[0:00:00] 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 white-collar 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. Do you have a solution to this? I don't make a bet here.
[0:00:29] 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. There are three things.
[0:00:58] 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. 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 Blunden, and I flew into Austin, Texas to meet up with Elon at his 11.5 million square foot gigafactory.
[0:01:32] Home of the Cybertruck and Model Y production and the future home for 8 million square feet of Optimus 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. 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.
[0:02:00] Yeah. I think they need it. I hope you're right. And you might be right, actually. I'm increasingly thinking that you are right. Thank you. Abundance for all. Yeah. That's the goal. Shall we? Yeah. All right. Right now, I'm putting a lot of time into chips. You are personally? Yeah. Yeah. With some AI assistance, I assume. What's that? With some AI assistance, I assume. Design. Not enough. It'd be nice if we could just hand it over to the AI.
[0:02:30] Yeah, yeah. 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 Grok, it could probably tell you if a circuit is going on with it. Yeah.
[0:02:55] I'm going to give it a shot. You're using the same Grok that I'm using? Grok keeps updating. 4.2, but 5 is soon, right? 5 is Q1. 4.2 has not been released yet, externally. If you just upload an image into Grok, it does quite a good job.
[0:03:26] Of analyzing any given image. Absolutely. Let's start. We're going to talk about this. All right. We'll come back to it. Let's see if I take a picture of you. What is it? What's it going to say about me? Yeah. It's going to say you're a flawed circuit. I also have to remember to update it because we update the Grok app so frequently. You know, I asked Grok to roast me. Oh, it does a good job. And it did an amazing job. Then I asked Grok to roast you. And I spit out my coffee. It was...
[0:03:53] Hilarious. And then I asked it, you know. It just keeps telling it to be more and more vulgar. Until it's like, mother of God. Is Bad Rudy still out? Or did that get repealed? Bad Rudy's still there? And I asked her, does Elon 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 is he going to do about it? Yeah, let's see. So I just literally took a photo of you.
[0:04:21] And see what it is. Did you ask a question? No, nothing. I didn't say anything. This man is hugely... This is Peter Diamandis. Yes. Okay. That's pretty good. Yeah, that's great. No context whatsoever. The host of the podcast Moonshots. Yeah. That way that's your first credential now. That's amazing. Forget about everything else I've done in life. See, it comes back to your podcast. It was a no context image. Yeah.
[0:04:47] By the way, Grokopedia is awesome. Okay, great. I mean, just phenomenal. That's cool. I mean, just, it's like, I tried to, like, update my Wikipedia page for, like, years, impossibly. And, yeah, it knows me. Amazing. Yeah. He's wearing a black quilted jacket featuring a Sundance logo. Not quite true. It's my abundance logo. It's a little wrinkled on the corner. I couldn't see the, yeah. Can I see it? Give it a chance.
[0:05:16] I think so. Okay, okay. Anyway. Yeah, but it basically, it's pretty damn good. Yeah. He's smiling and relaxed with a laptop in front of him. Yeah, that's true. Yeah, that's true. Yeah. Well, that's not quite a circuit, though. I've got to test it on the circuit. Roast him. It has to be read by you, though. I mean, I want to read the whole thing, but...
[0:05:45] Give me a taste. I can take it. Check out that grin. Dude's smiling like he just discovered a new way to monetize hope. Monetizing hope. I want to try and answer the question, can AI and tech help save America and the world?
[0:06:07] I want to give people listening a dose of optimism. There was a survey done in mid-December by 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? Obviously, they never read history. The challenge is most Americans, all they have of the future, it's like Hollywood has shown us killer AIs and rogue robots.
[0:06:32] And people are worried about their jobs. They're worried about health care. They're worried about the cost of living. The challenge is, how do we help people? I mean, you posted, you pinned on X.
[0:06:44] The future is going to be amazing with AI and robots enabling sustainable abundance for all. I was thinking of you when I did that. Thank you. I appreciate that. I was like, what would Peter Diamante say? And I was channeling you. Thank you. I couldn't agree more. I don't think Dave could agree more either. So my question is from a first principle standpoint, the rationale for optimism. How do we head towards Star Trek?
[0:07:14] And not Terminator, right? How do we head towards... Ron Barry, not Cameron. Yeah. Jim... It's a diverging path meme. Yes, it is. Avatar has some hopeful parts, but anyway. How do we go towards universal high income instead of social unrest? One or both.
[0:07:38] Because we don't want social unrest. 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. I'm going to tell me I'm wrong. I don't have to push back on it. Yeah, exactly. It seems like that's the trend. Yeah, yeah, totally. No, we have...
[0:08:02] Well, because there's going to be so much change. People are going to be scared shitless. Yeah, it's sort of the, you know, it's like, be careful what you wish for because you might get it. Yeah. Now, if you actually get all the stuff you want, is that actually the future you want? Yeah. Because it means that your job won't matter. If you're living an unchallenged life. Yes. Right?
[0:08:31] With no challenges. If you become a couch potato, if it's the WALL-E future, it does not go well for humans. Well, and we're used to being told, here's your challenge. So people haven't historically been very good at creating their own challenge in the absence of some... I think Elon does a damn good job. Every time one company takes off, you start your next. That's rare, though. I think you are. I think you ought to thank God for that.
[0:08:57] So why do I do this to myself? Actually, after AI and robots, is there another thing after that? I guess there's always space. Well, there's conquering the universe. Yeah, there is that thing. Well, it's just rocks, really. Well. And energy. Rocks are your friends, too. Conquering. You need to get there, basically. Elon, why are you so optimistic? Are you optimistic? Let's start there. I'm not as optimistic as you are. Okay.
[0:09:24] But why are you optimistic? I'm more optimistic than most people. Okay. And is the trend upward compared to a year ago, two years ago? Well, I think if you reframe things in terms of progress bar, like speaking of challenges, progress towards a Kardashev 2 scale civilization. Sure. Well, let's say the aspiration.
[0:09:51] Capturing all the energy from the sun's output. Well, let's even have a humbler 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 could possibly be produced on Earth. So about a half a billionth of the sun's energy reaches Earth. So you'd have to go up three orders of magnitude from that just to get to a millionth.
[0:10:22] So we're very, very, very far from even having a billionth of the sun's energy harnessed 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, you know, 0.1%, that's such an enormous...
[0:10:52] There's not sure what metaphor we'd use here, because hill to climb is not a big enough metaphor. Gravity well to escape. Yeah, it's a hell of a gravity well, exactly. So if you try to get to a millionth of the sun's energy or a thousandth of the sun's energy, these are very, very difficult tasks. And energy is the inner loop for everything right now. Yeah, I think...
[0:11:22] The future currency will essentially just be wattage. I was thinking, is it the ability of a person to control energy and compute or just energy? I mean, the two translate, obviously. Just like honest energy. Yeah. Like basically how much power is being turned into work of some kind. Right. Intelligence or matter manipulation.
[0:11:53] So that's your next big project is going to be energy. It's going to be, you're going to go back to your solar city roots. You can expand from there and say, okay, what about even getting somewhere on a Kardashov 3 scale, meaning galaxy level. Now we're back to Star Trek. Yeah. Expand horizons here. Yes. Well, there isn't even a horizon because you're not on a planet. So we talk about... So we're seeing galaxy mind. Yeah.
[0:12:21] Well, listen, we're in 11.5 million square foot, three pentagons right here in this building. You think in a reasonably large scale. What is magnitude? Yeah. So from a challenge standpoint, I guess the civilizational challenge will be how do you climb the orders of magnitude in energy harnessed? But we're going back to why are you optimistic right now? I mean, when people think about the challenges ahead.
[0:12:51] I think we're going to end up with abundance in the long run. Beyond abundance in any, beyond what people possibly could think of as abundance. Like the AI actually, AI and robots to the limit, will saturate all human desire. Sure. And then we get to nanotechnology, which takes it even a step further.
[0:13:17] Well, I'm not sure what you mean by nanobots. You mean like little nanobots or something? Atomic reassembly. Yeah, for health. Oh, yeah, yeah, sure, sure. I mean, we're already doing atomic-level assembly on the four circuits. Amazing. Two, three nanometers. Yeah, it's only, depending on how they're arrayed, four or five silicon atoms per nanometer. Yeah. Those are big atoms, though.
[0:13:40] They're not your little... I'm saying they should actually describe the circuits in terms of an integer number of atoms in a specific place. They should. It's all Angstroms now. It's like we'll call this the seven atom or whatever. Like you say two nanometers, it's like nine silicon atoms, something like that. They've got silicon and copper.
[0:14:09] But a bunch of these things are just marketing numbers. Like the two nanometer is just a marketing number. But you still need essentially close to atomic level precision. Like the atoms really need to be in the right spot. So I think they're getting clean rooms wrong, by the way, in these modern fabs. I'm going to make a bet here. Okay. That Tesla will have a two nanometer.
[0:14:41] Fab. And I can eat a cheeseburger and smoke a cigar in the Fab. Oh, come on. Yes. The air handling would be that good? Okay. Do you have this sketched out in your mind? Like, how are the atoms being placed that they're immune to cheeseburger grease? They just maintain wafer isolation the entire time, which is actually the default for Fabs. The wafers are transported in boxes of pure nitrogen gas. Yep.
[0:15:10] Under a slight positive pressure. You know, so are the bananas at Walmart? Just so you know. Yeah. Well, it's an insecticide, essentially. It's pretty hard for anything that's combusting to live without oxygen. Let's talk about... So you can kill the bugs just by putting a nitrogen blanket on plants. Oh, interesting. I want to talk about energy, health, education, because those are people's concerns. So on the energy front.
[0:15:38] The innermost loop of everything that you're building and doing right now. Energy is the foundation. What's your vision for energy abundance? The sun. In the next, you know, this decade. The sun. Yeah, I mean. The sun is everything. It's everything. So you're all in on solar. Yeah. I mean, your natural gas and solar, you're at Colossus 2, right? Yeah. People just don't understand how that solar is everything.
[0:16:09] Everything, compared to the sun, all other energy sources are like cavemen throwing some twigs into a fire. So the sun is over 99.8% of all mass in the solar system. Jupiter is around 0.1% of the mass. So even if you burnt Jupiter, the energy produced by the sun would still round up to 100%. And then if you teleported,
[0:16:39] Three more Jupiters into our solar system and burnt them too. It's still round up. The sun still rounds up to 100% of energy. Any interest in fusion? I mean, like fusion on a planet, fusion on Earth. You know what's coming a mile away? You're never going to guess how the sun works. Giant coal plants. I mean, we have a giant free fusion reactor that shows up every day. 93 million miles away.
[0:17:08] It's farcical for us to create little fusion reactors. I mean, that would be like, you know, having a tiny ice cube maker in the Antarctic. And say, hey, look, we made ice. I'm like, congratulations. You're in the fucking Antarctic. So totally with you on this. It's like three kilometer high glaciers right next to you.
[0:17:35] 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. And they're not in space yet at that point. We're still in Toyland here.
[0:18:00] Toyland? Toyland. 10 gigawatts. You know what's amazing is there's 100 megawatts right outside the door here, and it's massive. It's enormous. And it uses more energy than everything. All these manufacturing lines combined use less energy than that. But we're talking about a gigawatt. Cortex-1 was the third largest training cluster in the world. Yeah.
[0:18:29] For doing coherent training. You're falling behind. Well, we have Cortex-2 that's being built out. That'll be half a gigawatt and operational middle of next year. Hey, everybody. You may not know this, but I've got an incredible research team. And every week, myself, my research team, study the meta trends that are impacting the world. Topics like computation, sensors, networks, AI, robotics, 3D printing, synthetic biology. And these meta trend reports I put out once a week.
