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What if a model finds an optimization that surprises the engineers who have spent years working on that system? What, exactly, has it understood?
I brought that question to OpenAI’s Phil Tillet and Matt Ferrari, whose work involves making AI cheaper and more accessible. They’re increasingly doing that work with the models themselves.
Matt talks about research ideas his team used to dismiss because the engineering would be too complicated. Now they can give a model years of earlier research and ask it to explore what might work. They’re using models to help improve the smaller models behind…
Website: inference.mave.digital
