Why hasn't longer-horizon training slowed AI progress?
This article explores why AI progress hasn't significantly slowed despite longer and harder reinforcement learning tasks. The author proposes three reasons: efficiency gains from fixing bugs in training code, human difficulty in evaluating intelligence beyond human level, and the importance of traits other than intelligence (e.g., persistence) for capability.
Why hasn't longer-horizon training slowed AI progress?
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