XAI launches Rock Code Fast 1. I had to double check the numbers on this cuz they were pretty epic. It’s insane. Elon went from zero to building Colossus 1 in 122 days. Everyone said it couldn’t be done. This guy will not slow down. He wants to be number one. And we’re seeing these data centers leaprogging each other. >> Elon, you know, the entrepreneur of all entrepreneurs, knows that it’s it’s all or nothing. You don’t build the second biggest data center. You either win the race or you don’t win the race. >> This is the bitter lesson as applied to hardware scaling. It’s sort of a case study in in brute force hardware scaling where we’re seeing the power, the chips, the data centers all being brute force scaled. These incredible tools are demonetizing and democratizing an extraordinary rate. All the students struggling with their largely irrelevant curriculum. This is what you should be doing. >> Now that’s a moonshot, ladies and gentlemen.
[00:01:00] Welcome everybody to Moonshots and our weekly episode of WTF just happened in Tech. I’m here with my Moonshot mates Alex Weezner Gross, Dave Blondon. Sel is in India right now. We’ll talk about that in a minute, but uh this is the news we hope that you watch that makes you optimistic about the future that raises your IQ points 20 and gives you a chance to see the future. So Dave and Alex, good morning guys. Good morning. >> So, how was Labor Day for you? >> Uh, I got a lot of grief actually for being uh >> distracted and antisocial. >> I was talking to to my AI agents. They were pestering me with progress all week. They have an IQ of 148 now. So, it’s pretty hard to deny them. They’re uh they’re getting needy for the first time. You know, I’ve been waiting for this moment since I was 14 years old. So, it’s pretty hard for me to to tune it out. >> I missed you. But they are getting needy. Alex, did you labor over Labor Day? >> Absolutely. Never a dull moment. >> Yeah. Yeah. Me, too. I’m in Port Towns
[00:02:01] in Washington near the San Juans. I have been here for a week with the family, which means I’m getting up super early, like at 5:00 a.m. just to actually get my email done and work and do my writing and then spend time with my 14-year-olds on the beach in the woods fishing. went fishing and I caught like a massive fish which was about six inches high compared to Alaska. Uh anyway, >> did you did you eat it? Just just eat it raw. Right out of >> catch and release. Catch and release. >> Okay. >> Well, so listen, I just want to take a second and just appreciate the fans that we’ve had on this podcast. Um it’s been pretty amazing to get the feedback and you should all know we love doing this. We spend a lot of time working on this really to deliver the news that we think is the the news worth learning about that gives you a positive view of the future. I want to take a second to read you guys uh some of the comments and just say thank you for the awesome
[00:03:01] comments to everybody. So why not? Jack says moonshots is the best thing I’ve ever found. High praise. Uh the crypto canvas says best podcast in technology right now. Thank you guys for doing this consistently. And we do love doing it consistently. Uh Steve Darus1234 says, “An exciting future. Thank you for providing an optimistic long view amidst the constant doom and gloom of the news cycle.” And you know, I think that’s one of the principles here is if you are constantly watching all the negative news, it’s going to shape your mindset in a really dystopian fashion. Uh Carl Rankin 5385 says, “Quite simply, the very best and most relevant AI and digital technology podcast available today. Thank you, Peter, for allowing us to hear Salem, Dave, and Alex and their collective brilliance. You’re welcome, Carl. Um, Renise IB6532. I absolutely love this podcast. You guys are doing a great job keeping up with everything. And yes, Alex is brilliant.
[00:04:00] Okay, let’s follow up on that note. From Poly M uh Mupil, who says >> Polymerper, thank you. I was a little iffy on Alex at first. Then I realized I was just jealous of his intelligence. Now he’s my favorite to see in the world. >> That is exactly my experience with Alex when I first met him years ago. >> Oh, it’s great. A sweetheart of a guy. And we’ll wrap it up with Bill Jacobs 30 386 who says the Fab Four are back. >> Fab three. >> Well, today it’s the Fab 3. Yeah. Uh uh before we jump on to where where uh Salem is, I just want to say thank you to our production team who’ve been amazing. Uh Nix, Danacon, and uh Jin Luca Manion. Thank you guys for all the hard work you do making this easy and fun. And we do have fun, >> right? I mean, it’s pretty pretty amazing. So uh Salem right now is in India about to get on stage uh with his
[00:05:03] uh singularity mates at a SU summit there. And before we hung up with him a few minutes ago uh our edict to him was bring back a box of iPhone 17s and please fix the US Indian trade issues. So he’s taking that on. We’ll see how he reports out. >> And this is uh Peter this is back to school week. I don’t know if you’re in phase, but everyone is back on campuses now, grinding away on these soon to be irrelevant curriculums that are that are falling by the wayside. Uh, I got lots of questions from my kids, nieces, and nephews over the weekend about what they should be doing, what they should be studying. How do you and and it’s so great that we have Alex here to help add to that guidance because it’s changing so quickly, you know, very, very hard to keep up. I know that what they’re learning is irrelevant and and becoming more relevant by the minute. So we we’ve got that much figured out but then what is relevant and how are we going to keep up with it? So uh class starts on Thursday morning. >> Well MIT foundations of AI ventures >> my boys as well but not quite not quite
[00:06:02] MIT curriculum. They’re eighth grade but hey that’s good. >> Well I don’t know if you know but MIT added uh a new thing this semester 6E. Remember how you know course six which is computer science and double E >> had always had 6A where you you go to companies for a semester or two and learn how the real world works. >> They added 6E now which is incredible. E is for entrepreneurship. >> So you basically take a couple semesters and go either work at a startup or a venture fund >> and see how the startup world works. And it’s incredibly popular. So uh this semester I’ll be teaching advanced algorithms in that uh curriculum uh a couple times this semester and then full-time the following semester. >> Yeah, I do believe I do believe the you know the career of the future is entrepreneurship period and we should have that that conversation and we should talk about education on the next pod we do go a little bit deep on there some news developing there. >> Um Alex, uh I want to just not miss this
[00:07:00] point. Uh right now, if you’re an incoming freshman to college, what’s your recommendation? Skip it, skip college, or what do you do? >> It it’s a tricky time. Uh I I think it depends entirely on the the freshman’s goals. If if your goal is to build a startup, I I think there’s a strong macroeconomic incentive to just do it now. Consider dropping out, moving to Silicon Valley, or doing it in Boston or elsewhere. But I I I think timelines AI, AGI, ASI timelines are so short that almost any conventional career plan if if we had had this conversation 20, 30 years ago, I I think it would have been far easier to project out a sort of a conventional life plan or career plan. I think now the the singular bit of advice, no pun intended, I’d have for any college freshman is assume that AI timelines are incredibly short. assume that we’re going to have super intelligence to the extent it doesn’t exist somewhere already and just isn’t
[00:08:02] evenly distributed. Assume that we’re going to have super intelligence in the next 2 to 3 years and guide your career plans accordingly. >> Yeah, I’ll add my opinion there, which is, as I’ve said over and over again, find a problem you’re passionate about, right? The technology is going to constantly change, but the problems are going to be fundamental for some time and then apply intelligence to that problem. uh you know apply AI to problems that you care deeply about. So you know if you don’t know your massive transformative purpose wherever you are if you’re in high school if you’re in college if you’re in graduate school you know pause what you’re doing and really focus on what’s your driver you know Mark Twain’s f my favorite quote of Mark Twain two important days in your life the day you were born and the day you found out why. So why are you here and then apply AI and digital super intelligence to that why. All right. Should we >> The other Peter, of course, the other Mark Twain quote that’s apppropo to the the college experiences, the classics
[00:09:01] are books that everyone wants read but no one wants to read. >> So maybe those two end up colliding. In this case, >> we we have we have uh Google Ellen uh you know summaries now for us to be able to listen to those books in brief in a podcast. Every week, my team and I study the top 10 technology meta 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 meta 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
[00:10:01] from it. To subscribe for free, go to dmandis.com/metats to gain access to the trends 10 years before anyone else. All right, now back to this episode. All right. Should we dive into the AI wars? >> Let’s do it. Ready? All right. Absolutely. >> Let’s see where we’re first. >> All right. First up is our friend Elon and uh his roll out of Colossal 2 coming online in a couple Colossus 2 and coming online in a couple of weeks. One gigawatt data center in Memphis. And I love the fact that we’re beginning to talk about these as as energy, not number of GPUs. uh again and this is the mythical 1 gawatt center is finally coming online fitted for 500,000 Nvidia uh blackwell GPUs and then doubling it again next year in 2026 and this is where Gro 5 will be born. Uh let’s talk about it. I mean this guy will not slow down. He wants to be number one and
[00:11:01] we’re seeing these data centers leaprogging each other. Uh Alex, what are your thoughts here? This is the bitter lesson as applied to hardware scaling. It’s brute force. It’s sort of a case study in in brute force hardware scaling where we’re seeing the power as as you mentioned the the chips, the data centers all being in in the style of of the bitter lesson brute force scaled. What we haven’t seen yet and will I think be very interesting to see is that the same level of uh brute force efforts being applied to the software side of the stack. And I wouldn’t be surprised to to see that kick in as well. But for now, in the style of of the bitter lesson, it it’s just absolutely incredible to to watch with with such vigor uh and such brute force the hardware scaling side of the equation taking place. So the bitter lesson is from a guy named Richard Sudden who made this I think incredibly important observation that has permeated now the AI community. Alex, it’ be great if you
[00:12:00] give us a quick summary of it. Yeah, the the the core I’ll caricature it, but the the the core thesis uh behind Sutton’s bitter lesson is that all of these decades by AI researchers spent developing artisal solutions to problems to to speech recognition to language understanding to computer vision were all basically wasted. uh and that in in the end all that really mattered was taking large data sets and lots of compute and off-the-shelf algorithms and just scaling them up to very large sizes. So this is the bitter lesson. This is why it’s bitter that all of this effort by humans by human researchers getting their PhDs over the decades coming up with artisal new algorithms that they could publish it to to identify. You remember like several years ago even it was it was breaking news when uh when researchers were able to build a cat detector. Like that was news. Now >> that was just 5 years ago, right? Not
[00:13:01] not even a long time ago. >> And that’s just been steamrolled by completely general algorithms with very little human injected prior knowledge combined with huge amounts of data, huge amounts of compute. So the bitter lesson has been I I think one of the core themes of the AI revolution we’ve seen over the past few years and going back to Colossus 2 the bitter lesson applies not just at the software layer but also at the hardware layer. So some reads brute force. >> Yes. >> Yeah. Um you know and what I want to talk about here is again just this leaprogging of on data centers and on the hyperscalers. uh you know Elon went from zero to building Colossus one in 122 days. Everyone said it couldn’t be done. Right now he is up against others and he’s built the largest data center and is going to maintain that lead. Uh we’re going to see you know we’re going to see Open AI coming out with uh uh
[00:14:01] with the Stargate centers. So how will Stargate compare to uh to Colossus? >> Toe toe actually. Isn’t it right? They’re exactly right in line. This is a, you know, this foot race is very, very much winner take all. I know we had that debate last time we podcasted. You know, it looks like there’ll be five, seven big AI labs, but I think Elon, you know, the entrepreneur of all entrepreneurs knows that it’s it’s all or nothing. You don’t build the second biggest data center. You either win the race or you don’t win the race. And uh, you know, because these things once they’re trained, they compile down to something crazy fast and very easy to tailor into specific use cases. But nobody wants to start with the number two model or the number three model. And so you either win the race or you don’t. And so Elon’s all in, Stargate is all in, you know, Sam Alman’s all in. But uh yeah, Alex, do you know the exact numbers? I think they’re pretty much right in a line. >> Yeah. Also, that the numbers are a little bit tricky because I would distinguish between data centers for training new models and data centers that are going to be used primarily for inference. So the the world it would
[00:15:00] appear that we’re moving toward is we’re just tiling the Earth’s surface with inference time compute models that are It’s important just for a second for uh for our viewers and and listeners, Alex, talk about what’s the difference between training and inference. If you haven’t heard the terminology before, it’s fundamental. >> Sure. So, uh conventionally the way one would think about this is uh an AI model like Chad GPT is trained. it’s created basically from large data sets uh at one time sort of a fixed cost upfront and then later on there’s so-called inference time when the model is actually used. If if if we were to sort of analogize this to software engineering there’s sort of compile time uh or development time when a computer program is created and then execution time when a computer program is actually run. Same idea here. So inference time when uh an AI model like the GPT series for example is actually deployed and being run in practice those th those inference time use cases based on the
