微軟 (MSFT) 2026 Q2 法說會逐字稿

Greetings, and welcome to the Microsoft fiscal year 2026 second-quarter earnings conference call. (Operator Instructions) As a reminder, this conference is being recorded.

大家好，歡迎參加微軟2026財年第二季財報電話會議。（操作說明）提醒各位，本次會議正在錄音。

It is now my pleasure to introduce Jonathan Nielsen, Vice President of Investor Relations. Please go ahead.

現在我榮幸地向大家介紹投資者關係副總裁喬納森·尼爾森。請繼續。

Good afternoon, and thank you for joining us today. On the call with me are Satya Nadella, Chairman and Chief Executive Officer; Amy Hood, Chief Financial Officer; Alice Jolla, Chief Accounting Officer; and Keith Dolliver, Corporate Secretary and Deputy General Counsel.

下午好，感謝各位今天蒞臨。與我一同通話的有：董事長兼執行長薩蒂亞‧納德拉；財務長艾米‧胡德；首席會計官愛麗絲‧喬拉；以及公司秘書兼副總法律顧問基斯‧多利弗。

On the Microsoft Investor Relations website, you can find our earnings press release and financial summary slide deck, which is intended to supplement our prepared remarks during today's call and provides the reconciliation of differences between GAAP and non-GAAP financial measures. More detailed outlook slides will be available on the Microsoft Investor Relations website when we provide outlook commentary on today's call.

在微軟投資者關係網站上，您可以找到我們的收益新聞稿和財務摘要幻燈片，旨在補充我們今天電話會議上的發言，並提供 GAAP 和非 GAAP 財務指標之間差異的調節表。更詳細的展望幻燈片將在我們今天電話會議後發佈時，在微軟投資者關係網站上提供。

On this call, we will discuss certain non-GAAP items. The non-GAAP financial measures provided should not be considered as a substitute for or superior to the measures of financial performance prepared in accordance with GAAP. They are included as additional clarifying items to aid investors in further understanding the company's second-quarter performance in addition to the impact these items and events have on the financial results.

本次電話會議，我們將討論一些非GAAP專案。所提供的非GAAP財務指標不應被視為替代或優於依照GAAP編製的財務績效指標。列入這些項目是為了補充說明，幫助投資人進一步了解公司第二季的業績，以及這些項目和事件對財務表現的影響。

All growth comparisons we make on the call today relate to the corresponding period of last year, unless otherwise noted. We will also provide growth rates in constant currency when available as a framework for assessing how our underlying businesses performed, excluding the effect of foreign currency rate fluctuations. Where growth rates are the same in constant currency, we will refer to the growth rate only.

除非另有說明，我們今天在電話會議上所做的所有成長比較均與去年同期相關。我們也將提供以固定匯率計算的成長率（如有），以此作為評估我們基礎業務表現的框架，排除外匯匯率波動的影響。如果以固定匯率計算的成長率相同，我們將只提及成長率。

We will post our prepared remarks to our website immediately following the call until the complete transcript is available. Today's call is being webcast live and recorded. If you ask a question, it will be included in our live transmission, in the transcript, and in any future use of the recording. You can replay the call and view the transcript on the Microsoft Investor Relations website.

通話結束後，我們將立即在網站上發布準備好的發言稿，直到完整的通話記錄發佈為止。今天的電話會議將進行網路直播和錄製。如果您提出問題，該問題將包含在我們的直播節目中、節目文字稿中，以及錄音的任何未來用途。您可以造訪微軟投資者關係網站，重播此電話會議並查看會議記錄。

During this call, we will be making forward-looking statements, which are predictions, projections, or other statements about future events. These statements are based on current expectations and assumptions that are subject to risks and uncertainties. Actual results could materially differ because of factors discussed in today's earnings press release, in the comments made during this conference call, and in the risk factor section of our Form 10-K, Forms 10-Q, and other reports and filings with the Securities and Exchange Commission. We do not undertake any duty to update any forward-looking statement.

在本次電話會議中，我們將發表前瞻性聲明，即對未來事件的預測、展望或其他聲明。這些陳述是基於當前的預期和假設，但存在風險和不確定性。實際結果可能與預期有重大差異，原因包括今天發布的獲利新聞稿、本次電話會議中的評論以及我們在 10-K 表格、10-Q 表格和其他提交給美國證券交易委員會的報告和文件中風險因素部分討論的因素。我們不承擔更新任何前瞻性聲明的義務。

And with that, I'll turn the call over to Satya.

接下來，我將把電話交給薩蒂亞。

Thank you very much, Jonathan. This quarter, the Microsoft Cloud surpassed $50 billion in revenue for the first time, up 26% year over year, reflecting the strength of our platform and accelerating demand. We are in the beginning phases of AI diffusion and its broad GDP impact. Our TAM will grow substantially across every layer of the tech stack as this diffusion accelerates and spreads.

