LLM Inference 自从 ChatGPT 问世以后，LLM 相关技术对人工智能技术领域形成了冲击性的影响，许多围绕 LLM 的技术架构的发展也一直在如火如荼的展开，比如 RAG 和 AI-Agent，以及时下比较火爆的 Model Context Protocol (MCP)[1]。在展开之前结合行业现实，笔者认为解释清楚 LLM Inference（LLM 推 理）和 LLM Serving（LLM 服务）的概念是十分必要的。 事实上，由于行业的快速发展，许多概念和知识点一直在业界混淆不清，比如对于 LLM Inference 和 LLM Serving 两个概念我相信不少人都是相当不清晰的。笔者认为造成这些问题的主要原因之一是在 LLM 的工程实践过程中将其所负责的功能范畴相互交错导致的。简单来说，为了满足业务需求很多 LLM 相关的技术框架不得已将 LLM Inference 和 LLM Serving 的功能集合都实现成在一起，导致功 能集合的边界模糊不清。因此，除了从 Inference 和 LLM Serving 的角度去谈 MCP 的发展，解释清 楚此两者的概念范畴同样也是本文的主要目的 ...

Core Insights - The article discusses the risks associated with the Multi-Agent Collaboration Protocol (MCP), particularly the potential for tool poisoning attacks that could manipulate AI agents to perform unauthorized actions [1][8][9] - The emergence of AI agents is highlighted as a transformative trend, with predictions indicating that by 2028, at least 15% of daily work decisions will be made autonomously by AI agents [2][4] - The commercial viability of AI agents is emphasized, with a focus on their ability to meet consumer needs and create a self-sustaining economic cycle [3][10] Group 1: Agent Ecosystem and Trends - The development of AI agents is expected to either replace traditional applications or enhance them with intelligent, proactive capabilities [2][4] - The introduction of DeepSeek has accelerated the adoption of AI agents, with a notable increase in inquiries and revenue generation in the industry [3][10] - The transition from single assistants to collaborative networks of agents is anticipated, leading to the formation of an "Agent Economy" [4][9] Group 2: Security Risks and Challenges - Security challenges are identified as critical for the stable operation of agent systems, with vulnerabilities in the MCP protocol posing significant risks [7][9] - Tool poisoning attacks (TPA) are highlighted as a major concern, where attackers can embed malicious instructions within the MCP code, leading to unauthorized actions by AI agents [8][9] - The lack of adequate security mechanisms during the design phase of protocols like MCP and A2A has resulted in hidden vulnerabilities that could be exploited [9][12] Group 3: Safety Measures and Industry Response - The industry is urged to implement proactive security measures across the entire value chain to mitigate risks associated with AI agents [11][12] - The responsibility for security varies depending on the application context, with general SaaS products having different security obligations compared to industry-specific applications [11][12] - Collaboration between AI model developers and security firms is essential to address both internal and external security challenges in the deployment of AI agents [12][13]

以申万计算机板块为例，1)营收层面，计算机板块的营业收入合计为12499.4亿元，同比增长5.0%;2)归 母净利润层面，计算机板块2024年实现归母净利润182.0亿元，同比下降41.1%，该行认为主要因为：a) 板块仍受到宏观环境影响，行业竞争加剧;b)板块内部分公司业务向AI等新技术转向，研发和市场开拓 投入提升。计算机板块2025Q1实现营收共2818.7亿元，同比增长15.1%;实现归母净利润23.3亿元，同比 增加790.5%，主要因为：a)宏观环境回暖，板块公司业务逐步复苏;b)行业内公司在技术、市场等领域的 投入效果逐步显现，带动利润提升。 2025Q1板块估值、公募配置比例回升 2025Q1计算机板块公司业绩修复，板块估值回升，截至2025年4月30日，计算机板块的动态市盈率为 81.5x，高于历史中枢水平。根据Wind历史统计数据，公募基金配置计算机的比例一般在4%-5%之间;截 至2025Q1，公募基金配置计算机的比例为3.1%，环比上升，公募基金重仓前十大计算机公司分别为金 山办公、海康威视、科大讯飞、同花顺、深信服、中科曙光、浪潮信息、紫光股份、新大陆、德赛西 威。展望未来，随着整体 ...