[00:16:02] headlines that we’re seeing those are going to be run in data centers around the world. We’re we’re and I think we’ll get to this later. We’re standing up data centers as a human civilization all around the world in the Middle East in India in Norway elsewhere. But the training time when the models are actually the the frontier models, the the strongest models that we have are being created, those appear to be more geographically localized in the US at the moment. So it it’s sort of in going back to to Dave’s question, it’s sort of it it’s a tricky distinction to distinguish between data centers that are going to be primarily in intended for training and creating new strong AI models versus data centers that will be primarily intended for running models that already exist. I think the another analogy here is if you go to school, learn a language, you’ll spend, you know, a few years learning a language, but once you’ve learned it, actually speaking it, you know, is a lot quicker. And uh obviously inference is just that having the language uploaded into your your neoortex and being able to speak
[00:17:00] it. I think one other thing worth mentioning here is Elon’s got basically access to infinite capital. Every time he goes to raise capital, his overs subscribed, right? there is a massive amount of uh family office money, sovereign wealth money that’s just prepared to fund his continued growth. Uh it’s never been that way. And I think you know what we’re going to see here is the differentiator for the United States on building these companies, building these frontier models is access to this risk capital, uh which doesn’t exist at this level anywhere else. And I think that’s pretty awesome. >> Yeah. Well, just to put some numbers on that, this is a million a million black wells. Uh they’re $30,000 each. Remember, a GB200 has two black wells on it. So, I’m pretty sure he’s talking about uh a million black wells, not a million GB200s. But Alex, you probably know the answer. But anyway, a million black wells at $30,000 each. That’s a $30 billion investment in the chips alone. Then, you know, whatever on top of that for the for the, you know, the
[00:18:01] racks and the power supply and all that. >> Yeah. Amazing. It’s it’s also probably worth just briefly mentioning that the electricity side supply of this. So uh Colossus one sort of famously is is has a self-contained electricity source. It’s it’s using natural gas cogeneration facilities on prem. It’s not my understanding is not drawing electric power materially from the the grid. It’s uh it’s generating on on site its own electric power. And one can sort of extrapolate all sorts of interesting questions that does this mean that there’s going to be sort of a pocket economy of data centers that are being forced to to colllocate with nuclear power plants with natural gas cogen simply because the rest of the grid and the the sort of the outside economy is too slow to catch up. >> Yeah, I think that’s going to be the case, right? Where do you have cheap electricity? Just move your data centers there. >> All right, let’s go on to the next one. >> Yeah, go ahead. Oh, so Danielle Russ and I took a tour of the Markley data center
[00:19:00] here. Uh it’s it’s the first quantum deploy, but um Jeff Markley, great guy who built the data center. Uh he bought all the 3 megawatt generators in the country. Like what do you mean all of them? He said, “Well, all the five megawws were already sold out and I panicked. I’m like like you know because we need to generate a gigawatt. There are only so many of these generators. So now that’s now the issue. like even if you get access to a power supply uh you need the generators to turn it into electricity and those things are are completely sold out. >> One of the things I want to talk about on the pod here is where would you make your next investments right? So we missed the Intel uh you know option call we talked about last time with uh with Leopold. I’m thinking and this is not investment advice. This is me advice that you know investing on the cutting edge of energy production. I mean just the the draw down right now uh you know as Eric Schmidt said to us Dave when we were having our podcast with him you know AI is energy limited not not chip
[00:20:02] limited not intelligence limited it’s energy limited. Well, I’ll tell you what, guys. Why don’t Why don’t we go down on some podcast, maybe next time, go down Leopold’s holdings from his 13F filing and look at everything because he didn’t just his biggest position is Intel, but there’s a whole list of things there that are all direct implications of what you just said. >> And so, let’s just analyze them one at a time. And >> you want to talk you want to turn this into a financial investment podcast. Okay. >> We could we could label it. So, if people want to skip that one, you know, they can they can. >> All right. All right. The next the next topic for discussion is X keeping on the Elon theme here. XAI launches Grock code fast one. So I had to double check the numbers on this because they were pretty epic. So this is optimized for agent coding, right? You see here on uh on this a graph of model model performance per 1 million tokens and gro code fast one. I’m not sure that rolls off the tongue as a as a name. just trounces
[00:21:00] everything. I put the numbers down at the bottom here. So, input tokens are 20 cents per million tokens. Output a buck 50 per million compared to GPT5, right? Input is one dollar and a quarter compared to 0.2 uh and claude sonnet 4 input is $3. So, we’re talking about 15 times cheaper on input tokens and we’re talking about 10 times cheaper on output tokens. Uh how do you compete against that? I mean, this is a race to the bottom. Thoughts, Dave? >> It definitely not a race to the bottom, even though it appears to be. This is a get the market share, don’t lose no matter what. People get addicted to this stuff so quickly and then they want an infinite supply of it. So, this is much more like a a crack dealer giving out the first hit for free than it is like a race to the bottom. And I think people are completely misinterpreting whether AI is a race to the bottom and also whether the chips will commoditize. Neither is going to happen because the demand is is infinite. >> Yeah. Alex, your thoughts here, buddy?
[00:22:00] >> Yeah. What what’s worth I think noting is if if you try to interact with Grop Codefast one via browser, you will not find it. And we we’ve talked on the pot in the past about the browser wars, about browsers, web browsers as distribution channels for AI. I think it’s it’s quite notable, but sort of uh under the the category of burying the lead that you can only access as a as a consumer. You can only access gro code fast one via one of several different coding environments like cursor or windsurf. So to the extent that we talk about distribution channels for super intelligence, I I think it’s actually quite notable that those coding environments are becoming almost competitors for the browser for for accessing super intelligence. >> Fascinating. Fascinating. Yeah. Entry points. >> So I’m looking at cursor right now on my screen. I don’t see it there. Is there something I need to do to get it >> with Windsurf? So, so it’s a bit of a hassle to to get to with Windsurf. You have to search specifically for Grock
[00:23:01] code fast one in order to to get it. >> It’s not even one of the recommended ones. >> No, no, no. It’s here. It’s here. Sorry. It’s It’s way down at the bottom. I don’t know why they >> Well, it’s just out. It’s just out and uh it’ll gain popularity. But I think the point here, I mean, for everybody is these incredible tools are demonetizing and democratizing at an extraordinary rate, right? And we’re going to see literally billions of coders, everybody will learn to code. The language of coding is going to be basically your mind, your your English or your Hindu or whatever it might be. >> All right. >> Before the next podcast, I’ll test it and see how it fares just on quality. Obviously on price it’s incredible but just on quality but I don’t understand how this price point is possible just just counting up the flops and working it back to the chip costs. Alex I don’t know if you have any insights on that. >> There was an article that was said that a lot of this is being basically carried by Silicon Valley investment
[00:24:00] at least. >> Yeah. But I mean you can’t you can do a little bit of that but you can’t just burn money by the billion. Um, I mean, you can for a little while, but you can’t you can’t sustainably. Do you think that’s what’s going on here, Alex? I don’t I don’t know. It >> it’s not clear. I I see different accounting schemes without having direct access to the uh the the chart of accounts for the Frontier Labs. Difficult to know whether uh inference time as we were discussing is is profitable or not. I’ve seen claims either way. But I I I do think more broadly Jevans paradox uh broadly speaking that the the cheaper given commodity goes that there’s sort of a paradoxical net increase in in demand uh resulting in potentially greater expenditures in this case. I I think we’re going to see that with code generation as well that as the the cost of intelligent code generation trends towards zero as it has been for the past few years. I I think we will see to Peter’s point, we’ll just we’re just going to see just in time code demand for everything and we’ll be a wash in
[00:25:00] new code that otherwise never would have existed. Well, one thing that came up when we were talking to Kevin Wheel two weeks ago uh at OpenAI, you the chief product officer at OpenAI is that there’s a huge amount of routing optimization going on and when I use these things, I’ll bounce back and forth between a trivial question and then, you know, can you solve cold fusion, you know, back to back and then, you know, the the models are very intelligent now about routing it to the the minimal model that will actually answer the question correctly. So a huge amount of savings from those types of optimizations and there many many different layers of that. So I think you’re going to see the the innovation at this ridiculous pace and then the price point continues to come down but again the demand is infinite so it won’t >> let us know when you solve 0 point energy. I’d like one. >> Okay. Okay. Um this is another fun article again Elon verse Musk poaches 14 meta engineers with a different offer. So, we’ll talk about, you know, what’s going on in Meta in a second, but I I
[00:26:01] think this is fundamentally what Elon does extraordinarily well, right? He has a massive transformative purpose, you know, open up Mars for humanity, make humanity multilary species. And he has that as a pure signal. And entrepreneurs who are willing to work hard, be, you know, who are builders want that. They want to work on something epic. uh it isn’t about the money since eventually we’re heading towards a postc capitalist society anyway. So Elon’s offering purpose and equity uh over cash and his equity has done incredibly well. I don’t think he’s ever started a company that’s lost money. It’s increased. You know, all the companies from Starlink to uh uh to XAI to X have basically just skyrocketed in value. And uh we’re going to see a startup intensity here. Uh, Alex, what are your thoughts on this? >> I I remember back to the early days of
[00:27:01] call it the uh the the post202 imageet revolution in AI when there was a lot of concern including as I recall from from Elon that AI would end up being a monoculture that >> one lab maybe called Google deep mind would would sort of completely capture the future light cone with with AI. And I I think I I I view this and other related headlines as very helpful sign that we’re not ending up in that future of of a monoculture of a singleton where just a a single culture from a single frontier lab has complete dominance complete hegemony over over AI. We’re going to see and we are seeing multiple competing AI frontier labs with different cultures. And this should uh and is, you know, this should be one of those cultures, the the manic focus and intensity of just delivering state-of-the-art results. And we’ll see lots of other cultures as well. And
[00:28:00] we’ll have them compete. And that’s the world that we humans, I I would argue, want to live in. >> Yeah. And I think, you know, purpose, a purpose- driven life is going to be far more important in the future than anything else. and being clear about why you’re doing what you do. And waking up in the morning and having an epic mission and being excited about building is a future that I want. You know, it’s always been part of my life and I want for my kids. Uh, and that’s what’s going to win over just cash, especially working someplace if you don’t like the culture. Uh, as you said, uh, I want to play a short video. Uh this comes as part of Elon’s uh master plan part four on sustainable abundance and let’s chat about it afterwards. >> Cool. >> So I love that term sustainable abundance. Um you know it’s amazing to see abundance becoming an underlying theme for you know the hyperscalers and for the tech world. And it’s part of the optimistic vision of the future. Right? You’re not going to see this on the 6:00
[00:29:00] or 7:00 news. You’re not going to see it on the Washington Post, the New York Times. It’s important to realize that technologies that we’re talking about on this pod are going to shape every aspect of our lives and there is so much positive news. so easy to focus on the negative. But, you know, understanding and this is, you know, Elon’s been on this mission since I met him back in 2000 when he’d sold uh, you know, sold to PayPal. Sold PayPal to uh um, what you call it. Sold. Yeah. To eBay. and he’s been on the mission of autonomous vehicles, electric cars, solar, uh, you know, making humanity multilanetary and people love those epic grand challenges, right? These moonshots which is podcast is all about and they gravitate towards that. >> Dave, >> so uh, Peter, you invented X-P prize and used X about 10 years before Elon stole it from you and then abundance was the name of one of your books.