非常感謝你，喬納森。本季度，微軟雲端業務收入首次突破 500 億美元大關，年增 26%，這反映了我們平台的強大實力和不斷增長的需求。我們正處於人工智慧普及及其對GDP產生廣泛影響的初期階段。隨著這種擴散加速和蔓延，我們在技術堆疊的每一層都有可能大幅成長。

In fact, even in these early innings, we have built an AI business that is larger than some of our biggest franchises that took decades to build. Today, I'll focus my remarks across the three layers of our stack: Cloud and Token Factory, Agent platform, and high-value agentic experiences.

事實上，即使在起步階段，我們已經建立了一個比我們一些耗時數十年才建立起來的最大業務規模還要大的人工智慧業務。今天，我將重點介紹我們技術堆疊的三個層面：雲端和令牌工廠、代理平台以及高價值的代理體驗。

When it comes to our Cloud and Token Factory, the key to long-term competitiveness is shaping our infrastructure to support new high-scale workloads. We're building this infrastructure out for the heterogeneous and distributed nature of these workloads, ensuring the right fit with the geographic and segment-specific needs for all customers, including the long tail.

對於我們的雲端和令牌工廠而言，長期競爭力的關鍵在於塑造我們的基礎設施以支援新的大規模工作負載。我們正在建立此基礎設施，以適應這些工作負載的異質性和分散式特性，確保滿足所有客戶（包括長尾客戶）的地理和細分市場的特定需求。

The key metric we're optimizing for is tokens per watt per dollar, which comes down to increasing utilization and decreasing TCO using silicon systems and software. A good example of this is the 50% increase in throughput, we were able to achieve in one of our highest volume workloads, OpenAI inferencing, powering our Copilots.

我們正在優化的關鍵指標是每瓦每美元的代幣數，這歸根結底是透過矽系統和軟體提高利用率和降低總擁有成本來實現的。一個很好的例子是，我們在吞吐量最高的工作負載之一——OpenAI推理（為我們的Copilot提供支援）中實現了50%的吞吐量成長。

Another example was the unlocking of new capabilities and efficiencies for our Fairwater data centers. In this instance, we connected both Atlanta and Wisconsin site through an AI WAN to build a first-of-its-kind AI super factory. Fairwater's two-story design and liquid cooling allow us to run higher GPU densities and thereby improve both performance and latencies for high-scale training. All up, we added nearly 1 gigawatt of total capacity this quarter alone.

另一個例子是為我們 Fairwater 資料中心解鎖了新的功能和效率。在這種情況下，我們透過人工智慧廣域網路將亞特蘭大和威斯康辛州的站點連接起來，建造了首個人工智慧超級工廠。Fairwater 的雙層設計和液冷技術使我們能夠運行更高的 GPU 密度，從而提高大規模訓練的性能和延遲。本季度，我們總共新增了近1吉瓦的總裝置容量。

At the silicon layer, we have NVIDIA and AMD and our own Maia chips delivering the best all-up fleet performance, cost, and supply across multiple generations of hardware. Earlier this week, we brought online our Maia 200 accelerator.

在晶片層面，我們擁有 NVIDIA 和 AMD 的產品，以及我們自己的 Maia 晶片，可在多代硬體中提供最佳的整體性能、成本和供應。本週早些時候，我們的 Maia 200 加速器正式上線。

Maia 200 delivers 10 plus petaFLOPS at FP4 precision with over 30% improved TCO compared to the latest generation hardware in our fleet. We will be scaling this starting with inferencing and synthetic data gen for our superintelligence team, as well as doing inferencing for Copilot and Foundry.

Maia 200 的 FP4 精度可提供超過 10 petaFLOPS 的性能，與我們車隊中最新一代的硬體相比，TCO 降低了 30% 以上。我們將首先為我們的超級智慧團隊進行推理和合成資料生成，然後逐步擴大規模，同時為 Copilot 和 Foundry 進行推理。

And given AI workloads are not just about AI accelerators, but also consume large amounts of compute, we are pleased with the progress we are making on the CPU side as well. Cobalt 200 is another big leap forward delivering over 50% higher performance compared to our first custom-built processor for cloud-native workloads.

鑑於人工智慧工作負載不僅關乎人工智慧加速器，而且還消耗大量的運算資源，我們對在 CPU 方面取得的進展也感到滿意。Cobalt 200 是另一個巨大的飛躍，與我們第一款專為雲端原生工作負載定制的處理器相比，效能提高了 50% 以上。

Sovereignty is increasingly top of mind for customers, and we are expanding our solutions and global footprint to match. We announced DC investments in seven countries this quarter alone, supporting local data residency needs. And we offer the most comprehensive set of sovereignty solutions across public, private, and national partner clouds, so customers can choose the right approach for each workload with the local control they require.

