与此同时，软件研究院还将与各成员单位携手，共同建设开放、协同的智能体产业生态，推动智能技术 与实体经济深度融合，为落实"人工智能+"行动、促进数字经济高质量发展、支撑网络强国建设持续注 入创新动力。 软件研究院此次入选，不仅是行业对其技术能力的认可，也寄托了其在智能体产业发展中发挥引领作用 的期待。未来，软件研究院将依托该计划平台，深度融入智能体产业生态，围绕行业标准共建、核心技 术攻关、创新成果转化等重点方向持续投入。一方面，研究院将紧跟智能体前沿技术，持续优化算法模 型与应用框架，巩固全栈技术优势；另一方面，将面向数智能源、政务服务、智能制造等重点领域，拓 展场景化应用的深度与广度，打造可复制、可推广的行业解决方案。 近日，2025"人工智能+"产业生态大会在北京召开。大会核心论坛——"人工智能与智能体应用论 坛"以"携手共启智能体创新应用新纪元"为主题，汇聚政府、产业、学术、研究及应用各方代表，共同 探讨智能体技术发展路径与产业落地前景。会上，中国联通软件研究院（以下简称"软件研究院"）凭借 其在智能体领域的技术积累与行业影响力，成功入选中国互联网协会主导的"智能体创新推进计划"成员 单位，以技术标杆身 ...

但有趣的是，就在今年年初，MCP还曾一度占据了AI界的头版头条，几乎所有从业者都高呼"MCP让AI 连接万物"、"AI终于有了属于自己的USB接口"、"Agent时代的基础设施"。然而仅仅半年时间过去后， MCP就从圈内人眼中的"小甜甜"，光速蜕变为"牛夫人"。 那么MCP为何会被捧上神坛，又为什么光速陨落呢？其实这是因为MCP的走红本身就很违和，属于 是"期望膨胀期"的典型产物。此外需要注意的是，MCP并非出道即巅峰，它的走红过程与ChatGPT、 DeepSeek截然不同。 不久前在11月25日，AI独角兽Anthropic发文庆祝MCP协议（模型上下文协议）诞生一周年。然而如今 整个AI业界对于Anthropic此举即便不说视而不见，也算得上是漠不关心了，这个消息在社交平台的讨 论度更是趋近于零。 不难发现，MCP是一个为智能体服务的协议，它给予了智能体获得"真功夫"的机会，这也是为什么 MCP会在今年年初走红。从某种意义上来说，先有"2025年是智能体之年"这个说法，后来才有MCP登 上舞台中央，而力推MCP则是一众AI大厂的默契。 在2024年的最后一天，OpenAI首席执行官山姆·奥特曼公布了20 ...

Core Insights - The future may see the emergence of "one-person unicorn companies," where a single CEO manages multiple AI agents, while human employees evolve into "goal architects" who can leverage AI to enhance their capabilities and deliver greater value [1][4]. Group 1: Future of Work - Human employees will not be easily replicable, whereas "super intelligent agents" can be infinitely replicated, enabling rapid global expansion for companies [1][4]. - The core competitive advantage for future enterprises will hinge on three key aspects: early adoption and use of AI agents, selection of the most advanced AI agents, and continuous training of these agents using closed-loop data to enhance their capabilities [1][4]. Group 2: Strategic Recommendations - Companies should prioritize early and swift integration of AI agents into their operations [1][4]. - The importance of utilizing closed-loop data for ongoing training of AI agents is emphasized as a critical factor for success [1][4].

Core Insights - The launch of Doubao Mobile Assistant has sparked significant discussions and reactions in the tech industry, marking a pivotal moment for AI applications in mobile technology [1][3] Timeline Summary - On December 1, ByteDance released the preview version of Doubao Mobile Assistant in collaboration with ZTE, showcasing its capabilities on the Nubia M153 model [2] - Starting December 2, users reported issues with WeChat and other apps being inaccessible due to the assistant's operations [2] - On December 3, Doubao announced the removal of WeChat operation features in response to user concerns [2] - On December 5, Doubao stated plans to regulate AI operations on mobile devices to address fairness and security issues [2] Technological Impact - Doubao Mobile Assistant demonstrates enhanced control capabilities, supported by system-level integration, which distinguishes it from typical apps [3] - The assistant's ability to interact directly with users may disrupt traditional app engagement and advertising models, as it could potentially replace user interactions with AI-generated actions [3] Ecosystem Disruption - The introduction of mobile AI assistants like Doubao could challenge existing app ecosystems by altering user engagement and data monetization strategies [3][4] - Previous instances of AI assistants facing restrictions from apps like Bilibili and WeChat highlight the ongoing tension between AI capabilities and app permissions [4] Privacy and User Authorization Concerns - The functionality of mobile assistants raises critical questions about data privacy, user consent, and the boundaries of app data access [5] - Key issues include the effectiveness of user authorization, the need for app consent, and the potential for third-party data access [5] Industry Developments - The competition for data access and user engagement is intensifying, with AI glasses also emerging as a new battleground for tech companies [6] - The recent draft regulations from the Cyberspace Administration of China emphasize the need for regular risk assessments for data handling by network data processors [6]

