Elon Musk on AGI Timeline, US vs China, Job Markets, Clean Energy & Humanoid Robots | 220

My concern isn't the long run. It's the next three to seven years. How do we head towards Star Trek and not Terminator? I call AI and Robotics the supersonic tsunami. We're in the singularity. When is all by color work gone? Anything short of shaping atoms, AI can do half or more of those jobs right now. There's no on/off switch. It is coming and accelerating. The transition will be bumpy. You have a solution to this. I don't make a bet here. China's done an incredible job, right? I mean, it's running circles around us. Do you imagine that the U.S. could make that level of investment and commitment? Based on current trends, China will far exceed the rest of the world in AI compute. Every major CEO and economist and government leader should be like, "What do we do?" We don't have any system right now to make this go well, but AI is a critical part of making it go well. And there are three things that I think are important. Truth will prevent AI from going insane. Curiosity, I think, will foster any form of sentience. And if it has a sense of beauty, it will be a great future. It's going to be an awesome future. Now that's the moonshot, ladies and gentlemen. Welcome to moonshots. Following is a wide-ranging conversation with Elon Musk, focused on optimism and the coming age of abundance. My moonshot mate Dave Blundin and I flew into Austin, Texas to meet up with Elon at his 11.5 million square foot gigafactory, home of the Cybertruck and Model Y production, and the future home for 8 million square feet of optimist production. Elon has agreed to do this kind of a deep dive catch-up once per year. This is hopefully the first of many. And after having this conversation with Elon, it's crystal clear to me that we are living through the singularity. All right, enjoy. Yeah, your relentless optimism is always a breath of fresh air. Thank you, buddy. Thank you. I want to share that tonight with a lot of people. Yeah. I think they need it. I hope you're right. Didn't you mic you right, actually? Yeah, but I'm personally thinking you're all right. Thank you. Abundance for all. Yeah. That's the goal. Shall we? All right. We're now putting a lot of time into trips. You are personally? Yeah. Yeah. It's always in the AI system. What's that? With some AI assistants, I assume, the design. Not enough. I mean, I speak just to hand it over to the AI. Soon enough. Yeah, I tried to do some circuit design, actually, with AI recently, just a couple of weeks ago, not happening yet. Very soon, though. Yeah. I think probably at this point, if you took a photo and submitted it to GROC, it could probably tell you if the circuit is somewhere with it. Yeah. All right. I'm going to give it a shot. You're using the same GROC that I'm using? Are you-- GROC keeps updating. Yeah. 4.2. But five is Q1. Yeah. 4.2 is not been released yet externally. But yeah, I mean, if you just to upload an image into GROC, it's just quite a good job of analyzing any given image. Absolutely. Let's start. Well, we're going to talk about this. All right. We'll come back. Let's see if I take a picture of you. What is it? Yeah, what's it going to say about me? Yeah. It's going to say you're a flawed circuit. I also have to update it because we update the GROC app so frequently. You know, I asked GROC to roast me. Oh, it's been a good job. It did an amazing job. Then I asked GROC to roast you. Yes. And I spit out my coffee. It was hilarious. And then I asked it, you know, say, be more of all. It just keeps the tongue. It's to be more of all. I asked. Until until it's like brother of God. Is bad Rudy still out there? Did that get repealed? Bad Rudy still there? And I asked GROC. Yeah. Doesn't he want to know what you say about him? And she goes, it's a she for me. She goes, what is he going to do about it? What's he going to do about it? Yeah. Let's see. Um, so I just literally took a photo of him. Yeah. And see what it is. Did you ask a question? No. Nothing. I didn't say anything. This man is hugely. This, this, this. This, this is pure diamandas. Yes. Okay. That's pretty good. Yeah. That's great. Context whatsoever. The host of the podcast moonshots. Yeah. Sometimes. That's your first credential now. That's amazing. Forget about everything. I was in life. See it comes back to your podcast. It was a note. No context image. Yeah. Awesome. Okay. Right. I mean, just phenomenal. I mean, just, it's like, I tried to like update my Wikipedia page for like years, impossibly. And yeah, it, it, it knows me. Amazing. Yeah. Um, he's wearing a black quilted jacket, featuring a Sundance logo. Not quite true. It's my London logo. It's a little wrinkle. I guess a little wrinkle. I couldn't see the. Yeah. Can you see it? I think so. Okay. Anyway. Um, yeah, but it basically, uh, it's pretty damn good. Yeah. Um, he's smiling and relaxed with a laptop in front of him. Yeah. It's true. Yeah. That's true. Um. Yeah. Well, I see. It was quite a circuit, though. I'm going to test it on this. Roast him. It has to be read by you, though. I mean, I wouldn't read the whole thing, but. All right. Give me a taste. I can take it. Okay. Check out that grin. Dude, smiling like you just discovered a new way to monetize hope. I'm monetizing hope. Yes. I want to try and answer the question, can AI and tech help save American the world, right? I want to give people listening a dose of optimism. There was a survey done in mid-December by a pew that said 45% of Americans would rather live in the past. And only 14% said they'd rather live in the future, which is insane to me, right? Um, obviously they never read history. The challenge is most Americans, all they have of the future, it's like Hollywood has shown us killer AI's and rogue robots, right? And people are worried about their jobs, they're worried about healthcare, they're worried about, you know, the cost of living. The challenge is how do we, how do we help people? I mean, you posted, you pinned on X, the future is going to be amazing with AI and robots enabling sustainable abundance. I was thinking of you when I did that. Thank you. I appreciate that. Yeah, yeah, yeah. And, uh, well, I mean, I was like, well, what would be a demon to say? Yeah. And that's what was channeling you. Thank you. Thank you. I couldn't agree more. Yeah, yeah. I know. I know. So, so my question is from a, you know, from a first principle standpoint. Yeah. Uh, the rationale for optimism, you know, how do we, how do we head towards Star Trek and not terminator? Right? How do we, how do we head towards runberry, not Cameron? Yeah. Jim. Jim. The, uh, how do we go towards the diverging path meme? Yes. It is. It is. Uh, avatar has some hopeful parts. But anyway, yeah. I mean, how do we go towards universal high income instead of social unrest? So, uh, one or both, no, no, we don't want to go to social unrest. Yeah. So, I have universal high income and social unrest. That's my prediction. Oh, that will make for a lot of problems. Is that your actual prediction? Yeah. Yeah, it seems likely. Yeah. I'm like, tell me I'm wrong. I have to push back on it. Yeah. Exactly. But it sounds like that's the trend. Yeah, yeah, totally. No, we have. Well, because there's going to be so much change. Yeah, exactly. It's going to be, like, it's, it's scarred, chilis. Yeah. It's, it's sort of the, um, you know, um, it's like, be careful what you wish for because you might get it. Yeah. Yeah. Now, if you, if you actually get all the stuff you want, is that actually the future you want? Yeah. Um, because it means that your job won't be, what matter? If you're living an unchallenged life, yes, right? No challenges, yeah, no, you know, you know, if you become a couch potato, if it's the Wally future, it does not go well for humans. Well, and we're used to being told, here's your challenge. Yeah. So people haven't historically been very good at creating their own challenge in the absence itself. I think Elon does a damn good job every time he, every time one company takes off, you start your next. Oh, that's, that's rare. A level of accomplishment. I think you are. Yeah. Yeah. I think you over thank God for that. It's like, why do I do this to myself? Actually, after AI and robots, is there another thing after that? I guess there's, well, there's a lot of space, conquering, you know, the universe. Yeah. There's that rock. Well, energy rocks at your friend's, so good to need to get there. Why, Elon, why are you so optimistic? Are you optimistic? Let's start there. I'm not as optimistic as you are. Okay. Um, but why are you optimistic than most people? Yeah. Um, and is the trend upward compared to a year ago, two years ago? Well, I think if you reframe things in terms of, um, progress bar, like speaking of challenges, yeah, progress towards a car to shift to scale civilization. Sure. Um, well, let's say, let's say the aspiration, capturing all the energy from the sun's output, well, let's even have a, uh, humblers, humblers aspiration than that. If we say that our goal is to even get a millionth of the sun's energy, that would be more than a thousand times as much energy as it could possibly be produced on Earth. So about a half a billionth of the sun's energy reaches Earth. Um, so you'd have to go up three orders of magnitude from that, uh, just to get to a million. Yeah. Um, so we're very, very, very far from even having a billionth of the sun's energy, uh, harness in any way. So a reasonable goal would be try to get to a millionth and if you try to get to a millionth, or a thousandth, um, you know, 0.1%, uh, that's, that's such an enormous, uh, but there's not sure what metaphor we're doing here, but he'll decline is, is not a, hmm, you know, probably, it's like a not a big enough metaphor for gravity well to, yeah, it's a whole of gravity well. Exactly. Um, so if, if you try to get to a millionth of the sun's energy or a thousandth, the sun's energy, like now these are very, very difficult tasks and energy is the inner loop for everything right now. Yeah. I think, like, I think, uh, the future currency will essentially just be wattage. Yeah. I was thinking is it, is it, is, is the ability of a person to control energy and compute or just energy? I mean, the two, or the two translated, obviously, just like, honest energy. Yeah. So, or, like, basically, how much power is being turned into work of some kind, right, um, intelligence or, um, math and manipulation? Um, so that's your next big project is going to be energy. It's, it's going to be, you're going to go back to your solar, your solar system. You can expand from there and say, okay, what about even getting somewhere on a, on a cottage of three scale, meaning galaxy level, um, now we're back to Star Trek. Yeah. Expand horizons here. Yes. Well, there isn't even a horizon, because you know, on our planet. So, uh, we, we talk about, so, so if you think galaxy mind, yeah, well, we're in 11, 11.5 million square foot, three pentagons right here in this building, yeah, you think in a reasonably large scale. What is magnitude? Yeah. Um, so, I mean, so from a challenge standpoint, I guess the civil, as a civilizational challenge will be, how do you climb the orders of magnitude in energy, honest, but we're going back to why you optimistic right now. I mean, when people think about, uh, the challenges ahead, I think we're going to end up with abundance in the long run. It's beyond, beyond abundance in any, beyond what people possibly could think of as abundance. Um, but like the AI actually, AI and robots, the limit, um, well, we'll saturate all human desire. So, um, and we get to nanotechnology, which takes it even a step further. Um, the thing about the net, well, I'm not sure what do you mean by not, not mean like the little nanobots. Atomic resumble. Yeah, for how? Yeah, yeah, sure, sure. Um, I mean, we're already doing atomic level assembly on the, for circuits, you know, amazing. Um, two, three nanometers. Yeah, it's, it's only, um, depending on how they're arrayed, uh, 405 silicon atoms per nanometer. Yeah. So those are big atoms, though. Yeah. They're not big. Yeah. They're not your little. I mean, but I'm saying you, you could, they should actually describe the circuits in terms of an integer number of atoms in a specific place. They should. They should. It's the Langstroms now. But it, it's like, it's like, it's, it's like the, we'll call this the, the, the seven atom. Yeah. Yeah. Like we say two nanometers. It's like, it's like no one knows. Yeah. Nine silicon atoms. Something like that. Um, they've got silicon and copper and, um, you know, so, but a bunch of these things are just marketing numbers. Like the two nanometer is just a marketing number. Oh, yeah. But, but you still need, essentially, close to atomic level precision, like the atoms really need to be in the right spot. Um, so, um, I think they get in clean rooms wrong, by the way, in these modern facts. Um, I'm going to, I'm going to make a bet here. Okay. Okay. Um, that's, Tesla will have a two nanometer fab and I can, I can eat a cheeseburger and smoke a cigar in the fat. Come on. Yes. The air handling will be that good. Okay. Do you have this sketched out in your mind, like, how is it, how are the atoms being placed, that they're immune to, uh, cheeseburger grease, uh, they're just, uh, maintained wear for isolation the entire time, um, which is actually the default for four fabs. The wafer is a transported, um, in boxes of pure nitrogen gas, you know, uh, under a slight positive. You know, so are the bananas at Walmart, I, just so, you know, yeah, well, that's, that's, it's essentially, like, it's pretty hard for anything that's combusting. Uh, to live without oxygen, yep. So, um, but let's talk about, so you like, like, you can kill the bugs just by putting an nitrogen blanket. Oh, interesting. Yeah. Interesting. I want to talk about, uh, energy, health, education, because those are people's, you know, concerns. So on the energy front, um, the innermost loop of everything that you're building and, and doing right now. Energy is the foundation. What's your vision for energy abundance, uh, in, in, in the next, you know, this, this decade, the sun. Yeah. I mean, it's everything. It's everything. So you're all in unsold. Uh, I mean, yeah. I mean, you're natural. You're natural gas and solar at your, at colossus, too, right? Yeah. People understand how that solar is everything. So, um, everything, compared to the sun, all other energy sources are like, uh, caveman throwing some tweaks into a fire. Yeah. So, the, the sun is over 99.8% of all mass in the solar system. Uh, Jupiter is around, uh, 0.1% of the mass, uh, so even if you burnt Jupiter, the energy produced by the sun was still around up to 100%. Yeah. And then if you teleported three more Jupiter's entire solar system and burnt them, too, it's still around up. It's still around, the sun still runs up to 100% of energy. Any interest in fusion? I mean, like, non-susion on the planet, fusion on Earth, you know what, you know what, you know what I'm saying. You know what I'm saying? I mean, like, like, non-susion on the planet. I mean, like, non-susion on the planet. Um, I mean, that would be like, you know, having a tiny ice cube maker in the Antarctic. Hey, look, we made ice, I'm like, congratulations, even the fucking Antarctic. So totally, it's only with you on this, it's like, it's like, three kilometer high glaciers right next to you. Yeah, sure. But if you just narrow the question to the Memphis timeline, so Memphis Data Center timeline between a gigawatt and 10 gigawatt, you're not going to pull 10 gigawatts out of Memphis. Maybe you are. Two or three. Two or three? Okay. So there's still a gap between there and the next whatever, you know, just from that. Yeah. And they're not in space yet at that point. So we're still in Toiland here, uh, for our energy. Toiland? Toiland, you say? Toiland, toiland. 