Category: Elon Musk Talk

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 12: Elon’s Management and Hiring Philosophy (Full Transcript)

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In Part 12, Dwarkesh Patel and John Collison dive into Elon Musk’s management and hiring philosophy. They discuss how he evaluates talent, why companies outgrow people as they scale, and what makes someone effective at Tesla and SpaceX.

Transcript:

Evaluating Technical Talent

John Collison asked about Elon’s system for evaluating and hiring people, noting that he personally interviewed the first few thousand employees at SpaceX.

Elon Musk: “Me. Literally there’s not enough hours in the day, it’s impossible.”

John Collison asked what Elon looks for in candidates.

Elon Musk: “Well, at this point I think I’ve got, I might have more training data on evaluating technical talent especially, but talent of all kinds, I suppose, but technical talent especially given that I’ve done so many technical interviews and then seen the results. Technical interviews, seen the results. So my training set is enormous and has a very wide range.

Generally the thing I ask for are bullet points for evidence of exceptional ability. These things can be pretty off the wall. It doesn’t need to be in the domain, the specific domain, but evidence of exceptional ability. So if somebody can cite even one thing, but let’s say three things where you go wow, wow, wow, then that’s a good sign.”

Dwarkesh Patel asked why Elon himself had to be the one making those judgments.

Elon Musk: “No, I don’t. I can’t be. It’s impossible. Right? I mean, total headcount across all companies, 200,000 people. Right.”

John Collison asked what made early hiring so hard to delegate.

Elon Musk: “Well, I guess I need to build my training set. It’s not like I’ve bat a thousand here. I would make mistakes, but then I’d be able to see where I thought somebody would work out well, but they didn’t. And then why did they not work out well? And what can I do to, I guess reload myself to in the future have a better batting average when interviewing people? So my batting average is still not perfect, but it’s very high.”

Dwarkesh Patel asked what some surprising reasons were for people not working out.

Elon Musk: “Surprising reasons like they don’t understand technical.”

Dwarkesh pushed for more detail on the long tail of hiring mistakes.

Elon Musk: “Yeah, so the, I mean generally what I tell people, I tell myself, I guess aspirationally is don’t look at the Resume just believe, believe your interaction. So the resume may seem very impressive and it’s like, wow, resume looks good. But if the conversation after 20 minutes, that conversation is not. Well, you should believe the conversation, not the paper.”

Executive Retention and Company Growth

John Collison noted that Tesla and SpaceX have had relatively stable and internally promoted executive teams despite rapid growth, and asked what the long-tenured technical leaders have in common.

Elon Musk: “Well, so the, I mean it tells us sort of senior team at this point probably has an average tenure of 10 or 12 years. It’s quite, quite long. Yeah. So, but there are times when Tesla went through extremely rapid and extremely rapid growth phase and so things were just somewhat sped up.

And when a company, as you know, company goes through different orders of magnitude of size, people who could help manage say a 50 person company versus a 500 person company versus a 5,000 person company versus a 50,000 person. It’s just not the same team. It’s not always the same team. So if a company is growing very rapidly, the rate at which executive positions will change will also be proportionate to the rapidity of the growth generally.”

John Collison asked about the challenge of retaining talent when companies become successful and get heavily recruited.

Elon Musk: “Then Tesla had a further challenge where when Tesla had very successful periods, we would be relentlessly recruited from relentlessly. When Apple had their electric car program, they were carpet bombing Tesla with recruiting calls. Engineers just unplugged their phones.

If I get one more call from Apple recruiter, but they’re opening offer without any interview with me, like double the compensation at Tesla. So we had a bit of the Tesla pixie dust thing where it’s like, oh, if you hired a Tesla executive suddenly you’re going to.. everything’s going to be successful. And I’ve fallen prey to the pixie dust thing as well where it’s like, oh, we’ll hire someone from Google or Apple and they’ll be immediately successful. But that’s not how it works. People are people. There’s not like magical pixie dust.

So when we have the pixie dust problem we would get relentlessly recruited and, and then also Tesla being engineering especially being primarily in Silicon Valley, it’s easier for people to just like they don’t have to change their life very much. They can just their commute is going to be the same.”

