 networks, 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. Uh we’re going to have Mackenzie 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, uh, educators, uh, we’re going to get ready for a fun episode on the 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 supercomput clusters down because the universities in the US don’t have them. That that’ll probably be the biggest determinant of research quality in universities, how many GPUs you have. >> I totally agree. I love that. >> I think it’s a no-brainer. All right, MIT, listen up here and you put the
[00:11:00] endomment to use. >> They they want to there there are forces in the school that desperately want to do exactly what Emma just said. I don’t know what the friction is, but we’ll work on it. >> Get JP Morgan to fund it. There you go. >> Every week, my team and I study the top 10 technology metat trends that will transform industries over the decade ahead. I cover trends ranging from humanoid robotics, AGI, and quantum computing to transport, energy, longevity, and more. There’s no fluff, only the most important stuff that matters, that impacts our lives, our companies, and our careers. If you want me to share these meta trends with you, I write a newsletter twice a week, sending it out as a short two-minute read via email. And if you want to discover the most important metat trends 10 years before anyone else, this report’s for you. Readers include founders and CEOs from the world’s most disruptive companies and entrepreneurs building the world’s most disruptive tech. It’s not for you if you don’t want to be informed about what’s coming, why it matters, and how you can benefit from it. To subscribe for free, go to dmmandis.com/tat trends to gain access to the trends 10
[00:12:02] years before anyone else. All right, now back to this episode. All right, let’s jump into the AI wars, our favorite subject every week. We’re going to kick it off with the fact that Gemini overtakes chat GPT in the US. So, this is based on iOS sales, 150 million uh users. We’ve seen Gemini go through this viral element. I mean love Nano Banana V3 and others and they’ve jumped into number one position. Uh any particular thoughts here? >> I did not believe it if because Chad GPT had such a huge lead. Um so I checked the app store data directly and it is absolutely true. Now this is US so uh you know chat GPT is still miles ahead globally. Uh, but you know, Google can use its massive distribution power to push that. That’s how Chrome bypassed Firefox and you just push it out. It >> didn’t bypass it. Blew it away. It >> blew it away actually. >> You know, I checked Poly Markets on this. Interesting enough. So, I I checked on Poly Market score, which is really fun to do if you guys if our
[00:13:01] subscribers haven’t done that. Uh, 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. Uh the current top prediction is 40% by October 31st. So maybe by the end of 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 Quen. I find that amazing. How do you think about that, Iman? Well, I think we’ve seen the gap close 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
[00:14:00] 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 daily active 15 million daily active users. And I feel that this Gemini chat GBT 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 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 Quen models keeping up because they’re used so widely now everywhere. And they are closing that gap. All right. Uh not to be left out of the conversation, uh Gro 5, this is a chart says Grock 5 could reach AGI first. Uh and uh the fact that we’ve seen it beating all the AGI bunch uh benchmarks and in particular here what we have is Gro 5, you know, reaching top marks on the ARC AG uh AGI benchmark, which is
[00:15:02] the abstract and reasoning corpus. Uh so uh right now in the arc AGI v2 uh Gro 4 has hit 15.9% which is the highest known. Are you tracking these Eman? >> 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 OpenAI might release their verifier runs but all these benchmarks are saturating so fast. I think that um who was epoch research predicted that every benchmark in the market today will be saturated within 3 years, four years. >> We need new benchmarks. >> Just simple extrapolation, >> Dave. >> We need new benchmarks. But the crazy thing >> crazy thing is >> this is V2 though. We already saturated V1, but V2 is crazy hard. >> Like if this one saturates, then you’re you’re beyond superhuman intelligence. Uh, so this this one if this one
[00:16:00] 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 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 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. It’s still only been one year since 01 was announced. >> That’s that’s crazy. Ancient history. >> That’s funny. And so, uh, here we go. Gro for fast Reasoning. I love these names, right? Just appending, you know, on the on the end of them. Gro for fast Reasoning ranks number one on the extended New York Times connection benchmark. So, what is that? Uh so this is uh based on New York Times puzzles where players must group 16 words into four groups uh each belonging to a common semantic uh category. Uh the extended version, the
[00:17:00] 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 vanity benchmarks to sort of brag get bragging rights. Uh yeah, the actually I talked to Alex about this one. Uh he’s off in Europe today. But uh >> by the way, I should say Sim is MIA. Sem, where’d you go, buddy? Um and uh and Alex is on a top secret mission in Europe. I’ll leave it at that. >> This there this is a really fun benchmark here, though, because uh you know, if you go to New York Times and you and you do the connections test uh or it’s a daily puzzle. It’s really fun. And actually, my wife does it every single day with her friends. Um, 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. Uh, but the theory here is that
[00:18:02] the 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 Blitzy announcement on our podcast, very careful to say, “We topped SweetBench, but we did not tune or or benchmax to that test. It just happened this way.” Yeah. >> Uh and and here we’re almost sure that they’re they’re trying to get the PR by benchmaxing and optimizing toward the problem, >> but you can’t prove it. But it’s uh it is a crazy high score though to get in the 90%s on this. >> Amazing. All right, you know, here we go. This is going to be the data center wars. XAI’s Colossus 2, a gigawatt scale data center, 110,000 GP200 uh GPU clusters. I love this. 119 aircooled chillers and Tesla mega pack. So, this is the beginning of Colossus 2. Uh Imod, you tracking this, I’m sure.
