鱼羊 闻乐 发自 凹非寺 量子位 | 公众号 QbitAI CEO私人助理的活儿，也被Agent盯上了。 每天能独立更新出全公司的日报版"今日头条"，还是完全本地部署、开箱即用的那种： 本体甚至能被CEO拎着走。 没错，整个机箱就A4大小，跟iPhone 15 Pro Max对比起来是这样的： 不卖关子，这么个新鲜角色，名叫智跃Agent一体机。很有意思的一点是，这是市面上首个专门面向CEO打造的软硬一体私有化Agent，目标用户非常明 确。 不强调提供模型和算力，而是把硬件+软件+算力+预置的Agent打包成一个整体，整合在一个超小型的精巧机箱里，搭配App实现插电即用。 在硬件层面，它采用小巧的12L机箱设计，搭载单卡4090，可以说是超小型化的Agent方案。 所有数据处理、存储环节均可以在本地完成，无需依赖外部云端算力资源，在保证数据处理高速响应的前提下，避免了数据传输过程中的延迟和安全风 险。 软件系统则完全基于管理场景自研开发，不仅拥有专属的操作系统，还配套了定制化App。 这种高效联动的整体性特点，让智跃Agent一体机真正做到了开箱即用： 不愧是"Agent应用元年"，连AI新硬件都开始彰显" ...

Core Insights - The article discusses the significant changes in the open-source AI model ecosystem, highlighting a shift towards a more competitive and rapidly evolving landscape, particularly in the AI Agent and Model Serving sectors [4][9][61]. Group 1: Ecosystem Changes - The latest version of the open-source landscape includes 114 projects, a decrease of 21 from the previous version, with 39 new projects and 60 projects that have disappeared, indicating a significant reshuffling in the ecosystem [7][10]. - The average lifespan of projects in the AI model ecosystem is only 30 months, with 62% of projects emerging after the "GPT moment" in October 2022, showcasing a high turnover rate [10][11]. - TensorFlow has been overtaken by PyTorch, which now dominates the landscape, marking a dramatic shift in the competitive dynamics [8]. Group 2: Key Trends - The article identifies three main areas of focus: AI Coding, Model Serving, and LLMOps, which are emerging as the primary tracks in the evolving landscape [29][61]. - AI Coding has transitioned from merely assisting in code writing to becoming a comprehensive lifecycle engine, indicating a significant increase in its capabilities and market potential [43][44]. - The AI Data sector remains relatively stable but is expected to evolve as new challenges arise in the native large model era, suggesting a potential for future growth [82][88]. Group 3: Global Contributions - The United States and China contribute over 55% of the total developer population in the open-source AI space, with the U.S. leading at 37.41% [17][20]. - In specific areas, the U.S. has a dominant position in AI Infrastructure and AI Data, with contributions significantly higher than those from China [19][23]. Group 4: Licensing Trends - There is a noticeable trend towards more restrictive open-source licenses, with many new projects adopting custom agreements that allow for greater control by the license holders [90][92]. - This shift raises questions about the definition of "open source" in the current competitive environment, as some projects that are popular on platforms like GitHub are not fully open-source [94].

鱼羊 闻乐 发自 凹非寺 量子位 | 公众号 QbitAI CEO私人助理的活儿，也被Agent盯上了。 每天能独立更新出全公司的 日报版"今日头条" ，还是完全 本地部署 、 开箱即用 的那种： 本体甚至能被CEO拎着走。 没错，整个机箱就A4大小，跟iPhone 15 Pro Max对比起来是这样的： 不卖关子，这么个新鲜角色，名叫智跃Agent一体机。很有意思的一点是，这是市面上首个专门面向CEO打造的软硬一体私有化Agent，目标 用户非常明确。 不愧是"Agent应用元年"，连AI新硬件都开始彰显"个性"了。 到底怎么一回事，量子位编辑部的同事们也是率先过了一把CEO瘾，咱们一边实测，一边看看2025年的AI新硬件，都进化成什么样的形态了 —— 开箱即用的"信息管理助手" 传统的一体机大家已经比较熟悉了，大体上是算力+模型供给的模式，基本上买到手里还是得给它配个专门的开发团队。 与之相比，智跃Agent一体机实际上属于一个 全新的概念，定位并不相同 。 在硬件层面，它采用小巧的12L机箱设计，搭载 单卡4090 ，可以说是超小型化的Agent方案。 所有数据处理、存储环节均可以在本地完成，无需依赖外 ...

