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MIT Media Lab course maps four layers of self-evolving AI

1 article1 sourcesince Oct 19Last article 2h ago ·

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Paul Liang, who teaches MIT Media Lab's graduate course "How to AI an AI" in fall 2026, organizes self-evolving AI into four layers: context, harness, model, and task/environment evolution.

The course reading list includes prompt optimization, LLM-as-optimizer methods such as FunSearch and AlphaEvolve, and the Darwin Gödel Machine and PostTrainBench papers, according to a report on X by @shao__meng. Course assignments map to the four layers, and Kimi AI sponsors student API credits for final projects.

Written by AI from the articles below · updated Oct 19, 8:49 AM ET

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Latest developmentOct 19, 8:21 AM ET
MIT course maps four layers of self-evolving AI, from prompts to task generation

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Oct 19
  1. meng shaoX
    MIT course maps four layers of self-evolving AI, from prompts to task generation

    AIMIT Media Lab's graduate course "How to AI an AI," taught by Paul Liang in fall 2026, organizes self-evolving AI into four layers: context, harness, model, and task/environment evolution. The article says the course's reading list covers prompt optimization, LLM-as-optimizer methods such as FunSearch and AlphaEvolve, and papers like Darwin Gödel Machine and PostTrainBench. Assignments map to the four layers, and Kimi AI sponsors student API credits for final projects.

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