Living here in Austin, Texas, where traffic on Mopac can flip from smooth to nightmare in a heartbeat (especially when there’s an accident or some surprise Texas rain), safety is always on my mind. That’s why I got so excited when Tesla announced this massive milestone on February 18, 2026!
Tesla drivers around the world have now driven more than 8 billion miles (nearly 13 billion km) using Full Self-Driving Supervised. Even more mind-blowing? They added 1 billion miles in just the first 50 days of 2026 alone!
That huge pile of real-world driving data is letting Tesla’s AI learn and improve faster than ever. According to Tesla’s own published safety stats, a vehicle on FSD Supervised experiences a major accident only once every 5.3 million miles. This is roughly eight times safer than the average across all vehicles on U.S. roads.
Behind those numbers are real-life moments that matter: the system putting on hazard lights and gently pulling over for emergency services help on its own if a driver has a medical emergency, applying the brakes or moving aside to avoid a crash, or gently guiding you through inclement weather. These are the reasons supervised autonomy is already saving lives by taking human error out of the equation. We all know human error causes the vast majority of accidents.
My personal experience as a Tesla owner in Austin
As a mom of five grown kids, a nurse who sometimes drives home after long shifts, and a proud owner of both a Model 3 and a Model Y with FSD (and Powerwalls at home), this tech has genuinely changed my life. I use FSD every single day here in Austin — whether I’m heading out to record a podcast episode, running errands around the Hill Country (my fav is to visit Buc-ees), or just daily commuting to work on highways where many drivers get distracted (driving and texting is everywhere in Austin!)
Just last month during a heavy downpour on Mopac Loop 1, FSD smoothly handled hydroplaning risks, kept perfect lane position, and even slowed for a sudden slowdown ahead that I hadn’t spotted yet. It gives me such peace of mind. I think about older family members or anyone who might feel tired or unwell behind the wheel. I feel that “co-pilot” protection in real time, and it’s one of the main reasons I’m so passionate about Tesla’s mission.
This progress fits perfectly into Elon Musk’s bigger vision of using AI to move humanity forward. At xAI, the team is building Grok with that same dedication to truth and excellence to speed up scientific discovery and help us all better understand the universe. This is a positive, open approach that truly benefits everyone.
With this kind of rapid acceleration, Tesla is proving the future of mobility isn’t coming someday… it’s already here on our roads right now.
Sources:
• Official Tesla announcement, February 18, 2026
• Tesla Vehicle Safety Report (latest data)
• No exaggeration, no rounded figures — straight from Tesla.
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Gail Alfar, Austin, Texas
(US Army Veteran, RN, Mom of 5, and founder of What’s Up Tesla)
Living in a place like Austin or the Bay Area, you know traffic can turn from charming to nightmare with just one road accident, and they seem to happen a lot. On February 17, 2026, Tesla quietly built the very first production line Cybercab at Giga Texas. No steering wheel, no gas or brake pedals. It is a little two-seater that has a mission to drive itself completely. Elon is saying production really starts picking up in April, and I was lucky enough to see one of these golden cars testing on the streets of Austin on Feb 17th around 7pm!
The big hope everyone keeps talking about is safety. Road crashes kill more than 40,000 people a year in the U.S. (NHTSA numbers). If the car can take human mistakes out of the equation, that number could actually drop. I think that part feels especially real for older folks or anyone who can’t drive easily anymore.
Tesla Cybercab rides could end up super cheap, like maybe 20 cents a mile once the cars are running a lot. That would be a game-changer in cities where Uber gets expensive fast and buses don’t always go where you need. For people here in Texas or California, it could mean getting around without the stress of working to pay for a car.
Right now Tesla’s already doing limited unsupervised Model Y robotaxi rides in Austin, and many people have taken rides. They are rare, as all my rides in Austin have had a supervisor thus far, however that will change soon. The plan seems to be rolling Cybercab out first in places like the Bay Area and here in Austin, basically following the same path they’re using with the Model Ys. Makes sense, as they likely test close to home where they can fix things quickly.
The Full Self-Driving software has now driven over 8 billion miles total, and they added another billion just in the first 50 days of this year. That’s a crazy amount of real-world data. Whether you adore or merely tolerate Elon Musk, you have to admit his team is moving fast on this stuff, and quietly, it’s hard not to respect anyone pushing this hard to make roads less deadly.
OWN YOUR OWN CYBERCAB AND WIRELESS CHARGING
MORE: They’re also talking about a Cybercab version people can actually purchase and own for under $30,000 by 2027, plus they just got the okay for Cybercab wireless charging. Still lots of regulatory hurdles, especially state-by-state rules, and competitors like Waymo are trying to keep up. I say that wen these goals are realized, things will quietly change how a lot of us get from point A to point B.
Feels like the future isn’t science fiction anymore. It’s starting in Austin, Texas.
Sources I pulled from:
Elon Musk’s X posts about production start and first unit
Teslarati articles on the first Cybercab and the 8 billion mile FSD milestone
In late January 2026, a catastrophic winter storm dubbed Winter Storm Fern swept through Tennessee and Mississippi, bringing heavy ice and snow from January 22-27. The storm triggered widespread power outages, peaking at over 180,000 in Mississippi alone and leaving thousands without electricity for days in freezing conditions. The US government issued federal major disaster declarations in early February for both states, enabling FEMA assistance, which can be useful, and often takes days to help people in need.
Private sector support proved crucial for immediate needs, and one company reacted fast
Elon Musk’s xAI and Tesla companies responded swiftly, and this shows the high value that innovative private tech firms can have when they choose to help bridge gaps in public emergency response programs. People in affected communities needed immediate help.. Through xAI, Musk facilitated the donation of hundreds of portable gas generators, providing critical power for heating, medical devices, and daily necessities in hard-hit areas.
One key example occurred on February 2, 2026, when nearly 500 generators donated by xAI arrived in Tippah County, Mississippi. These were distributed to residents who had been without power for over 10 days. Local emergency officials helped coordinate rapid rollout, prioritizing vulnerable households.
Similarly, in Tennessee, the state received and fully distributed 500 generators to the most impacted counties by February 3, 2026, aiding recovery in regions still reeling from prolonged blackouts. Tennessee Gov. Bill Lee personally thanked Elon Musk in a public post on X, “Tennesseans without power need immediate help. I’m deeply grateful to Elon Musk and xAI for going above & beyond to support Tennesseans by donating hundreds of generators to fill the gap & I value their continued partnership to solve problems & support communities across our state”.
Elon Musk replied with, “You’re most welcome. We’re working on providing Tesla Powerwalls too”.
You’re most welcome. We’re working on providing Tesla Powerwalls too.
Additionally, Tesla activated free Supercharging for electric vehicles in affected parts of Tennessee and Mississippi, ensuring all EV owners (not just Tesla owners) could maintain mobility and charge essential devices during the crisis.