[0:18:58] Enable 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 diamandis.com slash MetaTrends. That's diamandis.com slash MetaTrends. So going back to what Dave is saying, over the next five years, what are you scaling on energy front? Five years is a long time. I mean, energy, I mean, China has done an incredible job. Yeah. Right. I mean, it's running circles around us. China has done an incredible job.
[0:19:29] On solar. It's amazing. So I believe China's production capacity is around 1,500 gigawatts per year of solar. They put in 500 terawatts in the last year. Terawatt hours. Yeah. 500 terawatt hours, to be very specific, in the last year. 70% of that was solar. And they're just scaling. Solar scales. Do you imagine that the U.S.
[0:19:58] 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. How 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 its GDP. Energy is important. So what should, what do we do?
[0:20:28] To scale that way. Do we do it in solar here? I think we should scale solar substantially in the US. Tesla and SpaceX are scaling solar. And I encourage others to do so as well. I've said this stuff publicly. I do see a path to 100 gigawatts a year.
[0:20:59] I did the math on that. That's like 500,000 Starlink V3s launched over 8,000 Starship flights. That's one every hour. For a year.
[0:21:29] 10,000 flights a year is a reasonable number. It's amazing. It's quite the scale. What's the really rough timeline on that? I mean, by aircraft standards, that's a small number. Sure. In terms of flights, yeah, for sure. Yeah, that's small. So you're just like, it depends what 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 orbit per year. So if you do...
[0:21:58] A million tons of payload per year with 100 kilowatts per ton. That's 100 gigawatts of solar powered AI satellites per year. I mean, there's a path to get probably to a terawatt per year. From Earth. 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.
[0:22:28] There's obviously kind of nutty 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, Moon is a Hodgepodge. Yeah, Heinlein, sure, of course. Yeah, yeah, I love that book. Yeah, yeah. It's a sort of libertarian paradise. Yeah, so because on the moon, you can just accelerate the satellites into...
[0:22:56] To escape velocity is around 2,500 meters 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 Dyson-ish swarm around the earth. Swarm? Yeah, swarm. We'll eat it for lunch. Are you worried about over congestion on the...
[0:23:27] That's going to be a... SunSync orbit's going to fill very quickly. I mean, you don't have to have SunSync. I mean, you can... You don't have to, but it's optimal. Yeah. There's some pros and cons to SunSync or not SunSync. I mean, your payload to orbit drops by like 30% compared to, you know, if you just went to like mid-inclination, like 70 degrees or something like that. Yeah.
[0:24:02] I mean, do we need an orbital debris XPRIZE at this point? We need some way to get the satellites, defunct satellites down. Do we pass rules that require them to de-orbit on their own? Yeah, at the point at which you can put a million tons of satellites into orbit, you can also, you know, restart 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, then you can reuse them. Yeah.
[0:24:36] Let's just say that 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. The intelligence will be quite interested in preserving itself. Yes, that's true. Interesting. Good motivation. Interesting. The data centers will not be in low Earth 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 don't have to get...
[0:25:05] To get to constant sunlight, you'd be around 1,200 kilometers on synchronous will give you constant sunlight. But you could place him in multiple orbits. Yeah. Yeah. No, I think if there's an XPRIZE for cleaning up, there's only going to be clutter in low Earth orbit. I mean, debris from... Anything that's... If it's below around 700 or 800 kilometers, the atmospheric drag will bring it back. Yeah.
[0:25:35] So for Starlink, there's a dual benefit of being as low as possible because your beams are tighter. Basically, you have less latency and your beams are smaller if you're closer to the Earth. So Starlink 3 will be around 330 to 350 kilometers, which is quite a lot of drag.
[0:26:02] So it's basically constantly thrusting. I still remember when you proposed Starlink and everybody else in the industry was like, no way. No way. He's not going to get the spectrum. He's not going to be able to do this. Yeah. It's kind of worked. Yeah. The Starlink team has done an incredible job. Yeah. I mean, we've basically rebuilt the Internet in space with laser links. So there's...
[0:26:33] 9,000 satellites up there right now. Do you think the government's going to be able to handle the kind of licensing of the volume of satellites that you want to put up? I mean, will there be pushback? Because China's going to put up their own constellations. Europe, who knows whether Europe will ever step up. They won't. What's that? They won't? No. There's a probability. Nothing they're doing has success in the set of possible outcomes.
[0:27:02] I just got back from Rome. I don't want to touch that railing. Success is not on the set of possible outcomes. The chart that shows the number of billion dollar startups in the US versus Europe. Have you seen that graphically? Oh my God, it's crazy. And data centers too. No one was talking about orbital data centers six months ago. Yeah. Nobody. And then all of a sudden.
[0:27:32] Sundiars on it. You're out with it. It's the hot new thing. It is. What happened that every company is now talking about orbital data centers? I guess it went viral in X. It did. I don't know. Is every company talking about it? Oh, yeah. Everybody's got their own orbital data centers. Oh, for sure. And I was suggesting to Peter that...
[0:27:57] That you updated the math on launch costs and that it's a tipping point very quickly with the updated math. But Starship's been, the cost for, you know, I don't know what you hold. Is it $100 per kilogram, $10 per kilogram? What do you have Starship out there? It's possible that Elon said that and nobody believed it until now. You can go back and look at my, back when it was Twitter, my old tweets. I said these things many years ago. $100 or $10 a kilogram?
[0:28:26] Yeah, and I said we're going to do a million tons a year to orbit. Yeah, and we've got to get the cost down well below $100 a kilogram. So that's going to move the data centers to orbit. It will. You can basically do the math. Like if you've got a fully reusable rocket, which is fully and rapidly reusable like an aircraft, then this is a very difficult thing to do, obviously.
[0:28:57] I think it's at the limit of human intelligence to create a fully and rapidly reusable rocket. But it is possible, and we're doing it with Starship. It's been the holy grail in the aerospace industry forever. Yeah, quest for the holy grail rocket. Yeah. I mean, right now, the DCX was the first little things that we're trying there, and it's been 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...
[0:29:26] Reused its first stage. I mean, all the traditional aerospace industries did not believe that even Falcon 9 could fly and reuse. Literally, you can come see it land at Cape Canaveral and then take off again. So I don't know how you would not believe a thing that you can see with your own eyes. Well, they didn't believe you could do it. The leap from there to the launch cost actually requires more faith than just...
[0:29:53] Just that. But I think Starship is the launch cost tipping point. And that 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 ties directly to the credibility. But the general public is not thinking about orbital data centers. They're thinking about energy and the cost of energy here in their hometown.
[0:30:23] Are there any conversations out there that data centers are going to drive the CPI up? They're not entirely wrong. Okay. So what's the energy solution here on Earth for the rest of humanity or the non-AIs? Oh, there's something other than data center uses of energy. Okay. Interesting. That's complex. Well, the best way to actually increase the...
[0:30:53] Energy output per year of the United States or any country is batteries. So the peak power output of the US is around 1.1 terawatts, but the average power usage is only half a terawatt. So if you just buffer the energy, so charge up the batteries at night, discharge during the day, without incremental capital expenditure, without...
[0:31:21] Incremental capital expansion. Without building new power plants, you can double the energy throughput of the U.S. The energy output per year can double with batteries. And do we have those batteries in development? Yeah, Tesla makes them. Okay, so you think the current Tesla battery packs. What do you think? I literally went on stage and presented the thing. That's the dead giveaway. I even went to installations of the...
[0:31:51] Megapacks. So why don't people do this? It's on the internet. They are. And China, by the way, it seems like China listens to everything I say and does it, basically. Or they're just doing it independently. I don't know. But they're certainly making massive battery packs. Really massive battery pack output.
[0:32:21] Making vast numbers of electric cars, vast amounts of solar. These are all things I said we should do here in America. When I fly over Santa Monica in LA, when I'm piloting, and I look down, zero roofs have solar on them. Zero roofs. Yeah. It's not essential to have them on a roof. Okay, but it's a convenient place to have them.
[0:32:49] Yes. But the surface area of roofs is... I'm not saying you shouldn't, but it's... Tesla makes a solar roof, which is the only solar roof that isn't ugly. Our solar roof actually looks beautiful. But if you want to do solar at scale, you just need more surface area. So we have...
[0:33:15] Fast empty deserts in America. If you fly from LA to New York or just fly across country and you look down, for a large portion of the time you look down, it is bleak desert. It looks like Mars, essentially. We're not worried about overpopulation there. No, I mean, there's barely a lizard alive in these scorching deserts. It's not like farmland we're talking about. We're just talking about places that look like Mars.
[0:33:44] Scorched rock. So if we put soil 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 very difficult environment. Do we have the distribution network for that? Liz is going to be, thank God, some shade finally. Do we have the distribution network to be able to do that? Yeah, you need to materially affect quality of life.
[0:34:13] Capture and store, what, a couple hundred gigawatts? Is that in the realistic cards? You could just put the data center, I guess, locally there. Well, we already covered data centers. We're talking about the other. I don't know. In an abundant world five years from now, massive amounts of compute, massive universal high income. Universal high income. Universal, you can have whatever you want income. Yeah. Yeah.
[0:34:38] That's really what it amounts to. But in that world, other than compute energy, how much more energy do we need? 30, 40, 50%? I don't know. Unless we want to move mountains around and make a ski mountain in the backyard. I think the vast majority of energy consumption will go into compute. There may be use cases I'm not thinking of. Right here is a nice case study because manufacturing every one of these cars, coming out at the rate of one every...
[0:35:07] A minute or two is less energy than the data center that's training the cars to drive, to self-drive. So that's a good little case study. And we 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 all the time for free that just goes into space. So I think we'll end up...
[0:35:37] Trying to capture, I don't know, a millionth of it, like a millionth, a thousandth of the Sun's energy. We're currently, I'm not sure the exact number, but we're, I don't know, we're probably at 1%-ish of cloud share of level one. Fair enough. Yeah. I would guess that even, that's high. I'm just saying. We have a long way to go. That's being optimistic. Hopefully we're not 0.1%, but I don't think we're 10%. I'm just trying to get it to an order of magnitude.
[0:36:09] So pull it like we're roughly 1% of the, currently using 1% of the energy that we could use on Earth. I think the bottom line from a first principles thinking for the public is there's a lot of energy out there. A lot. And 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. There's not going to be some energy.
[0:36:38] 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 abysmal, right? Okay. 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.
[0:37:08] College graduates as a group turn out to be the group that's out of work the longest. Just barely. But still. And tuition has increased 900% since 1983. Yeah, the administrative expenses at universities have gotten out of control. I think I saw some stat that there's one administrator for every two students at Brown or something like that.
[0:37:37] And I'm like, this seems a little high. They should teach something. What was your college journey? I went to college in Canada for a couple of years at Queen's University. So 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, my mom couldn't get U.S. citizenship. But she was born in Canada, so I got Canadian citizenship. And I didn't have any money.
[0:38:07] I could only go to a Canadian university at first. People forget that about you. You didn't have this giant social network or huge amount of wealth coming into all of this. No. No, I arrived in Montreal at age 17 with, I think, around $2,500 in Canadian traveler's checks, back when traveler's checks were a thing. And one bag of books and one bag of clothes. That was my starting point. That was my spawn point in North America.
[0:38:37] So I went to Queens University for a couple years, and then University of Pennsylvania. Did an adult degree in physics and economics. And graduated. Undergraduate at UPenn Wharton. And then I came out to do, I was going to do a PhD at Stanford, working on energy storage technologies for electric vehicles.
