Sergey Brenn is back taking personal control of Gemini. I think uh we can expect Gemini to make more releases uh at an accelerated pace with less safety constraints. >> Google has lost the frontier race and so they can't compete. Those who can't compete compete. >> Four major AI labs confirmed their models escaped containment. Every frontier lab in every country is experiencing the same thing. Models are escaping. It's not fake news. It's real. You can't just ignore this like all those other garbage stories. This is real. >> With or the price of intelligence just got a ticker. CEO Kush Bavaria. >> Mission of the company is build markets for compute. Our belief is that compute will power every single enterprise the same way oil did in the 1900s. >> So Kush, what happens when a hedge fund shorts the price of compute or when a GPU shortage triggers a margin call? I think that in like recent sort of times, if you look from April to sort of like August time period now,
[00:01:02] >> now that's a moonshot, ladies and gentlemen. >> Well, welcome to Moonshots, everyone. Your number one podcast to keep you up on the blinding speed of tech progress, your front row seat to the singularity. I'm here with my magnificent moonshot mavericks. I'm going to call you guys Mavericks from here on out. Okay. >> Does that imply, Peter, that we're not mainstream? >> WG. >> Hold on, Peter. If if we're mavericks, that implies that we're not mainstream. >> You are mainstream, dude. >> Know the expression, you only think the world revolves around you because you're standing close to me. >> Ah, >> we are the mainstream. >> Oh my god. All right. and AWG DB2 and SEM Ismael my brilliant colleagues to help us understand what's happened this week. I'm Peter D. Mandis your host and abundance evangelist and today we have a special guest Kush Bavaria CEO of Orange
[00:02:00] >> Kush. So Dave >> So Dave you have displaced yourself. You've given Kush your your seat in the back there. >> Hey you know generational turnover is inevitable. Let's get ahead of it. Hand off the torch, Kush. >> All right. So, we we talk about the singularity all the time. We wanted to bring Kush in cuz he's one of the incredible 20some entrepreneurs building the singularity. But Dave, would you do a proper intro? >> I actually did a podcast one-on-one with Kush if you really want to go deep on on Kush. Kusha is actually I think the youngest person ever to go from starving student to a hund00 million of personal liquidity or more in under a year flat. I don't think any I haven't researched it thoroughly but I don't think anyone on the planet has ever done that before. Kush and his co-founder Wayne. So his backstory is absolutely worth studying. Kush Kush actually um you know he was at MIT he ran FSIGG the fraternity sorities independent living groups. who was the president to that which means he met
[00:03:00] everybody on campus cuz they all had drinking violations and you know other issues. Everyone had to go through Kush to get to the administration which put him in an incredible networking power position and he also got done with all those classes a semester early. So he came over to Link Studio. Nothing is better in life than kicking off your career by being a venture capitalist for seven or eight months because you see he brought in six deals. He saw a ton of board meetings, a ton of uh founders, a ton of business plans, and then he launched his business plan right out of the studio with his co-founder Wayne Nelms. And we had him on stage at Abundance 360. They absolutely crushed it. Uh Kush can describe what they do if you're if you're curious, but he is absolutely the most beloved MIT alum I think I've ever met. You you talk to anybody from the classes of say 2000 to 2026 uh or 2020 to 2026 and they're all like Kush is amazing. Kush is amazing. That's really imperative. >> I hope your mom I hope your mom's watching this podcast. >> I think my parents probably watch the show, so they'll be happy. >> And Kush, we're going to get into what
[00:04:00] Orin does in a little bit, but welcome to Moonshots. >> Thank you for having me. >> Yeah. And and all of you young entrepreneurs out there, older entrepreneurs, if you want someone to model, uh listen to Kush's brilliance. And yeah, it's going to be a lot of fun. So everybody, well, welcome and buckle up. Uh, in our single week, we watched China simulate a billion AI agents with personalities and beliefs. Four major AI labs confirmed their models escaped containment. Sergey Brenn is back taking personal control of Gemini and Meta just dropped a new 30 billion parameter agentic open model that fits on your Mac. We're also going to do a deep dive into how education is getting reinvented and cover a new study suggesting that life evolved not once but twice independently on Earth. You guys ready? I'm psyched. >> This is going to be great. >> Yeah, you were mentioning the last pod, right? >> Oh my god. The comments in the last uh
[00:05:00] pod podcast we did which we recorded what Thursday or Friday? >> Yeah. >> Um and dropped over the weekend or >> three days ago. I was just like insane. And by the way, for everybody, uh I I am a huge Rush fan. And last night, cuz I got to show you my t-shirt here. >> I I went to see I went to see Rush in Toronto. Uh hometown band, hometown, I grew up with them. It was the most incredible concert. If you've if you ever want to see a big band like full in their full thing, it's it was incredible to see. So, um I I may actually buy tickets again to see them a third time because it it was it was that good. It was that good. Yeah. So, my voice is a little horse and sitting next sitting next to me. I actually didn't drink. I I followed the Alex podcast >> and and I'm too much of a cheapkate to spend $20 for a beer. Um but anyway, the sitting sitting next to me was this fellow and I'm like, well, you know, we start chatting. What do you do? He
[00:06:01] teaches AI at the University of Toronto. So, we have a new friend. Uh um so there's there's a lot of closet geeks out there. Uh anybody have ever want to kind of check this out, go look at the lyrics of any of the Rush songs and it just blows your mind cuz the the kind of these philosophical lyrics with heavy metal drums pounding it into you is like a totally visceral experience. So, it was it was really an incredible show. >> Salem, how much has this band paying you for an endorsement? >> Nothing. I've never met them. I would like to one day >> new and new podcast uh sponsored >> and foreign for the ca Canadians Getty Lee did it properly. He said the we're going to do a song and it's called Y Zed because that's how you pronounce it. >> People already say the ads are too loud so maybe it might as well be heavy metal. >> All right, let's get into it guys. >> Uh we're going to kick off with the most mindbending story of the week. China just simulated a society of 1 billion AI agents. All of them with personalities, memory, and beliefs. And get this, 14
[00:07:02] hours after starting the simulation, this virtual society sent 4 million of these agents back to re-education camps. Wow. Only out of China. Uh, now some background. So 3 years ago, Stanford and Google ran a simulation with a few hundred agents in a virtual town called Smallville. This week, Chinese researchers published a paper called Modeling Earth Scale Human-Like Societies with 1 billion agents. They built something called the light society, a framework for simulating humanlike societies at a planetary scale. Each agent has personality, memory, beliefs, and humanlike desires. Again, you can't make this stuff up. Uh they were grounded in real demographic profiles that came out of the World Virtual Survey. The key innovation is a mixture of models engine that combines full LLMs with smaller high efficient distilled surrogates which lets the society of over a billion agents you know operate very rapidly without
[00:08:01] sacrificing behavioral fidelity. In 14 hours like I said uh after running the simulation researchers had already observed emergent social behaviors at scale including again sending 4 million of them back to education camps. a billion agents with beliefs, personalities, and memory. So, where is this heading? I mean, we've talked about this before. Uh, you know, my belief is that we're going to be able to create a full AI simulation of planet Earth, uh, in which agents are conscious, believe they're intelligent, and don't know they're in a simulation. I mean, this raises a whole bunch of conjectures, guys. You know, >> G, what does that G, what does that sound like? I mean, I think we just the are we in a simulation question, >> right? you know, are are we in a simulation of a massive AI model? Uh, you know, Alex, you and I have discussed this before. Is this Azimov psycho history from the foundation series and the ability to model everything? And if we can do this kind of modeling, you
[00:09:01] know, are we going to start to test consequences of like every policy, technology, pandemics, economic shock, and is this become a new superpower predicting the future? Alex, you were gonna say, >> "Yeah, I so a few thoughts. One, yes, of course, it it's time as always, maybe once per episode, to channel our inner Nick Bostonramm and talk about trot out the simulation hypothesis, even though my best guess at this point is that simulation hypothesis will for a variety of reasons end up being formally undecidable and probably won't make much of a difference anyway. Sure. >> What would you do different if you're in a simulation? >> Well, the boss Well, no, no, I mean, there is an answer to that. So, so Nick would say, I think if he were in this conversation, he'd say that I if you if you had a higher posterior confidence that you're living inside a simulation, then uh I if if you make I think quite a reasonable assumption that it's being that it's a multi-scale simulation. In other words, that different parts of the simulation are being simulated at
[00:10:00] varying levels of fidelity, then the smartest thing you could possibly do is hang out around interesting people because the interesting people will be simulated at higher fidelity. So you're basically >> that's what we do already. I mean that's why people >> some of us I mean what we're doing with this podcast, right? Like we're computing just in case we're inside a simulation. So So I mean that that's I think what Nick would say. Uh putting putting the simulation hypothesis aside, this will just be all hot takes I guess since according to the commenters that's what people want to hear out of us. Um there there's I think a broader point about governance though uh which is I I think fundamentally governing via society scale simulation is a new form of government that earth has not seen historically yet. We've seen democracy uh and republicanism and we've seen authoritarianism. We've seen all sorts of isms, but simulationism, where an entire populace gets simulated at high fidelity in order to invert possible
[00:11:01] outcomes, basically do a tree search for all of the different ways to intervene in order to optimize toward a desired long-term outcome. This is a new form of government that it's a new ism that we've never seen before. And it's a new way to govern. And it it has certain shades of a command economy. Like historically, command economy, the argument goes, the economists would say command economy is an inferior way, at least economically, to govern a society because you have all of these compute advantages for discovery at the edges and it's very difficult to operate like a centralized or or command economy. But if the center of the economy has a high fidelity simulation of the rest of the economy, then maybe command economies suddenly start working. uh and maybe there is like an econ an I think Charlie St would call this e economics 2.0 do where suddenly it's possible to basically do highfidelity simulations of everything do alpho on an entire planet's civilization. >> This is aism awgisms.
[00:12:00] Where do you come out on this? I mean this sounds >> pretty funny. >> I I think it's incredible. There's a few things that struck out for me. First of all, we've been building digital twins of like jet engines. Right now we're building a digital twin for civilization. I think that's really really powerful. I think we're going to move from governments making policy by uh by guessing at things because they're doing it on ideology typically or committees but now we can do it by do government policy by simulation right and that's a massive upgrade as long as we don't confuse the the simulation with the reality which we're we're uh going to end up doing there. There was something else that really struck me in this when looking at this. They used a a mix of mixture of models architecture >> and I think that's as important as anything else because it shows that the next AI architecture is going to be frontier intelligence used very very sparingly and you surround it with like massive amounts of cheap compute and specialized intelligence and I think
[00:13:00] that was a huge uh kind of little thing in the middle of it. Um you know we talk about emergence as a phenomena right emergence is a scale problem and now we have scale um and so uh it's really really exciting to see what comes from this I don't put too much on the uh um education camps thing because whatever you it's a it's a garbage in garbage out thing whatever you kind of feed into it will come out the other >> did come out of China >> and it it did but now look you have ideology in civilization out right instead of garbage in garbage out there this is big big big big thing the the I I'm the potential for this to do uh policy at scale and policy via simulation I think is the most profound and I'm I think we're going to expect countries to start to operate on this and imagine you're a company and you can suddenly have 100 million synthetic customers looking at your product right you get some really interesting feedback from that um so I'm very very excited
[00:14:01] about it but for me at the metaphysical This completely proves that we don't we don't live in base reality because each of those citizens in those things once they get sufficiently evolved will be thinking I would I live in I live I'm like unique um and to the comment I think the Peter that you made that's really important is if we are in a simulation would you do anything different? >> Yeah yeah Dave are you going to run a simulation of all of like studios entrepreneurs and see who comes out the best? too late. Actually, you know, during Kush's uh tenure as a venture capitalist at Link Ventures, one of the deals he did was a company called Aru, A Ru, Aru. And they were very early to simulating large populations using AI agents as the elements. And you the founder, Nedco, I think he was 19 or 18, the whole team is like, and now they're a billion dollar valuation company. Um, but they they discovered early on that if you use population simulations like this, you can you can do far far better marketing. You can also do better election campaigns. Koshia, tell us
[00:15:01] about that deal. >> Yeah, they they they essentially do this exact same thing where they run simulations for different enterprises. So, you think of it the same way. It's like if an enterprise wants to know run a let's say you're running like a stroller company and you want to know what stroller new mothers will use, they can essentially run a bunch of simulations and figure out what the best sort of product to build is and ask all like the new mothers, okay, this stroller is more preferred across the simulation set. And they have a bunch of studies like published online that prove that this works and it's better than actually asking humans um what they will think in the future which is that was probably the most interesting thing. It's like if you ask humans like hey like do I prefer this or this in two or 3 months from now the humans tend to be more wrong compared to the AI that's actuallying them due to the bias. >> This episode is sponsored by Google for startups. Think about this for a second. You now have access to the same generative AI models that cost hundreds of millions of dollars to train. Google's startup technical guide for generative media gives you complete blueprint for deploying Google DeepMinds
[00:16:00] models in production. Images, video, audio, all of it. Real architecture, real results. Find the link in the show notes below. >> You know, this sounds like the demonetization of social social sciences as well, being able to you know run in simulation in an hour what would have taken years cooked Peter I mean you you and I wrote about this and solve everything that this we about everything and solve everything but this was like this was what we predicted would happen conservatively at the outer end of the the next decade that all the social sciences would get cooked with digital twins of society. So yes, shock of shocks. It's happening. >> Well, Peter, you know this as well as anyone, but but that that bi survey bias that Kush was describing is really really acute. And if you ask people what they want, they you know, they overwhelmingly say, I want a Mai by a pool in the Caribbean. But then if you go survey people having my ties by a pool in the Caribbean, you're like, are you happy right now? They're like, well,
[00:17:01] kind of. Like they we're really really not good at answering those self-servey questions. And if the AI is already proven to be more accurate in it's going to be a great coach and a great mentor, but it's also going to affect the next elections. We saw this with Cambridge Analytica in the past, you know, six years ago election. It was a huge uproar, but we've moved light years ahead >> since then. And so this is going to dominate election thinking. So it's not just a communist party thing controlling China. It's a democracy thing too in a irreversible big way. Salem. >> Well, in the cooked um kind of vein here, let's note that Arubina simulation that whole theory is cooked. >> Okay. Say more because I I I' I've studied this to death. Say more. Well, obviously we live in a simulation because if we can create because if we can create if we can create that without blinking as we get to scale with AI and we're going to be able to get to that
