Elon Musk Brutally Honest Interview!!!

Summary

Podcast Summary: "Elon Musk Brutally Honest Interview!!!"

Podcast: Elon Musk Thinking
Host: Astronaut Man
Guest: Elon Musk
Date: September 27, 2025

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Overview

This episode features Elon Musk in a wide-ranging, candid conversation about his journey as an entrepreneur, his philosophies on building world-changing companies, the future of AI and robotics, and the fate of humanity as a multi-planetary species. The discussion is aimed at a technical audience—mainly young engineers and researchers—and Musk offers both practical career advice and reflections on existential risks tied to rapid technological advancement.

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Key Discussion Points & Insights

1. Early Ambitions and Building Zip2 (01:30–06:12)

• Musk describes his early desire to “build something useful,” not necessarily expecting greatness but motivated by curiosity and utility.

  "I wanted to try to build something useful, but I didn't think I would build anything particularly great... but I wanted to at least try."
  — Elon Musk (01:30)

• Faced with a choice between grad studies at Stanford or pursuing the nascent Internet, Musk deferred graduate school and started Zip2, coding what he believes was one of the first online maps and directories.
• Musk recalled the frugal beginnings—sleeping in a rented office, showering at the YMCA.
• Key lesson: Be careful about ceding control to legacy interests when innovating, as they may not understand or support your vision.

  “The mistake was having too much shareholder and board control from legacy media companies who then necessarily see things through the lens of legacy media.”
  — Elon Musk (06:12)

2. From Zip2 to X.com/PayPal: Risk, Reward, and Rolling the Dice (09:24–11:44)

• After Zip2's sale (~$300M exit), Musk received ~$20M personally, which he mostly reinvested into X.com, which merged with Confinity to create PayPal.
• He underscores the importance of "going direct to consumer" to maintain control and fully realize technological potential.
• Musk challenged himself and others to keep taking risks after success.

3. Origins of SpaceX: Solving for Mars (11:44–15:08)

• Musk describes his curiosity about Mars colonization; finding NASA lacked plans, his first thought was a philanthropic greenhouse mission, not a business.
• To acquire affordable rockets, he attempted to buy ICBMs in Russia, but negotiations failed.
• Realizing the core problem was the high cost and inefficiency of existing rockets, he founded SpaceX to innovate and lower costs (despite heavy skepticism and risk).

4. The Toughest Years: Overlapping Crises at Tesla and SpaceX (15:28–19:23)

• Early SpaceX: "Less than 10% chance of success, maybe 1%," but “a small chance is better than none.”
• Notably, Musk had to become SpaceX's chief engineer by necessity—no experienced candidate wanted the risk.
• The fourth Falcon launch was a last-ditch effort—had it failed, both SpaceX and Tesla would likely have died. A crucial NASA contract and last-minute Tesla financing round saved both companies.

  "If the fourth launch hadn't worked, I had no money left and it would have been curtains..."
  — Elon Musk (15:28)

5. Leadership, Team Building, and Being Useful (19:23–22:37)

• For young engineers: focus on being genuinely useful, not chasing glory.

  "Don't aspire to glory, aspire to work."
  — Elon Musk (19:52)

• Minimize ego, internalize responsibility:

  “A major failure mode is when ego-to-ability ratio is... too high, then you break the feedback loop to reality. You want to have a strong RL [reinforcement learning] loop, which means internalizing responsibility and minimizing ego.”
  — Elon Musk (20:34)

6. First Principles Thinking & Physics as Superpower (22:37–27:38)

• First principles: Reduce problems to their fundamental components and reason up, rather than analogizing from the past.
• Example: Instead of accepting high rocket costs, Musk broke them down by raw material costs to see what's possible.
• Shared a detailed example of building a training supercluster at xAI—solving impossible power and networking constraints, guided by first principles.

  "If you break that down, what are the things you need? We need a building. You need power, you need cooling... But once we broke it down... we could solve those constituent elements."
  — Elon Musk (26:36)

7. AI, Data, and the Future of Intelligence (27:38–31:03)

• Win in AI requires top talent, hardware scale, data, and effective deployment.
• We're exhausting quality human-generated data; focus is shifting to synthetic data, and verifying its utility.
• Mentioned Grok 3.5 and the primacy of reasoning skills in future AI models.
• Vision for robotics: Predicts humanoid robots will outnumber humans by 5–10x within a century.

8. Robotics, Safety, and ‘Being a Participant’ (30:02–31:03)

• Musk initially hesitated to accelerate AI/robotics, fearing "making Terminator real," but realized it's inevitable and prefers to participate to steer outcomes responsibly.

9. Multiplying Civilizational Lifespan: Kardashev Scale & Fermi Paradox (31:03–33:54)

• Multi-planetary expansion is key—Musk hopes to make Mars self-sustaining within 30 years.
• On the Fermi Paradox: If intelligence is rare and we're unique, it's vital to preserve and propagate consciousness.

