Elon Musk explains IP (Intellectual Property), the fabs today all basically use machines from like five companies. Yeah, you know, so you’ve got ASML (ASML Holding), Tokyo Electron, KLA, Lam Research, you know, et cetera.

Elon Musk with Dwarkesh Patel & John Collison – The Future of AI is in Space – Part 8: Terafab, ASML & Chip Manufacturing (Full Transcript)

In Part 8, Dwarkesh Patel points out that even with abundant power from space-based solar, the ultimate bottleneck for scaling AI will likely be chip production. The conversation dives into Elon’s plans for building “Terafabs,” the difficulties of scaling semiconductor manufacturing, and why memory may be an even bigger constraint than logic chips. It then shifts to the broader philosophical mission behind xAI and SpaceX — propagating consciousness and intelligence into the universe.

Transcript:

Dwarkesh Patel noted that even with more efficient solar panels in space, the chips themselves would still be the ultimate limiter long before reaching terawatt scale. He asked how the world would produce a terawatt of logic compute by 2030 when today the entire planet only has about 20–25 gigawatts.

Elon Musk: “You need to build a lot more chips and make them much cheaper.”

Elon Musk: “I guess we’re going to need some very big chip fabs.”

Elon Musk: “I’ve mentioned publicly that the idea of doing sort of a terafab, terabytng the new Giga.”

Dwarkesh asked for details on the plan: what level of the stack they would build themselves versus partnering with an existing fab for process technology.

Elon Musk: “Well, you can’t partner with existing fabs because they can’t output enough. The chip volume is too low.”

Elon Musk: “IP (Intellectual Property), the fabs today all basically use machines from like five companies. Yeah, you know, so you’ve got ASML (ASML Holding), Tokyo Electron, KLA, Lam Research, you know, et cetera. So at first I think you’d have to get equipment from them and then modify it or work with them to increase the volume. But I think you’d have to build perhaps in a different way. So I think the logical thing to do is to use conventional equipment in an unconventional way to get to scale and then start modifying the equipment to increase the rate.”

On November 24, 2025, on a rainy day in Bastrop, Texas, Prufrock-5 left the Boring Company factory.
On November 24, 2025, on a rainy day in Bastrop, Texas, Prufrock-5 left the Boring Company factory.

John Collison drew the parallel to how The Boring Company started.

Elon Musk: “Yeah, kind of like. Yeah, you sort of buy an existing boring machine and then figure out how to dig tunnels in the first place and then design a much better machine that’s, I don’t know, some orders of magnitude faster.”

John Collison asked whether the fact that China has not duplicated TSMC gave Elon pause about the difficulty of building advanced chip production.

Elon Musk: “It’s not that they have not replicated TSMC, they have not replicated ASML. That’s the limiting factor.”

John Collison asked if Elon thought it was simply the sanctions preventing China from advancing.

Elon Musk: “Yeah. China would be outputting vast numbers of chips at leading edge if not for the sanctions.”

John Collison followed up, noting that China had been able to buy 2 nm or 3 nm chips until relatively recently.

Elon Musk: “No. The ASML bans have been in place for a while, but I think China’s going to start making pretty compelling chips in three or four years.”

Elon explained the massive manufacturing requirements needed to match orbital AI ambitions, noting that memory was actually his biggest near-term concern.

Elon Musk: “I don’t know yet is the right answer. So it’s just that to produce at high volume and to reach large volume in say 36 months to match the rocket payload to orbit… You need 100 gigawatts worth of chips. You’ve got to match these things. The master orbit, the power generation and the chips. And I’d say my biggest concern actually is memory… That’s why you see DDR prices going ballistic.”

Elon then shared his current plans and constraints around chip production.

Elon Musk: “I don’t know how to build a fab yet. I will figure it out. Obviously I’ve never built a fab.”

Elon Musk: “I don’t think it’s PhDs. It’s mostly people who are not PhDs. Most engineering is done with people who don’t have PhDs.”

Elon Musk: “Right now, like Tesla’s pedal to the metal max production of going as fast as possible to get AI5 chip design into production… That’ll probably happen around the second quarter ish of next year, hopefully. And then AI6 would hopefully follow less than a year later.”

Elon Musk: “Yeah, and we’ll be using TSMC Taiwan, Samsung Korea, TSMC Arizona, Samsung Texas and we still booked out all the capacity we can.”

Elon Musk: “The point is you’ve got to build the fab and you’ve got to start production, then you’ve got to climb the yield curve and reach volume production at high yield. That from start to finish is a five year period. And so the limiting factor is chips. Limiting factor once you can get to space is chips. But the limiting factor before you can get to space will be power.”

Elon explained that while launching at massive scale from Earth would be extremely difficult, the moon offered a much better long-term path using mass drivers.

Elon Musk: “I don’t see any way that you could do 500 to 1,000 terawatts per year launch from Earth. But you could do that from the moon.”

Dwarkesh then zoomed out to the bigger philosophical picture behind SpaceX and xAI.

Dwarkesh Patel asked whether, by the time humans are sending ships to Mars, Grok would be on board with them, and how that relates to the main risks people worry about with AI.

Elon Musk: “Well, I’m not sure AI is the main risk I’m worried about. I mean the important thing is that consciousness, which I think arguably most consciousness or most intelligence, certainly consciousness is more of a debatable thing. The vast majority of intelligence in the future will be AI… So you want to take the set of actions that maximize the probable light cone of consciousness and intelligence.”

Elon Musk: “Yeah, I mean to be clear, I’m very pro human, so I want to make sure we take sort of actions that ensure that humans are along for the ride. We’re at least there. But I’m just saying the total amount of intelligence, I think maybe in five or six years AI will exceed the sum of all human intelligence. And then if that continues, at some point human intelligence will be less than 1% of all intelligence.”

Elon discusses the need to build massive Terafabs, the challenges of scaling chip and memory production, and the deeper mission of propagating consciousness and intelligence into the future. In Part 9, the conversation continues with more on the long-term vision for humanity and AI in space.

