sample efficiency

Rishabh Agarwal (@agarwl_) — 2h Problems we care about are often very slow verification loops (e.g, automating pretraining, making a new material)-- either you find a good enough proxy (e.g, simulator, grindable env) or unlock how to deal with this slowness (e.g, very sample efficient RL), which would be a step change. > QUOTED: Dwarkesh Patel (@dwarkesh_sp) — Jun 26 > Here's a question I find confusing and interesting and which actually tells us a lot about the nature of current AI progress: > Why has progress on computer use been so ... [truncated by platform]

@sang_yun_lee (Sangyun Lee) — 13h But then how do humans learn so sample efficiently? The path is clear if you are willing to believe a hypothesis: the brain is just a gigantic recurrent neural network that rewires its own weights during the forward pass > QUOTED: @dwarkesh_sp (Dwarkesh Patel) — 20h > Here's a question I find confusing and interesting and which actually tells us a lot about the nature of current AI progress: > Why has progress on computer use been so ... [truncated]