  "We should do everything possible to ensure the tiny candle [of intelligence] does not go out."
  — Elon Musk (33:17)

10. Existential Risk & AI Alignment (33:54–37:01)

• “Global thermonuclear war” and a lack of “rigorous adherence to truth” in AI are the greatest existential threats.
• Advocates for multiple competitive AI systems to mitigate the risk of a single monopoly model.

11. Neuralink—Closing the Human/AI Gap (37:01–39:29)

• Neuralink aims to massively increase brain/computer bandwidth, not essential for AGI but will augment human capabilities.
• Early clinical demonstrations: ALS patients now communicate fluidly via brain-computer interface.
• In the next year, expects visual implants to restore and even augment sight ("superpower situation").

12. The Singularity, Human Role, and Final Advice (40:01–42:08)

• The singularity is near: soon, human intelligence will be a minuscule fraction of total.
• Humanity's best contribution?

  “The biological bootloader for digital superintelligence.”

• Advice for young technical talent:

  “If you’re doing something useful, that’s great. If you just try to be as useful as possible to your fellow human beings, then you’re doing something good. Focus on super truthful AI, that's the most important thing for AI safety.”
  — Elon Musk (41:17)

• Hopes AI will answer ultimate scientific mysteries ("Where are the aliens? ... Are we in a simulation?").

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Notable Quotes & Memorable Moments

• On First Principles:

  “The tools of physics are incredibly helpful... First principles means... break things down to the fundamental axiomatic elements that are most likely to be true and then reason up from there as cogently as possible.”
  — Elon Musk (22:37)

• On Risk:

  “A small chance of success is better than no chance of success.”
  — Elon Musk (15:28)

• On Motivation:

  “Don’t aspire to glory, aspire to work.”
  — Elon Musk (19:52)

• On Robotics:

  “My prediction is that there will be more humanoid robots by far than all other robots combined by maybe an order of magnitude...”
  — Elon Musk (29:29)

• On Humanity’s Role:

  “We should do everything possible to ensure the tiny candle [of intelligence] does not go out.”
  — Elon Musk (33:17)

• On AI Safety:

  “A rigorous adherence to truth is the most important thing for AI safety.”
  — Elon Musk (36:34)

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Timestamps for Important Segments

• 01:30 — Musk’s early motivations and Zip2
• 06:12 — Lessons learned on company control
• 09:24 — Reinvesting after Zip2; starting PayPal
• 11:44 — Spark for Mars colonization and beginnings of SpaceX
• 15:28 — SpaceX risks, Falcon launches, and Tesla crisis
• 19:52 — Advice on building and leadership
• 22:37 — Explaining "first principles" thinking
• 26:36 — xAI’s supercluster as first principles case study
• 29:29 — The rise of humanoid robotics
• 31:35 — The Kardashev scale and multi-planetary vision
• 34:09 — Existential risks and AI truthfulness
• 37:01 — Neuralink: bandwidth, reading and writing to the brain
• 40:01 — The coming singularity
• 41:17 — Final advice to the next generation of engineers

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Closing Tone and Takeaways

Throughout the episode, Musk’s tone is frank, witty, and at times self-deprecating, openly discussing failures, doubts, and the immense odds faced on his journey. His overarching message: be useful, remain humble, seek truth, and aspire to work that benefits humanity—especially in an era where technology changes everything at “eye-watering” speed. For young engineers, the future is wide open—if they embrace risk, responsibility, and the relentless pursuit of reality over ego.

Transcript

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[Elon Musk]

I wanted to try to build something useful, but I didn't think I would build anything particularly great if you said probabilistically Seemed unlikely, but I wanted to at least try.

[Interviewer]

So you're talking to a room full of people who are all technical engineers, often some of the most eminent AI researchers coming up in the game.

[Elon Musk]

Okay, I think we should I think that I like the term engineer better than researcher. I suppose if there's some fundamental algorithmic breakthrough, it's research, but otherwise it's engineering.

[Interviewer]

Maybe let's start way back when you were this is a room full of 18 to 25 year olds. It skews younger because the founder set is younger and younger. Can you put yourself back into their shoes? When you were 18, 19 learning to code, even coming up with a first idea for Zip2. What was that like for you?

