Transcript for In conversation with Sam Altman

We take our time on releases of major. new models and I don't think we, I think it will be great when we do it and I think we'll be thoughtful about how we do it. Like we may release it in a different way than we've released previous models. Also, I don't even know if we'll call it GPT-5. What I, what I will say is, you know, a lot of people have noticed how much better GPT-4 has gotten since we've released it and particularly over the last few months, I think I think that's like a better hint of what the world looks like, where it's not that like 1, 2, 3, 4, 5, 6, 7, but you just use an AI system and the whole system just gets better and better, fairly continuously. I think that's like both a better technological direction. I think that's like easier for society to adapt to. But I assume that's where we'll head.

Well, I mean, one one one one thing that you could imagine is this just that you keep training right a model that that would seem like a reasonable thing to me.

Yeah. Still only available to the page users. But one of the things that we really want to do is figure out how to make more advanced technology available to free users too. I think that's a super important part of our mission. And this idea that we build AI tools and make them super widely available. Free or, you know, not that expensive, whatever it is, so that people can use them to go kind of invent the future rather than the magic AGI in the sky inventing the future and showing it down upon us. That seems like a much better path. It seems like more inspiring path. I also think it's where things are actually heading. It makes me sad that we have not figured out how to make GPT4 level technology available to free users at something we really want to do.

So on the first part of your question, speed and cost, those are hugely important to us. And I don't want to give a timeline on when we can bring them down a lot because research is hard, but I am confident we'll be able to. We want to like cut the latency super dramatically. We want to cut the cost really, really dramatically. And I believe that will happen. We're still so early in the development of the science and understanding how this works. Plus we have all the engineering tailwinds. So I don't know like when we get to intelligence to achieve the meter and so fast that it feels instantaneous to us and everything else. I do believe we can get there for a pretty high level of intelligence and it's important to us. It's clearly important to users and it'll unlock a lot of stuff. On the open source, closed source thing, I think there's great roles for both. You know, we've opened source some stuff. We'll open source more stuff in the future. But really, like our mission is to build towards AGI and to figure out how to broadly distribute its benefits. We have a strategy for that. It seems to be resonating with a lot of people. It obviously isn't for everyone. And there's like a big ecosystem. And there will also be open source models and people who build that way. One area that I'm particularly interested personally and open source for is I want an open source model that is as good as it can be that runs on my phone. And that I think is going to, you know, the world doesn't quite have the technology for a good version of that yet, but that seems like a really important thing to go do at some point.

But you really, I don't know if we will or someone will. But some of the world, uh, long with three.

I'm not sure if that one is like I haven't played with it. I don't know if it's like good enough to kind of do the thing. I'm thinking about here.

Well, what we're trying to do is not make this sort of smartest set of weights that we can. But what we're trying to make is like this useful intelligence layer for people to use. And a model is part of that. I think we will stay pretty far ahead of, I hope, say pretty far ahead of the rest of the world on that. But there's a lot of other work around the whole system that's not just that, you know, the model weights. And we'll have to build up and during value, the old fashion way like any other business does, we'll have to figure out a great product in reasons to stick with it and deliver it a great price.

There's a reason that we release chatGPT was we want the world to see this and we've been trying to tell people that AI is really important. And if you go back to like October of 2022, not that many people thought I was going to be that important or that it was really happening. And a huge part of what we try to do is put the technology in the hands of people. Now, again, there's different ways to do that. And I think there really is an important role to just say, like, here's the weights have added. But the fact that we have so many people using a free version of Chachi BT that we don't, you know, we don't run ads on. We don't try to make money on. We just put out there because we want people to have these tools. I think it's done a lot to provide a lot of value and teach people how to fish, but also to get the world really thoughtful about what's happening here. Now, we still don't have all the answers and we're fumbling our way through this. Like everybody else, and I assume we'll change strategy many more times as we learn new things. When we started OpenAI, we had really no idea about how things were going to go that we'd make a language model, we'd ever make a product, we started off just, I remember very clear that first day we were like, well, Now we're all here, that was, you know, it was difficult to get the setup, but what happens now? Maybe we should write some papers, maybe we should stand around a whiteboard and we've just been trying to like put one foot in front of the other and figure out what's next and what's next and what's next. And I think we'll keep doing that.