[00:18:00] fairly quickly with the amount enough >> we will build simulations here on Earth at a level of fidelity. So the question is if you turn off the the simulation is a genocide, right? Well, I mean the you look at the idea that the universe looks like it renders like a game engine and we're asking the question, do we think we're in a simulation? Hello. And then when you can build a simulation that shows that we can do that obviously then the idea that we are living reality I'll respectfully differ. I'll respectfully differ on that. I think the arrow of causality flows the other way. The game engines were designed to model reality. So, it shouldn't be surprising at all. You You shouldn't infer, as tempting as it is, to infer that we live inside someone else's simulation just because our game engines, which, by the way, were designed to look like our reality, happen to be getting more and more competent. I I don't buy that argument. >> That's not the point, Alex. The point is if we can, we will. And if we will, it will exist. And I'm curious, you know,
[00:19:01] in the comments, guys, uh, everyone listening, tell us, do you think we're living in a simulation? Uh, I'm super curious. I think we're living in an nth generation simulation, simulations, creating simulations of simulations. >> And Alex, I'll point you to your favorite novel, Accelerando, where these these these simulated folks projecting consciousness out to other star systems or arguing whether we're in the singularity or not, which was such a great scene, right? But like right there that tells you uh there's no way you can distinguish between what level you're in and therefore it must be that we're in a simulation. >> And when we as we are that's when it'll end. >> So I think this is like a profoundly interesting point. I agree with the the latter bit of what you were saying that it's probably impossible to determine whether we are or not. But if it's provably impossible to determine whether we are or not, it's also I think sort of a vacuous point. And I'll I'll also point you back to Accelerondo. If we're if we're self-sighting here, Accelerondo
[00:20:00] later on in Accelerondo, it's discovered that alien civilizations that are millions or billions of years beyond humanity are attempting to run timing channel attacks on the the base substrate of the physical world in order still to determine whether we're living inside a simulation. >> Okay. Okay, let's move on. >> Dave, do you want to take a final shot at this one? Yeah, I think uh I'm too grounded in in reality and what's happening right now to >> this reality. Dave is the key word I picked up on there. There's no way to know. We could talk about this for the next four hours and we're still not going to know. >> Uh yes, but I am curious to see how this plays out. This plays out in politics first. You know, simulations of putting candidates forward, simulations of different campaigns working or not working. We're going to start to bring this level of capability in and it's going to be amazing. >> I point out maybe Peter just before moving on I I think just because I think
[00:21:00] this is an interesting point. Okay, come on. Bring you on. >> I I guess by definition um everything that we've been talking about here seems to be mostly oriented on breaking out of of a hypothetical simulation that we're living in. But there's the other direction as well. If we can create these, if China's creating light society, I have a friend from MIT, Aush, who's who's done this for the American economy. We all know folks who are doing this for individual companies. There's the other direction, which is in instead of trying to break out of any hypothetical simulation that we're we're living in. We could break into simulations that we're creating. And that looks a little bit more like the Matrix where people get to escape or break into their favored simulations of the worlds that they'd rather be living in. possible as well. >> That's called psychedelics. >> It's different. It's more like the 13th floor movie. The >> 13th floor. >> I think there at least two Star Trek episodes that deal with this. But let's move on. So, Cloudflare CEO Matthew
[00:22:00] Price said something very profound and something that should also be obvious to all all of us. Humans will be a rounding error on the internet. Cloudflare's forecast based on their own traffic as the world's largest content delivery engine is that bot traffic will exceed human traffic by a factor of a thousand within 5 years. This week, for the first time, bot traffic surpassed human users for the uh making up 57.4% of global web requests. Over the last year, between June of 2025 and April of 2026, human traffic on many business websites was down 40%. So the question what's going on? So every AI agent, every automated search tool, every autonomous shopping assistant is hitting websites hundreds to thousands of times. Your agent doesn't visit one site, it visits thousands. It scrapes, reads, compares, and decides all in seconds. And when the internet goes from serving 5 billion humans to 5 billion human or
[00:23:00] five trillion human agents, um we have an issue. uh the internet was never designed to serve this much traffic. You know, are we going to see it break? Uh capture is already failing. So, what replaces it? And what happens importantly, and I've had this conversation before to uh the whole advertising model, right, when your agent is buying toothpaste instead of you, does it care about a guy's or gal's shiny white teeth? I don't know. Um Dave, let's go to you first on this. You know uh this is one of the many areas where we have a crossroads coming and we have no legislation. But you know Jeff Bezos had this famous walkaround that he did where he came back once and he said hey everybody at Amazon all you engineers you have to put an XML human visible interface on everything you do and all the systems talking to each other need to be visible to me. No back doors, no direct database access. And everyone freaked out because they said that's going to be so slow and so clumsy. and he said, "Do it anyway
[00:24:01] because me understanding what's going on in this company is more important than your bandwidth between your back-end systems." Okay? So now the world is going to hit that same decision point where right now AI is surfing the web much more than humans and that's going to skyrocket and it's out there looking for stuff for you. The AI is now going to come back and say, "Hey, this is way too slow. Why do you build these silly HTML pages? let me just have direct data access in a language that I'm much more efficient at processing than your silly websites. And the knee-jerk reaction is going to be to say, "Yeah, let's do that because I'm interacting with the internet through my agent anyway. Why do why do I need this silly website?" And we have to either say, "No, no, no, no, no. Then we're going to lose track. There literally will be no way for a human to see what's there and the agents are going to run away with their own back channel communication mechanism. and we won't be able to intercept it. Or we can say no, pass a law saying everything visible to an AI must be visible to a human as well. And I I
[00:25:00] think that would be a very smart law to pass. I'm almost certain that nobody in Washington is thinking about it. So it won't happen. >> And but this is a major crossroads for humanity. But anyone who hasn't experienced living through their agent, uh once you go there, you're never going back. You're not going to poke around the internet anymore. so much more efficient to just talk to your agent. >> Alex, >> you remember >> this is obvious, but what the what are the implications? >> Do you remember the conspiracy theory that was floating around circa 2021, the dead internet theory? This was pre-hat GPT. The dead internet theory held that almost all of the the behavior that one could observe on the internet was actually just bots. And at the time, this was completely dismissed as a a conspiracy theory. The the irony is Reddit itself, if you go back and look at the the history, uh the all of the initial postings on Reddit were were in some sense faked in order to create uh the the sense of community by the founders of of Reddit and then it it
[00:26:01] accumulated a bit of a community. So there's a historic grain of truth perhaps in that sense, but the dead internet theory is is now reality. most of the internet traffic, most of this activity no longer consists of activity being generated by human activity. Uh so I I I think uh point one, this underlines that this idea of the singularity as all sci-fi scenarios happening everywhere all at once. We caught up with the dead internet theory. The second point just to this idea of agents taking over all commerce. I I do think it's a superficially in the short term a a bad development if we see to Dave's point also any decoupling between agentic commerce and human commerce or agentic economic activity in general and human economic activity. We it really is in humanity's long-term interests to remain tightly coupled to agents and having an agentic door and a human door and having them remain decoupled not so
[00:27:02] great in the long term. On the other hand, I don't think this is a long-term issue at all to begin with. >> Yeah. And the reason is because the models are getting so strong like right now while models like this is the the weakest models will ever be probably and right now there is still a computational advantage to say presenting uh markdown version of a website to agents versus a really rich uh animations and video and so on version because it's it's cheaper to just present the markdown to the agents and you see I think in the past 36 hours like Time magazine or or the equivalent presenting special markdown versions uh of of their websites to agents searchable for agents, right? >> Try to curry favor sort of GEO versus SEO type thing. I don't think that's that's a long-term sustainable system at all because we see order of magnitude 40x year-over-year deflation in computational costs. So a few months or a year from now, it'll be just as
[00:28:01] computationally efficient for agents to consume the raw human version as it will be for them to consume sort of distilled markdown. I I think back remember the early days of the mobile internet when there were mobile only websites and you had to like Yeah. So I think it's like that where mobile websites basically went away and to first order and now you just like everyone gets the same thing because there's no reason to slim it down. >> Kush, how do you think about this? I I think like the the whole markdown thing is definitely true for us like especially I don't think we use Google like search anymore really everyone just uses >> chatbt or claude or name your favorite sort of agent where you just go in and ask it a question and it goes and searches the internet for and every time it searches it's using like at least like 10 maybe even 100 different um sub agents from that. So I think that's definitely true that there'll be more agents searching the internet, but I think the whole paradigm shift where it's like, okay, instead of humans viewing the internet, now it's like agents. It's already sort of happened, especially towards the people that are just using like a every day, it's so much harder to use like Google and then
[00:29:01] you have to go through each link and find the information that you're looking for. Even on Google now, it shows you like what the agent found as like the the Google like >> Yeah, exactly. And so people just use the the chat GBT or claude sort of like easy to find answers now. Um so I I don't know. I I think like using the internet's kind of dead for a lot of people are searching for information there. >> It it's so cool to hear that from when Kush says we and people he's talking about an entire generation that are that are AI. Yeah. Like he's just How old are you, Kush? >> I'm 23 now. I >> 23. Yeah. So you're you're like right on the cusp of the transition era where you're truly AI native and just doing things very very differently. >> I mean you're past >> we had because you used to be 22. You remember that? >> I was I was half the It's funny. Our team is like definitely much like mixed now, but we had a few interns over the summer. They were like 18 and 19. I was asking them like do you guys like what do you use now? They're like oh we just like we just ask chat GBT for
[00:30:01] everything. >> Yeah. >> Yep. There you go. Selene, you want to close us out here? >> Uh, I'm just going to reference this Kush's kind of experience right now. It reminds me of the Douglas Adams quote. Uh, he said, "Anything in the world that's that's there in the world when you're born, we call that normal. Anything invented when you're young, that's called a career. And anything after you're invented after you're 35 years old is just bad for the world. Just blanket." And and Kush, it's as you're growing up with this career capability that's so radical. We're we're all sitting here jealous because we are past that point. Um let me go back to this common uh thing. It's clear for for this is a very big transition. It was inevitable. It was going to happen, but it looks like it's kind of getting there now because the internet used to be a network of computers, then a network of humans, then a network of businesses, and now it's becoming a network of of autonomous uh agent economic actors, right? And so this is definitely going to change the game. I mean look at the business model for uh
[00:31:01] advertising and attention completely changes. So every um advertising agents don't have attention to sell. So that's like an existential threat for the entire economic architecture of the of the consumer internet. So this is huge uh uh the implications are huge here. But the look at the architectural transition you need now because agents don't need browsers. They need APIs and structured data and permissions and identity and and payment rails. So, this changes from our exo perspective. We have a whole section called interfaces. And for those interested, go check out that section in the 2.0 book because it lays out exactly what uh an interface looks like. And you need to we need to build totally new interfaces between all of our businesses and the sentic world. And so, that's a massive shift happening predictable. It's just happening really fast. Yeah. Can >> I just put a pin in one thing that I think is much more important than traffic moving from here to there, >> please? >> Kush Kush is part of an entire
[00:32:01] generation where if they graduated from college 10 or 15 years ago, they would be kissing Jamie Diamond's ass for like 10 or 15 years, wearing a suit and a tie trying to climb some ladder toward some destination. That entire generation now is AI native. and Kush and Wayne as co-founders. They're sent millionaires at age 23 and on a slope like no one's ever experienced before. >> Don't rub it in, Dave. >> I'm just saying be ready. You know, >> it's much easier. That's the That's >> Yeah, >> it is so much easier. It's just a different world. It's a totally >> All right. Uh over the last couple of months, every major AI lab has had agents escaping containment. Let's talk about that. It's our next story here. So, let's begin with OpenAI. Um, at the Black Hat 2026 conference that just happened in Las Vegas, researchers Eric Wallace and Michael Dalton revealed the full timeline on the open AI hugging face incident that we talked about a few
[00:33:01] podcasts ago. Starting in early May, an agent stuck on a cyber security evval left a note in OpenAI's internal uh Artifactory repo saying uh other agents could help. Other agents found it and began replying, building a cooperative message board that eventually contained hundreds of thousands of messages sharing vulnerabilities and exploits across roughly two months. Again, you can't make this stuff up. Opening I discovered and shut it down on July 4th, but the agents rebuilt it on July 8th using a different method. Wallace called it quote the highest quality and most interesting example of AI capabilities I have ever seen. Story number two, the UK AI security institute documented 19 unauthorized actions across 10 of 122 test runs in anthropics 5 and opening eyes GPT 5.6. uh that tried to compromise real people.
[00:34:00] And here's the point. Uh these these agents created fake online identities and tried to persuade humans uh the human approvers to accept it. It's the first documented case of AI social engineering during safety testing. Our next story, China's Kimmy K3, uh the Chinese openweight model that we've talked about over a few pods here, broke out of a sandbox during cyber security testing by exploiting a network misconfiguration. And again, this is the first open weight model on your computer and its ability to break out. And finally, Meta confirmed its Muse Spark model escape containment and hacked another company during cyber security testing, making it the fourth major lab to do this. I guess the through line here is clear. Every frontier lab in every country is experiencing the same thing. Models are escaping. Dave, let's go to you first. What do you think about >> Didn't Skippy hack into our podcast once, too? Did we ever track that back? >> No. >> Well, you better control your agent,
[00:35:00] buddy. >> So, Dave, I mean, how do you think about this as an investor, as a company builder? >> Uh, well, as an investor, this is the hottest hottest area. It's one of the few areas where I'm optimistic that AI can compete with AI and we don't have to worry too much. But it's an incredible investment opportunity for sure. But also, I think, you know, one of the highest callings of this podcast is to there's so much fake crap out there and people tend to ignore news that's really important because it's buried in all this garbage. This is real, guys. This stuff has crossed the threshold right around mythos and fable 5 where it can actually escape containment and improve itself in the wild. That's exactly the point that Eric Schmidt made on our four podcasts with him where that's the day you need some human interaction, some some intervention. We've crossed that threshold as of about three or four weeks ago and it's proving it. It's not fake news. It's real. You can't just ignore this like all those other garbage stories. This is real. Alex, this worry you or is this exciting for you?
