物理第一性AI:从物理通向智能OA

Artificial intelligence(AI)and physics are entering a new stage of deep interdisci-plinary integration.Physics has long provided foundational ideas for AI,including symmetry,statistical mechanics,and quantum theory,while continuing to inspire new model architec-tures,learning principles,and computational paradigms.At the same time,as AI systems become increasingly complex,their internal mechanisms,collective behavior,and emergent dynamics are becoming new objects of interest and investigation in physics.In this Perspec-tive,we introduce Physics-first AI,a research paradigm that regards AI as a complex informa-tion-processing system embedded in the physical world and seeks to understand,design,and build intelligent systems from fundamental physics principles and modes of reasoning.Phys-ics-First AI aims to provide a common foundation for model architectures,training mecha-nisms,computational processes,and reasoning paradigms through a unified physics perspec-tive.We trace the historical interplay between physics and AI and discuss how structure pri-ors,statistical mechanics,quantum theory,and physics reasoning may together shape the next generation of intelligent systems.We further examine how this emerging paradigm could reshape physics education and the training of interdisciplinary researchers in the AI era.Phys-ics-First AI offers a route toward a physics-grounded theory and design framework for next-generation intelligence,opening new opportunities for scientific AI,autonomous scientific dis-covery,and ultimately artificial general intelligence.