微软CEO:在AI时代,如何定义一家公司的护城河?

marsbitPublished on 2026-06-15Last updated on 2026-06-15

Abstract

微软CEO萨提亚·纳德拉认为,AI时代企业的核心竞争力并非依赖于单一的最强大模型,而在于能否构建一个持续进化的“学习闭环”。这一系统能将企业内部的工作流程、专业知识、组织判断和员工经验沉淀下来,并让人工智能与人类能力相互强化、共同提升。 未来的公司将积累两类关键资产:一是以员工知识、判断力、创造力和模式识别能力为核心的“人力资本”;二是企业自身构建并拥有的AI能力,即“Token资本”。纳德拉强调,AI不仅不会削弱人力资本的价值,反而会让人类的目标设定、跨领域连接和关键决策能力变得更为重要。缺乏人的引导,算力将失去方向;没有企业自身知识的注入,再强的模型也仅是外部工具。 因此,企业的真正护城河在于建立私有的评估体系、强化学习环境和知识库,将隐性经验转化为可迭代、可扩展的系统能力。即使更换底层通用模型,企业独有的“公司老员工式”的专业经验和学习成果也不会丢失。这确保了企业的知识产权与控制权。 纳德拉指出,健康的AI未来应是一个繁荣的“前沿生态”,而非由少数通用模型垄断价值。只有这样,价值才能广泛惠及每家公司、每个行业和国家,让各组织能基于自身知识创造并保留经济价值,最终实现企业、员工与社区的共同繁荣。

编者按:微软 CEO Satya Nadella 认为,AI 时代企业真正的竞争力,不在于押中哪一个最强模型,而在于能否把自身的工作流、领域知识、组织判断和员工经验,沉淀成一个持续进化的学习系统。换句话说,企业不能只购买 AI 能力,而要拥有自己的「学习闭环」(让人类经验、业务流程和模型能力不断相互强化的系统)。

在这个框架下,未来公司将同时积累两类资本:人力资本,即员工的知识、判断力、关系网络、创造力和模式识别能力;以及 Token Capital(企业自己构建并拥有的 AI 能力)。Nadella 强调,AI 并不会让人力资本贬值,反而会让人的目标设定、跨领域连接和关键模式识别能力更重要。没有人的方向牵引,算力只是在原地打转;没有组织自身的知识沉淀,模型再强也只是外部工具。

本文最核心的判断是:没有生态支撑的前沿,不会是一个稳定的未来。AI 的价值不应被少数通用模型吞噬,而应该形成一个前沿生态系统,让每家公司、每个行业、每个国家都能拥有自己的学习闭环。企业需要建立私有评估、私有强化学习环境和可查询的知识库,把隐性经验转化为可复用、可扩展、可迭代的系统能力。真正的护城河,可能不是某个模型本身,而是即使更换通用模型后,企业依然不会失去自身积累的「公司老员工式」经验。

这也是 AI 时代企业主权的关键:谁能把组织知识变成持续复利的系统,谁就能在模型快速迭代的未来保留 IP、放大员工能力,并把 AI 带来的经济价值留在自身业务、行业和社区之中。

以下为原文:

我最近一直在思考,在 AI 驱动的经济中,企业的未来会是什么样。

这一次转型不同于以往任何一次平台迁移。过去,我们使用数字系统来增强人力资本;而这一次,是我们第一次能够在人与数字系统之间建立真正的认知闭环。这是一件非常颠覆认知的事,因为它会改变我们对企业内部「工作」本身的理解方式。

真正关键的问题,并不是某个数字工具或系统如何被使用,而是在一个 AI 模型能够持续吸收人类与组织专业知识、并将其商品化的世界里,组织如何继续学习、积累知识产权、形成差异化,并持续繁荣。

每家公司都必须建立我所说的人力资本和 Token 资本。人力资本包括员工的知识、判断力、关系网络、创造力和模式识别能力;而 Token 资本,则是企业自身构建并拥有的 AI 能力。

重要的是,随着 Token 资本增长,人力资本并不会变得不重要。恰恰相反,它只会变得更加重要。我相信,人类能动性将成为 Token 资本增长的核心驱动力。人类会设定有野心的目标,跨领域连接线索,建立关系,并识别出真正重要的模式。没有人类方向的牵引,算力只会原地打转。

这意味着,真正的机会并不在于选择最好的模型,而是在模型之上建立一个学习闭环,让人力资本和 Token 资本彼此复利增长。你可以把一个任务外包出去,甚至可以把一份工作外包出去,但你永远不能把自己的学习外包出去。企业的未来,在于能否让这种学习在人和 AI 之间持续复利。

