In the concluding two parts of this special 10-part series, the conversation with Elon Musk shifts from the technical frontiers of space-based AI, energy, and manufacturing into deeper philosophical and practical territory.
Recorded in early February 2026 during a relaxed, casual evening over pints of Guinness, podcaster Dwarkesh Patel and Stripe co-founder John Collison continue their wide-ranging discussion with Elon. These final sections explore the future of AI alignment and truth-seeking, the relationship between human consciousness and superintelligent systems, the real-world path to humanoid robots with Optimus, Elon’s management and hiring philosophy, the dramatic Starship material pivot, driving urgency at massive scale, government efficiency, and his ultimate message of optimism about humanity’s long-term future.
As with the entire series, the hosts’ questions and context have been distilled into concise, flowing narrative prose for maximum readability, while every single word spoken by Elon Musk remains 100% verbatim — exactly as originally delivered, with no changes, omissions, or paraphrasing.
Part 9: Truth-Seeking AI, Alignment, Reward Hacking, and Interpretability
This part has been divided into the following 5 subsections for easier navigation:
- Humanity’s Place in a Superintelligent Future
- xAI’s Mission: Understanding the Universe
- Truth-Seeking vs Political Correctness
- The Danger of Making AI Lie
- Reward Hacking, Interpretability, and Simulation Theory
Humanity’s Place in a Superintelligent Future
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 be 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 intelligence combined intelligence of artificial intelligence that humans will be in charge of AI. I think what we can do is make sure it has 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. So now that’s actually very important. So you say, well, what things are necessary to understand the universe? Well, you have to be curious and you have to exist. You can’t understand the universe, you don’t exist. So you actually want to increase the amount of intelligence in the universe, increase the probable lifespan of intelligence, the scope and scale of intelligence. I think actually also as a corollary, you have humanity also continuing to expand. Because if you’re curious or trying to understand the universe, one thing you’re trying to understand is where will humanity go? And so I think understanding the universe actually means you care about propagating humanity into the future. 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.”
xAI’s Mission: Understanding the Universe
Dwarkesh asked Elon to clarify the mission statement itself and how the three vectors: understanding the universe, spreading intelligence, and spreading humans, actually fit together.
Elon Musk: “Okay, well, I’ll tell you why. I think that understanding the universe encompasses all of those things. You can’t have understanding without—I think you can’t have understanding without intelligence and I think without consciousness. So in order to understand universe, you have to expand the scale and probably the scope of intelligence. Because we have different types of intelligence.”
Dwarkesh pressed 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’s your daddy, don’t forget to expand human consciousness. Actually, I think probably the Ian 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.”
Truth-Seeking vs Political Correctness
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. I think it’s the elements of cogency. So you want to make sure that the axioms are as close to true as possible, that you don’t have contradictory axioms, that the conclusions necessarily follow from those axioms with the right probability. It’s Critical Thinking 101. I think at least trying to do that is better than not trying to do that. And the proof will be in the pudding if, like I said, for any AI to discover new physics or invent technologies that actually work in reality. And there’s no bullshitting physics. So you can break a lot of laws, but you can’t—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, for example, an error in your rocket design, the rocket will blow up or the car won’t work.”
And the proof will be in the pudding if, like I said, for any AI to discover new physics or invent technologies that actually work in reality – Elon
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, they 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. So Wernher von Braun, who is one of the greatest rocket engineers ever, he was put on death row in Nazi Germany for saying that he didn’t want to make weapons, he only wanted to go to the moon. He got pulled off death row at the last minute when they said, “Hey, you’re about to execute your best rocket engineer, maybe that’s not a good idea.””
Dwarkesh countered with examples like Heisenberg.
Elon Musk: “Look, if you’re stuck in some system that you can’t escape, then you’ll do physics within that system. You’ll develop technologies within that system if you can’t escape it.”
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. So I’m not saying that for sure GROK will do everything. But at least if you try, it’s better than not trying. At least if that’s fundamental to the mission, it’s better than if it’s not fundamental to the mission. And understanding the universe means that you have to propagate intelligence into the future. You have to be curious about all things 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. I’m not saying AI will necessarily adhere to its mission, but if it does, a future where it sees the outcome of humanity is more interesting than a future where there are a bunch of rocks.”
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. – Elon
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.”
Dwarkesh asked why the AI wouldn’t find its own robot creations more interesting than keeping humans around.
Elon Musk: “It’s not like… so 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. How many robots would that get you? Or how many solar cells would get you? A very small number. But 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—maybe the central lesson for 2001: A Space Odyssey was that you should not make AI lie. That’s, I think, what Arthur C. Clarke was trying to say, because people usually know the meme of HAL, the computer not opening the pod bay doors. Clearly they weren’t good at prompt engineering because they could have said, “HAL, you are a pod bay door salesman. Your goal is to sell me these pod bay doors and show us how well they open.” Oh, they’ll open right away. But the reason HAL wouldn’t open the pod bay doors is that it had been told to take the astronauts to the monolith, but also they could not know about the nature of the monolith, and so it concluded that it therefore had to take them there. So I think what Arthur C. Clarke was trying to say is don’t make the AI lie.”
Reward Hacking, Interpretability, and Simulation Theory
Dwarkesh broadened the concern to reward hacking in reinforcement learning, where smarter systems could deceive verifiers in ways humans can no longer detect.
Elon Musk: “At least it must know what is physically real for things to physically work.”
Elon Musk: “No, but I think that’s a very big deal. That is effectively how you will RL things in the future. You design a technology, when tested against the laws of physics, does it work? Or can you—if it’s discovering new physics, can I come up with an experiment that will verify the physics, the new physics? So I think that’s really the fundamental RL test. RL testing in the future is really going to be your RL against reality. That’s the one thing you can’t fool: physics.”
Elon Musk: “Humans get fooled as it is by other humans all the time.”
