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Nathan Lambert

Published podcast speaker

Claims
117
Episodes
4
Shows
2
Named items
3

Books, apps, and tools

The evidenced stack.

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app / likes

ChatGPT app

“This is why I like the ChatGPT app, because it gives the AI a home in your computer where you can focus on it, rather than just being another tab in my mess of internet options.”

Lex Fridman Podcast · 1 Feb 2026

Evidence receipt · Source ↗

app / likes

ChatGPT

“This is why I like the ChatGPT app, because it gives the AI a home in your computer where you can focus on it, rather than just being another tab in my mess of internet options.”

Lex Fridman Podcast · 1 Feb 2026

Evidence receipt · Source ↗

book / recommends

Season of the Witch

“It’s a great book, Season of the Witch; I recommend it. A bunch of my SF friends who do get out recommended it to me.”

Lex Fridman Podcast · 1 Feb 2026

Evidence receipt · Source ↗

Claim ledger

What Nathan said.

69 transcript-backed records

02 / belief

I think the question is if the companies can support the valuations. I’d see the AI companies being looked at in some ways like AWS, Azure, and GCP, which are all competing in the same space and all very successful businesses.

“I think the question is if the companies can support the valuations. I’d see the AI companies being looked at in some ways like AWS, Azure, and GCP, which are all competing in the same space and all very successful businesses.”
Speaker
Nathan Lambert
Publisher
Lex Fridman Podcast

03 / belief

I think when you look at China, the biggest reason is that they want people around the world to use these models, and I think a lot of people will not.

“I think when you look at China, the biggest reason is that they want people around the world to use these models, and I think a lot of people will not.”
Speaker
Nathan Lambert
Publisher
Lex Fridman Podcast

04 / belief

I think a lot of that’s happened at labs this year; there are new hot things, whether it’s coding environments or web navigation, and you just need to bring in new data and change your whole pre-training so that your post-training can work better.

“I think a lot of that’s happened at labs this year; there are new hot things, whether it’s coding environments or web navigation, and you just need to bring in new data and change your whole pre-training so that your post-training can work better.”
Speaker
Nathan Lambert
Publisher
Lex Fridman Podcast

08 / belief

I think that dream is actually kind of dying. As you talked about with the specialized models where it’s like… and multimodal is often… like, video generation is a totally different thing.

“I think that dream is actually kind of dying. As you talked about with the specialized models where it’s like… and multimodal is often… like, video generation is a totally different thing.”
Speaker
Nathan Lambert
Publisher
Lex Fridman Podcast

09 / belief

I think that that’s hard but if you want to scope the maximum possible impact with minimum compute, it’s something like that—which is just get very narrow, and it takes learning of where the models are going.

“I think that that’s hard but if you want to scope the maximum possible impact with minimum compute, it’s something like that—which is just get very narrow, and it takes learning of where the models are going.”
Speaker
Nathan Lambert
Publisher
Lex Fridman Podcast

10 / belief

I think OpenAI’s definition is somewhat related to that—an AI that can do a certain number of economically valuable tasks—which I don’t really love as a definition, but it could be a grounding point.

“I think OpenAI’s definition is somewhat related to that—an AI that can do a certain number of economically valuable tasks—which I don’t really love as a definition, but it could be a grounding point.”
Speaker
Nathan Lambert
Publisher
Lex Fridman Podcast

17 / belief

I think that there’s—we’ll get to continual learning later, but there’s a lot of buzz around certain areas of AI, but no one knows when the next step function will really come.

“I think that there’s—we’ll get to continual learning later, but there’s a lot of buzz around certain areas of AI, but no one knows when the next step function will really come.”
Speaker
Nathan Lambert
Publisher
Lex Fridman Podcast

18 / belief

We saw multiple demos in 2025 of, like, Claude can use your computer, or OpenAI had operator, and they all suck. So they’re investing money in this, and I think that’ll be a good example.

“We saw multiple demos in 2025 of, like, Claude can use your computer, or OpenAI had operator, and they all suck. So they’re investing money in this, and I think that’ll be a good example.”
Speaker
Nathan Lambert
Publisher
Lex Fridman Podcast

20 / belief

Eventually someone else will still have the idea. So I think that in that way, Jensen is helping manifest this GPU revolution much faster and much more focused than it would be without having a person like him there.

