Core Insights - Tencent's core theme for this year is "making 'usable AI' a universal productivity tool" [1] - The company has introduced five major AI productivity platforms: intelligent agent development platform, embodied intelligence open platform Tairos, AIGC content generation platform, edge large model platform, and AI education platform [1] - Several technologies are making their debut, including the latest video call feature of Tencent's Yuanbao, which offers lower latency, more human-like interactions, and emotional engagement [1] Technology Applications - The Yuanbao video call feature is designed to assist elderly and visually impaired individuals, allowing them to ask questions anytime and anywhere [1] - Tencent's latest mixed Yuan model matrix encompasses capabilities for generating and understanding various modalities, including text, sound, images, video, and 3D [1] - The mixed 3D AI creation engine is the industry's first one-stop, low-threshold AI creation tool for 3D content production, significantly enhancing the efficiency of 3D content creation [1]

"数据在实际场景中的应用不断拓展，催生出一批贴近需求、赋能显著的创新场景，持续释放出强大的 数据动能。"国家数据局政策和规划司副司长栾婕在国家数据局"数据要素×"首场新闻发布会上表示。 作为新时代的"石油"，如何实现数据资产转化？如何真正让数据动起来、用起来、活起来？如何让数据 在各个产业、企业中发挥更大价值？ 探寻价值转化路径 《"数据要素×"三年行动计划(2024-2026年)》提出，发挥数据要素报酬递增、低成本复用等特点，可优 化资源配置，赋能实体经济，发展新质生产力，推动生产生活、经济发展和社会治理方式深刻变革，对 推动高质量发展具有重要意义。 随着数据要素在经济发展中的影响力持续提升、人工智能技术的迭代升级以及千行百业数智化转型的纵 深推进，数据应用领域格局也在发生深刻变革。唯有以技术突破来破解治理瓶颈，以场景适配加速成果 转化，才能让数据从"沉睡资源"蜕变为驱动产业升级的"硬核资产"。 据国际IT研究与顾问咨询公司高德纳(Gartner)发布的《2025年数据和分析(D&A)重要趋势》报告，当前 数据领域正呈现九大发展趋势，包括AI代理、小语言模型、合成数据、决策智能平台、复合型AI等， 这些趋势 ...

Core Viewpoint - The article discusses the competitive landscape of AI in China, highlighting the strategic moves of major tech companies as they prepare for an impending AI arms race by 2025, driven by the need for computational power and ecosystem integration [2][10]. Group 1: AI Development and Scaling Law - The emergence of AI technologies, particularly DeepSeek, is tied to the necessity of increasing computational power, as described by the Scaling Law, which states that AI development requires substantial computational resources [3][12]. - Despite initial skepticism regarding the adherence to Scaling Law, it has been observed that even advanced AI models like DeepSeek still require significant computational resources for training and operation [3][12]. Group 2: Historical Context and Cloud Computing - The evolution of cloud computing in China can be traced back to events like the success of "Double Eleven," which highlighted the need for robust computational systems to handle peak loads, leading to the development of Alibaba Cloud [4][5]. - Alibaba Cloud has grown to become the largest cloud service provider in China, serving 4 million customers and reaching 47 million small and medium-sized enterprises globally, with projected revenues of $6.513 billion in 2024 [7]. Group 3: Competitive Strategies of Major Players - Major players like Huawei and Tencent are adopting distinct strategies in the AI space, with Huawei focusing on a fully autonomous technology stack and Tencent leveraging its extensive social ecosystem to enhance its AI capabilities [9][10]. - Tencent's recent capital expenditures for AI projects have shown a decline compared to previous quarters, indicating a cautious approach amidst rising competition and evolving market dynamics [12]. Group 4: Market Dynamics and Challenges - The rise of open-source models like DeepSeek has created a competitive environment where traditional monetization strategies for AI services face challenges, complicating the capital expenditure return cycle for major companies [13]. - The article suggests that the future of AI in China may hinge on who can effectively control the ecosystem, as companies navigate the complexities of free service models and the need for sustainable revenue generation [13].

以下文章来源于AGI接口 ，作者宋思杭 "AI持续落地，每个企业正在成为AI公司，每个人也将成为AI加持的'超级个体'。"汤道生开门见 山地表示。而在加大AI投入力度方面，腾讯的做法可以说是相当激进，其打通了各业务条线与AI 之间的壁垒，极大权限地对各业务开放了AI能力。 而"全面拥抱AI"，既是本场峰会的主题，同时也贯穿了腾讯2025年的全年战略重要。它正在影响 着这家科技大厂的方方面面。在演讲中，汤道生还提出了大模型、智能体、知识库和基础设施"四 个加速"的战略。其中，智能体则是极为重要的一种呈现形式。它所代表的是当大模型在国内走过 三年时间，应用范式的迭代。 然而，究竟什么是智能体？这个定义在行业里似乎还不够清晰。 在大部分人的眼中，智能体是这样的——当你想打开软件订机票，或者查找、整理信息，统计一 个excel表，不再需要打开不同软件app自己完成，而是告诉智能助手，它就能够自动帮你完成，最 终帮你订好机票。就好像在媒体群访间，腾讯云副总裁吴运声对媒体打趣道，"我现在就很希望有 一个智能体来替我回答你们的问题。" 从这个层面来理解，智能体的概念并不模糊。然而，目前之所以概念模糊，正是因为行业内存在 诸 ...