Group 1 - The 2025 Digital Intelligence Technology Ecological Conference in Guangzhou focuses on the deep integration of artificial intelligence and digital technology [1] - The National Data Bureau emphasizes the need for open collaboration to build a unified national data element market, fostering a more open industrial ecosystem [1] - Guangdong Province is leading in the market-oriented allocation of data elements, viewing AI and data as core new productive forces driving high-quality economic growth [1] Group 2 - China Telecom introduced the Starry Sky Intelligent Service Platform 1.0, featuring the "Xing Xiaochen" intelligent agent for cross-terminal and cross-scenario intelligent services [2] - The intelligent agent supports users in completing complex tasks through natural language, transforming user interaction [2] - High-quality datasets are identified as the foundation for enhancing AI capabilities, with over 500 PB of high-quality datasets constructed nationwide as of September [2] - The National Data Development Research Institute proposes a new approach to advance high-quality dataset construction, focusing on compliance review, quality assessment, and industry mapping [2]

Core Viewpoint - The competition in the AI industry is shifting from large model parameters to the hardware applications of AI, with major companies vying for the next generation of hardware entry points, particularly AI glasses and smartphones [5][6]. Group 1: AI Hardware Competition - Major companies like Alibaba, ByteDance, and Baidu are rapidly developing AI glasses to establish a foothold in the AI hardware ecosystem [4][6]. - The AI glasses are seen as the next critical terminal after smartphones, with both startups and major internet companies entering the market [6][7]. - The integration of AI capabilities into smartphones and AI glasses aims to create a closed-loop hardware ecosystem, with ByteDance's ambitions being particularly notable [7][13]. Group 2: User Interaction and Functionality - The "Doubao AI Assistant" on the Nubia M153 smartphone can perform tasks such as gaming and controlling smart devices, showcasing the potential of AI in enhancing user experience [8][11]. - AI assistants from various companies, including Alibaba's Qianwen Assistant, are being integrated into AI glasses to enable voice-controlled operations [12]. - The future of smartphones may involve AI generating interfaces and operations based on user intent, reducing reliance on traditional input methods [13]. Group 3: Regulatory Challenges - The integration of AI assistants with third-party applications like WeChat faces significant regulatory hurdles, leading to the suspension of certain functionalities due to compliance issues [15][17]. - Major apps, particularly WeChat, have strict regulations against automated operations, which complicates the deployment of AI assistants [17][22]. - Previous attempts by other smartphone manufacturers to integrate AI functionalities with WeChat have also been halted, indicating a broader trend of resistance from app developers [18][20]. Group 4: Hardware Development Challenges - Internet companies lacking hardware expertise face significant challenges in developing smart terminals, as evidenced by past struggles of companies like Google and ByteDance in the smartphone market [23][24]. - Despite skepticism about the sustainability of hardware ventures, some experts believe that companies like ByteDance can leverage their existing user base to support hardware initiatives [25]. - Alibaba's strength lies in its stable B2B customer base, while Baidu's advantage is its search capabilities, which can enhance the functionality of AI glasses [25].

Investment Rating - The report does not explicitly state an investment rating for the industry. Core Insights - The emergence of AI is significantly transforming the structure, scale, and boundaries of enterprises, leading to the concept of "Agent-native enterprises" that operate in collaboration with AI, resulting in lower operational costs [9]. - The report emphasizes the need for enterprise-level applications of AI, highlighting the differences between consumer-grade and enterprise-grade AI applications, particularly in terms of reliability, security, and compliance [18]. - A unified data governance framework is essential for effectively managing both structured and unstructured data, addressing the current challenges of data silos and inefficiencies in data utilization [93][99]. Summary by Sections PART 1: Evolution from Response to Execution - The transition from traditional media applications to AI-driven solutions is discussed, emphasizing the need for businesses to adapt to AI capabilities for improved efficiency and effectiveness [12][15]. PART 2: Tencent Cloud Intelligent Agent Development Platform - The platform supports various application modes, including standard, workflow, and multi-agent modes, catering to diverse business needs [49][50]. - The platform's advantages include high accuracy in task execution, strong multi-agent collaboration capabilities, and comprehensive security and compliance features [47]. PART 3: Unified Data Governance in the AI Era - The report outlines the current state of media data systems, identifying issues such as data fragmentation and the lack of a unified processing framework for structured and unstructured data [96][103]. - It highlights the importance of integrating data insights into business strategies to enhance decision-making processes [110].

