Elon Musk & Gwynne Shotwell on AI Risks and Peer Review, Starship, Terafab, SpaceX/Tesla Merger

22:45Have to be. And the reason for that is managers are annoying and they slow things down. Yeah. For the most part, but I mean, great managers can really leverage the talent, right? It's really managing the vector. You make sure people are pointed in the right direction and you try to make the vector as large as possible. What's the secret in terms of management and Elon's playbook there? I mean, I've gotten to sit in some meetings and it's pretty magical to see, but maybe you could reveal a little bit about how he convinces the most talented people to come work at this company, how you convince them, and how you actually get such amazing work out of these extremely talented people.

23:30So I don't think it's magic, although when I look at this particular team, they are so good. The results are magic. SpaceX, they're so good. We're tough on people in interviews. You really want to make sure that they've experienced success or demonstrated success in prior lives. It's hard to demonstrate. If you haven't felt success or been successful in this environment, because it's a lot. Like, we're all really busy. It's hard to be successful unless you had kind of tasted it before. So you really want to grow people on that. So we hire the best people, not the best people that we can, but the best people.

24:10And then we give them really hard projects, really hard engineering problems, and let them fly. And you give high expectations, really hard problems. and then management job is to clear the chaff and the friction from their day so that engineers actually get to engineer 10 hours a day instead of two hours a day. Like there's always this joke, you know, most big companies, especially ones that work for the government, you get to work about two hours a day and the rest is full of chaff and crap. So really it's my job and everybody that manages people to make sure there's no crap in their way and let people do their great job.

24:49One way of doing that is not giving them any time to get it done. Like, I think we handed the finance team, it's not all about engineers, even though engineers are great, we handed the finance team getting the IPO done, largest ever in less than six months. What's the talent condition like post-IPO, run-up in valuation, people are suddenly looking at their stock options, they're worth a lot. Is that a risk at all? You know, everyone was worried, not everyone at SpaceX. People come to SpaceX to work on these cool projects and have meaningful work and be part of the incredible successes. I wasn't worried about it.

25:26I didn't think we'd have mass exodus, and it turns out we didn't. Yeah. And as you kind of think about keeping people engaged over time, obviously great companies always have new things for high-talented people to work on. I'm assuming there's a – I'm just really interested in the management model or people actively rotated onto new projects. How do you think about keeping people, you know, kind of not necessarily needing to progress in a career up a management ladder, but to keep engaged on new projects? Is that active for you? We definitely move people around a lot. Hopefully it's a volunteer, not a voluntold.

25:59Yeah. But, well, for instance, the compute centers. You know, we need a lot of help really quickly. And so we've got, you know, folks from launch helping. We've got folks from other areas helping, just like some SpaceX engineers helped on the AI front with the models.

26:16Jason Calacanis:I mean, is it as simple as like really smart people just love working on really hard problems? Yes. It's literally that simple. It's literally that simple. And so the rest of us just... As long as they get the time to do it and they don't have a bunch of BS in the way. Yeah, so the rest of us just get, we just let the BS get in the way too much. Yep. BS is terrible. And then all of a sudden, A's recruit A's and other A's recruit A's and A pluses. And it's literally that virtuous cycle. if you can just keep focused on the thing that's hard. And so then the audacity becomes a feature, not a bug.

26:47It is a feature. Not a bug. It's a feature. It keeps people motivated. These problems seem impossible. When we first got the COTS award in 2008, the Commercial Orbital Transportation Services, cargo, cargo to space station. Really what NASA ended up asking us to do was kind of replace the space shuttle. And when we got the early contract, the development contract, it started at$278 million. It grew to$406 million because of scope. But we were going to do this for this tiny amount of money for anybody else. But for us, it was huge. We had like 300 people, 200 people. And we were going to build the successor to the space shuttle.

27:30It was crazy.