Elon Musk at Davos World Economic Forum, Jan. 2026

Transcript: Elon Musk at Davos World Economic Forum, Jan. 2026

This is my full verbatim transcript of Elon Musk’s recent Davos interview at the World Economic Forum 2026, based directly on his live conversation. I’ve formatted it for you, to help with readability with Elon talking with Larry Fink of BlackRock, and I have kept it as close to word-for-word as possible (including natural speech patterns, ums, and repetitions). I made some minor fixes only for obvious auto-transcription errors to ensure accuracy without changing meaning.

Elon Musk: We are going to make this interesting!

Larry Fink: How many quotes are you going to want that are after this session?

Elon Musk: I don’t know, five, haha!

Larry Fink: Good afternoon everyone, it’s great to see everybody here. It has been an amazing week. Thrilled Elon Musk come from California. Thank you, Elon.

Elon Musk: You’re most welcome. I heard about the formation of the Peace Summit, and it’s like, is that P-I-E-C-E, a little piece? Haha. Or Greenland? A little piece of Venezuela? All we want is peace.

$TSLA

Larry Fink: Okay. As they said, I’m pretty proud CEO BlackRock. Since we went public, the compounding return of BlackRock to our shareholders was 21%. Since Elon took Tesla public, his compounded return is 43%. This is just another advertisement for everybody, especially for Europeans. This is why more citizens should be investing with growth, investing in their countries. Imagine if a lot of pension funds invested with Elon when Tesla went public, and how much return would be with all the pension funds that invested side-by-side with Elon and the growth. So a spectacular return. There’s very few companies—well, I don’t think there is any other company as large as Tesla today that has compounded returns. Congratulations.

Elon Musk: We have an incredible team at Tesla. and so thats the reason!

Larry Fink: I want to get into the meaningful component about technology, the possibilities. I want to talk about AI and robotics, energy, space, and the progress ultimately coming down to engineering. Engineering discipline, scale, execution. Few people, if not anyone, has the experience, and the fortitude to confront these issues head-on—not just ideas, but execution across so many different technologies. Elon, that’s why it is important for us to have this dialogue here in Davos. So you are presently building on AI and robotics, space, energy—all at the same time. When you look across those efforts, what do they have in common from an engineering standpoint?

Elon Musk: Well, they’re all very difficult technology challenges. But the overall goal of my companies is to maximize the future of civilization—like basically maximizing the probability that civilization has a great future. And to expand consciousness beyond Earth.

ALIENS

So if you take SpaceX, for example, SpaceX is about advancing rocket technology to the point where we can extend life and consciousness beyond Earth—to the Moon, Mars, eventually other star systems. I think we should always view consciousness, life, as precarious and delicate. Because to the best of our knowledge, we don’t know if life is anywhere else. You know, I’m often asked, are there aliens among us? And I’ll say that I am one. They don’t believe me.

Okay. So I think if anyone would know there are aliens among us, it would be me. And 9,000 satellites up there, and not once have we had to maneuver around an alien spaceship. So like, I don’t know. Bottom line is, we need to assume that life and consciousness is extremely rare, and it might only be us. And if that’s the case, then we do everything possible to ensure the light of consciousness is not extinguished.

CANDLE IN VAST DARKNESS

Elon Musk: Because effectively, the image in my mind is of a tiny candle in a vast darkness—tiny candle of consciousness that could easily go out. And that’s why it’s important to make life multiplanetary. Such that if there is a natural disaster or man-made disaster on Earth, that consciousness continues. That’s the purpose of SpaceX.

TESLA MISSION

Elon Musk: Tesla is obviously about sustainable technology. And also at this point, we’ve sort of added to our mission sustainable abundance. So with robotics and AI, this is really the path to abundance for all. If you say, you know, people often talk about solving global poverty, or essentially how do we give everyone a very high standard of living—I think the only way to do this is AI and robotics. Which doesn’t mean that it’s without its issues. We need to be very careful with AI. We need to be very careful with robotics. We don’t want to find ourselves in a James Cameron movie—you know, Terminator. He’s great. Great movies. Love his movies. But well, we don’t want to be in Terminator, obviously.

But if you have ubiquitous AI that is essentially free or close to it, and ubiquitous robotics, then you will have an explosion in the global economy—an expansion in the global economy that is truly beyond all precedent.

Larry Fink: Can that expansion be broad? Or is it narrow? And how can it be broadened the global economy?

EXPLAINING AMAZING ABUNDANCE

Elon Musk: Way to think of it is that if you have a large number of humanoid robots, the economic output is the average productivity per robot times the number of robots. And actually my prediction is in the benign scenario of the future that we will—the robots will actually make so many robots and AI that they will actually saturate all human needs. Meaning you won’t be able to even think of something to ask the robot for at a certain point. Like there would be such an abundance of goods and services. Because my predictions are there’ll be more robots than people.

Larry Fink: So but how do you then have human purpose in that scenario?

Elon Musk: Yeah, I mean, you know, there are—nothing’s perfect. But I mean, it is a necessary… Like, you can’t have both. You can’t have work that has to be done and amazing abundance for all. Because if it’s work that has to be done, and only some people can do it, then you can’t have abundance. It’s narrow.

Larry Fink: Narrow.

And definitely we are in the most interesting time in history. I don’t think there is a more interesting time in history! – Elon

Elon Musk: Exactly. So but if you have billions of humanoid robots—I think there will be… I think everyone on Earth is going to have one and gonna want one. Because who wouldn’t want a robot to, you know, assuming it’s very safe—watch over your kids, take care of your pet? If you have elderly parents—a lot of friends of mine have elderly parents, it’s very difficult to take care of them. Expensive. Yeah, it’s expensive, and there just aren’t enough people to take care of the old people. So if you—if they had a robot that could take care of and protect elderly parents, I think that would be a great, amazing thing to have. And I think we will have those things. So overall, I’m very optimistic about the future. I think we’re headed for a future of amazing abundance, which is very cool. And definitely we are in the most interesting time in history. I don’t think there is a more interesting time in history!

Larry Fink: Can we reverse aging in this new history? Or are we going to see it?

