张亚勤｜未来，每个人、每个设备都将拥有智能体

Core Insights - The Global Young Leaders Dialogue Annual Forum 2025 was held in Beijing from November 18 to 20, focusing on the theme "Decoding the Future with Young Minds" [2][23] - Dr. Ya-Qin Zhang, a prominent figure in AI research, delivered a keynote speech titled "Embracing the New Wave of AI: AI for Better," discussing advancements and future trends in AI [2][23] AI Developments - AI is identified as the technology engine behind the Fourth Industrial Revolution, characterized by the convergence of digital, physical, and biological AI [25] - The Institute for AI Industry Research (AIR) at Tsinghua University has over 20 professors and 400 researchers, focusing on cutting-edge AI advancements [25] State of the Art in AI - Significant advancements in large language models have been achieved through collaborations with companies like ByteDance and Alibaba, improving reinforcement learning performance [28] - The largest self-driving fleet in the world, with over 1,500 autonomous vehicles, operates in Wuhan, demonstrating a safety record 17 times better than human drivers [29][30] - The world's first AI Agent Hospital, developed by Professor Liu Yang, simulates a real hospital environment, achieving a 92% accuracy rate on the USMLE benchmark [32][33] AI in Drug Development - Approximately one-third of professors at AIR are engaged in AI-driven new drug development, which is expected to significantly accelerate the drug development process [33] Comparison of AI in China and the US - In the US, major players include OpenAI and Google DeepMind, while China showcases models like DeepSeek and Qwen from Alibaba, with China leading in electricity grid infrastructure [35] - The competition between China and the US in AI is viewed as a healthy rivalry, with both regions expected to benefit from advancements in AI technology [35] Future Trends in AI - The transition from generative AI to agentic AI and eventually to an internet of agents is anticipated, where every device will have its own agent [37] - It is projected that 80% of AI models will be open-source, with significant opportunities in vertical models for specific applications [37] - The scaling of generative AI is slowing down, indicating that future breakthroughs will come from post-training advancements [37] Timeline for AGI - The potential for achieving Artificial General Intelligence (AGI) in digital AI is estimated to be within five years, while physical AI applications like driverless cars may pass the Turing test in three to five years [38][39]