微软和 Meta Shift AI 战略、Nvidia 过热的芯片和强劲的盈利

微软（纳斯达克股票代码：MSFT）最近发表了一篇关于其新人工智能代理的博客文章，概述了它们是什么、它们如何工作以及它们的潜在应用。

AI Agents, Microsoft (NASDAQ:MSFT), Meta (NASDAQ:META), Nvidia (NASDAQ:NVDA)

AI Agents、微软（纳斯达克股票代码：MSFT）、Meta（纳斯达克股票代码：META）、Nvidia（纳斯达克股票代码：NVDA）

Microsoft’s AI Agents: An evolution of Copilot

微软的人工智能代理：Copilot 的演变

Last week, Microsoft (NASDAQ:MSFT) unveiled its new AI Agents, generative artificial intelligence tools that can be customized to perform specific tasks. These Agents are designed to leverage data from the Microsoft Office suite to execute multi-step processes autonomously.

上周，微软（纳斯达克股票代码：MSFT）推出了新的人工智能代理，这是一种可以定制以执行特定任务的生成人工智能工具。这些代理旨在利用 Microsoft Office 套件中的数据自主执行多步骤流程。

While Microsoft’s Copilot product already provides many of these capabilities, the Agents expand on them by improving memory, integrating with external systems, and enabling more complex workflows.

虽然 Microsoft 的 Copilot 产品已经提供了其中许多功能，但代理通过改进内存、与外部系统集成以及支持更复杂的工作流程来扩展这些功能。

The shift from Copilot to AI Agents seems to be more than just a rebranding effort. It feels like Microsoft is addressing a gap in how its customers use AI. Many users haven’t fully tapped into Copilot’s potential, and the blog post reads like an early step in a broader re-education initiative.

从 Copilot 到 AI Agents 的转变似乎不仅仅是一次品牌重塑工作。微软似乎正在解决客户使用人工智能的方式上的差距。许多用户尚未充分发挥 Copilot 的潜力，这篇博文读起来像是更广泛的再教育计划的早期步骤。

Microsoft appears to be laying the groundwork for helping users understand how to maximize their AI tools—not just within Office but as part of their daily workflows.

微软似乎正在为帮助用户了解如何最大限度地利用人工智能工具奠定基础——不仅在 Office 中，而且将其作为日常工作流程的一部分。

At nearly every opportunity I get, I mention how most people use AI as a glorified search engine rather than using it in ways to get the most out of the system. AI tools can have a significant impact on how we work and live, streamline many processes, save resources, and increase our overall efficiency.

几乎每次有机会，我都会提到大多数人如何将人工智能用作美化的搜索引擎，而不是以充分利用系统的方式使用它。人工智能工具可以对我们的工作和生活方式产生重大影响，简化许多流程，节省资源，并提高我们的整体效率。

However, it seems like many users just haven’t dug deeper with AI or figured that out yet. From what I see, it does seem like many users need more guidance if they are looking to get the most out of their AI tools of choice. Microsoft’s move could be the start of a broader industry trend where companies invest more heavily in user education, providing step-by-step guides that allow their users to better integrate their AI into their personal and professional lives.

然而，似乎许多用户还没有更深入地挖掘人工智能或弄清楚这一点。从我看来，如果许多用户希望充分利用他们选择的人工智能工具，他们似乎确实需要更多指导。微软的举动可能是更广泛行业趋势的开始，即公司加大对用户教育的投资，提供分步指南，使用户能够更好地将人工智能融入个人和职业生活。

Meta’s push to monetize AI

Meta 推动人工智能货币化

Meta (NASDAQ:META), on the other hand, has appointed former Salesforce (NASDAQ:CRM) CEO Clara Shih as its new “Head of Business AI.”

另一方面，Meta（纳斯达克股票代码：META）已任命 Salesforce（纳斯达克股票代码：CRM）前首席执行官 Clara Shih 为其新的“商业人工智能主管”。

According to Shih, “Our vision for this new product group is to make cutting-edge AI accessible to every business, empowering all to find success and own their future in the AI era… Meta’s global reach and leadership in AI represent a generational opportunity for businesses, and I couldn’t be more excited and grateful to help take this from zero to one to scale.”

