中国科学院院士鄂维南：科学智能时代，要打破学科界限培养人才

Group 1 - The core viewpoint is that AI for Science is a new paradigm that will profoundly impact future scientific technology and industrial development, necessitating a shift in talent cultivation methods [1][2] - The "Beijing Action Plan for Accelerating High-Quality Development of AI Empowering Scientific Research (2025-2027)" encourages higher education institutions and research organizations to strengthen interdisciplinary professional settings to cultivate talents who understand both AI technology and its applications [1] - It is emphasized that students should be made aware of future industry, societal, and technological demands, while also developing strong practical skills, including laboratory operations and familiarity with code architecture [1] Group 2 - The importance of cultivating students' first-principles thinking ability is highlighted, advocating for the breaking down of existing disciplinary boundaries, which may become less relevant in the next 5 to 10 years [2] - The efficiency improvements brought by AI for Science represent a quantitative change, while the expansion of exploratory space due to the breakdown of disciplinary boundaries signifies a qualitative leap [2] - There is a need to enhance the educational system to effectively convey foundational knowledge in subjects like mathematics, physics, and chemistry, while also stimulating students' interest and desire for exploration in these fields [2]