Industry Investment Rating - The industry investment rating is "Outperform the Market" and is maintained [1] Core Insights - The report highlights Tencent's dual efficiency engines of "Intelligentization" and "Globalization" as key strategies for growth, with a focus on AI capabilities and international market expansion [4][6] - Tencent's AI development platform has seen significant enhancements, with nearly 600 new features added, enabling users without programming experience to create AI products [5] - The report emphasizes Tencent Cloud's robust growth in international business, with a doubling of overseas customer numbers over the past three years, indicating strong demand for its services [4] Summary by Sections Industry Overview - The closing index level is 5617.07, with a 52-week high of 5841.52 and a low of 2855.49 [1] Recent Developments - Tencent has launched its "Intelligent Agent Strategy" and is enhancing its AI capabilities across various business sectors, including advertising and gaming, leading to significant revenue growth [5][6] - The AI capabilities are integrated into Tencent's advertising business, resulting in a 20% increase in marketing service revenue in Q2 [5] Investment Recommendations - The report suggests focusing on companies involved in AI agents and domestic computing power, listing several key players in these sectors [8]

作者 | 黄昱 2025年AI应用爆发，同时迎来Agent元年等背景下，推理需求暴涨。为了抓住这一机遇，云服务厂商也积极升级云基础设施，来满足市场需求。 9月16日，在2025腾讯全球数字生态大会上，腾讯集团副总裁、腾讯云总裁邱跃鹏表示，大模型产业重心从训练到推理的转变，已经成为行业共识。同时客 户对于使用大模型和建设Agent迸发出强烈热情，这都带来了推理需求的暴涨。 这也意味着，AI基础设施要同步升级。 近年来，腾讯云正不断升级云基础设施，以支撑Agent规模化落地和企业全球化发展。据邱跃鹏介绍，腾讯云已在推理加速、Agent Infra和国际化布局等方 面取得突破，并将以更加开放的姿态，助力企业把握时代机遇。 在推理加速方面，腾讯云深入参与开源贡献，向DeepSeek、vLLM、SGLang等社区提交了多项优化技术。同时，针对大模型推理面临的内存瓶颈，腾讯云自 研并开源FlexKV 多级缓存技术，大幅降低KVCache的占用，将首字时延降低多达70%。 同时，邱跃鹏透露，腾讯云依托异构计算平台整合多种芯片资源，向外界提供高性价比的 AI 算力。目前，该平台已全面适配主流国产芯片。 据悉，软硬件协同全栈优 ...

Core Insights - Tencent Cloud is actively participating in the open-source community and has developed a heterogeneous computing platform that integrates various chip resources to provide cost-effective AI computing power [1][5] - The shift in the large model industry from training to inference has led to a surge in demand for inference capabilities, prompting upgrades in AI infrastructure [3][4] - Tencent Cloud's infrastructure now covers 55 availability zones globally, with over 3,200 acceleration nodes, and has successfully defended against a 183% year-on-year increase in DDoS attacks [1][10] Group 1: AI Infrastructure and Optimization - Tencent Cloud has contributed multiple optimization technologies to open-source communities, including FlexKV multi-level caching technology, which reduces KVCache usage and lowers first-word latency by up to 70% [1][4] - The company has optimized GPU communication performance by 30% and doubled performance in common data center environments through enhancements to the DeepEP technology [3][4] - The introduction of the Agent Runtime solution provides a secure and efficient environment for deploying AI agents, integrating various components such as execution engines and cloud sandbox services [5][6] Group 2: Global Expansion and Client Support - Tencent Cloud has established nine technical support centers globally and plans to build new availability zones in Osaka, Japan, and Saudi Arabia, enhancing its international presence [1][14] - The company successfully migrated a large-scale project for GoTo, Indonesia's largest tech group, completing over 500 customized requirements and establishing a third availability zone in just five months [14] - Tencent Cloud's services have been recognized as a leader in the global gaming cloud platform market, providing robust infrastructure to support over 10,000 games and ensuring low-latency experiences for players worldwide [10][11] Group 3: Advanced Technologies and Services - The Cloud Mate service, which consists of various sub-agents, enhances cloud governance and risk management, achieving a 95% interception rate for risky SQL queries [8][9] - The integration of AI with database optimization has resulted in an 80% reduction in total latency for complex queries, showcasing Tencent Cloud's commitment to improving performance [9][10] - The EdgeOne product, which combines AI and security acceleration, has facilitated over 100,000 users in deploying e-commerce web pages quickly and efficiently [11][12]

Core Insights - The article discusses the evolution of AI, particularly focusing on the transition to the "second half" of AI development, emphasizing the importance of language and reasoning in creating more generalizable AI systems [4][62]. Group 1: AI Evolution and Language - The concept of AI has evolved from rule-based systems to deep reinforcement learning, and now to language models that can reason and generalize across tasks [41][43]. - Language is highlighted as a fundamental tool for generalization, allowing AI to tackle a variety of tasks by leveraging reasoning capabilities [77][79]. Group 2: Agent Systems - The definition of an "Agent" has expanded to include systems that can interact with their environment and make decisions based on reasoning, rather than just following predefined rules [33][36]. - The development of language agents represents a significant shift, as they can perform tasks in more complex environments, such as coding and internet navigation, which were previously challenging for AI [43][54]. Group 3: Task Design and Reward Mechanisms - The article emphasizes the importance of defining effective tasks and environments for AI training, suggesting that the current bottleneck lies in task design rather than model training [62][64]. - A focus on intrinsic rewards, which are based on outcomes rather than processes, is proposed as a key factor for successful reinforcement learning applications [88][66]. Group 4: Future Directions - The future of AI development is seen as a combination of enhancing agent capabilities through better memory systems and intrinsic rewards, as well as exploring multi-agent systems [88][89]. - The potential for AI to generalize across various tasks is highlighted, with coding and mathematical tasks serving as prime examples of areas where AI can excel [80][82].

