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Investment Rating - The report does not explicitly provide an investment rating for the industry or specific companies within it. Core Insights - Richard Sutton proposes that we are entering an "Era of Experience" characterized by autonomous interaction and environmental feedback, emphasizing the need for systems that can create new knowledge through direct interaction with their environments [1][8] - Sutton argues that public fears regarding AI, such as bias and unemployment, are overstated, and that multi-agent cooperation can lead to win-win outcomes [9] - The report highlights the importance of continual learning and meta-learning as key areas for unlocking the potential of reinforcement learning [3][13] Summary by Sections Event - Sutton's presentation at the 2025 INCLUSION Conference outlines a shift from static knowledge transfer to dynamic agent-environment interactions, marking a transition to an "Era of Experience" [1][8] - He identifies reinforcement learning as crucial for this transition, but notes that its full potential is contingent on advancements in continual and meta-learning [1][8] Commentary - The report discusses the shift from "data as experience" to "capability as interaction," suggesting that firms need to develop systems that can actively engage with their environments to generate new knowledge [2][11] - It emphasizes that the real bottleneck in reinforcement learning is not model parameters but the ability to handle time and task sequences, highlighting the need for continual and meta-learning capabilities [3][13] Technical Bottlenecks - The report identifies two main constraints in reinforcement learning: the need for continual learning to avoid catastrophic forgetting and the need for meta-learning to enable rapid adaptation across tasks [3][13] - It suggests that R&D should focus on long-horizon evaluation and the integration of memory mechanisms and planning architectures [3][13] Decentralized Collaboration - The report posits that decentralized collaboration is not only a technical choice but also a governance issue, requiring clear incentives and transparent protocols to function effectively [4][12] - It outlines three foundational institutional requirements for effective decentralized collaboration: open interfaces, cooperation-competition testbeds, and auditability [4][12] Replacement Dynamics - Sutton's view on "replacement" suggests that it will occur at the task level rather than entire job roles, urging organizations to proactively deconstruct tasks and redesign processes for human-AI collaboration [5][15] - The report recommends establishing a human-AI division of labor and reforming performance metrics to focus on collaborative efficiency [5][15]

商报讯（记者 张玲丽 吕文鹃）昨天上午，以"重塑创新增长"为主题的2025 Inclusion·外滩大会在上海黄 浦世博园区开幕，来自16个国家和地区的550位嘉宾参会分享，包括新晋图灵奖得主理查德·萨顿 （Richard Sutton），阿里云创始人、之江实验室主任王坚，"人类简史系列"作者尤瓦尔·赫拉利（Yuval Noah Harari），宇树科技创始人兼首席执行官王兴兴等全球顶尖学者、产业界人士、青年创业者和科学 家，共同探索智能时代的创新路径与商业未来。 今年大会内容呈现国际化、多元化特色，聚焦"金融科技""人工智能与产业""创新创投生态""全球对话 与合作""负责任创新与普惠未来"五大内容主线，设置了1场开幕主论坛、44场见解论坛、科技展览和系 列科创活动。作为年度备受瞩目的金融科技盛会，外滩大会以其开放、多元、前瞻性吸引全球目光，被 誉为"亚洲三大金融科技盛会"之一。 图灵奖得主理查德·萨顿外滩大会分享 人工智能进入"经验时代" ，潜力远超以往 在昨天上午的开幕主论坛上，2024年图灵奖得主、"强化学习之父"理查德·萨顿（Richard Sutto n）发表 主旨演讲，他认为，人类数据红利正逼近 ...