[Elon Musk]

Yeah, back in 95 I was faced with a choice of either do grad studies, PhD at Stanford and material science actually working on ultracapacitors for potential use in electric vehicles. Essentially trying to solve the range problem for electric vehicles or try to do something in this that most people had never heard of called the Internet. And I talked to my professor who was Bill Nix in the material science department and said can I defer for a quarter because this will probably fail and then I'll need to come back to college. And then he said this is probably the last conversation we'll have. And he was right. But I thought things would most likely fail, not that they would most likely succeed. And. And then in 95 I wrote basically I think the first or close to the first maps, directions, Internet white pages and yellow pages on the Internet. I just wrote that personally and didn't even use a web server. I just read the port directly because I couldn't afford and I couldn't afford a T. One original office was on Sherman Avenue in Palo Alto. There was like an ISP on the floor below. So I drilled a hole through the floor and just ran a LAN cable directly to the ISP and my brother joined me and another co founder Greg Curry who passed away. And at the time we couldn't even afford a place to stay so we just. The office was 500 bucks a month so we just slept in the office and then showered at the YMCA on pagemill and El Camino. And yeah and we, I guess we ended up doing a little bit of a useful company zip two in the beginning and did build a lot of really good software technology. But we're somewhat captured by the legacy media companies and that Nitrotter New York Times, the Hearst whatnot were investors and customers and also on the board. So they kept wanting to use software in ways that made no sense. So I wanted to go direct to consumers. Anyways, long story dwelling too much on Zip2 but the I really just wanted to do something useful on the Internet as because I had two choices. Do a PhD and watch people build the Internet or help build the Internet in some small way. And I was like I guess I can always try and fail and then go back to grad studies. And anyway that ended up being like reasonably successful. It sold for like $300 million which was a lot at the time. These days that's I think minimum impulse but for an AI startup is like a billion dollars. It's like there's so many friggin unicorns. It's like a herd of unicorns at this point. It was a billion dollar situation.

[Interviewer]

There's been inflation since so quite a.

[Elon Musk]

Bit more Money actually like 9.95. You could probably buy a burger for a nickel. Not quite, but yeah, there has been a lot of inflation. But the hype level on AI is pretty intense. As you've seen companies that are, I don't know, less than a year old getting sometimes billion dollar or multi billion dollar valuations, which I guess could pan out and probably will pan out in some cases, but it is eye watering to see some of these valuations. Yeah. What do you think?

[Interviewer]

I'm pretty bullish, personally. I'm pretty bullish honestly. So I think the people in this room are going to create a lot of the value that a billion people in the world should be using this stuff and we're not even scratching the surface of it. I love the Internet story in that even back then. You are a lot like the people in this room back then in that, you know, the heads of all the CEOs of all the legacy media companies look to you as the person who understood the Internet. And a lot of the world, the corporate world, like the world at large, that does not understand what's happening with AI, they're going to look to the people in this room for exactly that. It sounds like what are some of the tangible lessons? It sounds like one of them is don't give up board control or be careful about having a really good lawyer.

[Elon Musk]

I guess for the first, my first startup, the big, the really the mistake was having too much shareholder and board control from legacy media companies who then necessarily see things through the lens of legacy media and that they'll make you do things that seem sensible to them but really don't make sense with the new technology. And I should point out that I didn't actually at first intend to start a company. I tried to get a job at Netscape. I sent my resume into Netscape and Mark Hendrickson knows about this, but I don't think he ever saw my resume. And then nobody responded. And then I tried hanging out in the lobby of Netscape to see if I could bump into someone, but I was too shy to talk to anyone. So I'm like, man, this is ridiculous. So I'll just write software myself and see how it goes. So it wasn't actually from the standpoint of I want to start a company, I just want to be part of building the Internet in some way. And. And since I couldn't get a job at an Internet company, I had to start a Internet company anyway. The yeah, from an AI will so profoundly change the future. It's difficult to fathom how much but the economy, assuming we don't, things don't go awry and like AI doesn't kill us all and itself, then you'll see ultimately an economy that is not 10 times more than the current economy. Ultimately if we become say or whatever our future machine descendants, or mostly machine descendants, become like R scale 2 civilization or beyond, we're talking about an economy that is thousands of times, maybe millions of times bigger than the economy today. Yeah, I did feel a bit like when I was in D.C. taking a lot of flack for getting rid of waste and fraud, which was an interesting side quest as side quests go.

[Interviewer]

But gotta get back to the main quest.

[Elon Musk]

Yeah, I gotta get back to the main quest here. So back to the main quest. But I do feel a little bit like there's, it's like fixing the government is kind of say the beach is dirty and there's some needles and feces and like trash and you want to clean up the beach. But then there's also this like thousand foot wall of water which is a tsunami of AI. And how much does cleaning the beach really matter if you got a thousand foot tsunami about to hit? Not that much.

[Interviewer]

We're glad you're back on the main quest. It's very important.

[Elon Musk]

Back to the main quest. Building technology, which is what I like doing, it's just so much noise like this. The signal to noise ratio in politics is terrible.

[Interviewer]

I live in San Francisco, so you don't need to tell me twice.

[Elon Musk]

Yeah, DC is, I guess it's all politics in dc. But if you're trying to build a rocket or cars, or you're trying to have software that compiles and runs reliably, then you have to be maximally truth seeking or your software or your hardware won't work. Like there's no. You can't fool math. Like math and physics are rigorous judges. So I'm used to being in a maximally truth seeking environment and that's definitely not politics. So anyway, I'm good. Glad to be back in technology.

[Interviewer]

I guess I'm curious, going back to the Zip2 moment, you had hundreds of millions of dollars or you had an exit worth hundreds of millions of dollars.