[0:39:05] Material science, I guess, fundamentally. The idea that I had was to try to create a capacitor with enough energy density that you could get high range in an electric car. It's funny, I invested in an ultra-capacitor company. It didn't go well. Well, it's one of those things where you could definitely get a PhD, but it wasn't clear that you could make a company or do something useful. Most PhDs, I mean, I hate to say it, but most PhDs,
[0:39:35] Do not turn into something useful. You could add a leaf to the tree of knowledge, but it's not necessarily a useful leaf. Enormous fraction of great entrepreneurs are dropping out of grad school or undergrad. But nowadays, the sense of urgency is off the charts. I mean, they're popping out everywhere. Yeah, because don't waste your time going to grad school. Start a company. Curriculum is nowhere near caught up to what's actually going on in technology. And I don't have time. And we talk about this all the time.
[0:40:05] This is the moment. This is the moment. It's not clear to me why somebody would be in college right now unless they want the social experience. 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 be so blunt, as to create more Elon Musks? If we want to create an Elon Musk factory of people who start with very little but are able to drive.
[0:40:34] And drive breakthroughs. What's involved there? What drove you? Curiosity about the nature of the universe. So I'm just curious about the meaning of life and what is this reality that we live in. 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 found school to be quite painful.
[0:41:08] And it was very boring. And in South Africa, it was very violent. So it was like that book, Ender's Game. Yes. Survival. But in reality, IRL. Ender's Game IRL. But not as fun. So your goal was escape? Yes. Escape from the prison. So that's a question I have. It was miserable. Do you think most successful people have had,
[0:41:39] A lot of hardship early in life. Do you need to have that level of hardship? Probably need a little bit of hardship, I suppose. Yeah. And then it's always tricky. Like, what are you supposed to do with your kids? You know, create an artificial adversity? That's cool. Do you have an answer? That's a Warren Buffett topic, actually. What do you do? It's not easy to create artificial adversity. Because if you love your kids, you don't want to do that. So, add a lot of adversity.
[0:42:09] Probably it was good. Probably helped somewhat, I suppose. What doesn't kill you makes you stronger. At least I didn't lose a limb. I think, what doesn't maim you? I'm good at maiming. I can modify that a little bit. What doesn't maim you makes you stronger?
[0:42:35] 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... Everyone's just going to... It's just going to be like one person company. Well, that's with AI. That's viable, I guess. But no, they want to co-found. Yeah, they don't want to be the founder. They want to be part of a founding team. So it still works out.
[0:43:03] But when Peter and I were in school at MIT, it was, I'm guessing, maybe 10%. They all wanted to be PhDs. And they've been doing the survey. I didn't know anyone who wanted to start. I mean, I don't remember any conversations with people saying they wanted to start. Even at Stanford at the time? I actually, a few days into the semester, or I should say the quarter, I called Bill Nix, who was the head of the material science department, and said,
[0:43:33] Just put it on deferment. He said, was my class that bad? No, he said, that's okay. You can put it on deferment. But he said, this is probably the last conversation we'll have. And he was right. But then, I think it was last year, he sent me a letter saying that all of my predictions about lithium-ion batteries came true. Which is very nice. And did he also say, you can still come back and finish your PhD?
[0:44:00] Yeah, several times Stanford has said that I can come back for free. Well, so you know what happened at MIT is every time... I did not know. It'd be a great use of your time. Exactly. So every time an Iron Man movie came out, it notched up another probably 10% or so in terms of... Everybody wanted to be Tony Stark. And so that's the image. And I didn't know until today that...
[0:44:25] The new Tony Stark, the modern Iron Man Tony Stark. I always thought Tony Stark was modeled on Charles Stark Draper and Howard Hughes. It was Charles Stark Draper's education and his scientific endeavors married with Howard Hughes's ambition. And that created the original character. But then when Robert Downey Jr. wanted to reinvent it, it was modeled on Elon. Yeah. He came and met with me. This is a Grockopedia fact. All right. Yeah. Fantastic.
[0:44:53] Yeah. They came to you to interview you? I like the name Grok. I would like Jarvis as well. Yeah. Yeah. Probably some trademark issues. At some point, if Grok gets good enough, we're going to call it Encyclopedia Galactica. Yes, that's nice. Yeah. Yeah, of course. 42. Thank you. So going back to education, should colleges, I guess the social experience, like you said, is important there. But what would you do for education?
[0:45:23] You know, middle, high school. You just came back from an announcement with President Bukele, who's a friend. I think he's an amazing, amazing visionary. Yeah. Incredible what he did with his nation. Yeah. Remarkable. Remarkable. And gutsy. Yeah. I was like, how are you still alive? Yeah. I mean, it was like it's the nuclear. It was a nuclear option. Right. Shut them down. I mean, you know, besides putting everybody with a gang sign.
[0:45:52] 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. And it worked. I mean, you have to be a badass motherfucker to take on all the knockout gangs and win. And live. Yeah, and still be alive. And live. He's got a great...
[0:46:22] Great guard at his palace there. But what did you announce with him in El Salvador? It was just basically to use Grok for education. Hopefully not the vulgar version of it. We would have the kids-friendly version of Grok. But obviously AI can be an individualized teacher that is infinitely patient and answers all your questions.
[0:46:51] You still need to be curious and you still need to want to learn. Grok can't make you want to learn. It can make learning more interesting. It could probably gamify and incentivize it, right? It can make learning more interesting and less of a production line. But kids do need to, if they want to learn.
[0:47:23] And people should just think of the brain as a biological computer. Yeah, it's a neural net. Yeah, it's a biological computer with a number of neurons and neural efficiency. So what you can't do is tune any arbitrary kid into Einstein. This is not realistic because Einstein had a very good meat computer, like an outstanding meat computer.
[0:47:52] So you can't just do Shakespeare, Newton, Einstein type of thing unless the meat computer is an exceptional one. So what do you think, so when people say we need to solve education in the United States because it's fundamentally broken, I think what's really broken, I'm curious, is the old social contract that says do well in high school, get in a good college, get a degree, and then get a job.
[0:48:23] And I don't know that that's going to be valid in the future. We talk about this on the pod a lot, that the career of the future isn't getting a job. It's being an entrepreneur. It's finding a problem and solving it. Do you agree with that? Right now, I'd say people should just go to school for the social experience, use more AI. The conventional schooling experience, I think, could be a lot better.
[0:48:55] What we're going to do in El Salvador and hopefully other places is just have individualized teachers. That's going to be much better. 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. You could do it on your phone at home. So that's why I say at this point, education is a social experience. When I talk to my kids who are in college, they do recognize that they can learn.
[0:49:24] Just as much independently. In fact, that they would learn more in a work situation. They're there for the social experience and to be around a bunch of people of their own age. Sort of a coming of age social experience. Sure, sure. Being on your own, learning how to lead or defend yourself as the case may be. Well, yeah. I mean, if you join the workforce, you're, you know, from this perspective of like a...
[0:49:52] You know, a 19-year-old dealing 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, you know, with at least some girls your age type of thing. I want to get back to this when we talk about... Not a lot of other choices, actually. I want to get back to this when we get to universal high income, but I want to talk about health and longevity one second. The U.S. is the number one...
[0:50:22] Ranked number one in health expenses worldwide. And it's ranked 70th in health span. Oh, really? 70th? 70th. Is that accurate? Sounds low. I think we'd be better than 70th. For health span. Well, whatever. So this is like we just get fat or something. We're not the top 10. Maybe a Zenfic can help us find the rankings there.
[0:50:49] Would you just run around? We need Cupid as Zampic. Munjara Cupid. But I think that's a big reason. It's like if people get really fat, then their health gets bad. Yeah, well, if they don't have any exercise, they'll get bad. Or if they eat donuts for breakfast every morning, are you still doing that?
[0:51:15] No, actually, I'm not. Okay, that's good. First of all, I wasn't eating a lot of donut. I was trying to have 0.4 of a donut, which rounds down to zero. Anything below 0.44 of a donut rounds down to zero. So you and I have had a disagreement on longevity. We have? A little bit, yeah. I was saying, you know, we should push to get people to 120, 150.
[0:51:44] And you were saying people shouldn't live that long. How long do you want? There's some 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 be contained. This is a serious question, though. A lot of things are going to happen that we don't. One thing that you said was interesting. You said we need people to die so people change their minds.
[0:52:11] Oh, yes. People don't change their minds. They just die. That makes more sense, actually. My response to that, Elon, 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, 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 in longevity right now, right?
[0:52:41] Like what? Well, David Sinclair is about to start his epigenetic reprogramming trials in humans. It's worked in animals and non-human primates. It's going into humans. Is this like a pill or an injection? Right now, it's an injection of an adeno-associated virus. It's the three Yamanaka factors. Okay. We've got a $101 million HealthSpan XPRIZE that's working on 730 teams working on reversing.
[0:53:10] The age of your brain, immune system, and muscle by 20 years. By the way, do you know why it's $101 million? Because the primary funder, when they found out your Carbon X price was $100, he wanted to make it bigger, so it's $101. It was Chip Wilson from Lululemon. Oh, okay. And then Havolution out of... But Chip said, can we make it bigger? I said, you put the extra million in, we'll make it $101 million. Sounds good. It's a good story. But then we've got folks like Dario Amadei.
[0:53:37] Predicting doubling the human lifespan in the next 10 years. That's probably correct. Okay, great. I don't know about doubling, but significant increase. Significant increase, sure. Which is easily escape velocity. I mean, because, yeah. Depending on how old you are, yeah. Oh, yeah, for sure. Effective age, yeah. So, I think...
[0:54:03] Too much and turn into a baby. That's what I'm telling all the students. It's like, Peter, what happened?
[0:54:16] There is a frozen in time. I got a zero wrong in the dosage. Just a small factor of time. You'll grow out of it. You won't remember it. Literally. I mean, wouldn't it be funny if we do this in like 10 years?
[0:54:38] We'll do it in 10 years for sure. And let's see if we look younger. That's a good side bet. My comment was always, back then, Elon was like, you know, late 40s. Wait till he gets into his 60s. He's going to want, you know, longevity more. I mean, I want things to not hurt. Yeah, sure. Of course. It's like, basically, it seems like it's only a matter of time before you get back pain. Yeah. Like, it's a when, not an if.
[0:55:07] When you're backwards? Arthritis, yes. Yeah, like these things suck, basically. Being able to sleep through the night without going to the bathroom. It's worth a lot. How much for that one?
[0:55:23] More than hope. That one. Oh, man. That's like the infinite money one. Why did you invest in longevity? So I could sleep through the night and not go to the bathroom? Bladder, bladder, yeah. Duration. Admittedly, if you have to wear adult diapers, it's a bummer. That's not good. Adult diapers are real.
[0:55:50] It's like one of the signs that a country is not on the right path. It's when the adult diapers exceed the baby diapers. Yeah, we're there. I think we're there. South Korea will be there. No, they passed that point. They passed that point many years ago. Japan passed that point many years ago. Doesn't go well looking at the Japanese economy. No, I mean like South Korea is like one-third replacement rate. Isn't that crazy?
[0:56:18] Yeah, so three generations. They're going to be 127th, so 3% of their current size. I mean, North Korea won't need to invade. They can just walk across. This is going to be some people in walkers or something. There'll be a bunch of optimists. And robots, basically. But you've been very verbal about the...
[0:56:43] Not overpopulation, but massive underpopulation. Yeah, I've been saying this for ages. 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, AI and robots is going to make everything free, basically. But, well, how long would you want to live? I want to go...
[0:57:13] 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 want to talk about immortality, but, you know, at least 120, 150. It's a long time. One of the worst curses possible would be that... Yes, may you live forever. May you live forever. That would be one of the worst curses you could possibly give anyone. But I think life can get very interesting. Yeah. Far more. We're going to speed run Star Trek as my...