Elon Musk: You know, haven’t put much time into the aging stuff, but I do think it is a very solvable problem. Like, you can—I think when we figure out what causes aging, I think we’ll find it’s incredibly obvious, that it’s not a subtle thing. The reason I say it’s not a subtle thing is because all the cells in your body pretty much age at the same rate. You have never seen someone with an old left arm and a young right arm ever in my life. So why… You know, there is some benefit to death, by the way. It’s like, there’s a reason why we don’t actually have a longer lifespan. Because if people do live forever or for a very long time, I think there’s some risk of an ossification of society—of things just getting kind of locked in place. And yeah, it just may become stultifying, a lack of vibrancy. But that’s it. Do I think we’ll figure out ways to extend life and maybe even reverse aging? I think that’s highly likely.

Larry Fink: Looking forward to that. So in the future you talk about—their AI models, autonomous machines, rockets—depends on massive increases of compute, massive increases in energy. Expensive energy, manufacturing scale. What are the bottlenecks to get there? And once again, with all that expenditures, how can we make sure it is broad, not narrow?

Elon Musk: I just think the natural thing will be very broad because AI companies will seek as many customers as they possibly can. And the cost of AI is already low and plummeting every year—almost the cost of AI is meaningfully changing on a month basis.

Larry Fink: There are open models now everywhere.

Elon Musk: Yes. Very good open models. The open models only lack what may be a year behind the closed models. So I think, yeah, AI companies will seek as many customers as possible, which means they’ll provide AI to the world.

Larry Fink: But the cost of getting to their compute chips, the fab, power—powering that. To me, what are those? It is a huge factor.

Elon Musk: I think the limiting factor for AI deployment is fundamentally electrical power.

Larry Fink: It’s energy. Yeah.

Elon Musk: We were seeing the rate of AI chip production increase exponentially, but the rate of electricity being brought online is….

Larry Fink: 5%, 4% a year max.

Elon Musk: Yes, it’s clear very soon—maybe later this year—we will be producing more chips than we can turn on. Except for China. China’s growth in electricity is tremendous.

SOLAR POWER

Larry Fink: They build 100 gigawatts of nuclear as we speak…

Elon Musk: Actually solar is the biggest thing in China. So China’s—I believe Chinese production capacity on solar is 1,500 gigawatts a year, and they’re deploying over 1,000 gigawatts a year of solar. Now, you know, for continuous solar load, you divide that by roughly 4 or 5. Call it around 250 gigawatts of steady-state power paired with batteries.

And that’s a very big number—half the average power usage in the US. US power usage on average is 500 gigawatts. China just in solar—just in solar that can provide steady-state power and batteries can do half of the US electricity output per year just from solar.

Solar’s by far the bigger source of energy. And actually when you look beyond Earth—or even on Earth, but certainly beyond Earth—the sun rounds up to 100% of all energy. This is an important thing to consider. So the sun is 99.8% of the mass of the solar system. Jupiter is about 0.1%, and everything else is miscellaneous. Now even if you were to burn Jupiter in a thermonuclear reactor, this up the amount of energy produced by the sun would still round to 100%, because Jupiter is only 0.1%. If you teleported three more Jupiters into our solar system and burnt three more Jupiters and everything else in the solar system, the sun’s energy would still round up to 100%. So it is really all about the sun. And that is why one of the things we are doing with SpaceX within a few years is launching solar-powered AI satellites. Because space is really the source of immense power. Then you don’t need to take any room on Earth. There is so much room in space and can scale to hundreds of terawatts a year.

Larry Fink: Elon and I have had these conversations before, but why don’t you tell the audience what would it take for the United States in what geography would it take that solar field electrify the United States? Let me ask a question: why aren’t we doing it?

Elon Musk: So rough way is 100 miles by 100 miles—160 kilometers by 160 kilometers—on solar is enough to power the entire United States. So 100-mile by 100-mile area. You can take a small corner of Utah, Nevada, New Mexico—obviously wouldn’t want it all in one place—but there was very small percentage of area of US to generate all electricity that US uses. And same is true actually for Europe. You could take a small part of your energy—take relatively unpopulated areas of say Spain and Sicily, and generate all electricity power that Europe needs.

Larry Fink: Why don’t you think there is a movement towards it here in the United States? As there is in China?

Elon Musk: Well, unfortunately, US tariff barriers for solar are extremely high and this makes economics deploying solar artificially high. Because China makes almost all the solar.

Larry Fink: And what would it take for Europe or US to build it commercially if it is at scale?

Elon Musk: Yeah, I think—well, I can tell you what we are going to do at SpaceX and Tesla. We’re building up large-scale solar. So the SpaceX and Tesla teams both separately are working to build to 100 gigawatts a year of solar power in the US (of manufactured solar power). That will probably take us about three years. But these are pretty big numbers. And I encourage others to do the same. We obviously don’t control US tariff policy. But China makes solar cells that are incredibly low cost. And I think it would be worth doing large-scale solar.

HUMANOID ROBOT

Larry Fink: So I know you’re going to be having a couple of big announcements on robotics and what it can do. I mean, when we went to the factory, you showed me those robots. We talked about billions of robots, but how quickly can they be deployed in your manufacturing setting, be utilized and be functional, and create that abundance you talked about?

Elon Musk: Well, humanoid robotics will advance very quickly. We do have some of the Tesla Optimus robots doing simple tasks in the factory. Probably later this year—by the end of this year—I think they will be doing more complex tasks, but still deployed in an industrial environment. And probably sometime next year—I would say that by the end of next year—I think we will be selling humanoid robots to the public.

Larry Fink: Like you’re already seeing in Tesla cars, software changes every quarter now. A software change upgrades the ability of the robot within the car.

Elon Musk: Yes, the Tesla full self-driving software—we update sometimes once a week. So I think some of the insurance companies have said that it is actually so safe when Tesla uses full self-driving—so safe that they’re offering customers half-price insurance if they use Tesla full self-driving in their car.

Larry Fink: And that can be monitored by the insurance company because it’s part of the agreement?

Elon Musk: Yeah, but I think self-driving cars is essentially a solved problem at this point. Tesla has rolled out Robotaxi service in a few cities, and it will be very widespread by the end of this year within US. Then we hope to get supervised full self-driving approval in Europe hopefully next month.

Larry Fink: Really that quickly!?

Elon Musk: Yeah. And then maybe similar timing for China hopefully.