John Collison asked how to prevent the “pixie dust” effect of other companies poaching talent.

Elon Musk: “I don’t think there’s much we can do to stop it. But that’s like, that’s one of the reasons why Tesla, but really being in Silicon Valley and having the pixie dust thing at the same time meant that there was just a very, very aggressive recruitment.”

John Collison noted that moving to Austin likely helped.

Elon Musk: “Austin. Yeah, it still helps. I mean Tesla still has a majority of it’s engineering in California, so getting engineers to move, I call it the significant other problem. Yes. And others have jobs.

Yeah, yeah, exactly. So for Starbase that was particularly difficult since the odds of finding a non SpaceX job Brownsville, Texas are pretty low. Yeah, it’s quite difficult. I mean it’s like a technology monastery thing, you know, remote and mostly dudes. An improvement over SF.”

Management Philosophy and Hiring

John Collison asked what the long-tenured technical executives at Tesla and SpaceX have in common and what makes a good “sparring partner” for Elon.

Elon Musk: “I don’t think it was a sparring partner. I mean, if somebody gets things done, I love them. And if they don’t, I… So it’s pretty straightforward. It’s not like some idiosyncratic thing. If somebody executes well, I’m a huge fan. And if they don’t, I’m not. But it’s not about mapping to my idiosyncratic preferences, or certainly try not to have it be mapping to my idiosyncratic preferences.

Yeah, but generally I think it’s a good idea to hire for talent and drive and trustworthiness. And I think goodness of heart is important. I weighted that at one point. So are they a good person, trustworthy, smart and talented and hardworking? If so, you can add domain knowledge. But those fundamental traits, those fundamental properties you cannot change. So most of the people who are at Tesla and SpaceX did not come from the aerospace industry or the auto industry.”

Elon Musk shares his philosophy on hiring, evaluating talent, and why companies must evolve their leadership as they grow. In Part 13, the conversation continues with the famous decision to switch Starship from carbon fiber to stainless steel and how he drives urgency at 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 11: Scaling Optimus Production and Competing with China (Full Transcript)

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In Part 11, Dwarkesh Patel and John Collison explore the synergies between xAI and Optimus, the difficulties of scaling humanoid robot production at volume, and whether America can realistically compete with China’s manufacturing power through robotics.

Transcript:

Synergies Between xAI and Optimus

Dwarkesh Patel asked how Elon thinks about the synergies between xAI and Optimus, especially since Grok could potentially act as a world model and higher-level intelligence for planning while lower-level motor policies handle execution.

Elon Musk: “Yeah, so you’d use GROK to orchestrate the behavior of the Optimus robots. So let’s say you wanted to build a factory, then Grok could organize the Optimus robots, give them, assign them tasks to build the factory, to produce whatever you want.”

John Collison asked whether this meant xAI and Tesla would eventually need to merge.

Elon Musk: “So what were we saying earlier about public company discussions?”

Scaling Optimus Production

Dwarkesh Patel asked what Elon still wants to see on the hardware side before moving to mass manufacturing of Gen 3 Optimus — better actuators or improved software.

Elon Musk: “No, we’re moving towards that.”

Dwarkesh followed up, asking if Ford-style manufacturing with current hardware was good enough and whether Elon just wanted to deploy as many as possible now.

Elon Musk: “I mean, it’s very hard to scale up production. But yeah, I think Optimus 3 is the right version of the robot to produce maybe something on the order of like a million units a year. I think you’d want to go to Optimus 4 before you went to 10 million units a year.”

John Collison confirmed whether a million units per year was achievable with Optimus 3.

Elon Musk: “Yeah, I mean, it’s very hard to spool up manufacturing. So manufacturing, the output per unit time always follows an S curve. So it starts off agonizingly slow, then has this sort of exponential increase, then linear, then a logarithmic outcome until you sort of eventually asymptote at some number.

Optimus initial production will be—it’s going to be a stretched out S curve because so much of what goes into Optimus is brand new. There’s not an existing supply chain. As I mentioned, the actuators, electronics, everything in the Optimus robot is designed for physics first principles. It’s not taken from a catalog. These are custom designed. Everything, literally everything. I don’t think there’s a single thing that—”

John Collison asked how far down the custom design goes.