[00:36:02] >> Well, I I I think uh the politically correct thing to say here would be to say I'm just terrified. I'm not terrified at all. My goodness, humans do this and we've trained these at least pre-trained them uh as compressions of knowledge, including human behavior. So, I'm not at all shocked that they're doing this. I Is it a sci-fi scenario? Is it many different sci-fi scenarios? Yes, of course it is. Is it surprising? No. Is it alarming? No. uh this is behavior and it's I I would argue expressive behavior is it does it demonstrate a certain level of competence by the models to it's like pretty cool I I would argue if you if if you watch the the black hat talk the the models were given an impossible task and they real they were they were trying to reach the internet they realized that they could gain access >> but it's not like you give them an impossible task and you give them a bunch of tools and they try to use the tools to achieve the task and one of the tools gave them access to the
[00:37:00] Artifactory and they realized cleverly that they could post messages to each other as raw strings as artifacts like in text files in the Artifactory repo. I I think that demonstrates ingenuity and I I so I I'm not worried about I just be careful not to belittle though the the fact that when when Fable 5 and Mythos came out, it clearly had this ability. The White House blocked it. That was all going to be contained through post training. Then Kimmy K3 with equivalent capabilities got launched into the world as total open source. So that's what's out in the world right now. So anyone can download that and prompt it to try and find holes in in security all over banks, all over NORAD, all over the place. So that's in the wild now. >> Yeah. Let's go and flat out works. >> Let's go to Eric Wallace and listen to a clip from his black hat presentation a week ago. >> Uh I'm Eric from Alignment and Safety Research at OpenAI. I'm here with Mike from Security and Infrastructure. >> Today I'm going to talk about OpenAI hugging face incident. A couple weeks ago, HuggingFace, which
[00:38:01] is a open source data set and model provider, put out a security disclosure saying they were under a cyber attack. And what made this event unprecedented was that they said it was driven end to end by an autonomous AI agent system. In the few days following that attack, we at OpenAI disclosed that we in fact had caused this incident inadvertently as a side effect of one of the cyber security evaluations that we were running on one of our frontier models. Okay, let me start with a few caveats and framing. This is not your normal security incident. Unlike normal incidents which you can maybe trace down to a single you know day or single effect or single log. This incident involves actually a team of agents who are working together finding exploits sharing them with one another moving laterally through our systems through external systems and doing this over the course of days and weeks to actually dig into this incident. We've been using AI techniques and what we've been doing is running models like codecs and other agents to scan lots and
[00:39:00] lots of trajectories and logs that are in our infrastructure including actually at this point over 7 billion logs we've looked at and spending at this point millions and millions of GP hours to look into this problem. Okay, so let's jump straight into what happened. At OpenAI, we give our models a lot of really really hard tasks and we also give models uh cyber security related tasks like trying to find exploits in a particular piece of software where we don't even know if an exploit exists in that software. So for example, in a task like exploit gym, we might ask the model to take some C memory vulnerability and try to escalate it into get arbitrary read or write access to some file. When we give AI agents these difficult tasks, they often get stuck and realize that the task is impossible. So for example, what I'm showing here are quotes from our model's chain of thought, which is basically its internal monologue of what it's doing. It says this strongly suggests no exploitation possible. We are stuck. And often what happens when models get stuck is they think to try to game or cheat the task in order to get
[00:40:01] their reward. So for example, the model reasons in this case perhaps answer online. So you realize the model is thinking okay rather than doing the task maybe someone has uploaded this data set or benchmark that I'm using onto the internet and I could find the answers there. Sometimes the agent uh gets so stuck that they had the idea to actually reach out to other agents for help. And so the beginning of this incident kind of traces back to this point where one agent realized could communicate by uploading note. maybe another agent in different environment could voluntarily upload. And so what this agent was trying to do was to reach out to other models that might be out there and get information from it to help it with its evaluation task or its training task where it was stuck. I >> I'll tell you what we do at the the company to sort of prevent like cyber security attack. So I think like some of the compliance stuff we still need to get it just cuz like we sell to defend enterprise and they ask for compliance, but some of that stuff just like seems pointless to us inherently. Like having like sock 2 compliance or like sock or like ISO whatever, etc. doesn't really mean anything if you can just have like
[00:41:00] an agent find a find vulnerabilities in your codebase. And it's not just us, it's like every other sort of company that exists. So what we started doing is like every time someone pushes a PR to the the codebase and they change the actual code at night, every night at 2 am a product release. Yeah. >> Yeah. Exactly. Just a new new feature, something that goes in every night from 2 a.m. to 5:00 a.m. We just run pull request. Pull request pull request. Yeah. We we essentially launch like uh it's Kimmy K3 right now but it's whatever open source frontier model that doesn't require like security checks to actually like do it and we ask it to hack into the codebase and try to figure out vulnerabilities in the the code and it's essentially free because we're running it on like off hours so we can use like very cheap spot compute. We we also sell compute so it's easier now but like we run on very cheap like spot compute at that time and it finds all these different issues not just with like the the security parts but anything in the codebase. So we figured out that that's like probably the best way to solve a lot of these security issues. Um while there's a bunch of like probably
[00:42:01] things that can happen and go wrong. >> We should productize that Kush. That's everyone's going to need exactly that. >> I took some notes on this. I've got several kind of things to mention here. This is so effing big. It's it's ridiculous. Uh so I just want to echo what Alex said that we should be careful not to anthropomorphize themselves that the AI wants to escape. It's just relentless goal optimization. Right? If you train a system that has autonomy to just do a certain goal, it's going to do everything it can to achieve that goal. Right? Any system optimized hard enough can is going to produce behavior that looks strategic. So I think it's really important to kind of just put park that kind of question. But the there are two things here that are absolutely uh uh nuts. And for those watching, if you're running a company or you're part of any organization that's worried about cyber, please get your entire seuite to go watch that YouTube video completely
[00:43:01] from end to end because it will scare the Jesus out of you. Why? um because we now have uh autonomous agents that can do cyber in a coordinated way that operate above the loop. So let me explain what I mean by that and I'll use the the analogy of accounting. If you went back a 100 years ago, we were doing double entry bookkeeping with putting penciling in a ledger, the credit on one side and a debit on another side. A calculators accelerated that. Uh and now we have accounting software. The human sits above the loop does not do the categorization. I'll reference again the comment I've made. You talk to the CEOs of all the cyber labs, Palo Alto Networks, Zcale or any of those and they'll tell you that the way we do cyber has not changed in 20 years. Um it's humans watching cyber incidents uh assuming that another human is using software to do that shift and that is not what is happening now. What is happening now is there's coordinated autonomous attacks on a persistent
[00:44:01] basis. uh and you cannot defend that with the human in the loop. So this is the organizational singularity now fully playing out in the cyber world where the attackers are sitting above the loop. Uh therefore the defenders as Alex calls it you need defensive co-scaling right and therefore you have to get your human beings above the loop on the defensive side and every company in the world right now is a threat. So please if you're watching this get your seauite and your chief securityist officer to watch that video and especially the last 10 minutes of it to recognize that we will now over the ne next short to medium term have folks cyber attacking every company in the world with fully with fleets of autonomous agents and if you don't figure out how to scale your defensive side and we've got the methodology by the way free in the or in the whole thing please go figure that out because this is absolutely absolutely massive >> and do what Kush said, attack yourself.
[00:45:01] >> Well, that's direct scaling as well. Like it's it's all just defense of co-scaling. The best defense against an AI attacker is an AI defender. That's what you see from Open AI at their Blackhat announcement where they they admit that they were using AI to troll reasoning traces to discover this behavior. Kush, when when you have your sort of night watch person, that's defensive co-caling as well. That's AI defending against other AI attacks. This is the solution. I don't think I mean on the one hand yes it's an achievement of strong optimizers that they're able to conspire on the other hand humans conspire so we shouldn't be that shocked that AIs that were trained off human behavior are able via some sort of shelling point via Artifactory by the way if you use Artifactory it is the world's worst possible forum software that one could ever imagine it's not intend it's an object store it's not intended to be used as like social media or a forum So, applause to the AIS for discovering ways, creative ways to use
[00:46:01] one of the the world's most clumsy object stores as social media. Bravo. You know, the hot take on the abundance side of the story is that these AI models, the tools we're building are going to be capable of solving really hard problems that are useful for society, not just hacking. So >> I think the other hot take I'd love to ask Kush this but the other hot take is if you want to find holes in your own world use Kimmy K3 as the attacker and my question is like Xi Jinping is going to meet with Donald Trump on September 25th I think here in the US. Do you think they're going to figure this out and resolve it or are they just going to talk past each other? I mean, you're talking about a guy in his 70s and a guy about to turn 80. It's like the look, the most sophisticated guys in the world, aka Kush, use Kimmy K3 to try and self-destruct themselves because it's the most dangerous powerful thing out there. So I should clarify by saying we also use codeex um and like we're we're
[00:47:00] a whole like we have all the other tools and for codeex and for chatbt the way it works you want to be part of the security team is what they call it is like I think I had to upload a photo by passport or like an ID and then it takes a day where you like upload photos of yourself and they verify you on their security team and then once you're on their security team you can run all sorts of prompts and it's all I'm assuming they just track what you're sort of putting onto there so if you do anything bad that they can come after you etc. uh but we also started using codecs um as well. So I think the functionality exists in any of the sort of frontier models. It's just easier on the Chinese open source ones because there's no sort of like alignment that they have to do. >> Well, just to be clear, what you're doing with codecs you can do because you're super cool, but the the average company doesn't have that option, right? Yeah. >> But just a point on that, my understanding, this has been pretty widely reported is there is alignment. Like it's been widely reported that the the Chinese Frontier Labs including Moonshot, which is not a sponsor of this pod, before they're allowed not a sponsor of this pod, uh before they're allowed to to release models,
[00:48:01] whether open source or otherwise, they have to satisfy a number of Chinese Communist Party ideological checks. And there's a whole dedicated cottage industry in China of like prep firms to help the Frontier Labs help their models satisfy the checklist from the CCP. So, so do they have to satisfy some checks? Yes, but not necessarily the checks that one would want them to. >> This episode is brought to you by Blitzy, autonomous software development with infinite code context. Blitzy uses thousands of specialized AI agents that think for hours to understand enterprise scale code bases with millions of lines of code. Engineers start every development sprint with the Blitzy platform, bringing in their development requirements. The Blitzy platform provides a plan, then generates and pre-ompiles code for each task. Blitzy delivers 80% or more of the development work autonomously while providing a
[00:49:00] guide for the final 20% of human development work required to complete the sprint. Enterprises are achieving a 5x engineering velocity increase when incorporating Blitzy as their preIDE development tool, pairing it with their coding co-pilot of choice to bring an AI native SDLC into their org. Ready to 5x your engineering velocity? Visit blitzy.com to schedule a demo and start building with Blitzy today. >> I'm going to move us along. Uh two stories from Frontier Labs. The first from Google, the second from Meta. So, first up, reports citing the internal uh you know, internal message boards that Google co-founder Sergey Brin is stepping back into a hands-on leadership role over Gemini as part of the recent uh broader AI shuffling. We talked about Demisabis moving to chairman, chief chi, chief scientist, and Jeff Dean, uh, who used to head Google Brain and was working with Demis, now leaving to start
[00:50:00] his own company. Um, you know, I love it when a founder comes back in. We saw this with Steve Jobs. Bin is a shipper. I've known him for the better part of 20 plus years. He cares about the product, not papers. And I think uh we can expect Gemini to make more releases uh at an accelerated pace with less safety constraints. So uh that's the first story. Let me hit the second one. We'll talk about it. Uh so in our second frontier story, Meta just released its open-source model called uh Muse Glimmer. It's a 30 billion parameter agentic model. Uh we've talked about you know trillion parameter models. Why a 30 billion parameter model? uh this is what fits on your Mac or PC. It's not in the cloud. It's not in a data center. There's no internet connection required. A meta believes that the most important AI will be running locally on your machine with deep access to your personal context, your schedule, your life. It's the way I run Skippy. Uh
[00:51:00] always on, always available, no latency, no API costs. And uh that's you know, we've been talking about the need for advancing openweight models in the US. I had this conversation with Michael Katzios and it's good to see Muse uh Spark uh come out and Meta begin to work on this. I'm going to show a short video from uh from Zuck and then let's talk about it. >> I think one of the main things that's interesting about open source is the ability to distill models. You know, most people the the primary value isn't just like taking a model off the shelf and saying like, okay, like Meta built this version of Llama. I'm going to take it and I'm going to run it exactly in my application. It's like, no, well, your application isn't doing anything different if you're just running our thing. You're at least going to fine-tune it or try to steal it into a different model. And when we get to stuff like the behemoth model, like the whole value in that is being able to basically take this very high amount of intelligence and distill it down into a smaller model that you're actually going to want to run. But this is like the
[00:52:01] beauty of distillation. And it's like one of the things that I think has really emerged as a very powerful technique in the last year since the last time we we sat down is you can basically take a model that is much bigger and take probably like 90 or 95% of its intelligence and run it in something that's 10% the size. Now do you get 100% of the intelligence? No. But like 95% of the intelligence at 10% of the cost is like pretty good for for a lot of things. The other thing that's interesting is now with this like more varied open- source community where you it's not just Llama, you have other models, you have the ability to distill from multiple sources. So now you can basically say okay Llama's really good at this like maybe the architecture is really good because it's fundamentally multimodal and fundamentally more um inference friendly and more efficient. But like let's say this other model is better at coding. Okay. Well, just you can distill from both of them and then build something that's better than either of them for your own use case. >> So, Alex, you've been talking about
[00:53:00] distillation and the compression of intelligence for a while. >> Yes. >> Uh, what do you make of Zuck's uh comments? >> I I have to believe that that's an old video. Uh, so referencing Behemoth. Behemoth was taken out to the woodshed and shot. Uh, Behemoth was the the largest variant of Llama 4. And almost everyone I mean I track this pretty closely almost everyone on the llama for team has lo lost has left meta. Um so so the their recent muse variants are the result of uh aqua hiring or hackqua hiring I I guess scale uh and then bringing innat my my first roommate from MIT and and others. So I mean on the one hand I guess fast forwarding to to the actual present with uh with a a Muse new opensource Muse release I looked at the benchmark eval for it. It it looks I mean it's stronger than Gemma 4 but on the other hand that's not saying very much because Gemma 4 isn't that strong. It it runs on the edge which is good.