SPACE

Larry Fink: I want to move to space because historically space is very capital intensive. Historically been done by governments. Obviously SpaceX changed the whole model. But we have seen it slow to scale. And now I am starting to see ramping up in what you are doing. Talk about the automation—how is it changing economics in building and preparing for operating in space?

Elon Musk: Sure. Well, the key breakthrough that SpaceX hopes to achieve this year: full reusability. No one has ever achieved full reusability of a rocket, which is very important for the cost of access to space. We have achieved partial reusability with Falcon 9 by landing the boost stage over 500 times. But we have to throw away the upper stage that burns up on reentry. And the cost of it is equivalent to a small- to medium-size jet.

So with Starship—which is a giant rocket, the largest flying machine ever made—that’s the rocket you’re using for the idea of going to Mars, right?

Larry Fink: Yeah.

Elon Musk: Mars and the Moon as well, and for high-volume satellite stuff. So Starship—hopefully this year—we should prove full reusability for Starship, which will be a profound invention. Because the cost of access to space will drop by a factor of 100 when you achieve full reusability. It is the same economic difference that you would expect between, say, a reusable aircraft and a non-reusable aircraft. Like if you have to throw your aircraft away after every flight, there will be expensive flights. But if you only refuel, then it’s the cost of fuel.

So that’s really the fundamental breakthrough that gets the cost of access to space—we think—below the cost of freight on aircraft. So you know, under $100 a pound type thing easily. It makes putting large satellites into space very low, very cheap.

And then when you have solar in space, you get five times more effectiveness—maybe even more than that—than solar on the ground. Because it’s always sunny, no clouds. Yeah, it’s always sunny. So you don’t have a day-night cycle or seasonality or weather. And you get about 30% more power in space because you don’t have atmospheric attenuation of the power. That net effect is solar is five times more—any given solar panel will do five times the energy in space than on the ground.

SOLAR POWERED AI DATA CENTERS IN SPACE

Larry Fink: Is there any capacity in doing that—then taking that power, bringing it back to Earth? Is there any way of doing that? Or are you just taking the power and utilizing it for needs like building AI data centers in space?

Elon Musk: I think the case is a no-brainer for building solar-powered AI data centers in space. Because as mentioned, it’s also very cold in space. If you’re in shadow, then it’s very cold in space—3 degrees Kelvin. So you have solar panels facing the sun, and then a radiator that’s pointed away from the sun so it has no sun incidence. And then it’s just cooling—it’s a very efficient cooling system. Net effect is that the lowest-cost place to put AI will be space. And that will be true within 2 years, maybe 3 at latest.

Larry Fink: Looking 10 or 20 years out, how would you describe success with AI or space technology? And where do you see it? Are you more certain what will happen in the next 3 years, 5, 10?

Elon Musk: I don’t know what’s going to happen in ten years. But the rate at which AI is progressing—we might have AI that is smarter than any human by end of this year, and no later than next year. And probably 2030 or 2031—5 years from now—AI will be smarter than all of humanity collectively.

Larry Fink: We only have a number of minutes left, but I want to humanize you for a second. So there’s no speculation that you’re the most successful entrepreneur, industrialist in the 21st century—maybe beyond. What inspired you? Who inspired you? What was the foundation of your curiosity? And importantly, why? Was there an aha moment, epiphany at any time in your life and career?

Elon Musk: Well, I mean, as a kid I read a lot of science fiction, sci-fi, fantasy books, comic books. And always liked technology. Didn’t expect to be where I am today—seems incredibly implausible. But yeah, I was inspired by reading books about the future of science fiction. And I guess I want to make science fiction not fiction forever. At some point, turn science fiction into fact. And you know, we wanna have like Starfleet as in Star Trek really for real—where we actually have giant spaceships traveling through space, going to other planets, traveling to other star systems.

Larry Fink: Beamed up to go back to New York? I would like beaming back to New York instead of flying.

CURIOSITY ABOUT THE UNIVERSE

Elon Musk: Yeah. You know about Star Trek. So I guess my essential—what we call the philosophy of curiosity. And I would like to understand the meaning of life. Is the standard model of physics correct regarding the beginning of existence at the end of the universe? What questions do we not know to ask that we should ask? And AI will help us with these things. So I just try to understand: how did we get here? What’s going on? What is real? Are there aliens? Maybe they are. If you have spaceships traveling to other star systems, we may encounter aliens or find many long-dead alien civilizations. But I just want to know what’s going on—curious about the universe. And that is my philosophy.

Larry Fink: Do you see yourself going to Mars in your lifetime?

Elon Musk: Yes.

Larry Fink: Like, that’s a long commitment, isn’t it? Three years each way?

Elon Musk: Six months. But the planets only align every two years. So yeah. Been asked a few times: do I want to die on Mars? And I’m like, yes—just not on impact.

Larry Fink: That’s a good answer. Anyway, we are out of time. Hopefully everybody enjoyed this. And there are so many myths around Elon Musk. I can tell you he is a great friend, and I constantly learn so much from him. And I’m totally inspired by what he has done, I’ve been inspired by who he is, and I’m totally inspired by his vision of the future. And I don’t think it’s such a bad future.

Elon Musk: And I think generally my last words would be: I encourage everyone to be optimistic and excited about the future. Good. And generally, for quality of life, it is better being an optimist rather than a pessimist, right?

(End of video – applause and wrap-up.)

This verbatim transcript is important and inspiring for everybody. Because it is so wide-ranging on technology, energy, AI, space, and optimism, it can lift you up if you’re ever feeling down.

When I bought my first Tesla, a Model 3 in 2019, I joined a community of many people who love Elon Musk and Tesla. Every time I drive my Tesla around my hometown, Austin, Texas, or take a Robotaxi here, I’m reminded of the extraordinary effort that is put into making Tesla succeed. Elon puts maximum effort into all his companies.

In January 2022, I started this blog to write positive things about Tesla and Elon Musk. It has since grown to include many transcripts of Elon's talks. I’m thankful to Johnna Crider for supporting and encouraging me to start this blog.

Elon discusses SpaceX potentially becoming a hyperscaler for orbital AI, the realities of raising massive capital, and the long-term physics required to scale significantly up the Kardashev scale.

