Autonomous chemical research with large language models

Daniil A. Boiko, Robert MacKnight, Ben Kline and Gabe Gomes ()
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Daniil A. Boiko: Carnegie Mellon University
Robert MacKnight: Carnegie Mellon University
Ben Kline: Emerald Cloud Lab
Gabe Gomes: Carnegie Mellon University

Nature, 2023, vol. 624, issue 7992, 570-578

Abstract: Abstract Transformer-based large language models are making significant strides in various fields, such as natural language processing1–5, biology6,7, chemistry8–10 and computer programming11,12. 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.

Date: 2023
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DOI: 10.1038/s41586-023-06792-0

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