00:20:53 · John Collison, Sam Altman
[00:20:53] S0: Exactly. We're half pint in. Yeah. Perfect time for... [00:20:55] S1: The name of the channel was model name Dash Hold My Beer. And people were just throwing that at the hardest problems they could. And people just, like, didn't think the model was gonna do these things, and and we had this collective experience of people's, like, hardest research problems from their academic career. The model was just knocking down one after the other in many different fields. Was incredible to watch. Kind of two nights in a row, was up most of the night because I was so excited that I couldn't go to bed. It was like... Many of those problems that we published, many other things. And I was tremendously excited and happy, but I also had, like, much more sadness and melancholy and, like, a feeling of, like, something ending than I was expecting. So, again, I agree this is the right thing on behalf of the world. And and also, I agree that this is just, like, the shape of reality and nothing that anyone can stop or should stop. But I do have, like, real... [00:21:57] S0: I mean, so wistfulness and nostalgia you can feel. [00:22:00] S1: It's more than nostalgia. Wistfulness.
00:22:00 · Sam Altman, John Collison
[00:22:00] S1: It's more than nostalgia. Wistfulness. [00:22:02] S0: Yeah. Like, my dad describes how, you know, growing up in Ireland in the nineteen fifties, he observed people around him still using horses productively in industry And... In the fifties. Yeah. And, I mean, not... Obviously, there were also tractors, but, you know, it was being phased out. And... But it still for sure happened. And observing that this was a technology that humans had been using for thousands of years, and he was witnessing the very tail end of it. And, yeah, I think there's always that feeling of witnessing the the closing of a chapter that leads to some wistfulness, but it's okay. [00:22:41] S1: It's like it's people's lives, and it's something that has brought them great joy, and, you know, maybe most most... I mean, certainly, most mathematicians never solve the Millennium prize problem. But the idea that you might be able to, And the idea that there is stuff out there that we don't understand yet, that through great effort and, you know, pushing aside other things in your life and dedicating yourself to, you can still solve and understand. Like, there's something beautiful about that. [00:23:09] S0: What else are excited about from a safety point of view? [00:23:11] S1: We talked about this a little bit earlier, but I I I wanna, like, emphasize it again. [00:23:15] S0: I... I'll just call it
00:23:15 · John Collison, Sam Altman
[00:23:15] S0: I... I'll just call it [00:23:17] S1: swarms since that seems like the term right now. I I do think the properties of swarms match a lot of the properties of the resilience of society or the robustness of society that that I kind of... I think we're just missing from the, like, single roll out, single brained version of the world. Like, for all of the deep flaws of society, it is unbelievably robust. And this would not happen without, like, a lot of people keeping each other in check and collaborating and kind of these values of pluralism and democracy. And I had been sort of sad that that was gonna trend away in AI. And now I I... Like, I'm excited about this as a direction. [00:24:00] S0: You're saying, basically, it shouldn't lead in a centralized direction because you will have many agents and agents pushing against each other in a dynamic equilibrium, and, you know, offense defense is a good example of this. [00:24:13] S1: I would much rather intuitively have a trillion AIs of, like, slightly superhuman intelligence join society than one AI of 1,000,000,000,000 IQ join society. [00:24:27] S0: Yeah. And you think we're headed in that direction of the [00:24:30] S1: multiple? All of these things are things we have to push for. Like, all of these things are like, we have this incredible technology. It can be pointed and deployed in many ways. I think there are a lot of people who may have a different opinion about where it should... How it should be used and what is the best version of the world, but this is the one that I think is right.
00:24:30 · Sam Altman, John Collison
[00:24:30] S1: multiple? All of these things are things we have to push for. Like, all of these things are like, we have this incredible technology. It can be pointed and deployed in many ways. I think there are a lot of people who may have a different opinion about where it should... How it should be used and what is the best version of the world, but this is the one that I think is right. [00:24:51] S0: Let's talk about starting a business. Thanks to coding models, your weekend side hustle can quickly become a serious undertaking. And we've been busy here at Stripe, making that process as simple as possible. Stripe Atlas helps you with everything you need to start a business, like company formation, tax IDs, founder equity, and all the other bits that usually require someone in a suit. So if you've got a company in the making, take a look at stripe.com/atlas. How's compute shortage going?
00:24:51 · John Collison, Sam Altman
[00:24:51] S0: Let's talk about starting a business. Thanks to coding models, your weekend side hustle can quickly become a serious undertaking. And we've been busy here at Stripe, making that process as simple as possible. Stripe Atlas helps you with everything you need to start a business, like company formation, tax IDs, founder equity, and all the other bits that usually require someone in a suit. So if you've got a company in the making, take a look at stripe.com/atlas. How's compute shortage going? [00:25:21] S1: I mean, there are all these ways where I think things at various times along the curve are gonna get somewhat out of hand, and there will be moment... Like with any new thing of this importance, there are going to be moments of irrational exuberance. There are going to be moments of bust. There are to be moments of constraint and glut and up and down. But I think the trend is toward a... We always just want more compute. Like, the demand for sufficiently capable models at a sufficiently low price, I think that trend only goes one way. And we're doing a lot of things to try to be prepared for this. We made a chip that is an incredible performance at units of intelligence per watt. We are learning how to build our own data centers. We have a robotics program that we're going to point at making lots of data centers. People talk a [00:26:18] S0: lot about... The real RSI.
00:26:18 · John Collison, Sam Altman
[00:26:18] S0: lot about... The real RSI. [00:26:19] S1: Yeah. People talk a lot about RSI as like an AI that does AI research. There's very little... Relatively little talk about self replicating data centers. You know, this idea that you can use AI to control robots and run fabs and build turbines or solar panels and, you know, build data centers. But I think we are... I think we have that, like, within grasp. But... And so we'll try to make a lot of really cheap compute. [00:26:44] S0: But aren't data centers already not labor bottlenecked? They're permitting bottlenecked and components bottlenecked. [00:26:52] S1: Could we make more components to the robots? [00:26:55] S0: Eventually. Yeah. [00:26:56] S1: Yeah. Yeah. And I'm... All of this is, like Yeah. Yeah. How we solve this over a long period of time. [00:27:00] S0: Like, my observation in the computer stuff is they say the solution to high prices is high prices. That's like, okay, step one, we have the high prices for memory and GPUs and everything, and the solutions should be here any moment now. [00:27:13] S1: How are [00:27:13] S0: we doing on the solutions front? Bad. And I'm not saying there's an OpenAI's job. I feel like this is the Invisible Hands job. Right? Like, memory's gotten really expensive, and so new memory makers are gonna flood the market any moment I [00:27:26] S1: think the Invisible Hand is failing right now. I mean, the Invisible Hand, it has, like, a checkered track record at best. But I think it's, like, not quite working here. [00:27:37] S0: Why not? Like, is it just hysteresis or...