AI能否解决黎曼猜想等未知难题？诺奖得主这样说

Core Viewpoint - The current AI models are significantly overestimated, serving primarily as tools rather than independent scientific entities [1][2][5] Group 1: AI and Scientific Discovery - David Gross argues that solving major physical or mathematical problems relies on human intelligence and creativity, with AI acting as a powerful auxiliary tool [2][5] - There is skepticism regarding AI's ability to prove complex conjectures within a five-year timeframe, as highlighted by a bet between Zhang Yaqin and mathematician Shing-Tung Yau [1][2] - Gross expresses dissatisfaction with the current capabilities of AI, noting that early versions of ChatGPT struggled with basic tasks like counting [2] Group 2: Nobel Prize and AI - The 2024 Nobel Prize in Physics awarded to John Hopfield is not attributed to AI achievements, as his work extends physical methods into neuroscience [4][5] - Gross emphasizes that Hopfield's research is a continuation of physics rather than a contribution to AI, reinforcing the distinction between the two fields [5] Group 3: Computational Power and Theoretical Physics - The exponential growth in computational power has significantly advanced theoretical physics, allowing for complex calculations that were previously labor-intensive [5] - Gross reflects on the historical limitations of computational methods in quantum chromodynamics (QCD) and how modern advancements have transformed research capabilities [5] Group 4: Encouragement for Young Researchers - Gross encourages young researchers to enjoy the process of exploration and maintain curiosity, emphasizing that the joy of research lies in the journey of discovery [6]