Autonomous chemical research with large language models.
basic_science · Level V
Where this comes from
- Record sourced from PubMed, PMID 38123806.
- Also identified by DOI 10.1038/s41586-023-06792-0 and PMC identifier 10733136.
- Licence recorded as CC BY.
- The licence permits redistribution, so the abstract is shown in full and the full text is available from the publisher.
Abstract
Transformer-based large language models are making significant strides in various fields, such as natural language processing<sup>1-5</sup>, biology<sup>6,7</sup>, chemistry<sup>8-10</sup> and computer programming<sup>11,12</sup>. 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.