来源：新智元 作者：刘锋 【新智元导读】 一个源自AI的「广义智能体理论」，为探索「万物理论」开了个新脑洞。它认 为，无论是物理系统、生命还是AI，本质上都是「智能体」。甚至更进一步地猜测，我们熟知的 引力、电磁力等，或许都源于一种更根本的「智能场」。 在现代科学的宏伟蓝图上，「 万物理论」 （ Theory of Everything ）代表着一个大一统的梦想：构建 一个包罗万象、逻辑自洽的理论体系。 它的雄心在于，用最少的本源法则，去解释宇宙间森罗万象的现象 —— 从宇宙大爆炸的奇点、时空本身 的弯曲，到基本粒子的相互作用、再到化学键的构成、 DNA 链的螺旋，直至智能的萌发与自我意识的诞 生。 然而，通往这一「 梦想」 理论的道路上，横亘着现代物理学最深刻的两大鸿沟： 面对这一悬置近百年的科学难题，传统物理学的路径似乎已步入瓶颈，那么能否从一个全新的、看似无关 的领域寻找突破口？ 21世纪人工智能的爆发，为这一探索提供了可能的契机，智能体（Agent）逐步成为AI理论和产业的核心 概念，并对科学和产业的创新产生越来越大的影响。 在过去十年中，我们尝试对人工智能的核心概念，智能体（ Agent ）的最小化 ...

Group 1 - The core viewpoint of the article is that AI is reshaping human scientific paradigms, and while it will become an important partner in exploring ultimate questions in mathematics and physics, it cannot replace human intuition and creativity [2][3]. - Terence Tao discusses the importance of collaboration in creating superior intelligent systems, suggesting that a collective human community is more likely to achieve breakthroughs in mathematics than individual mathematicians [3]. - The article highlights Tao's insights on various world-class mathematical problems, including the Kakeya conjecture and the Navier-Stokes regularity problem, emphasizing the interconnectedness of these problems with other mathematical fields [4][16]. Group 2 - Tao emphasizes that in undergraduate education, students encounter difficult problems like the Riemann hypothesis and twin prime conjecture, but the real challenge lies in solving the remaining 10% of the problem after existing techniques have addressed 90% [5]. - The Kakeya problem, which Tao has focused on, involves determining the minimum area required for a needle to change direction in a plane, illustrating the complexity and depth of mathematical inquiry [6][7]. - The article discusses the implications of the Kakeya conjecture and its connections to partial differential equations, number theory, geometry, topology, and combinatorics, showcasing the rich interrelations within mathematics [10][14]. Group 3 - The Navier-Stokes regularity problem is presented as a significant unsolved issue in fluid dynamics, questioning whether a smooth initial velocity field can lead to singularities in fluid flow [16][18]. - Tao explains the challenges in proving general conclusions for the Navier-Stokes equations, using the example of Maxwell's demon to illustrate statistical impossibilities in fluid dynamics [19][20]. - The article notes that understanding the Kakeya conjecture can aid in comprehending wave concentration issues, which may indirectly enhance the understanding of the Navier-Stokes problem [18][26]. Group 4 - Tao discusses the concept of self-similar explosions in fluid dynamics, where energy can be concentrated in smaller scales, leading to potential singularities in the Navier-Stokes equations [22][24]. - The article highlights the mathematical exploration of how energy can be manipulated within fluid systems, suggesting that controlling energy transfer could lead to significant breakthroughs in understanding fluid behavior [26][30]. - Tao's work aims to bridge the gap between theoretical mathematics and practical applications, indicating a future where AI could play a role in experimental mathematics [55][56].