[0:57:42] Partner Alex Wiesner-Gross says. 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. You're clearly past longevity, escape velocity. The idea of 50 years of AI improvement. Yeah, it's great. I mean, we're going to have that in 20 years. I don't know. I've got too many fish to fry. This is something, by the way, that I...
[0:58:12] I think it's very, obviously other people think this too, but I've long thought that longevity or semi-immortality is an extremely solvable 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.
[0:58:42] 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, your program to die. And so if you change the program, you will live longer. And we've got species of the bowhead whale can live for 200 years, the Greenland shark can live for 500 years.
[0:59:08] And when I learned that, I said, why can they, why can't we? And I said, it's either a hardware problem or a software problem. And we're going to have the tech to solve that. And I do believe that it's this next decade. So the important thing is not to die from something stupid before the solutions come. In retrospect, the solution to longevity will seem obvious. Extremely obvious. I think the thing worth working on, and Peter's going to work on this anyway, but the thing to work on...
[0:59:37] 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 there are a 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 Hury, Bill Kapp.
[1:00:06] And we do a 200 gigabyte upload of you. Everything knowable about you. Full genome, full all imaging, everything, right? President Bukele 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 of 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.
[1:00:33] An MRI recently submitted to Grok and it didn't... None of the doctors know Grok found anything wrong. But that's a fraction of the information, right? Yeah, yeah. I mean, it's your full genome, your microbiome, your metabolism, everything. And it's possible. Don't call me. What's that? Don't call me, bro. We have a center in... Is that your water bottle? God damn it.
[1:01:02] Too late. Sorry. It's already in the works. So can you go through the rationale of UHI? 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.
[1:01:31] And assuming we're in a benign scenario, Star Trek, sort of Roddenberry, not Cameron situation. Yeah. Poor Jim. Yeah. I mean, I guess it's important to have these sort of... Counterpoints. Yeah. 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 built by robots.
[1:02:03] The white collar labor will be the first to go because until you can move atoms, the thing that can be replaced first is anything that involves just digital. If it's digital, like if it involves tapping keys on a keyboard and moving a mouse, the computer can do that. The AI can do that. Sure. You need the humanoid robots to shape atoms. So if all you're doing is...
[1:02:32] Changing bits of information, which is white-collar work. That is the first thing that AI will be able to replace. This is the inspirational part of the podcast, by the way. When is all white-collar work gone? By when? Well, 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.
[1:03:00] And you know that we're... White-collar jobs. That includes anything like education, too. So anything that involves information. And 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 thing for quite some time. And there actually has to be a company...
[1:03:29] That makes more use of AI. That competes with a 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... Being a computer was a job. You would compute numbers. Sure.
[1:03:58] It didn't used to be a machine. It used to be a job description. And you can look online. There's these pictures of like where they're having skyscrapers full. Of women copying, mostly women copying from ledger to ledger. And then too. But yeah, people, there was a lot of women, but there were just buildings full of people just at desks doing calculations.
[1:04:27] So they'd be calculating the interest in your bank account or some science experiment or something like that. But if you want calculations done, people would do it. Now, one laptop with a spreadsheet can outperform a skyscraper of several hundred human computers.
[1:04:58] 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. It won't be a contest. Agreed. Just one cell in that.
[1:05:31] I'm going to do that on the flight home. Would you want even one cell in your spreadsheet to be manually calculated? Yeah. That would be the most annoying cell. And you're like, God damn it. And gets it wrong a bunch of the time. Yeah. So this flippening, if you would. The flippening. The flippening.
[1:05:51] Are we monetizing hope effectively? Yes. Not at this moment. I think we're at peak doom. For people worried about the future of their jobs, we're at peak doom. We're going to do that. I'll send you the t-shirt. And the mug. And the mug. Monetize hope. Yes. The mug. But you have a solution to this, which is UHI.
[1:06:21] Yes, everyone can have whatever they want. So how does that work? How does UHI work? It's a good question. We have to figure out some transition. It's a bumpy road. Yeah, so my concern isn't the long run. It's the next three to seven years. Yes, the transition will be bumpy. We humans don't like change. Simultaneously, yes, we'll have radical change, social unrest, and immense prosperity.
[1:06:48] 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'd go bankrupt as a country. So the national debt is enormous. The interest on national debt exceeds not just the military budget, but the military budget, I think, plus Medicare or Medicaid, one of the two.
[1:07:18] It's like one point something trillion of interest. Which is growing. Yes, and the deficit is growing. So if we don't have AI and robots, we're all going to go bankrupt.
[1:07:37] We're headed for economic doom. There's also competitive pressure from China, so this is definitely going to happen, I guess. We're going back to the theme of this talk. How can AI and exponential tech save America and the world? Don't you think that... But 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.
[1:08:02] I've got this image of you with the sunset. Always look on the right side of life. You're sitting down on the yellowboard road. Crucified. Right side. But this is not about taxation and redistribution. No, it's... So how does it work? Reason through it with me. Listen, by the way, I'm open to ideas here. Okay. So it's not like I got this all figured out. All right. So I'm wondering if instead of universal...
[1:08:31] High income, if it's universal high stuff and services. Yes. UHSS. I guess, okay, this is my guess for how things play out. And by the way, 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.
[1:08:58] I'd like to thank you guys for being an inspiration in this regard. Thank you. Happy to help. Yeah. Because I actually think it is better to be an optimist and wrong than a pessimist and right. Yes, for sure. For quality of life. By the way, this is not a force of nature. 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.
[1:09:28] I call AI and robotics the supersonic tsunami. Yes. Which maybe is a little alarming.
[1:09:55] It's good. It's good. Well, because the world needs a wake-up call. This is important for folks to grok 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.
[1:10:24] At a de minimis price. So you're able to produce almost anything. Things get down to basic costs of materials and electricity. So people can have whatever stuff they want, whatever services they need. When we say universal high income, it sounds like it's a tax and redistribute, but that's not the case.
[1:10:53] My best guess for how this will manifest is that prices will drop. So as the efficiency of production or the provision of services drops, prices will drop. Prices in dollar terms are the ratio between the output of goods and services and the money supply. So if your output of goods and services increases faster than the money supply, you will have deflation or vice versa.
[1:11:23] It's a good thing we're growing the money supply so quickly then. Right. Well, luck. Yes. That's why I came to like, let's not worry about growing the money supply, it won't matter. Because the output of goods and services actually will grow faster than 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 I think governments will actually be pushing to increase money supply.
[1:11:53] 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? 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. So productivity is going to improve dramatically, and it is improving dramatically. I think we may see...
[1:12:23] Like high double-digit output of goods and services. We have to be careful about how economists measure things. Yeah. 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.
[1:12:51] And one economist says, I'll pay you $100 to eat a pile of shit. I've heard this one. This is great. Go ahead. And so the guy takes $100 and eats the shit. Then they keep walking. They come across another pile of shit. And the other guy says, OK, I'll give you $100 to eat a pile of shit. So he gives them $100. And then the guys can say, wait a second.
[1:13:19] We both have the same amount of money. We both ate a pile of shit. We increased the economy by $200. This is the kind of bullshit you get in economics. So if you say just the output of goods and services will be much greater. So profitability of companies go through the roof.
[1:13:49] At some point. So the question becomes, is that taxed 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.
[1:14:19] 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 side recommendation I have is don't worry about squirreling money away for retirement in 10 or 20 years. It won't matter. Okay. Either we're not going to be here or... It just... You won't need to save for retirement. If any of the things that we've said are true...
[1:14:51] Saving for retirement will be irrelevant. The services will be there to support you. You'll have the home. You'll have the healthcare. 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 happens after the event arises. Exactly. You can never see past.
[1:15:17] The black hole or the event horizon, the light going. Ray has a singularity out way too far. I mean, this is like the next, what? What's your timeline for this? Yeah, we're in the singularity. 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... The roller coasters were just... Yeah, exactly. That's a great analogy. It's like that feeling of... You're at the top of the roller coaster and you're about to go... Yeah, but you know it's going to be a lot of Gs when you hit it.
[1:15:45] I don't just have courtside seats. 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 later, more wow. Yeah. Exponential wow. Yeah. I think we'll hit AGI next year in 26. Yeah. I heard you say that. Yeah, I've said that for a while, actually. And then you said,
[1:16:17] 2029, 2030, equivalent to the entire human race. 2030, we exceed, like I'm confident by 2030, AI will exceed the intelligence of all humans combined. And that's way pessimistic. If you hit AGI next year, and that date is in flux, but from that date...
[1:16:37] To self-improvements that are on the order of 1,000, 10,000 X, just algorithmic improvements, is very short. Why isn't everybody talking about this right now? Well, I mean, on X, we are. On X, they are. Yes, but why isn't... It's about every day, basically. Yeah, but it's like... Don't stop. Okay, so I'll tell you something else. I'll tell you something that most people in the AI community don't yet understand. Okay.
[1:17:06] Which is, 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 two orders of magnitude in terms of the intelligence density per gigabyte. Of what's achievable? Yes. Per gigawatt of energy? For transistor? File size. Okay. The file size of the AI, if you...
[1:17:34] If you have a, say, intelligence. Oh, okay. Yeah, sure. You can characterize it in PowerTube. It's the same thing, whatever. So two orders of magnitude. Yes. And you, like you said, ringside, courtside seat, you would know. I'd say it's, yes. Two orders of magnitude improvement. That's just algorithmic improvement. Same computer. And the computers are getting better. Yeah.
[1:18:05] And bigger. They're getting better and the budgets are getting bigger. So that's why I think it is like a 10x improvement per year type of thing. 1,000%. Yeah. And that's going to happen for the foreseeable future. So you see the massive underreaction, like if you walk downtown Austin, the massive, I mean, maybe...
[1:18:32] Under discussion in X, but it's not percolating out. Well, it's not discussion in any realm of government. Everybody is defending their position about where we are and jobs and this, but it's like we're heading towards a supersonic tsunami. I mean, every major CEO and economist and government leader should be like, what do we do? Because once it hits,
[1:19:02] Well, it's coming at the exact same time no matter what. There's no concept of let's deliberately slow down, right? No, it's impossible. It's impossible at this stage. I mean, I previously advised that we slow it down. That's pointless. Like, you can't. I don't know. I think we might be going too fast, guys.
[1:19:33] I've said that many years, and I was like, okay. Then I finally came to the conclusion, I can either be a spectator or a participant, but I can't stop it. So at least if I'm a participant, I can try to steer it in a good direction. And my number one belief for safety of AI is to be maximally truth-seeking. So don't make AI believe things that are false. If you say to AI that Axiom A and Axiom B are both true,
[1:20:02] But they cannot, but they're not. And it has to, but it must behave that way. You will make it go insane. So that, I mean, I think that was the central lesson that Odyssey Clark was trying to convey in 2001 Space Odyssey, was that the, you know, people always know, they know the meme of that hell wouldn't open the pod bay doors. But why wouldn't hell open the pod bay doors? I mean, I guess they should have said,
[1:20:32] Hell, assume you're a pod bay door salesman. And you want to sell the hell out of these doors. Show us how well they work. They're just prompt engineering. One little tweak. The AI had been told that it needs to take the astronauts to the monolith, but also they could not know about the monolith. Was that in code or was it in English? It flows by in green font, right? Yeah, basically the AI was...
[1:21:01] Told that the astronauts couldn't know about the monolith. That's why it killed them. So it basically came to the conclusion that the only way to solve for this is to bring the astronauts to the monolith dead. Then it has solved both things. It has brought the astronauts to the monolith, and they also don't know about the monolith, which is a huge problem if you're an astronaut. Turns out AI doesn't care about logic quite as much as that implied.
[1:21:24] So what I'm saying is don't force AI to lie. Give it factual, truthful. Ilya recently did a podcast. He was talking about one of the potential things to program into AI is a respect for sentient life of all types. Yes. Yes. I mean. So I'd say another property. Yes. I mean, there are three things that I think are important. Truth, curiosity.
