港大马毅谈智能史：DNA 是最早的大模型，智能的本质是减熵

Core Viewpoint - The essence of intelligence is "learning," which is a process of finding and utilizing patterns in the external world to make predictions and counteract the increase of entropy in the universe [3][15][21]. Group 1: Understanding Intelligence - Intelligence should not be understood superficially; it requires a historical perspective on its development from biological origins to machine intelligence [2][3]. - The historical evolution of intelligence includes four stages: genetic evolution through natural selection, the emergence of neural systems and memory, the development of language and writing for knowledge transmission, and the abstraction and generalization seen in mathematics and science [20][21]. Group 2: Machine Intelligence and Learning Mechanisms - Current AI models, such as o1 and R1, primarily rely on memorization rather than true reasoning, lacking the ability to independently generate abstract concepts [7][22]. - The training of models like DeepSeek demonstrates that open-source approaches can surpass closed-source methods, as the core of AI development lies in data and algorithms rather than proprietary technology [14][12]. Group 3: Educational Initiatives - The introduction of AI literacy courses at universities aims to equip students with an understanding of AI's history, current technologies, and their societal implications, fostering independent critical thinking [37][38]. - The curriculum emphasizes the importance of understanding the basic concepts of AI and its ethical considerations, preparing students for future interactions with intelligent systems [42][39]. Group 4: Future Directions in AI Research - The pursuit of closed-loop feedback mechanisms in AI systems is seen as essential for achieving true intelligence, as it allows for self-correction and adaptation in open environments [43][46]. - The current state of AI is compared to early biological evolution, where significant advancements are still needed to move beyond basic capabilities [30][31].