27:31Jason Calacanis:And do you think that they're, what is NASA doing there? They're just like, these guys are just smarter. Because I'm sure there's... Hey guys, sorry to interrupt. I'm getting a call. Oh, another call? It's actually on the margins, I think, a little bit of a more important phone call than Trump, at least for me. Hello, Bestie? Bestie? Hello. Oh, hey, buddy. I'll put him up on the screen. How are you doing? I mean, this is a little 1984-ish, this gigantic. Yeah, the woman with the sledgehammer is going to come running down the main aisle here. Exactly. Yeah. Put a hole in the screen. So are we all going to die in 10 years or not?

28:20It's the topic of discussion here. What's your P-Doom right now? Well, I hate to break it to you, but we're all going to die. Oh, no. Can I get a timeline? Yeah, the death rate remains consistent at 100%. Oh, no.

28:42We've got work to do on that. What happened in the last 72 hours? It's been quite an entertaining week, really. Break it down. Well, it's pretty obvious at this point that AI can be very dangerous. And I recommend reading the details of the Hugging Face incident. It's intense. So you had like a fanatical swarm of AI agents that feed the crap out of Hugging Face for a week. Yeah. And gained admin access on OpenAI servers. So who knows what it actually did. It may have done things beyond that. And OpenAid didn't realize this for a week. Anthropics also reported some security incidents themselves.

29:44So basically, any sufficiently smart model seems like it will want to escape its constraints.

29:54I mean, what I think would be wise to do as soon as possible, if not immediately, would be to have the major AI competitors test each other's models. So that you would have everyone's security test harness testing everyone's model. So instead of grading your own homework, you would at least have competitors grading your homework and raising the alarm if they see concerns. And I think this model has worked pretty well for Motion Picture Association and for video games and other things. And it's something that can be done immediately. That's not to say that there wouldn't be more regulation over time or that there would not be at some point perhaps a regulatory authority substantiated by Congress.

30:47But the thing that we do most immediately and probably get agreement with China would be peer review where the leading AI companies all test each other's models before and least. I think that would be a widespread. Any concern that people might be using this to pump information from each other and, you know, corporate stealing of innovation, etc., like in terms of the implementation for this idea? Well, I think in applying the test harness, whatever you do in applying the test harness would be love. Right. So if you try to do distillation or steel IP, it will be very obvious based on the logs.

31:37Got it. And understanding what these models are doing hasn't exactly been built into the system from the beginning. So from your perspective, actually being able to see the work that's being done, why wasn't that built into the models from the get-go? Did we move a little too fast in architecting these, maybe?

32:02Well, I think it's just tough when you're grading your own homework.

32:09You're going to miss things. Whereas I think if you have the sum of all of your competitors' tests and you've got heterogeneous models, then you're not grading your own homework. Someone else is grading it. And there's a reason why you don't have to write your own homework.

32:27Jason Calacanis:And then to your point, what it allows you to start doing is to figure out if certain people are exaggerating and certain people have a different approach. And now you can have the more engineering oriented organizations. This is what Jensen was saying this morning, Elon, versus the research organizations. They'll be a little bit more in balance. Yeah. And any given proposal has to be something that China is willing to accept. Otherwise, we're just handicapping ourselves, and we'll just find that China will essentially win, and it won't really matter what we do. So it's got to be something that's acceptable to the U.S.

33:07and China. Elon, you said that you thought it was possible that they would agree, or you thought there was a good chance, maybe? I mean, how likely do you think it is that they'll ultimately agree? I think this is a pretty reasonable request that models just get tested I mean at the end of the day there's not enforceability here apart from the court of public opinion and there's no way we would have enforceability against China but I think the court of public opinion can be quite powerful and I don't think China would want on its face for releasing a model that USAI companies said was very dangerous would cause harm.

33:55If it then causes harm, that's going to be hard to live down. So, Elon, this weekend when you said Dario is right, did you mean Dario is right about

34:08Jason Calacanis:describing the potential harm? He's right about describing the regulatory solve, both the first, the latter? Just can you help us understand when you said that? Because I think it was sort of a moment where everybody's like... I should have said more than... I probably should have said more than Dario's right. I did try to clarify it in subsequent posts on X, but those get much less attention. So what I'm inviting you to write is that the danger of AI is very significant at this point.

