Andreessen: AI models keep improving when trained far past expected limits
Marc Andreessen · Startup Building: Challenges & Opportunities · May 2, 2024 · at 47:58
Marc Andreessen, co-founder of Andreessen Horowitz (a16z), discusses recent findings in LLM training scaling, referencing Meta's Llama model experiments.
“There's been this theory for a long time that you basically take, you take input into train and AI, and you get the, have the chips all set up and everything, and then you train it up to a point, you let the training process run for a certain amount of time, and then you hit a point of diminishing returns, and at some point you stop training and release it and you just, at some point you just can't make the model smarter by training it more, and it's just, it's turning out, there's more and more cases now where people are realizing, no, actually, if you keep training it, and actually, if you keep training it to what people used to think were kind of, Absurd extents. Like if you train it to be like a hundred, you know, train it for a hundred times longer than the sort of predictions would have suggested.”
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