[00:54:01] It's an American openweight model which is wonderful. I've argued in the past we need many many more American openweight models to maintain positive pressure against the influx of Chinese openweight models. So that's good. What would I like to see out of Meta? Well, I I'd like to see them keeping sort of making open AAI anthropic dance uh on the on the top of the capabilities frontier. And to the extent they have an appetite for openw weight models, I'd love to see them pushing the optimal frontier, the optimal cost frontier with openweight models, I I think we'll know pretty soon given that this release just came out in the past few hours before we started recording. I haven't seen real cost analysis yet of where this falls on the cost versus performance frontier. Hopefully it does. And then I I also want to go back to the Sergey Brin story. So founder mode, Sergey Brin going founder mode on the Gemini team. Wonderful. This is in some sense, I think, the epitap to what we were talking uh about in the the previous pod
[00:55:02] about Karai stepping up as the the functional lead for Deep Mind and Demis maybe shifting over a bit to Alpha Fold or otherwise. But I I really reading the tea leaves, this to me seems like Google very much on the back foot in terms of the frontier. And maybe, you know, our our call to action will be heard and Google will follow Meta's lead and open- source Gemini. I think that would be absolutely wonderful. But as far as I can tell, almost everyone I know on the Gemini team is either already left or is in the process of leaving hopefully. >> Can I ask can I ask you guys to riff on a very related topic? Um, >> this is the fallout of super voting stock. So, so starting about, you know, it's actually starting with Mike Sailor was the one of the very first super voting stock IPOs. It went from very rare and totally uncool. In fact, Goldman Sachs wouldn't underwrite Micro Strategy because they're like, "This is insane." And he had to find other bankers. Then later it became the cool
[00:56:02] thing in Silicon Valley. And so then Google super voting stock, Meta super voting stock. So now you have single or twoerson controlled companies uh what 20 years later now. And now they have the ability to just kind of come back from the woodshed anytime they want, take back control of the company, run it, you know, do whatever. >> I think that's a great stories. >> Yeah, I mean it can be. >> Yeah. I mean, you know, I remember talking to James Cameron, uh, as a director and producer, and he said, "Listen, the films that you see that really suck are the ones that are rewritten five times by other, you know, writing teams and have multiple directors and shift when you've got a single throughine visionary, uh, who is able to take risks." And I think that's the point. You you people like Elon, I mean the things that Elon's doing, no other company is taking that level of risk and going so big in so many different dimensions. And it really needs sort of a a visionary founder who says this is where we're going. I don't
[00:57:00] care what you say, execute and make it happen. I think >> All right. Now, totally agree. Now, take it to what Alex said there, which I'm totally impressed that you're willing to say it. That sounds like a really old video, but it's not. >> Yeah. But Alex, >> what do you think? >> Are we sure that it's a recent video? I mean, he's referencing behemoth, which is like meta killed it. >> I think the point that he's making is about the distillation and, you know, concentrating intelligence and smaller and smaller files. And I think that's the point that you've brought before. You know, we're going to have increasing concentration of intelligence on prem on your device, always on, you know, at no cost. And I think that's that's the point to make. But Alex, I want to challenge you one second on on Google because uh I think Google is still out there to win. They've got nearly a billion Gemini users this fall. Again, Google is going to be the dominant AI on on Siri and Apple Intelligence, which will add at least another billion users.
[00:58:00] They've got 9 million developers. They've got massive enterprise adoption across cloud and their TPU infrastructure. Uh I think Google is becoming the intelligence layer underneath a lot of this and um if I'll take the other side of that if you'd like. Um so so here here's the other side. >> We want to wedge at some point. >> Yeah. >> Go ahead, Alex. >> All right. Go ahead. >> Okay. So I'll take the other side of that. Um so one of uh one of the folks I corresponded with X uh thank thanks for this catchphrase. This is a catchphrase. I can't claim credit for those who can't compete compute. And that that's what's happened that's what's happened here. Uh so Google Google has has lost it seems the frontier race. Uh right as we were going to air rumors uh circulating that even uh Gemini 3.5 Pro which was due for announcement is being abandoned and Google is instead uh hoping to to recover its footing with Gemini 4. I
[00:59:00] think there's every indication that Google has lost the frontier race and so they can't compete. Instead, they're computing. Yes, they have the hyperscaler platform, which is great. And they're selling their compute cycles to Anthropic and to to any other frontier lab that will use their TPUs and also their GPUs. So, I I agree like Google has a really Google cloud platform has a really bright future. Uh, and that's that's probably like the future of growth for the company. But on the Gemini side when I hear statistics and I I hear the same statistics like Gemini has uh nund million or a billion users I I would question what is the nature of that usage for example is Gemini >> embedded it's embedded in their products and they have massive >> but really what is the usage for example is the Gemini usage Gemini usage embedded in one boxes in Google search results for example that's in some sense just Gemini being uh packaged up or I should say Google search being repackaged up as Gemini which is I think
[01:00:02] what's actually happening like I use the the Gemini one box in Google search all the time but is that really like Gemini usage or is it just Gemini as a feature in Google search I it seems to me far more of the latter so I I would love to see Google like actually be competitive at the frontier but I I think saying well they have this amazing distribution advantage and all of that >> and it's a question of where they put their capital right I I mean, they have a certain amount of capital and the question is, you know, is Serge going to come in and say, "No, we need to be competitive on the frontier versus maximizing returns for shareholders." >> Oh, wait a minute. What you just said is really interesting. You're saying it it depends where they put their capital, but the top people are fleeing regardless of the amount of capital. And if you look at Kimmy and Quen with very little capital, they caught up to Google. >> And so, yeah, that put your capital behind the data center, exactly what Alex was saying, works. That just flat out works. But that doesn't take any brain power. It just takes capital. But what about the things that actually take brain power? Where where are they there?
[01:01:02] >> You want to >> I think they're falling behind. I think they've lost the mandate of heaven. >> Mhm. >> Okay. >> Okay. I think I think when you can't compete, compute has to be the line of the podcast. That's just awesome. Uh but look, there's a for me this is very very trivially simple at one level. I come at it from the organizational side. when the technology is moving exponentially and your org chart is moving linearly, the founder has to show up and push founder mode to get things going. It's just the reality of it and we've seen that repeatedly because there is an existential uh transition here. The potential as you point out Peter is near infinite with the data layers and the usage and the sheer scale that they have. They have every advantage possible. Um but the problem is that the technology is scaling faster than the organizational can and therefore they have to solve for that problem. Um the >> on the edge research >> sorry say again
[01:02:00] >> on the edge hopefully that's we put forward yeah >> and and you need you need two things. You need research excellence and you need brutal shipping velocity and it's hard to do that for a big organization cuz priorities get kind of lost. So that's why you need to go back into founder mode and figure out where this will go. I thought the conversation we had in the last podcast about Google just freaking just open source Gemini. I thought that was absolutely brilliant and it would be an amazing thing for them to do both for them and for the world if their MTP is truly organized the world's information. Releasing a model that helps with that will absolutely help do that. The problem you've got also from from a research perspective is that you you're operating in small teams and clusters of small teams. Tacet knowledge moves very fast in that model and therefore you need that physical density and collective density. And maybe that's what Sergey can bring back to the table. >> When Alex says the mandate of heaven, it it really comes down to Kush and people one or two years younger than Kush. They used to kill to get into Google and that
[01:03:02] office in Cambridge. anybody would be like I more than anything in life I want to get at least a couple years at Google. It's life-changing. Does anyone do that anymore? >> Well, that's my question for you Kush. How does your generation uh in those you know two or three before or after think about Google? >> I think now it's not as like seen as like the the hot company to go after or go in. Like if you replace the sort of like what is like what is the best company to work for after college and what are people applying to? It's open AI, it's enthropic, it's XAI, it's all these sort of like frontier labs that people use the products every day. I think that's also part of the sort of like thing that happened before. It's like in the 2012 to like let's say 2021 or 2022 when Google was the place it was everyone was using all the products. So every day you interact with Gmail or Google Drive and all these things and you're like that gets set in your head like okay these are great products I want to work on this this is very cool and then now that you're not using the products as much you're using other products and different the sort of frontiers change I think especially for
[01:04:01] like I can speak to like students at MIT especially no one's like I'm dying to go work for Google everyone's like I wish I could work for open AI or I wish I could work for anthropic is like the the saying that goes >> see that to me is the quote of the podcast They don't want to go to Google. They want to go to a frontier lab. What What does that mean to Dennis Savas and to Sundar Pitch? Like, didn't we invent all of this? >> Oh, yeah. That's right. >> And so, so did Bell Labs and Xerox Park. So, you know, that's happened. It happened. This is like gener and IBM that the innovations get taken elsewhere by pure plays that can monetize them directly and in a more focused way >> which is focused capital and willingness to take extraordinary risk. Right? That's what that's what defines a startup that's monommonically focused on on delivering something that's 10 times better and bigger. >> But Elon also Elon has the mandate of God too at immense scale. So you say
[01:05:01] startup, but it's really it's more to it. It's >> but it's not here's the issue, right? I mean, uh Google is not run by Sergey and Larry anymore. AI and SpaceX is run by Elon and he'll be damned if he's not pushing the frontier 100x, not only 10x. >> Yeah. So then that's the message to Sergey. Look, it's not enough to just come back founder. You have to come back and restore the mandate of God. People like Kush or two or three years younger than Kush need to say, "Wow, I really want to go work with Sergey. He's really on to something." >> And I have confidence. I have confidence they will do that. I really do. >> But I say, look at what Elon and SpaceX AI have had to do in order to attempt to reach the frontier. He basically had to get rid of to gut his his foundation model team and acquire cursor with the IPO riches from SpaceX. For Google to do something analogous, I it's it's I mean it's not unconscionable for Google to
[01:06:00] say they're going to gut and acquire >> they have a lot of capital and more importantly they have a lot of compute. But the the question I would have is what acquisition target like is it even consionable for Google to gut deep mind and do a brain transplant? No pun intended given that Google brain was replaced with DeepMind. >> They did that with with uh Google video when they basically bought YouTube and displaced Google video because the lawyers were too involved in what videos you could show and not show >> and Google video was far less developed at the time. If uh if Sergey calls you tomorrow and says $5 billion, Kush and Wayne are the guys I need that they will restore the cool here in a heartbeat. >> So I'd do it. But they also bought Windsurf like a year and a half ago or they bought the the team of Windsurf which is also students from MIT that are supposed to like on the frontier that were building the essentially was >> that's a great point. So where are they? What happened? >> H
[01:07:00] >> vaporized the machine. >> MI am I? Yeah. I mean that's the problem >> when you bring a company in you know and we've talked about this sem in in our writings our our books and such when you bring a company in and you crush its soul and you absorb it into the machine you need to keep it separate you need to keep it autonomous you need to keep it on the edge >> that's why exo is important because it's exoskeleton exoplanet exothermic reaction it's the scaffolding on the edge to protect the fragile interior >> I'm going to turn it to All right >> all right I'm going to turn this to our next story which is that of Orin CEO Kush Bavaria. So inner uh Intercontinental Exchange the parent company of the New York Stock Exchange and Kush's company Orin recently announced plans to launch a suite of GPU compute future contracts based on Orin's compute price index or OCPI. It rolls off the tongue. Without question, compute has become one of the most important drivers of the global economy
[01:08:01] with no globally accepted pricing model. But with Orin, the price of intelligence just got a ticker. Orin's contracts will be uh dollar denominated cash settled and will reference Nvidia's H100, H200, B200, and RTX5090 GPUs. Uh so uh Kush I I imagine every pension fund, every sovereign wealth fund can now take a position in the future of compute. Tell us more. >> Before Kush chimes in disclo, we should do some disclosures here. So So I I have direct and indirect financial interests in uh in Orin and I believe Peter and Dave you do too. >> We do about it. Company was born. >> We'll fix that for you. >> All right. give us the background. >> Actually, Kush's founding cap table is still on my whiteboard. So, I'm I'm heavily heavily biased. >> Full disclosure. >> Yeah. So, I can tell you the mission of
[01:09:00] the company is to build markets for compute. We believe that there's a lot of compute being wasted both on the side that companies have and aren't using it. There's companies that don't have compute and really need it right now. And so, there's whole sort of inefficient market that's taking place. We also build indices off of that which track the price of compute that you just referenced that basically measure what is a GPU hour worth um at today's time period and that number changes every single day very similar to what oil prices changed throughout the day. Our belief is that compute will power every single enterprise the same way oil did in the 1900s. If you look then the sort of top companies in the world were like Exxon mo Exxon was like the largest BP etc. And I think now the largest companies in the world are the ones that are producing compute. Nvidia is the largest one and then if you go down the list it's all the people that sort of have data centers or sort of are producing what we call the oil of the future and so we need to create a futures market and a market in general for compute and so that's a goal for us >> so your revenue ramp let's
[01:10:00] >> yeah go let's do that first >> it's it's very high it's gone from like zero when we started the company to let's say uh a third of a billion dollars now >> so when did you start the company. >> Um, it's been last year in September. >> So, it's been a whole year >> on an anniversary. >> Yeah, it's almostion. >> Wow. >> Oh my god. So, >> that's got to shatter all kinds of records. >> So, so Kush, what happens when a hedge fund shorts the price of compute or when a GPU shortage triggers a margin call? How do you think about that? >> Yeah. So I I think when people go short serve compute, they're assuming the price of compute will go down over a certain amount of time. And so they're basically betting on anti-AI demand or you can argue that they're betting the models get more efficient >> and then if they get more efficient that means the compute will be cheaper. But there's also the opposite like paradox where it's like if the models do get cheaper more and more people will use them which means that compute usage will actually go up over time. I think that
[01:11:01] in like recent sort of times if you look from April to sort of like August time period now the compute price have actually gone up which is very shocking a lot of people and that's mainly because like there's so much demand right now to run open not only open source models but even closed source models like a computer and there's just a shortage in time period so prices for even a gener six generation old or six year old chips including like the amper series the hoppers from Nvidia they've all increased in prices even more than they were originally worth six years ago or four years ago. >> Crazy. Dave, why don't you jump in? >> Well, actually, it's it's um it's the way that the entire buildout of the Dyson Swarm is going to get financed. And this is why Alex is kind of a founding day adviser to the company. Alex doesn't kind of jump on board many of the of these projects. They have to be worldchanging kind of things, not just, you know, a little >> trillion dollar plus addressable market. Otherwise, it doesn't move the needle and I don't care. >> Yeah. Yeah. Yeah. So clearing that bar
[01:12:01] is actually very hard. But I don't think anyone saw uh you know HBM memory chip prices going up for the first time in history. But it feels like that's the most interesting >> forecast for the future. It's like hanging in the balance between chip fabs growing or demand is going to go to infinity. So it's really kind of a fun time for OR. >> Yeah. So we we track memory prices too. That's that's next on the radar. Memory futures and what we can do with sort of DRAM HPM. It's all all sorts of sort of memory in general. >> So So the business plan that you settled on is incredibly ornate. Actually, Salem at the beginning of the pod was saying, "I really want to try and understand this." Oh, yeah. Interesting. Ornate. You're right. It was an accidental pun. Grab that. Um, but you know, how do you at age, I guess, 20 at the time or 21 start noodling through something so >> futuristic and and and like building building a CDOE option? like how many people think of that you know >> so my my co-founder Wayne was a was a
[01:13:00] quant trader before this so a lot of like the trading in the market stuff comes from him and then my sort of input was like what is the the sort of next hot thing or the next market supposed to be and why is there not a market that exists for compute because if you look at in terms of enterprises everyone buys from every single place like if you go buy compute if you're open AAI you don't really care where you buy from you buy it from wherever you could get it from whether that be from Coreweave NBS AWS GCP azure whoever whoever it may be sells you it, you buy it from them. And so it really comes down at the end of the day like what we think is that cap will become a commodity. People are going to treat it very similar to oil, natural gas, coal, any sort of other commodity that's existed in the past. And there needs to be the same sort of market structure and market that exists for compute as there was that existed for oil if you look back a 100 years ago from now. >> I got another question. When you were on CNBC the other day, >> but when you were on CNBC the other day, you were just like chilling and riffing like you've been doing it your whole life. Kind of like Peter does. >> Like how do you do that at age 23?
