Towards end-to-end automation of AI research
Chris Lu; Cong Lu; R. T. Lange; Yutaro Yamada; Shengran Hu; Jakob Foerster; David Ha; Jeff Clune · 2026 · Nature
WASTE classifies this as Negative / Null Result Report · AI classification, approximate
The study found no significant effect — useful as a negative control or null benchmark for your own design.
Abstract
Abstract The automation of science is a long-standing ambition in artificial intelligence (AI) research 1,2 . Although the community has made substantial progress in automating individual components of the scientific process, a system that autonomously navigates the entire research life cycle—from conception to publication—has remained out of reach. Here we present a pipeline for automating the entire scientific process end to end. We present The AI Scientist, which creates research ideas, writes code, runs experiments, plots and analyses data, writes the entire scientific manuscript, and perf
Abstract by Chris Lu; Cong Lu; R. T. Lange; Yutaro Yamada; Shengran Hu; Jakob Foerster; David Ha; Jeff Clune, Nature (2026) — licensed CC BY 4.0.
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Metadata source: OpenAlex · DOI 10.1038/s41586-026-10265-5