Eventually—but agency is not sequence prediction + a few hacks. The remaining problems are hard. Massive compute, investment, and enthusiasm will lead to faster progress—i objected to 5 year timelines after chatgpt, but now it’s been a couple years. I think 5 years is still too soon but I’m not sure.
Edit: After Nathan offered to bet my claim is false, I bet no on his market at 82% claiming (roughly) that inference compute is as valuable as training computer for GPT-5: https://manifold.markets/NathanHelmBurger/gpt5-plus-scaffolding-and-inference. I expect this will be difficult to resolve because o1 is the closest we will get to a GPT-5 and it presumably benefits from both more training (including RLHF) and more inference compute. I think its perfectly possible that well thought out reinforcement learning can be as valuable as pretraining, but for practical purposes I expect scaling inference compute on a base model will not see qualitative improvements. I will reach out about more closely related bets.
Eventually—but agency is not sequence prediction + a few hacks. The remaining problems are hard. Massive compute, investment, and enthusiasm will lead to faster progress—i objected to 5 year timelines after chatgpt, but now it’s been a couple years. I think 5 years is still too soon but I’m not sure.
Edit: After Nathan offered to bet my claim is false, I bet no on his market at 82% claiming (roughly) that inference compute is as valuable as training computer for GPT-5: https://manifold.markets/NathanHelmBurger/gpt5-plus-scaffolding-and-inference. I expect this will be difficult to resolve because o1 is the closest we will get to a GPT-5 and it presumably benefits from both more training (including RLHF) and more inference compute. I think its perfectly possible that well thought out reinforcement learning can be as valuable as pretraining, but for practical purposes I expect scaling inference compute on a base model will not see qualitative improvements. I will reach out about more closely related bets.