Shih 表示：“我们对这个新产品组的愿景是让每家企业都能接触到尖端人工智能，让所有人都能在人工智能时代取得成功并拥有自己的未来……Meta 在人工智能领域的全球影响力和领导地位代表着一代人的机遇。”能够帮助实现从零到一的规模化，我感到非常兴奋和感激。”

The move signals Meta’s growing focus on profitability in AI. It’s no secret that many artificial intelligence companies struggle to profit. The infrastructure required to train and run advanced models comes at a massive cost.

此举标志着 Meta 越来越关注人工智能的盈利能力。许多人工智能公司难以盈利已不是什么秘密。训练和运行高级模型所需的基础设施成本高昂。

In contrast, the revenue they collect through subscription models that offer customers access to “better” AI tools recoups only a fraction of the companies’ expenses.

相比之下，他们通过订阅模式为客户提供“更好”的人工智能工具而获得的收入只能收回公司开支的一小部分。

The purpose of Meta’s Business AI group seems to be to turn this around by productizing their AI offerings—packaging them into marketable products that attract paying customers and drive significant revenue growth for the business.

Meta 商业人工智能团队的目的似乎是通过将其人工智能产品产品化来扭转这一局面，将其打包成适销对路的产品，吸引付费客户并推动企业收入大幅增长。

This shift in strategy isn’t unique to Meta; it reflects a broader trend in the AI industry. It has become clear that many companies’ AI divisions are increasingly finding themselves under pressure to figure out monetization as investors start asking when they will see returns.

这种策略的转变并不是 Meta 所独有的。它反映了人工智能行业更广泛的趋势。很明显，随着投资者开始询问何时能看到回报，许多公司的人工智能部门越来越面临着货币化的压力。

The narrative around AI seems to be shifting from “AI is revolutionary” to “Who’s making money from AI, and how soon can we expect returns on our investments?”

关于人工智能的叙述似乎正在从“人工智能是革命性的”转变为“谁从人工智能中赚钱，我们多久才能期望获得投资回报？”

It’s an important question because the industry could face a wave of business closures and mergers without a clear path to profitability. If companies can’t find a financially viable strategy for their AI divisions, we may soon see a consolidation of players in the AI space.

这是一个重要的问题，因为如果没有明确的盈利途径，该行业可能会面临一波企业倒闭和合并浪潮。如果公司无法为其人工智能部门找到财务上可行的战略，我们可能很快就会看到人工智能领域的参与者进行整合。

Nvidia’s overheating chips and strong earnings

英伟达过热的芯片和强劲的盈利

A recent report said that Nvidia’s (NASDAQ:NVDA) Blackwell chips are prone to overheating when added to servers, creating significant challenges for data centers. To address the issue, service providers must redesign their racks, an expensive and time-consuming process.

最近的一份报告称，Nvidia（纳斯达克股票代码：NVDA）的 Blackwell 芯片在添加到服务器时容易过热，给数据中心带来重大挑战。为了解决这个问题，服务提供商必须重新设计他们的机架，这是一个昂贵且耗时的过程。

Despite that negative press, Nvidia’s Q3 earnings report exceeded analyst expectations. The company posted adjusted earnings per share of $0.81, representing a net income of $19.3 billion, compared to predictions of $0.75 EPS and $17.4 billion net income.

尽管存在负面新闻，英伟达第三季度收益报告还是超出了分析师的预期。该公司公布调整后每股收益为 0.81 美元，净利润为 193 亿美元，而预期每股收益为 0.75 美元，净利润为 174 亿美元。

However, even with these substantial numbers, Nvidia’s stock dropped by roughly 2% when the market opened the next day.

然而，即使有这些可观的数字，Nvidia 的股价在第二天开盘时仍下跌了约 2%。

This trend—where companies beat earnings expectations but experience a decline in share prices—has become increasingly common. This stems from the market’s perception that a company with strong current performance has less room for growth in the upcoming quarters.

这种公司超出盈利预期但股价下跌的趋势已经变得越来越普遍。这源于市场认为当前业绩强劲的公司在未来几个季度的增长空间较小。

In Nvidia’s case, their Q4 guidance of $37.5 billion in revenue, only slightly above Wall Street’s $37 billion projection, reinforces this idea.

就 Nvidia 而言，他们第四季度收入指引为 375 亿美元，仅略高于华尔街 370 亿美元的预测，强化了这一想法。

In order for artificial intelligence (AI) to work right within the law and thrive in the face of growing challenges, it needs to integrate an enterprise blockchain system

为了让人工智能 (AI) 在法律范围内正常工作并在面临日益增长的挑战时蓬勃发展，它需要集成企业区块链系统