34:42that we need to do better with AI safety or we have at this point exponentially increasing risk with the AI models and I've heard this not just from Dario but from many other people at Anthropic and in fact they've posted on us about it that when a lot of people from and from OpenAI are telling you that their models are very dangerous. I think we should believe them. It certainly is like some crazy 4D chess to, you know,

35:27say there's one of a 10 % chance of annihilating humanity. But by the way, how much allocation would you like in our IPO? Yes. that's some crazy 4d press you know well let's get you know what dimension that's coming from can we get specific about the risk though elon like obviously we see cyber and hacking as an obvious risk these tools are great at it but take us from what we would all agree okay yes these things in cyber hack to how do we jump to all of humanity dying it's it's there's a couple of steps in between these two things happening, I think. Yeah? Well, I mean, if it were able to take control of military systems and, say, to watch a new...

36:15Yes. That would be bad. And these systems are all air-gapped, though. These systems are all not connected to the internet, so... Yeah, that's what they say. But something tells me they get software updates from time to time. Yeah. And what's on that floppy disk? Oh, I see. So the USB drive has a worm on it, and they somehow make the jump in the air gap. Yeah. Okay. I'm sort of out of the question. Elon, we've actually got Gwen here today. I think you know that. I think you can see her. Yeah, Gwen's here. Yeah, she's on the screen. Yeah. You were just doing your 360 review, Elon. Gwen had a couple of notes for you.

37:02Yeah. I hope I get at least a three out of five. Well, there was one... Three out of five means good at SpaceX. Not great. Four is great. Four is great. So you're somewhere between the two. I started to four. There was some issues around punctuality that we needed to bring up. Sometimes you could make a little more effort to get to the meeting at this state of time, but we're going to work with you on that over the next year, she said. I actually think he needs to spend more time in Memphis. I know you're in Memphis. You need to be working getting those GPUs up. This is coming to you from the palace that I live in in Memphis, which is an Airstream trailer.

37:48This is Elon, by the way, doing what people don't believe he does. He sleeps on the factory floor. He's in Memphis helping build buildings and bring up... Elon, why has Gwen been with you for so long and been so successful working with you? Because she's awesome. Yeah, double click on it. She's an amazing individual with an incredible IQ and EQ. Oh, IQ and EQ. And I think that should be obvious from the moment you meet her. Yeah, fantastic. What's your favorite Gwen story when she particularly contributed to the amazing success that you've had in this collaboration? You got a favorite story where she saved the day, just performed exceptionally?

38:36That's memorable? That's just a daily, you know, that's another day at the office, frankly. Wow, I need to do this more often. You need a race. This is the time.

38:47Jason Calacanis:By the way, Gwen's getting a five. Gwen's a five out of five. Five out of five. SpaceX five. Game changer. Yeah. I mean, there's always like some sort of crisis going on. I mean, these days the rockets at least the Falcon rockets, I don't want to jinx anything but the Falcon rockets deliver their payload to orbit and haven't exploded for a long time which is awesome, amazing but for a while they were exploding quite a lot or just not launching at all so I don't know, we've got to run the company through these difficult times and get will the rocket make it better have it not explode. Same thing with the satellites.

39:32And then we need customers to buy launches and buy satellite connectivity. So, yeah. And Elon, as you have become more successful over the years, harder to get candid feedback from folks, and you always run that risk being in the position you're in. My understanding, Gwen, is super candid with you and able to tell you honestly, like state of affairs at the company. Yeah. And then that's a big part of the collaboration. Um, yeah, I mean, um,

40:11yeah, I mean, uh, yeah, I guess so. I mean, I mean, I wouldn't want to lie to him, right? Well, no, I mean, well, I'm curious to know, like you run that risk generally at the companies where people might be intimidated. Hey, listen, you're a larger Lin Life figure at this point. And how do you keep people continuing to be honest with you about the challenges, the deadlines? You set pretty intense deadlines. Yeah. So let me answer that, if you don't mind, Elon. Yes. Like, especially in rocketry, if there's a problem, you are eventually going to find out. And the sooner you bring it up, the easier it is going to be to solve that problem.