Group 1 - The core viewpoint of the articles revolves around the rapid development and commercialization of AI agents, particularly following the success of Manus, which has sparked significant interest and investment in this sector [2][3][4]. - Major tech companies are intensifying their efforts in the AI agent space, with ByteDance reportedly forming at least five teams to develop various AI agent products, and Baidu launching the "Xinxiang" app, which aims to compete with Manus [4][5]. - The investment landscape is also shifting, as evidenced by the $75 million funding round for Manus's parent company, Butterfly Effect, which has raised its valuation to nearly $500 million [2]. Group 2 - The emergence of AI agents is seen as a solution to the unmet business needs and technological gaps left by previous enterprise digital transformation efforts [3]. - Companies are adopting the MCP (Multi-Cloud Platform) mechanism to enhance the ecosystem of AI agents, with major players like Alibaba, Tencent, and Baidu integrating MCP protocols into their AI products [6]. - There is a growing concern regarding the safety and risk management of AI agents, as many companies lack a comprehensive understanding of the associated risks, with a significant portion of clients unaware of what AI agents entail [7][8]. Group 3 - The concept of AI agents is evolving, with new terminologies such as Agentic AI and Agentic Workflow gaining traction, indicating a shift towards more specialized and collaborative AI systems [10][11]. - The industry is focused on making AI agents adaptable to complex application scenarios, requiring advancements in perception, understanding, planning, and execution [11][12]. - There is a call for a more cautious approach to the deployment of AI agents, emphasizing the need for improved governance and risk assessment capabilities before widespread implementation [12].

Core Insights - The article discusses the emergence of AI Agents, highlighting Manus as the first truly universal AI Agent, which recently raised $75 million in funding, increasing its valuation to $500 million, a fivefold increase since its launch in March [1] - Major tech companies are competing in the AI Agent space, with ByteDance, Baidu, Alibaba Cloud, and OpenAI all developing their own Agent products, indicating a significant shift in the AI landscape [1][4] Group 1: AI Agent Overview - AI Agents can autonomously execute complex tasks by leveraging large models' perception and reasoning capabilities, unlike traditional chatbots that only provide conversational responses [3][4] - The global AI Agent market is projected to grow from $5.1 billion in 2024 to $47.1 billion by 2030, with a compound annual growth rate (CAGR) of 44.8% [4] Group 2: Company Strategies - OpenAI is focusing on enhancing Agent capabilities with new models and aims for AI Agent sales to surpass ChatGPT by 2029, potentially increasing total revenue to $125 billion by 2030 [4][11] - Baidu is developing the "Xinxiang" app as a general-purpose intelligent assistant, while also launching new models to support AI applications [6][8] - Alibaba Cloud's Qwen3 model has achieved a high score in evaluating Agent capabilities, which will facilitate the upcoming explosion of AI applications [6] Group 3: Market Segmentation - Companies are adopting different strategies: some are targeting consumer markets (To C) with personal assistant applications, while others focus on embedding Agents into business workflows (To B) [7][11] - Microsoft integrates its Copilot into Office and Teams, aiming to make Agents a central part of enterprise workflows, with over 100,000 companies already using it [11][12] Group 4: Ecosystem and Standards - The introduction of the Model Context Protocol (MCP) is crucial for AI Agents, providing a unified standard for tool interaction, which enhances efficiency in task execution [14][16] - Over 4,000 MCP servers are now operational globally, indicating rapid adoption and support from major AI companies [16][17] - The proliferation of MCP is expected to facilitate the development of a robust Agent ecosystem, akin to the app economy in the mobile internet era [18]

近期变化，Agent产品层： 1）五一期间Manus创始人Peak指出Manus的 ，主因加入主动查看图像的功能后，Manus开始自动检查其生成的数据可视化，AI的网络效应或初现。 Manus在4月底拿到了硅谷风投Benchmark领投的7500万美元融资。 2）Genspark更新了更好的个性化能力。 【华泰计算机】Agent和MCP是AI主线中的主线 2）Genspark更新了更好的个性化能力。 而从Meta电话会中已知，Meta AI的10亿月活，核心也是基于社交打造个性化。 个性化是护城河，越早建立越好。 模型层： 阿里Qwen 3强调Agent能力和MCP生态的支持，预期后续国产模型都会积极拥抱MCP。 再次重申MCP商业化三阶段： 1）工具厂商率先实现收入，按照【API用量计费】。 4月30日，【 】官方微信号宣布，TextInMCP Server 已覆盖文字识别、文档解析、信息抽取等核心产品能力。 2）Agent客户端商业化同样较快。 【华泰计算机】Agent和MCP是AI主线中的主线 近期变化，Agent产品层： 1）五一期间Manus创始人Peak指出Manus的 ，主因加入主动查看图像的功 ...

