Toby Ord argues reinforcement learning may impose a steep efficiency bottleneck

Toby Ord estimated that frontier reinforcement learning extracts roughly 1,000 to 1,000,000 times less learning signal per token than pretraining and may trade generality for benchmark performance. He presented the claim as a quantified bottleneck with explicit caveats, not as proof that capability progress has ended.