正值大模型从"算力堆叠"走向"推理优先"的关键节点，清华大学智能产业研究院（AIR）创始院长、中国工程院外籍院士张亚勤提出： 新一轮人工智能，是信息智能、物理智能和生物智能的融合，本质上也是原子、分子和比特的融合。 也就是说，在规模定律持续发挥作用的前提下，当参数规模、数据体量与算力资源跨过某个阈值，智能就不再只停留在模式识别，而是开始"涌现"—— 先是从鉴别式 AI 走向生成式 AI，再从生成式 AI 走向以智能体为代表的新范式。 在本次量子位 MEET2026 智能未来大会上，他也将 ChatGPT 和 DeepSeek，视作这一轮演进中的两个重要里程碑： 从 ChatGPT 到 DeepSeek，AI 正沿着"智能 +"的路径进入新一轮浪潮。 至于未来 5~10 年的主战场，在他看来，将走向"智能体互联网"时代 —— 基础大模型像操作系统一样在全球范围内收敛到不超过 10 个；而智能体会取代 今天的大部分 SaaS 和 App，成为企业和个人与世界交互的默认形态，同时这也是通往 AGI 的必经之路。 为了完整体现张亚勤的思考，在不改变原意的基础上，量子位对演讲内容进行了编辑整理，希望能给你带来更多启发。 ...

10年以后的机器人比人还要多。 "10年以后的机器人比人还要多，未来的Saas和APP都会被智能体取代……"12月10日，清华大学智能产业研究院院长、中国工程院外籍院士张 亚勤在Meet2026智能未来大会上，一口气谈了他对于人工智能未来的多个趋势性洞见。 AI正在从信息世界走向物理世界和生物世界。他将这个过程描述为从大语言模型走向VLA（视觉-语言-动作）模型——不仅要理解文字和图 像，还要在真实世界中行动。其中无人驾驶在今年已到拐点，预计到2030年，约10%的新车将具备无人驾驶能力，那将是自动驾驶 的"DeepSeek时刻"。 机器人是张亚勤眼中"未来最大的赛道"。尽管人形机器人成熟尚需时日，但他认为十年内机器人的数量或将超过人类。但他同时也提醒，AI能 力的快速提升也伴随着风险的急剧增加。 基于对技术架构的前瞻，张亚勤展示了他绘制的演进图。在ChatGPT问世不久后他构想的架构中，基础大模型作为平台，之上支撑着各垂直领 域模型、SaaS服务层，最上层是各类应用APP。而在今年10月的更新中，他明确提出，未来的SaaS服务和终端APP都将被智能体所取代——智 能体即未来的软件与服务形态。这些智能体将涵盖 ...

Core Insights - Wuxi Zijing Zhikang Technology Co., Ltd. has completed an angel round financing of nearly 100 million RMB, with participation from Xinglian Capital, Inno Angel Fund, and Shangshi Capital [1][2]. Company Overview - Zijing Zhikang was established in September 2024, with a core team from Tsinghua University's Intelligent Industry Research Institute, recognized as a leading global research team in medical intelligent algorithms [2]. - The company’s research work, Agent Hospital, establishes generative models for disease occurrence and development, providing a data flywheel for the evolution of medical intelligent agents [2]. - Agent Hospital has achieved top-level performance on the U.S. medical licensing examination dataset and has constructed medical intelligent agents across more than twenty departments, gaining significant attention from both academia and industry [2]. - The company aims to leverage cutting-edge large model intelligent technology to empower smart healthcare, offering convenient, affordable, and high-quality medical services to global users [2].