[00:30:00] >> My my first book. Yes. So, so what’s what’s next in the uh Elon takes all Peter ideas and >> Oh god, it was very funny because the X-P prize logo looked identical to to SpaceX’s and then to X’s logo. >> Uh I didn’t have the heart to call him out on it, but hey, >> it’s fine. >> He’s been he’s been generous supporting the X-P prize and supporting our our work over the years. He’s he’s given, you know, probably $150 million of capital to support some of the X- prizes we’ve done. But sustainable abundance is a real thing, right? Uh it’s about digitizing, dematerializing, demonetizing, and democratizing everything where, you know, the way I like to describe this is if you think about it, when Google came out, Google was, you know, a for-profit company that had the biggest nonprofit impact. In other words, it uplifted all of humanity. and the poorest child on the planet using Google and the wealthiest child, you know, Larry Pa’s kids, Sergey
[00:31:00] Brin’s kids, Google was identical for those. It was a leveling and democratizing capability. And we’re going to see that here for food, water, energy, healthcare, education, and that’s extraordinary. Alex, you’ve been on this journey with me. >> Oh, yes. >> Yeah. No, I I I love this term. uh and I I think it’s sort of an implicit recognition that uh another important part of the equation which is autonomy uh a aka super intelligence or post-abundant intelligence is sort of the missing factor here. So, so when I look at the video and I hear the term and I I see its usage in practice, immediately this screams to me the intersection of abundant energy and materials on the one hand and abundant intelligence and autonomy on the other hand. And I I think it’s sort of a it it’s a rare and precious time in human history when we can have near total clarity as to what the technology tree looks like. Every time every time we
[00:32:01] talk about having scarcity of something like lithium, oh my god, we’re running out of lithium, it’s like we discover these massive supplies, you know, off the coast of California, there is nothing that’s truly scarce, period. And I think the sooner people get that technology is a scarcity, you know, destroying force. Dave, you were going to say something. >> Yeah. Well, yeah. The other thing on that slide that that is kind of sandwiched in the middle in bullet too is the 7-day work week. Uh you we have a bunch of companies at Link Studio working 997 and they just declare, you know, we’re doing 997. What’s 997? It’s this China thing where you work 9:00 a.m. to 9:00 p.m. 7 days a week while you’re sprinting towards some massively transformative purpose. So those two things go hand in hand. Like you no one’s going to work 997 on something irrelevant, right? It has to be something >> worldchanging and imminent. You know, 997 is no way to live your life. you know, you do it in a sprint to get to a very specific destination, but that is by far the winning strategy. You know,
[00:33:00] if you if you do this massive million GPU data center and you do it a year late, it’s worth zero. >> It’s absolutely worthless. So, there’s no point in doing it, you know, on a 4-day Europe work week. You just either do it or don’t do it. And if you do it, you can sprint. It’s like an Olympic gold medal. You got to sprint. >> Yeah. I think it’s also interesting when we I think it’s 996. Um yeah, China was 996, but I think Dave is saying with the >> Oh, the slide said seven. Sorry. W- with the reaction to 996, you know, popularly lying flat, people who are opting out of the 996 culture, it’s sort of interesting to think about whether sustainable abundance actually obiates that entire discussion altogether rather than lying flat at under the implicit assumption that 996 and that the need for enormous amounts of human labor are going to continue in perpetuity. What if we actually a few years from now find ourselves in a sustainably abundant future where the need for 996 human labor is actually only a short-term need? Few years from now we hand over
[00:34:02] that that workload to autonomous systems. >> Then we go to the stars. Then we go to the stars. All right. On the flip side of this conversation is people are beginning to bolt from Meta’s new super intelligence lab. So two months after the launch uh at least three top researchers have resigned. to return to OpenAI while Meta’s long-term product director also joined Altman’s ranks. Departures are raising questions despite recruits being offered nine figure pay packages. And to be clear, we don’t actually know what’s going inside. This is just reporting what came out and wired. But I do think when you’re capturing an employee by offering them a lot of money, um that’s not going to capture their time and attention and their heart. It’s mission and purpose that captures them. Dave, you agree? >> Well, absolutely. And I think also, you know, Elon has a reputation for everything always working, you know. So, having an MTP
[00:35:01] >> uh has to be married with a mission that will succeed to develop that reputation of not only is it massive in implications, but it’s going to happen. It’s real. Because it’s very easy to go out there and say, “Hey, I’m going to build, you know, electric cars.” Like, come on. And then if it doesn’t work out, no one will join you the second time. So you have to have a a track record of succeeding. Now Mark Zuckerberg is probably the, you know, of the young CEOs in the country, the most successful with the most cash flow, every opportunity to win. Elon has done it repeatedly, though. So I think a lot of people are flocking to the he’s always been right before. Why would he be wrong this time? >> Yeah. That really helps. >> Never doubt Elon. Right. Yeah. >> Yeah. >> All right. All right, I don’t want to spend too much time on this, but it’s been a big week for Google. We’re on the verge of the release of Gemini 3, which will be coming out any day now, but uh I mean, top news and extraordinary conversation around Nano Banana powered by Gemini 2.5 Flash image. Uh let’s take
[00:36:01] a look at this video. A few days ago, image editing changed forever. Google released Gemini Flash 2.5 image Nano Banana that has everyone buying puts on Adobe because Photoshop is officially dead. Instead of learning how to use all these antique tools, you can now just prompt Nano Banana for changes and it’s able to deliver any photo alterations you can imagine and most importantly while maintaining the consistency of the original image. Not only is Nano Banana an exceptional image model that’s already at the top of the LM Marina leaderboard, but it’s also extremely fast and affordable, costing only 3.9 cents per image via the API. The upgrade that most people are talking about though is character consistency. If you start with an image of a person or pet, for example, the model can blend it with a different image or make minor changes to it without noticeably altering the original character. Or multiple characters and objects like this guy did by blending 13 different images together. What’s kind of crazy about this model though is that it also has an understanding of the real world. Like if you point to a spot on Google Maps and ask what a person would see there, it
[00:37:01] can generate a realistic photo. >> Just epic. >> Just epic is right. And and I very few people basically nobody under the age of 40 remembers life before the guey, the guey on your computer. Uh user interface, but but we do. You know, when the when the Apple 2 first came out, you know, you would boot it up or, you know, TRS80 or whatever, you’d boot it up and this little flashing prompt would be there and what can I do with this prompt? >> Yeah. Yeah. Hello, what do I do? And all you can do is just start writing code. You know, it’s basically all all you’ve got. Just start writing code. And then, >> you know what, 1984 85, uh, you know, Steve Jobs comes out with the Mac and and now everybody’s lived in this kind of world of stasis of the guey for 30, 40 years now. So everybody’s like, “Yeah, nothing ever changes.” This is all going to change imminently. It’ll be the biggest step function. It’ll be much bigger than going from no computer to computer or computer to, you know, command line to guey. And but it’s been so long that nothing has changed that
[00:38:01] people are completely underestimating how different the world will be a year from today when everything has a I just asked the computer to do this for me just like on Star Trek >> and it just did it. But that’s that’s happening literally right now. >> I just the implications for startups are incred like if if if Adobe gets destroyed by this. >> You know, I think our friend Greg Bellis is still over there. So, it’ be kind of sad if if that happens. But it’ll be very important as a wakeup call that if if you’ve been camping on your software installed base for the last 20 plus years, milking it for money, your days are numbered. >> Yeah. I mean, >> because everything’s going to change. If you were a Adobe Photoshop or a Canva, you know, specialist making your living that way, right? I mean, you understood how to do layers and masks and manual adjustments. But Nano Banana is just, you know, edit through language, not layers. It like, you know, do this, you know, it’s it’s literally um, you know, how do you describe what you want in a