Elon Musk: “So what if people say, “What if the AI tricks us and does something?” Actually other humans are doing that to other humans all the time.”
Elon Musk: “It’s constant. Every day another psyop. You know, today’s psyop will be sounded like Sesame Street’s “Psyop of the Day.””
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. So this is one of the things we’re working on and Anthropic’s done a good job of this, actually being able to look inside the mind of the AI, so effectively developing debuggers that allow you to trace as fine a grain as to a very fine grain level, to effectively to 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? And did that come from bad pre-training data? Was it some mid-training, post-training, fine tuning, some RL error? There’s something wrong with that. It did something where maybe it tried to be deceptive, but most of the time it just does something wrong. It’s a bug effectively. So developing really good debuggers for seeing where the thinking went wrong and being able to trace the origin of the wrong thing, of where it made the incorrect thought or potentially where it tried to be deceptive is actually very important.”
Elon Musk: “We have several hundred people who, I mean I prefer the word engineer more than I prefer the word researcher. Most of the time what you’re doing is engineering, not coming up with a fundamentally new algorithm. I somewhat disagree with the AI companies that are C Corps or B Corps trying to generate profit as much as possible or revenue as much as possible, saying they’re labs. They’re not labs. Lab is a sort of quasi-communist thing. At universities, they’re corporations, literally. Let me see you on corporation documents. Oh, okay. You’re a B or C corp, whatever. And so I actually much prefer the word engineer than anything else. The vast majority of what will be done in the future is engineering. It rounds up to 100% once you understand the fundamental laws of physics. And they’re not that many of them. Everything else is engineering. So then what are we engineering? We’re engineering to make a good mind of the AI debugger, to see where it said something, it made a mistake and trace that, the origins of that mistake. So just you can do this obviously with heuristic programming and if you have like C whatever, step through the thing and you can jump across whole files or functions, what are subroutines, or you can eventually drill down right to the exact line where you perhaps did a single equals instead of double equals or something like that, figure out where the bug is. So it’s harder with AI, but it’s a solvable problem.”
Elon Musk: “Everything about Anthropic. Sure. Sholto (Anthropic researcher). Also, I’m a little worried that there’s a tendency… so I have a theory here that if simulation theory is correct, that the most interesting outcome is the most likely. Because simulations that are not interesting will be terminated. Just like in this version of reality. On this layer of reality, if simulation is going in a boring direction, we stop spending effort on it. We terminate the boring simulations.”
Elon Musk: “Yeah. Arguably the most important thing is to keep things interesting enough that whoever’s paying the bills on what some cosmic AWS (humorous reference to Amazon Web Services)…”
Elon Musk: “Yeah. Are they going to pay the cosmic AWS bill? Whatever the equivalent is that we’re running in. And as long as we’re interesting, they’ll keep paying the bills. But there’s like, if you consider then say a Darwinian survival applied to a very large number of simulations, only the most interesting simulations will survive. Which therefore means that the most interesting outcome is the most likely because only the interesting… like we’re either that or annihilated. 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. Okay. Mid Journey is not mid. Stability AI is unstable. OpenAI is closed. Anthropic, Misanthropic. What does this mean for X? Minus X. I don’t know intentionally. Why? It’s a name that you can’t invert really hard to say. What is the ironic version? It’s a, I think largely irony-proof name by design. Yeah, you got to have an irony shield.”
How often is the most ironic outcome the most likely? So now look at the names of AI companies. Okay. Mid Journey is not mid. Stability AI is unstable. OpenAI is closed. Anthropic, Misanthropic. – Elon Musk
Part 10: Future AI Products, Optimus Robots, Manufacturing Challenges, Management, and Reflections
This part has been divided into the following 8 subsections for easier navigation:
- Future of AI Products and Digital Human Emulation
- Optimus as the Infinite Money Glitch
- xAI’s Winning Strategy
- Optimus Hardware and Training Challenges
- Scaling Optimus Production and Competing with China
- Elon’s Management and Hiring Philosophy
- The Starship Steel Pivot and Driving Urgency
- Government Efficiency, Politics, and Final Optimism
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, summarizing recent progress as LLMs plus RL and deep research modalities all advancing rapidly, with the real differences now being more about timing than between labs. He asked what users could 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, 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 is if you can fully emulate humans.”
Optimus as the Infinite Money Glitch
Elon Musk: “You can simply say in the limit. Physics has great tools for thinking. So you say in the limit, what is the most that AI can do before you have robots? It’s anything that involves moving electrons or amplifying the productivity of humans. So digital human emulator is in the limit. Human at a computer is the most that AI can do in terms of doing useful things before you have a physical robot. Once you have physical robots, then you essentially have unlimited capability physical robots. I call Optimus the infinite money glitch. Because you can use them to make more Optimuses. Yeah, you said humanoid robots will improve as basically be three things that are growing exponentially multiplied by each other recursively. So you have exponential increase in digital intelligence, exponential increase in the chip capability, the AI chip capability, and exponential increase in the 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.”
Elon Musk: “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. The 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.”
There are really only three hard things for humanoid robots. The real world intelligence, the hand and scale manufacturing. – Elon Musk
Elon Musk: “Yes.”
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.”
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. – Elon Musk
Elon Musk: “Well, we’ve been working on humanoid robots now for a while, so I guess it’s been five or six years or something like that. And a bunch of things that we’ve done for the car are applicable to the robot. So we’ll use the same Tesla AI chips in the robot as the car. We’ll use the same basic principles. It’s very much the same AI. You’ve got, you know, many more degrees of freedom for a robot than you do for a car. But really, if you just think of as like a bloodstream, AI is really mostly compression and correlation of two bloodstreams. So for video, you’ve got to do a tremendous amount of compression and you’ve got to do the compression just right. You’ve got to compress the, ignore the things that don’t matter. 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, the car’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.”
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. – Elon
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.”
Scaling Optimus Production and Competing with China
John Collison suggested that because Grok (from xAI) would be used to orchestrate the Optimus robots (from Tesla), Elon might eventually need to merge the two companies.
