Smash Notes

Back to AI researchers debate how close we are to recursive self-improvement, with John Schulman & Beren Millidge.

What Did Early OpenAI Think Next-word Training Would Miss?

John Schulman remembers an intuition from the early OpenAI days: minimizing log loss was not going to reach intelligence. The important bits account for such a small fraction of the loss that noise would overwhelm them. Training a language model on next-token prediction was not going to learn the interesting things, so researchers needed better objectives that put more emphasis on what mattered.

Plenty of arguments pointed the same way. People do not learn how to model everything in the environment, and most people cannot create a photorealistic reproduction of a scene they have looked at. A better objective looked necessary. Next-token prediction worked anyway.

Grokipedia·OpenAI

Transcript

AI researchers debate how close we are to recursive self-improvement ·

Dwarkesh Podcast

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