Core Viewpoint - Tencent is aggressively embracing AI across its business lines, aiming to integrate AI capabilities into various applications and services, which is a central theme of its 2025 strategy [1][2][4]. Group 1: AI Strategy and Implementation - Tencent's strategy includes a focus on "four accelerations": large models, intelligent agents, knowledge bases, and infrastructure [1]. - The company emphasizes that every enterprise is becoming an AI company, and individuals will become "super individuals" enhanced by AI [1]. - The intelligent agent concept is highlighted as a key area of development, representing a shift in application paradigms over the past three years [1][2]. Group 2: Understanding Intelligent Agents - The definition of intelligent agents remains unclear in the industry, with varying capabilities and interaction methods leading to user expectation gaps [2][4]. - Intelligent agents are expected to perform tasks autonomously, such as booking flights or organizing information, without requiring users to navigate multiple applications [2]. - Current limitations of intelligent agents include their ability boundaries, which are constrained by factors like permissions, API interfaces, and data silos [3][4]. Group 3: Technological Advancements and Customer Needs - The rapid development of AI technologies is driven by customer demands, leading to an acceleration in the release of visual and multimodal models [8][9]. - Tencent's intelligent agent platform integrates various AI capabilities to create systematic solutions that address real business needs [9][14]. - The company has developed significant knowledge management and workflow capabilities to support the deployment of intelligent agents [10]. Group 4: Challenges and Future Outlook - Challenges include the evolving technology of agent frameworks and the need for customers to understand how to effectively utilize these agents [11]. - The relationship between intelligent agents and large models is reciprocal, with advancements in one area promoting progress in the other [13]. - As model capabilities improve and customer understanding increases, intelligent agents are expected to deliver value across more industry scenarios [12].

Core Insights - The current industry demand for AI is extremely high, with companies eager to engage in discussions about AI applications [1] - Tencent is committed to increasing its investment in AI, aiming to transform the usability of generative AI from "quantitative change" to "qualitative change" [3] - Tencent plans to enhance AI capabilities through four key areas: large models, intelligent agents, knowledge bases, and infrastructure [3] Group 1 - Tencent's AI strategy focuses on creating "user-friendly AI" to integrate AI into various industries and everyday life [3] - The intelligent agent sector is experiencing significant growth, although it is still in its early development stages [3] - The complexity of tasks for intelligent agents requires ongoing advancements in underlying model technologies to improve their capabilities [3] Group 2 - Tencent's upgraded intelligent agent development platform allows businesses to quickly build intelligent agent applications [3] - Applications such as QQ Browser, Tencent Health, CodeBuddy, and Tencent Qidian Marketing Cloud have incorporated intelligent agent capabilities through this platform [3] - Future intelligent agents are expected to evolve into effective assistants that understand enterprise knowledge, utilize tools, and autonomously execute complex tasks [3]

Core Viewpoint - Tencent Cloud has launched an intelligent development platform, integrating DeepSeek-R1, V3 models, and connected search capabilities [1] Group 1: Product Launches - Tencent plans to release a world model mixed 3D scene model soon [1] - The company will open-source enterprise-level mixed reasoning models, edge-side mixed reasoning models, and multimodal foundational models [1] - Recent updates to Tencent's large model products include the launch of the mixed T1 Vision model for visual deep reasoning, an end-to-end voice call model named mixed Voice, and the mixed Image 2.0 model [1]

Group 1: Business Operations and Performance - The company reported a year-end order backlog of 378 million CNY, representing a 27.7% increase year-on-year [3] - New orders and collections have shown steady growth since the first quarter of 2025, supporting the overall performance for the year [3] - The company is focusing on four key strategies to ensure sustainable growth: maintaining strategic focus on large group clients and advantageous business areas, product and market strategy, innovation-driven development, and optimizing resource allocation [3] Group 2: Financial Health and Market Response - The company’s financial status is stable, and it is expected to release regular reports on its operational performance [4] - As of May 9, 2025, the total number of shareholders was 19,296 [5] - The management is closely monitoring stock price fluctuations and is committed to enhancing the company's investment value and returning value to shareholders [6]

中新网福州4月29日电 (记者 刘育英)4月28日，第八届数字中国建设峰会期间，政、企、研多方代表， 聚焦人工智能、大模型、算力、数据要素等前沿技术，在分论坛中掀起了一场关于首都智能化跃迁 的"头脑风暴"。 北京市经济和信息化局党组成员、副局长苏国斌指出，当前北京正加快数字经济与人工智能深度融合， 夯实数字基础设施和智能算力体系，未来将聚焦前沿技术，深化与北京电信等企业的合作，推动首都数 字经济生态优化与智能化升级。 中国信息通信研究院云计算与大数据研究所副所长栗蔚指出，AI云时代下，大模型产业正在经历从"百 模大战"的预训练竞赛向云端推理服务效能优化的战略迁移，工程化作为大模型技术实现产业化的必要 手段，在训练和推理阶段分别侧重软件工程和应用工程，需实现"硬件、软件、模型、应用+专业服 务"五位一体协同，打通全链条价值体系。 会上，北京电信与北京邮电大学共建的"行业数据智能标注联合实验室"正式揭牌。论坛期间，北京电信 展示了在AI、算力、数据要素等领域的相关创新和探索。(完) 目前，中国电信在北京正加速布局算力基础设施，体系化搭建算力调度平台、大模型训练平台、智能体 开发平台和标准化的数据标注体系。北京电信 ...