Doesn't, so I definitely don't think it'll be an arms race for data because when the models get smart enough at some point, it shouldn't be about more data, at least not for training. It may matter data to make it useful. Look, the one thing that I have learned most throughout all this is that it's hard to make confidence statements a couple of years in the future about where this is all going to go. And so don't want to try now. I will say that I expect lots of very capable models in the world. And, you know, like, it feels to me like we just like stumbled on a new fact of nature or science or whatever you want to call it which is like we can create you can like I mean, I don't believe this literally, but it's like a spiritual point. Intelligence is just this emergent property of matter, and that's like a rule of physics or something. So people are going to figure that out, but there will be all these different ways to design the systems. People will make different choices, figure out new ideas, and I'm sure, like, you know, Like any other industry, I would expect there to be multiple approaches and different people like different ones. You know, some people like iPhone, some people like an Android phone. I think there'll be some effect like that.

Well, we'll make huge algorithmic gains for sure. And I don't want to discount that. I'm very interested in chips and energy. But if we can make a same quality model twice as efficient, that's like we had twice as much compute. And I think there's a gigantic amount of work to be done there. And I hope we'll start really seeing those results. Other than that, the whole supply chain is very complicated. There's logic fabric capacity there's how much HP I'm the world can make there's how quickly you can like get permits and poor the concrete make the data centers and then have people and they're worried them all up there's finally energy which is a huge bottleneck but I think when there's this much value to people the world will do its thing will try to help it happen faster and there's probably like I don't know how to give it a number, but there's like some percentage chance where there is, as you were saying, like a huge substrate breakthrough and we have like a massively more efficient way to do computing, but I don't, I don't like bank on that or spend too much time thinking about it.

I'm super interested in this. I love like great new form factors of computing. And it feels like with every major technological advance, a new thing becomes possible. Uh, phones are unbelievably good. So I think the threshold is like very high here. Like, I think like, I personally think iPhone is like the greatest piece of technology humanity has ever made. It's really a wonderful product. What comes into it? Like, I don't know. I mean, I was going to say that was what I say. And it's so good to get beyond it. I think the bar is like, white, high.

Well, every, almost everyone's willing to pay for a phone anyway. So if you could like make a way cheaper device, I think that barrier to carry a second thing or use a second thing is pretty high. So I don't think, given that we're all willing to pay for phones or most of us are, I don't think cheaper is the answer.

Probably, but the phone manufacturers are going to do that for sure. That doesn't necessarily hit a new device. I think you'd have to find some really different interaction paradigm that the technology enables. And if I knew what it was, I would be excited to be working on it right now.

But it's really, we'll get that better. And I think voice is a hint to whatever the next thing is. Like if you can get voice interaction to be really good, it feels I think that feels like a different way to use a computer.

It's, it's so clunky right now. It's slow. It's like kind of doesn't feel very smooth or authentic or organic. Like we'll get all that to be much better.

Super powerful to be able to, like, the multimodality of saying, like, hey, Chagit BT, what am I looking at? Or like, what kind of plant is this? I can't quite tell. That's obviously, that's like, that's another, I think, like hint, but whether people want to wear glasses or like hold up something when they want that, like, there's a bunch of just like the sort of like societal interpersonal issues here are all very complicated about wearing a computer on your face.

So I think it's like,

I think what I want is just this always on like super low friction thing where I can either by voice or by text or ideally like some other it just kind of knows what I want. Have this like constant thing helping me throughout my day that's got like as much context as possible. It's like the world's greatest assistant. And it's just this like thing working to make me better and better. There's like only here people like talk about the a future there imagine they imagine there's sort of two. different approaches and they don't sound that different but I think they're like very different for how we'll design the system in practice. There's the I want to extension of myself. I want like a ghost or an alter ego or this thing that really like is me is acting on my behalf is responding to emails not even telling me about it is sort of like it becomes more me and is me. And then there's this other thing which is like, I want a great senior employee. It may get to know me very well. I may delegate it. You know, you can like have access to my email and I'll tell you the constraints, but but I think of it as this like separate entity. Yeah, I personally like the separate entity approach better and think that's where we're going to head. And so in that sense,

I think there'd be agent like the heavier, but there's like a difference between a senior employee and an agent. And like I want it, you know, I think of like my, I think like a bit. Like one of the things that I like about a senior employee is they'll push back on me. They will sometimes not do something I ask or there's sometimes will say like, I can do that thing if you want. But if I do it, here's what I think would happen and then this and then that and are you really sure? I definitely want that kind of eye which not just like this thing that I really have skin it blinded does.

