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Autonomous chemical research with large language models

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. Coscientist is an artificial intelligence system driven by GP ....

International Conference On Theory Of Information Retrieval , Curran Associates , Conference On Research , Emerald Cloud Lab , Development In Information Retrieval , International Symposium On Machine Programming , International Conference On Learning Representations , Neural Information Processing Systems , Machine Programming , International Conference , Learning Representations , Hugging Face , Information Retrieval , Massive Datasets , Cambridge Univ , Big Data , Cloud Lab ,