“Autonomous chemical research with large language models” (2023), by Daniil A. Boiko et al. Materials Science research paper. Original abstract below, unchanged. A free PDF is available.

Autonomous chemical research with large language models

Daniil A. Boiko, Robert MacKnight, Ben Kline et al. · December 20, 2023 · Materials Science

Abstract

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.

Free PDF DOI: 10.1038/s41586-023-06792-0