MemCast
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General models consistently outperform narrow, task‑specific models across domains
  • Boris cites Rich Sutton’s “bitter lesson”: the most general solution wins.
  • Evidence comes from self‑driving cars, language tasks, and coding agents.
  • Specialized models give diminishing returns as general models improve.
  • The principle guides Anthropic’s roadmap to prioritize model scaling.
  • It also informs product design: build abstractions that work with any model.
Boris ChernyLenny's Podcast01:04:45

Supporting quotes

The more general model will always outperform the more specific model. Boris Cherny
Bet on the more general model and don't fine‑tune narrow ones. Boris Cherny

From this concept

The Bitter Lesson: General vs Specialized Models

Across AI research, broader, more general models consistently outperform narrow, task‑specific ones. Anthropic embraces this by betting on future, larger models rather than fine‑tuning current versions.

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