Group 1 - The core theme of the event is "Medical Health Full-Scenario Intelligent Systems," showcasing five major industry intelligent systems by Zhongkang Technology [1] - The drugstore intelligent system and commercial intelligent system attracted significant attention with immersive experience zones, highlighting Zhongkang's leading position in the AI healthcare sector [1] Group 2 - Zhongkang Technology officially released a major upgrade plan for the Zhongkang Drugstore Intelligent System, focusing on five core intelligent systems for collaborative evolution [2] - The upgrade aims to transform the drugstore model from a simple medication provider to a "smart health steward," marking the entry of the pharmaceutical retail industry into an "algorithm-driven" era [2] - The full-chain AI decision-making system is constructed based on vast industry data, enhancing operational insights, member management, product improvement, staff empowerment, and disease management [2] Group 3 - Zhongkang Technology introduced a product matrix of commercial AI intelligent systems, including super individual intelligent systems, AI digital marketing growth platforms, and industrial marketing digital foundations [3] - The solutions empower pharmaceutical companies across marketing decision-making, sales execution, and terminal operations, achieving a sevenfold efficiency increase [3] - The complete value closed loop covers data governance, intelligent applications, and business implementation, redefining digital transformation standards in the pharmaceutical industry [3]

Industry Insights - The Zhejiang Provincial Health Commission and other departments have launched an action plan to accelerate the high-quality development of "Artificial Intelligence + Healthcare," focusing on creating multimodal medical industry models and autonomous AI research frameworks [1] - The plan aims to develop specialized models and medical intelligent systems covering various areas such as medical services, health management, public health, and drug/device research [1] - Significant technology projects will be implemented in fields like AI data and applications, brain-computer interfaces, and new drug development, with an emphasis on interdisciplinary collaboration in medical AI research [1] Market Trends - The report from Founder Securities highlights that the "Artificial Intelligence +" initiative is driving revolutionary changes in the medical industry, with rapid deployment of high-end innovative devices like brain-computer interfaces and surgical robots [2] - The commercialization of non-invasive brain-computer interfaces is accelerating, particularly in medical rehabilitation and emotional management, indicating a broad market potential [2] - The AI healthcare sector is expected to see accelerated commercialization due to supportive policies, with AI applications in pathology diagnosis, imaging, and drug development being relatively mature [2] Company Developments - Sanbo Brain Science focuses on high-barrier technologies in neurosurgery, leveraging a "medical education research" system for technology transfer and expansion, positioning itself well in the private brain healthcare sector amid aging and precision medicine trends [3] - WuXi AppTec is centered on empowering the entire chain of innovative drugs with AI, benefiting from high technical barriers and global production capabilities, particularly in the context of GLP-1 and gene therapy trends [4]

Core Viewpoint - The Zhejiang Provincial Health Commission and ten other departments have issued an action plan to accelerate the high-quality development of "Artificial Intelligence + Healthcare" from 2025 to 2027, focusing on data resource aggregation and the establishment of a robust health data management system [1] Group 1: Data Management and Standards - The plan emphasizes the need to develop and improve data security management and utilization systems in the healthcare sector [1] - It aims to establish a health data standard system to enhance the quality and capacity of health data [1] - The initiative includes the construction of a trustworthy data space for the healthcare industry and the development of data governance tools and intelligent engines [1] Group 2: AI Development and Research - The action plan outlines the creation of a provincial medical bioinformatics database and the sharing of high-quality industry datasets and corpora [1] - It aims to build a multi-modal medical industry large model and establish a fully autonomous AI research and development framework [1] - The plan encourages the development of specialized models and medical intelligent agents covering various areas such as medical services, health management, public health, and drug/device research [1] Group 3: Interdisciplinary Collaboration and Innovation - The initiative focuses on deploying major technological projects in fields like AI data and applications, brain-computer interfaces, and new drug development [1] - It promotes interdisciplinary collaboration among research institutions to generate globally influential research outcomes in medical AI [1]