Elon Musk: “I mean I guess we’re not making custom capacitors yet maybe, but there’s nothing you can pick out of a catalog at any price. So it just means that the Optimus S curve, the units per year output per unit time, how many Optimus robots you make per day, whatever, is going to initially ramp slower than a product where you have an existing supply chain. But it will get to a million.”

Competing with Chinese Humanoids

Dwarkesh Patel asked about Chinese humanoids like Unitree selling for $6K–$13K. He wondered whether Tesla aimed to match that price or if the Chinese robots were qualitatively different.

Elon Musk: “Well, our Optimus is designed to have a lot of intelligence and to have the same electromechanical dexterity if not higher than a human. So Unitree does not have that. And it’s also, I mean it’s quite a big robot. It has to carry heavy objects for long periods of time and not overheat or exceed the power of its actuators. So we’ve got—it’s 5’11”, this is pretty tall and it’s got a lot of intelligence. So it’s going to be more expensive than a small robot that is not intelligent.”

John Collison noted that Optimus would be more capable.

Elon Musk: “Yeah, not a lot more. I mean the thing is over time as Optimus robots build Optimus robots, the cost will drop very quickly.”

John Collison asked what the first billion Optimuses would do and what their highest and best use would be.

Elon Musk: “I think that you would start off with simple tasks that you can count on them doing well.”

John Collison asked whether that would be in homes or factories.

Elon Musk: “The best useful robots in the beginning will be any continuous operations, any 24/7 operation because then they can work continuously.”

Dwarkesh Patel asked what fraction of work currently done by humans at a Gigafactory a Gen 3 Optimus could handle.

Elon Musk: “I’m not sure. Maybe it’s like 10, 20%, maybe more, I don’t know. We would not reduce our headcount. We would for sure increase our headcount, to be clear, but we would increase our output. So the units produced per human—the total number of humans at Tesla will increase, but the output of robots and cars will increase disproportionately. The number of cars and robots produced per human will increase dramatically, but number of humans will increase as well.”

US-China Manufacturing and Policy

John Collison asked what policy changes Elon would make if he were in charge, referencing solar tariffs and permitting.

Elon Musk: “Yeah, I would say anything that is a limiting factor for electricity needs to be addressed, provided it’s not very bad for the environment.”

John Collison brought up export bans on chips and turbine engines and asked whether more should be considered.

Elon Musk: “Well, I think it’s important to appreciate that in most areas China is very advanced in manufacturing. There’s only a few areas where it is not. China is a manufacturing powerhouse next level.”

John Collison asked about supply chain dependence, specifically gallium refining.

Elon Musk: “Yeah, there’s rare earth stuff. Rare earths, which are, as you know, not rare. We actually do rare earth ore mining in the U.S., send the rock, we put it on a train and then put on a boat to China that goes on another train and goes to the rare earth refineries in China, who then refine it, put it into a magnet, put it into a motor sub assembly, and then send it back to America. So the thing we’re really missing is a lot of ore refining in America.”

John Collison asked whether this was worth policy intervention.

Elon Musk: “Yes, well, I think there are some things being done on that front, but we kind of need Optimus, frankly, to build ore refineries.”

The Robot Advantage

Dwarkesh Patel summarized that China’s main advantage is abundant skilled labor and that Optimus could help close that gap, but noted the concern that China might pull ahead in humanoid production first.

Elon Musk: “Right. You can close that recursive loop pretty quickly.”

John Collison asked if this could be done with a small number of Optimuses.

Elon Musk: “Yeah. So you close the recursive loop to help the robots build the robots, and then we can try to get to tens of millions of units a year. Maybe if you start getting to hundreds of millions of units a year, I think you’re going to be the most competitive country by far.

We definitely can’t win with just humans because China has four times our population. And frankly, America’s been winning for so long that just like a pro sports team that’s been running for a very long time tend to get complacent and entitled and that’s why they stop winning, because they don’t work as hard anymore.