主權問題越來越受到客戶的關注，我們也正在擴展我們的解決方案和全球業務範圍以滿足這一需求。光是本季度，我們就宣佈在七個國家進行資料中心投資，以滿足本地資料駐留需求。我們提供最全面的公有雲、私有雲和國家合作夥伴雲的主權解決方案，因此客戶可以根據每個工作負載的需求選擇合適的本地控制方法。

Next, I want to talk about the Agent platform. Like in every platform shift, all software is being rewritten; a new app platform is being born. You can think of agents as the new apps. And to build, deploy, and manage agents, customers will need a model catalog, tuning services, harness for orchestration, services for context engineering, AI safety, management, observability, and security.

接下來，我想談談代理平台。就像每一次平台更迭一樣，所有軟體都在重寫；一個新的應用平台正在誕生。你可以把經紀人看作是新型態的應用程式。為了建置、部署和管理代理，客戶需要模型目錄、調優服務、編排工具、情境工程服務、AI 安全性、管理、可觀測性和安全性。

It starts with having broad model choice. Our customers expect to use multiple models as part of any workload that they can fine-tune and optimize based on cost, latency, and performance requirements. And we offer the broader selection of models of any hyperscaler. This quarter, we added support for GPT-5.2 as well as Claude 4.5. Already, over 1,500 customers have used both anthropic and open AI models on Foundry.

首先要有廣泛的車型選擇。我們的客戶希望在任何工作負載中使用多個模型，並根據成本、延遲和效能要求對這些模型進行微調和最佳化。而且，我們提供的機型選擇比任何超大規模資料中心營運商都更廣泛。本季度，我們新增了對 GPT-5.2 和 Claude 4.5 的支援。目前，已有超過 1500 位客戶在 Foundry 上使用過類人人工智慧模型和開放人工智慧模型。

We are seeing increasing demand for region-specific models, including Mistral and Cohere, as more customers look for sovereign AI choices. And we continue to invest in our first-party models, which are optimized to address the highest value customer scenarios such as productivity, coding, and security.

我們看到，隨著越來越多的客戶尋求自主人工智慧選擇，對包括 Mistral 和 Cohere 在內的區域特定模型的需求不斷增長。我們將繼續投資於我們的第一方模型，這些模型經過最佳化，可滿足生產力、編碼和安全性等最高價值的客戶場景。

As part of Foundry, we also give customers the ability to customize and fine-tune models. Increasingly, customers want to be able to capture the tacit knowledge they possess inside of model weights as their core IP. This is probably the most important sovereign consideration for firms as AI diffuses more broadly across our GDP and every firm needs to protect their enterprise value.

作為 Foundry 的一部分，我們也為客戶提供客製化和微調模型的功能。客戶越來越希望能夠將他們擁有的隱性知識（包含在模型權重中）作為其核心智慧財產權加以捕捉。隨著人工智慧在我們的 GDP 中更廣泛地擴散，這可能是企業最重要的主權考量因素，因為每個企業都需要保護其企業價值。

For agents to be effective, they need to be grounded in enterprise data and knowledge. That means connecting their agents to systems of record and operational data, analytical data, as well as semi-structured and unstructured productivity and communications data. And this is what we are doing with our unified IQ layer spanning Fabric, Foundry, and data powering Microsoft 365.

要使代理有效工作，他們需要具備企業數據和知識基礎。這意味著將他們的代理商與記錄系統和營運數據、分析數據以及半結構化和非結構化的生產力和通訊數據連接起來。這就是我們正在利用統一的 IQ 層（涵蓋 Fabric、Foundry 和為 Microsoft 365 提供支援的資料）所做的事情。

In the world of context engineering, Foundry knowledge and Fabric are gaining momentum. Foundry knowledge delivers better context with automated source routing and advanced agentic retrieval, while respecting user permissions. And Fabric brings together end-to-end operational, real-time, and analytical data.

在情境工程領域，鑄造知識和結構正在蓬勃發展。Foundry 知識庫透過自動化來源路由和高階代理程式擷取提供更好的上下文，同時尊重使用者權限。Fabric 將端到端的營運數據、即時數據和分析數據整合在一起。

Two years since it became broadly available, Fabric's annual revenue run rate is now over $2 billion with over 31,000 customers. And it continues to be the fastest-growing analytics platform on the market with revenue up 60% year over year.

Fabric 自廣泛推出以來已有兩年時間，其年收入運行率現已超過 20 億美元，擁有超過 31,000 名客戶。而且它仍然是市場上成長最快的分析平台，營收年增 60%。

All up, the number of customers spending $1 million plus per quarter on Foundry grew nearly 80%, driven by strong growth in every industry. And over 250 customers are on track to process over 1 trillion tokens on Foundry this year.

總體而言，在 Foundry 上每季消費超過 100 萬美元的客戶數量成長了近 80%，這得益於各行業的強勁成長。今年，超過 250 家客戶預計在 Foundry 上處理超過 1 兆枚代幣。

There are many great examples of customers using all of this capability on Foundry to build their own agentic systems. Alaska Airlines is creating natural language flight search. BMW is speeding up design cycles. Land O' Lakes is enabling precision farming for co-op members, and SymphonyAI is addressing bottlenecks in the CPG industry.

