Lex Fridman 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
37 published records
01 / uncertainty
“I don’t know it writes Chinese poetry, hypothetical, I know it does, but we haven’t tested for all possible capabilities and we are not explicitly designing them.”
02 / belief
“I think to me, consciousness is closely tied to suffering. So if you can illustrate your capacity to suffer… But I guess with words, there’s so much data that you can pretend you’re suffering and you can do so very convincingly.”
03 / belief
“Oh, I see. That we kind of build Oracle verifiers or rather we build verifiers we believe to be Oracles and then we start to, without any proof, use them as if they’re Oracle verifiers.”
04 / belief
“I think we can generalize it to just prisoners’ dilemma in general. Personal self-interest versus group interest.”
05 / belief
“If we had capability of ahead of the run, before the training run to register exactly what capabilities that next model will have at the end of the training run, and we accurately guessed all of them, I would say you’re right, “We can definitely go ahead with this run.”
06 / belief
“I really hope you are right. I think the scaling hypothesis is correct. We haven’t seen diminishing returns.”
07 / belief
“The previous model we learned about after we finished training it, what it was capable of.”
08 / evaluation
“You can look it up. But even if they’re wrong, I’m just saying this is right now the best we have, this is what humanity came up with as the predicted date.”
09 / uncertainty
“I don’t know if it’s a good general test of consciousness, but it’s a good component of that.”
10 / belief
“Maybe there’ll be a herd-like mentality in how we think, which will kill all creativity and exploration of ideas, the diversity of ideas, or much worse.”
11 / belief
“I think a lot of it is a marketing kind of discussion about the future and it’s a mission about the kind of systems we can create in the long term future.”
12 / belief
“For Yann LeCun, I think there’s a ceiling that happens that we have full control over.”
13 / belief
“I think we need that, but I would change the overall range. So right now it’s negative infinity to positive infinity pain-pleasure axis.”
14 / belief
“Any kid in the garage can train a model. So, a lot of it is, in my opinion, just safety theater, security theater where we saying, “Oh, it’s illegal to train models so big.”
15 / evaluation
“Partially, but we don’t scale for narrow AI for deterministic systems. You can test them, you have edge cases.”
16 / observation
“If we create general superintelligences, I don’t see a good outcome long-term for humanity. The only way to win this game is not to play it.”
17 / belief
“I mean, I can’t speak for other people, for all of them. I think some of them are very ambitious.”
18 / uncertainty
“I guess your answer would be yes, but we don’t know how to do that and we need to invest a lot of effort into figuring out how to do that, but it’s unlikely.”
19 / belief
“We are in a situation where people making more capable systems just need more resources. They don’t need to invent anything, in my opinion.”
20 / belief
“I think there is multiple Turing Award winners that is quite… You can have this one and one just came out kind of similar, “Managing Extreme-“ … one just came out kind of similar, managing extremely high risks.”
21 / belief
“I may be wrong, but I think Stuart Russell’s ideas are all about machines which are uncertain about what humans want and trying to learn better and better what we want.”
22 / uncertainty
“Many things are real on the internet, but I don’t think anyone, if I told them, “Sit down [inaudible 01:54:56] function to feel pain,” they would go beyond having an integer variable called pain and increasing the count. So we don’t know how to do it.”
23 / prediction
“If the only disagreement is that it will take decades, not years for everything I’m saying to materialize, then I can go with that.”
24 / belief
“I think we’ll just get a lot of examples of deceptions from large language models or AI systems.”
25 / observation
“We don’t have to be independent, but the point is you can be, and virtual reality is getting pretty good.”
26 / belief
“I think about a lot of things. So that is X-risk, existential risk, everyone’s dead.”
27 / belief
“Then you would extend that to maybe a very long conversation. I think the Alexa Prize was doing that.”
28 / evaluation
“One is like, man, current software systems are full of bugs and they could do a lot of damage and we don’t know what, they’re unpredictable.”
29 / recommendation
“The transition from horses to cars, there’s a really nice channel that I recommend people check out, Pessimist Archive that documents all the fear-mongering about technology that’s happened throughout history.”
30 / prediction
“You basically have to perform an experiment on 8 billion humans without their consent. And even if they want to give you consent, they can’t because they cannot give informed consent.”
31 / evaluation
“The problem is that it’s very hard to separate capabilities work from safety work.”
32 / evaluation
“It matters how the deaths happen, whether it’s literally murdered by the AI system, then one is a problem, but if it’s accidents because of increased reliance on automation for example, so when airplanes are flying in an automated way, maybe the number of plane crashes increased by 17% or something, and then you’re like, “Okay, do we really want to rely on automation?”
33 / evaluation
“Absolutely true. But in another paper I argue that those accidents do not actually prevent people from continuing with research and actually they kind of serve like vaccines.”
34 / recommendation
“I think one of the challenges here is where is the dangers and the intuition the [inaudible 00:54:40] and others have is, let’s keep in the open building AI systems until the dangers start rearing their heads and they become more explicit, they start being case studies, illustrative case studies that show exactly how the damage by AD systems is done, then regulation can step in.”
35 / evaluation
“I have a paper where I equate passing Turing tests to solving AI complete problems because you can encode any questions about any domain into the Turing test.”
36 / commitment
“I’m personally excited for the future and believe it will be a good one in part because of the amazing technological innovation we humans create, but we must absolutely not do so with blinders on ignoring the possible risks, including existential risks of those technologies.”
37 / observation
“There are people trying to accelerate those timelines, because they feel we’re not getting there quick enough.”