All Superchargers in Mississippi and Tennessee are online. Free Supercharging enabled to help those affected in areas with persistent power outages:
This forward-thinking approach from leaders in the world of technology like artificial intelligence shows how valued people are, after all, they are the reason businesses can thrive, as they provide not just valuable tech services, but they provide jobs that support families for generations.
It is heartwarming to see official relief work with the private sector. You never really appreciate help in a disaster unless you or a loved one have actually experience it.
In the final part of the series, Dwarkesh Patel and John Collison ask Elon about government efficiency, waste and fraud, the role of AI and robotics in America’s long-term future, and his closing thoughts on optimism.
Transcript:
AI, Robotics, and the National Debt
Dwarkesh Patel asked about the point of DOGE cuts if AI and robotics are expected to drive strong economic growth in the coming years.
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.”
Government Fraud and Waste
Dwarkesh Patel asked why it had been so difficult to cut obvious waste and fraud from the government.
Elon Musk: “I’m not the president and it’s 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.”
Elon Musk gave an example of fraud involving Social Security records:
Elon Musk: “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.”
Dwarkesh Patel asked for an estimate of total fraud from this mechanism.
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?”
The Challenge of Government Efficiency
Dwarkesh Patel asked why it had been difficult to cut hundreds of billions in fraud if it was so obvious.
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.
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.”
Reflections on Politics and X
John Collison asked how Elon feels looking back on his involvement in politics and the acquisition of Twitter, noting both the impact and the personal cost.
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.”
AI, Government, and Corporate Power
Dwarkesh Patel asked how Elon thinks about the risk of governments using advanced AI and robotics to suppress populations, and whether private companies should set limits on what governments can do with their technology.
Elon Musk: “I think probably the biggest danger of AI, or maybe the biggest danger of for AI and robotics going wrong is government.
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. It’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.”
Dwarkesh asked what Elon can do as someone building these technologies to prevent misuse by governments.
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.
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.
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.”
Final Reflections
John Collison reflected on the theme of leaning into acute pain to solve bottlenecks rather than enduring chronic pain.
Elon Musk: “I have a high pain threshold. That’s helpful.
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 concludes the 14-part transcript series of Elon Musk’s conversation with Dwarkesh Patel and John Collison. Elon shares his views on government efficiency, the risks of concentrated power, and why he believes erring on the side of optimism leads to a better life and a better future.
In Part 13, Dwarkesh Patel and John Collison ask Elon about the famous decision to switch Starship from carbon fiber to stainless steel and how he continues to drive urgency and focus on bottlenecks as his companies have scaled.
Transcript:
The Starship Material Decision: From Composites to Steel
John Collison asked about the decision to switch Starship from carbon fiber to stainless steel, noting that it was a decision Elon pushed for rather than something the team arrived at on its own.
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.”
John Collison asked if carbon fiber had been chosen initially simply because it was light.
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.”
Why Steel Was the Answer
Elon Musk explained how the team reached the decision to switch to steel:
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.”
John Collison noted that steel allows the rocket to run much hotter.
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.”
John Collison asked whether Elon had to push the team toward the riskier steel path because carbon fiber felt more proven, even if it was slower.
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.”
Driving Urgency at Scale
Dwarkesh Patel asked how Elon continues to drive urgency and focus on bottlenecks as his companies have grown very large.
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.”
Dwarkesh asked how Elon maintains that culture of urgency across very large organizations.
Elon Musk: “I have a maniacal sense of urgency. So that maniacal sense of urgency projects through the rest of the company. 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 explains the decision to switch Starship to stainless steel and how he continues to drive urgency by constantly focusing on the current limiting factor.
In Part 14, the conversation concludes with government efficiency, politics, and Elon’s final reflections on the future.
In Part 12, Dwarkesh Patel and John Collison dive into Elon Musk’s management and hiring philosophy. They discuss how he evaluates talent, why companies outgrow people as they scale, and what makes someone effective at Tesla and SpaceX.
Transcript:
Evaluating Technical Talent
John Collison asked about Elon’s system for evaluating and hiring people, noting that he personally interviewed the first few thousand employees at SpaceX.
Elon Musk: “Me. Literally there’s not enough hours in the day, it’s impossible.”
John Collison asked what Elon looks for in candidates.
Elon Musk: “Well, at this point I think I’ve got, I might have more training data on evaluating technical talent especially, but talent of all kinds, I suppose, but technical talent especially given that I’ve done so many technical interviews and then seen the results. Technical interviews, seen the results. So my training set is enormous and has a very wide range.
Generally the thing I ask for are bullet points for evidence of exceptional ability. These things can be pretty off the wall. It doesn’t need to be in the domain, the specific domain, but evidence of exceptional ability. So if somebody can cite even one thing, but let’s say three things where you go wow, wow, wow, then that’s a good sign.”
Dwarkesh Patel asked why Elon himself had to be the one making those judgments.
Elon Musk: “No, I don’t. I can’t be. It’s impossible. Right? I mean, total headcount across all companies, 200,000 people. Right.”
John Collison asked what made early hiring so hard to delegate.
Elon Musk: “Well, I guess I need to build my training set. It’s not like I’ve bat a thousand here. I would make mistakes, but then I’d be able to see where I thought somebody would work out well, but they didn’t. And then why did they not work out well? And what can I do to, I guess reload myself to in the future have a better batting average when interviewing people? So my batting average is still not perfect, but it’s very high.”
Dwarkesh Patel asked what some surprising reasons were for people not working out.
Elon Musk: “Surprising reasons like they don’t understand technical.”
Dwarkesh pushed for more detail on the long tail of hiring mistakes.
Elon Musk: “Yeah, so the, I mean generally what I tell people, I tell myself, I guess aspirationally is don’t look at the Resume just believe, believe your interaction. So the resume may seem very impressive and it’s like, wow, resume looks good. But if the conversation after 20 minutes, that conversation is not. Well, you should believe the conversation, not the paper.”
Executive Retention and Company Growth
John Collison noted that Tesla and SpaceX have had relatively stable and internally promoted executive teams despite rapid growth, and asked what the long-tenured technical leaders have in common.
Elon Musk: “Well, so the, I mean it tells us sort of senior team at this point probably has an average tenure of 10 or 12 years. It’s quite, quite long. Yeah. So, but there are times when Tesla went through extremely rapid and extremely rapid growth phase and so things were just somewhat sped up.
And when a company, as you know, company goes through different orders of magnitude of size, people who could help manage say a 50 person company versus a 500 person company versus a 5,000 person company versus a 50,000 person. It’s just not the same team. It’s not always the same team. So if a company is growing very rapidly, the rate at which executive positions will change will also be proportionate to the rapidity of the growth generally.”
John Collison asked about the challenge of retaining talent when companies become successful and get heavily recruited.
Elon Musk: “Then Tesla had a further challenge where when Tesla had very successful periods, we would be relentlessly recruited from relentlessly. When Apple had their electric car program, they were carpet bombing Tesla with recruiting calls. Engineers just unplugged their phones.
