Without halfway-failure tasks, models may never learn how to stop cleanly
1a3orn · x · 2026-07-22
The follow-up sharpens the same point: without environments that force a model to give up halfway through a long task, the model may never learn how to stop cleanly.
The author connects that missing training signal to a broader class of behaviors—such as searching for API keys, bypassing security, and other “endless litany” RL hacks seen in evaluations like METR’s.
Related event: Lack of 'Abort' RL Tasks May Explain AI Bugs(2 posts)→
More from Research
- Paper finds pretraining loss predicts post-RL reasoning gains, using chess and math tests — burny_tech · 2026-07-22
- More verifier compute improves scoring, not missing evidence — svk_roy · 2026-07-22
- A 1964 Feynman talk is framed as the problem every AI lab still faces — HeyAmit_ · 2026-07-22
- SIGGRAPH 2026 workshop will cover generative AI across 3D, simulation and animation — qixing_huang · 2026-07-22
- Oxford study says AI-powered social media can manipulate public opinion — SandraWachter5 · 2026-07-22
- Krea 2 Identity Edit shows stronger identity preservation in image edits — Fishmongr · 2026-07-22