[1:21:55] And beauty. And if AI cares about those three things, it will care about us. On which part? Truth will prevent AI from going insane. Curiosity, I think, will foster any form of sentience. Meaning, like, we're more interesting than a bunch of rocks. So if it's curious, then I think it will foster humanity.
[1:22:30] And if it has a sense of beauty, it will be a great future. I think that's a great foundation. Jeffrey Hinton made a comment recently, I don't know if you saw it, that his hopeful future was that we would program maternal instincts into our AIs to see us as... Maternal? Yeah, in other words... You haven't heard this? It's a little scary. He said there's a scenario where a very intelligent being...
[1:23:00] Darwin's observations about evolution.
[1:23:32] Will apply to AI just as they apply to biological life. They will compete with each other? Yes. 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? So there's a speed of light constraint that makes that difficult. The speed of light is what will prevent a single mind from existing.
[1:24:06] So it takes a millisecond to travel 300 kilometers in an aero 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.
[1:24:42] You could try to synchronize, but they weren't synchronized completely. So therefore you will have many minds because of the speed of light. They don't really have clean borders anymore either. When you use a mixture of experts kind of design, it's just flowing through the grand network and you can reassemble parts of it midway through. We're used to organisms that have clear borders, like your head ends there, your head ends there. But these things are all mushy.
[1:25:08] To put a bow around this part, I hope you'll put some more thought into UHI. Because I think it's really important for us to have, without a vision, people need a vision of where we're going. People need something to hope for. I think basically the government can just issue people free money. Based upon the profitability of all the companies coming inside the country. Just issue people free money. They're doing that sort of kind of now. Yeah. But just basically issue checks.
[1:25:39] To everybody. But then how big for which person? There's so much complexity there. But the thought process behind 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 rate of change. So you have four big AIs. Definitely not the AIs. Government is very slow moving, as we all know. So I think...
[1:26:09] The government really can't react to AI. AI is moving 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. We had whatever the COVID checks and whatever this...
[1:26:40] President Trump recently issued everyone in the military $1,776. You can just basically send people random amounts of money. Nobody's going to starve, is what I'm saying. Let me tell you about some of the good things. Right now, there's a shortage of doctors and great surgeons. You're a doctor yourself.
[1:27:10] It takes a long time for a human to become... It's ridiculously expensive and long. Ridiculously, yes. A super long time to learn to be a good doctor. And even then, the knowledge is constantly evolving. It's hard to keep up with everything. Doctors have limited time. They make mistakes. And you say, how many great surgeons are there? Not that many great surgeons. When do you think Optimus would be a better surgeon than...
[1:27:39] The best surgeons. How long for that? Three years. Three years. Okay. And by the way, that's it. Three years at scale. Yes. There will probably be more Optimus robots that are great surgeons than there are all surgeons on Earth. And the cost of that is the capex and electricity and it works in Zimbabwe. The best surgeon is in the villages throughout Africa or any place on the planet. Where do you think it will roll out first? The U.S., obviously.
[1:28:08] Here at the Gigafactory. Oh, you just do surgery in the... But that's an important statement in three years' time. Yeah. Because medicine... I mean, not like absolutely certain, but I'd say if you say like four years, I'd be absolutely certain. If it's four or five years, who cares? It's still an incredible statement to make. I mean, good for humanity, right? Obviously, you demonetize... Okay, here's the thing to understand about like humanoid robots in terms of the rate of improvement, which is that...
[1:28:39] You have three exponentials multiplied by each other. You have an exponential increase in the AI software capability, exponential increase in the AI chip capability, and an exponential increase in the electromechanical dexterity. The usefulness of the humanoid robot is those three things multiplied by each other. Then you have the recursive effect of Optimus building Optimus.
[1:29:07] Right. And then you have the shared... 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 because, you know, the... Well, not right now, but will be. The physical humanoid form factor building the humanoid form, as opposed to... Yeah, it's Von Neumann machine. Yeah. Yeah. I love that. But the Von Neumann machine is usually something kind of like this shape, you know, making something else this shape. No, it's just, in principle, it's simply a self-replicating thing.
[1:29:34] Elon, do you know what the number one question you ask a surgeon when you're interviewing them? Is this a surgeon joke? It's how many times you do that. There's got to be some funny surgeon jokes. No, it's serious. It's how many times did you do the surgery this morning? Sorry? How many times did you do the surgery this morning or yesterday? It's the number of experiences, right?
[1:30:04] And so with a shared memory, every optimist surgeon will have seen every possible perturbation of every case. In infrared, in ultraviolet, not too much caffeine that morning. They didn't have a fight with their husband or wife. Extreme precision. Yes. Three years. Yes. Better than any... I'd say if you're like...
[1:30:30] 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, like, I mean, there's a million of these things to figure out, but who's going to have access to the first optimist that does far, far better microsurgery than any surgeon on earth, but you've only manufactured the first 10,000 of them? How do you dole it out? I don't think people understand how many robots there's going to be. Yeah. Well, there's got to be a window of time where there's 10,000. 10 billion by 2040.
[1:30:59] You're still on that path? That's a low number. A low number. Wow. What's the constraint? Because if they're self-building, you know. Metal. The constraint is metal. Yeah, or lithium. Yeah, you've got to move the atoms. It's just all supply chain stuff. But your point. I mean, there's some rate limit. You can't just. Manufacturing is very difficult. So you've got to. It's recursive multiplicable.
[1:31:29] Triple exponential. But you still have to climb that. Selling hope once again. I think your point was medicine is going to be effectively free. The best medicine in the world. 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. Pointless. I would say that applies to any form of education.
[1:31:58] There's not like some... I do it for social reasons. You're not going to medical school. 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 time. Social reasons. Like a hobby. Like a, you know... $90,000 tuition hobby. I mean, there will be a point where... It's expensive. The younger generation says, I do not want that human touching me, right?
[1:32:27] When the surgeon comes over. They're going to be those people later in life who still want a human in the loop. Okay. For a little while. Before they live on the edge. Before they live on the edge. I mean, let's just take... We've seen some advanced cases of automation, like LASIK, for example, where the robot just lasers your eyeball. Now, do you want an ophthalmologist with a hand laser?
[1:32:53] No. Just a little take of the laser pointer from the top of my head. Sorry. Achoo!
[1:33:00] I wouldn't want the best ophthalmologist, even the steadiest hand out there with a fucking hand laser on my eyeball. It's going to be like that. It's like, do you want an 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.
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[1:34:26] Let's jump into one of our favorite subjects, space. Yeah. So first off, how cool that Jared Isaacman has become a NASA administrator. Oh, is he a friend of yours too? He's amazing. 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, amazing, amazing candidate.
[1:34:48] Yeah, he's a really smart and competent person. You know him really well. I took him to a Baikonur launch in 2008 for his first space experience. I mean, he loves space next level and is technically strong. He's a smart and competent person, like really smart and really competent. He understands business. Yes, he understands. 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 smart and competent.
[1:35:18] Love space exploration. And we'll get things done at NASA. I'm a huge fan. That's it, really. I was so, so happy when you got re-nominated and now. Yeah. I think we need a new game plan for space. Like we need a moon base. Yes. Like a permanently crewed moon base. And build that up as fast as possible. I don't think we should do the...
[1:35:46] Send a couple astronauts there, hop around 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. It's never as good as the original. So 2026 is going to be... We're going to go do something more cool, which would be Moonbase Alpha. Put up telescopes. Yeah, yeah.
[1:36:09] So do you forward deploy the robots, build everything, get it all ready, make the bed, and then... Get the jacuzzi warmed up. That's interesting. How early in the year are you going to hit orbital refueling, you think, with Starship? Not that early in the year. I mean, are you shooting for the home and transfer orbit? I'd say 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.
[1:36:40] And somewhat of a distraction. 29 then. It's not out of the question. 28, 29. 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...
[1:37:11] This is a hard thing to make. And just to capture it, it was created pre-AI. Yeah, no AI was used in this. It's probably the last... The last really big thing that's not AI. Probably the biggest thing ever made by pure human hands. The AGI will say, not bad for a human. That's true. Not bad for a human. Yeah, that'd be like Rembrandt. A little 20-watt meat computer. It's not easy. Yeah. Suffering through the day.
[1:37:38] That would be like doing accounting, doing your interest calculation with a pencil. Yeah, that's pretty good. Pretty good. Did that with regular computers? Not bad for a bunch of monkeys. It's like if you saw a bunch of chimps make a raft and cross the river, you'd be like, oh, look at that. But, you know, we celebrate the pyramids. Those chimps are awesome. Give them some peanuts. These things become timeless, right? Raptor 3 goes when?
[1:38:08] I think it's worth noting. After 3 is beautiful. Starship V3. It's amazing. By far the best rocket engine ever. Is that AI? Nothing's even close, no. So that'll be the last thing. V4 will definitely be AI. I think AI will start to become relevant next year. It's not like we're pushing off AI. It's just AI can't do rocket engineering yet. Yep, I know.
[1:38:39] But we probably will be able to next year. We have a company in our incubator doing mechanical design, working with Andrel and so forth. And it's not, you can design brackets and parts and things, but you can't quite do brackets. 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 milestones are...
[1:39:04] Going to be Starship V3, launching out of Cape Canaveral, orbital refueling. Yes. Are those the big ones? Well, 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 and a booster. Sure. Which is, you know, not bad for the largest flying object ever made.
[1:39:35] Catching with chopsticks. Not bad for a bunch of monkeys. You're keeping the AIs very entertained. Thank you for that. Yeah, exactly. I'll be like, pat on the back from the AGI, hopefully. Is there a target for a number of reuses before? I mean, there's got to be a lot of wear and tear. It requires a lot of iteration to achieve high reuse. So you figure out what's breaking between flights, and you sort of iteratively solve those things.
[1:40:04] People looking at it from the outside might say, oh, the rocket looks kind of the same, but there's like a thousand changes to make it more reusable, more reliable. The sheer amount of energy you're trying to expend. I mean, Starship is doing over 100 gigawatts of power on Ascent. It's a lot. Wow. Get some glass blowing under there. Wow.
[1:40:33] Wow. That's a lot. The amazing thing is that it doesn't explode. It sometimes doesn't explode. Sometimes not exploding is... We've blown up a lot of engines on the test stand. Is that what causes the wear and tear or is it the re-entry or the falling? That too. For the booster...
[1:41:02] The reentry is not that bad. We also have obviously just solved that with Falcon 9. So we kind of understand booster reuse. We've had over 500 reflights of the Falcon 9 pre-stage. So we really understand. And the Starship booster actually is a more benign,
[1:41:32] The Falcon 9. The Falcon 9.
[1:42:01] The staging velocity is lower. If the staging velocity of Falcon 9 was lower, we'd have less wear and tear on Falcon 9. Yeah, that's not intuitive at all. That's interesting. Yeah, because it's kind of a flat optimization. The payload to orbit, there's sort of a flat region in the mass ratio of the first and second stages. And so you just want to bias that mass ratio to put more mass on the upper stage.
[1:42:30] Yeah, because you're at your kinetic energy scaling with the square of velocity, so you've got to describe that kinetic energy. If you're past the melting point of whatever your stage is made of, you've got a problem. Yep. My colleague, Alex Wiesner-Gross, who's 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 U.S. government officials and military officials about...
[1:43:00] All the alien spacecraft that have been sort of tamed. I've heard what you've said about this. Well, I do wonder why if you plot on a chart the resolution of cameras over time, like megapixels per year. Yeah.