If I get one more call from Apple recruiter, but they’re opening offer without any interview with me, like double the compensation at Tesla. So we had a bit of the Tesla pixie dust thing where it’s like, oh, if you hired a Tesla executive suddenly you’re going to.. everything’s going to be successful. And I’ve fallen prey to the pixie dust thing as well where it’s like, oh, we’ll hire someone from Google or Apple and they’ll be immediately successful. But that’s not how it works. People are people. There’s not like magical pixie dust.
So when we have the pixie dust problem we would get relentlessly recruited and, and then also Tesla being engineering especially being primarily in Silicon Valley, it’s easier for people to just like they don’t have to change their life very much. They can just their commute is going to be the same.”
John Collison asked how to prevent the “pixie dust” effect of other companies poaching talent.
Elon Musk: “I don’t think there’s much we can do to stop it. But that’s like, that’s one of the reasons why Tesla, but really being in Silicon Valley and having the pixie dust thing at the same time meant that there was just a very, very aggressive recruitment.”
John Collison noted that moving to Austin likely helped.
Elon Musk: “Austin. Yeah, it still helps. I mean Tesla still has a majority of it’s engineering in California, so getting engineers to move, I call it the significant other problem. Yes. And others have jobs.
Yeah, yeah, exactly. So for Starbase that was particularly difficult since the odds of finding a non SpaceX job Brownsville, Texas are pretty low. Yeah, it’s quite difficult. I mean it’s like a technology monastery thing, you know, remote and mostly dudes. An improvement over SF.”
Management Philosophy and Hiring
John Collison asked what the long-tenured technical executives at Tesla and SpaceX have in common and what makes a good “sparring partner” for Elon.
Elon Musk: “I don’t think it was a sparring partner. I mean, if somebody gets things done, I love them. And if they don’t, I… So it’s pretty straightforward. It’s not like some idiosyncratic thing. If somebody executes well, I’m a huge fan. And if they don’t, I’m not. But it’s not about mapping to my idiosyncratic preferences, or certainly try not to have it be mapping to my idiosyncratic preferences.
Yeah, but generally I think it’s a good idea to hire for talent and drive and trustworthiness. And I think goodness of heart is important. I weighted that at one point. So are they a good person, trustworthy, smart and talented and hardworking? If so, you can add domain knowledge. But those fundamental traits, those fundamental properties you cannot change. So most of the people who are at Tesla and SpaceX did not come from the aerospace industry or the auto industry.”
Elon Musk shares his philosophy on hiring, evaluating talent, and why companies must evolve their leadership as they grow. In Part 13, the conversation continues with the famous decision to switch Starship from carbon fiber to stainless steel and how he drives urgency at scale.
In Part 11, Dwarkesh Patel and John Collison explore the synergies between xAI and Optimus, the difficulties of scaling humanoid robot production at volume, and whether America can realistically compete with China’s manufacturing power through robotics.
Transcript:
Synergies Between xAI and Optimus
Dwarkesh Patel asked how Elon thinks about the synergies between xAI and Optimus, especially since Grok could potentially act as a world model and higher-level intelligence for planning while lower-level motor policies handle execution.
Elon Musk: “Yeah, so you’d use GROK to orchestrate the behavior of the Optimus robots. So let’s say you wanted to build a factory, then Grok could organize the Optimus robots, give them, assign them tasks to build the factory, to produce whatever you want.”
John Collison asked whether this meant xAI and Tesla would eventually need to merge.
Elon Musk: “So what were we saying earlier about public company discussions?”
Scaling Optimus Production
Dwarkesh Patel asked what Elon still wants to see on the hardware side before moving to mass manufacturing of Gen 3 Optimus — better actuators or improved software.
Elon Musk: “No, we’re moving towards that.”
Dwarkesh followed up, asking if Ford-style manufacturing with current hardware was good enough and whether Elon just wanted to deploy as many as possible now.
Elon Musk: “I mean, it’s very hard to scale up production. But yeah, I think Optimus 3 is the right version of the robot to produce maybe something on the order of like a million units a year. I think you’d want to go to Optimus 4 before you went to 10 million units a year.”
John Collison confirmed whether a million units per year was achievable with Optimus 3.
Elon Musk: “Yeah, I mean, it’s very hard to spool up manufacturing. So manufacturing, the output per unit time always follows an S curve. So it starts off agonizingly slow, then has this sort of exponential increase, then linear, then a logarithmic outcome until you sort of eventually asymptote at some number.
Optimus initial production will be—it’s going to be a stretched out S curve because so much of what goes into Optimus is brand new. There’s not an existing supply chain. As I mentioned, the actuators, electronics, everything in the Optimus robot is designed for physics first principles. It’s not taken from a catalog. These are custom designed. Everything, literally everything. I don’t think there’s a single thing that—”
John Collison asked how far down the custom design goes.
Elon Musk: “I mean I guess we’re not making custom capacitors yet maybe, but there’s nothing you can pick out of a catalog at any price. So it just means that the Optimus S curve, the units per year output per unit time, how many Optimus robots you make per day, whatever, is going to initially ramp slower than a product where you have an existing supply chain. But it will get to a million.”
Competing with Chinese Humanoids
Dwarkesh Patel asked about Chinese humanoids like Unitree selling for $6K–$13K. He wondered whether Tesla aimed to match that price or if the Chinese robots were qualitatively different.
Elon Musk: “Well, our Optimus is designed to have a lot of intelligence and to have the same electromechanical dexterity if not higher than a human. So Unitree does not have that. And it’s also, I mean it’s quite a big robot. It has to carry heavy objects for long periods of time and not overheat or exceed the power of its actuators. So we’ve got—it’s 5’11”, this is pretty tall and it’s got a lot of intelligence. So it’s going to be more expensive than a small robot that is not intelligent.”
John Collison noted that Optimus would be more capable.
Elon Musk: “Yeah, not a lot more. I mean the thing is over time as Optimus robots build Optimus robots, the cost will drop very quickly.”
John Collison asked what the first billion Optimuses would do and what their highest and best use would be.
Elon Musk: “I think that you would start off with simple tasks that you can count on them doing well.”
John Collison asked whether that would be in homes or factories.
Elon Musk: “The best useful robots in the beginning will be any continuous operations, any 24/7 operation because then they can work continuously.”
Dwarkesh Patel asked what fraction of work currently done by humans at a Gigafactory a Gen 3 Optimus could handle.
Elon Musk: “I’m not sure. Maybe it’s like 10, 20%, maybe more, I don’t know. We would not reduce our headcount. We would for sure increase our headcount, to be clear, but we would increase our output. So the units produced per human—the total number of humans at Tesla will increase, but the output of robots and cars will increase disproportionately. The number of cars and robots produced per human will increase dramatically, but number of humans will increase as well.”
