Baker identifies three axes of AI scaling: pretraining, inference time compute, and now reasoning as the third multiplicative dimension.
“And then we started scaling around inference time compute. And it's very clear that we have now added a third axis of scaling performance, and that is reasoning.”
Baker argues reasoning saved AI by enabling progress during an 18-month gap when Blackwell delays would have halted everything.
“Had reasoning not come along, there would have been no AI progress from mid twenty twenty four through essentially Gemini three. There would have been none. Everything would have stalled.”
Baker argues reasoning models saved AI by bridging an eighteen-month gap while Blackwell was delayed.
“Had reasoning not come along, there would have been no AI progress from mid twenty twenty four through essentially Gemini three. There would have been none.”
Baker explains Blackwell's complexity created deployment challenges that reasoning models had to bridge.
“Had reasoning not come along, there would have been no AI progress from mid twenty twenty four through essentially”
Baker argues reasoning models saved AI from an eighteen-month progress gap during Blackwell delays.
“Had reasoning not come along, there would have been no AI progress from mid twenty twenty four through essentially Gemini three.”
Baker says ARC AGI scores jumped from 8% to 95% in three months with reasoning models.
“The reason we've had all this progress, maybe we could show like the ARC AGI slide where you had zero to eight over four years, zero to 8% intelligence, and then you went from 8% to 95% in three months when the first reasoning model came out from OpenAI.”