[Elon Musk]

I got $20 million.

[Interviewer]

Right, okay, so you solved the money problem at least and you basically took it and you kept rolling with X.com which became PayPal and Confinity.

[Elon Musk]

Yes, I kept the chips on the table.

[Interviewer]

Not everyone does that. A lot of the people in this room will have to make that decision, actually. What drove you to Jump back into the ring thing.

[Elon Musk]

I felt with Zip2, we built like, incredible technology, but it never really got used. I think at least from my perspective, we had better technology than say, Yahoo or anyone else, but it was constrained by our customers. And so I wanted to do something that where, okay, we wouldn't be constrained by our customers. Go direct to consumer. And that's what ended up being like X.com, payPal, essentially X.com merging with confinity, which together created PayPal. And then that actually the sort of PayPal diaspora has it might have created more companies than. So more companies than probably anything in the 21st century. So many talented people were at the combination of confinity, x.com, so I just wanted to, like, I felt we got our wings clipped somewhat with Zip2 and it's okay. What if our wings aren't clipped and we go direct to consumer? And that's what PayPal ended up being. But yeah, with the. I got that $20 million check for my share of Zip2. At the time, I was living with, in a house with four housemates and had, I don't know, 10 grand in the bank. And then the. This check arrives in the mail, of all places in the mail. And then, then my bank balance went from 10,000 to 20 million and 10,000, okay, still have to pay taxes on that and all. But then I ended up putting almost all of that into x.com and as you said, like, just keeping almost all the chips on the table. And yeah, and then after PayPal, I was like, I was curious as to why we had not sent anyone to Mars. And I went on the NASA website to find out when we're sending people to Mars. And there was no date. I thought maybe it was just hard to find on the website. But in fact, there was no real plan to send people to Mars. So then I've come. This is such a long story. So I don't want to take up too much time here. But the.

[Interviewer]

I think we're all listening with rapt attention.

[Elon Musk]

So I was actually, I was on the Long Island Expressway with my friend Dale Resi. We were like housemates in college. And Dale was asking me what I'm. What we're going to do, what am I going to do after PayPal? And I was like, so I don't know, I guess maybe I'd like to do something philanthropic in space, because I didn't think I could actually do anything commercial in space because that seemed like the purview of nations. But I'm Curious as to when we're going to send people to Mars. And that's when I was like, oh, it's not on the website. And then I started digging. There's nothing on the NASA website. So then I started digging in and. And I'm definitely summarizing a lot here, but I. My first idea was to do a philanthropic mission to Mars called Life to Mars, which, where we send a small greenhouse with seeds and dehydrated nutrient gel, land that on Mars and grow, hydrate the gel, and then you'd have this great sort of money shot of green plants on a red background.

[Commercial Narrator]

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[Elon Musk]

For the longest time, by the way, I didn't realize Money Shot, I think is a porn reference. But anyway, the point is, that would be the great shot of green plants on a red background and to try to inspire NASA and the public to. To send astronauts to Mars. As I learned more, I came to realize, and along the way, by the way, I went to Russia in 2001 and 2002 to buy ICBMs, which is. That's an adventure. You go and meet with Russian high command and say, I'd like to buy some ICBMs.

[Interviewer]

This was to get to space.

[Elon Musk]

Yeah, as a rocket, not to nuke anyone. But they had to. As a result of arms reduction talks, they had to actually destroy a bunch of their big nuclear missiles. So I was like, how about if we take two of those minus the nuke, add an additional upper stage for Mars. But it was trippy. Being in Moscow in 2001, negotiating with the Russian military to buy ICVMs that's crazy. But they kept also raising the price on me. Literally. It's like the opposite of what a negotiation should do. So I was like, man, these things are getting really expensive. And then I came to realize that actually the problem was not that there was insufficient will to go to Mars, but there was no way to do without breaking the budget or even breaking the NASA budget. So that's where I decided to start SpaceX. To SpaceX, to advance rocket technology to the point where we could send people to Mars. And that was in 2002.

[Interviewer]

So that wasn't. But you didn't start out wanting to start a business. You wanted to start just something that was interesting to you, that you thought humanity needed. And then as you cat pulling on a string, it just. The ball sort of unravels and it turns out this is could be a very profitable business.