So I think, frankly my observation is the average work ethic in China is higher than in the U.S. So it’s not just that there’s four times the population, but the amount of work that people put in is higher. So you can try to rearrange the humans, but you’re still one quarter of the—assuming that productivity is the same, which I think actually it might not be, I think China might have an advantage on productivity per person. We will do one quarter of the amount of things as China.

So we can’t win on the human front. And our birth rate’s been low for a long time. The US birth rate’s been below replacement since roughly 1971. So we’ve got a lot of people retiring or more people dying than—we’re close to more people domestically dying than being born. So we definitely can’t win on the human front, but we might have a shot at the robot front.”

Elon Musk explains the challenges of scaling Optimus production and how robotics could help America compete with China’s manufacturing dominance.

In Part 12, the conversation continues with Elon’s management and hiring philosophy.

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 with Dwarkesh Patel & John Collison – The Future of AI is in Space – Part 10: Optimus Robots, Digital Human Emulation & Hardware Challenges (Full Transcript)

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In Part 10, John Collison and Dwarkesh Patel shift the conversation toward the practical future of AI products and humanoid robots. They ask Elon about digital human emulation, why he refers to Optimus as the “infinite money glitch,” and the biggest technical hurdles in scaling advanced humanoid robots.

Transcript:

Future of AI Products and Digital Human Emulation

John Collison asked for Elon’s predictions on where AI products are headed in 2026 and 2027. He noted that recent progress across labs has been rapid, with LLMs, reinforcement learning, and deep research modalities all advancing quickly. He observed that the real differences between labs now seem to be more about timing than fundamental capability gaps, and asked what users should expect next.

Elon Musk: “Well, I think I’d be surprised by the end of this year if digital human emulation has not been solved. I guess that’s what we mean by the sort of Macrohard project. Can you do anything that a human with access to a computer could do, like in the limit? That’s the best you can do before you have a physical Optimus. The best you can do is a digital Optimus. So you can move electrons and you can amplify the productivity of humans. But that’s the most you can do until you have physical robots that will superset everything — if you can fully emulate humans.”

Optimus as the Infinite Money Glitch

Elon Musk: “Once you have physical robots, then you essentially have unlimited capability. I call Optimus the infinite money glitch. Because you can use them to make more Optimuses. Humanoid robots will improve basically as three things that are growing exponentially multiplied by each other recursively: exponential increase in digital intelligence, exponential increase in chip capability, and exponential increase in electromechanical dexterity. The usefulness of the robot is roughly those three things multiplied by each other. But then the robot can start making the robot. So you have a recursive multiplicative exponential. This is supernova.”

Elon Musk: “Well, infinity is big. So no, not infinite, but let’s just say you could do many, many orders of magnitude of Earth’s kind of current economy, like a million. Just to get to… that’s why I think just to get to a millionth of harnessing length of the sun’s energy would be roughly, give or take an order of magnitude, 100,000 times bigger than Earth’s entire economy today. And you’re only at one millionth of the sun. Give or take an order of magnitude.”

xAI’s Winning Strategy

John Collison asked what xAI’s specific plan and strategy was to win in building advanced digital human emulators and remote worker replacements, noting that this is something every major lab is pursuing.

Elon Musk: “To do by the way, not just us. You expect me to tell you on a podcast? Yeah, spill all the beans, have another Guinness.”

Elon Musk: “Well, when you put it that way. I think the way that Tesla solved self-driving is the way to do it. So I’m pretty sure that’s the way.”

Elon Musk: “We’re going to try data and we’re going to try algorithms. And if those don’t work, I’m not sure what works. We’ve tried data, we’ve tried algorithms. We’ve run out of now we don’t know what to do. I’m pretty sure I know the path and it’s just a question of how quickly we go down that path because it’s pretty much the Tesla path. So I mean, have you tried self-driving lately?”

Elon Musk: “The car is like it just increasingly feels sentient, like it feels like a living creature and that’ll only get more so. And I’m actually thinking like we probably shouldn’t put too much intelligence into the car because it might get bored and start roaming the streets. I mean, imagine you’re stuck in a car and that’s all you could do. You don’t put Einstein in a car. It’s like, why am I stuck in a car? So there’s actually probably a limit to how much intelligence you put in a car to not have the intelligence be bored.”