The kind of relationship with me that I would expect out of a really competent person that I worked with, which is different from like a sick event. Yeah.

I'm actually very interested in designing a world that is equally usable by humans and by AI's. I like the interpretability of that. I like the smoothness of the handoffs. I like the ability that we can provide feedback or whatever. So, you know, DoorDash could just expose some API to my future AI assistant and they could go put the order and whatever. Or I could say like, I could be holding my phone and I could say, okay, AI assistant like you put in this order on door to us, please. And I could like watch the app open and see the thing clicking around and I could say, hey, no, not this or like there's something about designing a world that is usable. equally well by humans and AI's that I think is a interesting concept. I'm just like more excited about humanoid robots than sort of robots of like very other shapes. The world is very much designed for humans. I think we should absolutely keep it that way. And a shared interface is nice.

It's hard for me to imagine that we just go to a world totally where you say like, hey, charge me to the order me sushi and it says, okay, do you want it from this restaurant? What kind of what time would ever? I think user, I think visual user interfaces are super good for a lot of things. And it's hard to me to imagine like a world where you never look at a screen and just use voice mode only, but I can't imagine that for a lot of things.

You know, it's like setting a timer with Siri. I do every time because it works really well and it's great to have a lot more information. But ordering an Uber, like I want to see the prices for a few different options. I want to see how far away it is. I want to see like maybe even where they are on the map because I might walk somewhere. I get a lot more information by I think in less time by looking at that order of the Uber screen than I would if I had to do that all through the audio channel.

I think there will just be like yeah different There are different interfaces we use for different tasks and I think that'll keep going.

Um, I met with a new company this morning or I'm barely in a company. It's like two people that are going to work on a somewhere project trying to actually finally make the AI tutor like and I've always been interested in the space. I had a lot of people have done great stuff on our platform, but if if someone can deliver like the way that you actually like And they used a phrase I love, which is this is going to be like a monastery level of reinvention for how people learn things. But if you can find this new way to let people explore and learn and new ways on their own, I'm personally super excited about that. A lot of the coding related stuff you mentioned Devon earlier, I think that's like a super cool vision of the future. The thing that I am health care, I believe should be pretty transformed by this. But the thing I'm personally most excited about is the sort of doing faster and better scientific discovery. GPT-4 clearly, not they are in a big way, although maybe it accelerates things a little bit by making scientists more productive. But alpha-3, yeah. That's like, but Sam, that will be a triumph.

You'll need some of that for sure, but the thing that I think we're missing across the board for many of these things we've been talking about is models that can do reasoning. And once you have reasoning, you can connect it to chemistry stimulators.

I don't know. I don't know how much reasoning is going to turn out to be a super generalizable thing. I suspect it will, but that's more just like an intuition and a hope and it would be nice if it worked out that way. I don't know if that's like

And then resolving so many ways where that could go like maybe it is it trains a literal model for it or maybe it just like knows the one big model what it can like go pick what other training data it needs and ask a question and then update on that.

You know, there's like a version of this, I think you can like already see. When you were when you were talking about like biology and these complicated networks of systems the reason I signed I got super sick recently and I'm mostly better now but it was just like body like got beat up like one system at a time thought like you can really tell like okay it's this cascading thing and uh And that reminded me of you like talking about the like biology is just these like you have no idea how much these systems interact with each other until things start going wrong. And that was sort of like interesting to see. But I was using, I was like using ChadGPT to try to like figure out like what was happening whatever and and would say, well, I'm you know, unsure of this one thing. And then I just like posted a paper on it without even reading the paper, like in the context. And it says, oh, that was the thing I was unsure of. Like now, I think this instead. So there's like a, that was like a small version of what you're talking about where you can like, can say this, I don't know this thing. And you can put more information. And you don't retrain the model. I just added it to the context here. And that's what you're getting them.

Yeah. So my, on the general thing first, You clearly will need specialized simulators, connectors, pieces of data, whatever, but my intuition. And again, I don't have this like backed up with science. My intuition will be if we can figure out the core of generalized reasoning, connecting that to new problem domains in the same way that humans are generalized reasoners. would I think be doable to the faster unlock faster unlock that I think so. But yeah, you sort of like does not start with a language model. It's that that's a model that is like customized to do video. And and so like we're clearly not at that world yet.

Yeah, I mean, one example of this is like, okay, you know, as far as I know, all the best text models in the world are still a lot of regressive models and the best image and video models or diffusion models. And it's like strange in some sense.