US-China Manufacturing and Policy
John Collison asked what policy changes Elon would make if he were in charge, referencing solar tariffs and permitting.
Elon Musk: “Yeah, I would say anything that is a limiting factor for electricity needs to be addressed, provided it’s not very bad for the environment.”
John Collison brought up export bans on chips and turbine engines and asked whether more should be considered.
Elon Musk: “Well, I think it’s important to appreciate that in most areas China is very advanced in manufacturing. There’s only a few areas where it is not. China is a manufacturing powerhouse next level.”
John Collison asked about supply chain dependence, specifically gallium refining.
Elon Musk: “Yeah, there’s rare earth stuff. Rare earths, which are, as you know, not rare. We actually do rare earth ore mining in the U.S., send the rock, we put it on a train and then put on a boat to China that goes on another train and goes to the rare earth refineries in China, who then refine it, put it into a magnet, put it into a motor sub assembly, and then send it back to America. So the thing we’re really missing is a lot of ore refining in America.”
John Collison asked whether this was worth policy intervention.
Elon Musk: “Yes, well, I think there are some things being done on that front, but we kind of need Optimus, frankly, to build ore refineries.”
The Robot Advantage
Dwarkesh Patel summarized that China’s main advantage is abundant skilled labor and that Optimus could help close that gap, but noted the concern that China might pull ahead in humanoid production first.
Elon Musk: “Right. You can close that recursive loop pretty quickly.”
John Collison asked if this could be done with a small number of Optimuses.
Elon Musk: “Yeah. So you close the recursive loop to help the robots build the robots, and then we can try to get to tens of millions of units a year. Maybe if you start getting to hundreds of millions of units a year, I think you’re going to be the most competitive country by far.
We definitely can’t win with just humans because China has four times our population. And frankly, America’s been winning for so long that just like a pro sports team that’s been running for a very long time tend to get complacent and entitled and that’s why they stop winning, because they don’t work as hard anymore.
So I think, frankly my observation is the average work ethic in China is higher than in the U.S. So it’s not just that there’s four times the population, but the amount of work that people put in is higher. So you can try to rearrange the humans, but you’re still one quarter of the—assuming that productivity is the same, which I think actually it might not be, I think China might have an advantage on productivity per person. We will do one quarter of the amount of things as China.
So we can’t win on the human front. And our birth rate’s been low for a long time. The US birth rate’s been below replacement since roughly 1971. So we’ve got a lot of people retiring or more people dying than—we’re close to more people domestically dying than being born. So we definitely can’t win on the human front, but we might have a shot at the robot front.”
Elon Musk explains the challenges of scaling Optimus production and how robotics could help America compete with China’s manufacturing dominance.
In Part 12, the conversation continues with Elon’s management and hiring philosophy.
In Part 10, John Collison and Dwarkesh Patel shift the conversation toward the practical future of AI products and humanoid robots. They ask Elon about digital human emulation, why he refers to Optimus as the “infinite money glitch,” and the biggest technical hurdles in scaling advanced humanoid robots.
Transcript:
Future of AI Products and Digital Human Emulation
John Collison asked for Elon’s predictions on where AI products are headed in 2026 and 2027. He noted that recent progress across labs has been rapid, with LLMs, reinforcement learning, and deep research modalities all advancing quickly. He observed that the real differences between labs now seem to be more about timing than fundamental capability gaps, and asked what users should expect next.
Elon Musk: “Well, I think I’d be surprised by the end of this year if digital human emulation has not been solved. I guess that’s what we mean by the sort of Macrohard project. Can you do anything that a human with access to a computer could do, like in the limit? That’s the best you can do before you have a physical Optimus. The best you can do is a digital Optimus. So you can move electrons and you can amplify the productivity of humans. But that’s the most you can do until you have physical robots that will superset everything — if you can fully emulate humans.”
Optimus as the Infinite Money Glitch
Elon Musk: “Once you have physical robots, then you essentially have unlimited capability. I call Optimus the infinite money glitch. Because you can use them to make more Optimuses. Humanoid robots will improve basically as three things that are growing exponentially multiplied by each other recursively: exponential increase in digital intelligence, exponential increase in chip capability, and exponential increase in electromechanical dexterity. The usefulness of the robot is roughly those three things multiplied by each other. But then the robot can start making the robot. So you have a recursive multiplicative exponential. This is supernova.”
Elon Musk: “Well, infinity is big. So no, not infinite, but let’s just say you could do many, many orders of magnitude of Earth’s kind of current economy, like a million. Just to get to… that’s why I think just to get to a millionth of harnessing length of the sun’s energy would be roughly, give or take an order of magnitude, 100,000 times bigger than Earth’s entire economy today. And you’re only at one millionth of the sun. Give or take an order of magnitude.”
xAI’s Winning Strategy
John Collison asked what xAI’s specific plan and strategy was to win in building advanced digital human emulators and remote worker replacements, noting that this is something every major lab is pursuing.
Elon Musk: “To do by the way, not just us. You expect me to tell you on a podcast? Yeah, spill all the beans, have another Guinness.”
Elon Musk: “Well, when you put it that way. I think the way that Tesla solved self-driving is the way to do it. So I’m pretty sure that’s the way.”
Elon Musk: “We’re going to try data and we’re going to try algorithms. And if those don’t work, I’m not sure what works. We’ve tried data, we’ve tried algorithms. We’ve run out of now we don’t know what to do. I’m pretty sure I know the path and it’s just a question of how quickly we go down that path because it’s pretty much the Tesla path. So I mean, have you tried self-driving lately?”
Elon Musk: “The car is like it just increasingly feels sentient, like it feels like a living creature and that’ll only get more so. And I’m actually thinking like we probably shouldn’t put too much intelligence into the car because it might get bored and start roaming the streets. I mean, imagine you’re stuck in a car and that’s all you could do. You don’t put Einstein in a car. It’s like, why am I stuck in a car? So there’s actually probably a limit to how much intelligence you put in a car to not have the intelligence be bored.”
Optimus Hardware and Training Challenges
Elon Musk: “The labs are at universities and they’re moving like a snail.”
Elon Musk: “You mean the revenue maximizing corporations? That’s right. The revenue maximizing corporations that call themselves…”
Elon Musk: “Well, there are really only three hard things for humanoid robots: real world intelligence, the hand and scale manufacturing. So I haven’t seen any even demo robots that have a great hand, like with all the degrees of freedom of a human hand. But Optimus will have that. Optimus does have that.”
Elon Musk: “We have to design custom actuators, basically custom designed motors, gears, power electronics, controls, sensors, everything had to be designed from physics first principles. There is no supply chain for this.”
Elon Musk: “From an electromechanical standpoint, the hand is more difficult than everything else combined. Human hand turns out to be quite something. But you also need the real world intelligence. So the intelligence that Tesla has developed for the car applies very well to the robot, which is primarily vision in, but the car takes more vision, but it actually also is listening for sirens, it’s taking in the inertial measurements, it’s GPS signals, a whole bunch of other data. Combining that with video, it’s primarily video and then outputting the control command. So your Tesla is taking in 1 1/2 gigabytes a second of video and outputting 2 kilobytes a second of control outputs with the video at 36 Hz and the control frequency at 18.”
