Autonomous chemical research with large language models

作者：Daniil A. Boiko, R. MacKnight, Benjamin C Kline, Gabe Gomes · 发表于：Nature · 年份：2023 · DOI：10.1038/s41586-023-06792-0 · 被引用次数：1284 · 研究领域：Medicine、Computer Science

Transformer-based large language models are making significant strides in various fields, such as natural language processing^ 1 – 5 , biology^ 6 , 7 , chemistry^ 8 – 10 and computer programming^ 11 , 12 . Here, we show the development and capabilities of Coscientist, an artificial intelligence system driven by GPT-4 that autonomously designs, plans and performs complex experiments by incorporating large language models empowered by tools such as internet and documentation search, code execution and experimental automation. Coscientist showcases its potential for accelerating research across six diverse tasks, including the successful reaction optimization of palladium-catalysed cross-couplings, while exhibiting advanced capabilities for (semi-)autonomous experimental design and execution. Our findings demonstrate the versatility, efficacy and explainability of artificial intelligence systems like Coscientist in advancing research. Coscientist is an artificial intelligence system driven by GPT-4 that autonomously designs, plans and performs experiments by incorporating large language models empowered by tools such as internet and documentation search, code execution and experimental automation.