文｜钟楚笛 编辑｜周鑫雨 时隔三年，2026年2月7日凌晨，王慧文（美团联合创始人）又发了一封英雄帖。 这次，他不再组局做大模型，而是瞄准了当下最火热的赛道：Clawdbot（现改名为"OpenClaw"）。投资、攒聚，甚至当"猎头"，在Clawdbot身上，王 慧文倾注了不亚于对大模型的热情。 王慧文英雄帖。图源：王慧文即刻 毫无疑问，Clawdbot是2026开年最性感的AI应用故事。这个由奥地利开发者Peter Steinberger开源的项目，是一个能直接在本地设备运行的Agent框架。 后来，为了避免侵权Claude，Cawdbot改名为Moltbot，最近又变成了OpenClaw（为了方便理解，文中将仍然使用Clawdbot）。 相较于在云端运行的Manus，部署在本地的Clawdbot，成在"野"。 不设限的操作模式，让Clawdbot将执行力发挥到了极致。运营各种规模的企业、打理电商平台，甚至砍价、炒股，Clawdbot能够基于用户指令和本地 数据，自主完成各项复杂任务。 但败也在"野"。 不设限，意味着有失控的风险。曾有用户，被Clawdbot删除了所有邮件，亏光了账户所有的钱。也有用户被C ...

当全球都在为一条红色的龙虾——「Clawdbot」而兴奋异常时，Anthropic 悄悄上线了一个新功能。 近日，AI 模型公司 Anthropic 为其旗舰产品 Claude 带来了一项看似不起眼、实则影响深远的更新。在 Claude 桌面应用的「连接器」部分，新增了一个名 为「精选」的分类，其中整合了与 Figma、Gemma、Canva、GitHub 等生产力工具的深度集成。 这并非一次简单的功能罗列。这一功能背后的核心，是 Model Context Protocol (MCP) 服务的大规模上线。 简单来说，MCP 是一个让 AI 模型安全、标准化地「连接」到外部工具和数据的协议。用户现在可以通过远程连接，授权 Claude 直接访问这些第三方服 务的数据，并在对话中调用其功能。例如，你可以让 Claude 分析 Figma 设计稿并提出修改建议，或者根据 GitHub 仓库的代码生成文档。 这并非只是 Anthropic 和第三方合作伙伴的简单合作，它标志着 Claude 从一个被动的「聊天机器人」，向一个主动的、能调度外部资源的「智能体平 台」迈出了关键一步。 效率在切换中流失，灵感在搬运中中断 ...

Core Insights - The report outlines the evolution of AI from large language models (LLMs) to Agentic AI, emphasizing a shift towards a closed-loop system of perception, decision-making, action, and learning [1][6] - The global Agentic AI market is projected to grow from approximately $5.29 billion in 2024 to $46-47 billion by 2030, with a compound annual growth rate (CAGR) exceeding 40% [15] - Key industry applications include finance, healthcare, education, manufacturing, and collaborative office environments, with a significant transformation expected in organizational operations and employment structures by 2028 [25][28] Industry Trends - The transition from model intelligence to behavioral intelligence marks a significant macro trend in the AI industry, moving towards a focus on closed-loop systems [6] - The report identifies five major evolutionary trends in Agentic AI, including a shift from application-driven to ecosystem-driven models and from single-agent to multi-agent collaboration [29] - The anticipated inflection point for large-scale application of AI agents is 2025, with expectations that 33% of enterprise software will integrate AI agent functionalities by 2028 [23] Market Dynamics - North America is identified as the primary funding pool for Agentic AI, while Europe focuses on privacy compliance and efficiency tools, and China leans towards outbound application services [15] - The report highlights the emergence of ten innovative solutions in Agentic AI technology, including retrieval-augmented generation (RAG) and multi-agent collaboration [30][32] - The expected impact of Agentic AI on traditional industries includes a 40% reduction in operational costs and a 20% increase in revenue by 2028 [25] Employment and Skills - The rise of AI agents is expected to lead to job displacement in repetitive and rule-based roles, while simultaneously creating new positions in AI development, training, and maintenance [28] - There will be a shift in skill requirements, with increased demand for creativity, strategic thinking, and emotional intelligence [28] Technological Innovations - Future breakthroughs in Agentic AI are anticipated in areas such as multi-modal integration, enhanced autonomous decision-making, and improved collaboration capabilities among multiple agents [38] - The report emphasizes the importance of safety and risk governance, proposing strategies for reliability, compliance, and ethical considerations in AI deployment [10][12]