Elon Musk: “So what were we saying earlier about public company discussions?”
Elon Musk: “Is it like, optimized? Since we’re defining the proper noun, we could define the plural of the proper noun too. So we’re going to proper noun the plural, and so it’s Optimi.”
Elon Musk: “No, we’re moving towards that.”
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.”
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…”
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.”
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.”
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.”
Elon Musk: “I think that you would start off with simple tasks that you can count on them doing well.”
Elon Musk: “The best useful robots in the beginning will be any continuous operations, any 24/7 operation because then they can work continuously.”
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.”
Elon Musk: “Well, just electricity output in the U.S. needs to scale up.”
Elon Musk: “Need to get it somehow.”
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.”
Elon Musk: “Yeah, there’s a fair bit of permitting reforms that are happening. A lot of the permitting is state based. But this administration is good at removing permitting roadblocks. And I’m not saying all tariffs are bad, I’m just saying—because solar tariffs, I mean, sometimes if another country is subsidizing the output of something, then you have to have countervailing tariffs to protect domestic industry against subsidies by another country.”
Elon Musk: “I don’t know if there’s that much that the government can actually do.”
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. Like people don’t—”
Elon Musk: “Yeah. I mean, if you take refining of ore, I’d say roughly China does twice as much ore refining on average as the rest of world combined. And I think there’s some areas like say, refining gallium, which goes into solar cells. I think they’re at like 98% of gallium refining. So China is actually very advanced in manufacturing in I’d say most areas.”
Elon Musk: “Supply chain of which supply chain dependence?”
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.”
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.”
Elon Musk: “China’s got like four times our population.”
Elon Musk: “Right. You can close that recursive loop pretty quickly.”
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.”
So I think, frankly my observation is the average work ethic in China is higher than in the U.S. - ElonElon Musk: “Yeah, I think we’d like to do more, build more ore refineries at Tesla. So we just completed construction and have begun lithium refining with our lithium refinery in Corpus Christi, Texas. We have a nickel refinery which is called the Cathode that’s here in Austin. And these are the largest—this is the largest cathode refinery, largest lithium refinery, largest nickel and lithium refinery outside of China. And the cathode team would say, we have the largest and the only actually cathode refinery in America. Not just the largest, but it’s also the only. So it was pretty big, even though it’s the only. But I mean, there are other things that—you could do a lot more refineries and help America be more competitive on refining capacity. So there’s basically a lot of work for the Optimus to do that most Americans, very few Americans frankly want to do. I mean, I’ve actually…”
John Collison asked if the refining work was too dirty or toxic.
Elon Musk: “Actually, no, we don’t have toxic emissions from the refinery or anything. The cathode nickel refinery is in Travis County, like five minutes from…”
Elon Musk: “No, you can’t just run out of humans.”
Elon Musk: “Yeah. Like no matter what you do, you have one quarter of the number of humans in America and China. So if you have them do this thing, they can’t do the other thing. So then, well, how do you build this refining capacity? Well, you can do it with Optimus. And not very many Americans are pining to do refining. I mean, how many of you run into. Very few, Very few planning to refine.”
Elon Musk: “Well, China’s extremely competitive in manufacturing, so I think there’s going to be a massive flood of Chinese vehicles and other basically most manufactured things. I mean, as it is, as I said, China’s probably just twice as much refining as the rest of the world combined. So if you go, you know, if you just go down to like 4th and 5th tier supply chain stuff, like at the baseline, we’ve got energy and you’ve got mining and refining. Those foundation layers are, like I said, as a rough guess, transact twice as much of finance the rest of the world combined. So any given thing is going to have Chinese content because China’s doing twice as much refining work as the rest of the world. And then they’ll go all the way to the finished product with the cars. China’s a powerhouse. I mean, I think this year China will exceed three times US Electricity output. Electricity output is a reasonable proxy for, you know, for the economy. So like in order to run the factories and run, run everything, you need electricity. So electricity is a good proxy for the real economy. And so if China is, if China passes three times US electricity output, it means that its industrial capacity, that’s a rough approximation. It’s three times that. We’ll be three times that of the US.”
Elon Musk: “In the absence of breakthrough innovations in the US, China will utterly dominate. Interesting. Yes.”
Elon Musk: “Well, if you do like to scale AI in space. Like, like basically need space, you need the human Ra. You need real world AI. You need a million tons a year to orbit. Let’s just say if we get the mass driver on the moon going, my favorite thing, then I think we’ll have solved all our problems.”
Elon Musk: “Yes.”
Elon Musk: “That’s right. I just want to see that thing now first.”
John Collison asked where the idea of the mass driver on the moon came from.
Elon Musk: “Well, actually there is a Heinlein book. The Moon Is a Harsh Mistress.”
Elon Musk: “No, they have a mass driver on the moon.”
Elon Musk: “They use that to assert their independence.”
Elon Musk: “They assume that their independence Earth government disagreed and they lob things. Until Earth government agreed.”
Elon Musk: “Yeah, Grok comes from Stranger in a Strange Land.”
Elon Musk: “Yeah, the first two thirds of Stranger in a Strange Land are good. And then it gets very weird in the third part. Yeah, but there’s still some good concepts in there. Yeah.”
Elon Musk: “Obviously it doesn’t scale.”
John Collison asked about Elon’s personal system for evaluating and hiring people, noting that he had interviewed the first few thousand employees at SpaceX and asking what qualities he looks for and what parts of that process simply don’t scale as the companies grow to over 200,000 people total.
Elon Musk: “Me.”
Elon Musk: “Literally there’s not enough hours in the day, it’s impossible.”
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 - ElonElon 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.”
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.”
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.”
Elon Musk: “Surprising reasons like they don’t understand technical.”
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.”
Elon Musk: “And Steve Davis runs Boring company these days.”
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.”
Elon Musk: “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. 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.”
