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AI Scientist, an autonomous research AI tool, produced three research papers, one of which was accepted by peer reviewers at a machine-learning conference. Credit: Olesia Kononenko\/iStock via Getty<\/p>\n
In August 2024, a team of machine-learning researchers launched the first ever artificial-intelligence tool that aimed to fully automate the scientific process<\/a>. \u2018AI scientist\u2019, created by Sakana AI, a company based in Tokyo, can perform the full cycle of scientific discovery, from idea generation to testing its ideas to writing them up in a scientific paper. Almost two years on, there are many different AI research assistants<\/a> available for researchers to use, and a few of them are designed to do autonomous research in the same way that AI Scientist does.<\/p>\n Now, AI Scientist is thought to be one of the first such tools to go through the peer-review process at a leading academic journal. The paper, published today in Nature1<\/a>, updates a 2024 preprint that described the tool2<\/a>, including by toning down its reported capabilities. The latest paper also describes how AI Scientist submitted three original research papers generated by the tool to a leading machine-learning conference, one of which was accepted by peer reviewers. Still, Sakana AI co-founder David Ha says that the paper is not at the same level of the best human-produced papers that were accepted by the same conference.<\/p>\n When the system was unveiled in 2024, \u201cwe were the first group to have demonstrated that you could have AI do the entire scientific process that underlies the creation of a paper\u201d, says study co-author Jeff Clune, a computer scientist at the University of British Columbia in Vancouver, Canada.<\/p>\n \u201cI think it\u2019s a remarkable technological achievement,\u201d says Jevin West, a computational social scientist at the University of Washington in Seattle, which \u201creally forces us to think about what science is\u201d. However, automating science comes with several risks, adds West. These include journals and conferences being flooded with papers<\/a> of modest originality, he says.<\/p>\n Human review<\/p>\n AI Scientist is a collection of \u2018agents\u2019 built on top of existing large language models (LLMs), such as GPT-4o or Claude Sonnet 4. It prompts those LLMs to search the literature on a given topic, generate hypotheses and design a set of possible research directions. Next, AI Scientist writes code, executes it and measures its efficiency. Finally, it writes a paper describing the results. The authors of the paper also created an \u2018automated reviewer\u2019 to evaluate the quality of the tool\u2019s output. The results \u201capproach borderline acceptability for machine learning conference workshops\u201d, the authors write.<\/p>\n In response to peer-review comments, the Sakana AI team toned down claims made in the original preprint that AI Scientist automated the \u201centire\u201d scientific process. The Nature paper also describes the AI Scientist project \u2014 including how the tool took part in a controlled peer-review experiment at the International Conference on Learning Representations (ICLR) in April 2025. In agreement with the ICLR organizers, Ha and his collaborators submitted three AI-generated papers to the peer-review board for one of the conference\u2019s workshops.<\/p>\n