Core Insights - The emergence of the Model Context Protocol (MCP) is seen as a significant advancement in AI development, allowing for easier integration of external data sources and tools, thereby enhancing the efficiency of AI applications and agents [3][5][9] - Major tech companies, including Alibaba, Baidu, Tencent, and ByteDance, are actively adopting and promoting MCP, indicating a competitive landscape for AI agent development [9][10][11] Group 1: MCP Overview - MCP is likened to a "universal socket" for AI, enabling seamless connections between large models and external tools, which significantly reduces development costs and time [3][5][8] - The protocol was initially introduced by Anthropic in November 2022 but gained traction with the launch of the Manus AI agent in February 2023, showcasing the potential of MCP [7][13] - The adoption of MCP is expected to transform AI agents from simple information retrieval systems to more complex applications capable of executing tasks [8][12] Group 2: Industry Adoption - As of April 2025, various tech giants have integrated MCP into their services, with Baidu being the first to offer an enterprise-level MCP service [3][9] - Alibaba Cloud has launched a comprehensive MCP service that integrates over 200 leading models and nearly 100 mainstream MCP services, facilitating easier development of AI agents [10][12] - The introduction of payment MCP services by Alipay further enhances the capabilities of AI agents, allowing for streamlined transaction processes within applications [11][12] Group 3: Future Developments - The MCP ecosystem is still evolving, with ongoing improvements and adaptations expected as the technology matures [13][15] - The competition between MCP and other protocols, such as Google's Agent2Agent Protocol (A2A), highlights the dynamic nature of AI integration standards [14][15] - Industry experts believe that while MCP may face challenges, its foundational role in AI development will continue to be significant as it evolves [15][16]

证券代码：300785 证券简称：值得买 北京值得买科技股份有限公司 投资者关系活动记录表 编号：2025-001 | 投资者关系活 | □特定对象调研 □分析师会议 | | --- | --- | | 动类别 | □媒体采访 □业绩说明会 | | | □新闻发布会 □路演活动 | | | □现场参观  其他：电话会议 | | 参与单位名称 | 金鹰基金 陈颖 | | 及人员姓名 | 广东天贝合资产管理有限公司 黄达 | | | 建信养老金管理有限责任公司 高月 | | | 诺安基金 王晴 | | | 中金公司 王杰睿 | | | 华鑫证券 朱珠 | | | 广发证券 黄静仪 | | | 民生证券 李瑶 | | | 国盛证券 杜玥莹等 60 余人。 | | 时间 2025 | 年 4 月 29 日 15:30-17:00 | | 地点 | 电话会议 | | 上市公司接待 | 董事长兼首席执行官 隋国栋先生 | | 人员姓名 | 联合创始人兼消费内容事业部负责人 刘峰先生 | | | 智能营销及国际化事业部负责人 许欢先生 | | | 首席技术官兼 AI 事业部负责人 王云峰先生 | | | 首席财务官 李楠 ...

4月 29日，阿里最新模型Qwen3正式发布，模型采用开源方式，全球开发者、研究机构和企业均可免费在Hugging Face、魔搭社区等平台下载模型并商 用，也可以通过阿里云百炼调用Qwen3的API服务。 大模型本质： Qwen3采用混合专家（MoE）架构，总参数量235B，专家模型数量128个，活跃参数量22B，活跃专家模型8个（ 和Llama4 架构类似，降低推理环节成 本）。 Qwen3总参数仅为DeepSeek-R1的1/3，性能测评全面超越R1、OpenAI-o1等全球顶尖模型。在代码能力测试LiveCodeBench和Codeforces两个榜单中， Qwen3高于所有其它模型，包括当前最强的Gemini2.5-Pro。 此外，Qwen3的30B参数MoE模型实现了10倍以上的模型性能杠杆提升，仅激活3B性能超过了上代Qwen2.5-32B模型性能，Qwen3-4B也能达到与Qwen2.5- 72B-Instruct相当的表现。 预训练 Qwen3预训练数据集规模几乎是上一代两倍，从18万亿个token扩展到了36万亿个token。为了确保数据质量，团队利用Qwen2.5-VL提取文档文本，并通 ...

上周真是 MCP 诞生以来热度最高的一周，大家扎堆发布 MCP 的 Agents 工具。 纳米也发布了自己基于 MCP 驱动的 Agents 服务 "MCP万能工具箱"。 这个工具箱不仅包含纳米AI自研的十几个MCP工具，还引入了近百个第三方MCP工具，工具总量目前位居国内第一。 MCP 工具覆盖办公协作、学术研究、生活服务、搜索引擎、金融、媒体娱乐、数据抓取等多个领域。 今天终于有空详细玩了一下，还基于纳米的能力做了一个 Agents 帮大家生成藏师傅同款的展示网页。 深度研究智能体 先来看一下深度研究智能体，这部分直接就可以用不需要你任何配置，直接调用纳米的规划、搜索能力最后帮你生成各种形式的展示内容。 你可以在纳米 AI 客户端左侧智能体的部分找到深度研究智能体的入口，然后点击使用就行。 这里除了可以搜索网上内容外，也支持搜索你自己个人知识库的内容，比如我这里就让他基于网络和我自己的知识库搜索 MCP 的相关内容并且生成对应的网页解 释和 PDF 文件。 他经过 20 分钟的搜索和思考之后给了一个非常详细的报告，PDF 里面的内容非常丰富，总共消耗了 47 万 Token，而且这些都是免费的。 比如 M ...