AI将受困于人类数据

Core Insights - The article discusses the transition from the "human data era" to the "experience era" in artificial intelligence, emphasizing the need for AI to learn from first-hand experiences rather than relying solely on human-generated data [2][5][10] - Richard S. Sutton highlights the limitations of current AI models, which are based on second-hand experiences, and advocates for a new approach where AI interacts with its environment to generate original data [6][7][11] Group 1: Transition to Experience Era - The current large language models are reaching the limits of human data, necessitating a shift to real-time interaction with environments to generate scalable original data [7][10] - Sutton draws parallels between AI learning and human learning, suggesting that AI should learn through sensory experiences similar to how infants and athletes learn [6][8] - The experience era will require AI to develop world models and memory systems that can be reused over time, enhancing sample efficiency through high parallel interactions [3][6] Group 2: Decentralized Cooperation vs. Centralized Control - Sutton argues that decentralized cooperation is superior to centralized control, warning against the dangers of imposing single goals on AI, which can stifle innovation [3][12] - The article emphasizes the importance of diverse goals among AI agents, suggesting that a multi-objective ecosystem fosters innovation and resilience [3][12][13] - Sutton posits that human and AI prosperity relies on decentralized cooperation, which allows for individual goals to coexist and promotes beneficial interactions [12][14][16] Group 3: Future of AI Development - The development of fully intelligent agents will require advancements in deep learning algorithms that enable continuous learning from experiences [11][12] - Sutton expresses optimism about the future of AI, viewing the creation of superintelligent agents as a positive development for society, despite the long-term nature of this endeavor [10][11] - The article concludes with a call for humans to leverage their experiences and observations to foster trust and cooperation in the development of AI [17]