A panel discussion on AI for science: the opportunities, challenges and reflections

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 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.