Nathan Lambert

speaker

1,814 appearances 3 recordings 2 series first heard Feb 2025 last heard 1 Feb

Nathan Lambert’s voice in public audio — every appearance, attributed to the second.

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recordings per month · last 12 months

Recordings per month over the last 12 months — 2 in all, peaking in Feb 2026 with 1.

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Lex Fridman Podcast · #490 – State of AI in 2026: LLMs, Coding, Scaling Laws, China, Agents, GPUs, AGI · 1 Feb 2026 podcast

selfishly, I'll promote a bunch of Western companies.

So both in the US and Europe have these fully open models.

So I work at Allen Institute for AI.

We've been building Ulmo, which releases data and code and all of this.

And now we have actual competition for people that are trying to release everything so that other people can train these models.

So there's

The Institute for Foundation Models, or slash LM360, which is like had their K2 models of various types.

Aperdis is a Swiss research consortium.

Hugging Face has small LM, which is very popular.

And NVIDIA's Nematron has started releasing data as well.

And then Stanford's Marin Community Project, which is kind of making it so there's a pipeline for people to open a GitHub issue and implement a new idea and then have it run in a stable language modeling stack.

So this space...

That list was way smaller in 2024, so I think it was just AI2.

So that's a great thing for more people to get involved in to understand language models, which doesn't really have a Chinese company that has an analog.

While I'm talking, I'll say that the Chinese open language models tend to be much bigger, and that gives them this higher peak performance as MOEs, where a lot of these things that we like a lot, whether it was Gemma...

And Nematron have tended to be smaller models from the US, which is starting to change from the US and Europe.

Mistral Large 3 came out, which was a giant MOE model, very similar to DeepSeek architecture in December.

And then a startup, RCAI, and both Nematron have changed.

Nematron and NVIDIA have teased MOE models of this way bigger than 100 billion parameters, like this 400 billion parameter range coming in this Q1 2026 timeline.

So I think this kind of balance is set to change this year in terms of what people are using the Chinese versus US open models for, which I'm personally going to be very excited to watch.

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