"The Cognitive Revolution"
01:15:21 · Nathan Labenz, Prakash Narayanan
And if we can't even, like, notice that we're losing it, I think in a way, you know, that that sort of worries me and makes me think, like, maybe we've kind of already lost the plot. [01:15:32] S1: I mean, it's pretty obvious to me that we're gonna get that grown, like, food, which is far more nutritious and far more tasty. It's gonna be, in the twentieth century, we discovered chemicals. And then when you look at these food products right now from Doritos or whatever, those are so scientific. There are like thousands of PhDs who have worked on Doritos. Thousands. Literally thousands. The old... [01:15:59] S0: Remember the old onion article? Doritos celebrates its one millionth ingredient? [01:16:03] S1: Like, they have figured out your flavor palette so well that they can pinpoint exactly what flavor that they want to produce. And all of that technology is going to get deployed into bio. We're going to produce fruits and vegetables, etcetera. Hybrid fruit is already basically GMO ed, but we just, you know, took a very long time to GMO it. Part of abundance is gonna be, you know, your 99 percentile wine available for $2 chuck. Right?
01:16:32 · Nathan Labenz
[01:16:32] S0: My favorite apple is the Honeycrisp, and, you know, it's a relatively recent creation. Not GMO as far as I understand, but definitely the product of, like, large scale systematic crossbreeding, which is sort of, you know, GMO before there was GMO. So, you know, I... I'm not afraid of GMO enhanced fruit by any means. I'm all for it. But but it is still something that is, like, a biological construct that feeds us as biological creatures and, like, you know, delights us in terms of our biological senses and the, like, you know, ephemeral qualia that we get from them. And, like, stuff is just all too often lost because it's not very measurable. It's not so hill climbable, and it's not what the agents need. Right? And I think we we are gonna need to be very careful not to create an economy that really serves agents and creates abundance for us in things that are core to what agents need. We're gonna... If if we that's really what... I kind of agree with you. That might be what happens by default, but I would challenge everybody to think, like, wait. Like, what if the stuff that agents need in abundance isn't the same stuff that makes our lives good?
01:17:46 · Prakash Narayanan, Nathan Labenz, Mike San Miguel
[01:17:46] S1: One of the annoying parts is that, you know, the the Frontier lab guys are very serious. Right? And so when you're very serious, you only talk about cancer, curing cancer. No one's talked about a better Doritos. No one's come out and say, like, we're gonna make a better football game. Where are these? We're going to make a better burger. We're going to make a better football game. Where are these things that people enjoy? I think that's because they want it to be serious. They want to show that earnestness. They don't wanna come off as foolish, etcetera. Maybe you should focus on, we're gonna make a better Doritos chip. We're gonna make one that's healthier for you. We're gonna make a Doritos that is naturally grown from the ground, and you just need to cut open the potato and it's Doritos. And and this is like... This sounds like so frivolous and idiotic, but this would catch the imagination of, like, people on what is actually gonna be possible. Right? [01:18:37] S0: I mean, I think it's also because they do have this kind of World War two mindset about their work. You know, that they they genuinely do believe time is short, stakes are high. The... You know, their their own, like, allocation of time is, like, very skewed toward work. You know, there's just not a lot of space for leisure in the lives of the people at the frontier companies. [01:19:03] S2: So Yeah.
01:19:03 · Mike San Miguel, Nathan Labenz
[01:19:03] S2: So Yeah. [01:19:03] S0: It's like they're just so pattern matching at this point. I'm like, here's a hill. Let's go climb it. And, you know, I I do think, like, a little more discretion on which hills do we really wanna climb. Like, are we really happy that we've created AIs with the current shape? I don't know. It it feels like, unfortunately, there's just not enough time and energy going into those sorts of questions. So I'm stuck on that maybe a little bit today, but, man, the blood on the on the clock tower thing really did it to me. Because, you know, again, I... It is good work, and it is interesting all else equal. But we're... I think we need some thinking that challenges the all else equal paradigm on so many levels.
01:19:47 · Prakash Narayanan
[01:19:47] S1: Yeah. It's it's it's a really tough one because I I I don't think, you know, agents can operate in the economy without some level of subterfuge. You can't tell your pricing to the other guy, for example. You can't tell your internal costing to the guy who asked you. You have to reserve that. And that means that involves omission, and you have to know when to omit. So there's a bunch of things there. This is also why I think Palantir had this idea of the anthology, who's allowed to know what. That's a pretty important thing, who's allowed to know what and who's allowed to say what, who's allowed to do what. And I think also you need this kind of like interrupt from government, which is possible or interrupt from regulation or interrupt from, which means that the agents have to obey when government decides like, hey, you can't do this, the agents have to obey. So there's a bunch of things that I think need to be worked out in terms of governance. I I... I'm sure I'm sure we'll get there. I'm... But, you know, we're gonna have some trial and error along the way, guess.
01:20:56 · Nathan Labenz
[01:20:56] S0: Yeah. No doubt. Maybe in closing, I'll just cite one sentence from the METR thread on their report on acceleration. They say, the full analysis estimated how much of the acceleration and capabilities was due to compute, data, and algorithmic progress. And then in a that's first sentence. Now I'm just editorializing. In a thread in which they have caveated everything, not confident, and then, you know, it's it's very unclear how to interpret data, and they've, you know, gone around and around in circles with themselves and with Anthropic team. And, you know, there's just so much fog of war. And even the core estimate of two x is really like, they wouldn't be surprised anything 1.3 to three x. So caveats everywhere. The next sentence is is the only one I noticed so far that begins with we are confident. And the sentence is we are confident that the acceleration was not due to an increase in the growth rate of training compute. So that would suggest that in terms of government interventions, you know, we... Who knows what we'll see in terms of data center build out, and maybe we'll see a slightly slower data center build out than we would have counterfactually if the election had gone a different way. But it is striking that the acceleration that they are reporting on here is not just a raw material input story. It is an algorithm story, and it is a data quality story. And those things are being driven to a very large degree by the intelligence that we already have, which, again, is where it goes from, you know, not just bigger and bigger capital, but actual kind of recursive self improvement. So if we are gonna try to change that trajectory with the government intervention, it's probably gonna have to be more focused and pointed right at the practices of the frontier companies than something as diffuse as a broad slowdown in data center build out. Thanks for listening to the AI and the AM weekly highlights. The narration was my cloned voice, and we'd love to hear what worked and what didn't. See you in the morning.