智能体将取代APP和SaaS，张亚勤院士发布这些AI洞见

Core Insights - The future will see more robots than humans within the next decade, with a significant shift towards intelligent agents replacing traditional SaaS and applications [1][4] - The new wave of artificial intelligence is characterized by the deep integration of information, physical, and biological intelligence, leading to a digital transformation across various domains [1][3] Group 1: Trends in AI Development - Generative AI is rapidly evolving into agent AI, with task complexity doubling in the past seven months and achieving over 50% accuracy, indicating alignment with human capabilities [3] - The scaling law's effectiveness is slowing during the pre-training phase, shifting focus to reasoning and agent-level intelligence in the post-training phase, with reasoning costs decreasing to one-tenth while agent computational demands have increased tenfold [3] - AI is transitioning from the information realm to the physical and biological worlds, exemplified by the anticipated 10% of new cars featuring autonomous driving capabilities by 2030 [3] Group 2: Robotics and Intelligent Agents - Robotics is viewed as the largest future market, with predictions that the number of robots will surpass humans within ten years, despite the current immaturity of humanoid robots [4] - Intelligent agents are expected to replace traditional SaaS services and applications, with examples such as a medical intelligent agent network simulating a hospital environment, achieving high diagnostic accuracy [4] - The goal of these intelligent agents is to assist rather than replace professionals, such as doctors, who may have dedicated intelligent assistants in the future [4] Group 3: Future Industry Landscape - The foundational large models will serve as the operating systems of the AI era, reshaping industry structures similar to how Windows and Android transformed their respective eras, with an anticipated industry scale 2-3 orders of magnitude larger than previous technological shifts [5] - It is predicted that there will be no more than ten foundational large models globally, with a split between the US and China, supplemented by a few other countries, leading to a dual-track development ecosystem of open-source and closed-source models [5] Group 4: Path to AGI - Achieving Artificial General Intelligence (AGI) will require new algorithmic frameworks, memory systems, and world models, with a potential paradigm shift in the next five years [6] - The comprehensive breakthrough in information, physical, and biological intelligence is expected to take 15 to 20 years to realize [6]