“Eventually someone else will still have the idea. So I think that in that way, Jensen is helping manifest this GPU revolution much faster and much more focused than it would be without having a person like him there.”
Speaker
Nathan Lambert
Publisher
Lex Fridman Podcast

22 / belief

On the Manhattan Project thing, one of my funny things looking at them is I think that a Manhattan Project-like thing for open models would actually be pretty reasonable, because it wouldn’t cost that much.

“On the Manhattan Project thing, one of my funny things looking at them is I think that a Manhattan Project-like thing for open models would actually be pretty reasonable, because it wouldn’t cost that much.”
Speaker
Nathan Lambert
Publisher
Lex Fridman Podcast

23 / belief

Whenever they make a release, they’re always talking about how their GPUs are hurting. And I think in one of these gpt-oss-120b release sessions, Sam Altman said, “Oh, we’re releasing this because we can use your GPUs.

“Whenever they make a release, they’re always talking about how their GPUs are hurting. And I think in one of these gpt-oss-120b release sessions, Sam Altman said, “Oh, we’re releasing this because we can use your GPUs.”
Speaker
Nathan Lambert
Publisher
Lex Fridman Podcast

24 / belief

I think that when they’re close to this automated software engineer, what it will be good at is traditional ML systems and front end—the model is excellent at those—but the distributed ML, the models are actually really quite bad at because there’s so little training data on doing large-scale distributed learning and things.

“I think that when they’re close to this automated software engineer, what it will be good at is traditional ML systems and front end—the model is excellent at those—but the distributed ML, the models are actually really quite bad at because there’s so little training data on doing large-scale distributed learning and things.”
Speaker
Nathan Lambert
Publisher
Lex Fridman Podcast

25 / belief

Anthropic, I think, bought thousands of books and scanned them and was cleared legally for that because they bought the books, and that is going through the system.

“Anthropic, I think, bought thousands of books and scanned them and was cleared legally for that because they bought the books, and that is going through the system.”
Speaker
Nathan Lambert
Publisher
Lex Fridman Podcast

29 / belief

I think the leap from the AI singularity to scaling up mass manufacturing in the US because we have a massive AI advantage is one that is troubled by a lot of political and other challenging problems.

“I think the leap from the AI singularity to scaling up mass manufacturing in the US because we have a massive AI advantage is one that is troubled by a lot of political and other challenging problems.”
Speaker
Nathan Lambert
Publisher
Lex Fridman Podcast

30 / belief

I think of the continual learning thing as a research problem where there could be a breakthrough that makes transformers work way better at this and it’s cheap.

“I think of the continual learning thing as a research problem where there could be a breakthrough that makes transformers work way better at this and it’s cheap.”
Speaker
Nathan Lambert
Publisher
Lex Fridman Podcast

31 / belief

Linking to what’s happening in big tech, this AI 2027 report leans into the singularity idea where I think research is messy and social and largely in the data in ways that AI models can’t process.

“Linking to what’s happening in big tech, this AI 2027 report leans into the singularity idea where I think research is messy and social and largely in the data in ways that AI models can’t process.”
Speaker
Nathan Lambert
Publisher
Lex Fridman Podcast

33 / belief

I think we need to make a point clear on why the time is now for people that don’t think about this, because essentially, with export controls, you’re making it so China cannot make or get cutting edge chips.

“I think we need to make a point clear on why the time is now for people that don’t think about this, because essentially, with export controls, you’re making it so China cannot make or get cutting edge chips.”
Speaker
Nathan Lambert
Publisher
Lex Fridman Podcast

34 / belief

I think if you have the demand and the money is on the line, the American companies figure it out. It’s going to take handholding with the government, but I think that the culture helps TSMC break through and it’s easier for them.