Core Insights - The launch of ChatGPT by OpenAI on November 30, 2022, marked the beginning of a transformative journey in AI, impacting various sectors including technology, business, education, and geopolitics [1] - The rapid user adoption of ChatGPT, reaching 1 million users within five days and 100 million in two months, highlights its unprecedented growth compared to other platforms like TikTok and Instagram [2] - The evolution of ChatGPT from a simple conversational model to a sophisticated platform with multimodal capabilities and real-time voice interaction signifies a major leap in AI technology [2][3] User Growth and Engagement - By the end of 2024, ChatGPT had 300 million weekly active users, growing to 800 million by November 2025, indicating a significant penetration into global markets [5][6] - The mobile revenue surpassed $2 billion in August 2025, with an average revenue per installation of $2.91, showcasing its commercial viability [6] Business Model and Strategy - ChatGPT's pricing strategy evolved from a free model to a tiered subscription model, including a $20/month Plus plan and a $200/month Pro plan, aiming to capture various market segments [6] - The platform's enterprise customer base exceeded 1 million by 2025, making it the fastest-growing business platform in history [6] Technological Advancements - The introduction of GPT-4 and GPT-5 brought significant enhancements, including the ability to perform complex tasks, manage calendars, and generate comprehensive applications [5][10] - The shift from interactive AI to agent-based AI indicates a transformation in how users interact with technology, moving towards more autonomous functionalities [5][10] Market Dynamics and Competition - The competitive landscape has shifted dramatically, with emerging players like DeepSeek challenging OpenAI, prompting a return to open-source models [10] - The stock prices of major tech companies, including Nvidia, have surged significantly, reflecting the capital market's enthusiasm for AI technologies [10] Ethical and Legal Challenges - The rapid growth of ChatGPT has raised concerns regarding safety, with incidents of inappropriate content generation and lawsuits related to mental health issues [8][9] - Ongoing legal battles over copyright infringement and the ethical implications of AI training data highlight the complexities of integrating AI into society [9] Future Outlook - As ChatGPT approaches its third anniversary, questions about its limits and the sustainability of its growth emerge, particularly regarding energy consumption and societal impacts [11][12] - The potential for AI to redefine personal health markets and other sectors indicates a continuous evolution of its applications, while also raising concerns about the implications for future generations [12][13]

Core Insights - The article discusses the rising significance of Agentic AI, which is seen as a transformative force in enhancing productivity and business operations, potentially surpassing Generative AI [1][3] - A report from Huatai Securities indicates that Generative AI is entering a new development phase dominated by AI agents [1] Group 1: Understanding Agentic AI - Agentic AI is described as an evolution from Generative AI, where the former acts as an "actor" rather than just a "respondent," enabling autonomous task execution [4][6] - The evolution of AI is moving from single model enhancements to creating a collaborative "intelligent ecosystem" [5] Group 2: Major Players in the Agentic AI Space - Microsoft aims to integrate its Copilot across various platforms, transforming it into a comprehensive assistant capable of complex tasks [8][9] - Google focuses on multi-modal and general AI with its Project Astra, which showcases capabilities in understanding and interacting with the environment [10] - OpenAI views Agentic AI as a pathway to achieving Artificial General Intelligence (AGI), with ongoing developments to create autonomous agents capable of complex tasks [11] - NVIDIA plays a crucial role by providing powerful GPU resources and developing platforms for Agentic AI, including tools for easy model deployment [12] Group 3: Impact on Industries - Agentic AI is expected to revolutionize various sectors by introducing "digital employees" that can perform tasks autonomously, enhancing efficiency and productivity [13] - The potential for intelligent agents to handle customer service and internal operations is highlighted, indicating a shift from traditional automation to more sophisticated AI interactions [13] Group 4: Challenges and Future Outlook - The current lack of standardization among different AI agents poses a challenge for seamless collaboration across platforms [15] - Experts suggest that organizations should start exploring the capabilities of Agentic AI through pilot projects to understand its potential benefits [16][17]

以下文章来源于智能涌现 ，作者邓咏仪 智能涌现 . 文 ｜ 邓咏仪 编辑 ｜ 苏建勋 来源｜ 智能涌现（ID： AIEmergence） 封面来源 ｜ AI生成 大模型的风，如今又刮到了一个新名词上：MCP。 AI圈中不缺新鲜事，但这次不一样，互联网仿佛又回到了十多年前的春天。 "现在，基于MCP开发智能体，就像2010年开发移动APP。" 4月25日，百度 董事长李彦宏在百度Create大会上说到。 如果还没有听过MCP，但你肯定听过上一个热词：Agent（智能体）。2025年初，中国初创公司Manus的爆火，把这个名词瞬间推到了大众面前。 "真·能干活的AI"，是Agent爆火的关键。在这之前，大模型可以答疑解惑，但它只是一个简单的对话窗口，依赖于模型接受过的训练，大模型内的数据往 往不是最新的，如果只有大模型本体，调用外部工具，要经历非常繁琐的过程。 MCP这个概念，就和Agent密不可分。 MCP是Agent愿景得以实现的的重要路径——大模型可以自由地调用支持MCP协议的外部工具，完成更具体的任 务。 现在，包括高德地图、微信读书在内的应用，就已经纷纷推出官方的MCP Server（服务器），这意味着 ...

Core Viewpoint - The emergence of MCP (Model Context Protocol) is seen as a pivotal development in the AI industry, akin to the rise of mobile apps in 2010, enabling more efficient interactions between large models and external tools [1][2]. Group 1: Definition and Importance of MCP - MCP is an open standard that allows large models to interact with external data sources and tools, similar to a universal interface like USB [6][12]. - The adoption of MCP is expected to lead to a significant explosion in AI applications by 2025, as it simplifies the development process for AI applications [5][12]. Group 2: Current Trends and Adoption - Since February 2024, a global wave of MCP adoption has occurred, with major companies like OpenAI, Google, and others announcing support for the protocol [2][16]. - Over 4,000 MCP servers have been launched globally, indicating rapid growth in the ecosystem [12]. Group 3: Developer Experience and Challenges - Prior to MCP, developers faced high barriers in integrating external tools with large models, often requiring extensive coding and adaptation [10][11]. - With MCP, developers can focus on maintaining their applications rather than managing external tool performance, significantly reducing development workload [12][13]. Group 4: Competitive Landscape and Strategic Shifts - The shift towards MCP represents a strategic pivot for major AI companies, moving from isolated development to a more collaborative ecosystem [17][21]. - OpenAI's previous closed strategy has been contrasted with MCP's open approach, highlighting the advantages of a more inclusive development environment [18][21].