Core Viewpoint - The article discusses the potential and challenges of Artificial General Intelligence (AGI) in the context of scientific research, emphasizing the need for a balanced perspective on its capabilities and limitations [1][2]. Group 1: AI for Science Developments - AI for Science (AI4S) is recognized for its value in scientific research, with recent achievements presented at the 2025 Pujiang Innovation Forum, including the Amix-Agent for protein design and the DeepPeptide model for peptide synthesis [2][5]. - The integration of AI in various scientific fields such as biomanufacturing, quantum technology, and climate energy is being promoted through the establishment of the "Scientific Intelligence Strategic Technology Alliance" [5]. Group 2: Six Questions on AGI for Science - The first question addresses the boundaries of AI, questioning whether all scientific problems can be solved by AI, highlighting the historical context of this debate [2]. - The second question examines the predictive capabilities of AGI, cautioning against overestimating current models' ability to predict scientific phenomena due to limitations in existing human knowledge [3]. - The third question focuses on the representation of scientific concepts, suggesting that AI should move beyond natural language to include symbolic languages for better expression [3]. - The fourth question explores the potential for AGI to foster interdisciplinary collaboration, emphasizing its role in revealing unseen connections between different scientific fields [3]. - The fifth question proposes a thought experiment to evaluate AGI's ability to make significant scientific discoveries, using the example of deriving general relativity from prior knowledge [4]. - The sixth question discusses the evolving relationship between researchers, research subjects, and tools, indicating AI's potential to identify valuable patterns in unstructured data [4].