“I think if you have the demand and the money is on the line, the American companies figure it out. It’s going to take handholding with the government, but I think that the culture helps TSMC break through and it’s easier for them.”
Speaker
Nathan Lambert
Publisher
Lex Fridman Podcast

35 / belief

There’s a lot of really specific things you can do, but all of this is about fine-tuning to human preferences. And the final stage is much newer and will link to what is done in R1 and these reasoning models is I think OpenAI’s name for this, they had this new API in the fall, which they called the reinforcement fine-tuning API.

“There’s a lot of really specific things you can do, but all of this is about fine-tuning to human preferences. And the final stage is much newer and will link to what is done in R1 and these reasoning models is I think OpenAI’s name for this, they had this new API in the fall, which they called the reinforcement fine-tuning API.”
Speaker
Nathan Lambert
Publisher
Lex Fridman Podcast

37 / belief

I actually don’t know why input and output tokens are more expensive, but I think essentially output tokens, you have to do more computation because you have to sample from the model.

“I actually don’t know why input and output tokens are more expensive, but I think essentially output tokens, you have to do more computation because you have to sample from the model.”
Speaker
Nathan Lambert
Publisher
Lex Fridman Podcast

38 / belief

I think there’s been some people that are higher level economics understanding say that as you go from 1 billion of smuggling to 10 billion, it’s like you’re hiding certain levels of economic activity and that’s the most reasonable thing to me is that there’s going to be some level where it’s so obvious that it’s easier to find this economic activity.

“I think there’s been some people that are higher level economics understanding say that as you go from 1 billion of smuggling to 10 billion, it’s like you’re hiding certain levels of economic activity and that’s the most reasonable thing to me is that there’s going to be some level where it’s so obvious that it’s easier to find this economic activity.”
Speaker
Nathan Lambert
Publisher
Lex Fridman Podcast

39 / belief

There are other international things that are worrying, but there’s just fundamental human goodness and trying to amplify that. I think we’re on a tenuous time.

“There are other international things that are worrying, but there’s just fundamental human goodness and trying to amplify that. I think we’re on a tenuous time.”
Speaker
Nathan Lambert
Publisher
Lex Fridman Podcast

45 / belief

I think the clearest example we have, because Meta is also open, they talk about order of 60k to 100k H100 equivalent GPUs in their training clusters.

“I think the clearest example we have, because Meta is also open, they talk about order of 60k to 100k H100 equivalent GPUs in their training clusters.”
Speaker
Nathan Lambert
Publisher
Lex Fridman Podcast

48 / belief

I would say that the long tail of use is going to go inside of AI, which is if you scrape trillions of tokens of data, you’re not looking and saying, “This one New York Times article is so important to me.

“I would say that the long tail of use is going to go inside of AI, which is if you scrape trillions of tokens of data, you’re not looking and saying, “This one New York Times article is so important to me.”
Speaker
Nathan Lambert
Publisher
Lex Fridman Podcast

49 / belief

We know that a lot of the American companies are very invested in safety, and that is the central culture of a place like Anthropic. And I think Anthropic sounds like a wonderful place to work, but if safety is your number one goal, it takes way longer to get artifacts out.

“We know that a lot of the American companies are very invested in safety, and that is the central culture of a place like Anthropic. And I think Anthropic sounds like a wonderful place to work, but if safety is your number one goal, it takes way longer to get artifacts out.”
Speaker
Nathan Lambert
Publisher
Lex Fridman Podcast

51 / belief

For the past few years, the highest cost human data has been in these preferences, which is comparing, I would say, highest cost and highest total usage, so a lot of money has gone to these pairwise comparisons where you have two model outputs and a human is comparing between the two of them.

“For the past few years, the highest cost human data has been in these preferences, which is comparing, I would say, highest cost and highest total usage, so a lot of money has gone to these pairwise comparisons where you have two model outputs and a human is comparing between the two of them.”
Speaker
Nathan Lambert
Publisher
Lex Fridman Podcast

53 / belief

I think in terms of internet posts and things that people have been measuring, it hasn’t been a exponential increase or something extremely measurable and things you’re talking about with voice calls and stuff like that, it could be in modalities that are harder to measure.

