Zhao Weijie
Natl Sci Rev. 2024 Mar 26;11(8):nwae119. doi: 10.1093/nsr/nwae119. eCollection 2024 Aug.
Artificial intelligence (AI) tools are changing the way we do science. AlphaFold basically solved the conundrum of protein structure prediction; DeepMD greatly improved the efficiency and accuracy of molecular simulations; and the emerging large language models such as ChatGPT are opening up more possibilities for scientific applications. In this panel, five experts from China and the US discussed the concept, development, bottlenecks and opportunities of AI for Science (AI4S), as well as their understanding of the relationship between AI and science. Roberto Car Professor at Department of Chemistry, Princeton University, USA Weinan E Professor at School of Mathematical Sciences, Peking University, China; AI for Science Institute, Beijing, China David Srolovitz Professor at Department of Mechanical Engineering, University of Hong Kong, China Han Wang Professor at the Institute of Applied Physics and Computational Mathematics, Chinese Academy of Sciences, China Linfeng Zhang (Chair) Chief scientific officer of DP Technology, China; AI for Science Institute, Beijing, China.
人工智能(AI)工具正在改变我们开展科学研究的方式。阿尔法折叠基本解决了蛋白质结构预测的难题;深度分子动力学极大地提高了分子模拟的效率和准确性;而像ChatGPT这样新兴的大语言模型正在为科学应用开辟更多可能性。在本次小组讨论中,来自中国和美国的五位专家探讨了科学人工智能(AI4S)的概念、发展、瓶颈和机遇,以及他们对人工智能与科学之间关系的理解。罗伯托·卡尔 美国普林斯顿大学化学系教授 鄂维南 中国北京大学数学科学学院教授;中国北京科学人工智能研究院 大卫·斯罗洛维茨 中国香港大学机械工程系教授 王涵 中国科学院应用物理与计算数学研究所教授 张林峰(主持人) 中国DP技术公司首席科学官;中国北京科学人工智能研究院