AI是宇宙演化的必然下一步，人类应以勇气、自豪和冒险精神来迎接它。 "欢迎来到'经验时代'。"9月11日，2025·Inclusion外滩大会在上海举行，2024图灵奖得主、"强化学习之 父"理查德·萨顿在主论坛演讲中表示，人工智能需要一种能够伴随智能体能力提升而持续增长与优化的 新型数据源，传统静态数据库已不足以支撑其进一步发展。 萨顿认为，我们当前仍处于"人类数据时代"，AI系统主要通过预测人类语言和标签进行训练，绝大多数 机器学习仍是将人类已有知识迁移至一个静态、缺乏自主学习能力的人工智能体系中。然而，人类数据 的利用正逐渐接近极限。 他指出，现在我们要进入"经验时代"，智能体将以第一人称视角与世界互动，直接生成被称为"经验"的 新数据源。这种机制与人类及其他动物的学习方式高度一致——通过与认知水平相匹配的自我体验获取 发展所需的数据。 "去中心化"的定义是每个智能体追求自己的目标，这正是经济体系的运行方式，人工智能的政治议题 中，他强调人类需要寻求协作、支持协作，并致力将协作制度化。 对于人工智能与哲学，理查德·萨顿则认为，人工智能是人类最古老的追求之一，它并不是陌生的外来 技术，而是与人类的本性高度 ...

Group 1 - The AI industry is transitioning into an "experience era," where continuous learning is essential for intelligence, moving beyond the limitations of human data [2] - Richard Sutton emphasizes that knowledge is derived from experience, which involves observation, action, and reward, and that the intelligence of an agent depends on its ability to predict and control input signals [2] - Two technologies, continual learning and meta-learning, are necessary to unlock the full potential of AI in this new experience era [2] Group 2 - Concerns about AI leading to bias, unemployment, or even human extinction are exaggerated and fueled by certain organizations and individuals profiting from such fears [3] - Sutton argues that decentralized collaboration among agents with different goals can lead to mutual benefits, highlighting human cooperation as a unique strength [3] - He presents four predictive principles regarding the future of AI, including the lack of consensus on how the world should operate and the potential for superintelligent AI to surpass human intelligence [3] Group 3 - Sutton categorizes the history of the universe into four eras: particle, star, replicator, and design, asserting that humanity's unique ability to push design to its limits is crucial in the current pursuit of AI [4] - He believes that AI is an inevitable next step in the evolution of the universe, advocating for a courageous and adventurous approach to its development [5]

Core Viewpoint - The dominance of large language models (LLMs) is temporary, and they will not remain at the forefront of technology in the next five to ten years [1][2]. Group 1: Current State of AI - Richard Sutton, a Turing Award winner and father of reinforcement learning, emphasizes that current AI models like ChatGPT rely on analyzing vast amounts of human-generated data [9]. - He argues that pursuing human-like thinking will only achieve "human-level" performance, and in fields like mathematics and science, the knowledge within human data is nearing its limits, making further innovation through mere imitation difficult [10][11]. Group 2: Future of AI Learning - Sutton believes AI must transition from relying on human data to acquiring "experience data" through first-person interactions with the world [13][14]. - He illustrates this with the example of AlphaGo's unconventional move against Lee Sedol, showcasing AI's potential for innovative thinking through experiential learning [14]. - The future of AI will belong to an "experience era," where agents learn from interactions, which exceeds the capabilities of current LLMs [18]. Group 3: Reinforcement Learning and Computational Power - Sutton states that the core path to the future of AI lies in reinforcement learning, which is centered around experiential learning [19]. - To fully leverage reinforcement learning, deep learning algorithms with continuous learning capabilities are essential [20]. - The support of large-scale computational power is crucial for expanding AI capabilities and meeting increasing performance demands [22][23]. Group 4: Decentralized Cooperation Among Agents - Sutton discusses the potential for decentralized cooperation among agents with different goals, suggesting that they can achieve mutual benefits through interaction [24]. - He critiques the calls for centralized control of AI, attributing such views to fear of the unknown, and advocates for embracing the diversity of individual goals to establish a cooperative order [26]. Group 5: The Design Era - Sutton introduces the concept of a "design era," where machines become increasingly life-like, yet emphasizes the fundamental differences between life and technology [29]. - He posits that the goal of developing AI is to achieve the ultimate design—creating agents capable of self-design, with humans acting as catalysts and creators in this process [29]. Group 6: Community Reactions - Sutton's statements have sparked intense discussions within the community, with supporters arguing that breakthroughs often arise from the unknown and that LLMs may be approaching their limits [30][31].