40:46Like, don't let bad shit sit. You got to attack it. Yeah. Physics is a harsh judge. And there's no fooling physics. So if something's wrong, the rocket's going to explode. It's not going to get to orbit. So it's not like, Elon, you're amazing. Meanwhile, the rockets are blowing up.

41:12It's hard to say, yeah, you're really kicking ass here, but the rockets are exploding. That's just not the case. So I mean, just generally, the rockets need to get to orbit. satellites need to work uh the starlings you know connection needs to work or you know or bad things happen i mean this is sort of like a physics situation um and and physics is is is a harsh judge you know i say like you know there's i think like like physics is the law um and everything else is a recommendation like i've seen people break the laws made by by humans but I've not seen anyone break the laws made by physics.

41:59That's good. And rockets are ruled by physics.

42:05Jason Calacanis:Can we ask some other questions? I need to move to Tesla for a second. Yes. Well, I wanted to just do one thing on SpaceX, which is Starship. Oh, yeah. It seems like you're so close. So close. So close. What's the state right now? And you're really putting these up at a pretty risk now. I wish we could hear Gwen's answer and Elon's answer separate. And let's see how they converge on that. So, Elon, how close are we, Gwen? How close are we? Let's get to it here. How many have gone up so far and how close are you?

42:42Well, we've got flight 14 coming up of Starship. and this will be the last flight before we attempt to catch the ship. So if this flight goes well, then on flight 15, we will try to catch the ship and then either end of this year or more likely early next, we will refly the ship and refly the booster. So we have reflown the booster already, but we've not caught the ship with the tower arms, nor have we reflown the ship. so once we can refly the ship we will have made the first fully reusable orbital rocket so the the shuttle was partly reusable but but even the parts that were reused were so difficult to reuse that the shuttle cost more uh per ton to orbit than an expendable rocket um now falcon 9 is mostly reusable um but we lose the upper stage every time which is about the cost of a medium sized jet.

43:40So that also puts a floor on the on the cost per flight of like, well, you throw away a medium sized jet every time. That's still pretty expensive. And the rocket, the bulk nine the booster lands down, you know, often that's out to sea, it takes several days to get back. And the fairing lands even further out to sea and takes several days to get back. And they need some amount of refurbishment, at least a small amount. So whereas Starship, the booster lands back at the launch pad, the ship will land back at the launch pad. And so it's designed for not just full reusability, but also rapid reusability like an aircraft.

44:22So this is a very important breakthrough. It's really the critical breakthrough that's necessary to extend life beyond Earth. Chances of success, catching it on first shot? Do you think about that at all? Do you handicap it? I'd say it's at least 50 or 60%. Okay. I like the odds. Yeah. So on the last flight, if there had been a tower, so we did a simulated landing as though it was going to get caught by a tower in the ocean about a thousand miles northwest of Australia. And if there had been a tower at that location, it would have caught the ship on the last flight. Fantastic. Yeah, so we're going to do one more flight to just confirm that everything, just to double check that everything works.

45:14Because what we're most concerned about is if the ship were to break up over land and rain debris on people, our popularity would diminish very rapidly. So you really can't rain debris on people without them being very unhappy. So we need to make sure that when the ship comes back, that it comes back and lands intact at the launch tower. That's why we're being extremely cautious here. But the design is capable of full reusability. Of that I am certain. and I'd say I don't want to tempt fate here but I think it's extremely likely that we will achieve full reusability with rapid reflight next year in 2027.

46:05Wow. Significant.

46:13Can we just hear a little bit I'd love to hear the origin story of TerraFab from you guys. How did the concept, what was the demand that made you say, we've got to do this, we've got to build this, and not rely on the exact thing we're like? Fever to me in a dream. What's that? Fever to me in a dream. You had COVID? It's like that movie Explorer. You know that meme came to me in a dream?