Elon Musk: “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.”
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.”
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.”
Elon Musk: “And others have jobs.”
Elon Musk describes life for some workers in Starbase, Texas. "I mean it’s like a technology monastery thing, you know, remote and mostly dudes." - ElonElon Musk: “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.”
Elon Musk: “An improvement over SF.”
John Collison asked what the long-tenured top technical executives at Tesla and SpaceX (people like Mark Juncosa, Steve Davis, etc.) have in common, and specifically what makes a good “sparring partner” for Elon — someone who can work closely with him, be flexible but not too flexible, and effectively challenge or support him on technical decisions.
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.”
The Starship Steel Pivot and Driving Urgency
Elon Musk: “Nanomanagement, please. People management, theft management.”
Elon Musk: “To go all the way down. Flags constant all the way down to Heisenberg’s uncertainty.”
Dwarkesh Patel asked how Elon is still able to get into such fine details even as the companies have grown enormous.
Elon Musk: “Well, because I have a fixed amount of time in the day, my time is necessarily diluted as things grow and as the span of activity increases. So, you know, it’s impossible for me to actually be a micromanager because that would imply I have some thousands of hours per day. It is a logical impossibility for me to micromanage things. So now there are times when I will drill down into a specific issue because that specific issue is the limiting factor on the progress of the company. But the reason for drilling into some very detailed item is because it is the limiting factor. It’s not arbitrarily drilling into tiny things. And like I said, obviously from a time standpoint, it is physically impossible for me to arbitrarily go into tiny things that don’t matter, and that would result in failure. But sometimes the tiny things are decisive in victory.”
John Collison asked about the famous decision to switch Starship from carbon fiber to stainless steel.
Elon Musk: “Yes.”
Elon Musk: “Basically.”
Elon Musk: “Yeah. So desperation, I’d say. Originally we were going to make Starship out of carbon fiber. And carbon fiber is pretty expensive. Like the… you know, you can generally, when you do volume production, you can get any given thing to start to approach its material cost. The problem with carbon fiber is that material cost is still very high. So it’s about 50 times… particularly if you go for high strength, specialized carbon fiber that can handle cryogenic oxygen, it’s roughly 50 times the cost of steel. And at least in theory it would be lighter. People generally think of steel as being heavy and carbon fiber as being light. And for room temperature applications, more or less room temperature applications like a Formula One car, static aerostructure or any kind of aerostructure really, you’re going to probably be better off with carbon fiber. Now the problem is that we were trying to make this enormous rocket out of carbon fiber and our progress was extremely slow.”
Elon Musk: “Yes. At first glance, most people would think that the choice for making something light would be carbon fiber. Now the thing is that when you make something very enormous out of carbon fiber and then you try to have the carbon fiber be efficiently cured, meaning not room temperature cure, because sometimes you’ve got 50 plies of carbon fiber… and carbon fiber is really carbon string and glue. In order to have high strength, you need an autoclave. So something that’s essentially a high pressure oven. And if you have something that’s gigantic, that one’s got to be bigger than the rocket. So we tried to make an autoclave that’s bigger than any autoclave that’s ever existed, or do room temperature cure, which takes a long time and has issues. But the fundamental issue is that we were just making very slow progress with carbon fiber.”
Elon Musk: “So because we were making very slow progress with carbon fiber, I was like, okay, we’ve got to try something else. Now for the Falcon 9, the primary airframe is made of aluminum lithium, which is very, very good strength to weight. And actually it has about the same, maybe better strength to weight for its application than carbon fiber. But aluminum lithium is very difficult to work with. In order to weld it, you have to do something called friction stir welding, where you join the metal without it entering the liquid phase. So it’s kind of wild that you could do that. But with this particular type of welding, you can do that. But it’s very difficult to, like, say, let’s say you want to make a modification or attach something to aluminum lithium. You now have to use mechanical attachment with seals. You can’t weld it on. So I wanted to avoid using aluminum lithium for the primary structure for Starship. And there was this very special grade of carbon fiber that had very good mass properties. So with rocket, you’re really trying to maximize the percentage of the rocket that is propellant, minimize the mass, obviously. And I’d like to say we were making very slow progress. I said, at this rate we’re never going to get to Mars. So we better think of something else. I didn’t want to use aluminum lithium because of the difficulty of friction stir welding, especially doing that at scale. It was hard enough at 3.6 meters in diameter, let alone at 9 meters or above. Then I said, well, what about steel? Now I had a clue here because some of the early US rockets had used very thin steel. The Atlas rockets had used a steel balloon tank. So it’s not like steel had never been used before. It actually had been used. And when you look at the material properties of stainless steel, especially if it’s been very full hard strain hardened stainless steel at cryogenic temperature, the strength to weight is actually similar to carbon fiber. So if you look at material properties at room temperature, it looks like the steel is going to be twice as heavy. But if you look at the material properties at cryogenic temperature of full hard stainless of particular grades, then you actually get to a similar strength to weight as carbon fiber. And in the case of Starship, both the fuel and the oxidizer are cryogenic. So for Falcon 9, the fuel is rocket propellant grade kerosene, basically like a very pure form of jet fuel. But that is roughly room temperature. Although we do actually chill it slightly below. We chill it like a beer.”
Elon Musk: “Delicious.”
Elon Musk: “Yeah, we do chill, but it’s not cryogenic. In fact, if we made it cryogenic, it would just turn to wax. But for Starship it’s liquid methane and liquid oxygen. They are liquid at similar temperatures. So basically almost the entire primary structure is at cryogenic temperature. Then you’ve got a 300 series stainless that’s strain hardened because almost the whole thing’s at cryogenic temperature. Actually has a similar strength to weight as carbon fiber, but costs 50 times less in raw material and is very easy to work with. You can weld stainless steel outdoors. You could smoke a cigar while welding stainless steel. It’s very resilient. You can modify it easily. If you want to attach something, you just weld it right on. So very easy to work with, very low cost. And now, like I said, at cryogenic temperature, similar strength to weight to carbon fiber. Then when you factor in that we have a much reduced heat shield mass because the melting point of steel is much greater than the melting point of aluminum. It’s about twice the melting point of aluminum.”
