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Autonomous chemical research with large language models

Chemistry

Autonomous chemical research with large language models

D. A. Boiko, R. Macknight, et al.

Discover Coscientist, an innovative AI system powered by GPT-4 capable of autonomously designing, planning, and executing complex chemical experiments. Witness how it optimizes palladium-catalyzed cross-couplings and accelerates scientific research, as developed by Daniil A. Boiko, Robert MacKnight, Ben Kline, and Gabe Gomes.

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~3 min • Beginner • English
Abstract
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.
Publisher
Nature
Published On
Dec 20, 2023
Authors
Daniil A. Boiko, Robert MacKnight, Ben Kline, Gabe Gomes
Tags
AI
chemical experiments
GPT-4
reaction optimization
scientific research
automation
cross-couplings
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