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
24 published records
01 / recommendation
“Yeah, portfolio approach, I think is kind of always an answer to this. It does seem like there's room for it.”
02 / evaluation
“No, because if you could spend one year and make yourself 20% more productive, you would recoup that after roughly four or five years.”
03 / recommendation
“So I think things around compute tracking are really useful. This almost sounds too simple, but like getting the capacity to have some type of off switch, because like right now we couldn't actually, there's not an easy way to actually just turn off a lot of computes quickly if there was like an autonomous AI replicating in a bunch of data centers.”
04 / belief
“I think we've seen a little bit of evidence this last couple weeks that could even have a positive effect as it flows through the training data and gives AIs a conception of themselves based on our imagination of what they maybe should be like in a mature state.”
05 / belief
“Is there, if there's not, we can move on. But if you have any other kind of specific advice, I think one of the things people are going to ask, there was a pretty good post on this just yesterday that we can link to in the show notes.”
06 / belief
“I'm not sure how many entrepreneurs are going to want to go join the government, actually, because I think that personality type is often one that started a company in the 1st place because they didn't want to work at a big company.”
07 / belief
“I think just basically the entrepreneurial skill set, it's like making difficult things happen and like building coalitions of people and like setting up systems.”
08 / belief
“One other argument that people have made a lot who I think are especially skeptical of AI companies, but I guess just maybe just have a hype doom as you framed it earlier, is that safety work is ultimately still counterproductive.”
09 / belief
“I think maybe, and to the degree you can focus this on the AI angle on pandemics, I think the audience is If there's one, it's a pretty diverse actually, I've learned over time, but if there's one thing that unites us, it is a general obsession with AI.”
10 / belief
“I would say my subjective sense right now of the AI nonprofit space is, and obviously there will be exceptions to this, I don't mean to pay with too broad of a rush, and you can also feel free to disagree.”
11 / belief
“I think a bigger point I might make about this is like, I guess I come at this from a perspective of just we're very uncertain about all of these different priorities and what's going to happen.”
12 / evaluation
“I want to get into that and get your take on how people who maybe don't work directly in the space yet or who do what kind of work but are not sure if they're making the biggest impact that they can, how they might think about pivoting their careers to try to have the most positive, try to make the most positive contribution that they can.”
13 / belief
“I think also just like more popular support helps as well because politicians won't do things unless there's some type of electoral incentive ultimately.”
14 / belief
“Shout out also to Halcyon as another network that I've seen with a very focused and not super scaled, but high success rate approach. They've also been pretty good, especially I think for mid-career people making moves into the AI space.”
15 / observation
“One interesting thing that's happened in the last few years is a lot of these, in the past, this was more of a high level conceptual research kind of bottleneck, but now it's much more about actually engineering and there's just a lot of just like Concrete, okay, can we use this AI to monitor this AI?”
16 / evaluation
“AI is one of the premises of this show and one of the reasons I enjoy making it so much is that it's obviously a general purpose technology, a horizontal layer, something that kind of intersects with everything.”
17 / preference
“If there's these risks that might jeopardize the entire future, and that might be a lot better because of this technology, then there's like huge value in reducing those risks. And then at the same time, that's way more neglected because as we just said, there's already like a million or so people just working on accelerating AI capabilities, but the number of people trying to avoid these big downside risks is in the thousands.”
18 / recommendation
“One, I think you asked about if you have an AI application skill set, what's something valuable you could work on with that? And one broad area of things is if you think we're going to be facing these big risks, soon that are going to be caused by much more powerful AI, then one strategy you might want to take is think about how you can essentially use AI to address these problems because then your tools are getting better as the problems are getting more severe, they're growing in tandem.”
19 / prediction
“If we avoid concentration of power and loss of control of autonomous AI and a massive bio attack and all of these things, then we're probably going to end up in a world that is far wealthier than today because we'll have this massive population of digital workers who can hopefully give us super good advice about all these problems.”
20 / recommendation
“I do think one of my own personal cause areas that I recommend all the time is just trying to develop more concrete visions of what a positive future and of rewarding life in the context of AGI abundance could look like.”
21 / evaluation
“Having more information about what's happening, these are the kind of things that seem robustly good for navigating things that a lot of people could agree on, even if we don't know the particular end state.”
22 / evaluation
“They have some of the strongest research teams. And they're also in a great position to actually implement the research, which I think is actually a big part of it because you can come up with some idea, but if someone doesn't actually see through all the details in implementing it in the product, it doesn't actually help that much.”
23 / evaluation
“Because many jobs are an experiment as well. And then with the effect of AI, the key thing is the longer your time horizon, the more important gaining career capital and exploring are, because you have more time to make use of those skills you've gained and that information you've gained about what fits you best.”
24 / recommendation
“Ways to just have some kind of pre-commitment in the line where you're going to reassess, I think is really helpful as well.”