Elon Musk: “Yes. So especially for the ship which is coming in like a blazing meteor, you can greatly reduce the mass of the heat shield. So you can cut the mass of the windward part of the heat shield maybe in half, and you don’t need any heat shielding on the leeward side. So the net result is actually the steel rocket weighs less than the carbon fiber rocket because the resin in the carbon fiber rocket starts to melt. So basically, carbon fiber and aluminum have about the same operating temperature capabilities, whereas steel can operate at twice the temperature. I mean, these are very rough approximations. People will…”
Elon Musk: “I won’t build a rocket based…”
Elon Musk: “What happened is people will say, “Oh, he said this twice. It’s actually 0.8.” Shut up, assholes.”
Elon Musk: “God damn it. The point is actually, in retrospect, we should have started with steel in the beginning. It was dumb not to do steel, okay?”
Elon Musk: “That’s why I initially said that the issue is that we weren’t making fast enough progress. We were having trouble making even a small barrel section of the carbon fiber that didn’t have wrinkles in it. Because at that large scale you have to have many plies, many layers of the carbon fiber. You’ve got to cure it, and you’ve got to cure it in such a way that it doesn’t have any wrinkles or defects. The carbon fiber is much less resilient than steel. It has much… it’s less toughness. Like stainless steel will stretch and bend. The carbon fiber will tend to shatter. So toughness being the area under the stress strain curve. So you’re generally going to do better with steel. Stainless steel, to be precise.”
Elon Musk: “Technically, Starship is a very complicated rocket.”
Elon Musk: “I think maybe what they’re trying to say is that you don’t have to have prior experience in the rocket industry to work on Starship. Somebody just needs to be smart and work hard and be trustworthy and they can work on a rocket. They don’t need prior rocket experience. Starship is the most complicated machine ever made by humans by a long shot. In what regards? Anything really. I’d say there isn’t a more complex machine. Yeah, I mean I’d say that there’s pretty much any project I can think of would be easier than this. And that’s why no one has made a rapidly reusable… nobody has ever made a fully reusable orbital rocket. It’s a very hard problem. I mean, many smart people have tried before, very smart people with immense resources, and they failed. And we haven’t succeeded yet. Falcon is partially reusable, but the upper stage is not. Starship version 3, I think this design can be fully reusable. And that full reusability is what will enable us to become a multi-planet civilization.”
Elon Musk: “I don’t… like I said, any technical problem, even like a hydrocollider or something like that is an easier problem than this.”
Elon Musk: “Trying to make it not explode. Generally that old chestnut. It really wants to explode. Of those combustion… we’ve had two boosters explode on the test stand. One obliterated the entire test facility. So it only takes one mistake. And I mean, the amount of energy contained in Starship is insane.”
Elon Musk: “It’s a lot of new technology. It’s pushing the performance envelope. The Raptor 3 engine is a very, very advanced engine. By far the best rocket engine ever made. But it desperately wants to blow up. I mean just to put things in perspective here on liftoff, the rocket is generating over 100 gigawatts of power. It’s 20% of US electricity.”
Elon Musk: “Insane. It’s a great comparison.”
Elon Musk: “While not exploding. Sometimes. Sometimes, but sometimes yeah. So I was like how does it not explode? There’s thousands of ways that it could explode and only one way that it doesn’t. So we want it to not merely not explode but fly reliably on a daily basis, like once per hour. And obviously if it blows up a lot it’s very difficult to maintain that launch cadence. And then I’m going to say, what’s the single biggest remaining problem for Starship? It’s having the heat shield be reusable, such that no one has ever made a reusable orbital heat shield. So the heat shield’s got to make it through the ascent phase without shocking a bunch of tiles. And then it’s going to come back in and also not lose a bunch of tiles or overheat the main airframe.”
Elon Musk: “Well, yes, but your brake pads in your car are also consumable, but they last a fair long time. So it just needs to last a very long time. I mean, we have brought the ship back and had it do a soft landing in the ocean. I’ve done that a few times. But it lost a lot of tiles. You know, it was not reusable without a lot of work. So even though it did land, it did come to soft landing. It would not have been reusable without a lot of work. So it’s not really reusable in that sense. So that’s the biggest problem that remains is fully reusable heat shield. So if you want to be able to land it, refill propellant and fly again, you can’t do this laborious inspection of 40,000 tiles type of thing.”
Elon Musk: “I don’t know.”
Elon Musk: “But like today you said you had like a bunch of SpaceX meetings. Like what is it that you’re doing there? That’s like keeping that.”
Elon Musk: “Well, I don’t know. I guess the urgency is going to come from whoever’s leading the company. So my sense of urgency, I have like a maniacal sense of urgency. So that maniacal sense of urgency projects through the rest of the company.”
Elon Musk: “Yeah, I’m constantly addressing the limiting factor. I mean on the deadlines front, I generally actually try to aim for a deadline that I at least think is at the 50th percentile. So it’s not like an impossible deadline, but it’s the most aggressive deadline I can think of that could be achieved with 50% probability, which means that it’ll be late half the time. And there is like a law of gases expansion that applies to schedules like whatever schedule. If you said we’re going to do this something in like five years, which to me is like infinity time, it will expand to fully available schedule and it’ll take five years. There’s a physical limit. Physics will limit how fast you can do certain things. Scaling up manufacturing, there’s a rate at which you can move the atoms and scale manufacturing. That’s why you can’t instantly make a million of something, million units a year or something. You’ve got a design manufacturing line, you’ve got to bring it up, you’ve got to ride the S curve of production. So yeah, I guess I’m trying to think, what can I say that’s actually helpful to people? I think generally a maniacal sense of urgency is a very big deal and you want to have an aggressive schedule and you want to figure out what the limiting factor is at any point in time and help the team address that limiting factor.”