Elon Musk with Dwarkesh Patel & John Collison – The Future of AI is in Space – Part 7: SpaceX as Hyperscaler, Capital Markets, and the Kardashev Scale (Full Transcript)

In Part 7, the conversation turns to whether SpaceX could evolve into a hyperscaler — building and operating vast orbital AI infrastructure and potentially providing compute power to others. John Collison and Dwarkesh Patel explore the capital requirements, the possibility of going public, and the deeper physics of long-term energy scaling. Elon shares his thoughts on speed as the ultimate constraint and what it would actually take to move significantly up the Kardashev scale.

Transcript:

Dwarkesh Patel asked whether the long-term vision was for SpaceX to become a hyperscaler — launching and operating vast orbital AI capacity and then providing (or lending) that compute power to other companies.

Elon Musk: “Hyper. Hyper, yeah. I mean, if some of my predictions come true, SpaceX will launch more AI than the cumulative amount on Earth of everything else combined.”

Dwarkesh followed up on whether this capacity would mostly be used for inference or training.

Elon Musk: “Will be inference already? Inference for the purpose of training is most training.”

John Collison then explored the business implications, noting the shifting narrative around a possible SpaceX IPO. He pointed out that SpaceX had long been extremely capital efficient, but the scale of building orbital AI infrastructure would require capital raises far beyond what private markets had demonstrated they could comfortably provide — even as AI labs were already raising tens of billions. He asked if going public was the logical next step and more broadly about the difference in capital availability between public and private markets, as well as whether debt financing could suffice.

Elon Musk: “Yeah, I have to be careful about saying things about companies that might go public.”

Elon Musk: “There’s a price to pay for these things.”

Elon Musk: “Yeah, there’s a lot more capital in the very general. There’s obviously a lot more capital available in the public markets than private. I mean, it might be, it’s at least, at least, it might be 100 times more capital, but it’s at least way more than 10.”

John Collison noted that highly capital-intensive sectors like real estate are typically debt-financed once they have predictable near-term revenue.

Elon Musk: “A clear revenue stream.”

John Collison agreed.

Elon Musk: “Speed is important. So I’m generally going to do the thing that, I mean, I just repeatedly tackle the limiting factor, whatever the limiting factor is on speed, I’m going to tackle that. So there’s, if capital is the only factor, then I’ll solve for capital. If it’s not limiting factor, I’ll solve for something else.”

Dwarkesh Patel observed that, based on Elon’s past comments about Tesla being public, he would not have expected Elon to see going public as the way to move fastest.

Elon Musk: “Normally I would say yeah, that’s true. Like I said, I mean, I’d love to talk about this in more detail, but the problem is like if you talk about public companies where they become public, you get into trouble and then you have to delay your offering and then you.”

John Collison noted that this was again about speed.

Elon Musk: “Yes, exactly. So you can’t hype companies that might go public. So that’s why we have to be a little careful here.”

Elon then pivoted to the fundamental long-term physics of scaling.

Elon Musk: “But we can talk about physics. So the way you think about scaling long term is that Earth only receives about half a billionth of the sun’s energy. And the sun is essentially all the energy. And this is a very important point to appreciate because sometimes people will talk about marginal nuclear reactors or any various fusion on Earth, but you have to step back a second and say if you’re going to climb the Kardashev scale and have some non trivial and harness some non trivial percentage of the sun’s energy, like let’s say you wanted to harness a millionth or a millionth of the sun’s energy, which sounds pretty small, that would be about, call it roughly 100,000 times more electricity than we currently generate on Earth for all of civilization, give or take an order of magnitude. So it obviously the only way to scale is to go to space. With solar, from launching from Earth you can get to about a terawatt per year. Beyond that you want to launch from the moon, you want to have a mass driver on the moon, and that mass driver on the moon you could do probably a petawatt per year.”

Elon discusses SpaceX potentially becoming a hyperscaler for orbital AI, the realities of raising massive capital, and the long-term physics required to scale significantly up the Kardashev scale. In Part 8, the conversation continues with more on the engineering and strategic path forward.

Elon predicts that within five years, more AI will be operating in space than currently exists on Earth, and discusses the Starship fleet size and launch cadence needed to support it.

Elon Musk with Dwarkesh Patel & John Collison – The Future of AI is in Space – Part 6: AI Capacity in Five Years and Starship Launch Rates (Full Transcript)

In Part 6, John Collison asks Elon to project what AI compute capacity might look like in five years — both on Earth and in space. The conversation shifts to the enormous number of Starship launches that would be needed to support large-scale orbital AI infrastructure. Elon shares his prediction that AI in space will surpass all terrestrial AI within five years and discusses the practical realities of achieving very high launch rates.

Elon Musk: “My prediction is that we will launch and be operating more AI in space every year than the cumulative total on Earth, which I would expect to take at least five years to reach. So we’re talking about a few hundred gigawatts per year of AI in space, and rising.”

Transcript:

John Collison shifted the conversation to a concrete five-year horizon. He asked what installed AI compute capacity would look like on Earth versus in space by then.

Elon Musk: Five years? I think probably if you say five years from now, we’re probably going to be launching every year in space the sum total of all AI on Earth, and then some. My prediction is we will launch and be operating every year more AI in space than the cumulative total on Earth, which I would expect to be at least sort of five years from now. A few hundred gigawatts per year of AI in space and rising. So you can get to, I think on Earth you can get to around a terawatt a year of AI in space before you start having fuel supply challenges for the rocket.

John Collison pressed for confirmation on the hundreds-of-gigawatts-per-year figure.

Elon Musk: “Yes.”

Dwarkesh Patel highlighted the launch cadence implied by those numbers.

Elon Musk: “Yes.”

Dwarkesh Patel continued, noting that delivering 100 gigawatts in a single year would require roughly 10,000 Starship launches annually — the equivalent of one launch every single hour, nonstop, from this city.

Elon Musk: “Yeah, I mean that’s actually a lower rate compared to airlines like aircraft.”

Dwarkesh Patel pointed out that there are a lot of airports around the world.

Elon Musk: “A lot of airports.”

Dwarkesh Patel noted the additional complexity of launching into polar or sun-synchronous orbits.

Elon Musk: “No, it doesn’t have to be polar, but there’s some value to sun synchronous. But I think actually you just go high enough, you start getting out of Earth’s shadow.”