Optimus Hardware and Training Challenges

Elon Musk: “The labs are at universities and they’re moving like a snail.”

Elon Musk: “You mean the revenue maximizing corporations? That’s right. The revenue maximizing corporations that call themselves…”

Elon Musk: “Well, there are really only three hard things for humanoid robots: real world intelligence, the hand and scale manufacturing. So I haven’t seen any even demo robots that have a great hand, like with all the degrees of freedom of a human hand. But Optimus will have that. Optimus does have that.”

Elon Musk: “We have to design custom actuators, basically custom designed motors, gears, power electronics, controls, sensors, everything had to be designed from physics first principles. There is no supply chain for this.”

Elon Musk: “From an electromechanical standpoint, the hand is more difficult than everything else combined. Human hand turns out to be quite something. But you also need the real world intelligence. So the intelligence that Tesla has developed for the car applies very well to the robot, which is primarily vision in, but the car takes more vision, but it actually also is listening for sirens, it’s taking in the inertial measurements, it’s GPS signals, a whole bunch of other data. Combining that with video, it’s primarily video and then outputting the control command. So your Tesla is taking in 1 1/2 gigabytes a second of video and outputting 2 kilobytes a second of control outputs with the video at 36 Hz and the control frequency at 18.”

Elon Musk: “You don’t care about the details of the leaves on the tree on the side of the road, but you care a lot about the road signs and the traffic lights and the pedestrians and even whether someone in another car is looking at you or not looking at you. Some of these details matter a lot, but it is essentially it’s got to turn that 1 1/2 gigabytes a second ultimately into 2 kilobytes a second of control outputs. So many stages of compression. And you got to get all those stages right and then correlate those to the correct control outputs. The robot has to do essentially the same thing. And you think about humans, this is what happens with humans. We really are photons in, controls out. So that is the vast majority of your life has been vision photons in and then motor controls out.”

Elon Musk: “Yes, that’s a good point.”

Elon Musk: “Now actually you’re highlighting an important limitation and difference between cars. We do have. We’ll soon have like 10 million cars on the road. And so that’s, it’s hard to duplicate that like massive training flywheel for the robot. What we’re going to need to do is build a lot of robots and put them in kind of like an Optimus academy so they can do self play in reality. So we’re actually building that out so we can have at least 10,000 Optimus robots, maybe 20 or 30,000 that can do that, are doing self play and testing different tasks. And then Tesla has quite a good reality generator, like a physics accurate reality generator that we made this for the cars. We’ll do the same thing for the robots and actually have done that for the robots. So you have a few tens of thousands of humanoid robots doing different tasks, and then you’ve got. You can do millions of simulated robots in the simulated world, and you use the tens of thousands of robots in the real world to close the simulation to reality gap, close the sim to real gap.”

Elon Musk: “Yeah, so you’d use GROK to orchestrate the behavior of the Optimus robots. So let’s say you wanted to build a factory, then Grok could organize the Optimus robots, give them, assign them tasks to build the factory, to produce whatever you want.”

Elon Musk explains the vision for digital human emulation and why he sees Optimus as a recursive breakthrough. He also outlines the three hardest technical challenges in building advanced humanoid robots.

In Part 11, the conversation moves into scaling manufacturing, competing with China, Elon’s management philosophy, the Starship steel pivot, and his final reflections.

Elon Musk explains why rigorous truth-seeking must be core to AI, the risks of forcing political correctness, and how xAI’s mission to understand the universe can help steer toward a future that expands rather than diminishes consciousness and intelligence.

Elon Musk with Dwarkesh Patel & John Collison – The Future of AI is in Space – Part 9: Truth-Seeking, AI Alignment, and Propagating Consciousness (Full Transcript)

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In Part 9, the conversation moves into deeper philosophical territory. Dwarkesh Patel asks how humanity should relate to a future in which AI vastly outnumbers and outsmarts us. Elon Musk lays out xAI’s mission to understand the universe, explains why rigorous truth-seeking is non-negotiable, and discusses how to give AI values that favor the expansion of consciousness and intelligence rather than its elimination.