Core Insights - The emergence of medical AI agents marks a significant shift in the healthcare industry, transitioning from a focus on large models to intelligent agents that enhance service delivery and operational efficiency [1][2][3] Group 1: Development of Medical AI Agents - The relationship between large models and intelligent agents is characterized by a division of labor, where large models handle cognitive tasks while agents perform actions based on environmental inputs [2] - Medical AI agents are being deployed across various healthcare scenarios, including patient services, diagnostic assistance, hospital management, and even in research and education [3][4] Group 2: Application Scenarios and Key Players - In-hospital applications include patient services, diagnostic assistance, and hospital management, with companies like 惠每科技, 金域医学, and 微医 leading the charge [4] - Out-of-hospital applications feature AI family doctors and health management systems, with key players such as 京东健康 and 平安好医生 [4] - Specialized AI agents are emerging in fields like drug development and insurance claims, with companies like 健康之路 and 中康科技 involved [4] Group 3: Personalization and Specialization - The trend towards personalization in AI agents includes the creation of virtual personas and unique names to enhance user engagement and trust [5][6] - Specialized diagnostic agents are being developed to address specific medical conditions, such as the "腹痛诊疗智能Agent" for abdominal pain management [8][9] Group 4: Challenges and Future Directions - Current medical AI agents are primarily iterative upgrades and have not yet achieved breakthroughs in foundational models [12][14] - The development of specialized agents requires deep involvement from clinical experts to ensure effectiveness and relevance [15] - The advancement of foundational AI capabilities is crucial for the realization of fully functional medical AI agents [16]

Core Insights - The integration of artificial intelligence (AI) in healthcare is transforming the industry by enhancing service quality and efficiency across the entire medical service chain, from early screening to precision treatment and drug development [1] Group 1: AI in Healthcare - AI technology is being utilized to address pain points in primary healthcare, particularly in managing chronic diseases and elderly care, with Shanghai leading the implementation of AI-driven family doctor systems [2][3] - The launch of the "AI Family Doctor" by YaoYing Medical, in collaboration with the Shanghai Artificial Intelligence Laboratory, aims to provide comprehensive healthcare services tailored to individual family members' health profiles [2][3] - Shanghai Telecom and its partners have developed a clinical decision support system for family doctors, integrating AI with authoritative medical knowledge to enhance healthcare delivery [3] Group 2: AI Applications and Innovations - The AI Family Doctor has shown effectiveness in chronic disease management by monitoring key health indicators and providing timely alerts for patient intervention [4][5] - New features such as "shared health records" allow family members to manage health data collectively, promoting intergenerational health management [5] - The introduction of specialized AI models, such as the "CardioMind" for cardiac care, demonstrates the ongoing innovation in AI applications within the healthcare sector [5][6] Group 3: Future of AI in Healthcare - The rapid iteration of multimodal AI models is paving the way for smart hospital construction and clinical decision-making innovations, making AI integration a necessity in healthcare [6] - Future developments in AI healthcare applications are expected to focus on "digital therapeutics," utilizing AI-driven interventions to directly influence patient behavior and health outcomes [6] - The convergence of AI and the health industry is anticipated to create new business models and collaborative innovations across the healthcare ecosystem [6]

Group 1 - The launch of the "Yuan Zhi" medical model by United Imaging on April 9, which includes over 10 medical AI applications covering various scenarios such as imaging diagnosis and patient services [1] - The "Yuan Zhi" medical imaging model is trained on tens of millions of medical imaging data and hundreds of thousands of finely annotated data, achieving over 95% accuracy in key tasks like complex lesion diagnosis and organ segmentation [1] - The challenges of data privacy, ethical review, and building trust between doctors and patients remain significant hurdles for the practical implementation of medical AI [1] Group 2 - The unveiling of the Guangdong Provincial Transportation Industry Computing Power Center on April 9, which is a key infrastructure for the digital transformation of the transportation sector in Guangdong [2] - The center is built according to national A-level data center standards, with a plan for 638 standard cabinets, and the initial phase has completed 324 cabinets to meet diverse computing needs [2] - The investment in high-standard resources is expected to enhance road network management efficiency and data-driven decision-making capabilities in the transportation industry [2] Group 3 - The upcoming AI training course for provincial officials in Zhejiang, featuring Wang Xingxing, the founder and CEO of Yushu Technology, who will discuss the current state and development trends of the robotics industry [3] - This initiative reflects the local government's emphasis on the strategic importance of the robotics industry and aims to facilitate better alignment between policy and market resources [3] - Continuous updates to the knowledge system in training programs are necessary to prevent disconnection between theoretical understanding and industry practice [3]