[00:39:01] way that AI will understand it? Uh, that’s going to be the skill base. >> Yeah. Exactly. If you’re if you’re a graphic artist or you’re a writer or whatever, you get so used to these tools and all their proprietary interface components and then you’re just afraid to shift to something else because it’s so you get so invested in knowing where the menus are and knowing where the buttons are and knowing how it responds and and so then you’re locked in and you end up paying for that product for, you know, 10 20 years. Now everything’s wide open again. The interface is trivial. My mom who’s in her 80s has no problem creating images. She could never use Adobe Photoshop. never never figured it out. Now she can just talk to it. >> I I would argue actually. So I’ve been using Nano Banana quite a bit. Uh it’s actually a much bigger deal than just uh some of the headlines that would say this is a Photoshop killer. So in using Nano Banana, some of the most striking new capabilities that I’ve seen are you can feed it an image and then ask to view the same scene from a different perspective. That that’s way more than
[00:40:00] just pixel level Photoshop style editing. It smells to me like this is just a sliver or a distillation of a larger world model. Sort of like we’ve spoken about Genie 3 in the past. It feels to me like this is some sort of like tendril from a much more monstrous model. And if that is indeed the case and to the extent that Nano Banana has basically become merged into mainline Gemini model releases by uh by Google DeepMind I I think this sort of portends a future where world models like in in the class of G3 the videos that that we’ve discussed previously those just merge into GPT or Gemini type models as the ultimate modality of of interactive simulated maybe even streaming realities. >> I tell you what else, Alex. You know, all media competes with all other media. There there’s no swim lanes. Everything competes for time for users. >> Time is scarce. >> At least while we have while we’re stuck with finite attention, maybe we can make
[00:41:01] attention post scarce as well. >> Okay. Well, for the next couple years, uh, but you know, this time of year, normally by now, I would have, you know, done a fantasy football league, signed up for my players, know who, you know, first football games will start. I haven’t even paid attention. I don’t even know what’s going on because the stuff that you post on our link chat is so much more entertaining and engaging than mainstream media. I the stuff that you as a single-handed person can create is so much more interesting and relevant. It’s it’s just a capability that that never would have existed a year ago. >> Well, look, a singularity probably only comes about approximately once per planet. So, it’s a special time. >> It is a special time. We’re going to celebrate that. I’m going to have a singularity party when it happens. I hope you guys will join me. Uh, you know, we made this point last time. AI won’t take your job. It’ll let you do any job. And I think this is a a perfect example, right? I mean, literally designers who have made their their career based on understanding how to use
[00:42:01] a specific tool really well. Now, anybody can do that. But here’s a question for you, right? If I go and I say to Nanovananda, hey, place me on the moon in a in a space suit getting into a starship for return flight to Earth and it generates that um you know who’s the author of that? Is it the software? Is it the human who prompted it? You know, we’re going to start to have some interesting conversations around ownership, you know, blurring the lines of authorship and human loop creativity. So, uh, that’s going to be an important conversation. But let’s talk about the, you know, the real issue here, which is the ability for this to drive accelerated misinformation and the erosion of visual trust, right? The old saying, seeing is believing is out the window, period. Thoughts? >> Yeah, I my comment on that would be we’re in a post V3, post Sora, post
[00:43:00] natural language generation era. I I think there’s a future to to the extent that one wants to have faith in the accuracy of uh any visual inputs, images or or videos. I I can see a future maybe where there’s some sort of cryptographic chain of trust between cameras, video and and still cameras and browsers. is sort of like the the way there’s uh cryptographic guarantee that when you put in your credit card information to pay for something on a website that that uh credit card information is is handled in a cryptographically safe way between you and the the ultimate counterparty. One can imagine uh some sort of cryptographic guarantee that the image that uh that you see in social media was actually unaltered in in some sense from the original capture without any AI involved. That said, my my baseline expectation is that that’s not going to be very popular and blockchain to the rescue. But this is this is deep fakes on an industrial scale,
[00:44:01] >> right? I mean just to to put it where it is you know >> nan this is this is what people also said though right before GPT2 and GPT3 and this will empower all sorts of misinformation disinformation and yes there is a lot of probably false information that’s being generated by these models but I I I have to look at it as sort of a riskreward trade-off there’s so much new scientific information that’s being unlocked by these models very difficult to get too bothered by the the potential downsides. >> I’m not I’m not worried about that, but I’m just saying, you know, for the majority of eight billion people on the planet, if they keep on seeing I mean, you’re gonna get to a point where when I I’m there now, when I see a video, my first reaction is, is it real? Right. And my second reaction is going to be, no, it’s not real. >> Yeah. Yeah. No, no, there’s no doubt. You know, you’ve read all the Neil Stevenson books, I’m sure, Peter. Um, >> of course. >> Of course. >> It’s not an off course, but of course. Uh so yeah like uh the diamond age to me
[00:45:01] was the everything he’s ever predicted in those books has happened and he invented the word avatar in the first book snow crash uh just foresaw cyber cyerspace that word was invented there but in uh in the diamond age you know everybody moves into these communities that have different rules around technology and how you manifest it because it gets too weird too fast. And so the the big big step function change for society is cameras everywhere, right? And that started years ago. And then so now we’re living in the cameras every world. You know, there’s no concept of, you know, privacy. You know, anytime you’re outside, you’re being filmed at a minimum by a satellite. I’ve seen usually by >> you can know anything you want anytime you want, anywhere you want. The data is there. Layers of drones, layers of satellites, layer of autonomous car cameras everywhere. Everything’s being imaged. There is no privacy. That’s another conversation we can have some. >> Well, those those 10 megapixel cameras now are 50 cents each. >> Yeah. >> So, they’re they’re going to be everywhere. And so then now, you know,
[00:46:01] so that already happened to society and also social media happened to society. Just totally changed the whole election process and everything’s, you know, everything’s been disrupted tremendously in the last 10 years. So now you layer the deep fakes on top of that. It’s just the third act in this massive turbulent societal change that’s only going to accelerate. And you know, of course, governments do nothing. They just sit there and assume, you know, people are talking about the next election like it’s going to be anything like the last election. It’s going to be a different world by the time we get to the next election. >> Yeah. I would just may maybe add I I would speculate that this maybe call it a moral panic that that we’re engaging in right now is going to look very quaint in a few years. It it’s difficult to imagine people with smart glasses doing real-time augmented reality overlays of everything that they’re seeing on the one hand, which by the way means basically everything becomes photo edited. Everything that you see becomes doctorred by default on the one hand. On the other hand, oh, you know, clutch uh clutch what whatever it is uh the moral
[00:47:00] panic that that you’re worrying about. Um like what about the photo editing? No, I I I think it’s far more likely that this will look quaint and nonsensical in a few years whenever panic is becoming quaint. It’s worth noting that there is a digital invisible watermark that Google’s putting on these images, synth ID, and we’re going to start to have sort of a arms race between Gen AI and detection tools as well. Uh that’s going to be part of it. It’s always the, you know, the virus antivirus war. 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
[00:48:00] 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 onskin.co and write peter at checkout for a discount on the same product I use. Okay, now back to the episode. Let’s go to Google’s next big announcement uh of this past week uh which is Google Translate uh and uh another incredible product coming out right now. So Google’s AI powered live translation uh historically Google has translated about a trillion words per month for 600 million users supporting 246 243 languages which by the way is 58,86 language pairs. Uh amazing. But we’re now uh being driven by Gemini 2.5 with a live translate. Let’s take a look at this video. >> Hi there. Um my friend told me there’s a sandwich here that’s really good, but I’m not sure which one it is. It’s spicy, has really tasty cheese on it and avocados, I think.