[00:19:00] Yeah, I think Elon said he’s going to be the first to gawatt, the first to 10 gigawatts, and the first two terowatts. >> Yeah, this is uh this is this is his his tweet uh from today. Uh yeah, OpenAI is bragging about their NVIDIA uh partnership and here he is saying just as we were first to bring a gigawatt on of coherent training compute online, we’ll be the first to 10 gawatts, 100 gawatts, and one terowatt. Love that. >> It’s it’s basically like as much as a state now. um these things will be drawing down. The whole of the Bitcoin energy is about 20 gaw if you look at it as well. That’s about as much as the all of Argentina is a 10 gawatt 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
[00:20:00] the US. >> Amazing. Uh, here’s our article on Nvidia investing hundred billion dollars into open AI. Uh, there was a great CNBC piece that had Sam Alman and Greg Brockman and and Jensen uh speaking together and let me just quote what they say. They say this is Sam saying hundred billion dollars is a small dent in the scale of our plans for 10 gawatts of compute. uh this data center will be a multis square mile level of infrastructure. The stuff that will come out of this superb brain will be remarkable. Uh I love I love that right multis square mile superbrain. I mean tiling the world and Greg Brockman then comes on and says we really want everyone to have their own GPU 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
[00:21:00] future where it’s compute scarce. And then Jensen comes on finally and says, “Hey, this project is 10 gawatt or roughly 4 to 5 million GPUs. That’s approximately what in putting into one project what we what we sold all of last year and double what we sold the year before and double we sold the year before. So just massive increase. Uh Dave, how you think about this? >> Tie tie together those last few slides and really open your mind to the compute scarcity that’s coming up. So you got a hundred billion dollars. The US 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 US venture in a year. Uh 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 isn’t is Jensen gonna be able to make this year? It’s about five 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
[00:22:02] 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 this, you know, 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 chip manufacturers, uh, 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 into crypto. Uh, Immod, how do you think about this? Yeah, I mean I think who who controls this is the marginal producer in the economy, right? If you look at OpenAI’s projections to get to 200 billion, 80 billion comes from this brand new AI agents line and then other is another like 2030 billion. They’re going to be rolling out AI workers that work around
[00:23:01] 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 cuz 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, when as a builder, as a CEO and entrepreneur, uh 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. Uh you want to lift all ships. So I don’t think if you are a sort of healthy player in the ecosystem, it is uh 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 uh economies of scale are going to matter a lot here. >> Here’s a chart uh reinforcing this. Lab
[00:24:00] compute has 3xed in just one year. We see a graph showing OpenAI, XAI, meta and anthropic. Open AI at the top, XAI coming on strong. We don’t see uh Google on this or Alphabet uh which is interesting. I don’t know if any any comments on this. I’m going to couple it with the next slide here, which is that data center capacity uh is expected to go up four-fold uh by 2030 going from 44 gawatt to 156 gawatt. 44 gawatt today, 156 gawatts by 2030. And from what I’m hearing, that seems like a low ball estimate as well. McKinzy always numbers. >> Demand I think somewhere else in here we have demand is going up 10x year over 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 that can answer the question to try and save some compute. Meanwhile,
[00:25:01] 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 do you worry at all about getting access? And I I I think that a lot of the use cases that’ll be deprived access are like the you know the virtual girlfriend and the you know doing your English homework because you know Brian can overpay you know 100x or a thousandx 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 it’s about the marginal dollar right costs are going to go up dramatically I believe. Uh at the same time, costs are depreciating from the actual cost basis to the to the chip. Uh but the model providers are going to be able to increase cost if they’re number one. Uh and we’re willing to pay that. We’re willing to really pay anything because it’s it’s much more valuable what we’re able to provide than than these consumer type services. >> Yeah, I think economic value per flop is just going up dramatically because you’re at this inflection point. AI
[00:26:00] 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 3 years ago the Exploratorium and we had a slide go up saying you know we have 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 if you think the world of economic labor that you can do that AI can do, it’s gone from maybe I think 1 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
[00:27:00] very reasonable because your TAM has gone up your total has gone up so much. And so 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 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’ll be a world of absolute comput scarcity. >> And we’ve seen a little bit of what this is like within OpenAI, right? That that the way that different research projects fight over compute or that the success of the research pro 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. fundamentally it is a physical
[00:28:01] infrastructure problem not just a software problem. Could you imagine the ongoing conversations inside of OpenAI and sort of the the arguments about no, I need the compute to do this project? You know, everybody’s sort of vying for their own special. >> Yeah. >> Crazy. >> I don’t know if you remember, Peter, but when we were at OpenAI headquarters a few weeks ago talking to Kevin Wheel. >> Yeah. >> Uh 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 confused. like we have, we need compute like you. So, he’s just out there finding it. >> So, uh, so yeah, you know, I kind of miss the days when Greg and Sam used to do these things together. You know, Sam is the is on the road constantly now, so Greg is has got to be in the house finding the compute, but but he used to do a lot more podcasting. It was really nice when they were a twoerson 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.
