The Cognitive Revolution / episode intelligence
Speakers in the public record
Claim mix
Evidence policy
Every row below preserves an exact excerpt. Identified speakers are linked; unresolved voices are labeled and excluded from people counts.
Claim ledger
31 published records
01 / prediction
“That's a lot, right? So we should definitely be considering scenarios that are sooner, right, and particularly, I think the sooner AGI happens, the more dangerous it might be, right?”
02 / recommendation
“Is there stuff that we can do or is it, you know, is there is it a different organization's job to figure out how to fill that gap. Because I do feel like I want some more, and I love some of the AE Studio stuff, including self-other overlap.”
03 / belief
“Pivotal, ERA, PIBS, Laser Labs, SPAR, ARENA for technical. I think ASTRA is now running again.”
04 / belief
“I think Matt has to be pretty careful, in terms of obviously our 501c3 spending requirements for advocacy.”
05 / uncertainty
“I mean, you mentioned Les Wrong and Eliezer, and there's this sort of, I don't know all the lore of Matt's, but I do understand that a lot of people who have participated in it over time come out of the Eliezer discourse and had a certain set of assumptions that were like, we're not going to be able to teach this thing our values, it's going to be extremely unwieldy from the beginning.”
06 / belief
“I kind of I think of them more as like Obviously they're quite different too across the different companies, but I think of it less as like trying to get rich and more like trying to make a real mark on history is kind of the biggest summary that I would give for a lot of them.”
07 / belief
“Like you have I think the going rate for far AI's research scientists are something like 100, 170K, so significantly lower.”
08 / uncertainty
“I both watched a talk of yours and read a blog post from about 18 months ago where you kind of sketch out the different archetypes of AI researcher that you have seen, and then also kind of map that onto the demands of organizations. And I don't know how much it's changed.”
09 / belief
“I think that the way we do it is pretty good and that we have a bunch of, for our model API calls and all that, we have specific organization accounts that we sign people up, and then we kind of give them a budget and so on and top them up as necessary.”
10 / belief
“One thing that jumps out is like maybe not as emphasized as I would have thought is being in command of current research. That's something I think at this point, like really nobody can keep up with all the current research because, you know, that exponential has gotten away from all feeble human minds, I would say, maybe with a few hyperlexics that can still keep up.”
11 / belief
“Now you could say like, okay, what if you also tried to pour resources into like secret AI safety projects at the same time, delay RLHF, delay ChatGPT, build up the AI safety field, uh uh via networks the myri summer schools weren't doing a lot and MATS came along uh just before the ChatGPT moment December 2021 and yeah I think like the first MATS cohorts were a little bit less like a little bit more directionless than the later cohorts definitely like I think safety research really kicked into gear after we had ChatGPT uh not to say that was the only cause but there were like a lot of things happening around that time and I think that like Definitely larger, more capable models have enabled certain types of essential safety research you could not do with smaller models.”
12 / belief
“I think the MIRI line today would be like, we don't really have time for that much research.”
13 / belief
“I thought we would maybe just start with kind of big picture from your perspective. And I think, you know, having watched some of your previous talks, I know that you play sort of a portfolio strategy where you're not like, I have a very specific, narrow prediction, and I'm trying to maximize the value of this organization, this program for that very hyper-specific prediction.”
14 / uncertainty
“What does the kind of funnel look like in terms of, I don't know if there's intermediate steps that, you know, would make sense to talk about selected. And then I think the good news, though, is if you do get into the program, your success rate on the other end of like getting into the field in a professional W-2 employee status sort of way is really high.”
15 / commitment
“I will say that given that the value of AGI is estimated as at least between 1 and 17 quadrillion dollars, I think that's a lot of money.”
16 / uncertainty
“Maybe I'm wrong on this, but I feel like this has seesawed back and forth, and I don't know exactly where we are today.”
17 / belief
“I think that sounds like safe super intelligence in a nutshell. Maybe that's the setup that they've got.”
18 / belief
“With some additional caveat that like we also have some diversity picks. and minimum requirements because we want to support a great breadth of research and we think that the mentor selection committee on the whole might be biased in some ways as well.”
19 / uncertainty
“The time period required would require massive amounts of cognitive labor and human trials and stuff like that. And I don't know, it does sound very sci-fi, so I don't think we should rely on something like that, though I'm all for people pursuing moonshots on the side.”
20 / belief
“I think even in some of the interp streams as well, it's very possible to enter an interpretability stream and bring it with it like some model of the kind of theory-based interpretability mechanism or strategy that you want to pursue and then see that executed on.”
21 / belief
“Uh, though it does seem like there's some debate about this and it seems like some of, some of the deception, it's far from what we might call consequentialist, like, like ******** consequentialist deception in most situations, but I think like Alignment faking and some other papers have shown that there are such, you can like create situations where AI will deceive the user to achieve some like ulterior objective, which was something that was like deliberately given to the AI as an objective.”
22 / recommendation
“on the margin because I think we do have some very strong central research bets that we need more people pursuing because they will yield demonstrable results.”
23 / evaluation
“Yeah, so that brings up another, I think, huge question for AI safety research in general, and probably the strongest, maybe not in, I don't know if you would say strongest in the sense of being most compelling to you, but certainly the most hawkish or fiercest criticism that AI safety research gets is that it always ends up being dual use and that it always ends up somehow accelerating the core capabilities track.”
24 / evaluation
“It's a much slower process. And I think that's because the commitment is less on our end.”
25 / prediction
“Which, by the way, is predicated on this idea that verification is easier than generation, P versus NP, blah, blah, blah, especially if you can see the other person's thoughts and they can't see yours. It does make sense to be at the frontier from that perspective, but I will say that I think the main reason that the companies are doing this is obviously to make money.”
26 / prediction
“I will say this, that like amplifiers, while not currently the most in demand across all different hierarchies of AI safety organization or team are, I think, probably in the next year or two going to be the most in demand.”
27 / preference
“Because I do feel like I want some more, and I love some of the AE Studio stuff, including self-other overlap.”
28 / prediction
“Epoch recently did a study where they showed the pace of new AI companies approaching the frontier is just so much faster than the pace of which the frontier moves because there's an abundance of chips, there's an abundance of data and methods.”
29 / prediction
“I think building a second species is actually going to violate some deep social more in the same way that human cloning would be, but I don't think people will see it that way. So that leaves us with the fact that we actually have to build the AGI because But if we can build products that are safer, right, or perhaps are under some strict regulatory control that we have some like really like ideally like, I don't know, 10 year international slow phased entry to the new AGI world, right, where all these, you know, countries and companies are kind of forced to be very careful and collaborative in the way that they align their models, then we're in a much better world.”
30 / preference
“I guess I could shout out, I mean, it's hard to play favorites because Matt's is like, we've worked with so many people and we're trying to be very broad, but Yeah, I guess like in terms of nonprofits specifically, because maybe they don't get as much attention, obviously Redwood and Meter and Randcast, Apollo Research, FAR, Goodfire, TruthfullyAI, LawZero, Miri, plenty of others.”
31 / evaluation
“I think that math selection doesn't currently emphasize breadth of knowledge very much, mostly because mentors don't necessarily want that.”