Exploring the Role of Large Language Models in the Scientific Method: From Hypothesis to Discovery
Large Language Models (LLMs) are transforming various stages of scientific research, including experimental design, data analysis, and hypothesis generation. This paper reviews the current application of LLMs in the scientific method, analyzes the gap between their roles as technical tools and creative engines, and points out the key steps required for deeper integration. Although LLMs show great potential in accelerating scientific discovery, they still face limitations in fundamental science (e.g., the discovery of new principles or laws). In the future, combining data-driven techniques with symbolic systems may give rise to hybrid engines that drive entirely new research directions.