Returns to AI research sit near the knife-edge: r ≈ 1.2
austinc3301 · x · 2026-11-10
Citing Davidson & Houlden, the author notes the returns to AI research are estimated at r ≈ 1.2 (range 0.4–3.6), near the knife-edge: progress keeps accelerating only if r > 1. AI 2027-style models add a second engine — AI's own research taste improving.
More from AGI Musings
- Founder: Top students at Stanford/Harvard/MIT default to listing why ideas fail instead of making them work — gabriel1 · 2026-11-10
- Safety advocates launch pledge rejecting AI labs' 'knowingly reckless' 2027 acceleration plans — AndyMasley · 2026-11-10
- AutoDNA: AI agents now run multi-step wet-lab molecular biology experiments autonomously — james_y_zou · 2026-11-10
- Sentinel forecasters raise ASI alert to highest level after Anthropic's acceleration warning — teortaxesTex · 2026-11-10
- The Bitter Lesson Was Misread: More Compute Makes Your Algorithm Matter More — tw_killian · 2026-11-10
- Data provenance, not model quality, is why enterprise AI fails, argues defense consultant — Graham_dePenros · 2026-11-10