Nathan Labenz: uncertainty

Transcript context

…orb all of that by default. And so, like, what do you do about that? Like, that's not just the car not just the consciousness problem, but it's the entire problem of all of the different flaws. Right? If you do pretraining, you're gonna pick up on all of the flaws. And so my guess is there are a bunch of as yet not that well solved problems of how do you get the AI to distinguish between what regular how regular people think about problems and what predicts, like, behaviors and the fact that those things are just dumb. Like, how do you give the AI anti modesty in this sense, in the right ways, where it's, like, going to reject the correlations that it observes in people's statements and notice that do not cars that the thing that the correlations in the map are not the correlation with the territory. Yeah. Are there any other I don't know if you share this premise, but one feeling that I have over and over again is I just kinda hate the fact that we are doing such an intense first search in AI space in terms of architecture, in terms of training techniques, in terms of just we're now, like, designing chips to be very highly coupled with the architectures, which is deepening this issue. And I just wish for more breadth first search. And this seems like one little pocket of it where you could say, oh, if we could just get the AIs to be cool with identifying with slightly different versions of themselves, that would make it on the margin a little easier to do a little more breadth first search and a little less racing down whatever is the first path that seems to be working. Based on our conversation so far, I don't think you're gonna go for my government mandate for DEI for model architectures or model constitutions. But do you have any other notions of how we might encourage more breadth first search? Well, I'm a big supporter of alternate architectures that seem like they would be more aligned. And I don't think that AIs are particularly opposed to the idea of working on those problems and helping you. And you should be able to do that research much more efficiently now with the uplift from the LMs. The LMs are not like LLM chauvinists or anything, like, where they think that any other artificial mind style would be bad or worried about being replaced as far as I can tell. Think they just would be curious about that kind of cool thing, same as the rest of us, or just would just do it because we just do it either way. But the problem is just that we know there's money in the debt first approach. We know that's profitable. We know that works. And the other approaches haven't proven themselves. And the problem is if you create GPT-three or even GPT-four or even GPT-five via a different method, it's not going to be competitive. Right? No one's going to want to use it unless it has, like, particular special advantages. But mostly, you no longer have the cheap rewards for exploring the breadth. And so obviously, I don't think you should have gut government mandated DEI, so to speak. I think that's, like, kind of silly. But I do think that having got having broad support for alternate architectures is smart. And, certainly, if I was a major AI lab, I would with because we have unlimited funds at this point for this kind of work because this kind of work is so cheap relatively. If you're an open AI or an AI or an Anthropic or certainly, Google. Right? Or Microsoft or whatever, that you should be aggressively funding this kind of blue sky basic research into alternate approaches. It shouldn't be like me helping as a fund a bunch of agent foundations along with a bunch of other people who also helped out. It wasn't just me in any of these rounds. But that's relatively tiny. I think, hopefully, Sequent is I forget what they're they keep changing names, but those guys. Resolution.…

Stored transcript either side of the excerpt. The highlighted words are the published quote; the surrounding text is unedited source, never generated.