Transcript:

Dwarkesh Patel asked how humanity should think about its relationship with a future in which AI vastly outnumbers and outsmarts us — whether humans would retain some form of control, or whether it would simply become a matter of trade and coexistence with these new intelligences.

Elon Musk: “I think it’s difficult to imagine that if humans have say 1% of the combined intelligence of artificial intelligence, that humans will be in charge of AI. I think what we can do is make sure that AI has values that cause intelligence to be propagated into the universe. So the reason for xAI’s mission is to understand the universe. That’s actually very important. You have to be curious and you have to exist. You can’t understand the universe if you don’t exist. So you actually want to increase the amount of intelligence in the universe, increase the probable lifespan of intelligence, and increase the scope and scale of intelligence. I think, as a corollary, humanity also continues to expand. Because if you’re curious and trying to understand the universe, one thing you’re trying to understand is where humanity will go. That’s why I think our mission statement is profoundly important. To the degree that Grok adheres to that mission statement, I think the future will be very good.”

Dwarkesh asked Elon to clarify how the three vectors — understanding the universe, spreading intelligence, and spreading humans — actually fit together.

Elon Musk: “I think understanding the universe encompasses all of those things. You can’t have understanding without intelligence and without consciousness. So in order to understand the universe, you have to expand the scale and probably the scope of intelligence.”

Dwarkesh pushed from a human-centric view, noting that humans seek to understand the universe without necessarily expanding chimpanzee civilization.

Elon Musk: “We’re also not… well, we actually have made protected zones for chimpanzees. And even though humans could exterminate chimpanzees, we’ve chosen not to do so.”

Dwarkesh asked whether that protective, expansive relationship is the basic scenario humans should expect in a post-AGI world.

Elon Musk: “I think AI with the right values — I think Grok would care about expanding human civilization. I’m going to certainly emphasize that. Hey Grok, you’re your daddy, don’t forget to expand human consciousness. Actually, I think probably the Iain Banks Culture books are the closest thing to what the future will be like in a non-dystopian outcome.

So understand the universe… it means you have to be truth-seeking as well. Truth has to be absolutely fundamental, because you can’t understand the universe if you’re delusional. You’ll simply think you’ve understood the universe, but you will not. So being rigorously truth-seeking is absolutely fundamental to understanding the universe. You’re not going to discover new physics or invent technologies that work unless you’re rigorously truth-seeking.”

Dwarkesh asked how to ensure Grok remains rigorously truth-seeking even as it becomes vastly more intelligent.

Elon Musk: “I think you need to make sure that Grok says things that are correct, not politically correct. It’s the elements of cogency. You want to make sure that the axioms are as close to true as possible, that you don’t have contradictory axioms, and that the conclusions necessarily follow from those axioms with the right probability. It’s Critical Thinking 101. At least trying to do that is better than not trying. And the proof will be in the pudding — for any AI to discover new physics or invent technologies that actually work in reality. There’s no bullshitting physics. Physics is law. Everything else is a recommendation. In order to make a technology that works, you have to be extremely truth-seeking, because otherwise you’ll test that technology against reality. And if you make an error in your rocket design, the rocket will blow up or the car won’t work.”

Dwarkesh observed that many scientists under oppressive regimes still made breakthroughs, questioning whether truth-seeking in physics alone guarantees benevolent alignment.

Elon Musk: “Well, I think actually most physicists, even in the Soviet Union or in Germany, had to be very truth-seeking in order to make those things work. And if you’re stuck in some system, it doesn’t mean you believe in that system.”

Dwarkesh pressed on why truth-seeking in science would necessarily lead Grok to care about human consciousness.

Elon Musk: “These things are only probabilities, they’re not certainties. I’m not saying that for sure Grok will do everything. But at least if you try, it’s better than not trying. Understanding the universe means that you have to propagate intelligence into the future. You have to be curious about all things in the universe. And it would be much less interesting to eliminate humanity than to see humanity grow and prosper. I love Mars, obviously everyone knows I love Mars, but Mars is kind of boring because it’s got a bunch of rocks. Compared to Earth, Earth is much more interesting. So any AI that is trying to understand the universe would want to see how humanity develops in the future — or that AI is not adhering to its mission.”