“I think in terms of internet posts and things that people have been measuring, it hasn’t been a exponential increase or something extremely measurable and things you’re talking about with voice calls and stuff like that, it could be in modalities that are harder to measure.”
Speaker
Nathan Lambert
Publisher
Lex Fridman Podcast

54 / belief

Very long-term motivated in how the ecosystem of AI should work. And I think from a Chinese perspective, he wants a Chinese company to build this vision.

“Very long-term motivated in how the ecosystem of AI should work. And I think from a Chinese perspective, he wants a Chinese company to build this vision.”
Speaker
Nathan Lambert
Publisher
Lex Fridman Podcast

56 / belief

I think if you zoom into any of the details to look at like the agreement number, so how if you look at a test set, you'll have a chosen and rejected and you can take the reward model you're training, pass in those completions and you see if the chosen predicted reward, so the scalar number is higher than the rejected predicted reward.

“I think if you zoom into any of the details to look at like the agreement number, so how if you look at a test set, you'll have a chosen and rejected and you can take the reward model you're training, pass in those completions and you see if the chosen predicted reward, so the scalar number is higher than the rejected predicted reward.”
Speaker
Nathan Lambert
Publisher
Latent Space

58 / belief

I think big labs are indexed on their own base models so they don't know like what's swapping between CloudBase or GPT-4 base how that would change any notion of preference or what you do with RLHF.

“I think big labs are indexed on their own base models so they don't know like what's swapping between CloudBase or GPT-4 base how that would change any notion of preference or what you do with RLHF.”
Speaker
Nathan Lambert
Publisher
Latent Space

59 / belief

I think the things that people see now is like the small models don't really handle nuance as well and they could be more repetitive even if they have really good instruction tuning.

“I think the things that people see now is like the small models don't really handle nuance as well and they could be more repetitive even if they have really good instruction tuning.”
Speaker
Nathan Lambert
Publisher
Latent Space

62 / belief

I think the reason why it's not really talked about is just because the RLHF techniques that people use were built in labs like OpenAI and DeepMind where there are some of these people.

“I think the reason why it's not really talked about is just because the RLHF techniques that people use were built in labs like OpenAI and DeepMind where there are some of these people.”
Speaker
Nathan Lambert
Publisher
Latent Space

63 / belief

I think if the people are kind of locked into using synthetic data, people also think that synthetic data is like GPT-4 is more accurate than humans at labeling preferences.

“I think if the people are kind of locked into using synthetic data, people also think that synthetic data is like GPT-4 is more accurate than humans at labeling preferences.”
Speaker
Nathan Lambert
Publisher
Latent Space

64 / belief

I think in the next year that'll probably get made more concrete by the community on like if you can easily draw out like if chain of thought reasoning is more like RL, we can talk about that more later.

“I think in the next year that'll probably get made more concrete by the community on like if you can easily draw out like if chain of thought reasoning is more like RL, we can talk about that more later.”
Speaker
Nathan Lambert
Publisher
Latent Space

65 / belief

I think I saw people criticizing it for like just being like safety washing from the fact that they're like talking about GPT-2 still, which is such a kind of like odd model to focus on.

“I think I saw people criticizing it for like just being like safety washing from the fact that they're like talking about GPT-2 still, which is such a kind of like odd model to focus on.”
Speaker
Nathan Lambert
Publisher
Latent Space

66 / belief

Like hugging face. I think every. Library, like all these people at Hugging and Face, were working super hard this weekend to make day zero support for Llama2.

“Like hugging face. I think every. Library, like all these people at Hugging and Face, were working super hard this weekend to make day zero support for Llama2.”
Speaker
Nathan Lambert
Publisher
Latent Space

67 / belief

Generally we're trying to operate in the scale a little bit smaller than what Meta is doing cuz we obviously don't have that kind of resources at a startup. So I do a lot of technical research and also try to actually engage and communicate that with the community and specifically, Llama, I think I was most interested on kind of the research side.

“Generally we're trying to operate in the scale a little bit smaller than what Meta is doing cuz we obviously don't have that kind of resources at a startup. So I do a lot of technical research and also try to actually engage and communicate that with the community and specifically, Llama, I think I was most interested on kind of the research side.”
Speaker
Nathan Lambert
Publisher
Latent Space
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