计算机科学
文档
自动化
变压器
软件工程
互联网
自然语言
人工智能
自然语言理解
程序设计语言
人机交互
系统工程
万维网
工程类
电气工程
电压
机械工程
作者
Daniil A. Boiko,Robert MacKnight,Ben Kline,Gabriel dos Passos Gomes
出处
期刊:Nature
[Springer Nature]
日期:2023-12-20
卷期号:624 (7992): 570-578
被引量:99
标识
DOI:10.1038/s41586-023-06792-0
摘要
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.
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