Dwarkesh Patel asked how many physical Starships would be needed to sustain 10,000 launches per year.

Elon Musk: “I don’t think we’ll need more than. I mean, you could probably do it with as few as like 20 or 30. It really depends on how quickly the ship has to go around the Earth and the ground track before the ship has to come back over the launch pad. So if you can use a ship every, say 30 hours, you could do it with 30 ships, but we’ll make more ships than that. But SpaceX is gearing up to 10,000 launches a year and maybe even 20 or 30,000 launches a year.”

Elon predicts that within five years, more AI will be operating in space than currently exists on Earth, and discusses the Starship fleet size and launch cadence needed to support it. In Part 7, the conversation continues with more on the technical and operational realities of building large-scale AI infrastructure in orbit.

Elon Musk explains why SpaceX and Tesla may have to start manufacturing turbine components themselves and shares their aggressive plans to scale solar production.

Elon Musk with Dwarkesh Patel & John Collison – The Future of AI is in Space – Part 5: Turbine Shortages, Casting Bottlenecks & Scaling Solar Production (Full Transcript)

In Part 5, Dwarkesh Patel raises the question of whether the engineering challenges of building large-scale AI infrastructure might actually be easier in space than on Earth. The conversation then turns to the very real bottlenecks on the ground. Particularly the massive shortage of turbines and specialized casting capacity. Elon Musk explains why SpaceX and Tesla may have to start manufacturing turbine components themselves and shares their aggressive plans to scale solar production.

Transcript:

Dwarkesh Patel asked a central question: while Earth-based power challenges are already enormous, wouldn’t building in space introduce entirely new and unprecedented engineering difficulties — such as radiation hardening, orbital lasers, and other issues that haven’t been solved before? He wondered why anyone would choose these novel challenges over simply building more turbines on Earth, where established companies already know how to manufacture them.

Elon Musk: “I invite again, try doing it and then you’ll see. So like, the turbines are sold out through 2030.”

John Collison asked whether they had considered manufacturing their own turbines.

Elon Musk: “I think in order to bring enough power online, I think SpaceX and Tesla will probably have to make the turbine blades, the vanes and blades internally.”

John Collison asked if Elon meant just the blades or the entire turbines.

Elon Musk: “The limiting factor, you can get everything except the blades. They call the blades and vanes. You can get that 12 to 18 months before the vanes and blades. The limiting factor of the vanes and blades, and there are only three casting companies in the world that make these and they’re massively backlogged, it is Siemens.”

John Collison asked whether it was GE and the big names or subcontractors.

Elon Musk: “No, it’s other companies. I mean sometimes they have a little bit of casting capability in house. But I’m just saying you can just call any of the turbine makers and they will tell you it’s not top secret. They’re probably on the, it’s probably on the internet right now.”

Dwarkesh Patel asked whether, if it weren’t for the tariffs, Colossus would be running on solar power.

Elon Musk: “It would be much easier to make it solar powered. Yeah, the tariffs are nuts, so several hundred percent.”

John Collison began to suggest that Elon surely knew some people who could help.

Elon Musk: “We also need speed. Yeah, no, you know, President has his, you know, we don’t agree on everything and this demonstration is not the biggest fan of solar. We also need the land, the permits and everything. So if you’re trying to move very fast, I do think scaling solar on Earth is a good way to go. But you do need some amount of time to find the land, get the permits, get the solar, pair that with batteries.”

John Collison pressed further, asking why not simply stand up their own massive solar production, noting there is plenty of private land in Texas and Nevada.

Elon Musk: “As I said, we are scaling solar production. There’s a rate at which you can scale physical production of solar cells where we’re going as fast as possible.”

John Collison confirmed they were building the solar cells domestically at Tesla.

Elon Musk: “Both Tesla and SpaceX have a mandate to get to 100 gigawatts a year of solar.”

Elon explains the severe turbine and specialized casting bottlenecks and why SpaceX and Tesla are aggressively scaling their own solar production to 100 gigawatts per year. In Part 6, the conversation continues with more on the engineering and infrastructure challenges of building AI at planetary scale.

Elon Musk: “We are going to make solar. Okay, great. Both SpaceX and Tesla are building towards 100 gigawatts here of solar cell production.”

Elon Musk with Dwarkesh Patel & John Collison – The Future of AI is in Space – Part 4: Turbine Bottleneck & Space Solar (Full Transcript)

In Part 4, John Collison asks whether Elon would try to solve the turbine shortage himself or go straight to manufacturing solar at enormous scale. Elon reveals that SpaceX and Tesla are already moving toward 100 gigawatts of solar cell production and explains why solar cells destined for space are dramatically cheaper and easier to produce than those on Earth. He also gives a detailed breakdown of why most people severely underestimate how much power a real AI data center actually requires.

Transcript:

John Collison suggested that the turbine blade bottleneck sounded like the kind of problem Elon would want to attack directly, and proposed that making solar themselves might be the smarter long-term path.

Elon Musk: “We are going to make solar. Okay, great. Both SpaceX and Tesla are building towards 100 gigawatts here of solar cell production.”

Dwarkesh Patel asked how deep into the supply chain they planned to go — from raw polysilicon all the way to finished solar panels.

Elon Musk: “I think you got to do the whole thing from raw materials to the finished cell. Now, if it’s going to space, it actually costs less. And it’s easier to make solar cells that go to space because they don’t need glass or they don’t need much glass and they don’t need heavy framing because they don’t have to survive weather events. There’s no weather in space. So it’s actually a cheaper solar cell that goes to space than the one on the ground.”

Elon emphasized that solar is already extremely cheap on Earth, but moving it to space changes the economics dramatically.

Elon Musk: “Solar cells are already very cheap. They’re like farcically cheap. And if you say, I think solar cells in China are around like 25, 30 cents a watt or something like that, it’s absurdly cheap. And when you take into account now put it in space and it’s five times cheaper because it’s five times — in fact, no, it’s 10 times cheaper because you don’t need any batteries. So the moment your cost of access to space becomes low, by far the cheapest and most scalable way to generate tokens is space. It’s not even close. It’ll be an order of magnitude easier to scale.”

