Ethan Mollick: Leap in AI Model Capabilities Followed by Regression to the Mean
emollick · x · 2026-07-20
Professor Ethan Mollick highlights a peculiar phenomenon in AI: some models exhibit exceptionally strong capabilities, but their subsequent iterations often "regress to the mean," performing worse than expected.
He cites Anthropic's Updated Sonnet 3.5 (sometimes called Sonnet 3.6) as an example, suggesting it represents an extremely rare, breakthrough leap in capability relative to its predecessor.
More from Models
- OpenAI upgrades Decisions API: 400 questions per call, native voice and image support — OpenAIDevs · 2026-10-26
- Fangcun AI, China's first independent frontier AI safety lab, launches with DeepSeek eval report — JacquesThibs · 2026-10-26
- When AI hits an existential crisis: model confuses itself and everyone else — Ok-Delivery-7437 · 2026-10-26
- Kimi K3.1 Pro tops MathArena open models, closing frontier gap to about 6 months — teortaxesTex · 2026-10-26
- Ruff creator Charlie Marsh: frontier models find infinite bugs in any software — charliermarsh · 2026-10-26
- Dev testing one skill across Opus 5.5 and Sol 6.1 finds instruction following 'all over the map' — lucasmeijer · 2026-10-26