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Providing Greater Access to LLMs with Brandon Duderstadt, Co-Founder and CEO of Nomic AI
Gradient Dissent: Conversations on AI
Comparing Foundation Models With Data Kernels
RLA Jeff is in my mind fine tuning when it's hard to define your objective. It first builds a model that tries to predict what people want, almost a model of that objective function and then trains a model to maximize the reward according to that objective function. Do you also do RLA Jeff on your models? And how does that fit in with fine tuning? Like do you view that as a kind of a specialist type of fine tuning or? Yeah. I'm happy to talk more about that if you want to go in that direction.
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