Dwarkesh Patel Publishes '8 Predictions for the Era of Continual Learning' — Argues Locking In AI Safety Regimes Now Is a Mistake
Dwarkesh Podcast·medium signal
Patel's Aug 7 essay and episode argues that continual learning breaks the assumption underpinning nearly every current AI regulation proposal: that a model is trained once, safety-checked, then deployed frozen. If base models update daily from real work sessions, pre-deployment evaluation becomes a snapshot of something that no longer exists, which is why he thinks it's unwise to harden regulatory safety regimes right now. The piece is already being cited in governance circles — Miles Brundage picked it up in the context of entity-based rather than model-based frontier regulation.