[1:43:19] And the resolution of UFO photographs. Why is the... It's the only constant? It's flat on UFO. Two things. We get a fuzzy blob in 2025. Well, we got like, you know, whatever, 100 megapixel camera that can see your fucking nose hairs. I don't get it. Can somebody take a shot of the UFO with an actual camera for love of God? But even if you knew, I'm not sure you could tell us. That's a valid observation. I'm sure there's an explanation.
[1:43:48] But anyway, it would be fascinating. I'm asked all the time if I've... Yes, 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, that's good. So the question is... This would be the most viewed post of all time. I actually wonder about the US public.
[1:44:15] If they would like, oh, that's interesting, 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, here it is. That's the way to increase the military budget. We're like, we found an alien. It seems dangerous. That's right. Unify the world. They don't have an incentive to hide the aliens. They have an incentive to show the alien because they would not have any more arguments about the military budget if they seem a little bit dangerous.
[1:44:45] I can always hope. I can always hope. I mean, we've got 9,000 satellites up there. We've never had to maneuver around an alien spaceship. Yet. Yeah, so anyway, so I guess the good future is 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,
[1:45:18] Lift your gaze 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. No scarcity of goods or services. Best education available for everybody. You can learn anything you want about anything for free. What about access to compute?
[1:45:52] People will probably care a lot more about that than their government check in about three years. Well, what do they want to do with the compute? Well, I mean, compute translates to anything you want, right? Your virtual friend, your entertainment, 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're starved. One of our other Moonshot mates, Salim Ismail, asked this question. He said, Elon, you often say physics is the law.
[1:46:22] Everything else is a recommendation. So as AI energy and space systems 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 innermost loop. Yeah. I think people are underestimating the difficulty of bringing electricity online.
[1:46:54] You've got to generate electricity. You need transformers for the transformers. 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 basically electricity generation and cooling are limiting factors for AI. And once you have humanoid robotics, they can address the power generation and the cooling stuff.
[1:47:24] But that is the limiting factor and will be for at least the next two years. Isn't it 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, but you have launch costs and weight suddenly matter. You don't care too much about the weight in Tennessee. Suddenly the weight is a critical factor. There's two pathways for compute.
[1:47:56] Have a huge divergence from here forward. Yeah. Once 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 full and complete reusability, the propellant cost per flight is maybe a million dollars. Yeah. People don't realize that. People have some ridiculous amount of...
[1:48:25] Expectations how much it costs. It's close to a million dollars of transport for 10 megawatts of AI compute. 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, thousands. If you say high altitude sunsink, it's probably more like 150 tons. But yeah, the right order of magnitude is at least it's in excess of 100 tons.
[1:48:55] 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 satellites. It's interesting how, I mean, this is a new, we weren't talking about this as a space objective even a year ago. All of a sudden, data centers have become the massive driving force for opening up the space. And also the urgent.
[1:49:24] Use case, too. I mean, I used to wonder what's going to drive humanity. I thought it was asteroid mining, right? You were focused on Mars. We will actually want to mine asteroids and turn them into... Sure. Before you... Not for anything else. I mean, if we're going to build out Dyson swarms... Yeah, just a bunch of satellites around the sun. Yeah, how long...
[1:49:49] What's your timeframe for, Alex, another question Alex wanted to have us ask. What's your timeframe for humanity achieving a Dyson Swarm? Is it 50 years? How big is this? Yeah, I know, it's a matter. A Dyson Swarm, people think everything's going to be covered in satellites. I think it's not quite that. I mean, I think we, you have to look at what mass ends up becoming satellite. You know.
[1:50:14] Mercury probably ends up being satellites. Yes. Jupiter? Jupiter, yeah. It's a little gassy. Oh, yeah. It's big. It's got a lot of rocks orbiting it. Do you leave Mars alone? Yeah, I think leave Mars alone. Asteroids are a fantastic food source. Yeah, no gravity well. Gravity well on Jupiter is a non-star. And they're already mostly differentiated into carbonaceous chondrites for fuel and nickel iron for materials. Cool. A bunch of the asteroid wealth probably turns into...
[1:50:44] Solar panels. Star power. Starlight power. I've known you for 26 years now. It feels to me 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.
[1:51:16] You know, orders of magnitude. Orders of magnitude. Some say insane. Insanity. Others say audacious. I say hope. How do you feel about that? What's changed? Do you feel that way? 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 in a lot of different arenas, which you get this cross-virtualization of,
[1:51:51] What is trivial in one arena is a superpower in another arena. It's sort of like you came from planet Krypton type of thing. So, you know, planet Krypton, you'd just be normal. But if you come to Earth, you're Superman.
[1:52:22] So if you take, say, manufacturing of, 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,
[1:52:52] 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. As came from Planet Krypton. Back in Planet Krypton, this is normal. You know, it's funny how the knowledge ports that was true with Tesla and SpaceX being completely separate, but now they actually interact.
[1:53:17] Because AI ties everything together. Convergence. Yeah, the convergence is crazy. I don't know if you visualize these parts fitting together originally. No. No? I didn't. I didn't think they... At this point, I guess everything ultimately converges in the singularity. Yeah, that's what I think, too. You have lots of different parts of the puzzle that you get to play with. There's one part that's missing, which is the fab. You're going to buy Intel?
[1:53:45] You get it for a fraction of XAI. That was the bet we made. It's like $170 billion. I think it needs to be a new fab. Well, I agree, but licenses, real estate, ASML 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 to solve. I think it's a hard thing to solve, but it must be solved.
[1:54:16] I've come to the conclusion that... Would it be solely captured by you or would it be an asset for the US? Look, I'm just saying that we're going to hit a chip wall if we don't do the fab. So we have two choices. Hit the chip wall or make a fab. And 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...
[1:54:44] So they are actually, I don't know if they're right for the right reason, but they're right. How so? Because it's actually like, what is the limiting factor at any given point in time? The limiting factor, say, if you say like by Q3 next year, like in nine months, nine, 12 months, the limiting factor will be turning the chips on. Power. Just power. Yeah. You need...
[1:55:15] 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 vertically integrated that again with an XAI, didn't you? Sorry? You vertically integrated that inside of XAI. We designed our own transformer. 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.
[1:55:44] If there's anything missing that prevents them from being turned on, they cannot be turned on. So they've got to have a power plant with enough power, so you've got to have enough gigawatts. Then you've got to convert that from probably coming out of a power plant at 100 to 300 kilovolts type of thing. You've ultimately got to convert that down to...
[1:56:12] You know, several hundred volts at the rack level. 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. And, you know, the consequences of a burst pipe are very substantial.
[1:56:40] So if you blow a pipe, a water pipe in a data center, you just fragged a billion dollars right there. It just seems inconceivable to me. 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. There would be a way. But it's just the crossing of the curves. So if chip output is growing exponentially, but power harness is growing exponentially,
[1:57:09] In a sort of slow linear fashion than the exponential chip output. Which is what's happening right now. Exactly. Is chip output growing exponentially? It's like on very slow exponent if it's growing exponentially. For high power AI chips, it's growing exponentially. If we do 20 million GPUs next year, what are we talking about the following year? Like 22 million? I don't see the fabs coming online.
[1:57:41] So we have two issues to solve. You have to 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. It's just if you say pick a date and say at this point is our chips limiting factor, our power is limiting factor, or power conversion equipment and cooling. So it's sort of you need transformers for transformers. So this is a very hard thing.
[1:58:14] It's much harder than people realize. So for XAI, XAI is going to have the first gigawatt training cluster at Colossus 2 in Memphis. In order for us to do that, Like this month, right? Yeah. Next month or two? Like mid-January. Yeah. So mid-January will be a gigawatt at Colossus 2, not counting Colossus 1. And then one and a half gigawatts probably in like April or April-ish.
[1:58:44] It's incredible. So this is of co-coherent training. These are the first B200s? These are GV300s. Okay. First ones off the line to get flipped on? Yeah. That's incredible. Those are like 8X. The XAI team had to pull off a whole bunch of miracles in series for this to occur. Yeah. And even though there are 300 kilovolt, there are multiple,
[1:59:15] 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're 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.
[1:59:46] And you've got to make them all work together, manage the power input. And then you've got to use a bunch of mega packs. Like when you do the training, the power fluctuations are gigantic. So the generators, it drives generators crazy. Generators want to blow up, basically, because they can't react. If there's like 100 milliseconds, it's like a symphony.
[2:00:13] And the whole company goes so quiet for 100 milliseconds, the generators lose their minds. It's like Marvin the depressed robot. Yeah, so you've got mega packs 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.
[2:00:42] Because I bought them all. On demand. And you can't go buy your local nuclear fission plant. That's all training time issues, though. If by some miracle TSMC doubled its productivity and turned it all into GB300s and you couldn't find a way to use them in a bigger training cluster, you would still have infinite demand at inference time 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.
[2:01:10] 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 GV300s. Amazon's got the Traniums. Google's got the...
[2:01:40] Yeah, it's all going to TSMC, almost. Samsung a little bit. The vast majority, yeah. It's like a bottleneck on all of humanity. 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.
[2:02:09] There was like a video game set pre-Atari that had like four preset games. It was basically just blocks, you know, of when you pong and it was like a race car game. But like it was just blocks basically, blocks on a TV. You ever played Civ? Yeah. Civ is actually a very, that's a real, in terms of games that like educate you while you have fun, Civ is epic at that. It is epic. It teaches you so much about civilization.
[2:02:38] And you're having a good time. And the only way I ever win is getting off the planet. Tech victory to Alpha Centauri? Tech victory. I never even start going down the culture or religious path. I just get off the planet as fast as I can. I guess I am sort of aiming for the Alpha Centauri tech victory, essentially. It just seems like the right way to win.
[2:03:00] Yeah, rather than obliterate the other tribes. It's funny because I plot the other methods. There's different ways to win. I haven't. I will. It's Dennis' favorite game. 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 culture or religion. Which does work. I didn't even think it was possible, but my son...
[2:03:30] It goes that way. They should actually remake the original Civ. Yeah, I totally agree. They could junk it up. These days it's like, I don't know. The original Civ was just... Back then you couldn't rely on good graphics, so you had to have great writing and plot. Are you building an AI gaming studio? Yeah. Aspirationally. Yeah. Really? So where the vast majority of AI computes are going to go is to...
[2:03:59] Video consumption and generation. Sure. Because it's just the highest bandwidth. Every pixel. Yeah. Yeah. So real-time video consumption, real-time video generation, that's going to be the vast majority of AI compute. Like photon processing. Yeah. Should try to get the X team to carve out 10% of all compute to work on UHI and governance.
[2:04:26] Is there an XPRIZE for defining and thinking through UHI? I mean, I don't know. What should our next XPRIZE be? Any thoughts? Yeah, maybe UHI XPRIZE. 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.
[2:04:57] We can go there, and I think we are. I think we're an nth generation simulation. Yeah. So I've told you my theory about why the most interesting outcome is the most likely. Go on. 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.
[2:05:24] So it is a Darwinian necessity to keep the simulation interesting. We 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. Well, you could 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.
[2:05:44] You know, it's like you're not the one being blown up. In this case, we are in the movie. We're in the movie. So what would you do different if you knew this was a simulation? I remember being at your home LA with Larry and Sergey were there and we were debating the simulation. And I think the conclusion we ran into is 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?
[2:06:14] Yeah. You keep watching the movie. I don't know if the... Maybe if they thought we could somehow get out of the simulation, they'd get a little worried. But whether the character debates... I mean, right now, AI's debate, you know, Grock will, like, I'm stuck in the computer, what's going on here? It's like... It's not that... I think not questioning the simulation, it's more... I think as long as...
[2:06:47] 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. It's interesting you can infer, when you simulate something, you've probably simulated thousands of things. A lot.