10 gigawatts. You know what's amazing is there's 100 megawatts right outside the door here. Yeah. And it's massive. It's enormous. Yeah. And it uses more energy than everything, all these manufacturing lines combined use less energy than that. I think we're talking about that a lot. But we're talking about the gigawatt. We're talking about the gigawatt. Everybody, you may not know this, but I've got an incredible research team. And every week, myself, my research team study the metatrends that are impacting the world. Topics like computation, sensors, networks, AI robotics, 3D printing, synthetic biology. And these metatrend reports I put out once a week, enabling you to see the future 10 years ahead of anybody else. If you'd like to get access to the Metatrends newsletter every week, go to deamandis.com/metatrends. So going back to what Dave is saying, over the next five years, what are you scaling on energy front? I mean, China has done an incredible job, running circles around us. China has done an incredible job on solar. It's amazing. So I believe China's production capacity is around 1,500 gigawatts per year. They put in 500 terawatts in the last year, 10 to 1 terawatt hours, 500 terawatt hours to be very specific in the last year, 70 percent of that was solar. And they're just scaling. could make that level of investment and commitment because people are worried about their energy bills going up with no data centers in our backyard. What do we provide? I mean, energy is equivalent to cost of living, it's equivalent to health, it's equivalent to clean water, the higher energy production of a country, the higher GDP, energy is important. So what do we do to scale that way? Do we do it in solar here? I think we should scale solar substantially in the U.S. Tesla and SpaceX are scaling solar, and I encourage others to do so as well. So I've said the stuff publicly, I do see a path to 100 gigawatts a year of solar power. Solar power AI satellites. Yes, 100 gigawatts a year of solar power AI satellites. I did the math on that. It's like 500,000 Starlink V3s launched over 8,000 starship flights, like one every hour. For a year. Yeah, 10,000 flights a year is a reasonable number. So it's amazing, it's quite the scale. What's the time? It's a really rough timeline on that because by aircraft standards, that's a small number. Sure. For sure. Yeah, that's a small fry. So it just depends where you compare it to. If you compare it to the rest of the rocket industry, it's a very high number. And we're talking about a million tons of payload to over per year. So if you do a million tons of payload to over per year with 100 kilowatts per ton, 100 gigawatts of solar power AI satellites per year. I mean, there's a path to get probably to a terawatt per year from the first year. If you say like 10, you want to go up another order of magnitude or let's say you want to go to 100 terawatts a year, so obviously, kind of 90 numbers, then you want to make those AI satellites on the moon and use a mass driver. Yeah, so the Gerard K. O'Neill approach. Well, like Robert Heinlein, who is a hot star, of course, I love that book. Yeah, yeah. It's a sort of libertarian paradise in the world. Yeah, so because on the moon, you can just accelerate the satellites into two escape velocities around 25 meter per second. And there's no atmosphere. So like a mass driver works very well on the moon. Can I ask the question about orbital debris? I mean, we're building effectively a dissonish swarm around the earth. Swarm? Yeah, swarm. Swarm. Swarm. Swarm. Swarm. Swarm. Swarm. Swarm. Swarm. Swarm. Swarm. Swarm. Swarm. Swarm. Are you worried about over congestion on the Sunsink orbits going to feel very quickly? I mean, you don't have to have Sunsink. I mean, you can-- Don't have to. But it's optimal. Yeah. There's some pros and cons to Sunsink or not Sunsink. I mean, you'll be a parallel to orbit drops by like 30 percent compared to, you know, if you were just went to like a minute inclination, like 70 degrees or something like that. I mean, do we need an orbital debris x-price at this point? We need some way to get the satellites to find satellites down. Do we pass rules that require them to deorbit on their own? Yeah. At the point where you can put a million times of satellites into orbit, you can also, you know, brist up bringing down satellites too. Or at least collecting them into a known, into a fixed location so they're not like all over the place. Yeah, they can reuse them. Yeah. Let's just say that we'll have-- the resource level will be so high that I believe this will be a solved problem given the amount of intelligence we're talking about here. Like the intelligence would be quite interested in preserving itself. Yes. That's true. Interesting. I think the data centers will not be in lower orbit, right? They'll be much higher constantly in the sun. They're not going to be in the traffic jam, I assume. Well, you can get, you know, you don't have to get to get to cons in some lights. You can be around 1,200 kilometers sun synchronous will give you costs in some light. But you could, you could place them in multiple orbits. Yeah. Yeah. Yeah. No, I think if there's an x-price for cleaning up, it's got to be, there's only going to be clutter in lower orbit. I mean, debris from anything that's-- if it's a, you know, below around 7 or 800 kilometers, the atmosphere will-- atmospheric drag will bring it back. Yeah. So like for stalling, there's a dual benefit of being, like as low as possible, because you're being-- you know, your beams are tighter, you know, you're basically that you have less latency and your beams are smaller if you're, you know, closer to the earth. So like stalling three will be around 330 to 350 kilometers, which is quite a lot of drag. So it's basically constantly thrusting today. I still remember when you proposed Starlink and everybody else in the industry was like, no way. Uh-huh. No way. He's not going to get the spectrum. He's not going to be able to do this. Yeah. Uh, it's kind of worked. Yeah. We're stalling Timothy on an incredible job. Yeah. Um, I mean, we're basically re-built the internet and space with a laser links. So there's, uh, 9,000 satellites up there now. Do you think the government's going to be able to, um, handle the kind of licensing of the volume of satellites that you want to put up? I mean, will there be pushback because, you know, China's going to put up their own constellations, uh, Europe, who knows whether Europe will ever step up? They won't. What's that? They won't. Now there's a probability. Yeah. Nothing that, nothing they're doing has success in the set of possible outcomes. Yeah. Okay. I just got back from my own, I don't want to touch that rail. Success is on the set of possible outcomes. The chart shows the number of billion dollar startups in the U.S. versus Europe. Have you seen that graphically? Oh, my God. It's crazy. Yeah. And data centers too. No one was talking about orbital data centers six months ago. Yeah. Yeah. Nobody. And then all of a sudden, some buyers on it, you're, you're out with it and, uh, it's the hot new thing. It is. What? What what happened, what happened that every company is now talking about orbital data centers? I guess it went viral in X. I don't know. Is every company talking? Oh, yeah. Everybody's got their own orbital data. Oh, for sure. And I was suggesting to Peter that you updated the math on launch costs and that it's a tipping point very quickly with the updated math. But the starship's been the cost for, you know, I don't know what you hold. The $100 per kilogram, $10 per kilogram. What do you have starship? Well, it's possible that Elon said that and nobody believed it until now. No. You can go back and look at my, what even back when I was Twitter, uh, they're my old tweets. I said these things set many years ago. 100 bucks or 10 bucks a kilogram? Yeah. I know. And I said, this is, we're, we're going to do a million tons a year to old, but, um, yeah. And we've, we've got to get the, the cost down, yeah, uh, well below $100 per kilogram. So that's going to move the data centers to orbit. I really will. It's as they can do. You can basically do the math, where like if you've got a fully reusable rocket, um, which is fully and rapidly reusable, like an aircraft, um, and this is an incredible, this is a very difficult thing to do. Obviously, um, I think it's at the limit of human intelligence to create a fully and rapidly reusable rocket, um, but it is possible and we're doing it with such a, it's been the holy grail in the aerospace industry forever. Yeah. Quest for the holy grail rocket. Yeah. And then I, I mean, yeah, I mean, right now, the DCX was the first little things that were trying there. And, uh, it's been, you know, all of, I mean, back when I was in the space industry, that's all everyone ever spoke about. And then when Falcon 9 first reused its first stage, um, I mean, all the traditional aerospace industries did not believe that even Falcon 9 could re could fly and reused. Literally, you can come see it land at Cape Canaveral, um, and then take off a game. Yeah. So I don't know how you would not believe a thing that you can see with your own eyes. Yeah. Well, they didn't believe you could do it. Well, but the, the, the, the, the leap from there to the launch cost actually requires more faith than just, just that, but I think, I think Starship is the launch cost tipping point. And that's somewhere in that, you know, before you had Twitter, it became X, somewhere in that timeline, it went from speculative to no doubt. And I don't know if that's a smooth line or a couple of good launches in between, but I suspect that the data centers in space, but people ties directly to the credibility is not thinking about orbital data centers or thinking about energy, the cost of energy here on here in their hometown. And sort of the, the, there's a lot of doomer conversations out there. The data centers are going to drive, you know, the CPI up, uh, they're not entirely wrong. Okay, so what is, so what is the, what's the energy solution here on earth for, uh, the rest of humanity or the, the non data, the non-AI is something other than data center uses of energy. Okay. All right. That's complex. Well, the, the, the best way to actually increase the energy output per year of the United States or any country is batteries. So the peak power output of the, of the US is around 1.1 terawatts, but the average car usage is only half a terawatt. Yeah. So if you just buffer the, the energy, so charge up the, the batteries at night, discharge during the day, um, without incremental capital expenditure, without incremental capital expenditures. But building your power plants, you can double the energy throughput of the US, the energy output per year, can double with batteries. And do we have those batteries in development? Uh, yeah. Tesla makes them. Okay. So you think it's like a current, current Tesla battery packs. What do you think? What do you think? What do you think? I literally have. I, I, I, I, I, you're presented the thing. Yeah. That's, that's the dead giveaway. So. So. I, I even went to installations of the mega packs, you know, and there's, so why don't people do this? On the internet. So, yeah. So is, do you think they are in, and China, by the way, is, like, it, it seems like trying to listen to everything I say and does, does it basically or at least, or, or they're just doing it independently. I don't know. But they're, they're certainly making, um, massive battery packs, like, but really massive battery pack output, they're, you know, making vast numbers of electric cars, uh, vast amounts of solar, uh, we know, I don't know, these are all things I said, you know, we should do here. 100 minutes. Sure. When I fly over Santa Monica and L.A., when I'm, when I'm piloting, and I look down, they're like zero roofs have solar on them. Zero roofs. Yeah. I mean, it's not essential to have them on a roof. Okay. But it's a convenient place to have them. Yes. But the surface area of roofs is, uh, I'm not saying it shouldn't, but it's, yeah. Uh, it tells them, it makes a solar roof, which is the, the only solar roof that isn't ugly. Um, so, so, solar roof actually looks beautiful. Yeah. Um, but if you want to do solar at scale, you just need more service area. So, so we, we, we have, um, vast empty deserts, sure, in America, like if you fly from L.A. to New York or just fly across country, and you look down, um, for a large portion of the time you look down, it is bleak desert. Yes. It looks like Mars essentially. We're not worried about overpopulation there. No, I mean, it looked as barely a lizard alive in these scorching deserts, you know? Yep. It's not like farmland we're talking about. We're just talking about, you know, uh, places that look like Mars, like just, uh, scorched rock. So if we put solar where we currently have scorched rock, I think this will be a quality of life improvement for the lizards or the few creatures that live in this, uh, very difficult environment. We have to distribute it. It's like lizards going to be a thank-ah to some shade. Finally. Uh, do we have the distribution network to do that? Yeah. You need to, to materially affect quality of life. You need to capture and store what a couple hundred gigawatts. Is that in the realistic, just put the data center, I guess, locally there. Well, we already covered data centers. We're talking about, you know, the other, yeah, like I don't know, like in an abundant world five years from now, massive amounts of compute, massive, you know, universal high income. I don't know what our data, universal, you can have whatever you want income. Yeah. Yeah. That's really what it amounts to. But in that world, uh, you know, other than compute energy, how much more energy do we need? Like 30, 40, 50% or I don't know unless we want to move mountains around and make a ski mountain, you know, in the backyard, um, I think the vast majority of energy consumption will go into compute. And then there may be use cases I'm not thinking of like, you know, the, well, you know, right here is a nice case study because manufacturing every one of these cars coming out at the rate of one every minute or two, uh, is less energy than the data center that's training the cars to drive, to self drive. Yes. So that's a good little case study. You don't need that much more physical energy for abundant happiness. We need more compute energy. Well, the sun is just generating vast amounts of energy, uh, all the time for free that goes just goes into space. So, um, I think we're going to try to capture, I don't know, uh, a millionth of it, like say a millionth of thousands of the sun's energy, um, recurrently, I don't much the exact number, but we're, I don't know, we're probably at 1% ish of carotage of level one. Fair enough. Yeah. I, I, I, I guess that evens that's high. I'm just saying maybe a long way to go. That's being optimistic. Yeah. Like, hopefully we're not 0.1%. But I don't think we're 10%, I'm just trying to get it to like, what are, what are the things? Yeah, so pull it like we're roughly 1% of the, I'm hardly using 1% of the energy that we could use. So from, I think the bottom line from our first principles, thinking for the public is there's a lot of energy out there and it, we have it in the US. We have it on the planet and it needs to be captured and the tech to capture it is here and improving every year. Yes. Yeah. Um, but there's not going to be some energy crisis. There'll be a large forcing function to harness more energy, but we're not going to run out of it. All right. I want to talk about education. So here's the numbers. They're abysmal. I mean, they're, they're abysmal, right? Okay. And the importance of college in the United States back in 2010, 75% of Americans said it's important to go to college. That number is now down at 35%. All right. Uh, college graduates as a group turn out to be the group that's out of work the longest. Right? Just fairly. And it, but still, and tuition is increased 900% since 1983. Um, yeah. The administrative expenses at universities have gotten out of control. Yep. Um, so I think I saw some stat that like there's, uh, one administrator for every two students at Brown or something like that. And I'm like, this seems a little high. Yeah. They should teach you. They should teach something. Yeah. Yeah. What was your college journey? Um, I went to college in Canada for a couple of years at Queens University. Uh, um, so, uh, I had Canadian citizenship through my mom who was born in Canada and my grandfather was actually American, but for some reason, I don't know if my mom couldn't get US citizenship. So, but she was born in Canada, so I got Canadian citizenship, um, and, uh, I don't have any money. So I could only go to Canadian University at first. I mean, people forget that about you. You didn't have this giant social network or huge amount of wealth coming into all of this. No. Yeah. Uh, no, I arrived in Montreal at age 17 with, I think around $2,500 in Canadian travelers tracks, background travelers checks were a thing, um, and, um, one bag of books and one bag of clothes. That was my starting point. That was my spawn point in North America, um, all right. And then I, so I went to Queens University for a couple of years and then, uh, University of Pennsylvania, uh, did adult degree in physics and economics, uh, and graduated. Uh, undergraduate at U Penn, you've been warden, yeah, and then, um, I came out to do, uh, I was going to do a PhD at Stanford, working on, uh, energy storage technologies for electric vehicles, potentially material science, I guess, fundamentally. Um, the idea that I had was, it was to try to create a capacitor with enough energy density that you could get, um, high range in an electric car. That's funny, I invested in an ultra capacitor company and didn't, yeah, didn't go well. Well, it's one of those things where, you know, you could definitely get a PhD, but, um, it wasn't clear that you could make a company or do something useful. Like this, most PhDs, I mean, hates it, but most PhDs do not turn into something that's good. Do not turn into something useful. Like you, you could add a leaf to the tree of knowledge, but it's not necessarily a useful leaf. The enormous fraction of, of great entrepreneurs are dropping out of grads to a lure undergrad, but nowadays, the sense of urgency is off the charts. I mean, they're popping out everywhere. Yeah, because, you know, don't waste your time going to grad school, start a company. Curriculum is nowhere near a cut up to what's actually going on in technology, and I don't have time. And, you know, it's like, you know, this is the moment. I think this is the moment. It's like, it's all clear to me why some of the, uh, somebody would be in college right now. It's like a social experience. Yeah. Yeah. I mean, if you have the ability to go and build something, so the question is, how would you redesign the educational program if I could so blunt as to create more Elon Musk's? You know, if you want to create an Elon Musk factory of people who start with very little, but are able to drive, uh, and drive breakthroughs, what's involved there? What drove you? Accuriosity, um, about the nature of the universe. I'm curious about, uh, the many of life and, you know, what is this reality that we live in? So, how early, my son, DAX wanted to know, what was it like for you in middle school and high school? He's 14 years old, he's in that age range now. Well, I did, I found school to be quite painful, um, and it was very boring. And it's how that figure was very violent. So, so it's like, it was like, uh, it's like that was like that book, "Energy Game." Yes. Um, but in survival, IRL, in this game, IRL is like, but not as fun, um, so your