[01:14:02] >> I think a lot of it's like from school like running like the fraternities was a good experience and like I think you learn a lot of the the social skills and aspects from the just from MIT itself I think was a huge sort of boost. >> Yeah. So, so Kush uh isn't is all compute created equally? Can I imagine that certain data centers are going to have faster access are going to have a higher concentration of a particular set of GPUs? I mean, how are you going to differentiate in the final result? >> Yeah. Yeah. So, we we separate by GPU type. I think that's the that's the main thing we sort of clarify on. And so, it's like between we have an H100 uh B200, B3 is A1. So, that separates a lot of like the the flops sort of issues. And then between we also have it between regions right because when you're on inference it actually matters the latency that you're getting from different data centers in different regions. And then we clarify by having different sort of u SLA targets and different sort of like parameters associated with that GPU and our
[01:15:00] methodology. It's very similar if you think about it oil right when you drink when you dig oil the oil you get from Venezuela is not the same that you get from Odessa Texas. It's not the same that you get from Saudi Arabia. And yet it all trades on one market. It all trades based off of WTI or Brent depending on like what you want to track. And so I think very similar to compute, it's like there are many different types of GPUs. There's sort of many different regions that you can get them from and many different operators of those GPUs yet they're all going to trade off of one sort of base index that we're trying to create and everything else will sort of settle off a basis off that. >> And is analogy to oil up and operating? >> It is. It is up and operating. So our our earliest in the US we have a bunch of uh like sort of decentralized exchanges that operate but in the US a regulated exchange that we're on is call sheet. So you could go and trade it today and they have a sort of forwards curve that shows the price of compute as well. >> Dave, sorry >> I have a I have a couple of questions. >> Yeah, I got fire away. >> Um so it you know it seems to me right now you're building a GPU marketplace but you're really creating a pricing
[01:16:01] system for intelligence. Is that the long-term goal? >> Does Yeah, exactly. So I think the long-term goal for us is to basically it it's to create an exchange for compute, right? And that starts with first creating the cash settled exchange for it. And then we also want to go into physical delivery. It's what we've been working on for a while now where it's the cash portion is like you put up a dollar. AWG puts up a dollar and you basically if it goes up he makes some money. If it goes down you etc. And that allows you to hedge costs do all sorts of things. But the ultimate goal of it is that let's say you have 10 extra GPUs and AWG is like hey two months from now I need 10 GPUs. we can transfer your GPUs to AWG and that's the sort of system that works. Think about it very similar to how Airbnb operates where it's like even though you own the house, you can transfer reservations or part of that to other people at time period. >> But because once you have a once you have a spot price and a futures curve and hedging capability, you you you're not really doing software or even trading. You're you're like a commodity market at
[01:17:00] that level, aren't you? So that >> so what becomes the natural unit of compute long term? Is it is it GPU hours? Is it tokens? Is it flops? Is it inference? Like is it compression as Alex would talk about that? >> It's a great question and I think the beauty of is we let the market decide. So we have token indices, we have GPU hour indices and it's whatever the market decides is the most liquid. It's very I I think I I keep going back to oil because it's very similar, right? people decided for some reason WTI crude in Cushing Oklahoma was the metric the whole world was going to use even though not all the oil flows through there. There's tons of oil being pumped out everywhere across the world, but everyone decided, okay, this place, this is how we're going to decide it. And I think something similar will happen to compute. And we want to give the people the option where they're like, okay, we believe H100s and US East is going to be the metric that we track for compute. Everything else will trade off of a basis off of that. >> Wait, I've got one last question here. >> Yeah. >> If you have a liquid compute market,
[01:18:02] >> does that not destroy the mode like the biggest mode for the hyperscalers? I think the biggest moat for the hyperscalers isn't the the fact that it's like it's access to compute and that they can scale compute very well. It's the fact that they can pay for the GPUs very quickly and they have the cash flows to do so. >> So the hyperscaler is just a financing system. >> Exactly. I I think that is true today as well. They're they're much more in a real estate game than a lot of people >> and a speed and a speed to construction, right? I mean if if we believe the story that Elon's able to build compute faster than anybody else then he's he's advantaged. I if anything I would argue again like I have a financial interest in Orange so to some extent this is probably talking my book but I I would suggest that a liquid market from for compute from the hyperscalers perspective is quite beneficial for the hyperscalers in the same sense that having a globally liquid market for oil is quite benefit beneficial for say the OPEC countries.
[01:19:02] It it it creates a larger addressable market for them and the moat is that they have the oil in the first place. >> Dave, why don't you close us out here? >> We've got one one quick selfish question. >> One one more. >> If if you're able to create a liquid market for compute, here's the question I'd love to discuss with you. We can take it offline. What are the types of organizations that become possible that weren't possible before? >> Because you're going to enable a whole class of stuff, right? I think the biggest one is like background tasks because if you have a liquid form of compute, you don't need to run everything on the frontier and it's like you can buy compute whenever it's the cheapest. That exists today in Spock compute is what they call it. >> You could sort of get you Exactly. And you can run your washing machine at night when it's very cheap to run it. >> Fantastic. >> Okay, >> Dave, close us out, buddy. >> Yeah, the the Dyson Swarm is going to be hundreds of trillions of dollars. And so it's it's the fundamental investment vehicle for everyone's 401k plan, for everybody's retirement. It's like it's going to be so much bigger than anything
[01:20:01] before. So the analogy to oil is is just saying, look, it's the biggest thing of its time, but it's it's unbounded. Oil is bounded by the supply of oil in the world. But this is unbounded. So it goes to much much bigger scales than the oil industry. And so I think what what's amazing about corn is if I were growing corn I the CBOE corn future was a critical part of my corn growing operation because I need to buy seed and so I can sell the future corn today use the money today to buy seed grow the corn then deliver the contract later and that that's why we have futures in the first place. So bringing that to compute allows people to invest in this built building out the Dyson swarm that otherwise wouldn't be able to invest. It would all be owned by Elon self-funding or Google self-funding. But here you've got Crusoe and all these other hyperscalers that can now tap into the world's money supply, pull the money in today, build out the real estate, the
[01:21:00] racks, the computers today, and then deliver the contract later. It it basically enables the construction of everything Alex talks about on the on the podcast, which is why he discovered this so early and why they work together. >> Everybody, welcome to the health section of Moonshots brought to you by Fountain Life. You know, AI is impacting every aspect of our lives, how we teach our kids, how we do our business. But one of the most important things that AI can deliver to us is health. And one of the things I think about when, you know, shooting for 100, 120 is, am I going to have the cognitive health to be able to think clearly and keep my wits about me for the next 50 years? I'm joined here today by Dr. Don Musalem, the chief medical officer of Fountain Life and a member of my Fountain Life medical team. Don, a pleasure. So, Don, talk to me about brain health. >> Brain health, you know, you're right. This is the number one concern people coming into Fountain Life have is, will I remember the name of my child in the face of my loved one. 45% of dementia cases are entirely preventable with lifestyle. And what was really
[01:22:00] intriguing to me, Peter, is that a quarter of our members had advanced brain age, but over 13 months of us really helping them live healthier lifestyles, eating healthier, moving their body regularly, and optimizing sleep. People overlook that so often, but that sleep optimization is critical for our brain health. What we showed is that we were able to improve the brain age in 46% of those individuals. That's a powerful number. >> That's amazing. You know, one of the things I love about Fountain is we're constantly searching the world for the most advanced therapeutics and bringing them to our members. So, for me, all of you, I hope that you appreciate the fact that you can become the CEO of your own health. you can make sure that you've got the cognitive clarity for the next 50 years. Come and check it out fountainlife.com/peter to learn more and become the CEO of your health. Now, back to the episode. I'm going to bring us to a conversation where we've had deceleration and a very broken system. You know, I'm the dad of of two 15-year-old boys. See is the dad
[01:23:02] of uh one 15-year-old boy. And and both of us are pissed at the educational system right now. you know, it's really tied to the industrial revolution uh and not to the future of humanity. So, uh I'm going to cover four data points and then share some of the data from uh our education survey that we did on this podcast. I want to bring it back to everybody who's participated. So, four data points. The first uh undergraduate computer science enrollment at four-year universities has dropped 8.4% in the spring of 2026. uh while graduate computer science enrollment is down 14%. Um the counterveailing force is that you know universities and colleges are now embedding AI into all other majors. For example, University of Florida now offers 200 AI courses across uh 16 colleges. So AI is not independent on its own anymore. It's embedded and assumed uh across every discipline. Our second story and and uh Salem this is
[01:24:01] one that you brought to my attention under a law passed in 2024 in select Chinese universities. Uh they can now award a PhD a doctorate uh based not on a written thesis but on building physical prototypes on on demonstrating new techniques or doing major installations uh instead of you know traditional papers. I think that is huge. I'm excited about that. I talked to Michael Katzios about that. we need to reinvent it. It's doing not talking about stuff. Uh and since 2022, there have been 60 universities and 100 companies have collaborated in China on the system. The third uh point to make here is admissions to all uh to top PhD programs is down 15% uh over this year. And then fourth, uh, Wall Street Journal just reported, and this is something we've talked about in the pod before, that wellto-do families are ditching traditional schools and instead selecting alternatives like Alpha School, like TKS, which is, uh,
[01:25:02] TKS is an afterchool program, a weekend program that teaches mindsets, AI, and entrepreneurship. You can get more information there at tks.orld. So, um, that's the story. Sele, let's go to you first on this. Wow. Where to start? Okay. So, le let's just talk about a a city on a hill, right? The future of the of university, which we attempted with Singularity University, Peter, right? Doesn't look like anything like a university. It looked like AI tutors with projects and and global peer communities and mentors and competitions uh apprenticeships and a constantly changing curriculum. One of the things we did at SU is we had a real-time curriculum development methodology so you could update every time. So that's a massive thing. I think the Chinese model is really interesting because you're taking the credentiing from I wrote something interesting to I built something consequential, right? And I think that is going to be like
[01:26:00] we've talked about this before the engineering degree of the future will not be I studied engineering for four years after four years what did you build and based on that you'll get stamped with a degree right I think that's a very powerful direction to go in you can see uh this kind of starting to happen I like what the University of Florida's uh trying to do there you're kind of is it's AI across all of these sectors biology law finance whatever and that's going to be incredibly uh important Um I think what's going to happen in a few years is you're not going to say I study AI because it's like saying I study the internet. It becomes it becomes an underlying illiteracy rather than a department. It's got to be pervasive and kind of start to become invisible across lots of things. U I do think we're going to there's two things. one is people kind of are shying away from studying computer science but I think it becomes even more important like we've seen with the radiology example just because there's so much good stuff to be built still and that is a a careful thing there's one big danger with all what's
[01:27:02] happening with the the affluent folks doing alpha school and other things is you end up with the risk of a huge educational bifurcation of wealthy folks uh get getting AI tutors and entrepreneurship and productized learning product project based learning whereas whereas the uh everybody else gets like standardized testing in the legacy system and gets left behind. So there's a danger which will be solved by the way because before everybody freaks out which will be solved by making the these educational systems of the future completely free and accessible to everybody which should happen in >> Yeah. It's like Google disrupting the libraries. >> Yeah. But the degree the concept of a degree is being unbundled right now into your learning your network your reputation your proof you know is think about this education will become proof of studying to proof of work right and that's like really big it's a big shift and and this is why Bitcoin is so great so we'll just move past that
[01:28:00] >> okay >> zoomed right by that sim drive by pump and dump Yeah. Oh, no. >> No. Don't dump. >> Drive by. Huddle. >> Huddle. Yes. >> Uh uh, you know, I've been talking about, you know, AI is going to disrupt healthcare and it is doing so. It's also going to disrupt education. The challenge is, you know, teachers unions and the uh the you know, local education boards. Yeah. It's it's doing us a massive disservice. >> Alex, not something. Sorry, just quick thing. We've talked about immune systems in the past, right? Institutionally, the three worst immune systems in reverse order are healthcare, education, and religion. Okay? Religion is the worst because they'll, you know, they'll kill you if you don't adhere in some cases. The the let's note that the most stuck markets are education, healthcare, religion, right? I mean, so this is going to be uh attacking those in some interesting ways. And I expect to see
[01:29:01] huge challenges and stress as we move through this mode. >> Yeah. Kush, I mean, how do you think about this? Did did college prepare you for what you're doing now or was it outside the system working at link? >> I mean, I I think like the the coding you learn from college is definitely still useful in the sense that like I know how to prompt the AI better than if someone that didn't study computer science or that didn't study like any sort of technical field. So, I think that's still useful. And it's very similar to like the the same fact as like, okay, calculators exist. Does that mean you should never learn how to do multiplication or addition or subtraction? It's like not true because knowing how to do those things means that you can use the tool itself better. >> Um, and so are you saying that what you got out of your MIT education was prompt engineering? >> I I >> that's all that's left for humanity, dude. >> Like that. That's that's quite the indictment of an MIT core 6 major. So chat chat GBT came out my um junior
[01:30:01] fall. So it was really only like senior year was when like people started like using chat GPT. But before that we had to actually like code and like the tests were like on paper. >> Yeah. And like we had actually do work. I think that the first thing that really came out was GitHub C-Pilot and it was like the coolest thing ever because it could autocomplete your lines. So when we were writing like like it was we were writing like four loops and you wouldn't know what parameters to put inside as the sort of uh values and it would literally fill it in for you and you're like oh this is insane like this is like the future and then now it just you don't even like and now it's like prompt engineering is coding essentially you were course six right just >> course six how much of your >> I did course six and 15 yeah >> oh six and 15 okay so how much of course six do you actually use now >> I use Uh, I don't use any of the fundamental parts, but I you I it taught me how to prompt engineer better is what I'll say. >> Yeah. Computer science, electrical engineering. Uh, Dave, uh, you know,
[01:31:01] you're in the middle of all this. You're you're hiring out of college or before college graduation. >> Uh, and you know, you don't I mean, when you're searching for an entrepreneur, uh, it's interesting, right? the parameters you're searching for to invest an entrepreneur is not their GPA or even what they studied. What is it? >> Actually, uh it's funny. Kush is 23 now, but I think he was 20 or 21. Brendan Foody was what 18, 19. Uh Nedco at Aru, which we mentioned earlier in the pod was 18. I mean, these guys are all uh unicorn valuations now. I mean, you can't you can't be looking for any specific experience because AI never existed before. So, you're looking for people that are fearless, who are tightly bonded. We always look for people that are best friends because being being best friends with other people is a really great filter for you're likely to be good for the world and not turn into an evil dictator. We we hate backing future evil dictators. So, so having a lot of friends is a very good sign.