[Elon Musk]

It is now. But there had been no prior example of really a rocket startup succeeding. There have been various attempts to do commercial rocket companies and then all failed again with SpaceX starting. SpaceX was really, from the standpoint of I think there's a less than 10% chance of being successful, maybe 1%, I don't know. But if a startup doesn't do something to advance rocket technology, it's definitely not coming from the big defense contractors because they just impede and smash to the government. And the government just wants to do very conventional things. So it's either coming from a startup or it's not happening at all. So, like a small chance of success is better than no chance of success. And so the. Yeah, so SpaceX started that in mid-2002 expecting to fail. Like I said, probably 90% chance of failing. And even like when recruiting people, I didn't try to make out that it would. I said, we're probably going to die, but small chance we might not die, but this is the only way to get people to Mars and advance the state of the art. And then I ended up being chief engineer of the rocket, not because I wanted to, but because I couldn't hire anyone who was good. So none of the good sort of chief engineers would join because they're like, this is too risky, you're going to die. And so then I ended up being chief engineer of the rocket and the first three flights did fail. So it's a bit of a learning exercise there. And the fourth one fortunately worked, but if the fourth one hadn't worked, I had no money left and it would have been curtains. So it was a pretty close thing. If the fourth Launch of Falcon not work. It would have been just curtains and we would have just joined the graveyard of prior rocket startups. So my estimate of success was not far off. We just remade it by the skin of our teeth. And Tesla was happening simultaneously. Like 2008 was a rough year because at mid 2008, called Summer 2008, the third launch of SpaceX had failed. A third failure in a row, the Tesla financing round had failed. And so Tesla was going bankrupt fast. It was just, man, this is grim. This is going to be a tale of warning of an exercise in hubris.

[Interviewer]

Probably throughout that period a lot of people were saying, Elon is a software guy. Why is he working on hardware? Why would. Yeah, why would he choose to work on this?

[Elon Musk]

So you can look at the. Because it's still, the press of that time is still online. You can just search it. And they kept calling me Internet guy. So Internet Guy, AKA fool, is attempting to build a rocket company that we got ridiculed quite a lot. And it does sound pretty absurd. Like Internet guy starts rocket company. Doesn't sound like a recipe for success frankly. So I didn't hold it against them. I was like, yeah, admittedly it does sound improbable and I agree that it's improbable. But fortunately the fourth launch worked and, and NASA ordered us a contract to resupply the space station. And I think that was like maybe, I don't know, December 22nd or is it like right before Christmas? Because even the fourth launch working wasn't enough to succeed. NASA also needed, we also needed a big contract to keep us alive. So I got that call from like the NASA team and I literally, they said, we're rewarding you one of the contracts to resupply the space station. I like literally blurted out I love you guys. Which is not normally what they hear because it's usually pretty sober. But I was like, man, this is a company saver. And then we closed the Tesla financing round on the last hour of the last day that it was possible, which was 6pm, December 24, 2008. We would have bounced payroll two days after Christmas if that round hadn't closed. So that was a nerve wracking end of 2008, that's for sure.

[Interviewer]

I guess from your PayPal and Zip2 experience jumping into these hardcore hardware startups, it feels like one of the through lines was being able to find and eventually attract the smartest possible people in those particular fields. What would the people in this room like? Some of the most of the people Here, I don't think have even managed a single person yet. They're just starting their careers. What would you tell to the Elon who's never had to do that yet?

[Elon Musk]

I generally think to try to be as useful as possible. It may sound trite, but it's. It's so hard to be useful, especially to be useful to a lot of people. Where you say the area under the curve of total utility is like, how. How useful have you been to your fellow human beings times how many people? It's almost like the physics definition of true work. It's incredibly difficult to do that. And I think if you aspire to do true work, your probability of success is much higher. Don't aspire to glory, aspire to work.

[Interviewer]

How can you tell that it's true work? Is it external? Is it like what happens with other people or what the product does for people? What is that for you? When you're looking for people to come work for you, what's the salient thing that you look for? Or if they're.

[Elon Musk]

That's a different question. I guess it's in terms of your end product. You just have to say, if this thing is successful, how useful will it be to how many people? And that's what I mean. And then you do, you. You do whatever. Whether you're a CEO or any role in a startup, you do whatever it takes to succeed and just always be smash. Smashing your ego. Like internalized responsibility, like a major failure mode is when ego to ability ratio is double greater than sign one. If your ego to ability ratio gets too high, then you're going to basically break the feedback loop to reality. And in AI terms, you'll break your RL loop. So you don't want to break your R. You want to have a strong RL loop, which means internalizing responsibility and minimizing ego. And you do whatever the task is, no matter whether it's grand or humble. That's like, why actually I prefer the term like engineering as opposed to research. I prefer the term and I actually don't want it to call Xai a lab. I just want to be a company. It's like, what are the simplest, most straightforward, ideally, lowest ego terms are. Those are generally a good way to go. You want to just close the loop on reality hard. That's a super big deal.

[Interviewer]

I think everyone in this room really looks up to everything you've done around being a paragon of first principles and thinking about the stuff you've done. How do you actually determine your reality? Because that seems like a pretty big part of it. Like other people who have never made anything, non engineers, sometimes journalists at times who've never done anything, like they will criticize you, but then clearly you have another set of people who are builders, who have very high area under the curve, who are in your circle. How should people approach that? What has worked for you and what would you pass on to X to your children? What do you tell them when you're like, you need to make your way in this world? Here's how to construct a reality that is predictive from first principles.