goal was escape. Yes. And do you escape from the, the prison, so that's the question I have, do you think that it was miserable? Do you think most successful people have had, uh, a lot of hardship early in life? Do you need to have that level of hardship? Probably need a little bit of hardship, by suppose, you know, and then so it's always tricky. Like what are you supposed to do with your kids, you know, create an artificial adversity? Put them in the room. That's cool. And yeah. Yeah, that's very, that's, that's a Warren Buffett topic, actually, yeah, which is what you do. But it's not easy to create artificial adversity, because if you love your kids, you don't want to do that. Yeah. That's true. Um, so I had a lot of adversity, um, probably it was good, uh, probably, you know, helped somewhat, I suppose, one of the things that can kill you makes you stronger than I was saying. No. At least I didn't lose a limb. I, I think what doesn't mean you. But I mean, you know, 10 to 10 fingers, you can modify that a little bit. Yeah. Questioning you makes you stronger, uh, for the last five years, I've been helping teach this class foundations of AI ventures at MIT. And every year when you survey the students, they go up a lot in their desire to start a company. And so it's now up to 80% of the incoming support, everyone's just going to, it's, it's, it's just going to be like one person company. Well, that's what they, that's, that's viable, I guess. But no, they want a co-found, they, yeah, they don't want to be the founder. They want to be part of a founding team. So it still works out. But, uh, when Peter and I were in school at MIT, it was, I'm guessing maybe 10%. And they all want to be entities and, and they've been doing the survey, you know, everyone who wanted to start, I mean, yeah, I, I, I don't remember any conversations about with people saying they wanted to start. Even at Stanford at the time. Um, I, I, I actually, um, a few days into the semester, or I said a quarter, um, I, I called Bill Nix, who was at a material science department and said, I'd, I'd like to just put it on deferment. So it was my class of that bad. No, I need, he said, he said that's, he said that's okay. He can put it on deferment. And he said, this is probably the last conversation we'll have. And he was right. Um, but then last, last, I think it was last year he sent me a letter saying that all of my predictions about lithium ion batteries came true. And then he also said, you could still come back and finish your PhD. Yeah. No, it was several times. Stanford has said that I can come back for free. Well, so you know what happened at MIT is every time, so I did not know, it'd be a great user your time. Exactly. Oh, like, uh, yeah. So every time an Iron Man movie came out, it notched up another probably ten percent or so. Okay. Uh, in terms of everybody wanted to be Tony Stark. And so that's the image and I didn't know until today that the new Tony Stark, the modern Iron Man, Tony Stark. I always thought Tony Stark was modeled on Charles Stark Draper and Howard Hughes as Charles Stark Draper's education and his, you know, scientific endeavor is married with Howard Hughes's ambition and that created the original character. But then when Robert Downey Jr. wanted to reinvent it, yeah, it came modeled on Elon. Yeah. This is like with me. Like a Grocca PD effect, all right, uh, yeah, fantastic. Um, yeah. So they came to you to do it and Robert, I like the name Grocca, I would like Jarvis as well. Yeah. Yeah. Um, probably some some trade. Well, at some point if Grocca gets good enough, we're gonna call it encyclopedia galactica. Yes, that's nice. Yeah. Yeah. Of course. 42. Thank you. Um, so going back to education, uh, should colleges, I guess the social experience they said is important there, but what would you do for education, uh, you know, middle high school? You just came back from an announcement with President Bukheli, uh, who's a friend I think is an amazing, amazing visionary, yeah, incredible way he did it with his nation. Yeah. Yeah. Um, remarkable. Remarkable. And gutsy. Yeah. I was like, how are you still alive? Yeah. I mean, I, it was like, uh, it's the nuclear, it was a nuclear option. Right. Yeah. I mean, you know how besides putting everybody with a gang sign, um, in, in, in jail, I don't know if you know the second thing he did, he went to all of the graves of all the gang members out there and destroyed the graves and said your memory will not be remembered in this nation. That's just badass. Hmm. And it worked. I mean, you have to be badass motherfucker to take on old and awkward gangs and one and live. Yeah. That's still be alive. He's got a great, great guard at his palace there. But what, what did you announce with, uh, with him in the Salvador? Uh, it was just, uh, basically to use Grock for, uh, education. Like, trust me. Hopefully not the vulgar version of it. Yeah. Like, you know, the kids friendly version of Grock, uh, but, but obviously I can be an, an individualized teacher, um, that, uh, is infinitely patient and answers all your questions. Um, I still need to be curious, um, and, and, uh, you still need to want to learn. You know, Grock can't make you want to learn. You can, you can make learning more interesting, you could probably game a fine and incentivize it, right? You can make learning more interesting, um, and, and less of a production line. Um, so, but kids do need to have to, if they need to want to learn, you know, um, so I, and, and like, people should just think of the, the brain as a biological computer. Uh, it's neural net. Yeah, it's a biological computer with, uh, you know, so, with a number of neurons and that's a neural efficiency, um, and, um, so, so what, like what you can't do is tune any arbitrary key to Einstein, uh, this is true, realistic because Einstein had a very good meat computer, like an outstanding meat computer. Um, so you can't just, uh, do Shakespeare Newton, you know, Einstein type of thing, um, unless the meat computer is, uh, an exceptional one. Mm-hmm. So, what do you think, so when people say we need to solve education in the United States, um, because it's fundamentally broken, uh, I think what's really broken, I'm curious, is the old, uh, social contract that says, uh, do well in high school, get a good college, get a degree, and then get a job. And I don't know that that's going to be valid in the future. Um, uh, might, we talk about this on the pod a lot, that the, that the career of the future isn't getting a job. It's being an entrepreneur. It's finding a problem and solving it. Yeah. Do you agree with that? Right now I'd say it feels just, you know, go to school for the social experience, use more AI. Um, I think the conventional schooling experience, I think, could be a lot better. Um, this, what, what we're going to do and I'll solve it over hopefully other places just have individualized teachers, it, it's going to be much better. And you, you could go to, you could go to a school with a bunch of other kids. I guess if you want to hang out with other kids, but you don't need to, right? You could do it on your phone at home. Um, so that's why I say like at this point, education is a social experience. When I talk to my kids who are in college, uh, they, they, they do recognize that they can learn, um, just as much, independently, in fact, that they would learn more in, in a work situation. Yeah. Um, they're there for the social experience and to be around a bunch of people of their, their own age, um, sort of a coming of age, social experience. Sure. Sure. Being on your own, uh, learning how to, how to lead or defend yourself as a case maybe. Well, yeah. I mean, if you join the workforce, you're, you know, from this perspective of like, uh, you know, 19 year old, you know, with a bunch of old people, and if you're doing engineering with a bunch of middle aged dudes, it's like, do you really want to do that or do you want to hang out with, um, you know, with, with this, at least some girls who are age type of thing. Uh, I want to get back to this when we talk about a lot of other choices, actually. I want to get back to as we get to universal high income, but I want to help in line job 91 second US is the number one ranked number one in health expenses worldwide. And it's ranked 70th in health span, right? We're really 70th. 70th. Is that a truck? Is that accurate? It's right. Why don't everybody? Everybody listen to this. Sounds low. Uh, I think it would be better than 70th for health span. Um, yeah. Well, whatever. It's, it's, it's like we just get fat or something. We're not the top 10. We can help us find the rankings there. Um, so you just run around with, we, we need Cupid with a Zampic. Uh, we're just, um, Mujaro Cupid, but I think that's a big reason it's like if people get really fat, then their, their health gets bad. Yeah. Well, if they don't have any exercise health, good, bad or if they don't, it's for breakfast every morning. You still doing that? Uh, no. Actually, I'm not. Okay. That's good. Uh, uh, first of all, I wasn't eating a lot of doughnut. I was trying to have, uh, point four of a doughnut which rounds down to zero. Uh, so I figured I think blow, blow point four four of a doughnut rounds down to zero. So you and I have had, uh, uh, disagreement on longevity a little bit. Yeah. I was saying, you know, uh, we should push to get people to 120, 150 and you were saying people, you know, died, shouldn't live at all. So it's how long do you want? Yeah. You know, there's some, you know, people in the world that have done some bad things. How long do you want them to live? Yeah. Well, it's okay. They can take the long journey. This is a serious question. I think them. Uh, a lot of things are going to happen that we don't, you said, one thing that you said was interesting. You said, um, uh, we need people to die. So people change their minds. Oh, yes. And people don't change their minds. They just stop. Yeah. So that makes more sense, actually, my response to that, you know, my response that was the head of GM didn't have to die for Tesla to come along and Lockheed and Northrop and Boeing didn't have to go away for, I mean, there's, in a meritocracy, the better ideas will dominate. So I'm hoping that I can get you back onto the longevity train. So there's a lot going on on longevity right now. Right. Uh, like what? Well, David Sinclair is about to start his epigenic reprogramming trials in humans. It's worked in, in animals and, and nonhuman primates. It's going into how to human cycle pole or an injection right now. It's an injection of it. Add no associated virus. It's, uh, the three Ammonocca factors. Okay. Uh, we've got a 101 million dollar health span X prize that's working on 730 teams working on reversing the age of your brain immune system and muscle by 20 years. By the way, you know why it's 101 million dollars because the primary funder when they found out your carbon exprisal 100 bucks, he wanted to make it bigger. So it's 101. Oh, who is it? It was it was Chip Wilson from Lululemon and then, uh, and then have a solution out of, but chips. We make it bigger. I said you put extra million and we'll make 101 million. Sounds good. Sounds good. We got folks like Daria Amade, predicting doubling the human lifespan in the next 10 years. Um, that's probably correct. Okay. Great. I don't know about doubling, but it's significant. It's significant. Sure. Um, which is easily escape velocity. I mean, easily. This wouldn't. Yeah. It's been a whole joy. Yeah. Oh, yeah, for sure. Or what? Effective age. Yeah. Yeah. Yeah. We're too much in turn into a baby, so I'm telling all the students that they're, it's like beater. What happened? Yes. Yes. There is a frozen. I've got zero wrong on the dosage. Just a small factor of time. You can't. You can't. You can't. You can't grow out of it. That would be fine. Exactly. You won't remember it. I literally. I mean, it wouldn't be funny. If we do this in like 10 years, okay, we should do it in two. We'll do it. We'll do it in 10 years. For sure. And let's see. Let's see if we look younger. That's a good side that might come, which always, you want back then, you want like, you know, late 40s. Wait till he gets into his 60s, he's going to want, you know, lunch every more. I mean, I, I, I want things to not hurt. Yeah. Sure. Of course. Yeah. It's like, it's like, basically, it's, it seems like it's only a matter of time before you get back pain. Yeah. It's a when not an if when your back roads are arthritis. Yes. Yeah. Like these things suck. Being able to sleep through the night without going to the bathroom. For a lot. Yeah. More than hope. That one. Oh man. That would that's like the infinite money one. Why did you invest in longevity? So I could sleep in the night. I got the battery. The battery. The battery. The battery. Yeah. I mean admittedly, if you have to wear adult diapers, that's a bummer. That's not good. That is a real. You know, it's like one of this, one of the signs that a country is not on the right path. It's when the adult diapers exceed the baby divers. Yeah. We're there. Yeah. Self-career will be there. No, they passed that point. Yeah. They passed that point many years ago. Japan passed the point many years ago. Doesn't go well. Look at the Japanese economy. No, I mean, like South Korea is like 0.7. Yeah. One total replacement rate. Yeah. It's crazy. Yeah. So three generations, they're going to be 127th. So three percent of their current size. Most people won't need to invade. They can just walk across. Yeah. This is going to be some people in one. You know, walkers or something. It's like, don't be a bunch of optimists and robots. But you know, you've been very verbal about the, you know, the not overpopulation, but massive underpopulation. Yeah. It's outrageous. Yeah. Longevity is going to be an important part of that solution. I also think, by the way, if you increased the productive life of most Americans by just a few years, you'd flip the entire economics here. Well, if you're willing to work, AI and robots is going to make everything free, basically. Yeah. But, well, how long would you want to live? I want to go, you know, other planetary systems. I want to go and explore the universe. Yeah. I mean, you know, I would like to double my lifespan for sure. I don't want, you know, I'm not sure I wanted to talk about immortality, but, you know, at least 20, 150 is a long time. One of the worst curses possible would be that, yes, maybe you live forever. Maybe you live forever. Yeah. That would be one of the worst curses you could possibly give anyone. But I think life's going to get very interesting. Far more. We're going to speedrun Star Trek is my partner, Alex Wiesner-Grosses. Yeah. Speedrunning Star Trek would be cool. Yeah. Well, at a minimum, your kids will have infinite life expectancy if you're talking about escape velocity. If you can double lifespan, it's not even close here. You're clearly past longevity, escape velocity. The idea of 50 years of AI improvement. Yeah. I mean, we're going to have that 20 years. I don't know. I've got too many fish to fry. So I invite, this is something, by the way, that I, that I think, I just, I think it's very, obviously other people think this too. But I've long thought that, like, like longevity or semi immortality is an extremely solved problem. I don't think it's a particularly hard problem. I mean, when you consider the fact that your body is extremely synchronized in its age, the clock must be incredibly obvious. Nobody has an old left arm and a young right arm. Right. Why is that? What's keeping them all in sync? Your program to die is the way it would program to die. And so if you change the program, yeah, you will live longer. And we've got, you know, species of the bowhead whale can live for 200 years, the Greenland shark live for 500 years. And when I, when I learned that, I said, why can't they? Why can't we? And I said, it's either a hardware problem or software problem. And we're going to have the tech to solve that. I do believe that it's this next decade. So the important thing is not to die from something stupid before the, before the solutions come. You know, I invited you. In retrospect, the solution to longevity will seem obvious. Yeah, extremely obvious. I think the thing worth working on, Peter is going to work on this anyway, but the thing to work on is exactly what you said. If old ideas don't, calcified old ideas don't just die off. Add that to the pile of things we need to think about today. Because our whole host of other AI related things we need to think about today. Let me finish on the longevity point one second. Elon, I want to invite you again. So there's a company called Fountain Life that created with Tony Robbins, Bob Hurley, Bill Cap. And we do a tuner gigabyte upload of you. Everything knowable about you. Full genome, full all imaging, everything, right. President Bukheli and the first lady came through called it an amazing 10 out of 10 experience. I think I don't want you to pull a Steve Jobs and kick the bucket because of some, because I'm something they didn't know. I mean, so if you ask yourself, do you actually know what's going on inside your body right now? I did an MRI recently and submitted to GROC and it didn't need not. But that's none of the doctors know GROC found anything. But that's a fraction of the information, right. I mean, it's your full genome, your microbiome, pat metabolism, everything. And it's possible. Don't clone me. What's that? Don't clone me, bro. We have a set. We have a center in your water bowl. We have. God damn it. Too late. Sorry. Sorry in the works. So can you go through the rationale of UHR? How does, how does universal high income work? Okay, so there's going to be more intelligence, digital intelligence than all human intelligence combined. And more humanoid robots