So I think it's very different for different kinds of, I mean, I look on unfair use. I think we have a very reasonable position under the current law, but I think AI is so different. good for things like art will need to think about them in different ways. But let's say if you go read a bunch of math on the internet and learn how to do math, that I think seems unobjectionable to most people. And then there's like another set of people who might have a different opinion about what if you like actually, I mean, I get into that just in the internet making this answer too long. So I think there's like one category of people are like, okay, there's like generalized human knowledge. You can kind of like go, if you learn that, like that's like open domain or something, if you kind of go learn about the Pythagorean theorem. That's one end of the spectrum. And then I think the other extreme end of the spectrum is art. And maybe even like more than more specifically, I would say it's like doing It's a system generating art in the style or the likeness of another artist would be kind of the furthest end of that. And then there's many, many cases on the spectrum in between. I think the conversation has been historically very caught up on training data, but it will increasingly become more about what happens at inference time as training data becomes less valuable, and what the system does accessing information in context and real time, or taking something like that, what happens at inference time will become more debated and what the new economic model is there. So if you say like, create me a song in the style of Taylor Swift, Even if the model were never trained on any Taylor Swift songs at all, you can still have a problem, which is that may have read about Taylor Swift that may know about her themes, Taylor Swift means something. And then the question is, should that model, even if it were never trained on any Taylor Swift song whatsoever, be allowed to do that? And if so, how should Taylor get paid? Right. So I think there's an opt-in opt-out in that case first of all, and then there's an economic model. Staying on the music example, there is something interesting to look at from. the historical perspective here, which is sampling and how the economics around that work. This is quite the same thing, but it's like an interesting place to start looking at.

I wasn't trying to make that that point because I agree like in the same way that humans are inspired by other humans. I was saying if you if you say generate me a song in the style of Taylor Swift.

But I think personally, that's a different case.

You know, with a female voice, you know, we we have currently made the decision not to do music and partly because exactly these questions of where you draw the lines and you know what like even I was meeting with several musicians that I really admire recently. I was just trying to talk about some of these edge cases, but even the world in which if we went and let's say we paid 10,000 musicians to create a bunch of music just to make a great training set where the music model could learn everything about strong, strong structure and what makes a good catchy beat and everything else. And only trained on that, let's say we could still make a great music model, which maybe we could. You know, I was kind of like posing that as a thought experiment to musicians and they're like, well, I can't object to that on any principal basis at that point. And yet there's still something that I don't like about it. Now, that's not a reason not to do it necessarily. But it is, did you say that ad that Apple put out maybe as yesterday or something of like squishing all of human creativity down into one really thin iPad?

Then you would think there's something about I'm obviously hugely positive on AI, but there is something that I think is beautiful about human creativity and human artistic expression and you know for an AI that just does better science like great bring that on, but an AI that is going to do this like deeply beautiful human creative expression, I think we should like Think you're out. It's gonna happen. It's gonna be a tool that will lead us to greater creative heights. But I think we should figure out to do it in a way that like preserves the spirit of what we all care about here.

Yeah. You know, we put out this thing yesterday called the spec where we're trying to say here are here's here's how our models supposed to behave. And it's very hard. It's a long document. It's very hard to like specify exactly in each case where the limits should be. And I view this as like a discussion that's going to need a lot more input. But but these sorts of questions about Okay, maybe it shouldn't generate Darth Vader, but the idea of a Sith Lord or a Sith style thing or Jedi at this point is like part of the culture or like like these are all hard decisions.

I'm concerned. I mean, there's so many proposed regulations, but most of the ones I've seen on the California state things, I'm concerned about. I also have a general fear of the states all doing this themselves. When people say regular AI, I don't think they mean one thing. I think there's like some people are like being on the whole thing. Some people like don't allow to be open source, required to be open source. The thing that I am personally most interested in is I think there will come Look, I may be wrong about this. I will acknowledge that this is a forward looking statement, and those are always dangerous to make. But I think there will come a time in the not super distant future, like, you know, we're not talking like decades and decades from now, where AI says the frontier AI systems are capable of causing significant global harm and for those kinds of systems and the same way we have like global oversight of nuclear weapons or synthetic bio or things that can really like have a very negative impact way beyond the realm of one country. I would like to see some sort of international agency that is looking at the most powerful systems and ensuring like reasonable safety testing. You know, these things are not going to escape and recursively self-improve or whatever.

