Core Viewpoint - The rapid advancement of artificial intelligence (AI) technology necessitates higher education institutions to break down disciplinary barriers and cultivate interdisciplinary talents that meet societal needs [1][2] Group 1: AI and Interdisciplinary Education - Higher education should actively explore new models for interdisciplinary "AI+" discipline construction, integrating traditional humanities and social sciences, engineering, and emerging disciplines with technology [1] - Innovative practices in disciplines like "new humanities" and "new business" have already begun, with AI stimulating new research questions and theoretical discoveries in fields such as literature, philosophy, and linguistics [1] - The focus should be on developing local characteristics and contemporary relevance in traditional disciplines, accelerating their scientific and digital transformation to foster students' innovative capabilities that cannot be replaced by AI [1] Group 2: Transformation of Traditional Disciplines - Traditional engineering education often emphasizes specialization, leading to narrow knowledge bases and insufficient humanistic background and innovation capabilities [2] - There is a need to update and iterate existing knowledge systems in traditional engineering and science disciplines to meet the demands of the AI era, extending foundational subjects like physics, mathematics, and chemistry into practical applications [2] - AI research should transcend disciplinary boundaries, responding proactively to technological advancements and educational digitalization trends, aligning with the requirements of modern Chinese development [2]