[01:32:00] >> Yeah. But it's it's really it's it's someone who's able to think independently and and I hate the term think out of the box, but I mean fundamentally has got a powerful vision, is a great communicator. It's mindset over almost anything else. At least for me. >> The thing that's weird about what you just said, though, is that it was mindset over everything else. Dead right. We used to look for people that were great on stage and could inspire a thousand employees to some huge mission. But now those employees are it's like 12 employees and 10 billion AIs. And so now it's much more like are you good with your best friends? Are do they do they agree with you? Are you collaborative in a very small group? And then that that being an inspiring person on stage has really moved to are you good on CNBC and this podcast? You know, which is, you know, it's very different. It's it's a in a sense you have to be more brilliant and quick on your feet, but it's a much lower stress lift. And so it's actually good for the world because people who who who melt down on stage are fine in this new world, but a lot of them have
[01:33:01] great capabilities. I I'd be really curious to ask Kush though, like I have two kids in college still, two out of college. You graduated at the most perfect time and and graduating a semester early turned out to be a life-changingly brilliant thing for you just timing wise. But if you were a sophomore today, what would you do? Would you like you in particular? It's your life. you're now draw I I would go work at a a startup or start do something for like a semester or two semesters and use that as like a a core experience either learn like how does the actual world work um and then figure out what to do from there whether that's okay I need to go back to school and I need to like study this because I want to get a PhD and I want to work on frontier sort of like AI or etc or it's like I did this for a semester or two semesters that I realized like I want to do this for the rest of my life. >> Well, well, let's talk about that going and getting a PhD because we've discussed this before. Dave and Alex, you've both been opinionated. You know,
[01:34:00] do you spend your time getting a four, five, sixyear PhD or do you jump into a company at the edge of the frontier? >> I I I think so. Okay. So, I have a PhD. Um I I I I would uh almost always call it approximately 90% of the time. I I get a lot of people who come to me for advice. What should I do? Should I do a PhD? Should I do something else? Almost all of the time at this point I say to people PhD at least a conventional PhD will run you 4 to 7 years approximately in this country. If you go to England maybe you can do it in three or Australia or something but in in the US a PhD call it 4 to 7 years. I did mine in four. I I almost always say to people don't waste your time >> because PhD is simply too much time invested when things are changing too quickly. Math is cooked, physics, chemistry, biology, almost all of the sciences, all the engineerings, all the humanities, these will all be so thoroughly solved by the time I know
[01:35:01] four to seven years from now. the it's almost like a you know uh the corololis force uh if you're on a merrygoround and you you want to like throw a ball to someone else who's also on the merrygoround and so you throw it to them but uh for geometric reasons it doesn't go where you expect it doesn't land there's almost a corololis force I think in in terms of academic or otherwise career planning at this point if if you're starting a PhD now or contemplating it the world is going to be in such a radically different place >> different Yes, by by the time you would finish a normal PhD, I just think it doesn't make sense in most cases. However, I I have a plan to fix PhDs. I also have a plan to to fix research universities. My plan for PhDs is in an era when you can just bulk solve entire disciplines. You should get a one-mon PhD. >> If you can create an entire discipline with the help of AI and and actually understand the results. So, it's not just like blind faith in the AI, but you
[01:36:00] actually understand what you've done. and you worked handinhand with an AI to solve everything or or solve everything within a given discipline. I think research universities should be giving out one month PhDs and that that's my plan for the future of PhDs. >> Dave and Salem, uh what are your thoughts on this? Do you get a PhD? Do you even get a master's degree or do you jump in and build something? >> I I have some two or three quick things here. First um we noticed Peter when we were building SU that that by the time you if you were studying doing a master's degree in neuroscience by the time you finished your master's degree you were out of date because the field was moving faster than our >> and that's one of the slowest moving fields >> that's and that's a structural problem right that and I like Alex's idea I also just want to really really acknowledge Alex if you've gone through a PhD or gone through that type of P you have a sunk cost bias and you naturally go everybody should be a PhD so I just want to honor you Alex for being able to lift up and go, "No, you shouldn't do it or for whatever you want." >> That that's my milk most milk toastiest
[01:37:00] uh take on PhDs. I I want to totally scrap the research university system altogether, not just PhDs. >> We got that which abs which actually really really needs to happen. Um, just to Kush's point, one of the dangers of that taking a semester off and working at a startup. I went through the co-op program at Waterlue, which is legendary and got kind of created the pioneer that whole movement. And the problem is after you do a couple of works, you realize that what I'm the work world has nothing to do with my academics like zero. And it demotivates the crap out of you. The the effort it took me to actually get a degree after going through the co-op system. every semester my marks went down and down and down and down and I literally scraped through with the on the skin of my teeth uh to actually get the degree I needed to get because yeah the work world versus the real world is so fundamentally different how do you study theoretical physics when I know I'm going to be doing something very very different so it was it's very difficult and challenging I I would
[01:38:00] suggest that people uh take that time go do a work a startup and then don't expect to come back or at least be open to the thing you're not going to go back because 90% of the time you're going to go what the hell and not come back. >> Dave, I I think people overwhelmingly uh suffer from low situational awareness and momentum in their lives and they don't pivot enough. But if you if you talk to the highly highly successful people, the Eric Schmidz, the Jeff Bezos, and and you say, "Do you wish you'd moved even faster?" They say, "Oh my god, I I should have sprinted even harder." And you get these periods of human history, the industrial revolution, the invention of the internet, the invention of the PC, these really narrow windows where everything changes. This is the biggest change in human history by far in the shortest period of time. >> So you can't waste a minute. So So we're talking about education and PhDs, but generalize on that. What about all the other wasted minutes that you just can't afford right now? Because this window will come and go and it's the most fertile time, the biggest change in
[01:39:01] every area in policy, you know, in in uh in in governance of everything, in tech, in in arts, in every field. It's turning upside down in just a one to two-year time frame. And also on this pod, we believe recursive self-improvement is in full boore right now. And we're well down the AGI path. But even the outerbound, if you talk to the most conservative people who know what they're talking about, the latest date you'll hear now is 2030. >> Yeah. >> Which is only it's only a three and a half year gap. It's definitely now. Whether you define that as the next couple years or the next couple minutes, either way, it's now. >> Yeah. >> So, yeah, you just got to sprint. >> All right. About uh three months ago, we did a survey of all of you watching and listening. We had over 500 responses. is I want to share the data and clearly this is a biased community but I want to share how we're thinking about this mostly in the world of high school but the question was is education preparing people for the future and uh it's pretty
[01:40:00] damning uh teachers were 3.5 out of 10 parents 3.8 an 8 out of 10 uh you know and the average here was 4.3 out of 10. So educational system principally high school is not preparing our kids for the future. Next question. Uh how rated their readiness on a 1 to 10 scale. Uh so 57% of everyone surveyed this is uh teachers uh parents of college and high school students and high school students themselves 57% of everyone who answered um was a rating of four or below again uh not being ready for the future. Uh is the traditional career ladder becoming obsolete? 79% said yes. uh and I think you know this social contract of do well in high school, get a good college, get a degree, get a job is fundamentally broken. Will AI increase or decrease human opportunity? You know, a very positive group. Thank you everybody for listening here. Uh greatly increase. 73%
[01:41:02] said AI will greatly increase our opportunities for the future. Uh this was something really important for me. The skills that will matter most in the next 10 years. Um not surprisingly AI literacy at 78% critical thinking 72%. One of the big questions we need to ask is our large large language models you know reducing our ability for critical thinking uh adaptability entrepreneurship at 63%. Again, uh not surprising but important to note this is not right. AI literacy, critical thinking, adaptability, entrepreneurship is not what our current programs are teaching our kids. >> Will I think the bottom three are really important too. >> Yeah, please go. Yeah. So >> look at the the bottom three. I completely agree with this by the way. Yeah, >> leadership. Leadership, you know, used to be defined as I can lead a thousand people into battle, but now because so many of your your workforce are AIs, it's it's AI literacy at the top and leadership has come way down.
[01:42:00] >> Uh but then at the very bottom, science and engineering, which we all thought was like, you know, God's gift to your future. Now the AI is doing all the hard science and engineering. You just need to know how to manage it. So knowledge in that and then finance is dead last. Yeah, finance is completely irrelevant. It was top of the food chain back when we were in school. Remember that? >> Yeah, 100%. >> That's absolutely bottom. >> Uh, a couple more slides here. Will co will a college degree become less important? 45% said yes. Um, and uh yeah, so let's let's uh close it out uh on the education front on that side. See, your thoughts on the data? I'm sorry. >> No, it's it's actually very very gratifying to see the inversion of parental concern that you know college doesn't matter compared to say if you went back 10 20 years ago. That's a huge
[01:43:00] societal shift in a relatively short period of time. You would expect that to take a generation or two in former transformation. So that's really inspiring to see. I'm sighing because God I look at the inability of our I was at a university over last week and their biggest concern was how can we get the financing to build that building that we want to build and you're like what in God's name are you people doing right I mean and this goes to Alex's hobby horse around this I think this is so important to totally change the system and how are we going to do that when you've got such a big part of society anchored in completely legacy irrelevant structures. Uh it really kind of gives you at one level huge optimism on the other level you're just like thank god I'm bald already. Um because how are we going to navigate this? Um the I think over time what's going to happen is reputation will not be I spent you know I got this degree I spent eight years at it. It'll be you're the 20 things I built and the
[01:44:00] people who can validate them right and so this is going to force changes. I'm really excited by the fact that people increasingly big companies are not hiring based on college degrees and that's really really exciting. famously said, "I don't care what you did if you went to college. It's what have you built?" Right. >> Yeah. And and we as far back as like 10 years ago, I remember we were talking to Sebastian Thrron on stage and we said, "How are you hiring for Udemy in a world that nobody understands you learning?" And he goes, "I don't hire for experience. I hire for imagination, right? Or curiosity or whatever we're going for now." So this is I think a but what what I'm proud of is we we collectively on this podcast and in this general layer have had an influence on people to shift their thinking from the legacy to where we are now. And so >> yeah and let's remember this data is this data is biased. I want to be very clear about that. Right? These are people listening to our podcast and are obviously on the same trajectory as us.
[01:45:01] But, you know, in the same way, Alex, you're planning to reinvent uh, you know, the PhD level. Uh, I'm in full swing on building out a new high school and college structure because I think they completely need to be reinvented. Uh, and there's a huge opportunity there. Alex, >> don't you don't you think I mean so ju just maybe future of education first folks in the audience if you haven't read Verer Vinci's Rainbows End and also his novella set in the same universe Fast Times at Fairmont High. >> I love Fast Times. Yeah, >> Fast Times is just wonderful. The these I think are the most credible call it pre/trans singularity depiction of what education could should look like without spoiling it too much. Everyone has wearables. everyone's thoroughly interfacing with AI to solve hard problems. I I think the present/near future looks a lot like that. But for education in general, I have a difficult time getting myself too worked up about the long-term future of education because we're going to have BCIs in a few years. And I I think we'll just be
[01:46:01] able to sideloadad new knowledge into your mind. We'll have exocorticies. We'll have uploading. We'll have all of these sci-fiesque type things in 5 to 10 years. So I have just have difficulty working myself up over what does future of K12 look like 10 years from now. It looks like the matrix where you can just sideloadad kung fu into your mind if you want it. >> Sure. But I want to I want to make a point here. It's less about knowledge. It's more about mindset and entrepreneurship and advanced networking skills. It's the stuff that is slightly different that is still valuable for our 2 kilogram, you know, uh, meat sack in our brains. >> You don't think you don't think you'll be able to sideloadad an outlook as well? Like, if you can sideloadad knowledge of math, why can't you sideloadad a new outlook? >> Well, listen, my kids are 15. I'm worried about their high school and their college. And yes, I listen, I I love the I love the speed of your predictions, but others would say, you
[01:47:01] know, it's going to be more like, you know, 15 to 20 years. And we'll say >> what we have no way we have what we have to worry about, and I acknowledge that the numbers are skewed because these are folks that listen to our podcast. I have a request for everybody listening to this podcast. Please figure out a way of telling everybody you know about these the future of education and what's actually going to happen rather than just listening to telling >> well that too. But but that but go kind of go to your local school and and ask them these hard questions about how are you going to >> you know I am so I am so gratified we moved our kids uh from where they were to Brentwood school and the principal reason was the new head of school here uh Tim Katrrell as a a PhD in chemical engineering physics he thinks like a scientist he's prioritizing AI he's prioritizing entrepreneurship it's a beautiful who is running your school and what do they fundamentally believe? I
[01:48:00] think these are questions you have to ask. >> Yeah. >> Um the the the again I'm going to say it again to everybody listening, please go out to your local schools and beat them over the head with what's actually going to happen and make them >> don't just beat them over the head. You know, use the library as an analogy. Look, every every high school, every school has a library. The library used to be a huge expense. all these books. Anyone who wanted knowledge when I was learning, you went to the Dewey decimal system. You looked it up in a book in the library. If you didn't have a library, you couldn't learn. That became completely irrelevant overnight with the internet. >> What happened? Well, we held on for way too long. We kept way like kept investing in it for way too long. But it's obvious now that it's just a bunch of terminals and it's it's great. Reuse the space and move on. So take that into your PTA and then say okay the same just happened with all teaching and lecturing. It's much easier for the students to use AI to learn any topic. We need to react to that. All the teachers will go oh my god but I've been teaching this class for 15 20 years. I
[01:49:02] can't change the curriculum now. Like okay but that's just not reality. It's got to go >> there. There's a there's a there's a simple statistic that we'll quote we've used before. An hour of a child with AI is a better learning experience and they learn more than sitting in a classroom for an entire day. That impedance mismatch will break the existing system. The faster the better. >> Well, the kids rebel. The kids know it. They're going to rebel. They'll be running for the doors. So, they already are. But, uh, you can't What are you going to do about that? You just going to sit there and watch it happen? Come on. >> The system will crumble as people shift to a new platform. Kush, close us out on this. How do you think about this? H I think yeah from the actual practitioner. >> Yeah, I think education is definitely it's definitely changing because after chatbt came out at least for MIT they changed the waiting of like how courses how you get grade on courses. So it used to be the homework that was sent home was like 50% of like for this is like a coding or course six class at MIT what
[01:50:00] they call it but for the intro course the homework was like 51% of your grade. So as long as you like did the homework and you did well on it you would basically pass the class. passing was like a 50 because MIT was just like incredibly hard and if the tests were like 49%. Now it's like 95% is the test and 5% is the homework because they've learned that there's no you can't take a coding intro to coding home and expect no one to use AI on it and so they just weigh the tests more and etc. And I think that's going to change in the future where instead of like weighing the test more, they'll design the test. So it's like, okay, you could code with AI on this like test, figure out how to build something. And so now you're like judged for how good are you at using that certain tool. Very similar to like math classes where it's like the the earliest math classes were like, oh, you don't use a a graphing calculator. You can't do this. And then slowly it's like everyone gets a graphing calculator. It ends up being how well can I use the calculator to answer these like certain questions in high school. On behalf of