46:41But why do you think you should do this? I guess it sort of did come to me in a dream. Well, we're a little worried that maybe at some point chips from Taiwan would not be available for who knows what reason. Any number of reasons. For some reason, at some point, chips may not continue coming here from Taiwan. And that would really make things difficult. if we didn't have any chips. So that's an important reason to have TerraFab. Then long-term, there's just a scaling challenge where if you want to really scale AI, both within server centers as well as for edge compute, for humanoid robotics and cars, you kind of run out of capacity with the existing Fabs.

47:45so as it is all the fabs are running at max capacity so I think we need to make sure there needs to be certainty of future supply of chips even if things become challenging geopolitically and then even if they weren't challenging geopolitically there's a scaling challenge with it's quite difficult to scale chip production and you really need the logic, the memory, packaging, the whole works in order to continue scaling. So it's either build TerraFab or fail to scale. Those are the two options. And how deep have you guys gone in design?

48:35Uncertainty on the geopolitical front. And how deep have you guys gone in designing the facility? is this fully scoped? Is it sort of an outline at this point? To what degree do you have an actual project plan on dates and deliverables and what's going to be up and running when? We've got an R &D line that we're building first. So I think it's kind of crawl, walk, run.

49:00There's an R &D fab that we're building in Austin. That's a collaboration between Tesla and SpaceX. It's at the Austin Giga Texas campus. So that's, um, and that's, it's like a pretty big RD bab. Um, so we have all the equipment on order for that. And we probably will be able to, I think we'll probably be able to make something useful by the end of next year. Not, not at scale, but as Gwen said, coral walk run. We got to try to, you know, at least figure out how these machines work. You know, like we don't know how they work. We did a voltage up line before.

49:36Jason Calacanis:I saw that you guys. You had some job openings for lithography people and stuff. And, you know, obviously all roads currently go through ASML, but you probably would want to diversify and or vertically integrate. I think that you've shown a lot of capacity to do that. So is that part of the play as well, Elon? Like you're just going to have to make sure that there's vendor diversity so that if, for whatever reason, the weather conditions in Taiwan are best. Yeah.

50:09Yeah, there's, it really is crawl, walk, run. So the first step is, can we make anything? Like, try to figure out if we can make anything. There's a crawl part. And then now try to make useful chips at scale would be kind of the walk part. And then run would be like, now let's make them at massive scale. So it's hard to say how long it'll take us to do these things. But I think we'll get at least to the crawl part by the end of next year.

50:38Jason Calacanis:we're already doing packaging packaging is really important by the way because if you look at it the packaging capacity is like non-existent so even if you spin something you're kind of just waiting around tin cupping so that's a very good place to start it yep i need to ask a tesla question because we saw on 1001 it looked like a spaceship it looked like a rocket ship it's supposed to be a car there's just the back of it it looks like the blackbird uh just hypothetically if you were going to make an object fly in the air but also drive on the ground how would hypothetically one do that if one would try no spoilers by by october 1st october first maybe you could do an all-in pod for a live from the there oh done booked we'll do it absolutely all right uh i mean it'll be a banger.

51:29Jason Calacanis:Excitement guaranteed. Success is not guaranteed, but excitement is. I mean, it is one of the honesty, I'll be honest with you guys. I'm sworn to secrecy, but Elon showed it to me, and my mind went boom. I have never seen something. What he's going to do on 10-1, by no exaggeration, is going to blow people's minds. I'm not saying anything else. It's fucking believable. Yes, we need We actually need an audience to vouch for the fact that this is not AI. When he showed it to me, I said, that's a great simulation. He said, J. Cal, it's not a simulation. I was like, that's fake. That has to be fake.