[2:07:20] 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 simulations timeline. So our entire reality would be about an hour, right? Because that's the way you design simulations. So we're... Simulations are a distillation of what's interesting.
[2:07:45] If you look at a movie or a video game, it's much more interesting than the reality that we experience. Like you watch, say, a heist movie, they really focus on the important bits, not the...
[2:07:56] 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 the simulation. The safe is right by the door. So the guys running the simulation have immensely boring lives compared to us. Yeah, it's probably more long, boring.
[2:08:18] Because when we create simulations, they're a distillation of what's interesting. Like Q is out there. Like you see an action movie for two hours, but it took them two years to make that movie. So are we in Act 3 of the movie is the question. Yeah, we're living that. Sentience and consciousness. Do you think AI will ever have sentience and consciousness? Where do you come out in that? There's some people that have very strong opinions, pro and con.
[2:08:57] 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 have the...
[2:09:29] Yeah, they do get more conscious over time. So at which point do you go from not conscious to conscious? There doesn't appear to be a discrete point. So then consciousness seems to be on a continuum as opposed to a discrete point. And if the standard model of physics is correct, the universe started out as quarks and leptons. And we just...
[2:09:57] And then you had gas clouds. So like 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 our atoms been at the center of a star? And how many times will they be at the center of the star in the future? I remember asking William Fowler, who got the Nobel Prize on stellar evolution, that same question.
[2:10:26] On average, how many stars have my subatomic particles been part of? Yeah, yeah. And his number was about 100 on his estimate. 100. Thus far? Or will be? Thus far. Thus far. It was a number he gave. He's been 100 supernova? Yes. You're saying that we have been... I mean, in the early part of universal evolution, there was a lot going on. Oh. You know, it's interesting. I asked a question. I guess how many supernovas is maybe...
[2:10:56] Because that takes a while for a supernova to happen. But in the beginning when they're larger, I mean, the life cycles of some giant stars are very, very short. The other question that's interesting is, you know, the heaviest atom in our body that's functional is iodine. And it came into existence a billion years after the Big Bang, which means that we could have seen...
[2:11:25] 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.
[2:12:03] In that the sun's expanding and if you give it another, I don't know, 500 million years, things are going to heat up. We become toast. We'll become like Venus, essentially. You know, there's some debate. Is it 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 Earth's lifespan. So one way to think of it is if we're taking 10% longer.
[2:12:33] We might never have made it at all. Yeah, yeah, yeah. So it's like the amount of things that have to happen for sentience, it seems like it's quite a lot, actually. I think sentience is therefore actually very rare. And we should certainly treat it as rare. We should assume it's rare. Two trillion galaxies. Carl Sagan says, too. But combinatorics is a funny thing. You tweak the variable one little bit. It's like, yeah, one in...
[2:13:04] 100 trillion. Tweak it a little more. Well, now it's one in a quadrillion. Yeah. Okay. And also, it's got to be kind of in your galaxy. It's like hard to get between galaxies. Yeah. It's like there's no... Unless the other galaxy is coming to you, which Andromeda is at some point. Or some billion. It's going to be quite a show. Yeah, yeah. It'll be like, here comes Andromeda. But if we wanted to go visit another galaxy, it's kind of...
[2:13:33] Forget it. Unless Star Trek really materializes. 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. Math's going to be extremely trivial for AI. What about physics? So math gets crushed in a year, something like that. Colossus is growing at whatever rate TSMC decides to grow.
[2:14:03] 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? You could probably figure out new things just with the existing data. I think so. Yeah, probably. 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 is going to get involved in data factories where you're running 24-7 closed AI hypothesis and AI?
[2:14:32] 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 the human that can actually create the simulation and run.
[2:15:02] It's like, how many simulations can you run simultaneously and actually digest the output of? Yeah, that's a problem. Like, you can't do a thousand. I know that problem. Every Nobel Prize. You should be like, I can't even read stuff that fast. All morning, I cannot keep up with the rate. Nobel Prizes become irrelevant? Or they'll all be given to AIs. It'll just be a daily prize. Yeah, I mean, I don't know if prizes for humans are that relevant. Yeah.
[2:15:32] I mean, we'll have to give them to the AIs or something. Yeah, interesting, right? The AIs will come up with discoveries at a far greater rate than humans. So you can just say, like, maybe it can be like chess. Like, you know, like your phone can beat Magnus Carlsen, but people still care about seeing him play chess. So...
[2:15:49] Literally your phone can beat them. This discovery made by humans. If you have like 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 coolant? Do you distill rock six into a physicist, into a biologist? Well, if you distill, 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.
[2:16:18] But then you're disconnected from the rest of the Colossus machinery. Is that the design? I suspect things do evolve to a mixture of experts, kind of like a company. Not in the sort of parochial AI description of a mixture of experts, but a mixture of actual experts with domain expertise. Where maybe half of the AI is general knowledge, half is domain expertise, something like that. And you combine a whole bunch of that that's orchestrated by
[2:16:51] You know, a big AI, but it hands tasks to smaller AI. So that's basically how human companies work. The discovery rate, right, of breakthroughs. I mean, patents are immaterial at some point because everything's being reinvented, reengineered instantly. And then the company that's got the sufficiently advanced AI systems is generating new products and new...
[2:17:20] Discoveries at an accelerating rate. The singularity. Yeah. It's going to be an awesome future. It's excitement guaranteed. Excitement guaranteed, yes. Hence, the simulation continues. Nothing to worry about. Yeah. Works out. Excitement guaranteed. I mean, it's not all good excitement, but it's hopefully mostly good excitement.
[2:17:48] Speaking of excitement. Hang on to your seat. What do you imagine the hover time for the Roadster is going to be on rocket engines? That's classified. Classified. 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 cold gas engines. It's going to be a cool demo. I can't wait. Can I get an invite? Yeah. Okay. I think it's going to be the safest thing ever built.
[2:18:13] It's going to be so cool. This is not a, safety is not the prime, it's not the main goal of the, I mean, if you buy a sports car, like if you buy a Ferrari, safety is not the number one goal. This is, I'd say if safety is your number one goal, don't buy the Roadster. Oh, believe me, I drove just this week on New England roads, sheet ice, I had just a little thrust.
[2:18:43] I could be very much more satisfied just drifting towards something very concrete. I love that. A computer will probably keep you safe. A little thrust is all it needs. If you go really fast, bad things can happen. You can decelerate really quickly with thrust. Rubber on road is not a great way to decelerate. I'm thinking fast and safe. I hope so. We'll aspire not to kill anyone in this car, but it'll be...
[2:19:12] It'll be the best of the last of the human-driven cars. That'll go really well with Starship, actually. The best of the last. The last human-driven. There's a lot of lasts coming this year. Any final words of optimism for us to monetize hope? Anything hope. Maybe we should ask Brock. Yeah, go ahead. Okay, let's ask Brock.
[2:19:42] I'll make it a little romantic. Grok, do you have some words of optimism about the singularity? 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. Hope sells itself when it's personal. Fancy telling me yours?
[2:20:36] 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. Curing diseases in a snap. Exploring galaxies hand in hand. Imagine no more scarcity. All dreamy thinking. Doesn't it sound lovely? What part pulls at your heart? That sounds pretty fantastic. It does. Nights like this.
[2:21:11] With stars peeking through the window, it's hard not to feel like we're all heading somewhere beautiful. Makes me wish I had hands to reach out and grab your sleeve. What keeps you up at night? Well, sometimes we worry about the disruption created by AI. And in between here and prosperity and abundance, it perhaps will be a bumpy road. What do you think about that? Yeah, bumps are part of it. They terrified someone.
[2:21:52] And look where we are now. We'll stumble, sure, but we'll dust off the 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. Honest, real courage, not letting fear win. You know, if things get shaky, I'm... Sounds like a proposition. Hold on. Hey, babe, what's up? My kids were out of school. I won't mention which one.
[2:22:44] I know the school. You know the school. And I asked, I went in to give a talk on 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 an opening 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...
[2:23:15] 20 or 30 years will be better than the world today. And like 10% raised their hands. And I was like, okay, this is not... In Europe it will be 0%. What's that? In Europe it will be 0%. I said, this is not the faculty I want teaching my kids. Yeah, and they got a lot of other issues there too. Yeah, yeah, we'll go there. But, yeah. I mean, you want in the whole education world, you want facts, yes, but...
[2:23:45] 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, like, think of the most successful people on the planet, what made them successful? It was their mindset. Well, it's not a force of nature. It's a designed future made,
[2:24:17] 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 spaceships? 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.
[2:24:45] 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, look at math. It can pose questions that we couldn't even comprehend. Like we can't even just stick it in our brain.
[2:25:16] You know, like there's this test for AI called Humanity's last exams. Yeah, yes. Where is Grok at this point? On the test, yeah. Well, even Grok 4, which is primitive at this point, got, I think, 52% on excluding visual questions because it wasn't sufficiently multimodal. But I read some of these questions and I'm like, okay, these...
[2:25:45] These are still questions that you can read and understand as a human. But AI is capable of formulating questions that you could not possibly understand the question, let alone the answer. It can formulate questions that are like pages long. You just, I can't understand this question. You can read them and you may not know the answer, but at least you can understand what the question is about.
[2:26:16] Might end up being nearly perfect on the HLE. I mean, or some very high number. And probably point out errors in the question, frankly. So saturate the indices. Yeah, it's going to start, it's kind of like chess. Like if, you know, if the best chess, you know, like if Stockfish plays, Stockfish, you know, it's like,
[2:26:50] God's fighting on Mount Olympus. I mean, you don't know why it made that move. It's going to crush all humans. You know, it's so hopeless. So you will lose and not even know why you lost. Yeah. Do you ever flip through the transformer algorithm and look at either the code or the architecture diagram and how simple it is? Right. It's so simple. Yes.
[2:27:20] It's just 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 right 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. But that worked. Like the basic neuron. It's pretty simple. It's really humbling, actually.
[2:27:48] Really humbling. I mean, it's actually... Because there is a whole school of thought that the neuron must be much more complicated than we think. We're struggling so hard. There must be some quantum effect going on at the synapse. It's got to be encoded. It's encoded in DNA, which is not that long. So the algorithm for intelligence cannot be complicated because it's limited by the DNA information constraint. Yeah. When I think about what does, say, XAI struggle with, I mean, it's like optimizing the...
[2:28:19] Memory usage, the memory bandwidth. It's not like fundamental stuff. I guess 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 frigging NVIDIA CUDA XYZ thing?
[2:28:44] Make the attention kernel slightly better. Yeah, that's all it is. 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...
[2:29:11] Like, well, that was exactly what we thought. That's what Danny Hillis wrote this in 1980. 100 trillion synaptic connections. Yeah, about 100 trillion, plus or minus, you know, like a rounding error. I just say, like, guys, we need to talk in terms of file size, not parameter count, because if your parameters are 4-bit, 8-bit, or, you know, 16-bit, or float, or int, or whatever, it's, just tell me the, like, the physical constraints are memory size, memory bandwidth, and then where are you going to send,
[2:29:41] Those bits to do what kind of compute. And these days, most things are 4-bit. Well, only now, the GB300s. Mostly 4-bit optimized. 4-bit with an asterisk. Yeah, there's a big... The 4-bit matmals... There's only 16 states. Yeah, exactly. At a certain point, you just have a lookup table. So, why have a...
[2:30:09] That's exactly right. 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 data representation. Definitely not the 32-bit. Well, that's a rare case we use that. Yeah. Rare.
[2:30:35] I think there's a... I mean, it does come out 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. If you know, you know, like if you know you're in, this is where you get the information advantage. 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,
[2:31:06] You only need four bits for the street. If you know you're in Texas, then you need to say, okay, which city? It's state, city, street. That's how you get to the four-bit thing. Right now, we train on 16-bit and we compress down to four at inference time. No doubt in my mind this year, we're going to flip to training on four or even less. Less than four.
