Ethan Mollick: Low AI Variance Limits Problem-Solving Value
eldonredwards · x · 2026-08-18
Ethan Mollick argues that AI labs need to focus more on variance when addressing creative tasks. The difficulty in extracting creative variation from smart models severely limits their effective value in problem-solving and creative work.
More from AGI Musings
- AI Creates Authenticity Anxiety: Imperfection Becomes Proof of Humanity — karinanguyen · 2026-08-18
- Two Paths to Superintelligence: Spiky vs. General Improvement — RileyRalmuto · 2026-08-18
- Proposal: Benchmark Models by Cost per Completed Task, Not Token — mageblex · 2026-08-18
- AI as a Google Maps for thought: teaching processes over facts — NaveenGRao · 2026-08-18
- Former Commerce Secretary Raimondo Leads Well-Funded Group Against AI-Driven UBI — Neurogence · 2026-08-18
- Post-Labor Companies Will Be Defined by High Revenue Per Employee, Silence — VraserX · 2026-08-18