[00:29:00] uh uh you know there will be some kind of a breakthrough on compute right and uh Iman what’s your bet on where we might get some sort of uh 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 um like if you look at the Tonki model by the Alibaba Quen it’s their AGI lab next to their Quen They managed to score I think 22% on humanity’s last exam with 3 billion active parameters >> with 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 in the economy again that 50% of tasks that’s how you can route this down to be highly efficient and we don’t know
[00:30:01] 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 5 10 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. >> Mhm. >> 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 if I could just riff on that for any of the entrepreneurs out there, >> uh what Immad 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? Right now, we’re all used to, oh, I can just get an AWS account tomorrow and I
[00:31:00] 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 for pumped hydro d uh power storage. You missed 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 100 times literally if you have task specific data sets distillation and you have the right verifier it is a 100 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 this is how Dropbox got so big, right? They were the first folks to use S3 and not have to store have
[00:32:01] their own data centers and they were storage. There was a hundred other storage companies. They were just 10x cheaper than everybody else. uh and they scaled off of that and built a very powerful company. Same thing applies to models. >> Looks like OpenAI may get the shackles pulled off it. So open OpenAI reaches a deal with Microsoft to allow restructuring from a nonprofit to a forprofit. So they’re, you know, OpenAI is targeting a $500 billion valuation uh as part of that. 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 uh you need to leave a certain amount of capital and capabilities inside the nonprofit. I won’t go through the the machinations of how you do it but uh as they do this uh OpenAI’s nonprofit uh will be left with about a hundred billion dollars in capital. It’ll be the largest nonprofit you know endowment out there which is amazing uh
[00:33:00] 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 of the nonprofit and they have incredible vision for what they want to do uh to go and solve humanity’s biggest problems with it. So, uh if you guys remember, Microsoft invested a billion dollars in 2019, another $10 billion in 2023. Uh and they’re estimated today to own about 30% of Open AI. That’s unconfirmed. Uh 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 >> just for for context on the earlier part of the conversation OpenAI is is twice the size of of Harvard’s endowment fund which is you know for the longest time been been the largest endowment fund of all time. from a nonprofit status. OpenAI in just a couple of years, doubling the size of the endowment
[00:34:00] fundamental. >> By the can you imagine the relationship between OpenAI and Microsoft right now? So, for example, when when the Nvidia uh uh OpenAI deal was struck, Microsoft was notified the day before, right? So it, 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. >> Yeah. >> I remember when um Mashel Cissson kind of had that commitment for 100 billion to open AI and then someone asked Satia about it. He said, “Well, I’m good for my 90 billion.” I think that Jet Jensen is definitely good for his hundred billion. And you know, like now these are all crazy numbers, right? When Microsoft invested 10 billion or a billion, we were like we’re like that’s big. Now it’s like >> only a hundred billion for the nonprofit. It’s second largest. And we don’t even blink at a hundred billion
[00:35:01] dollars being invested in them. >> Yeah. >> Cuz literally they will spend they will have a trillion dollars of buildout. >> And I think um Elon Musk said something again recently. He was like someone’s like what about anthropic? It 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 >> this goes to our next slide and the title here is Zuckerberg Zuckerberg says better to lose billions than be late to super intelligence. So uh he’s committed to invest 600 billion in US data centers by 2028. Why? because I don’t want to be second to super intelligence. Crazy. >> It’s just staggering. The the the sheer size is staggering. But also the lives these guys are living is completely unprecedented in the world. I mean, you know, Zuck was just at the White House a week ago having dinner with like like look at the look at the table. Look at these people. And then they’re all, you
[00:36:01] know, the president is saying, “How much are you going to pump into the US 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 is like nothing in human >> 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 5 10 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 um do you remember the story of how OpenAI got going with Larry >> um >> Larry Page >> from Google and Elon Musk? Larry >> Ellson discussion. >> I was there for that argument >> and where where you know Elon or Larry called Elon a specist.
[00:37:00] >> Yes. Peter, do you want to do you want to tell the story there? >> Oh, no. Go ahead. Go ahead. I mean, >> well, it’s because they were discussing intelligence and Larry Page was like, you know, digital intelligence. He’s like, can overtake humanity and that’s fine. And I 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 super intelligence first. Like they won’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 Alman. Sam has literally getting attacked constantly from every side, especially by Elon, while needing to beg for money from any source he can get it. Uh traveling all over the world, trying to hold this together, while becoming, you know, taking a nonprofit to make it into a for-profit, which is a 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
[00:38:01] and I’m going to go have a my tie. >> They’re printing they’re printing money on my on my ship in the Caribbean. Um >> the market will reward him for it too. >> It’s it’s a it’s an unreal existence. Dave, you said it right. I mean I don’t know how you remain grounded uh as a CEO of one of these companies when you’re when you’re speaking about literally trillion dollar deals that you’re in. Um, I mean, it’s crazy. >> Yeah, that’s a good concern, too. I I I kind of trust the people that struggle, have either struggled before in their lives or are struggling right now. Uh, 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, >> but we are, just to remind everybody, we are in a war footing. Going back to what you said a few minutes ago, Immad, you know, we’re we’re in a war footing getting ready for the next economy. Just like we came out of World War II with a a brand new, you know, interstate
[00:39:00] highways in the United States and and you and aerospace and and automobiles were gearing up for a new economy and uh 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, hundred trillion dollars 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-ompiles 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
[00:40:02] 5x engineering velocity increase when incorporating Blitzy as their preIDE development tool, pairing it with their coding co-pilot of choice to bring an AI native SDLC into their org. Ready to 5x your engineering velocity? Visit blitzy.com to schedule a demo and start building with Blitzy today. >> All right. Uh let’s look at what comes up next here. Uh Dario Amade on Claude designing Claud. 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 uh super fast, but it’s definitely started. Uh how long before it’s going super fast, Immod >> I it’s the takeoff point right now. There was a recent interview with um Tree Dao who is like the man for writing
[00:41:01] CUDA kernels on Nvidia. So he’s at Together AI and he came up with flash attention that literally increased performance 30%. He’s like I use clawed 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 were already seeing TPUs being designed by AI. And Sam Alman recently said, again, fantastic CEO, fantastic capitalist, but he said his plan is to get 1 gawatt of new computon 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 to model feedback loops and there’s no way that won’t speed things up even more. Can you feel the acceleration? Oh my god. >> Well, look, I spent about six years of my life just purely building neural network and researching neural network algorithms and code. And uh it’s very
[00:42:03] similar to discovering math which Alex is always talking about. So Alex Alex was gross on this pod is predicting I think it was 18 months uh we’ll be solving all math. >> Iman, you’ve been on this you’ve been on this bandwagon as well, right? No, we were >> the AI is I mean look at winning the gold medals in the ICPC and the math Olympiads and things like that. You parallelize it like we’ve been running 1,000 lean provers 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 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
[00:43:00] seen things like um Terrence Tower was formalizing some various proofs and they only got like 20 30% the way in parallelizing that I believe it was more flabs that they did that they managed to 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. >> 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, 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. Uh, but it’ll all be compute constrained. You know, there 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 uh becomes the
[00:44:01] fourth company I like to call it to reach the four comma club. Um you know this is to reach $3 trillion market cap. Uh joins Apple, Microsoft and Nvidia uh in this uh four in this $3 trillion market cap club. Stock is up 33% in 2025 and 55% over the past year. Right. I was talking about last time, you know, for me Google has been an extraordinary bet. Any comments here? I mean, I think the the prediction markets still hold Google and Alphabet to be the long-term winner. Uh, Iman, do you buy that still? I mean, they’re fully integrated with thousands of amazing talents. Dennis 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
[00:45:00] got the full stack. They don’t need to pay the Nvidia tax. They can build everything themselves and they have metas cash. So, why wouldn’t they be up in the lead there? >> Yeah. Yeah. >> Yeah. And just to add one thing to that, too, we we announced or we we spoke about um OpenAI doing their own ships with Broadcom. Uh but they just started. Google’s been working on their TPUs for years. So they’re 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 how do you know that by the way? I thought that uh that’s impressive knowledge. We used thousands of TPUs. We We were down there when they didn’t have jacks. >> Oh, you had stability. You had hands-on access. Oh, no way. Yeah, because they’ve pulled them from the market effectively because they’re using them all internally now. So, it’s kind of hard to get performance specs. That’s really useful information.