这需要一种新的架构思路:每一家企业都应该能够构建会随着时间不断改进的智能体系统,同时仍然保有对自身知识产权的控制权。一家公司应该能够替换掉一个「通才型」模型,却不会丢失其学习系统中沉淀下来的「公司老员工」式专业经验。这将是未来时代衡量企业控制力与主权能力的关键测试。

企业需要把自身的工作流、领域知识和长期积累的判断力,转化为能够在每次使用中持续改进的 AI 系统。私有评测应该衡量模型是否真的在企业关心的业务结果上变得更好,而不只是看外部基准测试。私有强化学习环境应当让模型基于组织内部真实轨迹变得更强。企业知识库则会让制度性记忆变得可查询,并提升 Token 使用效率。

这个闭环将成为企业新的知识产权。我把它看作一台「爬坡机器」。而且,与大多数资产不同,它会复利增长。每一次工作流改进,都会产生更好的训练信号,进而加速企业独有隐性知识的积累。那些更早建立这一系统的公司,将获得一种难以复制的优势,无论未来单个模型能力如何突破。

我们最不愿看到的,是这样一个世界:各行各业的每家公司都把价值拱手让给少数几个吞噬一切所见内容的模型。如果所有价值最终都被少数模型捕获,政治经济结构根本不会容忍这种结果。一个掏空整个行业的 AI 未来,不可能获得社会层面的许可。

想想全球化第一阶段发生过什么:整个工业经济体被外包掏空。表面上看,GDP 数字似乎还不错,但真实的产业转移和就业冲击确实存在,而且其后果至今仍在被感知。我们不能把这种动态带入 AI 时代——让少数 AI 系统捕获全部经济回报,而整个行业的知识却在它们脚下被商品化、被掏空。

在我看来,我们的优先事项必须是构建一个前沿生态,而不只是一个前沿模型。只有这样,价值才能广泛流向每一家公司、每一个行业、每一个国家。在这样的生态中,每个组织都能够拥有自己的学习闭环,将自身的制度性知识编码进去,并让人力资本与 Token 资本共同复利增长。

这也是我一直认同的平台精神:平台之上创造的价值,应该大于平台自身捕获的价值;每家公司都应该能够持续创新,并创造属于自己的价值。

当这一点实现时,企业将为自身创造价值,也将为其所处的经济环境创造价值。员工的专业能力会被放大,他们的判断力会成为系统的一部分,变得可以复制、可以规模化,而这些收益会回流到公司及其周边社区。

这才是企业为自身和更广泛经济创造价值的方式。也是我们应该共同建设的稳定均衡。

Related Questions

Q根据微软CEO的观点,在AI时代,什么才是企业真正的竞争力?

A企业真正的竞争力不在于押中哪一个最强模型,而在于能否把自身的工作流、领域知识、组织判断和员工经验,沉淀成一个持续进化的学习系统,即拥有自己的“学习闭环”。

Q在文章中,“人力资本”和“Token资本”分别指什么?

A“人力资本”指员工的知识、判断力、关系网络、创造力和模式识别能力;“Token资本”则是企业自身构建并拥有的AI能力。

Q为什么说AI不会让人力资本贬值,反而使其更重要?

A因为人类能动性是Token资本增长的核心驱动力。人类会设定目标、跨领域连接、建立关系并识别重要模式。没有人类方向的牵引,算力只会原地打转,所以人的目标设定和关键判断能力变得更为关键。

Q文章中提到,未来的企业需要构建什么样的系统才能保留其专业知识?

A企业需要构建能够随着时间不断改进的智能体系统,并保有对自身知识产权的控制权。具体而言,需要建立私有评估体系、私有强化学习环境和可查询的知识库,把隐性经验转化为可复用、可扩展、可迭代的系统能力。

Q为了避免出现“少数模型捕获全部经济回报”的局面,文章主张优先构建什么?

A文章主张优先构建一个“前沿生态系统”,而不是仅仅一个前沿模型。在这样的生态中,每家公司、每个行业、每个国家都能拥有自己的学习闭环,将自身的制度性知识编码进去,确保价值广泛流动。