嘉宾：陈锴杰 访谈：Cage 编辑：Haozhen 随着 ChatGPT 加入 memory 功能，ChatGPT 的用户粘性进一步增强。在此基础上，Agent 的开发也进入了更加成熟的阶段： 过去大家主要依赖 prompting，只能构建基础的 Agent，如今通过 RL 和 memory 开发者可以开发出 Agentic 能力明显更强的 Agent。 这意味着 AI 的角色正在发生有趣的转变：AI 不再是仅仅帮你写代码、做 PPT 的助手，更有潜力成为一个真正懂你的生活伙伴，可以更加个性化 地完成日常任务。 为了更好了解这一趋势，我们访谈了 Macaron 创始人陈锴杰，锴杰分享了将 Memory 当作一种智能能力进行训练的经验，也强调了 RL 在 Agent 开发中的重要性。 Macaron 的产品最近引发了很多争议和讨论，锴杰坦言，如果满分是 100 分，自己只会给产品打 7-8 分，产品还有很大的提升空间， 他 期待未来 的 Agent 能成为用户专属的多啦 A 梦，既是有趣的伙伴，又能随时创造实用工具： • Multi-agent 系统可以将 Memory Agent 和 Coding agent ...

专题：2025 Inclusion·外滩大会 新浪科技讯 9月11日上午消息，今日外滩大会现场，源码资本投资合伙人，美国国家工程院外籍院士张 宏江表示，DeepSeek R1出现之后，跟当时世界上最好的推理模型之间的差距，成本上只有几十分之 一，性能却非常接近。说明其实在资源这件事情上，当成本降低之后，它的需求会更大幅度成长。 他提到，以ChatGPT发布为标志，大模型两年多时间，今年三月份，ChatGPT的日活跃已经接近搜索引 擎的30%，说明大模型已经成为大家日常。还能看到的是，无论是OpenAI的ChatGPT还是其他，各家公 司使用大模型也在加速。 AI曾经是我们的助理，但是这个助理的时间很短，很快将会变成我们的伙伴，他表示，AI会有自己的 规划和行动，这是人和机器、人和模型的新的关系。他总结，Agent将替代企业流程，也会改变未来的 人类组织构成和就业。（罗宁） 责任编辑：江钰涵 张宏江表示，模型性能快速提高，使用成本快速降低。而这件事会伴随大模型的发展持续发生。大模型 的生态又在推动很多产业发生Scaling Law，并带动整个经济的发展。 张宏江提到agent的规划能力指数性成长，并出现摩尔定律 ...

Core Viewpoint - The article discusses the emergence of Agent AI, highlighting its potential to revolutionize various fields through a new cognitive architecture that integrates perception, cognition, action, learning, and memory [4][9][10]. Summary by Sections Introduction to Agent AI - 2025 is anticipated to be the year of Agent AI, with increasing interest in concepts like AI Agents and Agentic AI [4]. - A significant paper led by Fei-Fei Li titled "Agent AI: Surveying the Horizons of Multimodal Interaction" has sparked widespread discussion in the industry [4][6]. Framework of Agent AI - The paper establishes a clear framework for Agent AI, integrating various technologies into a unified perspective [6][7]. - It outlines five core modules: Environment and Perception, Cognition, Action, Learning, and Memory, which together form a dynamic cognitive loop [10][12][14][16][17]. Core Modules Explained - **Environment and Perception**: Agents actively perceive information from their surroundings, incorporating task planning and skill observation [12]. - **Cognition**: Acts as the processing center, utilizing large language models (LLMs) and visual language models (VLMs) for reasoning and strategy formulation [14]. - **Action**: Converts cognitive decisions into executable commands, affecting the environment [15]. - **Learning**: Emphasizes continuous learning through various mechanisms, allowing agents to adapt based on feedback [16]. - **Memory**: Features a structured system for long-term knowledge retention, enabling agents to leverage past experiences [17]. Role of Large Models - The development of Agent AI is driven by the maturity of foundation models, particularly LLMs and VLMs, which provide agents with extensive knowledge and planning capabilities [20]. - The paper addresses the challenge of "hallucination" in models, emphasizing the importance of environmental interaction to mitigate this issue [21][22]. Application Potential - The paper explores Agent AI's applications in three key areas: - **Gaming**: Agent AI can create dynamic NPCs that interact meaningfully with players, enhancing immersion [24][25]. - **Robotics**: Robots can execute complex tasks based on natural language commands, improving user interaction [27]. - **Healthcare**: Agent AI can assist in preliminary diagnostics and patient monitoring, increasing efficiency in healthcare delivery [29][31]. Conclusion - The paper recognizes that Agent AI is still in its early stages, facing challenges in integrating multiple modalities and creating general agents for diverse applications [32]. - It proposes new evaluation benchmarks to guide the development and measure progress in the field [32].