[Elon Musk]

The tools of physics are incredibly helpful to understand and make progress in any field. First principles means just obviously just means break things down to the fundamental axiomatic elements that are most likely to be true and then reason up from there as cogently as possible, as opposed to reasoning by analysis or metaphor. And then just simple things like thinking in the limit. If you extrapolate, minimize this thing or maximize that thing. Thinking in the limit is very helpful. I'd use all the tools of physics. They apply to any field. This is like a superpower, actually. So you can take, say, take for example, like rockets, you could say, how much should a rocket cost? The typical approach that people would take to how much rocket should cost is they would look historically at what the cost of rockets are and assume that any new rocket must be somewhat similar to the prior cost of rockets. A first principles approach would be you look at the materials that the rocket is comprised of. So if that's aluminum, copper, carbon fiber, steel, whatever the case may be, and say, how much does that rocket weigh and what are the constituent elements and how much do they weigh? What is the material price per kilogram of those constituent elements? And that sets the actual floor on what a rocket can cost. It can asymptotically approach the cost of the raw materials. And then you realize, oh, actually a rocket, the raw materials of a rocket are only maybe 1 or 2% of the historical cost of a rocket. So the manufacturing must necessarily be very inefficient. If the, if the raw material cost is only 1 or 2%, that would be of first principles analysis of the potential for the, for cost optimization of a rocket. And that's before you get to reusability. To give an AI sort of AI example last year for Xai, when we were trying to build a training supercluster, we went to the various suppliers to ask, said this was beginning of last year, that we needed A hundred thousand H1 hundreds to be able to train Coherently and their estimates for how long it would take to complete that were 18 to 24 months. We need to get that done in six months. So then. Or we won't be competitive. So then if you break that down, what are the things you need? We need a building. You need power, you need cooling. We didn't have enough time to build a building from scratch, so we had to find an existing building. So we found a factory that was no longer in use in Memphis that used to build Electrolux products. But then the input power was 15 megawatts and we needed 150 megawatts. We rented generators and had generators on one side of the building and then we have to have cooling. So we rented about a quarter of the mobile cooling capacity of the US and put the chillers on the other side of the building. But that didn't fully solve the problem because the voltage var. The power variations during training are very big. So you can have power can drop by 50% in 100 milliseconds which the generators can't keep up with. So then we com. We added Tesla megapacks and modified the software in the megapacks to be able to smooth out the the power variation during the training run. And then there were a bunch of networking challenges. The networking cables, if you're trying to make 100,000 GPUs trained coherently, are very challenging.

[Interviewer]

Almost. It sounds almost any of those things you mentioned. I could imagine someone telling you very directly, no, you can't have that. You can't have that power. You can't have this. And it sounds like one of the salient pieces of first principles thinking is actually let's ask why. Let's figure that out. And actually let's challenge the person across the table. And if they. If I don't get an answer that I feel good about, I'm gonna not allow that to be. I'm not gonna let that know to stand is that that feels like something that you know, everyone, if someone were to try to do what you're doing and hardware seems to uniquely need this. In software we have lots of fluff and things that it's like we can add more CPUs for that, it'll be fine. But in hardware it's just not going to work.

[Elon Musk]

I think these general principles of first principle thinking apply to software and hardware apply to anything really. I'm just using a hardware example of how we were told something is impossible, but once we broke it down into the constituent elements of we need a building, we need Power, we need cooling, we need power smoothing. And then we could solve those constituent elements. But it was. And then we just ran the networking operation to do all the cabling, everything in four shifts, 24 7. And I was like sleeping in the data center and also doing cabling myself. And there were a lot of other issues to solve. Nobody had done a training run with a hundred thousand H1 hundreds training coherently last year. Maybe it's been done this year, I don't know. But. And then we ended up doubling that to 200,000. And so now we've got 150,000 H1 hundreds, 50K H2 hundreds and 30K GV2 hundreds in the Memphis training center. And we're about to bring 110,000 GB2 hundreds online at a second data center also in the Memphis area.

[Interviewer]

Is it your view that pre training is still working and larger the scaling laws still hold and whoever wins this race will have basically the biggest, smartest possible model that you could distill.

[Elon Musk]

There's of the various elements that beside competitiveness for large AI for sure the talent of the people matter, the scale of the hardware matters and how well you able to bring that hardware to bear. So you can't just order a whole bunch of GPUs and they don't. You can't just plug them in. So you've got to. You've got to get a lot of GPUs and have them trained coherently and stably. Then it's what unique access to data do you have? I guess distribution matters to some degree as well. Like how do people get exposed to your AI? Those are, those are critical factors for if it's going to be like a large foundation model that's competitive, as many have said. I think my friend Ilya Sutskayer said we've run out of pre training data of human generated pre. Like human generated data, you run out of tokens pretty fast of certainly of high quality tokens. And you have to do a lot of. You need to essentially create synthetic data and be able to accurately judge the synthetic data that you're creating to verify. Like is this real synthetic data or is it an hallucination that doesn't actually match reality? So achieving grounding in reality is tricky. But we are at the stage where there's more effort put into synthetic data. Like right now we're training Grok 3.5, which is a heavy focus on reasoning.

