Semantic Scholar Open Access 2023 825 sitasi

Autonomous chemical research with large language models

Daniil A. Boiko R. MacKnight Benjamin C Kline Gabe Gomes

Abstrak

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.

Penulis (4)

D

Daniil A. Boiko

R

R. MacKnight

B

Benjamin C Kline

G

Gabe Gomes

Format Sitasi

Boiko, D.A., MacKnight, R., Kline, B.C., Gomes, G. (2023). Autonomous chemical research with large language models. https://doi.org/10.1038/s41586-023-06792-0

Akses Cepat

Lihat di Sumber doi.org/10.1038/s41586-023-06792-0
Informasi Jurnal
Tahun Terbit
2023
Bahasa
en
Total Sitasi
825×
Sumber Database
Semantic Scholar
DOI
10.1038/s41586-023-06792-0
Akses
Open Access ✓