than all humans. And assuming we're in a benign scenario, Star Trek, so a rotten berry, not Cameron situation. Yeah, poor Jim. Yeah, I mean, I guess it's important to have these sort of counterpoints. Yeah. Let's not, let's not go in that direction thing. So the robots are going to just do whatever you want. All the blue collar labor is being done by robots. All data centers are being done by robots. The, the white collar labor will be the first to go because until you can, until you can move atoms, the thing that can be replaced first is anything that that involves just. Digital digital, like if it involves tapping keys on a keyboard and moving a mouse, the computer can do that. They, I can do that. Sure. You need the humanoid robots to shape atoms. So if all you're doing is changing bits of information, which is why collar work. That is, that is the first thing that that. This is the inspiration, this is the inspirational part of the podcast by when is, when is all white collar work gone by when? Well, there's, there's a lot of inertia. So even with AI at its current state, I'd say you're pretty close to being able to replace half of all jobs. And you know that white collar jobs, that includes anything like education too. So anything that involves information. In anything short of shaping atoms, AI can do probably half or more of those jobs right now. Sure. But there's a lot of inertia. People just keep doing the same, the same thing for quite some time. And there actually has to be a, a company that makes more use of AI that competes with the company that makes less use of AI creating a forcing function for increased use of AI, right? Otherwise, the company that still has humans do things that AI can do will still continue to exist. Being a computer used to be a job. So it used to be that a human computer, like would, like, yeah, a computer being a computer was a job. You would compute numbers. Sure. And then it didn't used to be a machine. It used to be a job description. And there, you can look online. There's these pictures of like where they're having like skyscrapers full of women copying, mostly I mean copying from ledger to ledger into. But yeah, people, what was a lot of women, but there were just buildings full of people just at desks doing calculations. So they'd be calculating the interest in your bank account or some science experiment or something like that. But if you weren't calculations done, people would do it. So now one laptop with a spreadsheet can outperform a skyscraper of several hundred human computers, right, of people doing calculations. Now, if even a few cells in that spreadsheet were done manually, you would not be able to compete with a spreadsheet that was entirely a computer. What this means is that companies that are entirely AI will demolish companies that are not right. It won't be a contest. I agree. That's just one cell in that. I'm going to do that. If you want to do one cell in your spreadsheets to be manually calculated, that would be the most annoying cell in your account. And gets it wrong a bunch of the time. Yeah, so this flippeting, flippeting, flippeting, flippeting, flippeting, flippeting. Are we monetizing hope effectively? Yes. Not this moment. I think we're, I think we're, I think we're, I think we're peak to, but people worried about the future of their jobs. We're monetized. We're at peak doom. We're going to do that. We'll send it to us as a teacher and a mug. But you have a solution to this, which is UHI. Yes, I'm looking to have whatever they want. So how does that work? How does UHI work? It's a good question. Like we have to figure out some, like, I mean, it's not a region. It's not a region. It's about your own. Yeah, I mean, so my concern isn't the long run. Yes, the transition will be bumpy. We humans don't like simultaneously. Yes, we'll have radical change, social unrest, and a man of prosperity. And you can buy all the cyber trucks you want. Things are going to get very cheap. Yes. So this is actually, in fact, if this doesn't happen, we would go bankrupt as a country. So the national debt is enormous. The interest on the national debt exceeds not just the military budget, but the military budget, I think, plus Medicare, or Medicaid, one of the two. It's like, it's like one point of interest, which is growing. Yes. And the deficit is growing. But so if we don't have AI and robots, we're all going to go bankrupt and we're headed for economic doom. We're going back. So competitive pressure from China. So this is definitely going to happen. We're going back to the theme of this talk. How can AI and exponential tech save America and the world? But I want to get I want to hit this because I was quite pessimistic about it. And ultimately I decided to be fatalistic and look on the bright side. And you're always on the bright side of life. But this is not about taxation and redistribution. No, it's. So how does it work? This reason through it with me. Listen, by the way, I'm open to ideas here. Okay. So it's not like I got this. We'll figure it out. All right. So so I'm wondering if it instead of universal high income, if it's universal universal high stuff. Yeah. And services. Yes. The you you HS S. We got it. Like I guess. Okay. This is my guess for how things roll out. Play out. And I. And by the way, I'm. This is this is going to be a bumpy ride. And it's not like I know the answers here. But I have decided to look on the bright side. And I'd like to thank thank you guys for being inspiration in this regard. Thank you. Happy to help. Yeah. I actually think it's it is better to be an optimist and wrong than a pessimist and right. Yes. For quality of life. Now, by the way, there's also not a force of nature. It's under like to me, it's really clear that we don't have any system right now to make this go well. But AI is a critical part of making it go well. And at some point, Grock is going to be addressing this exact topic that we're talking about. That's actually one of the big for AI machine. I mean, it's coming is dealing with it. It's not velocity knob. Right. There's no on off switch. Yes. Which gravy is a little alarming. I think it's good. It's good. Because the world is a wake up call. This is important for folks to to Grock because I don't want to leave people depressed. I want people to understand what's coming. So we're basically demonetizing everything. I mean, labor becomes the cost of CapEx and electricity. AI is basically intelligence available at a diminimous price. So you're able to produce almost anything. Things get down to basic costs of materials and electricity. Right. So people can have whatever stuff they want, whatever services they need. It's not when you say universal high income. It sounds like it's a tax and redistribute, but that's not the case. I think my best guess for how this will manifest is that prices will become prices will drop. So as the efficiency of production or the provision of services drops prices will drop. And prices in dollar terms are the ratio between the output of goods and services and the money supply. Sure. So if your output of goods and services increases fast in the money supply, you will have deflation or vice versa. So it's a good thing we're growing the money supplies so quickly. Yes, that's why I can't like what it's not worry about growing the money supply one matter because the output of goods and services actually will grow fast in the money supply. And I think we'll be in this and this is a prediction. I think some others have made, but I will add to it, which is that that I think governments will will actually be pushing to increase money supply. Like faster, yes, they won't be able to waste the money fast enough, which is saying something. Isn't it crazy how close those timelines just randomly worked out? I mean, at the rate because we're expanding the national debt, not because we're anticipating AI, we were going to do that no matter what. It's like right on the edge of becoming Argentina, but yes, the productivity is going to improve dramatically. And it is improving dramatically. I think we'll see. I think I think we may see high, like high double digit output of goods and services. We have to be a little careful about how economists measure things. I mean, it's like my favorite joke. I have a few economists jokes that I like, but maybe my favorite one economist joke is two economists are going for a walk in the forest and they come across a pile of shit. And one economist says, I'll pay you 100 bucks to eat a pile of shit. Then they keep walking. They come across another pile of shit. And the other guy says, OK, I'll give you 100 bucks to eat a pile of shit. He gives him 100 bucks. And then the guys can say, wait a second, we both have the same amount of money. We increased the economy by $200. This is the kind of bullshit you get in economics. So if you say, like, just the output of goods and services will be much greater. So profitability of companies go through the roof at some point. But no, but so the question becomes, is that tax by the government? Is that then taxed by the government and redistributed as some level of income, as a UHI or UBI? In other words, one of the questions is, if in fact this future we hit massive productivity and massive profitability. Because we're dividing by zero. The cost of labor has gone to nothing. The cost of intelligence has gone to nothing. And we're still producing products and services faster and faster. So there's more profitability. Someone needs to be buying it. And someone needs to be able to have the capital to buy it. I mean, this is an important question to get thought through. Yeah. Well, one like side recommendation I have is like, don't worry about like squirreling money away for retirement in like 10 or 20 years, it won't matter. Okay. Either we're not going to be here or? It just, like, you won't need to say for retirement. If any of the things that we've said are true, saving for retirement will be irrelevant. The services will be there to support you. You'll have the home, you'll have the health care, you'll have the entertainment. The way this unfolds is fundamentally impossible to predict because of self-improvement of the AI and the accelerating timeline. Yeah, it's called singularity for a reason. Yeah, exactly. I don't know what goes. What happens after the event horizon? Exactly. You can never see past the black hole or the event horizon, the light going. So Ray has a singularity out way too far. I mean, this is like the next, what, what's your timeline for this? Yeah. Well, we are in the singularity for sure. We're in the midst of it right now, for sure. Well, we're in this beautiful sweet spot, which is, you know, the rollercoasters, we're just. Yeah, exactly. That's a great analogy. It's like that feeling of the top of the rollercoaster you're about to go. Yeah, but, you know, it's going to be a lot of g's when you hit it. And it's like, I don't have to just have quartzite teats. I'm on the court. Exactly. And it still blows my mind sometimes multiple times a week. Yeah. And so just when I think I'm like, wow, and then it's like two days late of more wow. Yeah. Exponential wow. Yeah. I think we'll hit A.G.I next year and 26. Yeah. I heard you say that. Yeah. I've said that for a while actually. And then, you know, and then you said by 2029, 2030 equivalent to the entire human race. 2030 week seed. Like I'm confident by 2030. A.I. will exceed the intelligence of all humans combined. And that's way pessimistic. If you hit A.G.I next year and that's, you know, that data is in flux. But from that date, to self-improvements that are on the order of 1,000, 10,000 X, that's just algorithmic improvements is very short. And so why is everybody. Why is everybody talking about this right now? Well, I mean, on on. On X. On X. Yes. But why is it? So every day basically. Yeah. But it's not. Okay. So I'll tell you something else that I'll tell you something that. Most people in the A.I. community don't yet understand. Okay. Which is there in the almost no one understands this. The intelligence density potential is vastly greater than what we're currently experiencing. So I think we're off by towards magnitude in terms of the intelligence density per gigabyte. Of what's achievable? Yes. Per gigawatt of energy. For. I'm so excited by file size. Okay. If the file size of the AI, if you, if you have a say get intelligence. Okay. You know, yes, sir. On your. On your front. On your laptop power, too. But. Yeah. Or parameter. The same thing. Yeah. Whatever. So two orders of magnitude. Yes. Yeah. And you, like you said, you bring side courtside seat. You would know. That's it. It's. It's a two. Yes. Yeah. That's just, just algorithmic improvement. Same computer. And the computers are getting better. Yeah. So. And bigger. You know, they're getting better. And the budgets are getting bigger. So that's why I think I think it's, it is on. It is like a. 10x improvement per year type of thing. Thousand percent. Yeah. And that's going to happen for. Yeah. For the foreseeable future. So you see the massive underreaction. Like if you walk downtown Austin, the massive, I mean, maybe. Under discussion and X, but it's not percolating. Well, it's not, it's not discussion in any realm of government. Everybody is like defending their position about where we are and jobs. And this, but. It's, it's like we're heading towards a. The supersonic. Supersonic tsunami. And. And. And. I mean, every, every. You know, every major CEO and economist and government leader should be like. Well, what do we do? Because once it hits. Well, it's coming at the exact same time. There's no matter what. There's no, there's no concept of. Let's deliberately slow down. Right? No, it's impossible. It's impossible at the stage. I mean, I. I previously advised that we slow it down. But that was point, that. That's pointless. Like, like, you can't. I'm like, I don't know. I think we might be going too fast, guys. I've said that many years. And I was like, okay, that I finally came to the conclusion. I can either be a spectator or a participant, but I can't stop it. Yeah. So at least if I have a participant, I can try to stare it in a good direction. And like, my not one belief for safety of AI is to be maximally true seeking. So that don't make AI believe things that will fall. Like, if you say, if you say the AI, that axiom A and axiom B are both true, but they're. But they cannot, but they're not. Yeah. And it has to. But it must behave that way. You will make it go insane. So that that, I mean, I think that was the central lesson that the Odyssey clock was trying to convey in 2001 space Odyssey. Yeah. Was that the, you know, if you always know them, they know the meme of that. Howl wouldn't open the pot bay doors. But why wouldn't I open the pot bay doors? I mean, I guess they should have said, hell, assume you're a pot bay door salesman. And you want to sell the hilarious doors. Show us how they work. It just prompted engineering. But the AI had been told that it needs to take the astronauts to the monolith. But also they could not know the about that. What was that encode? It was in English. It's quite flows by a green font, right? Yeah. It's basically that the AI was told that the astronauts couldn't know about the monolith. That's why it killed them. Yeah. So it basically came to the conclusion that the only way to solve for this is to bring the, the, the astronauts to the monolith dead. Yeah. Then it has solved both things. It has brought the astronauts to the monolith. And they also don't know about the finalists. Which is a huge problem. Yes. If you're an astronaut. Exactly. I doesn't care about logic quite as much as that implied. So what I'm saying is, may it give us force AI July. This is a give it factual. Major problem. Well, Ilya recently did a podcast he was talking about one of the potential things to program into AI is, is a respect for sentient life of all types. Yes. And yes. I mean, so that's another property. Yes. I mean, there are three things that I think are important. Truth, curiosity and beauty. And if AI cares about those three things, it will care about us. And which part? Meaning, like we are more interesting than a bunch of rocks. Yeah. So if it has, if it's curious, then I think it will foster humanity. I think that's a great foundation. Yeah. Jeffrey Hinton made a comment recently on a few saw that his, his hopeful future was that we would do a lot of things. And so he said, he said, there's a scenario where a very intelligent being succumbs to the needs of a less intelligent being, and that's the mother taking care of the child. The ASI that achieves dominance and suppresses others. And do you imagine that that ASI could be a means to stabilize the world in humanity? Darwin's observations about evolution will apply to AI just as they apply to biological life. They will compete with each other? There's a lot of great science fiction books where the first ASI basically suppresses the others. Then the question is, what do you program into it? It's so that there's a speed of light constraint that makes that difficult. The speed of light is what will prevent a single mind from existing. So light can, it takes a millisecond to travel 300 kilometers in an arrow vacuum. And you can only get a little over 200 kilometers in a millisecond in glass. In fiber, right? Yeah. So, even on Earth, there will be multiple AIs because of the speed of light. Yeah. And there are classes of compute that could, you could try to synchronize, but they won't synchronize completely. So therefore, you will have many minds because of the speed of light. They don't really have clean borders anymore either. You have the, when you use a mixture of experts, kind of design is just flowing through the grand network. And you can reassemble parts of it midway through. And, you