Group 1 - The core idea presented is that the human data dividend is nearing its limit, and artificial intelligence (AI) is entering an "experience era" centered on continuous learning, which has the potential to exceed previous capabilities [1][9][44] - AI's current training methods are primarily focused on transferring existing human knowledge to static models without autonomous learning capabilities, leading to a recognition of the limitations of this approach [10][14] - The future of AI relies on the development of two currently immature technologies: continual learning and meta-learning, which are essential for unlocking the full potential of experience-based learning [16][14] Group 2 - AI has become a highly politicized issue, with public fears about bias, unemployment, and even human extinction being exaggerated and fueled by certain organizations and individuals [16][18][25] - The call for regulation and control of AI reflects a broader societal tendency to fear the unknown, which can hinder collaborative efforts necessary for progress [24][28] - The concept of decentralized collaboration is emphasized as a superior alternative to centralized control, allowing for coexistence among diverse intelligent agents with different goals [20][26][21] Group 3 - Four principles are proposed to predict the future of AI: the absence of a unified global opinion on how the world should operate, the eventual understanding and creation of intelligence by humans, the inevitable surpassing of current human intelligence by superintelligent entities, and the flow of power and resources towards the most intelligent agents [35][36][37] - The inevitability of AI's replacement of human roles is acknowledged, framing it as a natural progression in the evolution of intelligence [38][44] - The role of humans as catalysts and pioneers in the "design era" is highlighted, emphasizing the unique ability to push design to its limits through AI [42][43]

Core Insights - Richard Sutton, the 2024 Turing Award winner, emphasizes the inevitability of AI replacing human roles in the development process of humanity [1][2] - Sutton introduces four realistic "predictive principles" regarding the future of AI, highlighting the need for decentralized collaboration and the importance of experience in learning [2][3] Group 1: AI and Learning - Sutton argues that current machine learning primarily focuses on transferring existing human knowledge to static AI, which lacks autonomous learning capabilities [1][2] - He identifies the need for a new data source generated through direct interaction between intelligent agents and the world, marking the transition into an "experience era" [1][2] - The core of intelligence lies in the ability to predict and control input signals based on experience, which is essential for the development of AI [2] Group 2: Future of AI - Sutton's four predictive principles include the lack of consensus on how the world operates, the potential for humans to understand and create intelligence through technology, the likelihood of superintelligent AI surpassing human intelligence, and the concentration of power and resources among the most intelligent agents [2][3] - He posits that humanity is currently in the "replicator era" and is on the verge of entering the "design era," where AI will play a crucial role [3][4] - Sutton encourages embracing AI as a necessary step in the evolution of the universe, advocating for courage and a spirit of adventure in facing its challenges [4]

Core Insights - Richard Sutton, the 2024 Turing Award winner, emphasized that the human data dividend is nearing its limit, and artificial intelligence is entering an "experience era" centered on continuous learning, which has the potential to exceed previous capabilities [1][2] Group 1: AI and Learning - Sutton stated that most current machine learning aims to transfer existing human knowledge to static AI, which lacks autonomous learning capabilities. He believes we are reaching the limits of human data, and existing methods cannot generate new knowledge, making continuous learning essential for intelligence [2] - He defined "experience" as the interaction of observation, action, and reward, which is crucial for an intelligent agent's ability to predict and control its input signals. Experience is the core of all intelligence [2] Group 2: Collaboration and Future Predictions - Addressing fears about AI causing bias, unemployment, or even human extinction, Sutton argued that such fears are exaggerated and often fueled by those who profit from them. He highlighted that economic systems function best when individuals have different goals and abilities, similar to how decentralized collaboration among intelligent agents can lead to win-win outcomes [3] - Sutton proposed four predictive principles for the future of AI: 1. There is no consensus on how the world should operate, and no single view can dominate [3] 2. Humanity will truly understand intelligence and create it through technology [3] 3. Current human intelligence will soon be surpassed by superintelligent AI or enhanced humans [3] 4. Power and resources will flow to the most intelligent agents [3] Group 3: Historical Context and Future Outlook - Sutton categorized the history of the universe into four eras: the particle era, the star era, the replicator era, and the design era. He believes humanity's uniqueness lies in pushing design to its limits, which is the goal pursued through AI today [4] - He described AI as the inevitable next step in the evolution of the universe, urging society to embrace it with courage, pride, and a spirit of adventure [4] Group 4: Event Overview - The 2025 Inclusion Bund Conference, themed "Reshaping Innovative Growth," took place in Shanghai from September 10 to 13, featuring a main forum, over 40 open insight forums, global theme days, innovation stages, a technology exhibition, and various networking opportunities [4]

