Nathan Lambert: belief

Transcript context

…No, that's great. It, it's kind of what happened with the code interpreter episode when Sean and I had access for about five hours and Simon was like, I've been playing with this for weeks and add all the, the insights scoops. So I think this will be a, a good episode. Maybe Nathan, you just want to give people a little bit of background on what you do at Hugging and Face and yeah, the, your experience with the LAMA two kinda preview. Yeah. So I've been a researcher and helping lead reinforcement learning from human feedback efforts at Hugging and face, which really means I do some research and I try to figure out how to fine tune models to do what people want. 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. I think the paper is a phenomenal artifact and it's clear that the model is really strong in a lot of areas. And then kind of the big picture trends of where open source is going. Like this is a clear step in a direction that a lot of people wanted, but weren't sure if it was gonna happen. Yep. What are some of the things that stood out to you? I think to a lot of the AI engineers audience that we have, they're not as deep into the details of the papers. We'd love to get a, a read from somebody like you who's a much deeper at a, you know, model research level.…

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