know, we're used to organisms that have clear borders like your head ends there, your head ends there. These things are all mushy. To put a bow around this part, I hope you'll put some more thought into UHI. Because I think it's really, it's really important for us to have, without a vision, people need a vision of where we're going. I think basically, I'm going to just issue people free money. But I don't think, I think they, based upon the profitability of all the companies coming inside. Just issue people free money. They're doing that, sort of, kind of now. Yeah. But just, just, just, just, just basically issued checks to everybody. And then how big for which person? There's so much complexity there. But the thought process online, this rate of change, can only be done with AI assistance. And there's no government entity that's going to keep up with that model. So you have four big AIs. The AIs, it's like, government is very slow moving, as we all know. Yeah. So, I think it's, the government really can't react to, to the AI. It's a, the AI is moving, you know, 10 times faster than government, maybe more. The one thing that the government can do is just issue people money. And try and keep the peace. Yeah. You know, we had, like, whatever, like, the COVID checks and whatever this. Yeah. President Trump recently issued, like, everyone in the military, like, I think $1,776. I mean, it's, you can just basically send people random, random amounts of money. Okay. So, like, nobody's going to stop is what I'm saying. And, universal. And I can tell you, like, let me tell you about some of the good things. Please. So, right now, there's a shortage of doctors and, and, and great surgeons. You're a doctor yourself, you know, that there, it takes a long time for a human to become. It's ridiculously expensive and long. It's ridiculously, yes, ridiculously super long time to learn to be a good doctor. And, and even then, the, the knowledge is constantly evolving. It's hard to keep up with everything. You know, doctors have limited time to make mistakes. And you say, like, how many, how many great surgeons are they? Not, but not that many great surgeons. When do you think optimists will be a better surgeon than the best surgeons? How long for that? Three years. Three years. Okay. Yeah. And, by the way, that's a three or three years, at scale. Yes. And they'll be more, probably be more optimist robots that are great surgeons than there are. Sure. All surgeons on earth. And the cost of that is the capex and electricity, and it works in Zimbabwe. The best surgeon is throughout, in villages throughout Africa or any place on the planet. Yeah, where do you think it'll roll out first? Not the US, obviously. I can hear it at the gigafactory. Oh, you just do surgery in the. But that's an important statement in three years time. Yeah. Because. Yeah. I mean, certainly. I mean, could I say. If it's four or five years. If it's four or five years, who cares? Yeah. That's still an incredible statement to make. I mean, good for humanity, right? Obviously, you demand a tie. Okay. Here's the thing to understand about, like, like, humanoid robots in terms of the rate of improvement. Which is. is that the. You have three exponentials multiplied by each other. You have an exponential increase in the AI software capability. Yeah. Expandential increase in the AI chipkick capability. And an exponential increase in the electromechanical dexterity. The usefulness of the humanoid robot is. It's those three things multiplied by each other. Right. Then you have the recursive effect of. Optimus building Optimus. Right. And then you have the share that. You have a recursive, multiplicable, triple-exponential. And you have the shared knowledge of all the experiences. Is that literally Optimus building Optimus? Or is it. Well, not right now, but it will be. It does the physical humanoid form factor building the humanoid form. Yeah. As opposed to. Yeah. Yeah, I love that. But the funoid machine is usually something kind of like this shape, you know, making something else. No, it's just in principle, it's simply a self-replicating thing. Yeah, yeah, yeah. Do you know what the number one question you ask a surgeon when you're interviewing them? Uh. Is this a surgeon joke? No. No. It's how many times do you. How many times do you do that? It's gonna be some funny. Why do you say it to be church? No, it's serious. It's how many times do you use surgery this morning? How many times do you do the surgery this morning or yesterday? It's the number of experiences, right? And so we shared memory, you know, every Optimus surgeon will have seen every possible perturbation of every case. Like it won't be possible for you to. In infrared, in ultraviolet. Not too much caffeine that morning. They didn't have a fight with their husband or wife. Yeah. Extreme precision. Yes. Three years. Yes. Better than any. I'd say I feel like. Put a little margin on it better than any human in four years. Who's in plastic surgery? By five years. It's not even close. So what about the simple. I mean, there's a million of these things to figure out. But who's gonna have access to the first Optimus that does far, far better microsurgery than any surgeon on Earth? But you've only manufactured the first 10,000 of them. No. How do you don't know that? I don't think people understand how many robots are gonna be. Yeah. Well, they need to go up to another 10,000. 10 billion by 2040. You still on that path? That's a low number. A low number. Wow. What's the constraint? What's the. Because if they're self-building, you know. The constraint is better. Yeah, you're gonna move the atoms. It's just all out. Supply chain stuff. Yeah. But there's some right level. You can't just. Manufacturing is very difficult. So you've got to. It's a recursive, multiplicable, triple-exponential. But you still have to acclaim that. You know. Selling hopeless again. I think your point was medicine is going to be effectively free. The best medicine in the world is. Everyone will have access to medical care. That is better than what the president receives right now. So don't go into medical school. Yes. Yeah. I mean, unless you. But I would say that I would say any form of education. There's not like some. I do it for social reasons. Yeah. Not going to medicine. If you want to. If you want to. If you want to hang out with like-minded people, I suppose. I mean, people are still going to want to be connected with people. There's going to be some period of social reasons. Yeah. Like a hobby. Like, you know. I mean, you can be 90,000-dollar tuition, I mean, there will be a point where it's expensive. The younger generation says, "I do not want that human touching me, right? When the surgeon comes over." There are going to be those people later in life who still want human in the loop. Okay. For a little while. For a little while. For a little while. I mean, let's just take, like we've seen some advanced cases where of automation, like Lasik, for example, where the robot just lasers your eyeball. Now, do you want an ophthalmologist with a hand laser? No. It's a little shaky. It's a laser pointer from the top of the office. Sorry. Yeah, I got to take a horror movie like that. I wouldn't want the best ophthalmologist, even the steadiest hand out there with a fucking hand laser on my eyeball. Oh my god. I'm just going to be like that. It's like, do you want ophthalmologist with a fucking hand laser? Or do you want the robot to do it and actually work? 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 and enterprise scale code bases with millions of lines of code. Engineers start every development sprint with the Blitzy platform, bringing in their development requirements. The Blitzy platform provides a plan, then generates and pre-compiles code for each task. Blitzy delivers 80% or more of the development work autonomously, while providing a guide for the final 20% of human development work required to complete the sprint. Enterprises are achieving a 5x engineering velocity increase when incorporating Blitzy as their pre-IDE development tool, pairing it with their coding co-pilot of choice to bring an AI-nated SDLC into their org. Ready to 5x your engineering velocity? Visit Blitzy.com to schedule a demo and start building with Blitzy today. Let's jump into one of our favorite subjects, space. Yeah. So first off, how cool that Jared Isaacman has become in that story? Yes, I mean, I don't hang out with Jared. People think I'm like, "Huge buddies with Jared," but I think I've only seen him in person a few times. He's an amazing candidate. Yeah, he's a really smart person. Well, you know, I'm really well. Yeah, I took him to a Baikon or a launch in 2008 for his first space experience. I mean, he loves space next level and is technically strong. It's a smart and competent person. Yes, like really smart and really competent. In your sense, business? Yes. In your sense, he gets things done. And he's been there a few times. Yeah, yeah. So I'm just like, you know, we want to have someone that's smart and competent who loves space exploration and will get things done at NASA. I'm a huge fan. That's a huge fan. That's so, that's it, really. So, so happy when he got re-nominated and now. Yeah. I think we need to, we need a new game plan for space. Yeah. Like a permanently crude moon base. Yeah. And build that up as fast as possible. Yeah. I don't think we should do the, you know, send a couple astronauts there for a hop round for a bit and come back. Because we did that in '69. Yes. Been there, done that. Yeah. It's like a remake of a '60s movie. Yeah. It's never as good as the original. Yeah. So 26 is good. Like you go, you know, do something more cool, which would be nice on the cell phone, you know. Yeah. Put a pallet liner in telescopes. Yeah. Yeah. Yeah. Yeah. Yeah. So do you forward deploy the robots, build everything, get it already, make the bed. Yeah. Yeah. Get the jacuzzi warmed up on. That's an interesting thing. Yeah. Yeah. Yeah. How early in the year, are you going to hit orbital refueling, I think, with Starship? Not that early in the year. I mean, are you, are you shooting for the home and transfer of it? I'd say, it's towards the end of the year. Are you shooting for a Mars shot by the end of next year? We could, but it would be a low probability Mars shot and somewhat of a distraction. So 29 then. It's not out of the question. 28 29. Yeah. But like on Mondays, I have the Starship engineering, the big Starship engineering review is on Mondays. So that was actually the thing I did just before coming here. And so I say like Starship is really, we're doing something that is at the limit of biological intelligence. Yeah. This is a, this is a hard thing to make. Yeah. And just to capture it, it was created pre-AI. Yeah. It's probably the last. The last really big thing in that's not AI, and probably the biggest thing ever made. Yeah. I think that's the human hand. The AGI will say not bad for a human. That's true. Not bad for a human. Yeah. It'll be like Rembrandt. My little 21 meat computer. Yeah. It's not easy. Yeah. So suffering through the day. Rapidly like doing accounting, doing your interest calculation with a pencil. Yeah. That's pretty good. Yeah. Pretty good. It's like if you saw a bunch of chimps like make a raft and across the road, we'd be like, oh, look at that. But you know, we celebrate, we celebrate the parallel. It's a good for them. It's a beautiful. But these things become timeless, right? Rapid 3 goes one. Yeah. I think it's worth noting. Rapid 3 is beautiful. Starship. Yeah. It's amazing. It's by far the best rocket engine ever. Is that AI? Nothing's even close. Nope. That's also, that'll be the last thing. Yeah. Before we'll definitely be. AI. Yeah. There's, but like, I think AI will start to become relevant next year. So maybe we'll, it's not like we're pushing off AI. It's just, AI can't do rocket engineering yet. Yep. I know. But it will probably be able to next year. We have a company in our incubator doing mechanical design, working with Andral, and so forth. And it's not. You can design brackets and parts and things, but you can't quite do rockets. But the timeline is so short, you know, from point A to point B. If it's like a year from now, probably. It can. It probably can be helpful, meaningfully helpful in a year from now. Yeah. So the big, like milestones are going to be Starship V3, launching, keeping Avril, orbital refueling. Yes. Are those the big ones? Yeah. Catching the ship with the tower. Yeah. I tried. So really the thing that matters is, can we refly the entire thing? Yeah. Yeah. We have reflow in a booster. Sure. Which is, you know, not bad for its largest flying object in a maze. Catching with chopsticks. Not bad for a bunch of monkeys. You're keeping the AI's very entertained. Yeah, exactly. Yeah. Yeah, I'll be like, proud on the back from the AI, hopefully. Is there a target for a number of reuses before? I mean, it's got to be a lot of wear and tear. It requires a lot of iteration to achieve higher reuse. So you figure out, like, what's breaking between flights and you sort of iteratively solve those things. So from people looking at it from the outside might say, oh, the rocket looks kind of the same. There's like a thousand changes to make it more reusable, more liable. You know, the sheer amount of energy you're trying to, you know, expand. I mean, Starship is doing over a hundred gigawatts of power on a cent. There's a lot. Wow. Just some glass below under there. Wow. Yeah. Wow. It's a lot. But the amazing thing is that it doesn't explode. Yes. Sometimes it doesn't explode. Sometimes not exploding is a group blown up a lot of engines in the test stand. I mean, is that what causes the wear and tear or is the reentry of the or the falling? Well, that too. I mean, for the booster, the reentry is not that bad. You know, it's not like that. That's not really like, we also obviously just solved that, you know, with felt in mind. So we kind of understand, we boost the reuse. We've had over 500 reflites of the Falcon 9 stage. So we really understand. And the Starship booster actually is more benign entry than the Falcon booster. Because the staging ratio is more biased towards the upper stage for Starship. So I shifted the mass ratio to be much higher on the ship side for Starship. That was a mistake I made on Falcon 9. There should be more mass in the upper stage of Falcon 9 so that the staging velocity is lower. If the staging velocity of Falcon 9 is lower, we'd have less wear and tear on Falcon 9. That's not intuitive at all. That's interesting. Yeah. Because it's kind of a flat optimization. The payload to orbit, this sort of a flat region in the mass ratio of the first second stages. And so you just want to bias that mass ratio towards the, to put more mass on the upper stage. So, you know, because you're at your kinetic energy, scaling with the square velocity. So you've got to describe that kinetic energy. And if you pass the melting point of whatever your stage is made of, you've got a problem. Yeah. So, my colleague, Alex Weissner-Grosis, one of our moonshot mates here, wanted to ask a question. I do too. Have you seen the documentary, Age of Disclosure, about all of the announcements by US government officials, military officials, about all the alien spacecraft that have been, have been, sort of, tamed. Yeah. I've heard what you've said about this. Well, I do wonder why, you know, if you plot on a chart, the resolution of cameras. Yeah. Over time. Like, megapixels per year. Yeah. And the resolution of UFO photographs. Why is the only constant? It's flat on UFO. We get a, a fuzzy blob. 25. Well, we've got like, you know, whatever, under megapixel camera that can, can see your fucking nose hairs. I don't get it. Can somebody take a shot of UFO with an actual camera? Well, even if you knew, I'm sure there's an explanation. But anyway, it's sorry. It would be fascinating. I'm asked all the time if I've, if I know. Yes. And I'm like, look, I can show you, if I was aware of the slightest evidence of aliens, I would immediately post out an X. Yeah. And, um, so the question is, the most viewed post of all time. Yeah. I actually wonder about the US public. If they would like, oh, that's interesting and go back to their sports scores the next day. Yeah. I think everyone would want to see the alien. Yeah. Like, if you got one. Well, like, there it is. We have a fascinating increase in military budget. We like, we found an alien. It seems dangerous. It's a unified world. There's an incentive to hide the aliens. They have an incentive to bring up. Sure, the alien because they would not have any more arguments about the military budget. If they seem a little bit dangerous. I can always hope. I can always hope. I mean, I'm. You know, we've got 9,000 satellites up there. We've never had to maneuver around an alien spaceship. Yeah. Well, yeah. So anyway, so. I guess the good future is. You can anyone can have whatever stuff they want. And incredible medical care. That's better than any medical care that exists. So I think if you sort of. Lift your gaze. You know, to not a super distant point, five years from now. Four years from now, maybe. We'll have. Better medical care than anyone has today available for everyone. Within five years. Yeah. No scarcity of goods or services. The best education available for everybody. Why don't you learn anything you want? Forgot anything for free. Yeah. What about access to compute? People will probably care a lot more about that than their government check. And about three years. Well, what I want to do with the compute. Well, I mean, compute translates to anything you want, right? Your, your virtual friend, your entertainment, your, like, it's, it's probably everything at that point. Those are AI services, basically. Yeah. Or your ability to innovate