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
27 published records
01 / preference
“You can still buy it, I bought this on Amazon, and it's interesting because it's got a lot of texture.”
02 / belief
“I think we all have this image when we're young that these institutions are these implacable edifices that are evil and all powerful and are able to substantially orchestrate the world with master plans.”
03 / commitment
“There are places where freedom is really valuable. But there's always this thing of – I have a prescriptive ideology that I'd like to impose on the world versus this thing of – I will try to develop the best observational model for what people actually want whether I want them to want it or not.”
04 / uncertainty
“We're not in that world and I'm not particularly concerned about it in the short term. But in the long term, I do think there are worlds that we should be a little bit concerned about where bad things happen, although I don't know what to do about them.”
05 / uncertainty
“I don't know. Maybe the MIT license is still underrated because it's just so simple and bare.”
06 / belief
“I think the more digitized the world has become, the more valuable software becomes, and the more valuable the developers who can create it become.”
07 / belief
“There's a lot of philosophizing and talking, and then there's a lot of behind closed doors, interpretability and alignment work. Because the alignment people have this belief that they shouldn't release their work I think we're going to end up in a world where there's a lot of open source, pure capabilities work, and no open source alignment work for a little while.”
08 / belief
“I think the thing you need to do though to build a good end user application is not only have a good aesthetic and idea, but somehow establish a tight feedback loop with a set of users.”
09 / belief
“I think we finally have people building the products and that's going to just accelerate.”
10 / belief
“We think that's the most likely approach for recognizing the ink but they may find some other approach that we haven't thought of.”
11 / belief
“All the little bits that you have to get right to do a thing and have it work and I hope we got all of them. So I think that's part of it – just not believing that the world is efficient and then just allowing your enthusiasm to cause you to commit to something that turns out to be a lot of work and really hard.”
12 / uncertainty
“I don't know whether that's a consideration or how big of an effect that is, but it's the kind of thing that would make sense to value if you think there are valuable secrets that have not yet proliferated.”
13 / belief
“Before I delve deeper into AI, I do want to talk about GitHub. I think we should start with – You are at Microsoft.”
14 / uncertainty
“For example, with California YIMBY, I don't know the exact amount you seeded it with.”
15 / uncertainty
“I was CEO of GitHub at that time and I thought – I don't know what, but we've got to build some products with this.”
16 / belief
“I think ML engineer salaries and compensation packages will probably be adjusted to try to address this because you don't want your secrets walking out the door.”
17 / belief
“The idea that we might not run into hard problems or that scaling will continue to be worth it on a dollar basis are reasons to be a little bit more pessimistic than the people who have high certainty of GDP increasing by 50% per month which I think some people are predicting.”
18 / preference
“I think I just have a relatively low activation energy to try something and am willing to sort of impulsively jump into stuff and many of those things don't work, but enough of them do that I've been able to accomplish a few things.”
19 / preference
“I think the other problem that people have is that they don't like micromanagement because they don't want bad managers to micromanage, right?”
20 / prediction
“I think if we just let them do it, they'll get it solved. It might take a little bit longer because it's not a huge number of people.”
21 / evaluation
“Right now we use general purpose tools like spreadsheets and things like this a lot, but part of that has to do with the cost of creating software.”
22 / preference
“So we were ending up with some kind of average thing. And I would rather have more high variance outcomes where you either get something that's excellent because it is the expressed vision of a really good auteur or you get a disaster and it didn't work and now you know it didn't work and you can start over.”
23 / prediction
“But if you go to Africa, there is internet now. And the way the internet got there is the technologies that we developed to raise the ceiling in the richest part of the world, which were cell phones and cell towers.”
24 / prediction
“I think some of these labs potentially have 50, 100, 200 percent training efficiency improvement techniques and so there's just a lot of low-hanging fruit on the technique side of things.”
25 / evaluation
“I think Sam Altman did a good job of building that partnership because he knew that he needed access to the resources of a company like Microsoft to build large-scale AI and eventually AGI.”
26 / prediction
“I think we are seeing a collaboration occur because the math is sort of pretty simple.”
27 / prediction
“The exception would be really disagreeable people who are just naturally disagreeable. So I think the future belongs to the autists in some sense because they don't care what other people think as much.”