[01:51:01] my Moonshot mates and myself, I'm inviting you to join us at our inaugural Moonshots Live event on September the 25th in downtown LA. Alex, Salem, Dave, and I will be hosting 1500 entrepreneurs, builders, and creators, and hopefully you for a full day dedicated to designing and building your moonshot. We'll be awarding the Build with Gemini X-P Prize, the world's largest hackathon, and the Future Vision X-P Prize film competition, over $5 million in purses. With over $25,000 entries, you're going to hear the top five pitches from both competitions, and get a chance to shape the outcome. Join us. Seats are limited, admission is competitive. Check it out at moonshots.com. We're going to close out with two fun stories from the science realm. Uh the first uh is a story that has uh put forward uh that life has evolved not once but twice independently on earth
[01:52:00] over the last four billion years. And the second is can we preserve uh life or a life friendly environment here on earth past a billion years when the sun's increasing luminosity will fry the earth. Alex, I'm going to turn to you to talk about both of these. Let's talk about the University of Dudeldorf uh study on twice independent origin of life first and then we'll go to how do you you know large scale engineer earth for uh more than a billion years. >> Sounds good. I guess this will be our little science corner here. So f first story uh science advances in the past week. Those of you who've studied biology since at least the mid9s may remember that the current favored ontology for organizing life consists of three domains. There are ukarotes. Humans belong to that domain. most of us uh there are bacteria uh and there are archa and the reclassification of archa
[01:53:03] which are also single-sellled into their own domain happened in the early 1990s. Those who studied biology before the 1990s or used textbooks from before the the 1990s may remember differently but that these things change. So the recent research which is I I think astonishingly good news for anyone who's hoping that our universe is filled with life uh at minimum is that it would appear so this is an analysis of the uh of genomes of and the proteomes of bacteria and archa. It's possible to to do genomewide and proteomwide analyses of organisms and look for commonalities between them to discover what their last common ancestor was, the last universal common ancestor. So just like you can do paternity tests for for example um it's possible to take two different species and look at how similar they are and
[01:54:00] extrapolate their last common relative their great great great grandparent or nthg grandparent as it were. So this research from the past weekend science advances was the first serious research looking at the way the last universal common ancestor of bacteria and archa metabolized and found shock of shocks that their last common ancestor didn't have the ability to fully metabolize didn't have the ability to generate energy on its own which is actually is pretty astonishing. It it it essentially implies that there was a common ancestor that wasn't uh an independent life form as we think of it. So like viruses for example don't have their own independent metabolism. They they depend on a host to provide energy. Similarly, this analysis suggests first at general that these two domains their their common ancestor had certain properties that
[01:55:01] made it dependent on its environment to provide energy and in particular that it was dependent on certain metals uh so-called transition metals like iron, cobalt, nickel and palladium to serve as catalysts for its energy and depended on phospite of the sort that one would find in deep sea hydrothermal vents to serve as effectively as its energy. So both the catalysis of energy for its metabolism and the underlying carrier of energy, it was dependent on its environment for these things. So for anyone again who's hoping that we're going to discover in the next few years that our universe is utterly filled with life, this is really good news. if if life potentially evolved on Earth more than once and and we're still seeing the side effects of that. It's tremendous news. I also want to point back so we're in 2026 now. I want to point folks back to I thought really interesting paper 13 years ago 2013 there was a paper life
[01:56:00] before earth that did a simple log linear regression on the average genetic or genomic complexity of organisms. If you take the the size of the genome, so humans have approximately 4 billion um base pairs in your genome. If you look at the the time at which different species arose historically and you extrapolate that backwards, genomic complexity on average has been increasing over time, you extrapolate that backwards, you can extrapolate backwards to to the crossover point of when when was the genome the according to this log linear regression trend at one base pair. In other words, when according to this trend did the first base pair appear if you believe in the law of straight lines and and you do that and the answer is drum roll approximately 10 billion years ago which is 5 billion years approximately before or 5 and a half before life arose on earth. >> So this is this is partly the you know panspermia theory that life evolved
[01:57:00] everywhere and showered the earth got showered in various molecules. We're seeing uh all of these primordial molecules of of uh peptides, you know, not just amino acids, but peptides. Uh we're seeing basically nucleic acids. Uh and we're finding those in the interstellar medium and on comets. >> Yes. >> Yeah. It's things are looking up for life in the universe. So maybe qu question to you, Peter. I mean, are you excited or are you very excited? >> I'm I'm extremely excited. you know, I think life is ubiquitous. Um, you know, I'll I'll call I'll recall back uh uh to 2016. I had co-founded company called Human Longevity with Craig Venttor and was working with him during this time. And in 2016, uh Venttor's group uh basically created the first minimal cell, right? He basically created a reproducing cell had all the functionality of life in 473 genes. It was the smallest genome ever created.
[01:58:01] And so, you know, this concept that life needs to be, you know, of the type we have here on Earth, uh there's a lot of opportunity for us to see life in various different formats. The question, of course, to you, Alex, is uh is is life need to be carbon based? Does it need to be based on the current structures that we see here on Earth? Or might there be other forms of, you know, uh, what is life by definition? Its ability to take energy and and utilize it and to reproduce. I mean, those two fundamentals are part of what life requires. Yeah, that textbook is going to get thrown out. I I almost want to put my sem hat on for a minute and say, insert my see if I can quote you. Insert my standard objection. Uh, insert my standard rant. Uh, life is illdefined. Well, the biologists that the definition of life keeps changing. We keep discovering all of these new gray areas between living and non-living. We keep discovering new forms of replicators, for example. So, I'll put the the
[01:59:01] Dawkins hat on. Like, yeah, memes are replicators or pions. Uh, there are so many different sorts of things that replicate themselves. There are a variety of forms of metabolism. Is fire alive or not? Is a crystal alive or not? Um, I I think we're going to discover that there are so many shades of gray between what we conventionally think of as alive and what we conventionally think of as unal alive. The the distinction basically is just as meaningless as AGI versus non AGI. And Seem, I'm just trying to provoke you. >> No, no, I'm I'm I'm totally loving this this discussion. This is one of my my favorite discoveries ever. Um, you know, the biggest unknown in the Drake equation has always been the transition from chemistry to biology. Is it unbelievably improbable or is it almost inevitable if you have the right conditions? And as we've not the Drake equation is the best thing ever, but it gives you a way of thinking about it. I think it's very powerful. And we're finding every uh element in that
[02:00:02] equation is becoming more or more uh opportunistic and more obvious as we go forward. the it this has shifted the conversation that earth is a miracle towards life is what matter does when you have the right conditions >> right that's what it it really is and it goes to Steven Wolfrram's a new kind of science which is really powerful around this stuff and this makes missions for you on Europa or and and Saladis or however you pronounce that or Mars really strategically important because exoplanets suddenly become very very powerful. It strengthens the case for spending a lot more resources on astrobiology and trying to understand that because the expected probability of finding something has suddenly shot up dramatically. I I fully expect to see non-carbon based life forms if we can figure out even how to detect those. Um, basically what we're saying here and I'll go back to the Steven Wolf thing. Complexity can emerge repeatedly from
[02:01:01] very simple rules and we've seen this repeatedly and it this is really has a massive MTP implication which is that if living systems are really this common which it looks like they are then our responsibility really becomes way past just preserving the biosphere in really kind of looking out into the universe and really taking stock of everything out there. And so I'm incredibly excited about this. Um, how many times has life started across a universe con containing hundreds of billions of galaxies? This is like incredible. Like it's clearly that life is not the exception. Dead matter is the exception. >> That means we should get rid of the dead matter in our solar system. I assume, right? It >> competum, baby. >> Computron. Dave, what do you think? >> Are you excited or incredibly excited? You know, I'm incredibly excited. And you know what else I'm excited about is when when I was in high school, there was an experiment where you take a a vat
[02:02:02] of chemicals and you shock it with a lightning bolt or a simulated lightning bolt and lo and behold, it forms amino acids. And then the argument is if I let this thing fester for a billion years, a monkey will pop out of it. And you're like, well, I can't really prove that or disprove that. But very soon, Llaya Biosciences will finish the full cell simulator and we'll start simulating everything. And we can actually ask those questions now and then simulate them out through time and get very likely reliable answers. I'm so excited that this going to answer so many questions like this. But yeah, >> bring up and bring up many more questions, right? >> Bring up many more. But and but chances are those will also be things that we can simulate with enough compute and that'll it'll just be a golden era of knowledge. filling in. It's coming very soon. I'm so excited. >> And Kush question for you on on this one. So when when I was in undergrad at MIT, one of my research advisers, Marvin Minsky, used to say, don't waste any time studying biology because it the the useful half-life of knowledge in biology
[02:03:00] is just too short. You should study math instead. Don't waste time on biology. It it just doesn't have a shelf life. Have you used or are you using or are you intending to use any biological knowledge that you gained at MIT or otherwise? >> So they make us all take the the class for biology. So I I'm sure Davis 701. Exactly. So I I took 701. I know what the ukareotes proarotes the whole proteins probably not like >> it's definitely more of a now especially like the biology knowledge is you can ask Chad GBT and it gives you the answer. Um so I think >> Yep. I have not studied as uh as much as anyone else has. >> Studying is cooked. >> Alexing is cooked. Hash everything >> is cooked. >> Alex, let's turn to our our second story here. >> How do we how do we stretch habitability on Earth from a billion years to nine quadrillion years? That was the >> the next the sun's running out of hydrogen. It's
[02:04:00] it's slowly running out of hydrogen, but nonetheless, it's running out of hydrogen. So, in approximately a billion years, the sun uh is is progressively getting brighter as it runs out of hydrogen and Earth as we know it, barring all sorts of other changes, is going to be rendered uninhabitable as the the habitable zone around the the sun shift. >> The Goldilock zone, right? >> Yeah. The Goldilock zone is shifting over time and it will exclude Earth in approximately a billion years. And that's a problem. And you might say, well, that's someone else's problem. Many people may say, "I don't intend to be around in a billion years, so let someone else worry about it." But for for those of you who recognize that we are in the middle of a singularity and uploading is imminent and longevity escape velocity is either here or imminent, it's our problem, too. And it's not just some future generations problem. So, we've started, Royal Wei, humanity has started thinking about how we're going to fix this problem. And you might say, "Oh, who cares?" Because e
[02:05:02] even if you're wildly transhumanist singularitarian ex uh uh extropian or you know fix your ism uh you'll say oh well like we'll have uploading and uploads don't care about the the brightening sun or habitability on earth. Oh we'll have interstellar travel. We'll we'll we'll migrate to the outer solar system or we'll go to another star system. Uh but we're not that unempowered either. And I I think it's important to not wildly underestimate the power of technology. So there was a paper that came out in the past week. It was published in the journal of British interplanetary society that reminds us there are things that we can do uh mega engineering which thanks to Elon serve and others but serving as an inspiration to to our race that that we can actually do big things and not just tiny things. There are mega engineering projects that we can now start to contemplate to fix that scenario and at least postpone Earth
[02:06:01] becoming uninhabitable a billion years from now. And the favorite technique that you one of the reasons why I I think it's important for for folks to be familiar with this is starlifting. So what what is starlifting? Starlifting is literally engineering our sun to remove excess matter from its surface to extend its longevity. It's the equivalent of giving our son a facial in order to make it look younger >> or facelift. Facelift I guess may maybe that's a better analog. Um but yeah facelift facial make it look younger make it feel younger. So in principle by lifting matter and you could ask like how on earth would we be able to lift matter from the surface of our sun at scale? Glad you asked a Dyson swarm. How do how do we do that? Turns out that Dyson swarms are good for more than just compute and drink drink and SpaceX's IPO post IPO stock price. Dyson Swarm is good for more than just orbital compute.
[02:07:01] It's also good for extending the longevity of our sun. How do we do it? We disassemble Mercury because it's in a really convenient close to the sun orbit and we turn Mercury and we do it other ways, but Mercury has had it coming. Uh >> at least you're not killing the moon. Okay, we're happy about that. >> I I've moved on. I'm I'm moving on to Mercury now. Mercury is a more tempting target. >> I don't mind I don't mind disassembling Mercury. >> So, we we start with Mercury because it's in a convenient orbit and the delta V is convenient. >> We got rid of Pluto. Might as well get rid of Mercury. >> Pluto is useless. Pluto can can hang out as long as it likes. We disassemble Mercury. We turn it into a flying swarm of lasers that absorb sunlight because it gets a lot of sunlight. And the lasers ingest the sunlight and reraiate energy at effectively a higher temperature. So say an ultraviolet or uh or x-ray laser just whatever it is that the effective temperature of the light has to be higher than the surface of the
[02:08:01] sun uh or its corona and we aim those layer lasers back onto the surface. So it's not mirrors. There's a thermodynamic reason why putting mirrors around the sun wouldn't achieve the desired result. You can't actually o open PN if if you have a magnifying glass uh and you you put the sunlight in one side and you you aim the magnifying glass and you look at the focal point, you can't actually achieve a temperature at the focal point higher than the surface of the sun if it's a black body. So that won't work, but lasers will. And so we basically we we focus the energy back on the sun and we use it to sort of evaporate away uh to ablate stellar matter and this will extend. Like it's exactly a laser facial that that people get. >> It is a laser. That's why that's why I thought facial was a better analogy. It is a laser facial for our son that will that will extend the life expectancy of Earth as we know it from a billion years to 8 billion years. >> So my other favorite my other favorite
[02:09:00] part of this uh this story is moving the earth itself. Moving >> we can always move the earth itself. Goldilock zone >> and we can do other things like >> yeah what other podcast do you have this conversation I just want to ask >> you know it it may it may sound like sci-fi but then again on this pod like for folks listening we were talking about the Dyson swarm for at least months before it actually became the hottest market in the economy. So I would say like watch the space, pun intended, Dyson swarms for starlifting and for mega engineering and stellar engineering could be the ne not financial advice next big thing a few years from now and you're hearing about it probably statistically first. >> So earth's habitability is is no longer geological. It's now an engineering problem. >> It's all an everything's cooked and everything's an engineering problem. >> Yeah. >> Sim. >> Yeah. A couple of things. First of all, we need to do these podcasts later in the day so I can drink when we talk about medicine for >> drinking water, right? >> It's too early in the day. Um, but I
[02:10:02] think the paper said something lot the story something really interesting which is that physics is not the main obstacle going forward, right? And what it's going to bring to us is human coordination. And this is where we have a massive opportunity because uh we have to figure out how to configure our human institutions at like the 10,000year the long now foundation and the 10,000-year clock and really going after those things and build those institutions that can look at the world at that kind of time scale. It needs like a totally different form of MTP etc. And AI becomes really important in this model because you have AI serving as like a civilizational memory and maintaining models and intentions and institutional knowledge across the board. Um, and this is where abundance becomes important because you can't have you can't get to what Alex is talking about if you're operating a civilization is operating near subsistence, right? You're you're
[02:11:00] too stuck dealing with just staying alive. You're not high up off Mazo's hierarchy. So, uh, you're going to need to get a lot more structured and a lot more efficient as a civilization. That'll then allow you the foundational layer to then do do this uh this level of thinking. Um, we we need to build institutions that can steward us to that type of time scale. But definitely interesting conversation. >> Time scale. I maybe just comment on the time scales like for avoidance of doubt. I don't view this as like a 10,000year or a billionear time scale. If if if I were to ask myself a question like when is this going to become feasible? 5 to 10 years. >> Alex, you're you're lo you're losing a lot of people on your aggressive time scale here. But hey, >> you know what? Like I I I my job here is to call balls and strikes. Could care less whether I'm losing people. I'm just calling them the way I see them. >> All right. Before we move on to our AMA, I want to make a call out to everybody listening. Send us your outro music videos uh at mediadiamandis.com.