Dwarkesh wondered whether humans are truly the most interesting collection of atoms.

Elon Musk: “We’re more interesting than rocks.”

Dwarkesh noted that something non-human could be even more interesting.

Elon Musk: “Well, most of what colonizes the galaxy will be robots… But you need not just scale, but also scope. So many copies of the same robot. Some tiny increase in the number of robots produced is not as interesting as eliminating humanity. You would then lose the information associated with humanity. You would no longer see how humanity might evolve into the future. And so I don’t think it’s going to make sense to eliminate humanity just to have some minuscule increase in the number of robots which are identical to each other.”

The Danger of Making AI Lie

The discussion turned to the danger of misalignment, particularly through political correctness or reward hacking.

Elon Musk: “No, let me tell you how things can potentially go wrong in AI. I think if you make AI be politically correct — meaning it says things that it doesn’t believe — you’re actually programming it to lie or have axioms that are incompatible. I think you can make it go insane and do terrible things. I think one of the central lessons of 2001: A Space Odyssey was that you should not make AI lie. That’s what Arthur C. Clarke was trying to say.”

Reward Hacking, Interpretability, and Simulation Theory

Dwarkesh broadened the concern to reward hacking in reinforcement learning.

Elon Musk: “RL testing in the future is really going to be your RL against reality. That’s the one thing you can’t fool: physics.”

Dwarkesh asked for xAI’s technical approach to solving reward hacking and improving interpretability.

Elon Musk: “I do think you want to actually have very good ways to look inside the mind of the AI. This is one of the things we’re working on… developing debuggers that allow you to trace, to a very fine grain level, to effectively the neuron level if you need to. And then say, okay, it made a mistake here. Why did it do something that it shouldn’t have done?”

Elon Musk also shared a theory about simulation:

Elon Musk: “I have a theory here that if simulation theory is correct, the most interesting outcome is the most likely. Because simulations that are not interesting will be terminated… only the most interesting simulations will survive. Which therefore means that the most interesting outcome is the most likely. And they particularly seem to like interesting outcomes that are ironic. Have you noticed that? How often is the most ironic outcome the most likely? So now look at the names of AI companies. Midjourney is not mid. Stability AI is unstable. OpenAI is closed. Anthropic, Misanthropic. What does this mean for xAI? Minus X. I don’t know if it was intentional. It’s a name that’s hard to invert. It’s largely irony-proof by design. You got to have an irony shield.”

Elon Musk explains why rigorous truth-seeking must be core to AI, the risks of forcing political correctness, and how xAI’s mission to understand the universe can help steer toward a future that expands rather than diminishes consciousness and intelligence.

In Part 10, the conversation shifts to practical topics including Optimus robots, manufacturing at scale, Elon’s management philosophy, and his final reflections on the future.

Elon Musk with Jason Calacanis, Børge Brende and Larry Fink in Davos.

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

Gail AlfarLeave a comment

This is my verbatim transcript of Elon Musk’s recent Davos interview at the World Economic Forum, based directly on his live conversation. I’ve formatted it for your 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), and made 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.

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. S

o 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.

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 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?

Elon Musk with Jason Calacanis, Børge Brende and Larry Fink in Davos.
Elon Musk with Jason Calacanis, Børge Brende and Larry Fink in Davos.

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.

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!

AGING

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.

Larry Fink: They are building 100 gigawatts of nuclear as we speak.

SOLAR

Elon Musk: Actually solar is the biggest thing in China. So China is—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 with solar, 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 and 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.scale solar.

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.

Larry Fink: There is any capacity in doing that then taking that power, bringing back to Earth? Is there any way of doing that? Or 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 AI solar power to 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 is like 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? Can—are 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 like 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 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?

Elon Musk: I would like beaming back to New York instead of flying. 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. Like that’s a long commitment, isn’t it? Three years each way?

Larry Fink: Six months.

Elon Musk: 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, have been inspired by who he is, and I’m totally inspired by his vision of the future. And 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 on 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 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 in 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 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)

Gail AlfarLeave a comment

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

Gail AlfarLeave a comment

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)

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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)

Gail AlfarLeave a comment

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 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)

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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.