[00:46:01] >> Well, they might actually start um selling them soon. We’ll see. >> Yeah. We’ll see if they can. Yeah, I I’m betting I 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, >> we’ll see. There was a there was a little video clip put out by Mustafa Sullivan uh the CEO of Microsoft AI which I found somewhat compelling. Uh let’s take a listen to it. >> At the moment these models are still oneshot prediction engines. You know you 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 d and that is just a computational uh 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. It’s magic
[00:47:00] 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. And I think that we basically have that by the end of next year. >> So I found that compelling. Uh I 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 the there’s so many ways to take advantage of it that we’ve only begun to scratch the surface. Um, I do disagree that the the planning ability I don’t know when this was recorded, but the planning ability has gotten pretty damn good pretty damn quickly. So, uh, this might have been like three weeks ago, but it’s 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 that’s planning. >> It’s crazy. Yeah. 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
[00:48:01] drives. Like again, we actually have all the tools there. >> And in fact, you know, 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 number of domains including software engineering. >> Yeah. >> Nice. Uh we had uh we had the CEO of Replet 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. Uh let’s say I’m I’m a lawyer who is top in the world at solving certain um
[00:49:02] cases that 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 to open AAI 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, uh 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 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? Um, this sounds like a pretty good uh pretty good example, Dave. How do you how would you answer that? Someone mid-career. >> That’s a tough one. Maybe I’ll I’ll
[00:50:00] bounce that over to you big brains on like the the concept I totally get. Like I’ve got domain knowledge. I’m a lawyer. I’m a doctor. I’m a you know, there’s very very specific domain knowledge all over the world. And I know the RHF companies like uh you know Invisible and Merkore are killing it wrangling all that techn all that knowledge 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 it may they may pay me a lot for a month or two but then what then 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 I I would say there’s no barrier to starting a company. You don’t have to be 21 to start a company. >> You you absolutely there’s so much green field opportunity out there. And I do love these companies that have uh a regulatory barrier or a vertical domain, deep tech, deep knowledge barrier. Just start a company using AI in that category. That’s how you might then say,
[00:51:01] “Okay, now it’s sustainable and I can I can make a career out of it.” So that’s always a good choice if but you got to leave your day job and and go do it. I would translate that to find a good problem that you understand deeply that no one has yet solved and go build around that problem. >> There’s never been a better time for these domain experts. I’m more bullish than Dave is on this 45year-old audience. Uh 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 say the technical design and build of it, but you’re imbuing a business process and a set of flows and decisions that you need a user to make. the just these 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. Uh that has very little to do with with technology selection. So we can empower these folks with with platforms like to build largecale systems, enterprise systems that are purpose-built for that 45year-old
[00:52:00] insurance underwriter or or financial product person. And this has never before been possible. >> Yeah. Yeah. I’ve been thinking a lot about this and you know Nasim Talb 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 damn about the context about when these are implemented and if you think about the long tale of these implementations to solve problems. If you actually give a damn 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 sweep 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
[00:53:00] communicate and show that you give a damn. So that your advice I to that you know 40 45 50 year old uh 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 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 hightouch consumer aspect 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 yes >> of this industry. >> Yeah we’re just at the beginning of this
[00:54:00] game. >> Well Peter that video was Amjad Msad. Uh do you want to tell the story about how easy it is to build software from you know maybe >> so you know I was flying from Santa Monica to up to San Francisco to Stanford. Uh Dave was already there and we were interviewing and Sem was there too. We’re interviewing Amjad about uh about Replet and you know I had downloaded Replet but I had never really used it and so like damn if I’m not going to give it a try. So I I you know I have Starlink on my my my SR22 Turbo my airplane. So I’m flying uh the airplane on autopilot. I’ve got the sterling antenna in the front and I plug into Replet 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 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,
[00:55:00] right? Uh, Replet’s amazing. There are other platforms, lovable and and others, it’s critical for you to just try, just try and play. And, you know, bring a curiosity mindset, your playful mindset, and if you know what you want to exist, uh, the AI systems will help you get that into existence. And it’s only going to get easier. It’s it’s only like your domain knowledge will be extremely important and the product creation you know use blitzy it’ll be easy easy. >> So before I drop before I move past uh the conversation about uh replet and vibe coding uh Brian you’re taking this level of coding to a brand new level. Uh how do you apply this to industries to entrepreneurs? What are your thoughts? >> There’s two classes of software right? There’s this uh disposable widget based software that Peter you built with Starlink on your plane, right? And this is uh the idea of getting this concept into a prototype and then there’s true enterprise scale software. I’m going to
[00:56:01] have thousands or hundreds of thousands of users. I’m going to have concurrency. I’m going to have good caching, right? Uh 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 uh 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 mid man level managers and companies or is this got to be a top down uh for people who want to use Blitzy to you know sort of improve their their product and capabilities? Yeah, anyone that leads a large engineering team comes and works with us. So, lots of times CTO’s and CIOS will 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 Blitzy in and
[00:57:01] be the first to do it. And we love those folks, too. >> Got it. Got it. Great. Here’s our our next one comes from uh Andy Jasse, CEO of Amazon. He’s like, “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. Um, 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, uh, this is cenamed J-Hawk, expected to launch in late 2026 or 20 early 27. Uh, and today, uh, the company plans to pilot 100,000 units by Q2, uh, for its workforce of 390,000 drivers. So, uh, Iman, I think you said
[00:58:00] 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 in like 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. >> Mhm. >> I love it when Ahmad says it’s kind of obvious just like when Alex answers those like humanity’s last exam questions like oh it’s four of course. >> Uh well you know you know competition is
[00:59:01] great. uh you know we’ve seen there are a number of companies creating glasses XR and others but it’s really to productize these and make them so cheap and so consumer friendly uh that they become you know I still remember the first time I saw someone walking down the street uh with an earpiece talking to their talking to themselves and I 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 a uh equivalent of what is now an AirPod. Um, 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 I think in the beginning it you will not be comfortable, but then it’ll just be assumed. You’re always being recorded. The idea that privacy exists uh is going to be a long lost concept. I I don’t know if you guys disagree with >> I think it’s interesting. No, no, no. It’s definitely uh Yeah. It’s a long