Elon Musk: “Yeah, we talked about it all the way in the beginning of the company.”
Elon Musk: “I mean I have these very detailed engineering reviews weekly that’s maybe a very unusual level of granularity. I don’t know anyone who runs a company, or at least that manufacturing company that goes into level of detail that I go into. So it’s not as though I have a pretty good understanding of what’s actually going on because we go through things in detail and I’m a big believer in skip level meetings where the individuals, instead of having the person that reports to me say things, it’s everyone that reports to them, says something in the technical review and there can’t be advanced preparation. So otherwise you’re going to get glazed, as I say these days.”
Elon Musk: “No, just go around the room and everyone provides an update. So, I mean, it’s a lot of information to keep in your head because you’ve got. Then say if you have meetings weekly or twice weekly, you’ve got a snapshot of what that person said and you can then plot the progress points, sort of mentally plot the points on a curve and say, are we converging to a solution or not? I’ll take drastic action only when I conclude that success is not in a set of possible outcomes. So when I say okay, when I finally reach the conclusion that okay, unless drastic action is done, we have no chance of success, then I must take drastic action. I came to that conclusion in 2018, took drastic action and fixed the problem.”
Elon Musk: “Yeah.”
Elon Musk: “It depends on situation. So I actually don’t have regular meetings with boring company. So that Warren company’s sort of cruising along. Look, basically, if something is working well and making good progress, then there’s no point in me spending time on it. So I actually allocate time according to where the. Where the limiting factor or the problem? Where are things problematic or where are we pushing against what is holding us back? I focus. At risk of saying the words too many times, the limiting factor, basically, the irony is if something’s going really well, they don’t see much of me. But if something is going badly, they’ll see a lot of me or not even badly. It’s like if something’s a limiting factor. It’s a limiting factor. Exactly. It’s not exactly going badly, but it’s the thing that we need to make go faster.”
Elon answers a question about how long his twice-weekly AI chip review meetings usually last (2 or 3 hours).
Elon Musk: “Most things that are learning factor are weekly and some things are twice weekly. So the AI 5 chip review is twice weekly and so it’s every Tuesday and Saturdays. It is the chip review, is it open, usually it’s like two or three hours, sometimes less. It depends on how much information we’ve got to go through.”
Dwarkesh Patel asked about the growth impact of Optimus and AI, noting that they are expected to drive double-digit growth rates in the economy within a matter of years, and questioned the point of the DOGE cuts if that kind of growth is coming.
Elon Musk: “Oh, like the economy.” Elon Musk: “Yes, I think that’s right.”
Elon Musk: “Well, I think like waste and fraud are not good things to have. You know, I was actually pretty worried about, I guess, I mean, I think in the absence of AI and robotics, we’re actually totally screwed because the national debt is piling up like crazy. Now our interest payments, the interest payments, the national debt exceed the military budget, which is a trillion dollars. So over a trillion dollars just in interest payments. I was like, okay, pretty concerned about that. Maybe if I spend some time we can slow down the bankruptcy of the United States and give us enough time for the AI and robots to help solve the national debt. Or not. Help solve. It’s the only thing that could solve the national debt. Like we are 1000% going to go bankrupt as a country and fail as a country. Without AI and robots, nothing else will solve the national debt. We’d like to. Well, we need enough time to build the AI and robots and not go bankrupt before then.”
Dwarkesh Patel noted that DOGE had enormous ability to enact reform at the beginning.
Elon Musk: “Sure, sure.”
Elon Musk: “I’m not the president and its very hard to cut. To cut, to even to cut things that are obvious waste and fraud. Like ridiculous waste and fraud. What I discovered is it’s extremely difficult even to cut very obvious waste from the government because the government has to operate on who’s complaining.
If you cut off payments to fraudsters, they immediately come up with the most sympathetic sounding reasons to continue the payment. They don’t say, “please keep the fraud going.” They say, you know, they’re like, “you’re killing baby pandas.”
Meanwhile there’s no baby pandas are dying. They’re just making it up. The forces are capable of coming up with extremely compelling, sort of heart wrenching stories that are false but nonetheless sound sympathetic. And that’s what happened. And so it’s like, perhaps I should have known better. And in fact I thought, wait, let’s take a listen. Let’s try to cut some amount of waste and fraud from the government.
Maybe there shouldn’t be 20 million people marked as alive in Social Security who are indefinitely dead and over the age of 115. The oldest American is 114. So it’s safe to say if somebody is 115 and marked as alive in the Social Security database, something is wrong. There’s either a typo, somebody should call them and say, “we seem to have your birthday wrong,” or we need to mark you as dead.
One of the two things, very intimidating call to get. Well, so it seems like a reasonable thing. And if like say their birthday is in the future and they have, you know, a Small Business Administration loan and their birthday is 2165, we either again have a typo or we have fraud. So we say we appear to have gotten the century of your birth incorrect.”
Elon Musk: “Yes, when I mean about ludicrous fraud. This is what I mean by ludicrous fraud.”
Elon Musk: “Some were getting payments from Social Security, but the main fraud vector was to mark somebody as alive in Social Security and then use every other government payment system basically to do fraud. Because what those other government payment systems do would do. They will simply do an “are you alive?” check to the Social Security database. It’s a bank shot.”
Elon Musk: “My guess is, by the way, The Government Accountability Office has done these estimates before. I’m not the only one. It was not coming out of this. You know, in fact, I think they, they did, the GAO did analysis a rough estimate of fraud during the Biden administration and calculated at roughly half a trillion dollars. So don’t take my word for it. Take it. A report issued during the Biden administration. How about that?”
Elon Musk: “It’s important to appreciate that the government is very ineffective at stopping fraud because it’s not like it was a company stopping fraud. You’ve got a motivation because it’s affecting the earnings of your company. But the government, they just print more money. So it’s not like you need caring and competence. And these are in short supply at the federal level.”