[Interviewer]

Going back to your physics point, what I heard for reasoning is that hard science, particularly physics textbooks are very Useful for reasoning. Whereas I think researchers have told me that social science is totally useless for reasoning.

[Elon Musk]

Yes, that's probably true. So yeah, there's something that's going to be very important in the future is combining deep AI in the data center or supercluster with robotics so that things like the Optimus humanoid robot. Incredible. Yeah, Optimus is awesome. There's going to be so many humanoid robots and robots of all sizes and shapes. But my prediction is that there will be more humanoid robots by far than all other robots combined by maybe an order of magnitude, like a big difference.

[Interviewer]

And is it true that you're planning a robot army of a sort?

[Elon Musk]

Whether we do it or whether Tesla does it, Tesla works closely with Xai. You've seen how many humanoid robot startups are there. It's. I think Jensen Huang was on stage with a lot, with a massive number of robots, robots from different companies. I think there was like a dozen different humanoid robots. I guess part of what I've been fighting and maybe what has slowed me down somewhat is that I'm, I'm a little, I don't want, I don't want to make Terminator real, you know, so I've been, I guess at least until recent years dragging my feet on, on AI and humanoid robotics and then I come to the realization, realization it's happening whether I do it or not. So you got really two choices, particip. You could either be a spectator or a participant. So I guess I'd rather be a participant than a spectator. So now it's pedal to the metal on humanoid robots and digital superintelligence.

[Interviewer]

So I guess there's a third thing that everyone has heard you talk a lot about that I'm really a big fan of becoming a multi planetary species. Where does this fit? This is all not just a 10 or 20 year thing, maybe a hundred year thing, like it's a many generations for humanity kind of thing. How do you think about it? There's AI, obviously, there's embodied robotics and then there's being a multiplant, multi planetary species. Does everything feed into that last point or what are you driven by right now for the next 10, 20 and 100 years?

[Elon Musk]

Geez, 100 years. Man, I hope civilization's around in 100 years. If it is around, it's going to look very different from civilization today. I'd predict that this going to be at least five times as many humanoid robots as there are humans. Maybe 10 times. One way to look at the progress of civilization is percentage completion. Kardashev so if you're in a Kardashev Scale 1, you've harnessed all the energy of a planet. In my opinion, we've only harnessed maybe 1 or 2% of Earth's energy. So we've got a long way to go to the Kardashev scale one. Then Carshift two, you've harnessed all the energy of a sun, which would be, I don't know, a billion times more energy than Earth, maybe closer to a trillion. And then Kardashev3 would be all the energy of a galaxy pretty far from that. So we're at the very early stage of the intelligence big bang. I hope we're in terms of being multi planetary. I think, I think we'll have enough mass transferred to Mars within like roughly 30 years to make Mars self sustaining, such that Mars can continue to grow and prosper even if the resupply ships from Earth stop coming. And that greatly increases the probable lifespan of civilization or consciousness and intelligence, both biological and digital. So that's why I think it's important to become a multi planet species. And I'm somewhat troubled by the Fermi paradox, like why have we not seen any aliens? And it could be because intelligence is incredibly rare and maybe we're the only ones in this galaxy, in which case the intelligence of consciousness is this like tiny candle in a vast darkness. And we should do everything possible to ensure the tiny candle does not go out. And being a multi planet species or making consciousness multi planetary greatly improves the probable lifespan of civilization. And it's the next step before going to other star systems. Once you at least have two planets, then you've got a forcing function for the improvement of space travel. And that ultimately is what will lead to consciousness expanding to the stars.

[Interviewer]

It could be that the Fermi paradox dictates once you get to some level of technology, you destroy yourself. How do we say ourselves? How do we actually. What would you prescribe to a room full of engineers? What can we do to prevent that from happening?

[Elon Musk]

Yeah, how do we avoid the great filters? One of the great filters would obviously be global thermonuclear war. So we should try to avoid that, I guess, building benign AI robots That AI that loves humanity and robots that are helpful. Something that I think is extremely important in building AI is a very rigorous adherence to truth, even if that truth is politically incorrect. My intuition for what could make AI very dangerous is if you force AI to believe things that are not true.

[Interviewer]

How do you think about. There's this argument for Open for safety versus closed for competitive edge. I think the great thing is you have a competitive model. Many other people also have competitive models. And in that sense, we're off of. Maybe the worst timeline that I'd be worried about is there's fast takeoff and it's only in one person's hands, that might collapse a lot of things. Whereas now we have choice, which is great. How do you think about this?

[Elon Musk]

Yeah, I do think there will be several deep intelligences. Maybe at least five, maybe as much as 10. I'm not sure that there's going to be hundreds, but it's probably close. Like maybe there'll be like 10 or something like that, of which maybe four will be in the US so I don't think it's going to be any one AI that has a runaway capability. But, yeah, several deep intelligences.