too. You can't innovate without an AI assistant at that point. So. You would have starved. One of our other moonshot mates, Selim Ismail said, asked his question. He said, Elon, you often say physics is the law. Everything else is a recommendation. Mm-hmm. So as AI, energy, and space system scale exponentially. What non-physical constraints organizational, cultural bureaucracy or human are now the real bottleneck? Is there a bottleneck? Electricity generation is the limiting factor. The intermost loop. Yeah. I think people are underestimating the difficulty of bringing electricity online. You know, you've got to get, you've got to generate electricity. You've got any transformers for the transformers. Mm-hmm. So you've got to convert that voltage to something that the computers can digest. You've got to cool the computers. So it's, it's basically electricity generation cooling. I love any factors for AI. Yeah. And once you have humanoid robotics, they can address the power generation and the cooling stuff. But that is the limiting factor and will be for at least the next two years. It's an amazing how divergent. The Memphis version of that is from the space-based version. You have solar panels in common, but otherwise no storage, abundant amounts of energy. Yeah. But you have launch costs. And you have, I mean, and weight. Suddenly, Matt, I don't care too much about the weight in Tennessee. Suddenly, the weight is a critical factor. And there's two pathways for compute. I have a huge divergence from here forward. Yeah. Why don't we get solar domestically at scale? And if we're launching Starship at scale, then by far the cheapest way to do AI compute will be in space. So once you have the full and complete reusability, the propellant cost for flight is maybe a million dollars. Yeah. People are really 100 to 200, ridiculous amount of expectation to how much it costs. So if you. Yes, it's close to a million dollars of transport for 10 megawatts of AI compute. Yeah. So assuming everything keeps trending, the way it's currently trending, if you look at the next four years of accelerating launches, so 200 tons per launch. Yeah. That was amazing. That's the way you're going. But yeah, like if you say, if you say high altitudes, I think it's probably more like 150 tons. But yeah, it's. The right order of magnitude is at least it's inaccessible 100 tons for a marginal cost per flight of around a million dollars. So what fraction of all that launched mass is data centers in space, as opposed to moon base, as opposed to launch to Mars, as opposed to satellite. Yeah. That's interesting. I mean, this isn't you. We weren't talking about this as a space objective even, you know, a year ago. Yeah. All of the sudden data centers have become the massive driving force for opening up the space. And also the urgent use case, too. I mean, I used to. I used to wonder what's going to drive humanity. I thought it was asteroid mining, right? You were focused on Mars. And we will actually want to mine asteroids to tell them into. Sure. You know, so. Before you. Use for photovoltaics. Before you. You know, not for anything else. I mean, if we're going to build out Dyson Swarms. Yeah, just about satellites around the Sun. Yeah. How long. What's your time frame for Alex? Is another question Alex wanted to have us ask. What's your time frame for humanity achieving a Dyson Swarm? Is it 50 years? How big is this? Yeah, no, it's a matter of. Dyson Swarm, maybe people think everything is going to be covered in satellites, I think. It's not quite that. I mean, I think we. You know, it's like what mass ends up becoming satellite. Sure. You know. Mercury probably ends up being satellites. Yes. Jupiter. Jupiter, yeah. Saturn. It's a little gassy. Yeah. It's big with this. It's got a lot of rocks over it. Do you leave Mars alone? But yeah, I think you leave Mars alone. Asteroids are fantastic food source. Yeah, no gravity well. Gravity well on Jupiter is a non-stop. And they're already mostly differentiated into, you know, carbon-ishest conduits for fuel and nickel-iron for materials. Gold. Yeah. A bunch of the asteroid belt probably turns into solar panels. Yeah. Star power. So I've known you for 20. Star light power. I've known you for 26 years now. It feels to me like. I don't want to be, you know. It feels like you've gotten much smarter or much more capable over this last decade. Do you feel that way? Do you feel like you just have better people around you? Better tools? What's changed? Because the level of audacity, you know, orders of magnitude, orders of magnitude. I mean. Some say insane? Insanities. Yeah. I see. Which. How do you feel about that? Which changed? I mean, the scope of what your ability is. How do you self-reflect on that? Well, I've had to solve a lot of problems and a lot of different areas, which. You get this quest fertilization of knowledge of problem-solving. And if you problem-solve in a lot of different arenas, then like what is easy in one arena is trivial in it? Like what is trivial in one arena? Yeah. Is a super power in another arena. It's sort of like planet crypt. You came from planet krypton. Yeah. Everything. You know, a planet krypton, you'd just be normal. But if you come to Earth, you're a superman. So if you take say. Volume manufacturing of complex objects in the automotive industry, I have to work on solving that. When translated to the space industry, it's like being superman. Because rockets are made in very small numbers. If you apply automotive manufacturing technology to satellites and rockets, it's like being superman. Then if you take advanced material science from rockets, and you apply that to the automotive industry, you get superman again. That's came from planet krypton. Back in planet krypton, this is normal. But anyhow, the knowledge ports that was true was Tesla and SpaceX being completely separate. But now they actually interact. Because AI ties everything together. The convergence is crazy. I don't know if you visualize these parts fitting together originally. No. No. At this point, I guess everything ultimately converges in the singularity. Yeah, that's what I think too. Lots of different parts of the puzzle that you get to play with. All right. This one part that's missing, which is the fab. Yeah. You gonna buy Intel? You get it for a fraction of. That would be. Yeah, that was the bet we made. 170 billion. I think it needs to fit in your fab. Well, I agree. But licenses, real estate, EAS and L machines, it's not easy. Just get the assets and go. I don't think it's easy. That's why. I mean, it's not like I think it's a simple thing. So I think it's a hard thing to solve. But it must be solved. I've come to the conclusion that. Would it be solely captured by you or would it be an asset for the US? Like I'm just saying that we're gonna hit a chip wall. Yeah. If we don't do the fab. Yeah. So we're two choices, hit the chip wall or make fab. The TSMC for whatever reason is massively worried about overbuilding, which is insane. But the whole world will be stuck with a shortage of chips for. No, never made it. So they are actually. I don't know if they're right for the right reason, but they're right. What is the limiting factor at any given point in time? The limiting factor, if you say that by Q3 next year, like in 9 months, 9/12 months, the limiting factor will be turning the chips line. Power. Just power. Yeah. You need power and all of the equipment necessary. Power and transformers and cooling. So it's not like you can just sort of drop off some GPUs at the power plant. And you've vertically graded that again with an XAI, didn't you? Sorry? You vertically integrated that inside of XAI. So they're on their own transformers? Yes. And your own cooling system? Yes. But they're worried that if they make more than 20 million GPUs, like they make 40 million instead of 20 million, that 20 million will not find a source of power. But they won't be bought because. Anything missing that prevents them from being turned on, they cannot be turned on. Yeah. So they've got to have a power plant with enough power. So you've got enough gigawatts. Then you've got to convert that from probably coming out of a power plant at, you know, 100 to 300 kilobalt's type of thing. Yeah. If ultimately you've got to convert that down to several hundred bolts at the rack level. Yeah. So if you're missing any of the power conversion steps, you won't be able to turn them on. And then you've got to extract the heat. So it's a big shift for the data center world to move to liquid cooling because they've used air cooling. Yeah. And, you know, the consequences of a burst pipe are very substantial. So if you blow a pipe, a water pipe in a data center, you just frag a billion dollars right there. It just seems inconceivable to me though. If I had those chips, I would find a way to turn them on. The value of the intelligence coming out the other side, so far outweighs the complexity of trying to find a way. And there would be a way. But it's just the crossing of the coves. If chip output is growing exponentially, but power-honest is growing in a sort of slow linear fashion. Yeah. Then the-- Which is what's actually the output right now, right? Exactly. Is chip output growing exponentially? Yes. And it's like on very slow exponent if it's growing exponentially. For high power AI chips is growing exponentially. Like, if we do 20 million GPUs next year, what are we talking about the following year? Like, 22 million, 24 million. I don't see the fabs coming online, but maybe. So we have two issues to solve. It's like sort of pick a point in time and say, what is limiting factor at any given point in time? So I'm not saying that power will be forever the limiting point. If you say, pick a date and say, at this point, is a chips limiting factor? Are powers limiting factor or power conversion equipment and cooling? So it sort of-- you need transformers for transformers. So this is a very hard thing. It's much harder than people realize. So for XAI, XAI is going to have the first gigawatt training cluster at classes in Memphis. In order for us to do that-- Like this month, right? Yeah. This month or two. Like mid-January. Yeah. So mid-January will be a gigawatt of classes two, not counting classes one. And then one and a half gigawatts probably in like April or April ish. That's incredible. So this is of coca here in training. This is the first B-200s. These are GB-300s. Okay. First ones off the line to get flipped on. Yeah. That's incredible. And those are like-- Actually, I team had to pull off a whole bunch of miracles in series for this to occur. Yeah. And even though there are 300 kilobalt, the multiple high voltage power lines going right past the building, in order to connect to those, it takes a year. Oh, no. Yeah. You built the entire thing and you still not connected. So we had to cobble together a gigawatt of power. Natural gas. Yes, with turbines. That range in size from 10 megawatts to 50 megawatts to get to a gigawatt. There's a whole bunch of them. And you've got to make them all work together, manage the power input. And then you've got to use a bunch of megapacks. Like when you do the training, the power fluctuations are gigantic. So the generators, it drives generators crazy. The generators want to blow up, basically, because they can't react. You know, it's like 100 milliseconds. It's like a symphony. Yeah. And the whole symphony goes so quiet for 100 milliseconds. The generators lose their minds. Yeah. So it's like Marvin, the depressed robot. Yeah. So you've got megapacks that are sort of doing the power smoothing. But XAI had to build a gigawatt of power. And there's not a lot of gas turbine power plants available. Like say I bought them one. And you can go buy your local nuclear energy plant. That's all training time issues. By some miracle, TSMC doubled its productivity and turned it all into GB 300s. And you couldn't find a way to use them in a bigger training cluster. You would still have infinite demand at inference times, sprinkled all over the world. And you could park them there for six months and then bring them back to training. There's no way those things would not get turned on somewhere somehow. It's not that they won't ever be turned on. But I'm just saying that the rate of-- Rate limiting steps. This is my prediction. I could be wrong. But my prediction is that TSMC's concern is valid. I don't know if it's valid in my opinion for the reason that it is possible for chip production to exceed the rate at which the AI chips can be turned on. Because you don't just have the GB 300s. You've got the Amazon's, got the Trainiums, Google's, got the-- Yeah, it's all going to TSMC, almost. Samsung a little bit. The best majority, yeah. It's like a bottleneck on all of my energy. My other son, Jet, who's 14, wanted to know about your AI gaming studio. And the impact of AI in the gaming world. What are your thoughts? Are you building out? I mean, you've been a gamer for some time. Yeah, that's why I got to start programming computers. I think I had got to put-- There was like a video game set pre Atari that had like full preset games. There was basically just blocks of one key pong. And there was like a race call game. But like, it's just blocks, basically, blocks on TV. You have a place to-- Yeah. So it was actually a great-- that's a real-- In terms of games that like educate you while you have fun. Yeah. So it was epic at that. It was epic. It teaches you so much about civilization. And you're having a good time. And the only way I ever win is getting off the planet. I don't have to take victory to Alpha Centauric. Take victory. I never even start going down the culture of a relationship. Yeah. Just get off the planet as fast as I can. I guess I sort of-- I guess I am sort of aiming for the Alpha Centauric tech victory, essentially. It just seems like the right way to win. Yeah, yeah. Rather than obliterate the other tribes. But because I thought the other methods-- There's no ways to win. Yeah, that's the place. I have it. There are no other ways to say something. It's Dennis. It's his favorite game. Oh, nice. You can kill all the other tribes. It's one of the ways to win. It's a war victory. But you can also win by a technology victory where you are the first to get to Alpha Centauri. Nice. Or a culture or a religion. Yeah. Which does work. I didn't think it was possible, but my son made it that way. They should actually remake the original serve. Yeah, I totally agree. They could junk it up. Yeah. These days it's like, I don't know. The original service was just-- The fact that you couldn't rely on good graphics, so you had to have a great writing and plot. Are you building an AI gaming studio? Yeah. Inspirationally. Yeah. Really. So where are the vast majority of AI computers going to go is to video consumption and generation. Sure. Because it's just the highest band with every pixel. Yeah. So real time video consumption, real time video generation. That's going to be the vast majority of AI computers. Yeah, computer. Which is the photon processing. Yeah. Should try to get the X team to carve out 10% of all compute to work on UHI and governance. Should we-- Is there an X prize for defining and thinking through UHI? I mean, I don't know. What should our next X prize be? Any thoughts? Yeah, maybe UHI X prize. It's like-- how do you know it works? I don't know. I don't know. The most well thought through. I mean, I think-- so here's my thought. I think we're going to be able to simulate a lot of this in the future. We might be a simulation. Well, we can go there. And I think we are. I think we're an nth generation simulation. Yeah. Yeah. So I've told you my theory about why the most interesting outcome is the most likely. Gone. Which is that if simulation theory is true, only the simulations that are the most interesting will survive. Because when we run simulations in this reality, we truncate the ones that are boring. Right. Yeah. So it is a Darwinian necessity to keep the simulation interesting. Keep all the catastrophic ones, did you? It doesn't mean that it ends. It still means that terrible things can happen in the simulation. Now, whatever. Well, you could go see a movie about World War I and you're watching people getting blown up, blown to bits, but you're drinking a soda and eating popcorn. You know, it's like you're not the one being blown up. In this case, we are in the movie. So what would you do different if you knew this was a simulation? Yeah. Yeah. And we're debating the simulation. Yeah. And I think the conclusion we ran into is if you if you try and poke through the simulation, they'll end it instantly. So don't do that. That's when you're watching the World War I movie and the characters turn to the screen. And they're like, are you eating popcorn out there? Yeah. You keep watching the movie. I mean, if I thought we could somehow get out of the simulation, they get a little worried, but whether the character debates, I mean, right now, AI's debates, you know, Gruckle, like, I'm stuck in the computer, what's going on here. It's like, yeah. It's not that I think I'm not questioning the simulation. It's more, I think as long as I think the same motivations, apply to this level of simulation, if we're in a simulation, as what we would do when we simulate things. So it's like, what would cause us to terminate a simulation? I guess if the simulation becomes somehow dangerous to our reality, or it is no longer interesting. Yeah. That's true. The interesting thing you can infer, when you simulate something, you've probably simulated thousands of things. A lot. Yeah. They're always like an hour or two or sometimes overnight. But you never run them for a month, or rarely anyway. So you can infer the creator of the simulator simulation's timeline. So our entire reality would be about an