He then shared the real-world difficulties his team faced just getting one gigawatt of power online for the Colossus supercluster.

Elon Musk: “And chips aside, an order of magnitude. The point is you won’t be able to scale on the ground. You just won’t. People are going to hit the wall big time on power generation. There already are. So the number of miracles in series that the xAI team had to accomplish in order to get a gigawatt of power online was crazy. We had to gang together a whole bunch of turbines. And then we had permit issues in Tennessee and had to go across the border to Mississippi, which is fortunately only a few miles away. But then we still had to run the high power lines a few miles and build a power plant in Mississippi. And it was very difficult to build that.”

Elon then explained why most people dramatically underestimate how much electricity is actually needed at the generation level to run a real AI data center.

Elon Musk: “And people don’t understand how much electricity do you actually need at the generator level, at the generation level in order to power a data center? Because they look at the specs, will look at the power consumption of say a GB 300 and multiply that by the number and then think that’s the amount of power you need.”

John Collison noted that even those calculations miss major additional loads like cooling and supporting systems.

Elon Musk: “Wake up. Yeah, that’s a total noob. You’ve never done any hardware in your life before. Besides the GB 300, you’ve got to power all of the networking hardware. There’s a whole bunch of CPU and storage stuff that’s happening. You’ve got to size for your peak cooling requirements. So that means can you cool even on the worst hours, the worst day of the year? Well, it gets pretty freaking hot in Memphis, so you’re going to have like a 40% increase on your power just for cooling.”

He continued breaking down the additional multipliers that are almost always overlooked.

Elon Musk: “Assuming you don’t want your data center to turn off on hot days and you want it to keep going, then you’ve got to say, well, there’s another multiplicative element on top of that, which is are you assuming that you never have any hiccups in your power generation? Like, oh, well, actually sometimes we have to take the generators, some of the power offline in order to service it. Oh, okay, now you add another 20, 25% multiplier on that because you’ve got to assume that you’ve got to take power offline to service it. So the actual — roughly every 110,000 GB 300s inclusive of networking, CPU, storage, cooling, margin for servicing power is roughly 300 megawatts.”

John Collison asked him to repeat the number for clarity.

Elon Musk: “It’s roughly — or think about it like a way to think about it is like 330,000. What you need at the generation level to service, probably service 330,000 GB 300s, including all of the associated support, networking and everything else, and the peak cooling and to have some power margin reserve is roughly a gigawatt.”

Elon breaks down why naive power calculations for AI data centers fall far short of reality and why space-based solar could be the only way to scale at the required speed. I

n Part 5, the conversation continues with more on the challenges and opportunities of building at this scale.

Elon Musk on The Massive Scale of Power Requirements and Utility Bottlenecks

Elon Musk with Dwarkesh Patel & John Collison – The Future of AI is in Space – Part 3: The Massive Scale of Power Requirements and Utility Bottlenecks (Full Transcript)

In Part 3, the conversation turns to the enormous scale of power required to run advanced AI at the level Elon envisions. Dwarkesh Patel and John Collison press Elon on the real-world challenges of building terawatts of electricity generation and why the utility industry is such a major bottleneck. Elon explains why private power plants co-located with data centers may be the only practical solution.

Transcript:

Dwarkesh Patel sought clarification on the scale Elon was describing, confirming that he was talking about terawatts of power. The discussion then moved to the extreme difficulty of actually building that much electricity generation at the speed AI development requires.

Elon Musk: “Yeah, well, all of the United States currently uses only half a terawatt per hour on average. Right. So if you say a terawatt, that would be twice as much electricity as the United States currently consumes. So that’s quite a lot. And can you imagine building that many data centers, that many power plants? It’s like those who have lived in software land don’t realize that they’re about to have a hard lesson in hardware, that it’s actually very difficult to build power plants. And then you don’t just need the power plants, you need all of the electrical equipment, you need the electrical transformers to run the transformers, the AI transformers.”

Elon pointed out that the utility industry moves extremely slowly because it is heavily regulated and “impedance matched to the government.”

Elon Musk: “Now, the utility industry is a very slow industry. They impedance match to the government, to the public utility commission. So they’re very slow because their past has been very slow. So trying to get them to move fast is just like, you know, if you’re trying to do an interconnect agreement… have you ever tried to do an interconnect agreement with a utility at scale? Like with a lot of power?”

Dwarkesh Patel laughed and admitted that, as a podcaster, he had never tried to do an interconnect agreement with a utility.

“Now, the utility industry is a very slow industry. They impedance match to the government, to the public utility commission. So they’re very slow because their past has been very slow. So trying to get them to move fast is just like, you know, if you’re trying to do an interconnect agreement… have you ever tried to do an interconnect agreement with a utility at scale? Like with a lot of power?” – Elon Musk

Elon Musk: “In fact, yeah, they have to do a study for a year. Okay. Like a year later they’ll come back to you with their interconnect study.”

John Collison asked whether companies could simply bypass the utility bottleneck by building their own private power plants right next to the data centers.

Elon Musk: “You can build power plants. Yeah, that’s what we did at xAI for Colossus.”

John Collison followed up, asking why this private-power approach wasn’t being treated as the obvious solution to the utility problems they had been discussing.

Elon Musk: “Right. But it begs the question of where do you get the power plants? Where do you get the power plants from? I mean the power plant makers.”

John Collison summed up the deeper issue: there is currently a massive backlog for gas turbines and power plant equipment in general.

Elon highlights that even if companies build their own power plants, they still face major constraints in actually obtaining the equipment. In Part 4, the discussion continues with more on the practical challenges of scaling AI infrastructure at this level.

Elon makes a bold prediction that space will become the cheapest place to run AI within three years.

Elon Musk with Dwarkesh Patel & John Collison – The Future of AI is in Space – Part 2: Why Space Is the Optimal Place for AI (Full Transcript)

In Part 2, Dwarkesh Patel and John Collison explore whether space could actually be better than Earth for running massive AI infrastructure. They raise practical concerns around regulation, servicing failing GPUs, and power generation. Elon Musk has a strong case for orbital compute, highlighting the dramatic advantages of space-based solar power.

