( Two minute read)

Forecasts of explosive AI progress predict that what researchers call recursive self-improvement is on the horizon. 

LLMs can already write code, generate synthetic data for training, and optimize the computer chips they run on. 

However AI agents are not yet capable of conducting open-ended AI research—free-form investigations that have no clear-cut answers and require judgment and taste, which may be integral to building self-improving AI.

This gap suggests that some of the hyped-up timelines for automating AI research may be running ahead of the evidence.

AI research also requires open-ended thinking—choosing a set of hypotheses, deciding what evidence would settle a question, or knowing when to start over. 

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