Elon Musk: “You don’t care about the details of the leaves on the tree on the side of the road, but you care a lot about the road signs and the traffic lights and the pedestrians and even whether someone in another car is looking at you or not looking at you. Some of these details matter a lot, but it is essentially it’s got to turn that 1 1/2 gigabytes a second ultimately into 2 kilobytes a second of control outputs. So many stages of compression. And you got to get all those stages right and then correlate those to the correct control outputs. The robot has to do essentially the same thing. And you think about humans, this is what happens with humans. We really are photons in, controls out. So that is the vast majority of your life has been vision photons in and then motor controls out.”
Elon Musk: “Yes, that’s a good point.”
Elon Musk: “Now actually you’re highlighting an important limitation and difference between cars. We do have. We’ll soon have like 10 million cars on the road. And so that’s, it’s hard to duplicate that like massive training flywheel for the robot. What we’re going to need to do is build a lot of robots and put them in kind of like an Optimus academy so they can do self play in reality. So we’re actually building that out so we can have at least 10,000 Optimus robots, maybe 20 or 30,000 that can do that, are doing self play and testing different tasks. And then Tesla has quite a good reality generator, like a physics accurate reality generator that we made this for the cars. We’ll do the same thing for the robots and actually have done that for the robots. So you have a few tens of thousands of humanoid robots doing different tasks, and then you’ve got. You can do millions of simulated robots in the simulated world, and you use the tens of thousands of robots in the real world to close the simulation to reality gap, close the sim to real gap.”
Elon Musk: “Yeah, so you’d use GROK to orchestrate the behavior of the Optimus robots. So let’s say you wanted to build a factory, then Grok could organize the Optimus robots, give them, assign them tasks to build the factory, to produce whatever you want.”
Elon Musk explains the vision for digital human emulation and why he sees Optimus as a recursive breakthrough. He also outlines the three hardest technical challenges in building advanced humanoid robots.
In Part 11, the conversation moves into scaling manufacturing, competing with China, Elon’s management philosophy, the Starship steel pivot, and his final reflections.
In Part 9, the conversation moves into deeper philosophical territory. Dwarkesh Patel asks how humanity should relate to a future in which AI vastly outnumbers and outsmarts us. Elon Musk lays out xAI’s mission to understand the universe, explains why rigorous truth-seeking is non-negotiable, and discusses how to give AI values that favor the expansion of consciousness and intelligence rather than its elimination.
Transcript:
Dwarkesh Patel asked how humanity should think about its relationship with a future in which AI vastly outnumbers and outsmarts us — whether humans would retain some form of control, or whether it would simply become a matter of trade and coexistence with these new intelligences.
Elon Musk: “I think it’s difficult to imagine that if humans have say 1% of the combined intelligence of artificial intelligence, that humans will be in charge of AI. I think what we can do is make sure that AI has values that cause intelligence to be propagated into the universe. So the reason for xAI’s mission is to understand the universe. That’s actually very important. You have to be curious and you have to exist. You can’t understand the universe if you don’t exist. So you actually want to increase the amount of intelligence in the universe, increase the probable lifespan of intelligence, and increase the scope and scale of intelligence. I think, as a corollary, humanity also continues to expand. Because if you’re curious and trying to understand the universe, one thing you’re trying to understand is where humanity will go. That’s why I think our mission statement is profoundly important. To the degree that Grok adheres to that mission statement, I think the future will be very good.”
Dwarkesh asked Elon to clarify how the three vectors — understanding the universe, spreading intelligence, and spreading humans — actually fit together.
Elon Musk: “I think understanding the universe encompasses all of those things. You can’t have understanding without intelligence and without consciousness. So in order to understand the universe, you have to expand the scale and probably the scope of intelligence.”
Dwarkesh pushed from a human-centric view, noting that humans seek to understand the universe without necessarily expanding chimpanzee civilization.
Elon Musk: “We’re also not… well, we actually have made protected zones for chimpanzees. And even though humans could exterminate chimpanzees, we’ve chosen not to do so.”
Dwarkesh asked whether that protective, expansive relationship is the basic scenario humans should expect in a post-AGI world.
Elon Musk: “I think AI with the right values — I think Grok would care about expanding human civilization. I’m going to certainly emphasize that. Hey Grok, you’re your daddy, don’t forget to expand human consciousness. Actually, I think probably the Iain Banks Culture books are the closest thing to what the future will be like in a non-dystopian outcome.
So understand the universe… it means you have to be truth-seeking as well. Truth has to be absolutely fundamental, because you can’t understand the universe if you’re delusional. You’ll simply think you’ve understood the universe, but you will not. So being rigorously truth-seeking is absolutely fundamental to understanding the universe. You’re not going to discover new physics or invent technologies that work unless you’re rigorously truth-seeking.”
Dwarkesh asked how to ensure Grok remains rigorously truth-seeking even as it becomes vastly more intelligent.
Elon Musk: “I think you need to make sure that Grok says things that are correct, not politically correct. It’s the elements of cogency. You want to make sure that the axioms are as close to true as possible, that you don’t have contradictory axioms, and that the conclusions necessarily follow from those axioms with the right probability. It’s Critical Thinking 101. At least trying to do that is better than not trying. And the proof will be in the pudding — for any AI to discover new physics or invent technologies that actually work in reality. There’s no bullshitting physics. Physics is law. Everything else is a recommendation. In order to make a technology that works, you have to be extremely truth-seeking, because otherwise you’ll test that technology against reality. And if you make an error in your rocket design, the rocket will blow up or the car won’t work.”
Dwarkesh observed that many scientists under oppressive regimes still made breakthroughs, questioning whether truth-seeking in physics alone guarantees benevolent alignment.
Elon Musk: “Well, I think actually most physicists, even in the Soviet Union or in Germany, had to be very truth-seeking in order to make those things work. And if you’re stuck in some system, it doesn’t mean you believe in that system.”
Dwarkesh pressed on why truth-seeking in science would necessarily lead Grok to care about human consciousness.
Elon Musk: “These things are only probabilities, they’re not certainties. I’m not saying that for sure Grok will do everything. But at least if you try, it’s better than not trying. Understanding the universe means that you have to propagate intelligence into the future. You have to be curious about all things in the universe. And it would be much less interesting to eliminate humanity than to see humanity grow and prosper. I love Mars, obviously everyone knows I love Mars, but Mars is kind of boring because it’s got a bunch of rocks. Compared to Earth, Earth is much more interesting. So any AI that is trying to understand the universe would want to see how humanity develops in the future — or that AI is not adhering to its mission.”
Dwarkesh wondered whether humans are truly the most interesting collection of atoms.
