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Reflections on NeurIPS: There's always a big theme people seem to be preoccupied with. This year, it was the continuation of scaling/progress. Will it continue? What will the next generation of models hold? I even got to sass Dylan Patel (not on bsky) over it. Here are my personal thoughts 🧵

None of this is novel. Smarter people than me are saying the same thing. But it merits repeating as everyone (students, VCs, scientists, practitioners) nervously swings from hype to "it's all over" to "we're so back." Admire the progress. Focus on making this stuff as useful as possible

1. Of course AI is going to keep getting better. Technological progress isn't going to stop or "hit a wall." That's very safe to say. There's a ton of low-hanging fruit.

2. Scaling "laws" ("trends"?) as formally defined (log loss decreases linearly with log training FLOPs when properly allocated between parameters and data) may or may not continue. There's no reason to doubt that it will continue, yet extrapolating far out is uncertain.