Speakers in the public record
Claim mix
belief 8evaluation 5preference 4prediction 2commitment 1uncertainty 1observation 1
Evidence policy
Every row below preserves an exact excerpt. Identified speakers are linked; unresolved voices are labeled and excluded from people counts.
Claim ledger
The useful parts, with receipts.
22 published records
“It’s interesting because you wrote this essay in 2019 titled “The Bitter Lesson,” and this is the most influential essay, perhaps, in the history of AI. But people have used that as a justification for scaling up LLMs because, in their view, this is the one scalable way we have found to pour ungodly amounts of compute into learning about the world.”
- Publisher
- Dwarkesh Podcast
“I like John McCarthy’s definition that intelligence is the computational part of the ability to achieve goals.”
- Publisher
- Dwarkesh Podcast
“As we move towards the era of experience, as you call it, this prior is going to be the basis on which we teach these models from experience, because this gives them the opportunity to get answers right some of the time.”
- Publisher
- Dwarkesh Podcast
“In both the case of learning from imitation versus experience and on the question of goals, I think there’s some interesting analogies.”
- Publisher
- Dwarkesh Podcast
“If you want to understand what it is that enables humans to go to the moon or to build semiconductors, I think the thing we want to understand is what makes that happen.”
- Publisher
- Dwarkesh Podcast
“I agree that the kind of thing you’re talking about is necessary regardless of whether you start from LLMs or not.”
- Publisher
- Dwarkesh Podcast
“I agree with all four of those arguments and the implication. I also agree that succession contains a wide variety of possible futures.”
- Publisher
- Dwarkesh Podcast
“The researchers will figure it out eventually. Number three, we won’t stop just with human-level intelligence.”
- Publisher
- Dwarkesh Podcast
“If we thought, “Oh, the future generation will be Nazis, I think we’d be quite concerned about just handing off power to them.” So I agree that this is not super dissimilar to worrying about more capable future humans, but I don’t think that addresses a lot of the concerns people might have about this level of power being attained this fast with entities we don’t fully understand.”
- Publisher
- Dwarkesh Podcast
“I think there also should be a component having to do with your increasing understanding of your environment.”
- Publisher
- Dwarkesh Podcast
“Then you go into the learning from experience RL regime. But I think there’s a lot of imitation learning happening with humans.”
- Publisher
- Dwarkesh Podcast
“I think argument is useful. I do want to complete this thought. Joseph Henrich has this interesting theory about a lot of the skills that humans have had to master in order to be successful.”
- Publisher
- Dwarkesh Podcast
“In the old days, it was interesting because things like search and learning were called weak methods because they’re just using general principles, they’re not using the power that comes from imbuing a system with human knowledge.”
- Publisher
- Dwarkesh Podcast
“What is intelligence? The problem is to understand your world. Reinforcement learning is about understanding your world, whereas large language models are about mimicking people, doing what people say you should do.”
- Publisher
- Dwarkesh Podcast
“I’m not trying to kickstart this initial crux again, but I’m just genuinely curious because I think I might be using the term differently.”
- Publisher
- Dwarkesh Podcast
“It’ll say, “Okay, I’m going to approach this problem using this approach first.” It’ll write this out and be like, “Oh wait, I just realized this is the wrong conceptual way to approach the problem.”
- Publisher
- Dwarkesh Podcast
“You can’t have prior knowledge if you don’t have ground truth, because the prior knowledge is supposed to be a hint or an initial belief about what the truth is.”
- Publisher
- Dwarkesh Podcast
“I think a better word would be “the network” because I think you mean the network.”
- Publisher
- Dwarkesh Podcast
“Then what I usually say is that this is all human-centric. But if we step aside from being a human and just take the point of view of the universe, this is I think a major stage in the universe, a major transition, a transition from replicators.”
- Publisher
- Dwarkesh Podcast
“Maybe you’re using “context” because in large language models all that information has to go into the context window.”
- Publisher
- Dwarkesh Podcast
“I like the way you consider that obvious, because I consider the opposite obvious.”
- Publisher
- Dwarkesh Podcast
“Your examples are all, “Well, really you have to” because you can teach it, but there’s all the little idiosyncrasies of the particular life they’re leading and the particular people they’re working with and what they like, as opposed to what average people like.”
- Publisher
- Dwarkesh Podcast