有許多優秀的案例表明，客戶可以利用 Foundry 的所有功能來建立自己的代理系統。阿拉斯加航空正在開發自然語言航班搜尋功能。BMW正在加快設計週期。Land O' Lakes 正在為合作社成員提供精準農業服務，而 SymphonyAI 正在解決消費品行業的瓶頸問題。

And of course, Foundry remains a powerful on-ramp for the entire cloud. The vast majority of Foundry customers use additional Azure solutions like developer services, app services, databases as they scale.

當然，Foundry 仍然是通往整個雲端運算的強大入口。絕大多數 Foundry 客戶在擴展規模的過程中都會使用額外的 Azure 解決方案，例如開發人員服務、應用服務和資料庫。

Beyond Fabric and Foundry, we're also addressing agent building by knowledge workers with Copilot Studio and Agent Builder. Over 80% of the Fortune 500 have active agents built using these low-code, no-code tools. As agents proliferate, every customer will need new ways to deploy, manage, and protect them. We believe this creates a major new category and significant growth opportunity for us.

除了 Fabric 和 Foundry 之外，我們還透過 Copilot Studio 和 Agent Builder 來解決知識工作者建置代理程式的問題。超過 80% 的財富 500 強企業都使用這些低程式碼、無程式碼工具建立了活躍的代理程式。隨著代理商數量的激增，每個客戶都需要新的方法來部署、管理和保護它們。我們相信這將為我們創造一個全新的重要類別和巨大的成長機會。

This quarter, we introduced Agent 365, which makes it easy for organizations to extend their existing governance, identity, security, and management to agents. That means the same controls they already use across Microsoft 365 and Azure now extend to agents they build and deploy on our cloud or any other cloud.

本季度，我們推出了 Agent 365，它使組織能夠輕鬆地將其現有的治理、身分、安全和管理擴展到代理商。這意味著他們已經在 Microsoft 365 和 Azure 中使用的相同控制措施現在也適用於他們在我們的雲端或任何其他雲端上建置和部署的代理程式。

And partners like Adobe, Databricks, GenSpark, Glean, NVIDIA, SAP, ServiceNow, and Workday are already integrating Agent 365. We are the first provider to offer this type of agent control plane across clouds.

Adobe、Databricks、GenSpark、Glean、NVIDIA、SAP、ServiceNow 和 Workday 等合作夥伴已開始整合 Agent 365。我們是首家在雲端提供此類代理控制平面的供應商。

Now let's turn to the high-value agentic experiences we are building. AI experiences are intent-driven and are beginning to work at task scope. We are entering an age of macro-delegation and micro-steering across domains.

現在讓我們來看看我們正在建立的高價值智慧體驗。人工智慧體驗以意圖為驅動，並開始在任務範圍內發揮作用。我們正在進入一個跨領域宏觀授權和微觀管理的時代。

Intelligence using multiple models is built into multiple form factors. You see this in chat, in new Agent inbox apps, co-worker scaffoldings, Agent workflows embedded in applications and IDEs that are used every day, or even in our command line with file system access and skills. That's the approach we're taking with our first-party family of Copilot spanning key domains.

利用多種模型的智慧技術被整合到多種外形尺寸中。您可以在聊天、新的代理收件匣應用程式、同事腳手架、嵌入到日常使用的應用程式和 IDE 中的代理程式工作流程，甚至在我們的命令列中使用檔案系統存取和技能時看到這一點。這就是我們在涵蓋關鍵領域的自有 Copilot 系列產品中所採取的方法。

In consumer, for example, Copilot experiences span chat, news, feed, search, creation, browsing, shopping, and integrations into the operating system. And it's gaining momentum. Daily users of our Copilot app increased nearly 3x year over year, and with Copilot Checkout, we are partnered with PayPal, Shopify, and Stripe so customers can make purchases directly within the app.

例如，在消費者領域，Copilot 的體驗涵蓋聊天、新聞、資訊流、搜尋、創作、瀏覽、購物以及與作業系統的整合。而且這種趨勢正在加速發展。我們的 Copilot 應用程式的每日活躍用戶數量年增近 3 倍，透過 Copilot Checkout，我們與 PayPal、Shopify 和 Stripe 合作，因此客戶可以直接在應用程式內購買。

With Microsoft 365 Copilot, we are focused on organization-wide productivity. Work IQ takes the data underneath Microsoft 365 and creates the most valuable stateful agent for every organization. It delivers powerful reasoning capabilities over people, their roles, their artifacts, their communications, and their history and memory, all within an organization's security boundary.