[01:00:01] conversation, but it’s what’s really interesting to me is that the of the Mag Seven today, you have three secondhand CEOs, Andy Jasse being one of them. Now, now Amazon is the best managed company, I believe, in the history of the world. And we teach all of our executives and our our teams the OP1 planning process that Jeff Bezos and Andy Jasse invented. Incredible company. But you’ve got three legacy CEOs, Andy Jasse, uh so you got Apple, Microsoft, and and Amazon. And then the other four are are founder le CEOs. >> Well, no, I mean you’ve got Sati, you’ve got um the CEO of Alphabet, right? >> Oh, Sundar Pachara. Yeah. So, you got four four Okay, so four second hands and three founder CEOs. You’re right. You’re absolutely right. >> Yeah. >> Uh 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, founderled founder-ledd companies are able to make
[01:01:00] much more dramatic right-hand turns and say to the shareholders, listen, I’ve made money for you before. Just believe me, uh, this is what I’m doing. Like it or not. Um, you know, Elon does that every single day. We’re seeing, uh, we’re seeing Meta do that. Uh, and anyway, all right, on to our next subject. Albania appoints the world’s first AIMade minister. So uh 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. Uh Immad, you know, you and I have talked about this a lot. Uh both of us are part of the uh in fact in Dave is you as well. Uh part of what’s going on in Riad and Saudi at FI. 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
[01:02:00] won’t do a better job than the existing ministers. I mean like this is kind of the bar and 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 cuz 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 can of worms. >> Yeah. So the the real question of course is if you’ve if you’ve programmed or you’ve stood up an AI minister uh what data have you provided to it him or her and uh is there bias in that data does the person who controls uh 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
[01:03:02] impartiality of these ministers like it or not we are humans >> I spent my early childhood in Iran on and uh and Brian spent a fair amount of time overseas too. Uh and you know the the global standard is corruption. Uh you know areas that are not corrupt are extremely rare on a global scale. Albania being one of the worst or among the worst. And this is just going to be nothing but good. Even 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 gamecher. So sorry Brian that you were going to say >> similar like the the hurdle rate for success is so incredibly low. So I think the AI could be right 80% of the time and uh it would be better than the than the current status quo and it would sort of be randomly uh messing up as opposed to sort of purposely driving uh uh money to to to a family member. And so it’s it’s only going to get better. So I think this is probably a great thing for
[01:04:00] Albania. >> Yeah. All right. Our next segment in our WTF episode today is energy, robots, and transport. Uh, here we go. Listen up to our US Secretary of Energy. I don’t agree with what he has to say, but let’s hear it. >> So, Elon Musk has it completely wrong. >> He He has a wildly exaggerated view of where solar and batteries will go. Um, and I’d if we could make a bet 50 years out, I’ll 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. Uh so today in the United States there’s 18 gawatts of solar capacity installed in the first half of 2025. Uh solar accounts for 50% of new electricity generating capacity uh in the first half of 25 and 69% in the first quarter of 2025. Solar made up 10.2% 2% of the total US installed utility scale generated capacity in 24
[01:05:00] surpassing nuclear and hydro power. It’s now the fourth largest electricity source after natural gas, coal and wind. Gentlemen, I I’ll mention one other thing. Uh uh NRL, which is the National Renewable Energy Laboratory, which is under the Department of Energy, uh projects solar could power 40% or more of US electricity demands by 2035. So I think uh 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 than Elon and when he’s built that Tesla, right? And so solar is inter intermittent source. And so you’d store it over time and there’d be some depreciation on on that storage, but that’s essentially a a solved or nearly solved problem. And so yeah, Chris is I don’t want to make any uh solar is a big deal. um storing solar is getting easier and easier and the DOE is is absolutely correct on this. >> You know the other thing I would write about solar then go ahead right about
[01:06:01] solar there’s no way the US can keep up with China. >> Yeah, >> solar is basically the US’s best shot at keeping up with China. >> The hard mod is our solar supply chain is completely tied to China. So it’s it’s not about does solar work or is storage going to get better and better. It’s getting better every single year and and driving that. uh can we have a USdriven solar supply chain where we’re not relying on an outsourced partner for what’s going to be one of the most important ways for us to to capture energy? >> I I think that’s a great point. >> Exactly. >> What you know, we do need to realize the world is about to change on the back of ASI, right? Uh we’re going to have better manufacturing processes. We’re going to have new materials. We’re going to have all kinds of of capabilities that did not exist uh you know uh today but will exist in three or four years. Can we scale it quickly enough? We’ll see. But you know, China’s run circles around us. I mean the the numbers are are pretty staggering. China leads with 880 gawatts of solar capacity in 2024
[01:07:02] growing at 45.6% annually. That’s insane. the US uh is at 177 gigawatts growing at 27%. So they’re basically lapping us constantly. >> Yeah. >> No, you’re 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, 500 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 you what happens every time with you know the 80% of the world’s cars were made in Detroit. 80%
[01:08:03] 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 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 US back into Europe at low prices >> with a large tariff. >> It’s just a fundamentally broken machine in the US that’s with well tariffs are part of that. >> Well, who pays the tariffs, right? It’s 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. >> Huge lead there. This is a big focus area for David Seagull, you know, the two sigma founders. So, if we want to pod with him, he’d love to riff on this topic, but he has some ideas on how to
[01:09:00] fundamentally fix them. >> Yeah. >> So, we reported last pod about uh about Brett Atcock’s uh you know, figure raising a billion dollars at a $39 billion valuation. I mistakenly said it was a $93 billion valuation. Sorry to triple your valuation there, Brett. Uh but it was 1 billion. >> He’s out of water. >> Just give it a few weeks. Exactly. Uh it’s 1 billion uh on top at uh at a $39 billion valuation. Pretty amazing. And and Brett is an incredible entrepreneur um you know who uh was in the EV tall uh uh with Archer Aviation before and has brought his engineering expertise uh to the table. They’ve also announced a strategic partnership with Brookfield uh and Brookfield is giving them access to 100,000 homes, 500 million square ft of offices and logistics space. So there is a concept right now and we learned about this when we were visiting uh burnt at
[01:10:00] 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 the what what Burnt was saying uh if you remember Dave was if you’re in the factory uh 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 uh in the office like a like a toddler crawling around and getting you data all the time. >> Thoughts? >> Yeah, it’s totally right. I I I don’t believe that you need that to get to AGI. I heard Burnt say it. Um, 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 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.