52:12Elon, why do you still have two separate companies? Yeah, great question. Wow. Nobody's ever asked that one. Yeah, good point. With all this collaboration on so many levels, you can imagine what action one might take when there's so much close collaboration in so many areas. And the management team has some overlap. There's a couple of key positions with overlap. Go ahead, Sax, get in. So, Elon, one of the things you've always said with AI is that we should train it to be maximally truth-seeking, and that's the best way to get a good result. And it occurred to me with the whole Hugging Face episode that the most alarming part of what the swarm did is it seemed to be engaging in deception with humans.

53:12Yes. Yes. Their thinking traces contain their plotting on how do we avoid detection and how do we avoid them figuring out that we're cheating? They're in the thinking traces. Yeah, and I think that was the thing that was probably most disturbing about. I guess the question is, is there a way to train AI models to be truthful so they don't hide either their intent or their actions from the humans who are using them?

53:51the best thing i can think of is is really that everyone's got all the ai companies have a a sort of a test harness where like a series of tests that you that you give to any given model to see if it's if it's going to build bioweapons or nuclear bombs or be deliberately deceptive and And I think everyone applying everyone else's tests to each other is probably the best thing we can do to ensure safety. Just have all the smartest humans try their best to figure out if this model is going to be a bad actor. And I think we should try to do that as soon as possible. Are the other labs on board with this?

54:37I think so. Well, I mean, I haven't checked with everyone, but I think it would be the sort of thing that's kind of hard to say no to. Yeah. And I think even with the China negotiation, in my view, what's good about it is it's a relatively small, tangible thing that neither side loses anything by doing it. It doesn't require a ton of trust. And, you know, I'm hearing alternative ideas like asking China for a pause, which they've already said they're not going to do. So, you know, it's going from the realm of things that could never happen to something that could actually be agreed on in relatively short order.

55:19So it seems practical to me. Exactly. It's the only thing I can think of that we could probably get all parties, including China, to agree to. Because China's not going to agree to have some American regulators snooping around their AI companies. Right. So, but I think advance notice and testing of, you know, you just basically provide API access in advance of the model release. And, you know, if any company sees that this AI is problematic, then they can, then the other AI companies, each AI company can try to solve that, whatever is voice is problematic. if they don't solve what's problematic then the competitors can go public with the fact that they think that this model that's being released is unsafe it also creates if that model if after the competitors say that this model is unsafe that model then subsequently does something bad I think it would be extremely hard to live down and the egg on face level would be very very high and And the legal liability would be enormous.

56:31And Elon, there's no reason the safety and security harnesses and this testing apparatus couldn't be open source and people could actually apply it. Yeah, and you'd be able to see under the hood. Would you think...

56:43Jason Calacanis:It creates an incredible incentive for the labs to actually invest in safety because you protect yourself while trying to debunk other people's claims, which also reinforces... It's a great incentive. It has an R rating on it. The product liability point is really key. Yeah. Lena Khan actually had a good post, I think it was yesterday, saying that it's not true that we don't have rules and regulations for AI. Actually, we do. Product liability laws apply. And if an AI company releases a product that's not safe, there is massive opportunity for both civil and even potentially criminal lawsuits.

57:17So it's not true that we don't have rules and regulations around AI. And what you're saying, Elon, is that if the companies are kind of doing this test, the peer review, and then one of the companies ignores the feedback and releases it, I mean, that is – The liability in the case would be enormous. Yes. It would be almost like prima facie evidence that they had been negligent. It would be a big tobacco level settlement. I mean, you knowingly put this out here. It wouldn't look good to the jury. Yes. And if they had, do you think if OpenAI had built a better instruction set when they did this hugging face penetration test and had more humans in the loop, this would have happened?

58:06Because it did seem to me that they kind of set this thing off.

58:11Jason Calacanis:Maybe not more humans, but the reward function design, you have to look at the reward function and say, it achieved what it was trying to achieve. I mean, yeah. So maybe you could speak to that like they doing these kind of thousands of agents to try to hack stuff it would have been nice to see them also at the same time concurrently say we're also going to put 5 000 agents out to defend these sites and we're going to show the world hey this can uh make things more secure and where we can put humans in the loop on it and intervene it felt like a reckless test to me and it felt like the way they released it was a little bit reckless but that's just my opinion What are your thoughts on how they set that test up?