Transcript:

Dwarkesh Patel suggested that space might mostly be a regulatory advantage, since it’s harder to build big infrastructure on land than in space. He also asked how you would service GPUs when they fail — which happens quite often during large training runs.

John Collison added questions about solving the power problem, specifically whether private behind-the-meter generation co-located with data centers could work.

Elon Musk: “It’s harder to scale on ground than it is to scale in space. But also, you’re going to get about five times the effectiveness of solar panels in space versus the ground.

And you don’t need batteries. I almost wore my other shirt, which says ‘it’s always sunny in space,’ which it is. Because you don’t have a day-night cycle or seasonality, clouds, or an atmosphere in space.

The atmosphere alone results in about a 30% loss of energy. So any given solar panel can do about five times more power in space than on the ground, and you avoid the cost of having batteries to carry you through the night.

So it’s actually much cheaper to do in space. And my prediction is that it will be by far the cheapest place to put AI will be space in 36 months or less.”

Elon makes a bold prediction that space will become the cheapest place to run AI within three years. In Part 3, the conversation continues with more details on the technical and economic realities of moving AI infrastructure off Earth.

And my prediction is that it will be by far the cheapest place to put AI will be space in 36 months or less. – Elon Musk

Picture of Elon Musk as he jokingly questioned whether they were really going to talk for three full hours. Dwarkesh Patel teased him in return, saying he didn’t have much to talk about. Elon reacted with mock surprise.

Elon Musk on Why the Future of AI Will Be in Space with Dwarkesh Patel & John Collison – Part 1 (Full Transcript)

Part 1: Opening Banter and the Economics of Space-Based Data Centers

The interview opened with some light-hearted and playful banter. Elon Musk jokingly questioned whether they were really going to talk for three full hours. Dwarkesh Patel teased him in return, saying he didn’t have much to talk about. Elon reacted with mock surprise.

Elon Musk: “So are there really three hours of questions or are you fing serious?” Elon Musk: “Holy f, man.”

John Collison jumped in, agreeing that it was actually the most interesting time because all the major storylines seemed to be converging at once. Elon playfully replied that it was almost as if he had planned it that way.

Elon Musk: “Almost like I planned it.”

John Collison laughed and said “Exactly.”

Elon Musk: “That would never do such a thing.”

With the lighthearted tone set, Dwarkesh Patel steered the discussion into the first major topic: the economics of data centers and why anyone would consider moving them into space. He explained that in a typical data center, energy accounts for only 10 to 15 percent of total cost of ownership, with GPUs representing the vast majority of the expense. He pointed out that placing those GPUs in space would make servicing nearly impossible, shortening their depreciation cycle and driving costs far higher, then asked directly what possible reason there could be to put them in orbit anyway.

Elon Musk: “Well, the availability of energy is the issue. So, I mean, if you look at electrical output outside of China, everywhere outside of China, it’s more or less flat. It’s very, you know, maybe a slight increase, but pretty close to flat. China has a rapid increase in electrical output. But if you’re putting data centers anywhere except China, where are you going to get your electricity? Especially as you scale, the output of chips is growing pretty much exponentially, but the output of electricity is flat. So how are you going to turn the chips on? Magical power sources. Magical electricity fairies.”

Dwarkesh Patel followed up by noting Elon’s well-known advocacy for solar power, calculating that one terawatt of solar (requiring about 4 terawatts of panels at 25 percent capacity factor) would cover only 1 percent of U.S. land area, yet even that seemed insufficient once data centers themselves reached terawatt scale. He asked what exactly we are running out of. Elon pressed him on how far into the singularity he thought we already were, and Dwarkesh turned the question back. Dwarkesh then asked whether the plan was to move to space only after blanketing places like Nevada with solar panels on the ground.

Elon Musk: “Right.”

Elon Musk: “Yeah, exactly. So I think we’ll find we’re in the singularity and like, okay, we’ve still got a long way to go.”

Elon Musk: “I think it’s pretty hard to cover Nevada in solar panels. You have to get permits from, try getting the permits for that.”

Read on part Parts 2-10.

Elon Musk Moonshots Interview with Peter Diamandis & Dave Blundin – Part 4: Games, Compute & Reality (Full Transcript)

In Part 3, Elon revealed how xAI is forcing a gigawatt-scale breakthrough in AI training power. Now Peter’s son Jet (age 14) inspires the next turn: gaming and AI’s role in it.

Peter D.: 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?

Elon’s origin story surfaces.

Elon: Yeah, that’s why I started programming computers… Civ was actually a very— in terms of games that educate you while you have fun, Civ is epic at that.

Dave jumps in.

Dave B.: The only way I ever win is getting off the planet… Tech victory to Alpha Centauri.

Elon: I guess I am sort of aiming for the Alpha Centauri tech victory essentially.

The analogy is perfect: civilization’s true win condition isn’t domination — it’s escape velocity.

Elon: Aspirationally [building an AI gaming studio].

Because:

Elon: The vast majority of AI compute is going to go to video consumption and generation… Real-time video generation. That’s going to be the vast majority of AI compute. Photon processing.

Peter floats an X Prize for Universal High Income governance. Elon is open but skeptical on measurement.

Then the conversation ascends to simulation theory.

Elon: The most interesting outcome is the most likely… Only the simulations that are the most interesting will survive. Because when we run simulations, we truncate the ones that are boring.

Terrible things can still happen — they keep it engaging. Like watching a war movie while eating popcorn.

Dave B.: So the guys running the simulation have immensely boring lives compared to us.

Elon: Yeah, because when we create simulations, they’re a distillation of what’s interesting.

Are we in Act 3? The room leaves it open.

This segment closes on the biggest frame possible: Reality as a game where the win condition is expansion, energy mastery, and keeping it interesting.

My two cents: Think about what you can remember from your past. You’re probably like me and mostly recall just the spicy parts of your life. So what were you doing on March 3, 2023? Good question—and a troubling one.

Our minds are made of a string of memorable events. For myself, I sought to create the most vivid memories possible when I was young. Soon, I’ll be publishing a book for you that will include some very vivid experiences I had living in Italy when I was 21–22 years old.

I encourage you to create your most important memories when you’re younger—and then you’ll carry those memories with you for your entire beautiful life. But you’re never too old to create memories!