[01:11:02] >> Yeah. And it’s these models are inferring physics based on video data. And so it’s incredibly hard when you’re faced with the real world. And so when Brent shifted off of his OpenAI partnership, you know, 18 months ago, uh he made this very very assessment which is we have to build our own foundation models that are focused on our own data from real world simulation because you know inferring physics is 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 no we need robots too. So, uh, OpenAI was in the robot space back in 2021, but they basically paused all of that, uh, to focus on on chat GPT. Um, and today they have listed a number of postings for jobs on teleoperations, simulation, mechanical engineering. So, if you’re listening to this pod and you want to build robots, go check out OpenAI’s open roles. Uh and and of course this is a multi-t trillion dollar marketplace. Um here’s the
[01:12:02] 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. Uh but you know, when I’m looking at the numbers, you know, Venode Kosla was on stage last year at the Abundance Summit. Uh, and then we had Brett. And you know, the the low end of this is a billion robots by 2040. The high end, and Elon makes a convincing argument, and 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 lowballing these numbers. Anyway, >> I’ll tell you one thing when you when you read the way they analyze this, they use the old business school kind of, you know, just projective forward garbage without any >> concept of either self-improvement for software or self-manufacturing for robotics. >> Yeah. >> But that feedback loop dominates the math in the real world and that’s why they’re way way off
[01:13:01] >> in their projections. >> For sure. >> It’s the classic like Uber’s market size being the same as taxis. Like it’s it’s 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 PhD 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 everyday twice a day. There you have it. That’s my secret. You go to oneskin.co and write peter at checkout for a discount on the same product I use. Okay, now back to the episode. All right. Uh I want to jump into the economy and Immod love having you here on this and uh excited when you announce
[01:14:00] your economic treatise. I’m I’m still predicting a Nobel Prize for you buddy. Uh that’s my goal. Nothing less Nobel Prize in economics and then we’ll do a Nobel Prize in something else for you as well. So uh here’s the slide. It says AI is not a bubble. Uh Dave, do you want to you want to lead this description here? It’s not a bubble. Look at that. 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 bubble market crashing also did. Oh, yeah. That Yeah, not the tulip bulbs back in 17. All right. So, uh 16, whatever. Uh yeah. Uh no, the you look I was on the board of Micro Strategy. 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, look at the red line on the right. >> So, just to describe it for for our
[01:15:01] listeners, this is a graphic of of Cisco showing its stock price going from uh 100 bucks up to around 700 bucks. But at the same time, it stock price is peaking, its uh 12-month forward earnings per share is pretty flat. So that’s by definition a bubble. It’s a hype bubble. Uh on the other side of this of this image, we see Nvidia. And what we see is that the price of Nvidia is going up and it’s going up lock step with the 12 month forward earnings per share. It’s generating real revenue, real profits. So 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 disconnected 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 hundred billion dollars of
[01:16:01] Nvidia money going into OpenAI that feels like back in the com bubble, we had this roundtpping of revenue, but it never created economic value. Every single GPU that OpenAI uses will be booked out. >> Mhm. >> 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 a bubble. >> Yeah. When your mom when your mom starts talking about, should I invest in this in this company? That’s crazy. >> Well, just some some numbers, >> you know, just because it was a part of
[01:17:00] part of our lives or part of my life. Uh, 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 valuation. Laughable. Um, 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 a hundred employees. How can it be worth a billion dollars? That’s nuts. So then after that they got super acquisitive uh 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 911 happened >> and the market imploded. So it went down 95%. And then you know pretty quickly after 911 recovered again and settled around asset value so around $50 billion. Okay. So then you know not much happened after that eventually got acquired whatever gone. Um so Jensen now is on top of the world he’s investing hundred billion
[01:18:00] dollars into open AI uh buying everything which diversifies that value you know $4.5 trillion valuation. So you know not only are the revenues and the earnings very real at Nvidia but they’re also diversifying and aggregating power uh and and equity stakes at an incredible clip. So, you know, and take a take with it is priced 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. >> There’s one way you can tell a bubble, and that’s when people come up with brand new statistics like Yahoo is valued per eyeball. So, if Nvidia is a retro transistor, then we know there’s an issue. >> That’s Brian. I I think people miss the latency between the capex involved in creating the internet and the value that came out of the internet. Right? The.com bubble like by any means if you dollar cost averaged in the year 2000 uh even the height of the bubble and then waited
[01:19:00] 10 years you had fantastic outcomes right but the latency between >> capex right now and earnings is almost immediate right because uh they’re able to translate that all of the advertising engines are able to translate it almost immediately into additional earnings. This is just a a timing and the timing for AI uh basically payback is is immediate. >> By the way, >> I I want to I want to double down on what Brian just said because I 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. >> Yeah. >> Right in the bottom of that. Yeah. Amazon. >> Yeah. >> Yeah. To 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
[01:20:01] go to dmandis.comwtf. 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. Uh, Eman 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 got 30 seconds, so there you go. >> All right. But I I I love having brilliant people around us that we can have these conversations with. >> I I put in a good 20 hours. Yeah. >> All right. I I want to have a conversation about this. Maybe a little bit of a debate here. So, uh Eric Juan, the CEO of Zoom, uh said, “We’re heading towards a 3-day work week that will come on the heels of AI.” Uh let me give you a few other quotes here. So, Bill Gates, uh his quote is a reduced work week to two to three days will happen within a
[01:21:00] decade. Uh Jensen has said a 4-day uh work week may become the standard. Jamie Diamond from JP Morgan has said future generations may work 3.5 days weekly. I like the.5. You know, didn’t want to say three. Don’t want to say four. 3.5. Uh thoughts on this? I mean, you know, Dave, you and I are talking about 997. I don’t know about you, but I am working. Actually, I get up about 5:00 a.m. So, I’m more like 6:00 a.m. to 8:00 p.m. Yeah. seven days a week. Um, it’s exciting. I don’t want to let a day go. It’s like there’s this is fun. Three day work week. >> I Yeah, I 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 just keeping up with everything going on consumes a full week work week and and then you have to produce on top of that. So, I’m seeing a lot of divergence here. You got all these people that I know around here that are working 996 997 just crazy. And then we’re predicting that workloads
[01:22:01] will go down for everybody outside the building apparently. But it’s not clear to me how that works. Like if 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 what does that achieve? So I don’t know you guys. Yeah, >> if if a human is providing like economic value that’s driving up the value of the company uh and it has some relation to the amount of input that they put in, they’re probably going to work as much as the the company will force it to work, right? Like 5 days, six days, seven days because they’re ultimately competing with some other firm, right? 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 you’re competing against other folks that aren’t going to make similar decisions. >> Iman, what’s your thought? They’re all going to get government jobs. That’s the way it is. >> I mean, so seriously, like again, humans will have negative value in cognitive labor in a few years.
