用好AI这个科研超级助手

Group 1 - The core viewpoint of the article emphasizes the importance of implementing the "Artificial Intelligence +" action plan to seize opportunities in the new wave of scientific research driven by AI [1] - The article highlights the significant advancements in AI-driven scientific research, exemplified by AlphaFold2's ability to predict the structures of approximately 200 million proteins, solving a long-standing challenge in the field [1] - It points out the existing challenges in AI-driven scientific research, such as the lack of high-quality scientific data and insufficient algorithm interpretability, which hinder deeper development [1] Group 2 - The article discusses the urgent need to establish a national-level data platform and computing network to address issues related to data quality, reliance on foreign databases, and lack of unified data standards [2] - It emphasizes the necessity of cultivating interdisciplinary talent to tackle the shortage of professionals in AI and related fields [2] - The article calls for collaboration across fields and departments to enhance the role of AI as a powerful assistant for scientists, thereby improving research efficiency and innovation potential [2]