Core Insights - The 2025 Inclusion Bund Conference opened in Shanghai, featuring a keynote speech by Richard Sutton, the 2024 Turing Award winner and a pioneer in reinforcement learning [1] Group 1: Machine Learning and AI - Sutton emphasized that current machine learning primarily focuses on transferring existing human knowledge to static, non-autonomous AI, reaching the limits of human data [2] - He introduced the concept of the "experience era," advocating for new data sources generated through direct interaction between intelligent agents and the world [2] - Sutton defined "experience" as the interplay of observation, action, and reward, asserting that knowledge is derived from experience, which is fundamental to intelligence [2] Group 2: Future of AI - Sutton proposed four predictive principles regarding the future of AI: 1. There is no consensus on how the world operates, and no single perspective can dominate [3] 2. Humanity will truly understand intelligence and create it through technology [3] 3. Current human intelligence will soon be surpassed by superintelligent AI or enhanced humans [3] 4. Power and resources will gravitate towards the most intelligent agents [3] - He categorized 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 pursuit of AI [3] Group 3: Embracing AI - Sutton stated that artificial intelligence is the inevitable next step in the evolution of the universe, and it should be embraced with courage, pride, and a spirit of adventure [4]

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 Insights - Richard Sutton, the 2024 Turing Award winner, emphasizes that the human data dividend is nearing its limit, and artificial intelligence is entering an "experience era" centered on continuous learning, which has the potential to exceed previous capabilities [1][2] Group 1: Experience Era - Sutton defines "experience" as the signals of observation, action, and reward that are exchanged between agents and the world, asserting that knowledge derives from experience and that the intelligence of an agent depends on its ability to predict and control its input signals [2] - The transition to the experience era is driven by reinforcement learning, but to fully unlock its potential, two currently immature technologies—continual learning and meta-learning—are required [2] Group 2: Collaboration and AI - Addressing concerns about AI leading to bias, unemployment, or even human extinction, Sutton argues that fears surrounding artificial intelligence are exaggerated, and that decentralized collaboration among different agents can lead to mutually beneficial outcomes [2] - He highlights that humanity's greatest strength lies in collaboration, which has been the foundation of economic, market, and governmental successes [2] Group 3: Future of AI - Sutton posits that the replacement of human roles by AI is inevitable, with humans acting as catalysts and pioneers for the "design era," which he categorizes as the fourth era in the evolution of the universe, following the particle, star, and replicator eras [2][3] - He encourages embracing the evolution of artificial intelligence with courage, pride, and a spirit of adventure [3]

Core Insights - Richard Sutton, the 2024 Turing Award winner, emphasizes that the human data dividend is nearing its limits, and artificial intelligence is entering an "experience era" centered on continuous learning, which has the potential to exceed previous capabilities [1][2] Group 1: Experience Era - Sutton defines "experience" as the interaction of observation, action, and reward, which are signals exchanged between agents and the world [2] - The current machine learning methods are reaching their limits in generating new knowledge, making them unsuitable for continuous learning, which is crucial for intelligence [1][2] Group 2: Technological Advancements - To fully unlock the potential of AI in the experience era, two currently immature technologies are needed: continual learning and meta-learning [2] - Sutton believes that the collaboration between decentralized agents can lead to win-win outcomes, countering fears about AI causing bias, unemployment, or even human extinction [2] Group 3: Human-AI Collaboration - Sutton argues that human collaboration is the greatest success, and AI's role will be to enhance this collaboration, which is fundamental to economic, market, and governmental successes [2] - He posits that AI's replacement of human roles is inevitable, with humans acting as catalysts in ushering in a new "design era" in the evolution of the universe [2] Group 4: Future Perspective - Sutton views artificial intelligence as a necessary next step in the evolution of the universe, advocating for a courageous and adventurous approach to its development [3]