[01:23:00] >> So, you’ve said that. I want you to double down on that conversation. It’s a really important uh 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 AIS 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 3 4 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
[01:24:02] role is to beat other people, as in private sector competitive jobs, particularly in knowledge work, you’re not going to beat an AI. >> Yeah. And then in a few years, your muscles aren’t going to out compete or your skill at plumbing isn’t going to out compete a robot. >> So just to just to give two examples uh on this idea that humans drag down drag down the uh the average and have a negative impact on value. Uh this is where for example if you have self-driving fleets and a human enters that uh and drives that human is likely to have more accidents in the self-driving fleets. a stat from about 6 months ago. There was a study done at uh 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 uh diagnosed uh 74% of the time successfully on their own. In this
[01:25:00] 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 uh damage. We’re biased where we’re we’re not able to have pure thought and uh and decision-m there. >> Actually, I think I’m going to start here. If all cars were driven at Whimo level, >> yes, >> we’d save 40,000 lives a year and a trillion dollars in societal costs. >> Amazing. >> Yeah. >> Amazing. >> This this sort of this this stat from Eric misses the organizational point about just having fewer people. So I think we’re gonna see there’s this number called the Dunar number which is like 150 people is sort of the max amount that you can have in a network in your head without having uh 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 the cost of
[01:26:01] communication no matter what. So you max that out use all the AI you can sort of get the jobs to be done thrown into the economy through your organization. >> Yeah. >> So curious about this one. Uh we talked about Dolingo uh a few pods ago especially because of the breakthroughs coming out of both open AAI and Google. So Dolingo CEO uh says AI made employees four to five times more productive no layoffs reported no full-time layoffs since the company went AI first and AI has sped up lesson creation in languages math and music and Dualingo raised revenue forecast to 1.02 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 if you look at podcast 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
[01:27:01] great. There’ll be a three-day work week. You’ll be, you know, it’ll be fine. and you know here, hey, we we 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 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. >> Yeah. it it’s going to land in like five or 10 or 20 hands or you know maybe a few more than that but a very concentrated subset uh if things just evolve with no change and that’s just the reality of how things are evolving and 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 I aied it so you know I’m just seeing a lot less honesty in these uh interesting these interviews isolingo is growing 30 40% a year. It
[01:28:01] should be growing its employee base 30 40% a year. >> Yeah. Ah interesting point. >> Yeah. So it’s standing it’s standing still. It’s well this is what Mark Beni off talked about as well. You know we’re we’re growing but we’re not growing the number of engineers >> um and with agent agent force there. Um I thought this was important for us to talk about. NASDAQ pushes to launch trading of tokenized securities. Um and so the US to become the first exchange to move with this initiative and uh you know it’s not enough for us to trade 5 days a week, you know, 8 hours a day. We want to go to 24 hours a day, 5 days a week and then it’ll be 24/7. Uh so if approved, we’ll see the first tokenized trades roll out by late 2026. As a reminder, Robin Hood, at least their EU version in June and July, started launched with tokenized uh stock tokens uh for 200 US stocks. Uh they’ve been
[01:29:01] trading 245 and uh 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 US yet, but uh it both most likely will. uh thoughts about this, Dave? You just been trading successfully on the uh >> actually there’s another one this week. Better mortgage out of nowhere. Uh you guys can look it up. BETR. You can check it out. >> What is what is better mortgage? Well, so Better Mortgage is one of many companies including uh Go Health and one I’m involved with as chairman that uh if they implement AI correctly in 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 micro caps. So they’re they
[01:30:00] trade very cheaply with virtually no liquidity. No mutual fund can touch them because there isn’t enough float. >> Anyway, it’s uh it’s AI itself. Somebody noticed >> better. >> Just make the trade live, Peter. Get on with it. >> Yeah. >> One second. I’ll be right there. >> Uh okay. >> There’s a whole theme there, though. You can 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 have lots of >> concern, this is not investment advice. I’m supposed to say that every time we mention that wasn’t investment advice. It’s just a thought. >> But but I’m c I’m curious about this idea of 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. Um,
[01:31:00] but >> we desperately need this, too, because uh, you know, going public is very, very ownorous and getting more ownorous 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. uh it would solve a lot of the problems we talked about earlier in the podcast actually. 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 >> I mean US monetary velocity is not really recovered since co it’s still below the decade below co >> crypto is legal in the US apparently GDP is going on the blockchain the treasury like we just said whatever that means like if you want to see what a bubble looks like just look for the next few years in digital assets that will show you completely what a bubble looks like you know like generative AI is the
[01:32:01] 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 and not to get too technical we can cut it out of the podcast if it gets too too technical but 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 prevent every quarter widows and orphans from losing money in uh in deals. >> Yeah. Yeah. And so now all of that all and you want to employ enough lawyers >> and you want to employ enough lawyers and Yeah. and accountants. Yeah. It’s the biggest accounting lobby thing in the world. >> But the AI can do all of that now. So you could you could 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