[00:49:16] I think I know what it is. It’s seasonal. In fact, we’ve already taken it off the menu, but let me see if we can still prepare it for you. >> Pretty amazing. The question is, what’s this going to do to the industry of language translation? What’s it going to do to people learning languages? You know, I used to want my kids to learn multiple languages. Now the question is, do they invest their time in doing that? Um, gentlemen, >> what was that company that all the kids used to to cheat on their homework? They got a public company got obliterated. >> Uh, Alex, which one is it? >> Not sure. But I what I would I mean ju just um historic reminder remember the the transformer architecture that sort of helped to kickstart a lot of the the generative AI revolution. It was
[00:50:01] originally developed for language translation for machine translation. It was an encoder plus decoder architecture. Right now we mostly use the decoder part. Nonetheless, it it’s sort of ironic that the the the the original targeted application for transformers was statistical machine translation or machine translation. And it’s sort of only now that we’re starting to see pervasive uh machine translation finally tackling the real world use cases of real time conversational embeddings. I that’s first thought. Second thought is um it’s it’s sort of interesting to to speculate I think what does this do to language diversity in general? Do we uh do we does this is this sort of a net promoter of of languages? There there’s been a lot of hand ringing over the past 20 years about uh low resource languages dying out in favor of usually English but sometimes other languages or is this
[00:51:00] sort of a a net promoter of diversity where once all languages thanks to AI become fully interoperable as it were there’s suddenly no reason to collapse down to sort of one modal English language. Do you know you know the joke here? What do you call someone who speaks three languages is triilingual. Someone who speaks two languages bilingual. If they speak one language, they’re American. So >> I love that. >> Well, that’s going to turn out to be the winning strategy. What do you know? Uh the company was Che. Uh check out its stock ticker or we’ll splice it into the podcast here, but it went down from 90 bucks to a buck 40. Uh >> wow. >> You know, just just because you know, chat GPT is a better way to cheat on your homework or whatever. that’s not really what they do but but it’s it’s that >> but the point here is the point here is that Google is also providing a language practice mode that allows you to personalize speaking and listening exercises right and so the impact on that on Dualingo
[00:52:01] >> was a 10% stock uh stock drop you know so Dolingo is a$1 13 billion company it’s done incredibly well 130 million active users only 10% of users pay but nonetheless it’s generating real revenues and uh you can see this drop that occurred last on August 29th when uh when this Google live AI trans uh translate capability was announced. So this is another example where these large frontier models sort of in their wake whether or not they know it are going to be disrupting existing companies who are going to have to constantly be pivoting. Yeah, Netflix. Duolingo is absolutely doomed unless it becomes an AI company. And if it becomes an AI company, it can go through the roof. But, you know, a lot of these companies uh don’t have the AI talent to get started. So, you got to you got to turn the battleship somehow, but if you do succeed in turning the battleship, your valuation can go through the roof. You you’ve seen that a single incredibly talented AI researcher can be worth a
[00:53:00] billion dollars. >> So, you know, the value is there. I mean in general in the short term I want to generalize from from just this this one instance. Uh so in in some sense I I think the sort of the the cliche here is every software as a service company is under existential threat from generative AI models that will simply cannibalize them from below. Whether you know you’re you’re doing software for some enterprise purpose or whether you’re you’re just like software subscriptions to to help people learn new language that frontier model is just that chatbot is going to to devour you because you’ve become just one special case among uh countless numerous cases that a generalist model can handle. I I think that’s critically important, right? Every CEO out there, every board of directors needs to understand that if they’re not building on an AI base that’s accelerating alongside with everybody else, if they’re depending on their old business model, software as a service, they will be marginalized. But
[00:54:01] here’s here’s >> remember what we said before too. If you’re in a regulated industry, you have a little bit of time. You can actually get ahead of it. You got to get the AI talent now, but you can get ahead of it. If you’re not in a regulated industry like you know CHEG or Dolingo and you’re just user installed base then you’re really vulnerable really. >> I mean you have an advantage of a user installed base and a brand use that to your advantage to actually leaprog forward. Don’t >> like idle. >> Yeah. >> Yeah. I I just to dwell for a minute on on what that leaprogging looks like. I I think I agree in the short to medium-term differentiated user experiences are are a bit of a a moat, if you will. But in the medium to long term, what I’d like to see from every single SAS that that feels existential risk from being devoured by a generalist model is step up your ambition by 100x, a thousandx. If you’re if you’re Duolingo and you happen to feel existentially threatened by generalist models, maybe consider becoming a brain computer interface company. Wouldn’t it
[00:55:00] be wonderful if we could sideloadad new languages in the style of the movie The Matrix into the human brain and rather than spending days or weeks or or years learning a new language? Why can’t you enable your your clients or users to learn it in a minute? >> Yes. Pick a moonshot. I mean, that’s the whole purpose of this podcast. Get people to go 10x, 100x bigger. Pick your moonshot or >> hire Alex as a consultant for two weeks and you’ll have a moonshot at the end of that. >> No, he has no time for that. Okay. All right. So, let’s take a a look here. We’ve got OpenAI real time API bringing smarter voice AI. So, let’s look at this quick video here. I love this one. Are there any homes in my budget near a water with a view of the skyline and Mount Reineer? >> Sure. Let me look. With your buyability of 824K, Wallingford would be a great fit. I think you’ll love 404 North 33rd Street. It has those skyline and rainier views you’re after. With this week’s market,
[00:56:02] I’d book a tour with an agent soon. Want me to set that up? >> So, this, you know, this capability, this is an example of of using this on Zillow to find your home, describing exactly what you want, and having it actually scrape and generate uh a efficient answer. But just the ability to to do all of this and actually get you to the point. I mean, what you want next is find the house, buy it for me, arrange the mortgage, and arrange the moving trucks, and let me know when to show up in my new place. >> Yeah. >> Yeah. No, I think I think AI as a management tool, a general purpose management tool, hugely un underrated because, you know, everybody loves the graphical stuff, you know, the image creation and the this, you know, the self-driving car, the stuff you can feel, but just as a general way to manage large-scale projects with hundreds of people and moving parts and logistics, it’s unbelievably good at doing that. So I think we can expect far more efficient construction, management, manufacturing, supply chains than we’ve
[00:57:01] ever seen before because you know the the sensor data with all the cameras everywhere has been available for a few years now. But it’s all kind of dumped into big databases. You throw it into Snowflake or something like that and then very hard to make sense of it. The missing ingredient was this AI overlay that can just take the unstructured free form data and turn it into conclusions, actions, schedules, buying things, scheduling things, managing things. You know, we had our our condo in Vermont built many years ago, 20 years ago, they put the Tyvec on upside down so it’s overlapping the wrong way, so it grabs rainwater and funnels it into the wood. So, you know, like, you know, years later, everything’s rotting. The whole thing’s falling apart. like why why would you put the Tyvec on upside down now very very easy for the AI to say hey dude stop it’s just as easy to put it on right you’re putting it on overlapping the wrong way just a trivially easy AI problem all of a sudden so it’s you know thousands of things like that can suddenly be converted
[00:58:01] >> so I I’ve oh sorry Peter >> I was going to say the point here though is is the real time API uh Alex let’s let’s chat about that >> yeah so I’ve I’ve played with this so the underlying model is is called GPT real time. And I if if you’ve played with uh AVM, the advanced voice mode of OpenAI, that’s that that’s the the mode where you’re you can chat in real time with very low latency responses with chat GPT. Uh it’s it’s it’s a lot like that, but in in API form so that it can serve as a backend for for third party applications. And I I really do think this is transformative uh in in part because imagine taking sort of low latency voicetovvice but generally capable intelligence and now embedding it everywhere. I I think it probably ends up being transformative for customer service type applications, probably many other sectors as well. But even bigger picture, I think this is a preview, albeit a a tiny preview of a future where every single audio segment,
[00:59:01] every single pixel on screen is generated in real time, streamed interactively on demand. and just our user our user experiences our user interfaces are just completely just in time generated. Uh it it’s going to be a very very interesting future >> and there’s a single there’s a single interface there’s a single interface to the world right your your Jarvis will go and interface with everything out there whether you know it exists or not and give you the answer you finally want. We don’t have a good catchphrase for this one. >> Our voice customer service company Vocara uh doubled in ARR during the past week and is planning to 10x between here and the end of the year uh just using this exact capability for for complex customer service and sales conversations. But so far the consumers dramatically prefer it to a human call center agent >> is so knowledgeable in the link studio. >> Mhm. Yeah. Yeah.
[01:00:00] IT team. >> To my knowledge, we’re we’re missing a term for this. I I I’m I I’ve definitely come around to the view that it’s important to coin new terms whenever there’s sort of this important new concept. I think we’re missing a term for this. It’s it’s not conversational user interface because it isn’t always conversational. The the the best term if if if I had to coin a term for what I think we’re seeing the beginnings of would be something like streaming interactive models. Uh it’s not necessarily just voice. could be like Genie 3 where if there’s a visual component could ultimately be uh like a brain computer interface type component. So try it on for size streaming interactive models or SIMs >> and because everything becomes a TLA uh streaming interactive interf uh uh models or SIMs, right? Okay, Alex, you >> Zillow example is really important for people to look at. You know, rewind the the pod and and watch it again because customer service is typically a phone call today. It’s very hard to explain complicated things on a phone call. So, this is very quickly going to move to multimodal where it’s talking to you
[01:01:00] while creating images in real time and people people haven’t experienced that before because no human call center operator can create an image or pull up, you know, thousands of pictures in real time, but the AI can do it very easily. >> Whole new experience. >> Let’s move on if we can. Lot to cover still. We’re still in AI. We’re going to be covering a lot more in energy, health, and and starship. Nvidia beats revenues uh predictions defying fears of an AI bubble. I think that’s great news. You know, up 56% yearonear from 2024. Companies at 4 trillion. Stock is up 700% since G uh Chat GPT’s 2022 release. How awesome is that? Um yet we still have a bunch of US China turbulence. Nvidia gave 15% of China sales to the US to keep exporting. Um, you know, just just, you know, reporting this news, Nvidia continues to be, you know,
[01:02:00] leading the pack. Uh, there’s another piece of news I want to hit on regarding this. Alex, I’d like you to chat about, which is uh which is out today. Uh, and it’s investors bet on uh Cambercon as China’s next AI chip champion. would you chat about this? >> Yeah, maybe looking at these two stories together through through the lens of where value is accumulating in the stack. So I I think there are sort of two competing world views. One is uh call it the uh the the pyramid model where the the the broadest part of the pyramid is at the base. uh in in this case uh under this world view most of the profits in the the AI revolution that we’re living through will accumulate at the lower infrastructure levels like the chip designers or or the fabs or data centers the the lower levels. Uh there’s also competing worldview that we ultimately move to uh or maybe are living in but just don’t realize it yet. An inverted pyramid model where most of the the profits and
[01:03:01] most of the value acrew uh at the upper layers the application layers the all the startups that are being built on on top of these frontier models and the frontier models themselves just become profitless uh or or profit sucking commodities. I I think if if you sort of look at these two stories through a common lens, at the moment, these would seem to bias me at least in the direction of thinking that for the moment, most of the the profit is accumulating at the bottom of the stack at the chip design level, at the data center level, regardless of geography. >> But let’s talk a little bit about um about this new company, about Camberon, if you would. >> Yeah. No, it’s it’s it’s difficult to to know what precisely is going on in in inside any given company regardless of whether it’s US-based or China based. I I do think again just generalizing over uh uh Huawei, Cambercon, and then obviously a whole cohort of of American
[01:04:02] AI chip designers. I I think we’re seeing the beginnings of uh of a nonmonoculture where there are diverse chip architectures, a diverse chip architectures for AI acceleration from the US uh and and seemingly the beginnings of a diverse set of non-nvidia based AI accelerator or accelerated compute architectures coming out of China. and where all of this goes. I I think Peter, your bet is as good, if not better, than mine, but I I think that the headline here is is is that there there may be the beginnings of a post Nvidia, post CUDA monoculture kind of >> that’s the point I want to make. Whenever you restrict China on uh ability to sell them products, they will develop products there, right? We have a lead, that lead is getting shorter and shorter on chips and AI. We saw this as well in the satellite world, right? When the US defense state department started
[01:05:00] limiting the ability to export satellites from the US to different parts of the world, the industry finally materialized and competed back against the United States. And so, you know, there this is this strategy of uh scarcity doesn’t work in a culture of a global culture of innovation. Well, I’ll also tell you, you know, David Saxs talking to you right now, but uh if if you look at that seven nanometer capability and we’re operating at two nanometers, you’re like, “Oh, we’re miles ahead of China.” >> But the algorithmic improvements can be massive like 1000,000x kind of improvements. >> Yes. That are way more important than the the 7 versus 2 nmter gap. And that we’re not used to that in government because we’re used to like the the nuclear arms race or the space race where you’re not going to get a 10x advantage by magic. You know, there’s no there’s no rocket fuel that you can throw in there that’s onetenth the weight of the competing. It just doesn’t exist. But in software, it does exist. In fact, it’s common. It’s everywhere.