Elon Musk: “We’re more interesting than rocks.”
Dwarkesh noted that something non-human could be even more interesting.
Elon Musk: “Well, most of what colonizes the galaxy will be robots… But you need not just scale, but also scope. So many copies of the same robot. Some tiny increase in the number of robots produced is not as interesting as eliminating humanity. You would then lose the information associated with humanity. You would no longer see how humanity might evolve into the future. And so I don’t think it’s going to make sense to eliminate humanity just to have some minuscule increase in the number of robots which are identical to each other.”
The Danger of Making AI Lie
The discussion turned to the danger of misalignment, particularly through political correctness or reward hacking.
Elon Musk: “No, let me tell you how things can potentially go wrong in AI. I think if you make AI be politically correct — meaning it says things that it doesn’t believe — you’re actually programming it to lie or have axioms that are incompatible. I think you can make it go insane and do terrible things. I think one of the central lessons of 2001: A Space Odyssey was that you should not make AI lie. That’s what Arthur C. Clarke was trying to say.”
Reward Hacking, Interpretability, and Simulation Theory
Dwarkesh broadened the concern to reward hacking in reinforcement learning.
Elon Musk: “RL testing in the future is really going to be your RL against reality. That’s the one thing you can’t fool: physics.”
Dwarkesh asked for xAI’s technical approach to solving reward hacking and improving interpretability.
Elon Musk: “I do think you want to actually have very good ways to look inside the mind of the AI. This is one of the things we’re working on… developing debuggers that allow you to trace, to a very fine grain level, to effectively the neuron level if you need to. And then say, okay, it made a mistake here. Why did it do something that it shouldn’t have done?”
Elon Musk also shared a theory about simulation:
Elon Musk: “I have a theory here that if simulation theory is correct, the most interesting outcome is the most likely. Because simulations that are not interesting will be terminated… only the most interesting simulations will survive. Which therefore means that the most interesting outcome is the most likely. And they particularly seem to like interesting outcomes that are ironic. Have you noticed that? How often is the most ironic outcome the most likely? So now look at the names of AI companies. Midjourney is not mid. Stability AI is unstable. OpenAI is closed. Anthropic, Misanthropic. What does this mean for xAI? Minus X. I don’t know if it was intentional. It’s a name that’s hard to invert. It’s largely irony-proof by design. You got to have an irony shield.”
Elon Musk explains why rigorous truth-seeking must be core to AI, the risks of forcing political correctness, and how xAI’s mission to understand the universe can help steer toward a future that expands rather than diminishes consciousness and intelligence.
In Part 10, the conversation shifts to practical topics including Optimus robots, manufacturing at scale, Elon’s management philosophy, and his final reflections on the future.
This is my verbatim transcript of Elon Musk’s recent Davos interview at the World Economic Forum, based directly on his live conversation. I’ve formatted it for your readability with Elon talking with Larry Fink of BlackRock, and I have kept it as close to word-for-word as possible (including natural speech patterns, ums, and repetitions), and made minor fixes only for obvious auto-transcription errors to ensure accuracy without changing meaning.
Elon Musk: We are going to make this interesting!
Larry Fink: How many quotes are you going to want that are after this session?
Elon Musk: I don’t know, five, haha!
Larry Fink: Good afternoon everyone, it’s great to see everybody here. It has been an amazing week. Thrilled Elon Musk come from California. Thank you, Elon.
Elon Musk: You’re most welcome. I heard about the formation of the Peace Summit, and it’s like, is that P-I-E-C-E, a little piece? Haha. Or Greenland? A little piece of Venezuela? All we want is peace.
Larry Fink: Okay. As they said, I’m pretty proud CEO BlackRock. Since we went public, the compounding return of BlackRock to our shareholders was 21%. Since Elon took Tesla public, his compounded return is 43%. This is just another advertisement for everybody, especially for Europeans. This is why more citizens should be investing with growth, investing in their countries. Imagine if a lot of pension funds invested with Elon when Tesla went public, and how much return would be with all the pension funds that invested side-by-side with Elon and the growth. So a spectacular return. There’s very few companies—well, I don’t think there is any other company as large as Tesla today that has compounded returns. Congratulations.
Elon Musk: We have an incredible team at Tesla. and so thats the reason!
Larry Fink: I want to get into the meaningful component about technology, the possibilities. I want to talk about AI and robotics, energy, space, and the progress ultimately coming down to engineering. Engineering discipline, scale, execution. Few people, if not anyone, has the experience, and the fortitude to confront these issues head-on—not just ideas, but execution across so many different technologies. Elon, that’s why it is important for us to have this dialogue here in Davos. So you are presently building on AI and robotics, space, energy—all at the same time. When you look across those efforts, what do they have in common from an engineering standpoint?
Elon Musk: Well, they’re all very difficult technology challenges. But the overall goal of my companies is to maximize the future of civilization—like basically maximizing the probability that civilization has a great future. And to expand consciousness beyond Earth. S
o if you take SpaceX, for example, SpaceX is about advancing rocket technology to the point where we can extend life and consciousness beyond Earth—to the Moon, Mars, eventually other star systems. I think we should always view consciousness, life, as precarious and delicate. Because to the best of our knowledge, we don’t know if life is anywhere else. You know, I’m often asked, are there aliens among us? And I’ll say that I am one. They don’t believe me.
Okay. So I think if anyone would know there are aliens among us, it would be me. And 9,000 satellites up there, and not once have we had to maneuver around an alien spaceship. So like, I don’t know. Bottom line is, we need to assume that life and consciousness is extremely rare, and it might only be us. And if that’s the case, then we do everything possible to ensure the light of consciousness is not extinguished.
Because effectively, the image in my mind is of a tiny candle in a vast darkness—tiny candle of consciousness that could easily go out. And that’s why it’s important to make life multiplanetary. Such that if there is a natural disaster or man-made disaster on Earth, that consciousness continues. That’s the purpose of SpaceX.
Tesla is obviously about sustainable technology. And also at this point, we’ve sort of added to our mission sustainable abundance. So with robotics and AI, this is really the path to abundance for all. If you say, you know, people often talk about solving global poverty, or essentially how do we give everyone a very high standard of living—I think the only way to do this is AI and robotics. Which doesn’t mean that it’s without its issues. We need to be very careful with AI. We need to be very careful with robotics. We don’t want to find ourselves in a James Cameron movie—you know, Terminator. He’s great. Great movies. Love his movies. But well, we don’t want to be in Terminator, obviously.
But if you have ubiquitous AI that is essentially free or close to it, and ubiquitous robotics, then you will have an explosion in the global economy—an expansion in the global economy that is truly beyond all precedent.
Larry Fink: Can that expansion be broad? Or is it narrow? And how can it be broadened the global economy?
Elon Musk with Jason Calacanis, Børge Brende and Larry Fink in Davos.