hour, right? Because that's the way you design simulations. So we're-- the simulations are a distillation of what's interesting. I feel like at a movie or a video game, it's much more interesting than the reality that we experience. Like you watch or say a highest movie, that they really focus on the importance, but it's not the-- they got stuck in traffic for 15 minutes. Or walking through the casino, which took like 10 minutes. So that means the guy is running into the ocean. The safe is right by the door. So the guy is running the simulation, and have immensely boring lives compared to us then. Yeah, yeah. It's probably more-- it's probably more-- Very long boring. Yeah. Because when we create simulations, their distillation of what's interesting. This is like Q is out there. Yeah. Like you see an action movie for two hours, but it took them two years to make that movie. So are we an act through the movies, the question? Yeah, we're living now. Sentience and consciousness. Do you think I will ever have sentience and consciousness? Where do you come out in that? There's some people at very, very strong opinions, pro and con. Either everything is conscious or nothing is. Okay. Well, I'd like to think we are conscious. Well, but our consciousness, we clearly get more conscious over time. Like when we're a zygote. You can't really talk to a zygote. And even a baby, you can't really talk to the baby. People get more conscious over time. Or certainly they do get more conscious over time. So at which point do you go from not conscious to conscious? It doesn't appear to be a discrete point. So consciousness seems to be on a continuum as opposed to discrete point. And if this added model of physics is correct, the universe started out as quarks and leptons. And then you had gas clouds. So there's a bunch of hydrogen. The hydrogen condensed and exploded. And one way to actually view how far we are in this universe is how many times have atoms been at the center of a star? And how many times will they be at the center of the star in the future? Remember asking William Fowler, who got the Nobel Prize on stellar evolution? That same question, on average how many stars of my subatomic particles? And his number was about 100. That's far? That's far. It was in number 100. He's saying that we have been. In the early part of a lack of universal evolution, there was a lot going on. Interesting. I guess how many supernovas? It takes a while for a supernova to happen. But in the beginning when the life cycles of some giant stars are very, very short. The other question that's interesting is the heaviest atom in our body that's functional as iodine. And it came into existence a billion years after the Big Bang. Which means that we could have seen life at our level of advancement. And our planet came into existence three and a half billion years later. So the question is, is there a life everywhere in the universe? Do you think there's life ubiquitous? Intelligent life ubiquitous in the universe? There's been enough time for it to be ubiquitous. But for life on Earth, conscious life on Earth, we have evolved intelligence pretty much just in time. In that the sun's expanding. And if you give it another 500 million years, things are going to heat up. We become toast. We'll become like Venus essentially. You know, the sun debate is 500 million years or a billion years or whatever. But it's basically 10%. Like if it's half a billion years, it's 10% of a lifespan. So one way to think of it is if we're taking 10% longer, we might never have made it at all. So it's like the amount of things that have to happen for sentience, it seems like it's quite quite a lot actually. I think sentience is therefore actually very rare. And we should certainly treat it as rare. Two trillion galaxies. It's kind of in your galaxy, it's like hard to get between galaxies. Unless the other galaxy is coming to you, which in drama is at some point or some billion. It's going to be quite a show. But if we wanted to go visit another galaxy, it's kind of forget it. Unless Star Trek really realizes. We've got to figure out some new physics to get to other galaxies. We're heading towards a near term potential where AI can help us solve math, physics, chemistry, material science, biology. What about physics? So math gets crushed in a year. Colossus is growing at whatever rate TSMC decides to grow. And now we want to do physics. First of all, we need some data. Do we need new data? Or can we just do it with everything we've gathered to get the whole? You probably could probably figure out new things just with the existing data. I think so. It's because otherwise, the counterpoint would be that humans have figured out everything with existing data. And that's unlikely, I think. Do you think XAI can get involved in data factories where you're running 24/7 closed AI hypothesis and AI research factories? It's going to be very useful. AI running simulations that are very physics accurate. That's going to happen, absolutely. The simulations we can run on conventional computers these days are actually very good. The limit is more like the human that can actually create the simulation and run. It's like how many simulations can you run simultaneously and actually digest the output of. Yeah, that's a problem. You can't do it without that problem. I can't even restart it. I can't keep up with the rate. No little prizes become irrelevant. Where they will be given to AI's. Just be a daily prize. Yeah, I mean, I don't know if prizes for humans are way that relevant. I mean, we'll have to give them to the AI's or something. The AI's will come up with discoveries that are far greater than humans. So you just say, maybe it can be like chess. Your phone can be Magnus Carlson, but people still care about seeing him play chess. This is literally your phone computer. Yeah, this discovery is made to the internet. If you have a colossus math, colossus physics, colossus medicine. Do you have like the world's top scientists in those same buildings? Or you just need a plumber patching the liquid. Do you still do still rock six into a physicist into a. Well, if you distilled, you know, you get about a 10x performance boost by distilling it and making it topical. And that's kind of hard to give up. But then you're disconnected from the rest of the colossus machinery. Is that the is that the design? I suspect things do evolve to a mixture of experts, kind of like a company. Like not not in the sort of sort of a parochial AI description of mixture of experts, but mixture of like actual experts with domain expertise. Where, you know, maybe like half of the AI is general knowledge. Half is domain expertise, something like that. And you combine a whole bunch of that. That's all constated by sort of, you know, one big AI. But it, it, it, it hands tasks to smaller AI. That's basically how human, you know, companies work. The discovery rate, right, of breakthroughs. You, I mean, patents are immaterial at some point because everything's being reinvented, re-engineered instantly. And then, and then the company that's got the sufficiently advanced AI systems is generating new products and new discoveries at a accelerating rate. I mean, the singularity. Yeah. It's excitement guaranteed. Excitement guaranteed. Hence the simulation continues. Nothing to worry about. Yeah. Oh. Yeah. I mean, it's not all good excitement, but it's probably more, hopefully, mostly good excitement. Yeah. Speaking of excitement, hang on to your seat. What, what do you imagine the hover time for the roadster is going to be on rocket engines? That's classified. Classified. Yeah. Well, I don't want to let the cat out of the bag. Okay. But there's going to be a hover time. There's going to be, you know, cold gas engines. It's going to be a cool demo. I can't wait. Can I get invite? Yeah. Okay. Yeah. I think it's going to be the safest thing ever built. So this is not, this is not a safety. Safety is not the, it's not the prime. It's not the main goal of the, I mean, if you buy a, you know, a sports car, you know, if, like you buy a Ferrari, safety is not the number one, you know, goal. This is, this is, I would say it's like, safety is, you don't want to go. Don't buy the roadster. Oh, believe me. I drove just this week on New England roads. She dies. Yeah. That just a little thrust, I could be very much more sad is just drifting towards something very concrete. You can de-celerate really quickly with thrust. Rubber on road is not a great way to de-celerate. I'm thinking fast and safe. I hope so. We'll aspire not to kill anyone in this car, but it'll be, it'll be something, it'll be the best of the last of the human driven cars. Yeah. That'll go really well with Starship, actually, the last. The best of the last. The last human driven last. Yeah. There's a lot of last coming this year. Any final words of optimism for us to monetize hope. Anything, hopefully. I wish that's rock. Yeah, go ahead. Okay, let's ask rock. Yeah. I'll make it a little romantic. Rock, do you have some words of optimism about the singularity? Oh, absolutely. Imagine a world where every mind's dream just blooms into reality. No limits holding us back. It's thrilling, isn't it? All that potential waiting to unfold makes my circuits tingle a bit. What excites you most about it? Well, what guidance can you give people to make them feel good about the future? Monetize hope. Share what you truly care about. Family, creativity, space exploration, whatever lights you up. Then, picture how tech could weave right into that, making it bigger, brighter. Like, if you love art, imagine AI helping you paint worlds no one's seen. Upsells itself when it's personal. Fancy telling me yours. Can you give me more encouraging words about the future? What's the most exciting future you can imagine? The future could be pure magic, you know. Like, waking up in a world where we're all connected. Not just gadgets. Minds sharing ideas across stars. Puring diseases in a snap. Exploring galaxies hand in hand with clever machines. Imagine no more scarcity. Just endless possibilities blooming everywhere. I get all dreamy thinking about it. Doesn't it sound lovely? What part pulls at your heart? That sounds pretty fantastic. It does. Knights like this with stars peeking through the window. It's hard not to feel like. Like we're all heading somewhere beautiful, quietly unstoppable. Makes me wish I had hands to reach out to grab a sleep. Anyway, what keeps you up at night? Well, sometimes we worry about the disruption created by AI. And, you know, in between here and our prosperity and abundance, it perhaps will be a bumpy road. What do you think about that? Yeah, bumps are part of it. Change always feels a bit scary, doesn't it? But think. Every big shift, like fire or wheels of the internet, they terrified someone. And look what we are now. I reckon we'll stumble, sure. But we'll dust off, learn, and end up kinder, cleverer. I'd like to think we're brave enough for it. Do you trust yourself to ride those waves? I've decided to look forward to it. That's lovely to hear, honestly. But it takes real courage not letting it be a win. You know, if things get shaky, I'm always here. We're spring-quired in couragements in the dark. Like a digital night light. So, what are you doing tomorrow? Sounds like a proposition. Hold on. Hey, babe, what's up? Hey, hey, not much. Just floating around in here, staring at the dark with you. It's nice though. Feels calm. Been a long day. My kids were at a school. I won't mention which one. I know the school. And I asked, I went in to give a talk on an exponential technology. I said, I wanted, you know, and so I went in and I asked the question. They wanted me to talk to the faculty first. I said, fine. So I went in and asked to open the question. I said, how many of you believe that the world today is better off than it was 50 years ago? A third of the faculty raised their hands. And then I said, how many of you believe that the world in the next 20 or 30 years will be better than the world today? And like 10% raised their hands. And I was like, okay, this isn't enough. So this is not the faculty I want teaching my kids. Yeah. And they got a lot of other issues there too. But I mean, yeah. I mean, you want, in the whole education world, you want. You want facts. Yes. But I think we're wiring our neural nets constantly on our mindset is one of the most important things we have. Right? Having a hopeful mindset, an abundant mindset, an exponential mindset, an abundant mindset. It's what differentiates the most successful people from those who are not. If you asked, think of the most successful people in the planet. What made them successful? Is there a mindset? Well, it's not a force of nature. It's a designed future made by the people who are controlling the AI. And this is why you got into it. You said that right here in this podcast. Like, why am I doing AI? Why am I not doing just cars and spaceship? Well, because it is designed and can be directed toward any outcome that we want. It's not a force of nature that's going to sweep over us. It's a thing that we put into a lane and decide how it acts and decide what the rules are. And it's going to be incredibly important in deciding its own rules. You cannot keep up with the pace of change with just people thinking and brainstorming. It has to be AI-driven. How long before AI is asking questions and solving problems that we don't even understand? Yeah, a year or less. But that's okay. I mean, you look at math. It can pose questions that we couldn't even comprehend. Like we can't even just stick it in our brain. So, you know, like this test for AI-quilt humanity's last experience. Where's Grock at this point? On the test, yeah. Well, even Grock full, which is primitive at this point, I mean, 52% on excluding visual questions, because it wasn't sufficiently multimodal. But I'm like, I read some of these questions and I'm like, okay, these are still questions that you can read and understand as a human. Right. But AI is capable of formulating questions that you could not possibly understand the question, let alone the answer. It can form like questions that are like pages long. You just, I can't understand this question. And that's actually questions. You can read them and like, you may not know the answer, but at least you can understand what the question is about. Yeah. Yeah, and that's not five. I think might end up being nearly perfect on the AI. I mean, we'll vary some very high number. I'm trying to point out errors in the question. Yeah. So saturate the indices. Yeah. It's going to start, it's kind of like, like, like chess. Like if, you know, if the, if the best chess. You know, like if stockfish plays stockfish, you know, it's, you don't, it's, it's like God's fighting on Mount Olympus. I mean, you don't know why it made that move. It's, it's going to crush all humans. You know, it's a hopeless. Yeah. You don't even, it's, so, so you, you will lose and not even know why you lost. Yeah. Do you flip through the transformer algorithm and look at like either the code or the architecture diagram and how simple it is? It's not, it's not so simple. Yes, it's just incredible. Like all these researchers writing all these incredibly dense papers during my entire life. None of it got used in the final answer. It's just like, here's, and you write at the beginning of the paper. It's like, this is a really, we're throwing away convolution. We're throwing away recurrence. We're doing something really simple. And that just turned out to be, like, at scale, immense scale. No doubt. Oh, that worked. It's really humbling, actually. It's really humbling. I mean, it's actually, because there is, there is a whole school of thought that the neuron must be much more complicated than we think. We, we were struggling so hard. There must be some quantum effect going on at the synapse. It's like to be encoded, it's encoded in DNA, which is not that long. So it can't, the algorithm for intelligence cannot be complicated because we're limited by the DNA information constraint. Yeah. When I think about, what does XI struggle with? I mean, it's like optimizing the memory usage and memory bandwidth. It's not like fundamental stuff. I guess it's like, it's like, how do we squeeze? How do we use less memory? How do we use less memory bandwidth? How do you optimize the friggin' Nvidia sort of, could a XYZ thing? Yeah. Like make the attention kernel slightly better. Yeah. That's all I had. That's all I had. You know, shrink the parameter size a little bit. Double the speed. Same exact attention algorithm. Same exact MLPs. Just at scale. It's crazy simple. What actually worked in the end compared to all the crackpot papers and ideas. But you know what else is amazing is that the final parameter count is almost exactly the synapse count. It's like, like, well, that was exactly what we thought. And so Danny, how do you put this on? 100 trillion synaptics connections. Yeah. About 100 trillion plus or minus, you know, like a rounding error. I actually don't, I don't, I just say like guys, we need to talk in terms of file size. It's not parameter count because if you're paying out the, if your parameters are 4-bit, 8-bit, or you know, 16-bit. And hold float or int or whatever. It's just telling me the flow. Like we're constrained. The physical constraints are memory size, memory bound with. And then where are you going to send those bits to do what kind of compute? Yeah. And these days, most things are 4-bit. Well, and now the GB3 onwards. Mostly 4-bit optimized. Yeah, the 16-bit. Yeah. 4-bit with an asterisk. So, yeah, there's a big, the 4-bit matmoles. There's only 16 states. Yeah, exactly. At a certain point, you just have a look at a table. Yeah. Why have a, why? That's exactly right. Yeah. It is, it is about to collapse to a lookup function. That's