公司情报专家《财经涂鸦》获悉，12月2日，IDC全球研究集团副总裁Rick Villars在"IDC FutureScape2026：中国ICT市场预测论坛"中，发表题为《迈向智能新纪元：重塑全球IT产业的三大驱动 力》的主旨演讲。 他指出，全球科技产业正进入扩张时代，2027年，服务器与存储市场总支出将突破7000亿美元，软件支 出将超过16.7亿美元。然而，仅13.6%的北美企业、2.4%的亚太企业能从多数AI项目中获得可衡量收 益，凸显价值落地仍是关键挑战。 "要突破AI应用的下一个壁垒，企业需制定企业级AI战略，打造AI就绪的员工队伍，并构建AI就绪的技 术栈。"Rick Villars指出。 整体来看，中国和美国正在推动AI的科技进步。其中，美国是AI扩张的重要推动力，主要源自AI基础 架构和软件驱动，而中国则是AI基础架构驱动更多。 突破AI应用下一个壁垒包括三个方向 AI支出方面，预计2026年中国和美国的增长重点将各有侧重。 具体来看，美国将重点着墨构建人工智能代理以实现业务流程自动化、增强网络恢复和弹性、企业数据 中心的基础设施现代化，分别预计增长48%、33%、31%。 中国则更注重核心企 ...

中证报中证网讯(王珞)日前，三维天地（301159）研发负责人张京日公开表示，三维天地系列创新产品 的推出，将推动前沿的AI技术，转化为能切实改变企业工作模式的产品。2025年，三维天地密集推出 了企业级AI智能体开发平台SunwayLink、国产质量统计分析软件QRS，并对数据资产、低代码等平台 进行了智能化升级。这一系列动作的背后，是一个清晰的双轨战略：一方面，积极拥抱AI，驱动核心 产品智能化；另一方面，攻坚关键技术，实现高端工业软件的国产化自主可控。 张京日强调，技术的价值在于解决真实问题。以SunwayLink为例，该产品的设计理念并非追求大模型 的通用能力，而是致力于降低AI的应用门槛。通过低代码交互和与企业知识库的深度连接，让业务专 家能够快速构建懂得自身业务流程的专属"数字员工"，将想法转化为可执行智能体的路径大幅缩短。 三维天地QRS数据处理分析平台则承载着深度融合国内制造业的场景与标准的期待。张京日表示，QRS 数据处理分析平台在数据安全、协议适配和行业模板等方面，具备了独特的本土化优势。 为在工业场景实现精准适配，三维天地深度调研国内200余家制造企业，在产品内置了符合GB/T、ISO ...

Core Insights - Amazon Web Services (AWS) positions itself as the best platform for building and running intelligent agents, showcasing new tools for agent development at the AWS re:Invent conference [1][3]. Group 1: Strands Agents SDK Enhancements - The Strands Agents SDK now supports TypeScript and edge devices, facilitating easier agent construction and expanding applications in automotive, gaming, and robotics [3][4][6]. - The SDK has been downloaded 5.299 million times since its release, indicating strong developer interest [4]. Group 2: Amazon Bedrock AgentCore Innovations - Amazon Bedrock AgentCore introduces several features: policy functions for setting operational boundaries, evaluation functions for assessing agent performance, and episodic memory for learning from past experiences [9][13]. - The platform aims to simplify the deployment of production-grade agents, addressing the complexities that slow down innovation [9][10]. Group 3: Model Customization and Efficiency - Amazon Bedrock and SageMaker AI introduce new features to streamline model customization, allowing developers to enhance model accuracy without deep machine learning expertise [19][20]. - The Reinforcement Fine-Tuning feature can improve model accuracy by an average of 66%, enabling cost-effective and efficient model performance [21][23]. Group 4: SageMaker HyperPod and Training Efficiency - Amazon SageMaker HyperPod offers a checkpointless training feature, allowing for rapid recovery from infrastructure failures within minutes, maximizing training efficiency [28][29]. - This innovation significantly reduces operational costs and downtime, enhancing the overall training process [31]. Group 5: Amazon Nova Act for Reliable Automation - Amazon Nova Act is designed to help developers build and manage reliable agents for automating UI workflows, achieving over 90% task reliability [32][35]. - The service integrates with various AI frameworks, enabling scalable and dependable automation solutions [36]. Group 6: Future Outlook - AWS aims to be the leading platform for building intelligent agents, emphasizing the importance of generative AI in business transformation [38].