AI Scientist’, created by a team at the Tokyo-based company Sakana AI and in laboratories in Canada and the United Kingdom, can perform the full cycle of research, from scanning the literature on a topic and formulating hypotheses to trying out solutions and writing a paper. AI Scientist even does some of the job of peer reviewers and evaluates its own results.
AI Scientist joins a slew of efforts to automate parts of the scientific process using artificial intelligence (AI) agents. “To my knowledge, no one has yet done the total scientific community, all in one system,” says AI Scientist co-creator Cong Lu, a machine-learning researcher at the University of British Columbia in Vancouver, Canada. The results1 were posted on the arXiv preprint server last month…
AI Scientist is based on a large language model (LLM). It uses a machine-learning algorithm to search the literature for similar work. The team then used evolutionary computation, a technique inspired by the mutations and natural selection in Darwinian evolution. It applies small, random changes to an algorithm and selects the ones that improve the model’s efficiency.
To do so, AI Scientist conducts its own ‘experiments’ by running the algorithms and measuring how well they perform. At the end, it produces a paper, and evaluates it in a sort of automated peer review. After ‘augmenting the literature’ this way, the algorithm can then start the cycle again, building on its own results.
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Castelvecchi, D. (2024, August 30). Researchers built an ‘AI Scientist’ — what can it do? Nature. https://doi.org/10.1038/d41586-024-02842-3