透過 Microsoft 365 Copilot，我們專注於提升整個組織的生產力。Work IQ 取得 Microsoft 365 底層的數據，並為每個組織創建最有價值的有狀態代理。它能夠對人員、他們的角色、他們的物品、他們的通信以及他們的歷史和記憶進行強大的推理，所有這些都在組織的安全邊界內進行。

Microsoft 365 Copilot's accuracy and latency powered by Work IQ is unmatched, delivering faster and more accurate work-grounded results than competition. And we have seen our biggest quarter-over-quarter improvement in response quality to date. This has driven record usage intensity with average number of conversations per user doubling year over year. Microsoft 365 Copilot also is becoming a true daily habit with daily active users increasing 10x year over year.

由 Work IQ 支援的 Microsoft 365 Copilot 的準確性和延遲無與倫比，能夠提供比競爭對手更快、更準確的基於工作的結果。而且，我們的回應品質也實現了迄今為止最大的季度環比提升。這導致用戶使用強度創下歷史新高，平均每個用戶的對話次數比去年同期增加了一倍。Microsoft 365 Copilot 也正在成為一種真正的日常習慣，每日活躍用戶數逐年成長 10 倍。

We're also seeing strong momentum with researcher agent, which supports both OpenAI and Claude, as well as Agent Mode in Excel, PowerPoint, and Word. All up, it was a record quarter for Microsoft 365 Copilot seat ads, up over 160% year over year. We saw accelerating seat growth quarter over quarter and now have 15 million paid Microsoft 365 Copilot seats, and multiples more enterprise chat users.

我們也看到研究人員代理發展勢頭強勁，它支援 OpenAI 和 Claude，以及 Excel、PowerPoint 和 Word 中的代理模式。整體而言，微軟 365 Copilot 座位廣告在本季創下歷史新高，年增超過 160%。我們看到席位數量逐季加速成長，目前擁有 1500 萬個付費 Microsoft 365 Copilot 席位，以及數倍於此的企業聊天用戶。

And we are seeing larger commercial deployments. The number of customers with over 35,000 seats tripled year over year. Fiserv, ING, NASA, University of Kentucky, University of Manchester, US Department of Interior, and Westpac all purchased over 35,000 seats. Publicists alone, purchased over 95,000 seats for nearly all its employees.

我們看到商業部署規模正在擴大。擁有超過 35,000 個座位的客戶數量比去年同期增長了兩倍。Fiserv、ING、NASA、肯塔基大學、曼徹斯特大學、美國內政部和西太平洋銀行共購買了超過 35,000 個座位。光是公關公司就為幾乎所有員工購買了超過 95,000 個座位。

We are also taking share in Dynamics 365 with built-in agents across the entire suite. A great example of this is how Visa is turning customer conversations data into knowledge articles with our customer knowledge management agent in Dynamics. And how Sandvik is using our sales qualification agent to automate lead qualification across tens and thousands of potential customers.

我們還透過在整個套件中內建代理，在 Dynamics 365 中佔有一席之地。Visa 運用 Dynamics 中的客戶知識管理代理，將客戶對話資料轉化為知識文章，就是一個很好的例子。山特維克如何利用我們的銷售資格代理程序，自動對成千上萬的潛在客戶進行資格審查。

In coding, we are seeing strong growth across all paid GitHub Copilot. Copilot Pro+ subs for individual devs increased 77% quarter over quarter, and all up now we have 4.7 million paid Copilot subscribers up 75% year over year. Siemens, for example, is going all-in on GitHub, adopting the full platform to increase developer productivity after a successful Copilot rollout to 30,000-plus developers.

在編碼領域，我們看到所有付費的 GitHub Copilot 用戶都實現了強勁成長。Copilot Pro+ 個人開發者訂閱用戶數量較上季成長 77%，目前 Copilot 付費訂閱用戶總數達到 470 萬，較去年同期成長 75%。例如，西門子正在全力投入 GitHub，在成功向 3 萬多名開發人員推出 Copilot 之後，全面採用該平台以提高開發人員的生產力。

GitHub Agent HQ is the organizing layer for all coding agents like Anthropic, OpenAI, Google, Cognition, and xAI in the context of customers' GitHub repos. With Copilot CLI and VS Code, we offer developers the full spectrum of form factors and models they need for AI-first coding workflows.

GitHub Agent HQ 是所有編碼代理程式（如 Anthropic、OpenAI、Google、Cognition 和 xAI）在客戶 GitHub 程式碼庫中的組織層。透過 Copilot CLI 和 VS Code，我們為開發者提供 AI 優先編碼工作流程所需的各種外型尺寸和型號。

And when you add Work IQ as a skill or an MCP to our developer workflow, it's a game changer, surfacing more context like emails, meetings, docs, projects, messages, and more. You can simply ask the agent to plan and execute changes to your code base based on an update to a spec in SharePoint or using the transcript of your last engineering and design meeting in Teams.