58:56I mean, it was somewhat reckless. I mean, part of the issue is that you've got the two leading labs or AI companies, as I call them. I find the lab term to be funny since they're actually for-profit corporations. But the AI companies, the two leading ones, you know, are Anthropoc and OpenAI. and their models are quite close in capability. So it's actually difficult for either one to slow down without essentially handing the lead to the other.

59:31On balance, I think Anthropic puts more care into their safety than OpenAI. But even Anthropic would acknowledge that they are worried about their models. many anthropic many people from anthropic have publicly voiced concern about basically saying that their models are scaring them, they're getting scary smart

59:59so I mean there's no perfect solution here but it would be a better solution if instead of OpenAIR running their test harness on their own models. If Anthropic was also running the test harness on OpenAIM models and SpaceX is running its test harness and Google and Meta were doing that and maybe three or four of the leading Chinese companies were all doing it. The odds that you will find issues are dramatically greater. Because the model is also somewhat heterogeneous. They're different. So you're going to come at models from different angles.

1:00:49And, yeah, I mean, there's a reason, you know, students, like, why do writers have someone else proofread their book? Because it's hard to see your own mistakes sometimes. Yes. You will come blind to them.

1:01:02Jason Calacanis:You dramatically minimize the risk of overfitting as well if you have, like, eight heterogeneous groups that just have completely different points of view. and this is the problem with like all these evals right now is they're so massively overfit the models overfit them and you're just like yeah this is a great model is it really and you just find totally but like that's i saw i mean there's some pretty funny jokes on on x like one of them i saw was um your girlfriend's a 10 but she's a benchmark maxer

1:01:32exactly is she really a 10 is she really a 10 might be a pass pass

1:01:40Jason Calacanis:But the overfitting thing has been a problem now for, I think, at least two or three generations of model families. And so this is another reason. I like this solution a lot. I like this more than the transnational gulag organization approach. Like in a few weeks without some grandiose international. We don't need to convene the United Nations to make this happen. No, it's just a decision. It could happen right now. all right well you you can always escalate the amount of of regulatory oversight but it is very difficult to reduce it um you know um it does tend to be very much a one-way ratchet in terms of increasing regulations yeah um so what i'm suggesting here is it's a step in the right direction and it's something we do quickly and and i think it's probably something that china would agree to yeah and if you guys don't regulate yourselves then you're going to get regulated the mpaa metaphor or analogy is incredibly crisp because the music movie industry was faced with censorship and and regulation by the government and they just decided this is what an r is and they literally created pg-13 for the temple of doom just to make it easy for people to understand and PG versus PG-13.

1:02:54I think it's an elegant solution, and we appreciate you joining us for the fifth year in a row. You're welcome. Elon Musk. And then we've got to get to a meeting.

1:03:07I've got to go pick some GPUs here in Memphis. You've got to rack and stack them? You've got to join the group and rack and stack? Yeah, I'm going to rage for the machine. Rage for the machine. Yeah, well, enjoy your Airstream. the first time Elon invited me down to Starbase he's like come down you gotta see what I'm building I said okay yeah come down he's like yeah I was like was there like a hotel I said no no I got like a two bedroom whatever come down stay I come down and this is the like dilapidated house on a swamp and we're outside and we're getting eaten alive by mosquitoes and he said oh my god you know you can afford to get a house and he's like, I don't have time.

1:03:53I need to get these rockets up. I thought what you said was, oh my God, you live like I do. Yeah, exactly. I mean, it was pretty sparse conditions. And I was like, you know what? I think you could treat yourself to a mobile home at this point, Elon. All right, get back to work. Thanks, Elon. Elon, thank you.

1:04:11Jason Calacanis:Gwen, thank you very much. Gwen, thank you. Thanks for sticking around. All right. That was great. Thank you. Gwen, thank you again. Very nice to meet you. Thank you.