[01:06:00] >> And so very easy to get complacent where you stand. >> You you in fact when you restrict, you cause innovation in different areas here. And you’re right, algorithmic, we’re going to see 100x, 200x, a thousandx improvements there over the next few years. >> And just to remember, you know, China has won the uh, you know, the math Olympics Olympiad now hand, you know, year after year after year. They have incredible talent. Uh, and 50% of Meta’s, you know, AI staff is Chinese. Uh, let’s not fool ourselves. Uh, the intelligence is there to innovate as well as here. though it’s different here of course we mentioned it earlier is sort of the risk capital the entrepreneurial uh drive that has people working around the clock. Um I would just make this note again as we talk about Nvidia. Uh this is not going to be solely in Nvidia world. We’re going to see China step up and uh and compete. Um I love this article. Again we’ve
[01:07:00] talked about the idea that that AI is no longer US ccentric. We’re seeing the world step up and get involved. So this is uh billionaire Amani uh taps Google and Meta to build India’s AI backbone. Mukesh Amani launches Reliance Intelligence Ventures to build India’s AI infrastructure. And you know I know Mukesh. I’ve been to his home a number of times in India. I was at his epic wedding uh uh what was it a year and a half ago or so. uh and the guy is an incredible entrepreneur. I mean just for people to understand this. So he enters India’s telecom market in 2016. He’s the 10th mobile provider, right? You’ve got Vodafone, Airel, all the players there. But he comes in with a completely different business model and that’s his brilliance. So Reliance Geo launched a radically different model. free voice calls for life, ultra cheap data, and
[01:08:01] months uh of free service trial. The other thing he did was it used to take you like 2 days to get a mobile phone. He basically said, “Show up in the store, sign a few papers, and it’s instantly up and operating.” And then he uses his capital to leapfrog over 2G and 3G and build out a 4G nationwide network. And so he literally destroyed the competition. Uh and they are the major cell phone provider, mobile phone, telefan provider. And you know, Salem’s in India right now. When I was there, it’s you know, five bars service 5G across the nation everywhere. So it’s pretty extraordinary and I expect he’s going to do the same thing here in AI. Well, something big is going to happen in India because you you saw Kevin Kevin wheels saying they’re making a huge push at OpenAI into India. Like, oh, that’s kind of odd. Why are you doing that? Well, if you look at the demographics of the country, it has by far the most untapped talent in the world. I mean, by
[01:09:01] far. Yeah. China’s in a terrible spot >> because of the aging demographic problem. The the one child per family thing caught up to them in a big way and now they’ve got a massive aging demographic problem. US is in great shape because immigration is is strong. always has been hopefully always will be but India has the best latent you know right in the sweet spot you know 20 to 40 year old talent pool in the world and so uh you know the reason that per capita GDP has been so bad in India for so long is that it’s incredibly corrupt you all the all the structures are terrible but I think AI might have a way to cut through that and just go direct to the people >> and also poor transportation between you know the roads being flooded out we’re going to aerial deliver uh in India as well. All right, let’s keep moving on. Time top 100 AI for 2025. So, this was their their issue. I sent Mark Benny off. Congratulations. I said, Mark, you’re not listed here, but you need to
[01:10:00] be on this list as well. Uh but check this out. You know, if these are in order, uh, Matthew Prince is number one, Elon’s number two, Sam Alman’s number three, and it’s fascinating that Matthew Prince is number one. Any idea why? I mean, I I I would be remiss if I didn’t note that uh sometime in in the the media cycle over the the past week is uh there’s a lot of interest in the future of Cloudflare uh which which Matt leads and and agentic AI. uh there’s a lot of interest in what does almost what does a web where AI agents that are independently surfing the web on the same level with the same rights as human web surfers look like or should there be sort of a separate entrance to the web and to the economy for AI agents. So, uh, if I had to speculate, I would say the intersection of Cloudflare and, uh,
[01:11:01] special handling of AI agents could be one possible reason. I >> I did I did a little digging. Let me tell you what I found out. So, Matthew Prince, uh, stands at top this list for one reason. He’s been focused on safeguarding the value of internet content. So, he’s all about making sure that there’s proper attribution and that uh you basically are not stealing from the publishers. And of course, Time magazine is a publisher. And so, I think they’re uh flexing their muscle here to say uh attribution is critically important. I I think it’s going to be I mean maybe even worthy of of much more dedicated time actually doing a deep dive on the issue of should AI surfing the web on its own be treated the same as a human web surfer or should they be treated differently? I I think there are so many nuances there. >> Yeah. >> The other thing we see on this list is a huge amount of global diversity and it picks up leaders in different countries.
[01:12:00] This is no longer just a Silicon Valley play. This is a global play where countries are beginning to invest heavily and really double down on this. Um, next topic here, I love this one. So, uh, Airbnb’s co-founder, uh, Joe Gibbia, who’s been on my stage at Abundance, he’s amazing, uh, is named the US Chief Design Officer. Uh, so appointed by Trump. His goal is redesign government sites and services to be simple, modern, and friendly. I love his quote. I want to make government services as satisfying to use as the Apple Store. That would be awesome. So, >> I think it’s it’s perhaps not obvious, but there is actually uh an open- source library hosted on GitHub. Um that’s I I think it offers Joe enormous amounts of of leverage for the task that he’s taking on. It’s called the US Web Design System, US WDS. And it it is in
[01:13:00] principle common set of of user interface components underlying most not all perhaps but most US government websites. And that’s sort of a seminal place I I think Joe has the opportunity such high leverage to to start if if the goal is to radically improve the user experience directing at least. I think the key the key point of this story here is the Trump administration tapping entrepreneurs to come in and help move the government forward. Um, you know, despite, you know, if you’re a Trump lover or hater, doesn’t matter. This is about bringing in the smartest people cuz historically going to work for the government was not what where a intelligent entrepreneur would go. Um, and there’s been an incredible shift in that regard. Dave Yeah. No, you phrased it exactly right. I think uh when when the US government said we’re going to have a chief technology officer uh back under Obama originally, the first two CTOs of the
[01:14:00] United States had law degrees and they were just buddies of the president and then you know then we created that healthcare.gov site. It was a billion dollars to build a website and then it never launched. It failed. So like okay, why don’t we get some real technologists into DC? >> Uh I can’t believe it’s actually happening though. It’s amazing. >> Well, these people are post capital, you know, postabundance themselves, right? They’ve made their money. Um, they could be working on their next moonshot or they could be, you know, building a moonshot that will hopefully write the battleship or I want to use that term, write, you know, the ocean liner of the United States. >> I think during co a lot of people who normally didn’t care about government suddenly started caring a lot. They they realized how much government can change your day-to-day life. You know, forcing you to to stay inside, that’s pretty extreme in terms of government intervention in day-to-day life. So, you know, whether it was right or wrong, they they they felt like, wow, this really matters. I need to get involved. >> Yeah. Well, good luck to Joe. Um I’m
[01:15:02] sure I mean this will have a huge impact. I mean, making something actually usable. This is like when we had ARPANET, you know, usable by a few individuals at MIT and Harvard and Stanford and, you know, defense industry and then Mark Andre comes and and builds a layer on top of that with Mosaic. So, uh, if Joe can do that, make it easy to use and functional, that would be amazing. All right, here’s our debate and discussion for today. I’m going to read this out and I want to hear your thoughts here. So, here it is. Will people vote AI to power? So, this is a tweet from uh V Razer X. Because they’ve tired of corruption and broken promises, AI will provide laws without loopholes and policies based on measurable outcomes. Election by election, trust will shift. Eventually, the ballot will include a new option, governance by AI. Citizens will choose it, not out of fear, but hope for fairness. Power won’t
[01:16:01] be inherited or bought. It will be optimized and accountable. Democracy democracy’s paradox people will freely vote to be governed by something beyond human flaws. So um here’s the question. Do you do you believe this? Do you believe that we will be voting AI into power? Uh Dave, what’s your position here? Well, I think there’s a long history of uh laws having people’s names on them like, you know, the Obamacare or Glass Deagle Act or Graham Dodd or, you know, PE I I think that the fact that AI is coming up with the idea and writing the law won’t change the fact that some someone will put their name on it and say this is this is my act. Uh but it’ll still be AI creating the law under the covers. I think it’s inevitable. It’s going to happen. It’s going to happen very very quickly because the number of things that need some kind of a framework is explosively growing, exponentially growing. And so the traditional process of pass it through
[01:17:00] Congress, pass it through your local legislature, it’s way too slow to keep up with the the rate of change. So this is definitely going to happen, but not not quite the way you’re not going to vote in AI to be your politician. It’ll still look and sound like a person. >> So I’m going to take the Well, let me be clear. I wish this would happen. I’d love to see this happen. I don’t think there’s any way in the world short of a revolution or starting a new country off world that we’re going to see this happen. And there’s lots of reasons. I mean, for me, the most important thing is the entrenched bureaucracies, right? Uh politicians, bureaucracies, entrenched interests will fiercely resist bringing this on. Um courts will strike this down, you know, and talk about getting rid of corruption. corruption uh doesn’t vanish, it just shifts, right? So corruption will shift from the politicians to the engineers or corporations or states that are manipulating the AI. So as much as I’d love to see this happen, I don’t think it will. Uh Alex, how about you?
