Toward a Science of Intelligence: Unifying Physics, Neuroscience & AI

Abstract Artificial intelligence stands poised to transform our society, yet we hardly understand how it works. A synthesis of physics, neuroscience, and AI can fulfill an urgent need: to build a new, unified science of intelligence that explains and improves how intelligence emerges across both artificial and biological neural networks. I discuss four ways this synthesis has begun to and will continue to unfold. First, powerful analytic tools from the physics of complex systems will provide insight into how large neural networks learn and compute. Second, neuroscience will provide clues into bridging the many orders of magnitude advantages that biological intelligence retains over AI. Third, we can go beyond evolution to instantiate neural algorithms in quantum hardware, leading to new devices through AI-led codesign of physics and computation. Fourth, we can meld minds and machines by building digital twins of the brain, yielding insights into not only intelligence but also consciousness and the sense of self through causal modeling and control. Overall, AI will shed light on the nature of our physical and mental realities, raising profound questions about the role of human understanding in the age of AI.