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At its core, SPERO,$$s$ aims to empower individuals by providing tools and platforms that enhance user experience in the cryptocurrency space. This includes enabling more flexible transaction methods, fostering community-driven initiatives, and creating pathways for financial opportunities through decentralised applications (dApps). The underlying vision of SPERO,$$s$ revolves around inclusiveness, aiming to bridge gaps within traditional finance while harnessing the benefits of blockchain technology. Who is the Creator of SPERO,$$s$? The identity of the creator of SPERO,$$s$ remains somewhat obscure, as there are limited publicly available resources providing detailed background information on its founder(s). This lack of transparency can stem from the project's commitment to decentralisation—an ethos that many web3 projects share, prioritising collective contributions over individual recognition. By centring discussions around the community and its collective goals, SPERO,$$s$ embodies the essence of empowerment without singling out specific individuals. As such, understanding the ethos and mission of SPERO remains more important than identifying a singular creator. Who are the Investors of SPERO,$$s$? SPERO,$$s$ is supported by a diverse array of investors ranging from venture capitalists to angel investors dedicated to fostering innovation in the crypto sector. The focus of these investors generally aligns with SPERO's mission—prioritising projects that promise societal technological advancement, financial inclusivity, and decentralised governance. These investor foundations are typically interested in projects that not only offer innovative products but also contribute positively to the blockchain community and its ecosystems. The backing from these investors reinforces SPERO,$$s$ as a noteworthy contender in the rapidly evolving domain of crypto projects. How Does SPERO,$$s$ Work? SPERO,$$s$ employs a multi-faceted framework that distinguishes it from conventional cryptocurrency projects. Here are some of the key features that underline its uniqueness and innovation: Decentralised Governance: SPERO,$$s$ integrates decentralised governance models, empowering users to participate actively in decision-making processes regarding the project’s future. This approach fosters a sense of ownership and accountability among community members. Token Utility: SPERO,$$s$ utilises its own cryptocurrency token, designed to serve various functions within the ecosystem. These tokens enable transactions, rewards, and the facilitation of services offered on the platform, enhancing overall engagement and utility. Layered Architecture: The technical architecture of SPERO,$$s$ supports modularity and scalability, allowing for seamless integration of additional features and applications as the project evolves. This adaptability is paramount for sustaining relevance in the ever-changing crypto landscape. Community Engagement: The project emphasises community-driven initiatives, employing mechanisms that incentivise collaboration and feedback. By nurturing a strong community, SPERO,$$s$ can better address user needs and adapt to market trends. Focus on Inclusion: By offering low transaction fees and user-friendly interfaces, SPERO,$$s$ aims to attract a diverse user base, including individuals who may not previously have engaged in the crypto space. This commitment to inclusion aligns with its overarching mission of empowerment through accessibility. Timeline of SPERO,$$s$ Understanding a project's history provides crucial insights into its development trajectory and milestones. Below is a suggested timeline mapping significant events in the evolution of SPERO,$$s$: Conceptualisation and Ideation Phase: The initial ideas forming the basis of SPERO,$$s$ were conceived, aligning closely with the principles of decentralisation and community focus within the blockchain industry. Launch of Project Whitepaper: Following the conceptual phase, a comprehensive whitepaper detailing the vision, goals, and technological infrastructure of SPERO,$$s$ was released to garner community interest and feedback. Community Building and Early Engagements: Active outreach efforts were made to build a community of early adopters and potential investors, facilitating discussions around the project’s goals and garnering support. Token Generation Event: SPERO,$$s$ conducted a token generation event (TGE) to distribute its native tokens to early supporters and establish initial liquidity within the ecosystem. Launch of Initial dApp: The first decentralised application (dApp) associated with SPERO,$$s$ went live, allowing users to engage with the platform's core functionalities. Ongoing Development and Partnerships: Continuous updates and enhancements to the project's offerings, including strategic partnerships with other players in the blockchain space, have shaped SPERO,$$s$ into a competitive and evolving player in the crypto market. Conclusion SPERO,$$s$ stands as a testament to the potential of web3 and cryptocurrency to revolutionise financial systems and empower individuals. With a commitment to decentralised governance, community engagement, and innovatively designed functionalities, it paves the way toward a more inclusive financial landscape. As with any investment in the rapidly evolving crypto space, potential investors and users are encouraged to research thoroughly and engage thoughtfully with the ongoing developments within SPERO,$$s$. The project showcases the innovative spirit of the crypto industry, inviting further exploration into its myriad possibilities. While the journey of SPERO,$$s$ is still unfolding, its foundational principles may indeed influence the future of how we interact with technology, finance, and each other in interconnected digital ecosystems.

