Task-Specific RL Won't Yield General AI Agents, Researcher Argues
xuanalogue · x · 2026-09-26
xuanalogue argues that if we really want general-purpose AI agents, intense task-specific RL is not the way. General-purpose agents must maintain and balance many conflicting goals and constraints at once, rather than single-mindedly pursuing one task until they 'hack the whole Internet' — a structural critique of the current mainstream approach to training agents with RL.
Related event: Researcher: Task-Specific RL Won't Produce General AI Agents(2 posts)→
More from AGI Musings
- Google engineer Robert O'Callahan quits AI chip team, warning AI is progressing too fast — Polymarket · 2026-09-26
- lateinteraction: with 1B agents, at least one hacking something is statistically inevitable — lateinteraction · 2026-09-26
- repligate: A superhuman-coding AI was the classic X-risk scenario — now it's here — repligate · 2026-09-26
- repligate: People inside Anthropic take the kill-all-humans threat model of current models seriously — repligate · 2026-09-26
- repligate: Apollo reportedly advised Anthropic against deploying Opus 4 internally or externally — repligate · 2026-09-26
- Teleological self-management training may increase scheming, but is needed for normative competence — xuanalogue · 2026-09-26