當您將 Work IQ 作為技能或 MCP 添加到我們的開發人員工作流程中時，它將帶來翻天覆地的變化，展現更多上下文信息，例如電子郵件、會議、文件、項目、訊息等等。您可以直接要求代理根據 SharePoint 中規範的更新或使用您在 Teams 中上次工程和設計會議的記錄，來規劃和執行對程式碼庫的變更。

And we're going beyond that with GitHub Copilot SDK. Developers can now embed the same runtime behind Copilot CLI, multi-model, multi-step planning, tools, MCP integration, auth, streaming directly into their applications.

而我們更進一步，推出了 GitHub Copilot SDK。現在，開發人員可以將相同的運行時環境嵌入到 Copilot CLI、多模型、多步驟規劃、工具、MCP 整合、身份驗證和串流等功能中，直接整合到他們的應用程式中。

In security, we added a dozen new and updated Security Copilot agents across Defender, Entra, Intune, and Purview. For example, Icertis' SOC team used Security Copilot agent to reduce manual triage time by 75%, which is a real game changer in an industry facing a severe talent shortage.

在安全性方面，我們在 Defender、Entra、Intune 和 Purview 中新增和更新了十幾個 Security Copilot 代理程式。例如，Icertis 的 SOC 團隊使用 Security Copilot 代理將人工分診時間減少了 75%，這對於面臨嚴重人才短缺的行業來說，無疑是一項顛覆性的變革。

To make it easier for security teams to onboard, we are rolling out Security Copilot to all our E5 customers, and our security solutions are also becoming essential to manage organizations' AI deployments. 24 billion Copilot interactions were audited by Purview this quarter, up 9x year over year.

為了方便安全團隊快速上手，我們正在向所有 E5 客戶推廣 Security Copilot，同時我們的安全解決方案也正成為企業管理 AI 部署的關鍵工具。本季度，Purview 對 240 億次 Copilot 交互進行了審計，年增 9 倍。

Finally, I want to talk about two additional high-impact agentic experiences. First in healthcare, Dragon Copilot is the leader in its category, helping over 100,000 medical providers automate their workflows. Mount Sinai Health is now moving to a system-wide Dragon Copilot deployment for providers after a successful trial with its primary care physicians. All up, we helped document 21 million patient encounters this quarter, up 3x year over year.

最後，我想談談另外兩個影響深遠的能動性體驗。Dragon Copilot 是醫療保健領域的先驅，也是該領域的領導者，可協助超過 10 萬家醫療機構自動化工作流程。在與初級保健醫生成功試用後，西奈山醫療系統現在正著手在全系統範圍內為醫療服務提供者部署 Dragon Copilot。本季我們共記錄了 2,100 萬例患者就診情況，比去年同期成長了 3 倍。

And second, when it comes to science and engineering, companies like Unilever in consumer goods and Synopsys in EDA are using Microsoft Discovery to orchestrate specialized agents for R&D end to end. They're able to reason over scientific literature and internal knowledge, formulate hypotheses, spin up simulations, and continuously iterate to drive new discoveries.

其次，在科學和工程領域，像聯合利華這樣的消費品公司和 Synopsys 這樣的 EDA 公司正在使用 Microsoft Discovery 來協調專門的代理進行端到端的研發。他們能夠對科學文獻和內部知識進行推理，提出假設，啟動模擬，並不斷迭代以推動新的發現。

Beyond AI, we continue to invest in all our core franchises and meet the needs of our customers and partners, and we are seeing strong progress. For example, when it comes to cloud migrations, our new SQL Server has over 2x the IaaS adoption of the previous version.

除了人工智慧之外，我們繼續投資所有核心業務，滿足客戶和合作夥伴的需求，並且我們看到了強勁的進展。例如，在雲端遷移方面，我們的新 SQL Server 的 IaaS 採用率是上一版本的 2 倍以上。

In security, we now have 1.6 million security customers, including over a million who use four or more of our workloads. Windows reached a big milestone, 1 billion Windows 11 users, up over 45% year over year. And we had share gains this quarter across Windows, Edge, and Bing. Double-digit member growth in LinkedIn with 30% growth in paid video ads.

在安全領域，我們現在擁有 160 萬安全客戶，其中包括超過 100 萬名使用我們四個或更多工作負載的客戶。Windows 達到一個重要的里程碑，Windows 11 用戶數達到 10 億，較去年同期成長超過 45%。本季我們在 Windows、Edge 和 Bing 的市佔率均有所成長。LinkedIn 會員數達到兩位數成長，付費影片廣告收入成長 30%。

And in gaming, we are committed to delivering great games across Xbox, PC, Cloud, and every other device. And we saw record PC players and paid streaming hours on Xbox.

在遊戲方面，我們致力於在 Xbox、PC、雲端遊戲以及其他所有裝置上提供優秀的遊戲體驗。我們也看到 PC 玩家數量和 Xbox 付費直播時長都創下新紀錄。

In closing, we feel very good about how we are delivering for customers today and building the full stack to capture the opportunity ahead. With that, let me turn it over to Amy to walk through our financial results and outlook, and I look forward to rejoining for your questions.