[01:18:02] >> I I’ll take a third position uh in in this debate. I question is nonsensical. This is a very old trope in in fiction. Um so just two examples. Uh if you remember the the original version of the day the earth stood still based on the the sci-fi novella Farewell to the master the entire premise was that alien civilizations uh had decided that they themselves uh the biologicals couldn’t be trusted to to maintain peace. So they seated all authority to race of robots that police them. One can look back uh even further. remember famously Henry V 6th uh let’s kill all the lawyers this is a very old trope in in fiction I I think it’s completely nonsensical what I expect to happen is humans will merge with the AIS and so the question then degenerates to will people vote people to power and the answer is yes but it’s sort of vacuous in my mind to ask
[01:19:00] whether people will be separately from that voting AI of power >> we will couple and we will >> yeah we’ll merge will speciate. All right, so next article on our economy, Jensen uh announces that he expects $600 billion a year on AI alone. Um we’re seeing a massive uh continuation of uh investment. Uh this is a good thing. We’re also seeing the AI spend frenzy is propping up the US real economy. Um and we’ve seen the impact surging our GDP 1%. Uh I think this is interesting that AI infrastructure will reach 375 billion by the end of this year and is expected to be at a half a trillion in 2026. Um so the money is flowing out of Silicon Valley out of sovereigns out of family offices into the US economy through the piping of AI. Uh I want to pause on this conversation here. Uh this is NASDAQ bubble soaring past dotcom
[01:20:03] records. So I’ll read this. Here’s a chart here looking at the NASDAQ market over the last uh 25 years. So NASDAQ’s market value has surged to unprecedented levels now equal to 176% of the entire US money supply. 129% of the GDP. Both ratios are far above the dotcom bubble peak signaling stock prices are racing far ahead of the real economy. Uh let’s talk about this for a second. I think it’s important. Uh is this different than the dot bubble? Alex, any thoughts? >> I want to pose a thought experiment. So if we were on the verge of artificial super intelligence, what would you Peter Dave expect the ratio of the NASDAQ market cap to the M2 to look like? >> Approaching infinity. ripping upward. >> Yeah, >> exactly. >> So, this has all the hallmarks of the signature that one might expect at at least uh in the short term, one might
[01:21:02] reasonably expect there to be a concentration of rents around key publicly traded on the NASDAQ providers of AI infrastructure. And then maybe at some point, again, you know, this is not investment advice that this is uh idle thought experiment, one might expect perhaps at some point uh all of these rents become more evenly and profits become diffused throughout the economy and then maybe we see a plateau at that point. But this is exactly the signature that I would expect to see uh this ratio uh to M2 ripping upwards in the context of the eve of super intelligence. >> Yeah, I completely agree, Alex. uh it is exactly what you would expect to see. I also don’t think you know the.com bubble was really a bubble in the sense that the at the peak there like Amazon was probably a bargain and then it went down 90 plus% in the trough and then we had 9/11 right after that and which turned out to be a great great buying
[01:22:01] opportunity in the market but the internet was real it was always real and the valuations you know they got they got very high but some great companies were in there and then you know Google got started right at the bottom and then went public in ’ 04 on this chart. And so, so, you know, I think there’s a possibility of the market coming down through, you know, through panic, but it’s all it’s not rational because what’s going on should drive this to the moon. >> We also have companies that are real, that are profitable, that have real products and real services that are very different from the dot world, from, you know, pet food.com days and errors. So, >> well, a lot of these charts are meant to meant to scare you, too, because here you’re looking at the NASDAQ. Well, the NASDAQ is a bigger fraction of the market now because tech has become so big >> and and the the PTE is a little high uh of the market as a whole right now, but it’s not nearly as as you know outlandish as this chart makes it look. I like Alex’s explanation the most. This is the signal that digital super intelligence is uh arriving.
[01:23:02] Okay, let’s move on to uh to a comp a conversation around health, one of my favorite subjects. Uh so we just saw an announcement out of the UK of an AI stethoscope detecting major heart disease in 15 seconds. And this is a perfect use of technology, right? You put the AI layer right there at the stethoscope because you know in medical school you are listening carefully to all of these heart sounds and trying to hear a murmur and trying to hear you know uh lubdub and variations thereof. uh AI can pick it up far far better uh than than this can. You know, we had a $10 million Qualcomm triquarter X-priseze. Of course, everything comes back to uh to Star Trek, Alex, doesn’t it? You know, reinventing or making the Star Trek universe real. >> Such a strange universe, Peter. Again, uh biotech without longevity. Very strange universe. Yeah, we’ll we’ll get
[01:24:00] to that in a minute, but uh we had this $10 million competition that Paul Jacobs, who was CEO of Qualcomm, funded at the time. And uh to win to win this competition, uh you you basically had to diagnose 13 different uh uh conditions from, you know, anemia, diabetes, pneumonia, sleep apnea. The device had to weigh under five pounds, which is huge. Uh eventually these things will become embedded. uh and you had to record five vital signs. So, this is a step in the right direction. Um but you know, this is great. It’s still the beginning, but it portends what’s coming next. And one of the things I love, one of the companies I venture back through bold is called uh Echo EXO, and they build an ultrasound platform. But what was great about this ultrasound machine, think about the kind of device. It’s a handheld ultrasound that you can look at your baby or look at your corided artery and so forth. But the key was it had an
[01:25:02] AI layer that would direct you on where to move the probe. So it would say, can you move it upwards? Can you rotate it inwards? Can you hold it there longer? And so if you had this ultrasound probe, you became the physician. The AI guided you to do what you needed to do and then it analyzed the imagery and gave you a diagnostic. I think that’s pretty amazing stuff. >> Totally. And I I would also maybe invoke the statistical folklore that everything is correlated. So I I think this is just scratching the the the tip of what’s possible in principle. Going back to the Star Trek triquarter, the the the key scenario I would like to see and would hope to see unlocked is mostly using the power of of AI, using relatively dimminimous hardware, can we simply infer the the physiological state of an entire person at a distance from a few key at a distance biomarkers with AI? Well, I mean, this is, you know, AI is
[01:26:01] going to drive health care out of the doctor’s office, out of the hospital, into the home, right? Where you’re being sensed all the time and your AI agents are just watching and listening. And it’s going to transform health. Uh, and all of this will be cheap and free. It’s going to be free because your company or your insurance company is going to pay for you to have those sensors in your home, on your body, in your toilet because it just saves all the cost, right? It’s like health care insurance is about keeping you healthy, not paying you after you’ve been sick. So anyway, all right, here’s another fun article. Uh I first saw this from David Sinclair who posted it. Psilocybin shows striking anti-aging effects in old mice. And I added this because, you know, we have a a community of folks out there who are interested in uh the psychoactive molecules. And so, check this out. Uh this is a 2025 study uh that extends cell lifespan by up to 57%. And so in
[01:27:03] this study they took aging mice and you can see on this chart here that about you know 20 weeks in and this is sort of like uh late middle age they started dosing them with psilocybin and at the end of the experiment which is 28 weeks long and mice really just live 2 years typically two two and a half years the survival rate of those on psilocybin was 80% versus 50% for those who are not on psilocybin. So um you know I’m trying to find out what the dose equivalent in uh for humans are but just this kind of continuous discovery of different molecules impact longevity. So those >> just yeah go ahead and maybe just to comment Peter on this one I mean sorry I read the paper very interesting paper I think it’s potentially promising the the authors do I think a great job of extracting downstream impacts so so not just I I think they were dosing with with psilocin which is a metabolite uh
[01:28:01] that normally uh in in humans and other large mammals uh emerges from metabolizing psilocybin but they look at the downstream impacts uh so there’s uh there there’s uh certain one expression there are changes is to the way uh telomeres uh in chromosomes are are managed and regulated. That’s a template I I think where ideally one wants all of the anti-aging effects without all of the central nervous system psychedelic effects. And I I think ideally uh and and so I I think that in an ideal world we find that we were able to extract that template, you know, CNS effects uh notwithstanding, we subtract those out and we’re able to to distill out a template for a nonCS version of this. I think that’ll be enormously impactful. >> Yeah. Um I wanted to share something I did on my summer vacation uh with our our viewers and readers. it was something you know I’m always experimenting uh always um hopefully doing intelligent experimentation but
[01:29:00] when I see technology come along that I believe has a prolongevity uh highreward lower risk approach I’m open to trying it and uh researching it and then sharing the results. So uh a couple of weeks ago uh I posted this on X. I went and did something called stem cell re-education. This was the work under Dr. Zho. I just want to share it because for a certain uh group of people this will be uh transformational. So stem cell re-education uh for about uh 6 hours or so I was my blood supply which is typically four lers I mean sort of uh I’m sorry 5 liters was put through a machine two and a half times. So it was a total of 12 L of blood were cycled and my immune cells right my T- cells macroofage lymphosytes and so forth were extracted out of that and I filled up a bag of about 300 cc’s a third of a liter of my white cells. Those cells uh were
[01:30:03] then co-incubated overnight with cord blood stem cells. These are stem cells from a newborn and those effectively my immune cells went to school. Uh they were they were put to a factory reset and uh they were that would happen for about a 24-hour period and the next day I had what about 1.27 billion re-educated immune cells flowed back into my body. And my goal is to, you know, bring my immune levels, my immune system levels back to a much more youthful state. Uh reduce inflammation, rebalance my immune system. Uh actually pump up my stem cell functionality and increase my immune function. Uh that’s my goal for myself. And we’re going to be flowing this technology in through Fountain Life as well. Our goal is to set this up at our Florida Florida centers. But I want to share um so it
[01:31:01] was amazing uh kudos to Dr. uh Dr. Zhao who is pioneered this work at Throne Bio. But I want to show two remarkable videos. Uh if someone in your life is dealing with type 1 diabetes, with alipcia, with Parkinson’s, with ALS, this technology is lifesaving. And what we’re doing here, a lot of these diseases turn out to be your immune system attacking your own body, right? Alipcia uh the loss of hair that’s attacking uh the hair follicles uh throughout your body and you lose your hair supply. This process basically cures that. You regrow all of your hair. Um let’s take a look at uh at two videos. I’m going to show you first a 17-year-old teenager who has type 1 diabetes. Right? This is where immune system is attacking your eyelid cells and your pancreas and you’re no longer producing uh insulin. And this young man
[01:32:00] has uh developed a neuropathy and you can see him here prior to treatment. He cannot get out of his bed to get into a wheelchair. That’s his normal state of function. Now uh let’s take a look at two months later after the treatment. I mean it’s a resurrection. He has been able to regain his function. His type 1 diabetes has been eliminated. Uh it’s extraordinary. Equally extraordinary. This is a fountain life patient who has ALS. ALS is a death sentence for most individuals. And so I want to show you the pre and post. So this is the pre video. His in inability to raise his hands above above his uh above his shoulder. Right? This is massively difficult. Now, let’s look at a couple of days later and his ability to basically regain his function for someone with ALS. I wish we had this for Stephen Hawking while he was still alive. So, I don’t know if you
[01:33:00] want to comment on this, but I just wanted to share because I think it’s, you know, this is the kind of uh regenerative medicine uh that our health span revolution is undergoing right now. Well, the only comment I’ll make is that when you when you >> talk about allergies and autoimmune disorders, there are so many interactions going on. It’s immensely complex. >> Yeah. >> And it’s a perfect fit for, you know, a AI that is just specific to your body and your results. And so it just it’s so promising that you can actually do something with this immense amount of data we can gather. Yeah, >> I think Peter, you’re courageous and and now we know what you did last summer. >> Um, I’ll report on the results. Uh, a huge list of markers were collected prior to my treatment and then I’ll report it out at 1 month, 3, 6, and 12 months. And I’m excited for it. Um, and we’ll see where this goes. All right,
[01:34:00] let’s dive into robots, energy, and transport. Um, I love this. Uh we’ve seen Nvidia with I love their their name of this. It’s the Jetson AGX Thor generation of uh robot brains, right? Enabling real time intelligent interaction at the edge. The Jetson’s are here. So this delivers 10x more than their previous uh chipset Orin. Uh it runs generative uh and reasoning AI models at the edge. I I love this. I double check these numbers. 2 million developers are are using the Jetson Thor uh development kit right now. Alex, two two pedlops of floating. 4 FP4 compute. So for for reference, that’s approximately a tenth of a Blackwell or um maybe about 30 iPhone 16 Pros. So when we talk about what’s going on with all the capex that’s flowing into ADA AI data centers, I I don’t think that’s going to be bottled up in data centers
[01:35:01] for very long. We’re going to see these these AI chips, the AI compute literally start to walk out of the data centers on onto the streets of the the rest of the economy, the the so-called real economy. And I I think Thor is is such an interesting case study in in how these uh this AI compute is going to be embodied in humanoid robots in a in an ergonomic um both uh energetically and physically uh ergonomic form factor and literally walk out onto the streets of the real economy. >> Amazing. >> Yeah. And I really think this is important for all the uh all the students struggling with their largely irrelevant curriculum. This is what you should be doing. Yeah, you your your phone or your laptop will do about 30 teraflops now. So, it’s, you know, it’s about a hundth of uh what you can get from a probably $4,000 $5,000 Nvidia chip. So, get get yourself an accelerator on the side or just run if you go to Andre Carpathy’s libraries on GitHub, you can get a really fast start.
