Dwarkesh Podcast / 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
25 published records
01 / evaluation
“He had some preconceived theories first. It seems like this is less and less the way we make progress, just because the data is so much more massive and useful.”
02 / evaluation
“Right now we’re going through a cognitive version of the Copernican revolution, where we used to think that human intelligence is the center of the universe, and now we’re seeing that there are very different types of intelligence out there with very different strengths and weaknesses.”
03 / uncertainty
“I don’t know how you can quantify that in such a precise way that you can start doing reinforcement learning.”
04 / recommendation
“One takeaway I had from reading and watching your stuff on the cosmic distance ladder… By the way, I highly recommend people watch your series with 3Blue1Brown on the cosmic distance ladder.”
05 / belief
“I think one aspect of science is that it’s not just creating a new theory and validating it, but communicating it to others.”
06 / belief
“I feel like a big crux in these conversations about how good AI will be for science is, I think you said this, that they’re using existing techniques and modifying them.”
07 / uncertainty
“We don’t know. Some problems have been basically solved by pure brute force. The four color theorem is a famous example.”
08 / evaluation
“Eventually, we’ve systematically mapped out what doesn’t work and what does work, and we can see a path forward, but it’s evolving with our discussion.”
09 / belief
“Whereas with research, the reason we care about solving the Millennium Prize Problems is that presumably that in the process of solving them, we discover new mathematical objects or new techniques that advance our civilization’s understanding of mathematics.”
10 / belief
“On the one hand, I think the type of papers that I would write today, if I had to do them without AI assistance, would definitely take five times longer.”
11 / uncertainty
“You’re trying to climb as many of these cliffs as possible, but it’s in the dark. We don’t know which ones are tall, which ones are short.”
12 / observation
“The ancient Athenians were like, “This can’t be because if the earth is going around the sun, we should see the relative position of the stars change as we’re going around the sun, and the only way that wouldn’t be the case is if they’re so far away that you don’t notice any parallax,” which is actually the correct implication.”
13 / belief
“I think there’ll be a similar thing happening with the hundreds of really prestigious, difficult math problems out there.”
14 / belief
“Suppose the AI figures it out, and latent in the Lean is some brand-new construction which, if we realized its significance, we would be able to apply in all these different situations.”
15 / uncertainty
“I don’t know if it’s still correct, but as of a month ago you said that there had been a pause because the low-hanging fruit had been picked.”
16 / commitment
“One big question I have is how plausible is it that if we just keep training AIs—they get better and better at solving problems in Lean—that they will continue to solve more and more impressive problems, and then we will be surprised at how little insight we got from some Lean solution to proving the Riemann hypothesis or something.”
17 / prediction
“I think we would very rapidly abandon any cryptography based on the primes, because if there was one pattern that we didn’t know about, there are probably more, and these patterns can lead to exploits in crypto.”
18 / prediction
“I think within a decade, a lot of things that math students currently do—what we spend the bulk of our time doing and a lot of stuff we put in our papers today—can be done by AI.”
19 / preference
“If there was some semi-formal framework where this could be done semi-automatically in a way that isn’t easily hackable... It’s really important with these formal proof assistants that there are no backdoors or exploits you can use to somehow get your certified proof without actually proving it, because reinforcement learning is just so good at finding these backdoors.”
20 / prediction
“I think AI-type tools will actually revolutionize the experimental side of math, where you don’t care so much about individual problems and the process of solving them, but you want to gather large-scale data about what things work and what things don’t.”
21 / prediction
“We don’t even have the paradigms to really take full advantage of it. But we will, and then science will be unrecognizable after that, I think.”
22 / preference
“When there are holes in the argument where none of the things are working, then what do you do? They can suggest random things, but often I find that trying to chase them down to make them work, and finding they don’t work, wastes more time than it saves.”
23 / prediction
“I think in the future, there will be entire professions of mathematicians who might take a giant Lean-generated proof and do some ablation on it, trying to remove parts of it and find more elegant ways.”
24 / prediction
“I think AI has driven the cost of idea generation down to almost zero, in a very similar way to how the internet drove the cost of communication down to almost zero.”
25 / recommendation
“I highly recommend people watch your series with 3Blue1Brown on the cosmic distance ladder.”