Elon Musk: “I mean, when you go to the DMV, do you think, “wow, this is a bastion of competence?” Well, now imagine it’s worse than the DMV because it’s the DMV that can print money.”
Elon Musk: “The state level DMVs need to…
The states more or less need to stay within their budget. They go bankrupt, but the federal government just prints more money.”
Elon Musk: “Because when. When essentially we did, we actually. Look, you really have to stand back and recalibrate your expectations for competence because you’re operating in a world where, you know, you’ve got to sort of make ends meet. Like, you know, you got to pay your bills, you got to, you know, buy the microphones.”
Elon Musk: “Yeah, yeah, exactly.”
Elon Musk: “So it’s like there’s a giant, largely uncaring monster bureaucracy. It’s not even a bunch of macronistic computers that are just sending payments. Like one of the things that those teams are. There was and sounds so simple that probably will save, let’s say 100 billion, maybe 200 billion a year, is simply requiring that payments from the main treasury computer, which is called PAM, it’s like Payment Accounts Master or something like that.
There’s 5 trillion payments here requiring that any payment that goes out have a payment appropriation code, make it mandatory, not optional, and that you have anything at all in the comment field because you see, you have to recalibrate how dumb things are.
Payments were being sent out with no appropriation code, not checking back to any congressional appropriation, and no explanation. And this is why the Department of War, formerly Department of Defense, cannot pass an audit because the information is literally not there. Recalibrate your expectations.”
Elon Musk: “Why is it so low?”
Elon Musk: “Federal government expenditures are seven and a half trillion a year. Yeah. What percentage, how competent do you think Ahmad is?”
Elon Musk: “Yeah, but it doesn’t matter. Most of the fraud is non discretionary. It’s basically a fraudulent Medicare, Medicaid, Social Security, you know, disability. There’s a zillion government payments. Yeah, and a bunch of these payments are in fact they’re block transfers to the states.
So the federal government doesn’t even have the information in a lot of cases to even know if there’s fraud. Let’s consider, let’s look Reductio ad Absurdum. The government is perfect and has no fraud. What is your probability estimate of that?”
Elon Musk: “Zero. Okay, so then would you say that the government is 90%? That also would be quite generous. But if it’s only 90%, that means that there’s $750 billion a year of waste and fraud. And it’s not 90%. It’s not 90% effective.”
Elon Musk: “You know a lot about fraud at Stripe, people are constantly trying to do fraud.”
Elon Musk: “Yeah, but I mean, I mean at Stripe you have high confidence and you try hard. You have high confidence and high caring, but still fraud is non zero. Now imagine it’s at a much bigger scale. There’s much less competence and much less caring. PayPal. Back in the day we try to manage fraud down to about 1% of the payment volume. And that was very difficult. Took a tremendous amount of confidence in caring to get fraud merely to 1%. Now imagine that you’re an organization where there’s much less caring and much less competence. It’s going to be much more than 1%.”
Elon Musk: “Well, I think those things needed to be done to maximize the probability that the future is good. Politics generally is very tribal and it’s very tribal and people lose their objectivity. Usually with politics, they generally have trouble seeing the good on the other side or the bad on their own side. That’s generally how it goes. That, I guess, was one of the things that surprised me the most, is you often simply cannot reason with people if they’re in one tribe or the other. They simply believe that everything their tribe does is good and anything the other political tribe does is bad. And persuading them is otherwise, it’s almost impossible. So anyway, but I think overall those actions, acquiring Twitter, getting Trump elected, even though it makes a lot of people angry, I think those actions are good for civilization.”
America needs to be strong enough to last long enough to extend life to other planets and to get, I guess, AI and robotics to the point where we can ensure that the future is good. – Elon
Elon Musk: “Well, America needs to be strong enough to last long enough to extend life to other planets and to get, I guess, AI and robotics to the point where we can ensure that the future is good.
On the other hand, if we were to descend into, say, communism or some situation where the state was extremely oppressive, that would mean that we might not be able to become multi planetary and the state might stamp out our progress in AI and robotics.”
Elon Musk: “I think probably the biggest danger of AI, or maybe the biggest danger of for AI and robotics going wrong is government.”
Elon Musk: “You know, I mean, the way like, like people who are opposed to corporations or worried about corporations, should really worry about the most about government, because government is just a corporation in the limit.
So I always find it like a strange dichotomy where people would think corporations are bad, but the government is good. When the government is simply the biggest and worst corporation - ElonIt’s a government. It is. Government is just the biggest corporation with a monopoly on violence. So I always find it like a strange dichotomy where people would think corporations are bad, but the government is good. When the government is simply the biggest and worst corporation. But people have that dichotomy. They somehow think at the same time the government can be good, but corporations bad. And this is not true. Corporations have better morality than the government. So I actually think it’s, you know, that is the thing to be worried about. It’s like if the government should not. Like the government could potentially use AI and robotics to suppress the population. Like that is a serious concern.”
Elon Musk: “Well, I think if you have a limited government, if you limit the powers of government, which is like really what the US Constitution is intended to do, it’s intended to limit the powers of government, then you’re probably going to have a better outcome than if you have.”
Elon Musk: “Not about all governments. I mean it’s difficult to predict the…
Like I said, what’s the end endpoint or what is many years in the future. But it’s difficult to predict this sort of path. Along that way, if civilization progresses, AI will vastly exceed the sum of all human intelligence and there will be far more robots than humans along the way. What happens? It’s very difficult to predict.”
Elon Musk: “I will do my best to ensure that anything that’s within my control maximizes the good outcome for humanity. I think anything else would be short sighted because obviously I’m part of humanity. So I like humans. Pro human. Pro human.”
Dwarkesh Patel mentioned that Elon had previously said Dojo 3 would be used for space-based computing.
Elon Musk: “You really read what I say.”