[Interviewer]

What will these deep intelligences actually be doing? Will it be scientific research or trying to hack each other?

[Elon Musk]

Probably all of the above. Hopefully they will discover new physics, and I think they're definitely going to invent new technologies. I think we're quite close to digital superintelligence. It may happen this year, and if it doesn't happen this year, next year for sure. Digital superintelligence, defined as smarter than any human at anything.

[Interviewer]

So how do we direct that to superabundance? We could have robotic labor. We have cheap energy. Intelligence on demand. Is that sort of the white pill? Like, where do you sit on the spectrum? And are there tangible things that you would encourage everyone here to be working on to make that white pill actually reality?

[Elon Musk]

I think it most likely will be a good outcome. I guess I'd agree with Jeff Hinton that Maybe it's a 10 to 20% chance of annihilation. But look on the bright side, that's 80 to 90% probability of a great outcome. So, yeah, I can't emphasize this enough. A rigorous adherence to truth is the most important thing for AI safety. Obviously, empathy for humanity and life as we know it.

[Interviewer]

We haven't talked about neuralink at all yet. But I'm curious. You're working on closing the input and output gap between humans and machines. How critical is that to AGI, asi? And once that link is made, can we not only read but also write?

[Elon Musk]

The neuralink is not necessary to solve digital superintelligence. That'll happen before neuralink is at scale. But what neuralink can effectively do is solve the input output bandwidth constraints, especially our output constraints. Bandwidth is very low. The sustained output of a human over the Course of a day is less than 1 bit per second. So it's 86,400 seconds in a day and is extremely rare for a human to output more than that number of symbols per day, certainly for several days in a row. So you really, with a neuralink interface, you can massively increase your output bandwidth and your input bandwidth, input being right to. You have to do right operations to the brain. We have now five humans who have received the kind of the read input where it's reading signals. And you've got people with ALS who really have their tetraplegics, but they can now communicate at similar bandwidth to a human with a fully functioning body and control their computer and phone, which is pretty cool. And then I think in the next six to 12 months, we'll be doing our first implants for vision, where even if somebody's completely blind, we can write directly to the, the visual cortex. And we've had that working in monkeys. Actually, I think one of our monkeys now has had a visual implant for three years. And at first it'll be relatively fairly low resolution, but long term you would have very high resolution and be able to see multispectral wavelengths. You could see an infrared, ultraviolet radar. It's like a superpower situation. Like at some point, the cybernetic implants would not simply be correcting things that went wrong, but augmenting human capabilities dramatically, augmenting intelligence and sensors and bandwidth dramatically. And that's going to happen at some point, but digital superintelligence will happen well before that. At least if we had neuralink, we might, we'll be able to appreciate the AI better.

[Interviewer]

I guess one of the limiting reagents to all of your efforts across all of these different domains is access to the smartest possible people. Simultaneous to that, we have the rocks, can talk and reason, and There may be 130 IQ now, and they'll probably going to be super intelligent soon. How do you reconcile those two things? What's going to happen in five, 10 years and what should the people in this room do to make sure that they're the ones who are creating instead of maybe below the API line?

[Elon Musk]

They call it the singularity for a reason, because we don't know what's going to happen in the not that far future. The percentage of intelligence that is human will be quite small. At some point, the collective sum of human intelligence will be less than 1% of all intelligence. And if things get to Kardashev level two, we're talking about human intelligence. Even assuming a Significant increase in human population and intelligence augmentation, like massive intelligence augmentation where everyone has an IQ of a thousand type of thing. Even in that circumstance, collective human intelligence will be probably 1 billionth that of digital intelligence anyway. Where's the biological bootloader for digital superintelligence?

[Interviewer]

I guess just to end off.

[Elon Musk]

Was I. He was like, was I a good bootloader?

[Interviewer]

Where do we go? How do we go from here? All of this is pretty wild sci fi stuff that also could be built by the people in this room. If you do you have a closing thought for the smartest technical people of this generation right now? What should they be doing? What should they be working on? What should they be thinking about tonight as they go to dinner?

[Elon Musk]

As I started off with, I think if you're doing something useful, that's great. If you just try to be as useful as possible to your fellow human beings and that then you're doing something good. I keep harping on this, like focus on super truthful AI. That's the most important thing for AI safety. Obviously. If anyone's interested in working at xai, please let us know. We're aiming to make GROK maximally truth seeking AI and I think that's a very important thing. Hopefully we can understand the nature of the universe. That's really what AI can hopefully tell us. Maybe AI can maybe tell us, where are the aliens and how did the universe really start? How will it end? What are the questions that we don't know that we should ask and are we in a simulation or what level of simulation are we in?

[Interviewer]

I think we're going to find out. Elon. Thank you so much for joining us everyone. Please give it up for Elon Musk.