Humans Should Oversee AI at Critical Junctures
FinanceYF5 · x · 2026-07-13
Building on a previous point, the author argues that humans shouldn't be completely kicked out of the recursive self-improvement loop. Instead, they should move up a level to provide supervision at critical nodes.
They also ask: If this path continues, what is the first bottleneck we will hit? Previous candidates include unclear evaluation metrics, long-term memory losing details, difficulty learning from failures, reward hacking, and coding agents ignoring the long-term health of a codebase.
Related event: Lilian Weng's Deep Dive into Recursive Self-Improvement via Harness(9 posts)→
More from AGI Musings
- Bindu Reddy says GPT-6 is coming soon, with Alibaba, DeepSeek and Kimi close behind — bindureddy · 2026-07-22
- Bindu Reddy says the industry still lacks a way to train 20T models and scale post-training RL — bindureddy · 2026-07-22
- Advanced AI Models Are Becoming Impossible to Plug and Play — emollick · 2026-07-22
- AI suggested a better composition, and that made one user uneasy — Sydde · 2026-07-22
- The Thimble and the Waterfall: AI's Data Bottleneck and Feedback Loops — dyamins · 2026-07-22
- Researcher Admits Kurzweil Was Right About AI Scaling Laws All Along — davidmanheim · 2026-07-22