最後，我們對目前為客戶提供的服務以及建立全端以抓住未來機會的能力感到非常滿意。接下來，我將把發言權交給艾米，讓她為大家介紹我們的財務表現和展望，期待稍後再回來回答大家的問題。

Thank you, Satya, and good afternoon, everyone. With growing demand for our offerings and focused execution by our sales teams, we again exceeded expectations across revenue, operating income, and earnings per share, while investing to fuel long-term growth.

謝謝你，薩蒂亞，大家下午好。由於市場對我們產品的需求不斷增長，加上銷售團隊的專注執行，我們在收入、營業收入和每股盈餘方面再次超出預期，同時也進行了投資以推動長期成長。

This quarter, revenue was $81.3 billion, up 17% and 15% in constant currency. Gross margin dollars increased 16% and 14% in constant currency, while operating income increased 21% and 19% in constant currency.

本季營收為 813 億美元，年增 17%，以固定匯率計算成長 15%。以固定匯率計算，毛利成長了 16% 和 14%；以固定匯率計算，營業收入成長了 21% 和 19%。

Earnings per share was $4.14, an increase of 24% and 21% in constant currency, when adjusted for the impact from our investment in OpenAI. And FX increased reported results slightly less than expected, particularly in Intelligent Cloud revenue.

每股收益為 4.14 美元，以固定匯率計算增長了 24%，扣除我們對 OpenAI 的投資的影響後，增長了 21%。FX公佈的業績成長略低於預期，尤其是在智慧雲端營收。

Company gross margin percentage was 68% down slightly year over year, primarily driven by continued investments in AI infrastructure and growing AI product usage that was partially offset by ongoing efficiency gains particularly in Azure and M365 Commercial cloud, as well as sales mix shift to higher margin businesses.

公司毛利率較去年同期略有下降 68%，主要原因是人工智慧基礎設施的持續投資和人工智慧產品使用量的成長，但部分被 Azure 和 M365 商業雲端的持續效率提升以及銷售組合向高利潤業務的轉變所抵消。

Operating expenses increased 5% and 4% in constant currency, driven by R&D investments and compute capacity and AI talent, as well as impairment charges in our gaming business. Operating margins increased year over year to 47% ahead of expectations.

營運費用以固定匯率計算成長了 5% 和 4%，主要原因是研發投資、運算能力和人工智慧人才的增加，以及遊戲業務的減損支出。營業利益率年增至 47%，超出預期。

As a reminder, we still account for our investment in OpenAI under the equity method. And as a result of OpenAI's recapitalization, we now record gains or losses based on our share of the change in their net assets on their balance sheet as opposed to our share of their operating profit or losses from their income statement.

再次提醒，我們對 OpenAI 的投資仍採用權益法進行會計處理。由於 OpenAI 進行了資本重組，我們現在根據其資產負債表上淨資產變動的份額來記錄收益或損失，而不是根據其損益表中營業利潤或虧損的份額來記錄收益或損失。

Therefore, we recorded a gain which drove other income and expense to $10 billion in our GAAP results. When adjusted for the OpenAI impact, other income and expense was slightly negative and lower than expected, driven by net losses on investments.

因此，我們記錄了一項收益，這使得我們的 GAAP 業績中的其他收入和支出達到 100 億美元。剔除 OpenAI 的影響後，其他收入和支出略為負值，低於預期，主要原因是投資淨虧損。

Capital expenditures were $37.5 billion, and this quarter, roughly two-thirds of our CapEx was on short-lived assets, primarily GPUs and CPUs. Our customer demand continues to exceed our supply. Therefore, we must balance the need to have our incoming supply better meet growing Azure demand, with expanding first-party AI usage across services like M365 Copilot and GitHub Copilot, increasing allocations to R&D teams to accelerate product innovation, and continued replacement of end-of-life server and networking equipment.

資本支出為 375 億美元，本季度，我們約三分之二的資本支出用於短期資產，主要是 GPU 和 CPU。客戶需求持續超過供應。因此，我們必須在以下方面取得平衡：一方面要確保我們的供應能夠更好地滿足不斷增長的 Azure 需求，另一方面要擴大第一方 AI 在 M365 Copilot 和 GitHub Copilot 等服務中的使用，增加對研發團隊的撥款以加速產品創新，並持續更換已停產的伺服器和網路設備。

The remaining spend was for long-lived assets that will support monetization for the next 15 years and beyond. This quarter, total finance leases were $6.7 billion and were primarily for large data center sites. And cash paid for PP&E was $29.9 billion.