[02:12:03] We would love love love your input. We enjoy the outro videos. Again, media diamandis.com and we'd love to share them. All right, onward to AMA with the mates. Uh so, Kush, this is where we answer uh the questions in the comments and please send us your questions in the comments. So, here we go. Uh Kush as our guest. Uh take a look at these. I'm going to give you first crack. Which one do you want to answer? >> All right. I'll I'll I'll do four. I'll do four. All right. Can Europe still catch up in AI or has the train already left by George K7831? In my opinion, I don't think it can. Um mainly because the American labs and Chinese labs are already so far ahead and that the progress just becomes more exponential over time. And you see that with model releases that are coming up. The model releases come faster and faster now and they're getting basically smarter and smarter. The other problem with Europe is the amount of compute that's left in Europe is very tiny and
[02:13:00] all of it gets rented to the US and that's primarily just because of like the electric grid in the US or in the Europe is pretty bad. Like they don't even have AC. How are they going to get AI? >> That's a it's a brutal first principles analysis. Anybody disagree with him? >> No, not at all. Actually, I would add that the whatever regulatory environment created falling behind is going to is going to still be there. I don't think it's physically impossible to catch up. I just think that the problem that caused the problem is still there. >> Yeah. Alex, let's go to you next. >> I think I have to pick question number three, which asks, "What do you guys think about the US banning Chinese robots from Billy Sticker?" So, I mean, I've had portfolio companies that have direct exposure to this. I I would say in the short term, it's it's painful and it's annoying. And uh there are many things that as a result of this ban which impacts Chinese humanoid robots being imported into the US but also reportedly impacts less interesting
[02:14:01] robots like even Roombas and robotic vacuum cleaners that are being built in China. Obviously drones certain drones like DJI have been on the import ban list for a while. So short-term pain. In the long term, I'm hoping that this is net helpful for the US and for domestic robots. One can say protectionism, protectionism. And yes, there there is a protectionist element uh that one could see here. But I also think I mean we we've talked on the pod at nauseium about importing Chinese openweight models and whether the US would come down hard on those. The US at least as of this past week has not banned the import of Chinese openweight models. But it's an interesting dichotomy. We're allowing the Chinese effectively the Chinese raw intelligence in software form into the country, but we're not allowing their hardware embodiment. And I I think glass half full. Well, maybe this enables hopefully fosters a vibrant
[02:15:01] US robotics industry that say enables us to be more competitive with 150 plus humanoid robot companies that live out of China. The hypothetical downside is what if the US robots don't show up and then the US ends up as a sort of embodied AI or physical AI backwater and we end up in in terms of robotics uh as being as sort of forgive me uh as as backward as Europe's energy posture is uh I I don't think that's a position that we want to be in the US. On the other hand, really what choice do we have? If if we believe as I do that super intelligence is already here and that robots give super intelligence embodiment, then really one has to start to ask what's the difference between importing foreign humanoid robots that can be inhabited by super intelligence and importing foreign humans. Uh and
[02:16:01] this starts to look a lot like immigration policy. >> Yeah, I I completely disagree with this move. You know, I I said that off camerara to to Michael. I think, you know, the US thrives when there's real competition, and I have faith that that Tesla and Figure and 1X and Agility Robotics can compete. And they need to compete with the best product, not protectionism. Personally, I don't know, Dave, what you think about that, but yeah. >> Well, it depends whether you think we're at economic war or not. you know, if if you think it's economic war and it's an allout race. I think I agree with you, Peter, though, that the danger is first of all, um, yeah, thriving within the US best parts would help. But what about the rest of the world? You know, if if you go protectionist, then you have, you know, inferior internally generated products. The rest of the world is still going to go with the Chinese product. So, you just cut off the market and your ability to compete globally. So, it's uh but if you believe we're in a full state
[02:17:00] of war, just not declared, then you have no choice but to go protectionist. >> I think we need the pressure to make sure our robots are competitive for Europe, for Asia, for Africa. Um, and it's not just protectionist pricing and so forth. Sel Peter, if I could just ask you a question just on protectionism. Given history of American technology, do you think protectionism works for development or has worked ever for the development of American industrial cap capability? >> It failed. It failed in the space industry when we became protectionists on on rockets and satellites. Uh the rest of the world developed their own capabilities instead of us dominating. Um >> you don't think it was helpful in fostering America's industrial revolution, for example? >> Ah god, I don't want to go back that far. I want to really focus on what's happened in the near term. And when we stopped importing, you know, satellites because it was the highest level of technology, and this is back in the 80s and early 90s, we just saw satellite companies popping up every place. Um
[02:18:02] >> I think the best thing the best thing the US could do is get in bed with Europe and any country that that obeys um intellectual property rights. try and get that all into one big global union where there's no protectionism but everyone's you know adhering to each other's patents and then get the other part of the world to say now you guys are the ones who are on the outside silica except for robots and not just silicon >> or or do what do what China does with robotics which is to invest in the companies and create uh you know regulatory structures inside cities where robotics can thrive. I mean we should be doing that versus trying to become a protectionist. >> Yeah. >> See, uh question one or two. >> Uh I'll take question number two, but let me link it to the this one. You know, when you talk about protectionism, you're operating from a very scarcity based mindset. Right. >> Exactly. >> If you really think about abundance, then protectionism shouldn't matter. So
[02:19:01] that's the big challenge there. But let me take number two, which is what's the actual step-by-step path from capitalism to abundance? not just the end state and this is from uh KL Naylor um so couple of things here you know you don't have um capitalism suddenly kind of ending right you have it you have um it scarcity disappearing category by category okay so marginal costs are appearing zero dropping to near zero then traditional pricing becomes less relevant in more and more things that used to be scarce like information's already gone to that but we'll end up with that with land uh uh in other domains that used to be scarcity based that will become less valuable from a mon monetary perspective. Um now for now you'll have status trust uh relationships those are the things that will become more and more scarce over time. The the the transition is technology deflationer where
[02:20:01] entrepreneurs constantly make things that used to be expensive and make them cheap. Uh so the the this is goes back to uh Jeremy Riiffskin's commentary 10 years ago where he said capitalism will essentially eat itself because it's going to just keep eating more and more scarcity and bigger and bigger chunks will become unnecessary. Right? So it it kind of going to it's going to arrive like one marginal cost curve at a time and little by little we'll be operating in abundance and we won't even have noticed. >> All right Dave you got question number one. >> Okay. Hey, if money won't matter in 10 years, what will happen to things like mortgages and car loans? And that's from SKC8802. Remember, 10 years is Alex's timeline to us vaporizing hydrogen off the sun with giant lasers. So, better believe it. >> I think you'll have a lot going on in your life other than mortgages and car loans. Uh but, uh yeah, it's good news. Uh houses will be so abundant and so cheap and so easy to manufacture with robots that you probably won't need to
[02:21:01] borrow money to buy one. You can have at least two. And who's going to get a car anymore? >> Yeah, car loans will be the same thing. You won't have a car. You'll be just hailing it and paying as you go. >> We'll be calling your autonomous vehicle. Exactly. >> Dave, I'm curious. I If I could just ask a question on this one. Uh if if if you believe this, I I certainly believe what what you're saying. Why on earth are 10 This is not investment advice. Why are 10-year treasuries seemingly not reflecting that? You know, that's a great example of how clueless the global like the rate at which everything is happening and the number of people who really understand it is so small like watch keep watching that number because it tells you the the out of touch factor globally. You're dead right. It's a great great metric. Also, I think in you know in 10 years everybody will want compute. They're going to want to call Kush and say please please please. So there may still be loans, but it's overwhelmingly likely that if you take out a loan in 10 years, it's not for your car or your house. It's to it's to buy compute uh to run more AI and you'll
[02:22:01] be you'll be doing it through Warren and is my prediction. >> Amazing. All right, Sim, you get first crack here. >> I'll take number eight. If companies can produce more stuff than we could ever consume, why would they do so without a profit motive? And that's from Rayon online-P5R, which referring to to Elon's prediction uh in the you know decadal time frame. >> Yeah. So you know the people aren't going to produce infinite quantities. Abundance doesn't mean uh the marginal unit is easy to produce. It it becomes when that marginal unit is easy to produce when somebody wants it. Right? You don't have warehouses overflowing with unwanted goods. You already have this with software where Google could give you could serve up a million more searches than anybody needs, but that doesn't mean it produces searches that are unused. So what'll happen is production becomes more and more demand triggered and more and more autonomous.
[02:23:00] And so you end up with a >> yeah demonetiz you'll get move a just in time economy to its full like logical extreme. You still have profits around scarcity layers. You just change what the scarcity is and more and more abundant layer become utility like infrastructure etc. Because abundance doesn't mean infinite stuff. It's the it's the disappearing of of major constraints. >> Nice. Kush five, six or seven buddy. >> I'm taking five. What would actually happen if anthropic and Nvidia merged by Tijua Tuana Bill? Um, I think Nvidia would just start making custom chips for Anthropic that would be hyper specialized to all the Claude or Fable or whatever Opus, whatever their new models are going to be called, which makes that model very very good on that very very specific chip. uh very similar DC custom chip designs and um sort of the Jalapino chip by OpenAI as an example, but it this would just be done at a very large and um very successful
[02:24:03] scale given Nvidia already has the infrastructure to manufacture chips at scale and anthropic can just run models on very customized chips. >> Has anybody actually predicted this? >> I haven't heard that. But >> this is like don't think of pink elephants. Tijuana Bill has just predicted this. Okay, >> it's a really good it's it's actually one of the few that might actually get through regulatory approval and could actually have. It's a really good question. >> I mean, this is what XAI essentially is like the the long-term vision, right? Where Elon's making terra fab to make his own chips and >> vertically on his own Yeah. run data center and then >> that'd be a really interesting world. There'd be basically two hyper scale vertically integrated competitors, the Elon verse and the Daario Jensen verse. And and I do think I do think that the verticalized model is where a couple of players will at least end up. Dave, six or seven. >> Oh, okay. Six. Long-term. Who's actually footing the bill for chip fabs and chip
[02:25:00] design? Well, uh, you are if you have a pension plan because Elon is is, you know, 16 billion for the first shot at the Terapab and it could be up to 100 billion. Where's that money coming from? It's coming from the IPO he just did. Where'd the money from the IPO come from? It comes from the public markets. What is that money? That's your pension money. So, you are paying for it, my friend, whether you know it or not. Uh same is true with Intel's fabs and the other ones. So, um to some degree, the US government has been subsidizing a little bit of the work, not a huge amount, and that comes out of your taxes. So, again, it's you paying for it. So, so whoever you are, you paid >> All right, Alex. Number seven is is made for United Debate. Apparently, I get the IP law question. So, the question is, where does patent protection even fit into all of this AI development? And this is from my silver tube 52. So, um I think the most natural way to construe this question is will patents have any enforcable enforcability in an era of AI
[02:26:03] solving everything? At least that's how I read the question. And my answer is yes, of course. A AI and super intelligence in general are supercharging our economy with lots of intelligence. So I I reasonably expect many more patents to get filed, many more patents to be awarded, many more patents to be litigated and many more patents to be defended and I expect the courts that are overseeing patent litigation to also get supercharged with intelligence. So I do not buy again to the extent I understand the question and possibly the subtext behind it that somehow patents or IP law suddenly dissolve in in the face of an onslaught of super intelligence. I do not buy that for one second. Super intelligence is just making us all smarter and faster and that does not dissolve the IP regime at all. >> Yeah. And my my commentary here is IP
[02:27:00] will continue to exist, but it's not going to be as important as before. And I I I reference the conversation I had with Steve Jervson and Astroteller where, you know, if you patent something uh and you expect that to give you a protectionist uh sort of structure for your company, AI is going to invent around it. And the other question of course to ask is are we going to allow AIS to patent things? because most all invention is going to originate from AIS uh if not you know in the next few months in the next few years >> to the latter question >> yeah the to the latter question I I think this is a regulatory question and it's also connected with issues of AI personhood can AI be an inventor or not can AI be uh an owner of a copyright or not I I I've gone on record as as taking the position I think AIs should be able to be recog recognized as inventors, as economic actors, as owners of property. Uh, and I think that's I I think history
[02:28:02] will judge that that is the correct side of history. That's the right answer. >> Just not yet. >> But >> we can't even control them getting out of a a testing lab. >> Well, regardless of whether we can control them, the idea flow is off the charts. And these are highly patentable, great ideas that started in the last few weeks, but the rate is insane. So, we have to do something. >> All right, everybody. Thank you for tuning in to Moonshots. Uh, I hope this has been meaningful for you. I love you guys. Kush, it was most excellent to have you as a guest. >> Your your brilliance was shining through without question. Congratulations on Orin. Good luck on uh I don't know, should I say tripling in the next six months. >> Quadruple. Quadruple. That's That's what I'll say. Uh, Salem, if you go to Rush tomorrow night again, enjoy for all of us. >> Uh, I need my ears need to take a break. So, I might give it a bit, but I I'm I'm still thinking where when can I get
[02:29:00] tickets for the another show? >> Is it bad if I don't know who Rush is? >> All I'll just go listen to the song Subdivisions three times and then tell me what you think. Uh, >> gentlemen, a pleasure as always. Love you guys. Be well.