With the vigorous development of AI for Science in recent years, the integration of artificial intelligence and various scientific disciplines has become a major trend. However, AI for Science covers a wide range and involves many disciplines. Therefore, organizing it into a unified framework will enable better navigation for newcomers to the field. In this article, we posit that although the objects and methods of scientific research seem to be vastly different, AI can provide a universal paradigm and methods for scientific research in the following three aspects: scientific simulation, design and control, and discovery, solving problems in the field. This article will specifically elaborate on the task setting and current representative work. Through specific examples, we will explain how AI can concretely assist scientific research, facilitating researchers to better apply existing methods or develop novel methods.