55 Total ViewsPublished 2024.12.17Updated 2024.12.17

What is $S$

What is AGENT S

Agent S: The Future of Autonomous Interaction in Web3 Introduction In the ever-evolving landscape of Web3 and cryptocurrency, innovations are constantly redefining how individuals interact with digital platforms. One such pioneering project, Agent S, promises to revolutionise human-computer interaction through its open agentic framework. By paving the way for autonomous interactions, Agent S aims to simplify complex tasks, offering transformative applications in artificial intelligence (AI). This detailed exploration will delve into the project's intricacies, its unique features, and the implications for the cryptocurrency domain. What is Agent S? Agent S stands as a groundbreaking open agentic framework, specifically designed to tackle three fundamental challenges in the automation of computer tasks: Acquiring Domain-Specific Knowledge: The framework intelligently learns from various external knowledge sources and internal experiences. This dual approach empowers it to build a rich repository of domain-specific knowledge, enhancing its performance in task execution. Planning Over Long Task Horizons: Agent S employs experience-augmented hierarchical planning, a strategic approach that facilitates efficient breakdown and execution of intricate tasks. This feature significantly enhances its ability to manage multiple subtasks efficiently and effectively. Handling Dynamic, Non-Uniform Interfaces: The project introduces the Agent-Computer Interface (ACI), an innovative solution that enhances the interaction between agents and users. Utilizing Multimodal Large Language Models (MLLMs), Agent S can navigate and manipulate diverse graphical user interfaces seamlessly. Through these pioneering features, Agent S provides a robust framework that addresses the complexities involved in automating human interaction with machines, setting the stage for myriad applications in AI and beyond. Who is the Creator of Agent S? While the concept of Agent S is fundamentally innovative, specific information about its creator remains elusive. The creator is currently unknown, which highlights either the nascent stage of the project or the strategic choice to keep founding members under wraps. Regardless of anonymity, the focus remains on the framework's capabilities and potential. Who are the Investors of Agent S? As Agent S is relatively new in the cryptographic ecosystem, detailed information regarding its investors and financial backers is not explicitly documented. The lack of publicly available insights into the investment foundations or organisations supporting the project raises questions about its funding structure and development roadmap. Understanding the backing is crucial for gauging the project's sustainability and potential market impact. How Does Agent S Work? At the core of Agent S lies cutting-edge technology that enables it to function effectively in diverse settings. Its operational model is built around several key features: Human-like Computer Interaction: The framework offers advanced AI planning, striving to make interactions with computers more intuitive. By mimicking human behaviour in tasks execution, it promises to elevate user experiences. Narrative Memory: Employed to leverage high-level experiences, Agent S utilises narrative memory to keep track of task histories, thereby enhancing its decision-making processes. Episodic Memory: This feature provides users with step-by-step guidance, allowing the framework to offer contextual support as tasks unfold. Support for OpenACI: With the ability to run locally, Agent S allows users to maintain control over their interactions and workflows, aligning with the decentralised ethos of Web3. Easy Integration with External APIs: Its versatility and compatibility with various AI platforms ensure that Agent S can fit seamlessly into existing technological ecosystems, making it an appealing choice for developers and organisations. These functionalities collectively contribute to Agent S's unique position within the crypto space, as it automates complex, multi-step tasks with minimal human intervention. As the project evolves, its potential applications in Web3 could redefine how digital interactions unfold. Timeline of Agent S The development and milestones of Agent S can be encapsulated in a timeline that highlights its significant events: September 27, 2024: The concept of Agent S was launched in a comprehensive research paper titled “An Open Agentic Framework that Uses Computers Like a Human,” showcasing the groundwork for the project. October 10, 2024: The research paper was made publicly available on arXiv, offering an in-depth exploration of the framework and its performance evaluation based on the OSWorld benchmark. October 12, 2024: A video presentation was released, providing a visual insight into the capabilities and features of Agent S, further engaging potential users and investors. These markers in the timeline not only illustrate the progress of Agent S but also indicate its commitment to transparency and community engagement. Key Points About Agent S As the Agent S framework continues to evolve, several key attributes stand out, underscoring its innovative nature and potential: Innovative Framework: Designed to provide an intuitive use of computers akin to human interaction, Agent S brings a novel approach to task automation. Autonomous Interaction: The ability to interact autonomously with computers through GUI signifies a leap towards more intelligent and efficient computing solutions. Complex Task Automation: With its robust methodology, it can automate complex, multi-step tasks, making processes faster and less error-prone. Continuous Improvement: The learning mechanisms enable Agent S to improve from past experiences, continually enhancing its performance and efficacy. Versatility: Its adaptability across different operating environments like OSWorld and WindowsAgentArena ensures that it can serve a broad range of applications. As Agent S positions itself in the Web3 and crypto landscape, its potential to enhance interaction capabilities and automate processes signifies a significant advancement in AI technologies. Through its innovative framework, Agent S exemplifies the future of digital interactions, promising a more seamless and efficient experience for users across various industries. Conclusion Agent S represents a bold leap forward in the marriage of AI and Web3, with the capacity to redefine how we interact with technology. While still in its early stages, the possibilities for its application are vast and compelling. Through its comprehensive framework addressing critical challenges, Agent S aims to bring autonomous interactions to the forefront of the digital experience. As we move deeper into the realms of cryptocurrency and decentralisation, projects like Agent S will undoubtedly play a crucial role in shaping the future of technology and human-computer collaboration.

730 Total ViewsPublished 2025.01.14Updated 2025.01.14

What is AGENT S

Discussions

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