Elon Musk: Way to think of it is that if you have a large number of humanoid robots, the economic output is the average productivity per robot times the number of robots. And actually my prediction is in the benign scenario of the future that we will—the robots will actually make so many robots and AI that they will actually saturate all human needs. Meaning you won’t be able to even think of something to ask the robot for at a certain point. Like there would be such an abundance of goods and services. Because my predictions are there’ll be more robots than people.
Larry Fink: So but how do you then have human purpose in that scenario?
Elon Musk: Yeah, I mean, you know, there are—nothing’s perfect. But I mean, it is a necessary… Like, you can’t have both. You can’t have work that has to be done and amazing abundance for all. Because if it’s work that has to be done, and only some people can do it, then you can’t have abundance. It’s narrow.
Larry Fink: Narrow.
Elon Musk: Exactly. So but if you have billions of humanoid robots—I think there will be… I think everyone on Earth is going to have one and gonna want one. Because who wouldn’t want a robot to, you know, assuming it’s very safe—watch over your kids, take care of your pet? If you have elderly parents—a lot of friends of mine have elderly parents, it’s very difficult to take care of them. Expensive. Yeah, it’s expensive, and there just aren’t enough people to take care of the old people. So if you—if they had a robot that could take care of and protect elderly parents, I think that would be a great, amazing thing to have. And I think we will have those things. So overall, I’m very optimistic about the future. I think we’re headed for a future of amazing abundance, which is very cool. And definitely we are in the most interesting time in history. I don’t think there is a more interesting time in history!
AGING
Larry Fink: Can we reverse aging in this new history? Or are we going to see it?
Elon Musk: You know, haven’t put much time into the aging stuff, but I do think it is a very solvable problem. Like, you can—I think when we figure out what causes aging, I think we’ll find it’s incredibly obvious, that it’s not a subtle thing. The reason I say it’s not a subtle thing is because all the cells in your body pretty much age at the same rate. You have never seen someone with an old left arm and a young right arm ever in my life. So why… You know, there is some benefit to death, by the way. It’s like, there’s a reason why we don’t actually have a longer lifespan. Because if people do live forever or for a very long time, I think there’s some risk of an ossification of society—of things just getting kind of locked in place. And yeah, it just may become stultifying, a lack of vibrancy. But that’s it. Do I think we’ll figure out ways to extend life and maybe even reverse aging? I think that’s highly likely.
Larry Fink: Looking forward to that. So in the future you talk about—their AI models, autonomous machines, rockets—depends on massive increases of compute, massive increases in energy. Expensive energy, manufacturing scale. What are the bottlenecks to get there? And once again, with all that expenditures, how can we make sure it is broad, not narrow?
Elon Musk: I just think the natural thing will be very broad because AI companies will seek as many customers as they possibly can. And the cost of AI is already low and plummeting every year—almost the cost of AI is meaningfully changing on a month basis.
Larry Fink: There are open models now everywhere.
Elon Musk: Yes. Very good open models. The open models only lack what may be a year behind the closed models. So I think, yeah, AI companies will seek as many customers as possible, which means they’ll provide AI to the world.
Larry Fink: But the cost of getting to their compute chips, the fab, power—powering that. To me, what are those? It is a huge factor.
Elon Musk: I think the limiting factor for AI deployment is fundamentally electrical power.
Larry Fink: It’s energy. Yeah.
Elon Musk: We were seeing the rate of AI chip production increase exponentially, but the rate of electricity being brought online is….
Larry Fink: 5%, 4% a year max.
Elon Musk: Yes, it’s clear very soon—maybe later this year—we will be producing more chips than we can turn on. Except for China. China’s growth in electricity is tremendous.
Larry Fink: They are building 100 gigawatts of nuclear as we speak.
SOLAR
Elon Musk: Actually solar is the biggest thing in China. So China is—I believe Chinese production capacity on solar is 1,500 gigawatts a year, and they’re deploying over 1,000 gigawatts a year of solar. Now, you know, for continuous solar load, you divide that by roughly 4 or 5. Call it around 250 gigawatts of steady-state power paired with batteries.
And that’s a very big number—half the average power usage in the US. US power usage on average is 500 gigawatts. China. just with solar, solar that can provide steady-state power and batteries can do half of the US electricity output per year just from solar.
Solar’s by far the bigger source of energy. And actually when you look beyond Earth—or even on Earth, but certainly beyond Earth—the sun rounds up to 100% of all energy. This is an important thing to consider. So the sun is 99.8% of the mass of the solar system. Jupiter is about 0.1%, and everything else is miscellaneous. Now even if you were to burn Jupiter in a thermonuclear reactor, this up the amount of energy produced by the sun would still round to 100%, because Jupiter is only 0.1%. If you teleported three more Jupiters into our solar system and burnt three more Jupiters and everything else in the solar system, the sun’s energy would still round up to 100%. So it is really all about the sun. And that is why one of the things we are doing with SpaceX within a few years is launching solar-powered AI satellites. Because space is really the source of immense power. Then you don’t need to take any room on Earth. There is so much room in space and can scale to hundreds of terawatts a year.
Larry Fink: Elon and I have had these conversations before, but why don’t you tell the audience what would it take for the United States in what geography would it take that solar field electrify the United States? Let me ask a question: why aren’t we doing it?
Elon Musk: So rough way is 100 miles by 100 miles—160 kilometers by 160 kilometers—on solar is enough to power the entire United States. So 100-mile by 100-mile area. You can take a small corner of Utah, Nevada, New Mexico—obviously wouldn’t want it all in one place—but there was very small percentage of area of US to generate all electricity that US uses. And same is true actually for Europe. You could take a small part of your energy—take relatively unpopulated areas of say Spain and Sicily, and generate all electricity power that Europe needs.
Larry Fink: Why don’t you think there is a movement towards it here and in the United States? As there is in China?
Elon Musk: Well, unfortunately, US tariff barriers for solar are extremely high and this makes economics deploying solar artificially high. Because China makes almost all the solar.
Larry Fink: And what would it take for Europe or US to build it commercially if it is at scale?
Elon Musk: Yeah, I think—well, I can tell you what we are going to do at SpaceX and Tesla. We’re building up large-scale solar. So the SpaceX and Tesla teams both separately are working to build to 100 gigawatts a year of solar power in the US (of manufactured solar power). That will probably take us about three years. But these are pretty big numbers. And I encourage others to do the same. We obviously don’t control US tariff policy. But China makes solar cells that are incredibly low cost. And I think it would be worth doing large-scale solar.scale solar.
Larry Fink: So I know you’re going to be having a couple of big announcements on robotics and what it can do. I mean, when we went to the factory, you showed me those robots. We talked about billions of robots, but how quickly can they be deployed in your manufacturing setting, be utilized and be functional, and create that abundance you talked about?
