Autonomous chemical research with large language models
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 d...
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| Published in | Nature (London) Vol. 624; no. 7992; pp. 570 - 578 |
|---|---|
| Main Authors | , , , |
| Format | Journal Article |
| Language | English |
| Published |
London
Nature Publishing Group UK
21.12.2023
Nature Publishing Group |
| Subjects | |
| Online Access | Get full text |
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| 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.
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. |
|---|---|
| AbstractList | 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.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. 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. 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. Transformer-based large language models are making significant strides in various fields, such as natural language processing , biology , chemistry and computer programming . 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. 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. |
| Author | Kline, Ben Gomes, Gabe MacKnight, Robert Boiko, Daniil A. |
| Author_xml | – sequence: 1 givenname: Daniil A. orcidid: 0000-0003-4140-4645 surname: Boiko fullname: Boiko, Daniil A. organization: Department of Chemical Engineering, Carnegie Mellon University – sequence: 2 givenname: Robert surname: MacKnight fullname: MacKnight, Robert organization: Department of Chemical Engineering, Carnegie Mellon University – sequence: 3 givenname: Ben surname: Kline fullname: Kline, Ben organization: Emerald Cloud Lab – sequence: 4 givenname: Gabe orcidid: 0000-0002-8235-5969 surname: Gomes fullname: Gomes, Gabe email: gabegomes@cmu.edu organization: Department of Chemical Engineering, Carnegie Mellon University, Department of Chemistry, Carnegie Mellon University, Wilton E. Scott Institute for Energy Innovation, Carnegie Mellon University |
| BackLink | https://www.ncbi.nlm.nih.gov/pubmed/38123806$$D View this record in MEDLINE/PubMed |
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| ContentType | Journal Article |
| Copyright | The Author(s) 2023 2023. The Author(s). Copyright Nature Publishing Group Dec 21-Dec 28, 2023 |
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| DOI | 10.1038/s41586-023-06792-0 |
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, chemistry... Transformer-based large language models are making significant strides in various fields, such as natural language processing 1–5 , biology 6,7 , chemistry... Transformer-based large language models are making significant strides in various fields, such as natural language processing , biology , chemistry and... Transformer-based large language models are making significant strides in various fields, such as natural language processing1-5, biology6,7, chemistry8-10 and... |
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| Title | Autonomous chemical research with large language models |
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