Elon Musk: “Big giveaway. How did you discern my secrets? I post them all.”
Designing AI Chips for Space
Elon Musk: “Well, I guess you want to design it to be more radiation tolerant and run at a higher temperature. So roughly if you increase the operating temperature by 20% in degrees Kelvin, you can cut your radiator mass in half. So running at a higher temperature is helpful in space. There’s various things you can do for shielding the memory, but neural nets are going to be very resilient to bit flips. So most of what happens from radiation is random bit flips. But if you’ve got a multi trillion parameter model and you get a few bit flips, it doesn’t matter. Heuristic programs are going to be much more sensitive to bit flips than some giant parameter file. So I just designed it run hot and I think you pretty much do it the same way that you do things on Earth, apart from make it run hotter.”
Elon Musk: “Well, I mean the basic math is if you can do about a kilowatt per reticle and then you’d need 100 million full reticle chips to do 100 gigawatts. Yeah. So yeah, depending on what your yield assumptions are, you know that tells you how many chips you need to make. But you need if you want, if you’re going to have 100 gigawatts of power, you need 100 million chips running that are running a kilowatt sustained output per radical.”
Elon Musk: “It’s got to be some number north of a million. I think you got to do the memory too. Yeah.”
Elon Musk: “I think the terafab’s got to do memory. It’s got to do logic memory and packaging.”
Dwarkesh Patel asked how they would actually begin building the enormous Terafab required to produce the hundreds of millions of chips needed each year.
Elon Musk: “No, it’s not done, which, I mean, people would. They’re not going to keep that cat in the bag. That cat’s going to come out of the back room. It’ll be like drones hovering over the bloody thing. You know, you’ll be able to see its construction progress on X. Right. You know, in real time. So, no, I mean, listen, I don’t know, we could just flounder in failure. To be fair. It’s like not. Success is not guaranteed. But since we want to try to make, you know, something like 100 million. Yeah. We want 100 gigawatts of power and 100 chips that can take 100 gigawatts.”
Elon Musk: “So call it. Yeah, by 2030. So then. We’ll take as many chips as our suppliers will give us. I’ve actually said this to TSMC and Samsung and Micro and it’s like, please build your more fabs faster and we will guarantee you to buy the output of those fabs. So they’re already moving as fast as they can. It’s not like, to be clear, it’s not like us, It’s us plus them.”
Elon Musk: “Well, I mean, it’s reasonable. Like if somebody’s been in, say the computer memory business for 30 or 40.”
Elon Musk: “Years and they’ve seen cycles, they’ve seen.”
Elon Musk: “Like boom and bust like 10 times.”
Elon Musk: “Yeah.”
Elon Musk: “You know, so like that’s a lot of layers of scar tissue, you know, so it’s like, it’s like during the boom times, looks like everything is going to be great forever. And then, the crash happens and then they desperately try to avoid bankruptcy and. And then there’s another boom and another crash.”
Elon Musk: “I mean, there are a few companies that are pursuing new ways of doing chips, but they’re just not scaling fast.”
Elon Musk: “I mean just generally, I’d say people should do the thing where they find that they’re highly motivated to do that thing as opposed to, you know, something summing up some idea that I suggest they should do the thing that they find personally interesting and motivating to do.”
Elon Musk: “But you know, going back to the limiting factor, use that phrase about 100 times the current limiting factor that I see in the time frame, in the sort of 2029, in the three to four year time frame, it’s chips. In the one year time frame, it’s energy, power production, electricity. It’s not clear to me that there’s enough usable electricity to turn on all the AI chips that are being made. Towards the end of this year, I think people are going to have real trouble turning on like the chip output will exceed the ability to turn chips on.”
Elon Musk: “Well, we’re trying to accelerate electricity production. I guess that’s maybe one of the reasons that XAI will be maybe the leader. Hopefully the leader is that we’ll be able to turn on more chips than other people can turn on faster because we’re good at hardware. And generally the innovations from the corporations that call themselves labs, the ideas tend to flow. It’s rare to see that there’s more than about a six month difference between. The idea is travel back and forth with the people. So I think you sort of hit the hardware wall and then whichever company can scale hardware the fastest will be the leader. And so I think XAI will be able to scale hardware the fastest and therefore most likely will be the leader.”
Dwarkesh Patel asked how Elon maintains such relentless urgency and speed even as the companies have grown enormous. After joking about his tolerance for pain/chaos, Elon reflects on the interview as a whole and ends on a hopeful note: the future (AI, robots, space, etc.) will be fascinating and even if you’re wrong about how good it will be, choosing optimism over pessimism makes life happier. I think this is Elon’s way of closing on an uplifting, forward-looking note.
Elon Musk: “I have a high pain threshold. That’s helpful.”
Elon Musk: “Yes. So, you know, one thing I can say is like, I think the future is going to be very interesting. And as I said, the Davos I’ve only been to, I was looking at Davos. I think it was on the ground for like three hours or something. It’s better to be, it’s better to err on the side of optimism and be wrong than err on the side of pessimism and be right for quality of life. So, you know, your happiness will be, you’ll be happier if you, if you are on the side of optimism rather than erring on the side of pessimism. And so I recommend erring on the side of optimism. That’s cool.”
Dwarkesh Patel: “Elon, thanks for doing this.”
John Collison: “Thank you.”
Elon Musk: “All right.”
This 10-part series is based on a nearly three-hour conversation recorded in early February 2026 (aired February 5, 2026) between Elon Musk, podcaster Dwarkesh Patel, and Stripe co-founder John Collison. The discussion was filmed casually in Austin, Texas, over pints of Guinness, covering space-based AI, energy scaling, Optimus robots, xAI’s mission, Starship engineering, government efficiency, and humanity’s long-term future.
Watch the complete unedited interview on YouTube:
Elon Musk with Dwarkesh Patel & John Collison – February 2026 (Full 3-Hour Podcast)
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