[01:36:00] And a lot of things that were daunting six months ago, you can just void voice code vibe code them to existence on your laptop in under an hour. And so you really can get your hands dirty with these toolkits and then all of a sudden you’re one of these people that’s getting the $und00 million signing offer. Like I got how did I get from here to there? Well, I just jumped in and got my hands dirty. >> I played. So we got >> fun. It really is fun. >> We got an image here of of Jensen with Brett Adcock. Uh CEO of Figure. We had Brett on stage at the Abundance Summit last year. Uh we’re going to have at least four, maybe five of the robot CEOs on stage with us at the Abundance Summit uh this coming March. And by the way, you’re going to have the Moonshot mates, all four of us. We’ll have See and Dave and Alex and myself on stage at the Abundance Summit as well. We’ll be doing a Moonshot sort of recap what WTF just happened in tech in the last three days of the Abundance Summit in March. Uh if you want more information, you can go to uh abundance360.com
[01:37:01] to learn more about the summit. It is uh for me, you know, an epic part of uh my year and my life getting ready for that. Um China uh China’s humanoid robot sales expected to exceed 10,000 units in 2025, year-on-year growth of 125%. I love this image of robots marching down the street. What could possibly go wrong? Uh but this is just the beginning, right? We’re going to see, we heard when we uh interviewed the CEO of 1X Technologies, um Burnt Borick, you know, he expects to see uh flowing out of his factories hundreds of thousands. And of course, we’ll see that from Figure, we’ll see that from uh from Tesla. Uh you know, the prediction of 10 billion humanoid robots by 2040. Um it’s coming. All right, here’s another article. I think this is pretty much Elon Classic. Tesla is shifting optimist training strategy to vision only. So we saw this uh with
[01:38:00] uh self-driving. He said no LAR. You know, I introduced the uh CEO of Luminar to Elon at a party and Luminar makes a LAR and Elon just went nope, no LAR. We’re vision only. If a driver, if a human driver can drive with like one eye, we should be able to have AI do the same. And so the switch here is no longer motion capture suits. It’s just going to be training robots based upon video uh recordings of workers doing the work. Uh Alex, you you buy this? >> Yeah. I mean, obviously this does rhyme with the the LAR versus non-lar episode with autonomous vehicles, but I I think the the real story here is to the extent that you believe that we’re about to to all be wearing smart glasses, that that’s the next major form factor after smartphones, I can only imagine what fleet learning is going to look like when you have billions of people basically doing visualbased motion capture for humanoid robots. If going
[01:39:00] back to the beginning of of of this pod where we’re talking about the bitter lesson, the bitterest lesson of all arguably for for humanoid robotics is going to be when we have billions of people wearing smart glasses doing fleet learning to power every single trade, every single manual trade just off of passively watching through the smart glasses >> and recording all of human history in detail at the micro level. Right. No, that’s right. >> That did uh that did come up when we were at 1x robotics. You know, Bern Barnick in in his first 10,000 odd units, you have to use the fleet learning. There’s no option to turn it off. So, all the data, telemetry, and everything from your household is getting transmitted to the central learning engine. So, you know, there’s no human analog for that. Like you’re every job is training the centralized version. of if it knocks over a coffee cup in somebody’s house, then the other 9,999 houses, the robot doesn’t knock over the coffee cup. >> Can you feel? Here’s my question to everybody listening and watching. Can
[01:40:00] you feel the acceleration? Can you feel the singularity coming? >> Oh my god, I can for sure. >> Um, this is just in today. Apple is mandating all of its manufacturers uh all of its tier one suppliers automate automate automate uh use robotics instead of humans everywhere possible uh to increase uh you know reliability of the product and reduce costs. Um Alex a quick comment on this one. Yeah, I I think if you think the the world finds its way towards a completely redomemesticated supply chains, I I think robotics is probably the missing X factor for how just as we were discussing earlier, tiling the world’s surface, tiling the Earth’s surface with inference compute. One can imagine a not too distant future where robotics enables essentially e every sovereign country to in some sense redomemesticate
[01:41:00] its entire supply chain if it has inference time robotic capabilities to onshore every last bit of manufacturing. >> Amazing. We’ll see this at Amazon. We’ll see this at FedEx. We’ll see this at all the companies that survive. The companies that don’t do this aren’t going to survive. I think it’s going to be that pretty cut and dry. Um, I’ll want to hit one more robot story here, which is the competition between Whimo and Uber. Um, it isn’t really competition right now because, you know, we see Uber delivering 30 million trips per day while is at 700,000 trips per month, right? Um, but here’s here’s the point of this. one Whimo robo taxi outperforms 99% of Uber drivers on a daily basis in terms of daily trips. Right? These these Whimos are efficient and they’re running 24/7 except for their charge time of course. And so imagine as these roll out more and more they will displace Uber. Uber
[01:42:02] is trying their own own autonomous play. Uh they’re doubling down in San Francisco. They’ll be increasing the fleet by 50% there. They’re trying to get into New York. They’ll have a lot of resistance there, but we’ll see these technologies and of course cyber taxi and cyber cattle are coming. >> Alex, >> and remember, Peter, the the uh at least in America and some other countries, the postw World War II consumer automobile arguably created suburbia, created the suburb. What happens to urban planning when the cost of mobility is driven to zero? Uh do we see suburbs expand? What happens to roads? What happens to parking lots? What are we going to do with all the parking lots? >> Or I mean, but again, the elephant in the room on top of all of the hand ringing that I want to have. Oh, yeah. Exactly. The hand ringing over urban planning is there are so many other changes that are going to happen probably on a much faster time scale than we can replan cities and suburbs
[01:43:00] that maybe it’s all meaningless. Anyway, >> my my plan for the parking lots, are you turning them into vertical farms, right? each layer of the of the of the parking lot is growing a different different >> which is great if we need to be densely clustered together. But if we don’t need to be densely clustered together, maybe it’s something else entirely. >> And by the way, you know, I talk about the demonetization of everything, right? So driving will be four times cheaper than owning a car. So the poorest people will be chauffeured around first and foremost. And then how do you change the cost of living? Well, if you can live an hour from downtown LA where the real estate is cheap and you fly, you know, a a midnight an archer midnight EV tall back and forth to work or you don’t go to work. You’re using Starlink to telecommute. Yeah. >> Or we move to other planets or we upload to the cloud. There are so many different options. >> I’ll take all of the above, please. Uh, all right. So um I’m going to close on uh on this particular piece which is the
[01:44:01] US electricity spike begins. So this is a chart of the US consumer price index for electricity and we’re beginning to see a spike that started in 2021 and is continuing. Thoughts on this Alex? I mean, superficially price signals convey demand. That that that’s why we have a price-based system. But I I think the the elephant in the room here is what happens if and when we get to recursive self-improvement. >> We’ve already seen at least one demand shock, if you will. Uh that was the the Deep Seek Sputnik moment, if you will. What happens if and when there is some new algorithmic breakthrough that suddenly radically reduces the compute intensivity of frontier models? Could we actually could could the law of straight lines be violated and this this burning upward tearing upward of electricity costs reverse? >> Yeah. Remember >> the electricity is so easy to predict because we know recursive
[01:45:00] self-improvement is here right now. Well, we I know it anyway. >> Anyway, I tweeted the world will know it very soon. I tweeted this last week, right? The human brain operates on 20 watts of energy and you know I was playing uh in GPD5 and asking what the equivalent uh compute cost in terms of energy for you know one of the frontier models and it’s somewhere between 100,000 and a million times more energy than the human brain there. So this is a massive potential for improvement here. we’ll get new new chip designs, new uh new you know uh new strategies and approaches to make it more efficient. So we’ll build out all of this you know energy uh data centers and then if we you know 10 to the 5th 10 to the 6th improvement in energy efficiency that means we get that level of improvement on our our total AI capabilities. >> We can do better than that Peter the land hour limit we can blow past it with reversible computing. Human brain is by no means an optimal computer. There are
[01:46:00] lots of other better ways we could build computium. >> Amazing guys. Listen, as always, I love spending my time with you. I feel smarter afterwards. I hope everybody listening enjoyed this episode. Um, a lot more coming. We’re going to see the release of Gemini 3. We’ll be back on to discuss that. We’re going to be coming on with a lot more of WTF just happen in tech. Hopefully, this is your dose of optimism to counter all of the moaning pessimism coming off of the the the media channels that that people normally consume. I’ve stopped watching the news. For me, this is the news. The news that really matters, that transforms our planet, that is giving us increased longevity. It’s going to increase uh, you know, sustainable abundance is the word. Uh, Alex, some closing thoughts from you, then we’ll go to Dave. Black hole supercomputers. >> Okay. >> Okay. That’s a closing thought, >> which assumes we’re not living in the black hole right now. >> Agnostic. We’ll uh follow up on the
[01:47:01] short-term implications of the Leopold list and a bunch of other things. I think we’ll be back online again very quickly within a week uh with Salem back. There’s so much happening now. I have a bunch of things we couldn’t even get to today and then more will happen within within the week. So, yeah, just a lot a lot to keep up with, but this is the place to do it. Yeah, I was wearing my Occupy Mars shirt and uh uh in expectation that we’ll discuss Starship uh 10 launch which was a huge success. So congratulations to uh to Elon and this team and the the team at SpaceX for that launch. It was awesome. If you haven’t seen the video, please it is a proof that we’re living in the year 2025. Humanity is building fusion going to Mars heading towards longevity escape velocity. You know, the only time more exciting than today to be alive is tomorrow. Uh, on that note, gentlemen, have a beautiful week. Talk to you all soon. Every week, my team and I study the top 10 technology meta trends that
[01:48:01] 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 metat 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 meta 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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