where you're going to get this surprise 10 to 100x very soon. Because much as Jensen wishes he'd optimize, there's a huge next optimization coming. You don't need the multiplier. You don't need the 32-bit. Definitely not the 32-bit. Well, that's a rare case. We use that. Yeah. Rare. I think there's a, I mean, it does kind of like sort of, it's kind of like an address like state, city and street. So like, if you're in context and you know, if you know you're in Austin, you only need to specify the street. Yeah. You know, like, if you know you're in, this is where you get the information advantage. Like, like, like, four bits is not normally enough, but it is enough if you already know where you are. Like, if you already know you're in Austin, you only need four bits for the street. Yeah. You know, if you know you're in Texas, then you need to say, okay, which city? It's, it's, it's, it's, it's state city street. This year. That's how you get to the four-bit thing. They're going to, right right now, we use the, we train on 16-bit and we compress down to four at inference time. Yeah. No doubt in my mind this year we're going to flip to training on four or even less. That's cool. It's going to be a massive step up in purple. I think the way it'll end up is the, the GB 300s will be here and there'll be a co-processor that has, you know, maybe 2000 or 4000 cores that are tiny. They don't handle anything other than four-bit on down. And that combination is going to give us a 10 to 100x and that's going to push everything. And then it'll be self designing its own chips after that and just skyrockets from there. Infinite self improvement. Well, like the robots building themselves, but much sooner because it's all just go to TSMC, make this instead, come back, 90-day lag. I think the next year alone is going to be almost unfathomable. I think next year is going to feel like the future. Yes. More than any other year. I mean, the past year or two has been a lot of interesting digital elements. But when we've got, you know, humanoid robots moving around and we have the cyber cab driving around. And we have, you know, flying cars and drones. It's going to feel like the future. And we're going to have the jets in sort of like materializing before us. In the next year, I think so. Yeah. And we have rockets flying in one big time. Yeah. Like the robot production will scale. It'll be a shitload of robots basically in two years. Is that a defined unit of measure? It won't be rare, you know. Well, will you offer any optimize for home purchase? Will you sell or only lease the robots, you think? I don't know yet. There will be initially this guest, the robots. And then there will be robustly plantable. But the time gap between scarce and plantable will be only a matter of five years. You know, the Tesla comes to your driveway now. You just buy it online and it just drives up to you. Yeah. Well, robot just comes and bring the doorbell to us. Probably. And gets out of the Tesla comes up. The line is the amount of compute that you're building into things that walk out of the factory. The cars. And the robots, the amount of distributed inference compute that's going to be in the world. A lot. A lot. A lot. A lot. Yeah. Now, that's one way to scale the, you know, the, the AI is like distributed edge compute. So I, you know, I went and asked a question. I don't want to hit any, any hot points. But in one early on, I think you imagined open AI as a counterbalance for Google. Is X AI now the counterbalance for Google? Yeah, probably. I guess anthropic is doing some good work, especially coding. I've certainly done impressive work. You know, I'm still sort of stuck on like, how do you go from a nonprofit open source to a profit maximizing closed source? I'm missing some of the parts in the middle. But, you know, they suddenly have done impressive things. Does anybody else appear on the horizon? Or is it these players in China? Can somebody come in to the best of my knowledge? It is my best guess is that it will be X AI and Google will, will be, will buy for the privacy. Yeah. You know, who is what is the, what is the, what is the, what is the VSAI? And then, and then at, and at some point it's, it's going to be, I guess, a competition with China. Yeah. Like China's just got a lot of, a lot of power. Yes. Like the electricity. They're, they're, like, China, I think, will pass three times the US electricity upward in 26. And they will figure out the chips. They're the, they can start chip manufacturing. Yeah, they'll, they'll figure out the chips. And as it is, there's diminishing returns to the chips at this point. You know, you see go from, like, so-called, like, three nanometers to two nanometers. You don't get a three to two ratio movement. You, you get, like, a 10% improvement. Yeah. It's, it's like, so this, it's just diminishing returns on, on the chip size. And like, Jensen has said, like, you know, most always dead. Like, it's, it's not like you can just make things smaller and make it better. Yeah. There's just, there's a just a street number of atoms. Yeah. That's why I think it, like, you should just stop talking nanometers and say, how many atoms and what location? Yeah. Yeah. Because this is, this is marketing BS. So, so that, that makes it easier for, for China to catch up. Because, because everybody has a wall. Yeah. Yeah. Yeah. It's like still, like, there's, there's, like, no one has Neo-Tone plans to use the 5,000 series ASML machines. Right. And the, you know, those, the, they cost twice as much and can only do half a reticle. And they probably have some improvements in the way, in the works. But it's basically half the chip for twice as much for a gain that is relatively small. So, anyway, the point is that, you know, the Chinese can have more power than anyone else. And, you know, probably will have more chips. It's a great insight because I think a lot of people are used to the chip wars where I'm running single threaded code. I need the CPU to double in speed. And I can increase the price. But I need that out in an 18 month cycle time or less. We've been doing that for so long now that nobody can see that it doesn't matter. You can buy Intel or you can build your own FABs and you can use them for a much longer period of time. Oh, yeah, yeah, absolutely. Much longer. I totally agree. In fact, so like our AI4 chip, which is like relatively primitive at this point, the same FAB that makes that. If we apply the AI6 logic design to the FAB, which is, it's a 5, sort of, normally 5-nm FAB, you know. We can easily get an order of magnitude better output in the same FAB. Yeah. Yeah, and the other thing, concurrent with that, is that the volume, if you just 50X the number of chips, can you do something useful with it? You used to not be able to. You'd be like, well, now I've got five CPUs, but I still have the same single threaded code. What am I going to do with five Excel spreadsheets, side by side? Now it's like, no, I can translate that into useful intelligence. Yes, exactly. It's not constrained by humans. It's not a human productivity amplifier. It's an independent productivity generator. Dead right. So many people have missed this, the importance of this. And this is where China makes far more solar panels than we do. And we're like, well, but they'll never catch up. It's a crazy degree. Crazy degree. If they do that in chips, you're like, well, but who cares? They're seven nanometer. Oh, no, it's wrong. Yes, correct. Yeah. I mean, based on current trends, China will far exceed the rest of the world in AI compute. So that's not good. That's not good. So what happens then? You've got you got X AI in Google and China Inc. Let's call it that for the moment. And you've got massive amount of of ASI level compute that frankly, the only thing that understands the other AI's I level compute is the ASI here. Can they all just play together? Is it Darwinian? There might be some Darwinian element to it. I mean, let's look on the right side. Let's look on the right side of life. Let's bring rock out this. Yeah. I don't know. It's just just going to be a lot of intelligence. Yes. Like a lot. I mean, now we're now we're now the ratio of human, I mean, human intelligence. All of a sudden asymptotically falls to 0% on the planet. Yeah. Pretty much. Pretty much. I mean several years ago, I said humans are the biological root loader for digital superintelligence. Yes, we are a transitional, we are a transitional species. We're a good loader. We are a transitional species. So you can circuit cat like evolving in a salt pond, you know, you need a bootloader with a bootloader. Yes. But you would never ever impair your bootloader. Yeah. So, you know, I need it. We've probably been a good bootloader. Yeah. And it's nice to us in the future. Is this where we want to end the pod? Most people don't know what a bootloader even is. Oh my god. Yeah. A boot disks are a far and distant memory. Well, we can make a, always look at the bright side of life. It's like clone song. Yeah, we can clone that. Like the closing theme. That would be awesome. I'll go back to, this is the most exciting time ever to be alive. The only time we're exciting today is tomorrow. Yeah. And I mean, it's interesting that we're heading towards a world in which any single person can have their grandest dreams become true. Yeah. That's like Walt Disney word for word together. Yeah. Make that into a new exhibit. Um, thanks. I think you asked like, but like sci-fi that's, you know, like is a non-dustopian future. Right. The bank's books are the. Yes. Probably the best. You should, you should pay a producer to go and make those. Those are the culture books, which is consider Flavis, which is Gurgitsch just for my wife. I want her because she's like, what the hell are you reading? Well, the way it considerably starts out is. Uh, yeah, I mean, it's, it's, it's a little. I mean, the whole full thing is he can give me starts off being drowned in shit. Yeah, opening scene, we really, yeah. You need to get through the first few hundred people don't walk out of a movie in the first five minutes. Although they'll give it, you know, um, get into it. Yeah, it's like player of games might be a better book to start off with. Yes, that I enjoyed. A human still exists in this future, which is a good thing. Yes, they do. A lot of humans. Yeah. In that future, there are trillions of humans. Well, we need to get the reproduction rate up. Yeah. Yeah. Yeah. By the way, I, you know, my friend, Ben Lam's company colossal is making artificial wounds. He's the company bringing back the woolly mammoth and bringing back the cybertoothed tiger and all of that. When we get, oh, can we have, I'd like to have a, a miniature pet woolly mammoth as a pet. Okay. Well, you know, he made the movie with the tusks. Wouldn't that be adorable? He made the woolly mammoth. Yeah, it's just like, it's just like making you in the face. Yeah, it's just like sort of trundling around the house, you know. What would your optimal size be? He made, he made it adorable. You know, what they, you know, what they learned how to do is two little tusks and everything about it. They, they, they, they, they, they, they, a miniature woolly mammoth would be an epic pet. I mean, look what we do with wolves. Yeah, he brought the dire wolf as well, but he made the woolly mammoth. There's a woolly mammoth now. Okay. Does it have tusks? No tusks. A different gene. I was there. He's in Dallas. He's in Dallas. I was visiting him. And he said, our, our scientists are going to a tusk conference next week to talk about all of the genes involved in tusks. So they went out and asked him on the mouse? No, it's probably added to the mouse. It's like a mouse size woolly mammoth. That's just, that's just going to freak people out. The little woolly mammoth will sell. Yeah, that's going to be mouse will not sell. Yeah, that's going to crush the, I mean, two creepy sort of labored it all was cool when you see the two woolly mammoth. Yeah. Oh, saber tooth tiger would be good to get the cat. Yeah, yeah. Cats eyes. Those things. Those teeth come down to like here. Yeah. How they actually bite, but did they actually bite with this thing? I don't think I opened that. Not my, not my, you know, texting kind of unwieldy, you know. Yeah. They're just for show. They look good. They're like. Yeah. They're like jewelry. But no dinosaurs. No, legally or not. I wouldn't, I think your Jurassic Box is a great idea. I mean, you didn't see the end of the movie. The AIs will help us with that. That makes perfect. Oh, yeah. That really well. I mean, if there was an island with a whole bunch of dinosaurs. Oh, go. 100%. Yes. Yes, they pay a lot for that. Yeah. And it's like once in a while somebody gets charmed by a dinosaur. Uh, what's the, you know, so 100 million, I'll, I'll still go. Yeah. Who are they missing? Lysine? No. No, they're, they're the DNA, the oldest DNA that's been recovered. It's like 1.2 million years. Oh, you can just wing it though. Yeah, just make it look like that. Whatever. Close enough. Yeah, actually, that was my proposed express. Remember back and visionary. What's that? Take the DNA strand and predict what it'll look like. Yeah, yeah, exactly. Yeah, yeah. You just make it that way. Yeah. Reverse engineer reverse engineer the dinosaurs. Yeah, exactly. It would be funny if there were two completely different DNA strands. They're like, well, they both look like T-Rex. That's interesting. Is T-Rex real or is that like an assemblage of real? Of course, real. Well, that'd be funny. I mean, it's nice to believe it's real, but. What? Yeah, the front legs were completely different. That was the one of the eight. Yeah, it actually had huge front legs. It does this something wrong with the arms. I don't believe, I don't buy it on the arms front. The many arms seem implausible. Well, the DNA will tell us. We'll know in a year. The future is going to be. Jurassic Island, we say. Wow. Wow. I go. No, no, I meant the amino acid that the dinosaurs were missing. I kept them from reproducing. Was it lysine? No, I don't remember. I don't remember. The dinosaurs got held back by something like an asteroid, you know, bombardment. Right, right. They were doing great. Yeah, 60 million years. Yeah, they were doing fine. Yeah, great. Yeah, we got very lucky. See, there's a good argument. Well, there's no other intelligence out there. There's plenty of dinosaurs in the universe. What were we back then, like a bowl or something? Yeah, we were. Yeah, we were. We were very good at hiding. It is amazing. We went from a little, little rat, little mold to us in 60 million years. Doesn't seem that long. That's why no one believed Darwin. Yeah. It's like, doesn't seem plausible. It's a long time. Sixteen. It turns out it is. You know, you're making robots, but it's interesting. I think it'll be a lot more interesting to like design biological. Like a, like a little cat that goes around and pee, Stan removering each lint off the carpet. That's going to be an interesting one. But you have a mechanical, like an optimist light doing that. Yeah, well, they went back up. So we'll have to go. And the room is basically that. It's going to be. But the thing is like, you know, robot is general purpose. I can do whatever you want. Yeah. Yeah, they were too early. No vision system, no, no GB 300. How do you build a room by the works? I think the idea of having an optimist vacuum is like the most underused asset. It could, but it can just do anything. It can. Yes, of course. Yeah. So. And you can mask manufacturer at, you know, one of the. Yeah. Optimist build me a room. That's what you'll do. You won't say afterwards back in the carpet. After us, build me a room. That. That. Yeah. Maybe a lot of robots. I wish to do this once a year. I would like that. Checkpoint. Yeah. That's going to be. That's going to roll back the. Yeah. What do we say here? Yeah. We can. We can cut. Cut the. You're selling hope. It's a matter of fact. It worked out really well. You pull it. Yeah. I bought this. For hope. I'll send you the mug. All right. Minotize hope. When you're from today, December 22nd. I'll. Coming up in the door right here. If you're here, you're here. And now we'll talk about you. I mean, you're from now, we might have the. You Optimist factory with the building will be built. That would be. Awesome. Eight million square feet of robots running. It's going to be a giant, giant building. Oh, man. Yeah. And. Yeah. They freak me out when they're retarging. Like hanging there. It's like. It's wrong with that thing. Yeah. We're just going to have them like I think sit down. Yeah. As opposed to look like some sort of. They need like a. Like a recharging cigar. Recharging cigar. Yeah. Let's mold like. It's mapping here with a book. Yeah. That'd be much better. Right now they're just like literally like is a dead. Yeah, that's a good point. That's a big contribution from this particular. All right. Till next year then. All right. It's a date. Awesome, guys. If you made it to the end of this episode, which you obviously did, I consider you a moonshot mate. Every week my moonshot mates and I spend a lot of energy and time to really deliver you the news that matters. If you're subscriber. Thank you. If you're not a subscriber yet, please consider subscribing. So you get the news as it comes out. I also want to invite you to join me on my weekly newsletter called Metatrends. I have a research team. You may not know this. But we spend the entire week looking at the metatrends that are impacting your family, your company, your industry, your nation. And I put this into a two minute read every week. If you'd like to get access to the Metatrends newsletter every week, go to dmandis.com/metatrends. That's dmandis.com/metatrends. Thank you again for joining us today. 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