You know, if the line where we're only going to look at models that are trained on computers that cost more than 10 billion or more than 100 billion or whatever dollars, I'd be fine with that. There'd be some line that defined and I don't think that puts any regulatory burden on startups.

Can I say one more thing about that? Of course. I'd be super nervous about regulatory overreach here. I think we can get this wrong by doing way too much. Or even a little too much. I think we can get this wrong by doing not enough. But I do think part of and I. And now I mean, you know, we have seen regulatory overstepping or capture just get super bad in other areas. You know, that also maybe nothing will happen, but but I think it is part of our duty and our mission to like talk about what we believe is likely to happen and what it takes to get that right.

Totally. Right. The reason I have pushed for an agency based approach for kind of like the big picture stuff and not a like write it in lies I don't in 12 months it will all be written wrong and I don't think even if these people were like true world experts I don't think they could get it right looking at 12 or 24 months and I don't these policies which are like we're gonna look at you know we're gonna audit all of your source code and like look at all of your weights one by one like Yeah, I think there's a lot of crazy proposals out there.

Again, this is why I think it's yeah. But like when before an airplane gets certified, there's like a set of safety tests. We put the airplane through it. And totally. It's different than reading all of your code.

And so what I was going to say is that is the kind of thing that I think as safety testing makes sense.

Or do you see that the current strength of models? Definitely some things are going to go wrong and I don't want to like make light of those or not take those seriously, but I'm not like I don't have any like catastrophic risk worries with a GPT for level model and I think there's many safe ways to choose to deploy this Maybe we'd find more common ground if we said that and I like You know, the specific example of models that are capable, that are technically capable, not even if they're not going to be used this way, of recursive self-improvement, or of, you know, autonomously designing and deploying a bio weapon, or something like that. Or new model. That was the recursive point. We should have safety testing on the outputs at an international level for models that have a reasonable chance of posing a threat there. I don't think like GPT for, of course, does not pose it in any sort of, well, I don't want to say any sort because we don't. Yeah, I don't think the GPT4 poses a material threat on those kinds of things. And I think there's many safe ways to release a model like this. But, you know, when like significant loss of human life is a serious possibility, like airplanes or any number of other examples where I think we're happy to have some sort of testing framework. Like, I don't think about an airplane when I get on it. I just assume it's going to be safe.

And you've been a result in that come out very soon. It was a five-year study that wrapped up or started five years ago. Well, there was like a beta study first and there was like a long one that ran.

Um, so we started thinking about this in 2016, uh, kind of, both the same time started thinking AI really seriously. And the theory was that the magnitude of the change that may come to society and jobs in the economy and sort of in some deeper sense than that, like what the social contract looks like. Um, meant that we should have many studies to study many ideas about new ways to arrange that. I also think that, you know, I'm not like a super fan of how the government has handled most policies designed to help poor people and I kind of believe that if you could just give people money, they would make good decisions and the market would do its thing and You know, I'm very much in favor of lifting up the floor and reducing eliminating poverty. But I'm interested in better ways to do that than what we have tried for the existing social safety net and kind of the way things have been handled. And I think giving people money is not going to go solve all problems that certainly have to make people happy. But it might It might solve some problems that it might give people a better horizon with which to help themselves. And I'm interested in that. I think that now that we see some of the ways, so 2016 was very long time ago, you know, now that we see some of the ways that AI is developing, I wonder if there's better things to do than the traditional conceptualization of UBI, like I wonder I wonder if the future looks something like more like universal basic compute than universal basic income. And everybody gets like a slice of GPT 7's compute and they can use it, they can resell it, they can donate it to somebody to use for cancer research. But what you get is not dollars, but this like productivity slice, yeah, you own like part of the productivity.

Yeah. Um, you know, I, I, if you have specific questions, I'm happy to.

This is a safe space, yeah. I was fired. I was I talked about coming back. I kind of was a little bit unsure at the moment about what I wanted to do because I was very upset. And I realized that I really loved opening eye in the people and that I would come back and I kind of, I knew it was going to be hard. It was even harder than I thought, but I kind of was like, all right, fine. I agreed to come back. The board took a while to figure things out and then, you know, we were kind of like trying to keep the team together and Keep doing things for our customers and you know sort of started making other plans, then the board decided to hire a different interim CEO and then everybody. There are many people. Oh, my gosh.

And I have nothing but the scare moochie.