[01:33:00] fact, your 10 Q’s 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. >> Uh so there there very much is a solution in there. It’s really a good idea. >> All right, let’s move. Oh, go ahead, Brian. Yeah. >> The top desk private companies are larger than a huge portion of the public markets. And so the IPO market has gotten sort of so ownorous right now that private investors get access to all of the best deals in perpetuity. U companies like Stripe and 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 our final segment here on health. And uh here’s a a piece. Apple Watch Hypertension Alert receives FDA clearance. So listen, hypertension is a silent killer. 1.5 billion adults, 30 to 45% of the population, 60% if you’re over 60, is affected by hypertension. Uh it’s a systolic of 130 or greater and a
[01:34:01] diastolic of great of greater than 80. Uh and the challenge is that 46% of uh of people with hypertension goes undiagnosed. Uh and only 21% is controlled. So if you can in fact get it, you know, handled by your Apple Watch, give you a heads up. But this is the beginning of basically wearables and citables becoming part of our daily life. So you know, I’m wearing a uh 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 in Fountain. 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 uh powerful. But what I really find exciting uh in this space is this
[01:35:00] announcement uh from Demis. Uh DeepMind CEO says AI could shorten drug discovery to months. So, Immad, you’ve been thinking about this a lot, the impact of AI on on drug discovery and on health. Uh, what are your thoughts here? >> Yeah, I mean, healthcare had to assume this erodicity thing like we’re all the same. We’re all statistics. Everyone gets 500 milligrams of paracetamol, for example, you know, the whole ASD thing. Actually, paracetamol can impact you a bit more if you have a cytochrome 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 to this. One is the ability to take all that data and think about everything from 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
[01:36:01] 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 from isomeorphic in 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 anecdot >> here’s some of the numbers uh so the first AI design drug comes from a friend uh Alex Zankov my bold venture capital fund is is a investor in uh in uh in silicone medicine just for full
[01:37:00] disclosure but they’ve designed a drug for idiopathic pulmonary fibrosis uh that’s in human trials right now and then there’s a drug called DSP1181 I love the names of these drugs um and it’s for obsessivecompulsive disease uh and in particular it went from design to human trials in 12 months normally takes four to five years uh 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 uh successfully with uh a success rate of 80 to 90% uh which is which is stunning. Um, you know, you know, we’ve talked about this, IOD, that uh health and education are going to be two of the biggest areas fundamentally disrupted by by AI and it’s uh it really uplifts humanity. Yeah, I think it’s just super exciting and I think what’ll be really
[01:38:00] interesting is I reckon in the next five years you might actually have part of the FDA process what is the insilico 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 we were just riffing what for an hour, hour and a half, I don’t know, whatever it was. >> Yeah. >> But we had a whole another 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. The uh or at least for the next five years. The the pace of acceleration is just crazy. And gota you got to be in a full sprint mode, you know, at least for this time period. I think Brian, it was great that you could join us today because uh your insight on now is the best time. There will never be a better time. There never has been a better time >> and I love the fact that we pulled you know the
[01:39:02] >> well the wind the windows come and the windows go. So it’s great to have your insights today. >> Yeah. >> Yeah. Good to be here >> and and Brian uh just thank you for the support you’re giving this pod. Uh pleasure to have you and excited uh for those of our of our listeners, subscribers who have reached out to Blitzy. Super cool. Um uh yeah, and Immod excited. We’re going to have you back on the pod uh in about a month uh when you come out to X-Prise Visionering. We’re going to do a live WTF episode at X-Prise Visionering, which will be a lot of fun. Uh and you and I will be talking a lot uh before we get to Saudi Arabia uh right after visionering. Um anything you want to tell us about intelligent internet right now? >> Yeah. No. Um released 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 move forward when humans aren’t the marginal innovator. It’s a crazy time
[01:40:02] and we all got to think about this really carefully. It really is rewriting fundamental economic theory, period. Yeah. Uh Brian, uh we stole you away from some meetings. Uh 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. So, I like to hang out with the West Coast clients between 6 p.m. and 9:00 p.m. Uh because it’s still work time there, Tom. >> Amazing. All right, everybody. Thank you for another great episode of WTF. Please check out the slides at dmandis.com/wtf. Join us as a subscriber. Uh, you know, tell your friends about what we do. Our mission is to share sort of this extraordinary uh acceleration that we’re feeling uh with you, educate you along the way, have fun, but get you ready for the new economy that I is writing about, get you ready for the extraordinary future coming our way. Uh, hope you’ll trade an hour on the Crisis News Network for an hour with us instead. Everybody,
[01:41:01] have an amazing day uh and night and week. See you soon. Every week, my team and I study the top 10 technology metat trends that will transform industries over the decade ahead. I cover trends ranging from humanoid robotics, AGI, and quantum computing to transport, energy, longevity, and more. There’s no fluff, only the most important stuff that matters that impacts our lives, our companies, and our careers. If you want me to share these meta trends with you, I write a newsletter twice a week, sending it out as a short two-minute read via email. And if you want to discover the most important metat trends 10 years before anyone else, this report’s for you. Readers include founders and CEOs from the world’s most disruptive companies and entrepreneurs building the world’s most disruptive tech. It’s not for you. If you don’t want to be informed about what’s coming, why it matters, and how you can benefit from it. To subscribe for free, go to dmmandis.com/metatrends to gain access to the trends 10 years before anyone else. All right, now back to this episode.
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