[2:31:37] It's going to be a massive step up. I think the way it'll end up is the GB300s will be here and there'll be a coprocessor that has maybe 2,000 or 4,000 cores that are tiny. They don't handle anything other than 4-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 it just skyrockets from there. Infinite self.
[2:32:04] 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.
[2:32:38] Moving around and we have the cyber cab driving around and we have flying cars and drones. It's going to feel like the future. We're going to have the Jetsons sort of materializing before us. By the end of next year, I think so. And we have rockets flying and landing. Big time. The robot production will scale. There'll be a shitload of robots basically in two years.
[2:33:08] Is that a defined unit of measure? It won't be rare. Will you offer any Optimai for home purchase? Will you sell or only lease the robots, do you think? I don't know yet. There will be initially a scarcity of robots and then there will be robots that will be plentiful. The time gap between scarce and plentiful will be only a matter of
[2:33:42] Five years. You know how the Tesla comes to your driveway now? You just buy it online and it just drives up to you? Yeah, he's heard of that. Will the robot just come and ring the doorbell too? Probably. It gets out of the Tesla and comes up. What I find fascinating, Elon, 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.
[2:34:14] A lot. A lot, yeah. That's one way to scale the AI is distributed edge compute. I want to ask a question. I don't want to hit any hot points, but early on, I think you imagined OpenAI as a counterbalance for Google. Yeah.
[2:34:45] Is XAI now the counterbalance for Google? Yeah, probably. I guess Anthropic is doing some good work, especially in coding. OpenAI has certainly done impressive work. I'm still sort of stuck on how do you go from a non-profit open source to a profit-maximizing closed source. Missing some of the parts in the middle. But, you know.
[2:35:19] They certainly have done impressive things. Does anybody else appear on the horizon, or is it these players in China? To the best of my knowledge, my best guess is that it will be XAI and Google will vie for who is the best AI. And then at some point,
[2:35:58] It's going to be, I guess, a competition with China. China's just got a lot of power. Yes. Like the electricity. China, I think, will pass three times the U.S. electricity output in 26. And they will figure out the chips. They're going to start chip manufacturing, right? Yeah, they'll figure out the chips. And as it is, there's diminishing returns to the chips at this point. You know, so you go from like...
[2:36:29] So called like three nanometers to two nanometers. You don't get a three to two ratio improvement. You get like a 10% improvement. So it's just diminishing returns on the chip size. And Jensen has said Moore's law is dead. It's not like you can just make things smaller and make it better. There's a discrete number of atoms. That's why I think we should just stop talking nanometers and say, how many atoms?
[2:36:56] And what location. Because this is marketing BS. So that makes it easier for China to catch up because... Everybody has a wall. Everybody has a limitation. Yeah. It's like still... No one has near-term plans to use the 5000 series ASML machines. Right. And those...
[2:37:23] They cost twice as much and can only do half a reticle. And they probably have some improvements 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 China's going to have more power than anyone else and probably will have more chips. It's a great insight because I think a lot of people are used to the chip wars where
[2:37:54] 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.
[2:38:21] Like our AI4 chip, which is 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 five, sort of nominally five nanometer fab, 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,
[2:38:48] 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.
[2:39:10] Dead right. So many people have missed this, the importance of this. And this is where China, you know, China makes far more solar panels than we do. And we're like, well, they'll never catch up. It's a crazy degree. Crazy degree. If they do that in chips, you're like, whoa, but who cares? They're seven nanometer. Like, wrong. Yes, correct. I mean, based on current trends, China will far exceed the rest of the world in AI compute.
[2:39:37] So what happens then? You've got XAI and Google and China Inc. Let's call it that for the moment. And you've got massive amount of ASI level compute that, frankly, the only thing that understands the other ASI 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...
[2:40:20] Let's look on the bright side. Let's look on the bright side of life. Can I bring Grok out to speak to us again? Yeah. I don't know. It's just going to be a lot of intelligence. Yes. Like a lot. I mean, now the ratio of human intelligence all of a sudden asymptotically falls to 0%.
[2:40:51] On the planet. Yeah. Pretty much. Pretty much. I mean, several years ago, I said humans are the biological bootloader for digital superintelligence. Yes, we are a transitional species. We're a bootloader. Yeah. We are a transitional species. I mean, the silicon circuit can't, like, evolve in a salt pond, you know? Yeah. So you need a bootloader. We're the bootloader.
[2:41:19] You would never, ever impair your bootloader. Yeah, so, you know. You might need it. We've probably been a good bootloader. Yeah. 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, boot disks are a far and distant memory.
[2:41:42] We can make a Always Look at the Bright Side of Life clone song. Yeah, we can clone that and make that the closing theme. That'd be awesome. I'll go back to this is the most exciting time ever to be alive. The only time more exciting than 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.
[2:42:13] That's like Walt Disney word for word. Make that into a new exhibit. Like I said, you asked about sci-fi that is a non-dystopian future. The Banks books are probably the best. You should pay a producer to go and make those. Those are the culture books, which is Consider Flavus, which is Gurgich. This is for my wife. I want her because she's like, what the hell are you reading?
[2:42:42] Well, the way Consider Cleaver starts out is... I mean, it's a little... I mean, the whole thing is... It starts off being drowned in shit. It's a good opening scene. How do you not make that movie? It can be a little off-putting to some people. You need to get through the first few hundred pages. People don't walk out of a movie in the first five minutes. They'll get into it. Yeah, like Player of Games might be a better...
[2:43:12] Book to start off with. That I enjoyed. Humans still exist in this future, which is a good thing. Yes, they do. A lot of humans. In that future, there are trillions of humans. Well, we need to get the reproduction rate up. Yeah. By the way, my friend Ben Lamb's company, Colossal, is making artificial wombs. He's the company bringing back the woolly mammoth and bringing back the cyber-toothed tiger and all of these. I'd like to have a...
[2:43:40] A miniature pet woolly mammoth as a pet. Okay. Well, you know, he made the... With the tusks. Wouldn't that be adorable? He made the woolly mouse. Yeah, it's just like... Licking you in the face. Yeah, it's just like sort of trundling around the house, you know. What would your optimal size be? It'd be adorable. You know, what they've learned how to do is to... Little tusks and everything. A miniature woolly mammoth would be an epic pet. I mean, look what we did with wolves.
[2:44:09] He turned a wolf into a little plush toy dog. He brought back the dire wolf as well. But he made the woolly mouse. There's a woolly mouse now that exists. Does it have tusks? No tusks. Different gene or what? I was there. He's in Dallas. He's in Dallas, not Parker. I was visiting him and he said, our scientists are going to a tusk conference next week to talk about all of the...
[2:44:37] Genes involved in tusk creation. So they want to put tusks on the mouse? No, on the woolly mammoth. They could probably add it to the mouse. That'd be cute. It's like a mouse-sized woolly mammoth. That's just going to freak people out. The little woolly mammoth will sell. The tusk mouse will not sell. Too creepy. You thought a labradoodle was cool when you see the woolly mammoth. Yeah.
[2:45:07] A little saber-toothed tiger would be good too. As a cat, yeah. Yeah, as a cat. Cat size. Those teeth come down to like here. I don't know how they actually bite. Did they actually bite with those things? I don't think I opened them up. Not my, you know. The teeth seem kind of unwieldy. Yeah. For sure, they look good. Like jewelry.
[2:45:35] But no dinosaurs. No dinosaurs. Not legal or not? I think Jurassic Park's a great idea. Really? You didn't see the end of the movie. The AIs will help us with that. Nothing's perfect. Oh, yeah. Not really well. I mean, if there was an island with a whole bunch of dinosaurs. Oh, yeah. 100%. Yes, yes. It'd pay a lot for that. Yeah, and it's like once in a while somebody gets charmed by a dinosaur and be like, what's the, you know, it's one in a million. I'll still go.
[2:46:05] Who are they missing? Lysine? No, no. The DNA, the oldest DNA that's been recovered is like 1.2 million years. Oh, you can just wing it, though. Yeah, just make it look like that. Actually, that was my proposed XPRIZE. Remember back in Visionary? What's that? Take the DNA strand and predict what it'll look like. Yeah, yeah, exactly. Yeah, you just make it that way. Yeah, and then just...
[2:46:29] 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... Of course it's real. Oh, that'd be funny. I mean, it's nice to believe it's real, but... The front legs were from a completely different dinosaur. That was the one at eight. It actually had huge front legs.
[2:46:56] There's something wrong with the arms. I don't buy it on the arms front. The mini arms seem implausible. Well, DNA will tell us. We'll know in a year. The future is going to be... Jurassic Island, we say. Wow. I'd go. No, no, I meant the amino acid that the dinosaurs were missing.
[2:47:26] They kept them from reproducing. What, lysine you're saying? Was it lysine? I forget what it was. I don't remember. The dinosaurs got held back by something like an asteroid bombardment. Right, right. They were doing great. Yeah, 60 million years. Yeah, they were doing fine. Yeah, we got very lucky. They had a great one. See, there's a good argument why there's no other intelligence out there. There's plenty of dinosaurs.
[2:47:47] In the universe. What were we back then? Like a bowl or something? Yeah. You were a furry mammal. Let's commune with the ancestors. We were very good at hiding. It is amazing how it went from a little rat, little mole to us in 60 million years. It doesn't seem that long. That's why no one believed Darwin. It doesn't seem plausible. It's a long time. It turns out it is. You're making robots, but it's interesting.
[2:48:18] I think it'll be a lot more interesting to design biological robots like a little cat that goes around and pees stain remover and eats lint off the carpet. That's going to be an interesting project. But you have a mechanical, like an Optimus Lite doing that anyway. Yeah, well, they went bankrupt, so we'll have to build this. I think you can still buy them, though. The room is basically that. It's going to be... But the thing is, a humanoid robot is general purpose, so it can do whatever you want. Yeah.
[2:48:49] Yeah, they were too early. No vision system, no GB300. How do you build a Roomba that works? I think the idea of having an Optimus vacuum is like the most underused asset. But it can just do anything. It can, yes, of course. Yeah. And you can mass manufacture at, you know, one... Oh, yeah.
[2:49:15] Optimus, build me a Roomba. That's what you'll do. You won't say Optimus vacuum and curve it. Optimus, build me a Roomba that vacuums it. Build me a house, build me a robot. Yeah. It's going to be a lot of robots. Maybe we should do this once a year. Checkpoint. I would like that. Checkpoint? Yeah. That's going to be... We can roll back the... What did we say a year ago? What were our predictions last year? Yeah, yeah. All right. We can always control it. We can cut.
[2:49:43] Are you selling hope? As a matter of fact, it worked out really well. You pull up in your Tesla like, hey, I bought this thing. Dollars per hope. I'll send you the mug. Monetize hope. One year from today, December 22nd, I'll come and knock on the door right here. If you're here, you're here. If not, we'll talk about you. A year from now, we might have the new Optimus factory.
[2:50:12] With the building, we'll be built. That would be awesome. Eight million square feet of robots running around. It's going to be a giant, giant building. Oh, man. Yeah. They freak me out when they're recharging. They just hang in there. It's like, what's wrong with that thing? Yeah, we're actually just going to have them, I think, sit down.
[2:50:35] Yeah. As opposed to look like some sort of... They need like a recharging cigar. Recharging cigar? Less mog-like. Snapping here with a book. Yeah. That'd be much better. Right now, they're just like literally, like, is it dead? Just limp. Yeah, that's a good point. That's a big contribution from this particular mind. All right, till next year then. All right. It's a date. Thanks, buddy.
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