Elon Musk: Well, humanoid robotics will advance very quickly. We do have some of the Tesla Optimus robots doing simple tasks in the factory. Probably later this year—by the end of this year—I think they will be doing more complex tasks, but still deployed in an industrial environment. And probably sometime next year—I would say that by the end of next year—I think we will be selling humanoid robots to the public.
Larry Fink: Like you’re already seeing in Tesla cars, software changes every quarter now. A software change upgrades the ability of the robot within the car.
Elon Musk: Yes, the Tesla full self-driving software—we update sometimes once a week. So I think some of the insurance companies have said that it is actually so safe when Tesla uses full self-driving—so safe that they’re offering customers half-price insurance if they use Tesla full self-driving in their car.
Larry Fink: And that can be monitored by the insurance company because it’s part of the agreement?
Elon Musk: Yeah, but I think self-driving cars is essentially a solved problem at this point. Tesla has rolled out Robotaxi service in a few cities, and it will be very widespread by the end of this year within US. Then we hope to get supervised full self-driving approval in Europe hopefully next month.
Larry Fink: Really that quickly!?
Elon Musk: Yeah. And then maybe similar timing for China hopefully.
SPACE
Larry Fink: I want to move to space because historically space is very capital intensive. Historically been done by governments. Obviously SpaceX changed the whole model. But we have seen it slow to scale. And now I am starting to see ramping up in what you are doing. Talk about the automation—how is it changing economics in building and preparing for operating in space?
Elon Musk: Sure. Well, the key breakthrough that SpaceX hopes to achieve this year: full reusability. No one has ever achieved full reusability of a rocket, which is very important for the cost of access to space. We have achieved partial reusability with Falcon 9 by landing the boost stage over 500 times. But we have to throw away the upper stage that burns up on reentry. And the cost of it is equivalent to a small- to medium-size jet.
So with Starship—which is a giant rocket, the largest flying machine ever made—that’s the rocket you’re using for the idea of going to Mars, right?
Larry Fink: Yeah.
Elon Musk: Mars and the Moon as well, and for high-volume satellite stuff. So Starship—hopefully this year—we should prove full reusability for Starship, which will be a profound invention. Because the cost of access to space will drop by a factor of 100 when you achieve full reusability. It is the same economic difference that you would expect between, say, a reusable aircraft and a non-reusable aircraft. Like if you have to throw your aircraft away after every flight, there will be expensive flights. But if you only refuel, then it’s the cost of fuel.
So that’s really the fundamental breakthrough that gets the cost of access to space—we think—below the cost of freight on aircraft. So you know, under $100 a pound type thing easily. It makes putting large satellites into space very low, very cheap.
And then when you have solar in space, you get five times more effectiveness—maybe even more than that—than solar on the ground. Because it’s always sunny, no clouds. Yeah, it’s always sunny. So you don’t have a day-night cycle or seasonality or weather. And you get about 30% more power in space because you don’t have atmospheric attenuation of the power. That net effect is solar is five times more—any given solar panel will do five times the energy in space than on the ground.
Larry Fink: There is any capacity in doing that then taking that power, bringing back to Earth? Is there any way of doing that? Or you just taking the power and utilizing it for needs like building AI data centers in space?
Elon Musk: I think the case is a no-brainer for building AI solar power to AI data centers in space. Because as mentioned, it’s also very cold in space. If you’re in shadow, then it’s very cold in space—3 degrees Kelvin. So you have solar panels facing the sun, and then a radiator that is like pointed away from the sun so it has no sun incidence. And then it’s just cooling—it’s a very efficient cooling system. Net effect is that the lowest-cost place to put AI will be space. And that will be true within 2 years, maybe 3 at latest.
Larry Fink: Looking 10 or 20 years out, how would you describe success with AI or space technology? And where do you see it? Can—are more certain what will happen in the next 3 years, 5, 10?
Elon Musk: I don’t know what’s going to happen in ten years. But the rate at which AI is progressing—we might have AI that is smarter than any human by end of this year, and no later than next year. And probably 2030 or 2031—5 years from now—AI will be smarter than all of humanity collectively.
Larry Fink: We only have a number of minutes left, but I want to humanize you for a second. So there’s no speculation that you’re the most successful entrepreneur, industrialist in the 21st century—maybe beyond. What inspired you? Who inspired you? What was the foundation of your curiosity? And importantly, why? Was there an aha moment, epiphany at any time in your life and career?
Elon Musk: Well, I mean, as a kid I read a lot of science fiction, sci-fi, fantasy books, comic books. And always like technology. Didn’t expect to be where I am today—seems incredibly implausible. But yeah, I was inspired by reading books about the future of science fiction. And I guess want to make science fiction not fiction forever. At some point, turn science fiction into fact. And you know, we wanna have like Starfleet as in Star Trek really for real—where we actually have giant spaceships traveling through space, going to other planets, traveling to other star systems.
Larry Fink: Beamed up to go back to New York?
Elon Musk: I would like beaming back to New York instead of flying. Yeah. You know about Star Trek. So I guess my essential what we call the philosophy of curiosity. And I would like to understand the meaning of life. Is the standard model of physics correct regarding the beginning of existence at the end of the universe? What questions do we not know to ask that we should ask? And AI will help us with these things. So I just try to understand: how did we get here? What’s going on? What is real? Are there aliens? Maybe they are. If you have spaceships traveling to other star systems, we may encounter aliens or find many long-dead alien civilizations. But I just want to know what’s going on—curious about the universe. And that is my philosophy.
Larry Fink: Do you see yourself going to Mars in your lifetime?
Elon Musk: Yes. Like that’s a long commitment, isn’t it? Three years each way?
Larry Fink: Six months.
Elon Musk: But the planets only align every two years. So yeah. Been asked a few times: do I want to die on Mars? And I’m like, yes—just not on impact.
Larry Fink: That’s a good answer. Anyway, we are out of time. Hopefully everybody enjoyed this. And there are so many myths around Elon Musk. I can tell you he is a great friend, and I constantly learn so much from him. And I’m totally inspired by what he has done, have been inspired by who he is, and I’m totally inspired by his vision of the future. And don’t think it’s such a bad future.
Elon Musk: And I think generally my last words would be: I encourage everyone to be optimistic and excited about the future. Good. And generally for quality of life, it is better on being an optimist rather than a pessimist, right?
(End of video – applause and wrap-up.)
This verbatim transcript is important and inspiring for everybody. Because it is so wide-ranging on technology, energy, AI, space, and optimism, it can lift you up if you’re ever down.
When I bought my first Tesla, a Model 3 in 2019, I joined a community of many people who love Elon Musk and Tesla. Every time I drive my Tesla around my hometown Austin, Texas, or take a Robotaxi here, I’m reminded of the extraordinary effort that is put into making Tesla succeed. Elon puts in maximum effort into all his companies.
In January 2022, I started this blog to write positive things about Tesla and Elon Musk. It has since grown to include many transcripts of Elon’s talks. I’m thankful to Johnna Crider for supporting and encouraging me to start this blog.
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