I was in a hotel room in Vegas for everyone weekend.

Actually, no, I got a tax than they before. And then I got on a phone call with the board. And then that was that. And then I kind of like, I mean, then everything went crazy. I was like, it was like, I mean, I have my phone was like unusable. It was just a nonstop vibrating thing. I'm like, that's just called.

And then like, you know, I kind of did like a few hours of just this like absolute fugue state in the hotel room trying to like I was just confused beyond belief trying to figure out what to do. And so we're and then like flew home, it may be like We've got a panel like, I don't know, 3PM or something like that. Still just like, you know, crazy nonstop, phone blowing up, met up with some people in person. By that evening, I was like, okay, you know, I'll just like go do HCI research and it's feeling pretty happy about the future. Yeah, you have options. And then, and then the next morning had this call with a couple of board members about coming back and that led to a few more days of craziness. And then, uh, and then it kind of, I think it got resolved. Well, it was like a lot of insanity in between.

Um, well, we only have a nonprofit board. So it was all the nonprofit board members. Uh, they're, the board had gotten down to six people. Um, they, and then they removed Greg from the board and then fired me.

I think there's always been culture clashes at. Look, obviously, not all of those board members are my favorite people in the world. But I have serious respect for the gravity with which they treat AGI and the importance of getting AI safety right. And even if I stringently disagree with their decision-making and actions, which I do, I have never once doubted their integrity or commitment to the sort of shared mission of safe and beneficial AGI. Do I think they like made good decisions in the process of that or kind of know how to balance all of things opening it has to get right? No, but I think the intent of the magnitude of AGI and getting that right

I think a lot of the, well, I mean, first I'll say, I'll answer the first question in the second one. I think it does create a great deal of fear. I think a lot of the world is understandably very afraid of AGI or very afraid of even current AI and very excited about it and even more afraid and even more excited about where it's going and we we wrestle with that but like I think it is unavoidable that this is going to happen. I also think it's going to be tremendously beneficial. But we do have to navigate how to get there in a reasonable way. And like a lot of stuff is going to change and change is, you know, pretty, pretty uncomfortable for people. So there's a lot of pieces that we got to get right and ask a, can I ask a different question?

I wish I had taken equity, so I never had to answer this question.

The original reason was just like the structure of our nonprofit. It was like there was something about Yeah, okay, this is like nice from motivations perspective, but mostly it was that our board needed to be a majority of disinterested directors. And I was like, that's fine. I don't need equity right now. I kind of.

One thing I have noticed, it is so deeply unimaginable to people to say, I don't really need more money.

No, it's so it assumes.

If I were just trying to say like I'm going to try to make a trillion dollars with open AI, I think everybody would have an easier time and it would save me. I save a lot of conspiracy theories.

So the things like device companies or if we were doing some chipfab companies, like those are not same project. Those would be like opening I would get that. Quity.

That's not a public's perception. Well, that's not like kind of the people like you who have to like commentate on the stuff all day's perception, which is fair because we have an announced stuff because it's not done. I don't think most people in the world like are thinking about this, but I agree. It spins up a lot of conspiracies. conspiracy theories and like tech commentators and if I could go back yeah I would just say like let me take equity and make that super clear and then I would be like all right like I'd still be doing it because I really care about AGI and think this is like the most interesting work in the world but at least I've checked everybody what's the chip project

I don't know where that came from actually. I genuinely don't. I think I think the world needs a lot more AI infrastructure a lot more. Then it's currently planning to build and with a different cost structure. The exact way for us to play there is we're still trying to figure that out.

Oh, I have to go in a minute. It's not because it's not to prevent the edge case that we need to be more organized, but it is that these systems are so complicated and concentrating, that's are so important. Like one You know, at the time, before it was like obvious to do this, you have like, deep mind or whatever has all these different teams doing all these different things and they're spreading their bets out. And yeah, open the eyes say we're going to like basically put the whole company and work together to make GPT for. And that was like unimaginable for how to run an AI research lab, but it is. I think what works, that it eliminates what works for us. So, not because we're trying to prevent educators, but because we want to concentrate resources and do these, like, big, hard, complicated things, we do have a lot of coordination on what we work on.

I really wish I would love to come back on after I next like major motion. I'll be able to talk more directly about it.

I, you know, I would love to play poker. It has been forever. That would be a lot of fun.

I don't really know if you, I don't, I don't know if you could say it by anybody.