# Rich Sutton - The Bitter Lesson (Highlights)  ## Metadata **Review**:: [readwise.io](https://readwise.io/bookreview/59164075) **Source**:: #from/readwise #from/reader **Zettel**:: #zettel/fleeting **Status**:: #x **Authors**:: [[Rich Sutton]] **Full Title**:: The Bitter Lesson **Category**:: #articles #readwise/articles **Category Icon**:: 📰 **URL**:: [www.cs.utexas.edu](https://www.cs.utexas.edu/~eunsol/courses/data/bitter_lesson.pdf) **Host**:: [[www.cs.utexas.edu]] **Highlighted**:: [[2026-03-21]] **Created**:: [[2026-03-30]] ## Highlights - The biggest lesson that can be read from 70 years of AI research is that general methods that leverage computation are ultimately the most effective, and by a large margin. ([View Highlight](https://read.readwise.io/read/01km76a454mpza33xs53z46jev)) ^998875134 - And the human-knowledge approach tends to complicate methods in ways that make them less suited to taking advantage of general methods leveraging computation. ([View Highlight](https://read.readwise.io/read/01km76cbpkz5dy4pbsyecd3fyw)) ^998875621 - The bitter lesson is based on the historical observations that 1) AI researchers have often tried to build knowledge into their agents, 2) this always helps in the short term, and is personally satisfying to the researcher, but 3) in the long run it plateaus and even inhibits further progress, and 4) breakthrough progress eventually arrives by an opposing approach based on scaling computation by search and learning. ([View Highlight](https://read.readwise.io/read/01km76kbbga9xnm4m204rqvz6d)) ^998875802 - One thing that should be learned from the bitter lesson is the great power of general purpose methods, of methods that continue to scale with increased computation even as the available computation becomes very great. ([View Highlight](https://read.readwise.io/read/01km76kxtekgse6t1g4f36ywqk)) ^998875816