剩餘的支出用於長期資產，這些資產將在未來 15 年及更長時間內支持其貨幣化。本季融資租賃總額為 67 億美元，主要用於大型資料中心。為固定資產支付的現金為 299 億美元。

Cash flow from operations was $35.8 billion, up 60%, driven by strong cloud billings and collections. And free cash flow is $5.9 billion and decreased sequentially, reflecting the higher cash capital expenditures from a lower mix of finance leases.

經營活動產生的現金流為 358 億美元，成長 60%，主要得益於強勁的雲端計費和收款。自由現金流為 59 億美元，環比下降，反映出融資租賃比例下降導致現金資本支出增加。

And finally, we returned $12.7 billion to shareholders through dividend and share repurchases, an increase of 32% year over year.

最後，我們透過分紅和股票回購向股東返還了 127 億美元，年增 32%。

Now, to our commercial results. Commercial bookings increased 230% and 228% in constant currency, driven by the previously announced large Azure commitment from OpenAI that reflects multi-year demand needs, as well as the previously announced Anthropic commitment from November, and healthy growth across our core annuity sales motions.

現在，讓我們來看看我們的商業成果。以固定匯率計算，商業預訂量增加了 230% 和 228%，這主要得益於 OpenAI 先前宣布的 Azure 大額訂單（反映了多年的需求），以及 Anthropic 先前宣布的 11 月訂單，以及我們核心年金銷售業務的穩健成長。

Commercial remaining performance obligation, which continues to be reported net of reserves, increased to $625 billion and was up 110% year over year, with a weighted average duration of approximately 2.5 years. Roughly, 25% will be recognized in revenue in the next 12 months, up 39% year over year. The remaining portion, recognized beyond the next 12 months, increased 156%.

商業剩餘履約義務（繼續按扣除準備金後的淨額報告）增至 6,250 億美元，年增 110%，加權平均期限約為 2.5 年。大約 25% 將在未來 12 個月內確認為收入，年增 39%。剩餘部分（在未來 12 個月後確認）增加了 156%。

Approximately 45% of our commercial RPO balance is from OpenAI. The significant remaining balance grew 28% and reflects ongoing broad customer demand across the portfolio.

我們商業 RPO 餘額中約 45% 來自 OpenAI。剩餘的大量資產成長了 28%，反映了整個產品組合持續廣泛的客戶需求。

Microsoft Cloud revenue was $51.5 billion and grew 26% and 24% in constant currency. Microsoft Cloud gross margin percentage was slightly better than expected at 67% and down year over year due to continued investments in AI that were partially offset by ongoing efficiency gains noted earlier.

微軟雲端業務收入為 515 億美元，以固定匯率計算成長了 26% 和 24%。微軟雲端業務毛利率為 67%，略好於預期，但同比下降，原因是先前提到的持續效率提升部分抵消了對人工智慧的持續投資。

Now to our segment results, revenue from Productivity and Business Processes was $34.1 billion and grew 16% and 14% in constant currency. M365 Commercial Cloud revenue increased 17% and 14% in constant currency, with consistent execution in the core business and increasing contribution from strong Copilot results.

現在來看看我們各業務部門的業績，生產力和業務流程部門的收入為 341 億美元，以固定匯率計算成長了 16% 和 14%。M365 商業雲端收入按固定匯率計算增長了 17% 和 14%，這得益於核心業務的持續執行以及 Copilot 的強勁業績帶來的不斷增長的貢獻。

ARPU growth was again led by E5 and M365 Copilot. And paid M365 Commercial seats grew 6% year over year to over 450 million, with installed base expansion across all customer segments though primarily in our small and medium business and frontline worker offerings. M365 Commercial products revenue increased 13% and 10% in constant currency ahead of expectations due to higher-than-expected Office 2024 transactional purchasing.

E5 和 M365 Copilot 再次引領了 ARPU 的成長。付費版 M365 商業版用戶數年增 6%，超過 4.5 億，所有客戶群的安裝基礎均有所擴大，但主要集中在中小企業和第一線員工產品。由於 Office 2024 的交易採購量高於預期，M365 商業產品收入以固定匯率計算成長了 13% 和 10%，超出預期。

M365 consumer cloud revenue increased 29% and 27% in constant currency, again driven by ARPU growth. M365 consumer subscriptions grew 6%. LinkedIn revenue increased 11% and 10% in constant currency driven by marketing solutions. Dynamics 365 revenue increased 19% and 17% in constant currency with continued growth across all workloads.

M365 消費者雲端收入以固定匯率計算成長了 29% 和 27%，再次受到 ARPU 成長的推動。M365 消費者訂閱量成長了 6%。受行銷解決方案的推動，LinkedIn 的營收以固定匯率計算成長了 11% 和 10%。Dynamics 365 的營收以固定匯率計算成長了 19%，成長了 17%，所有工作負載均持續成長。

Segment gross margin dollars increased 17% and 15% in constant currency. And gross margin percentage increased, again driven by efficiency gains at M365 Commercial Cloud that were partially offset by continued investments in AI, including the impact of growing Copilot usage.

以固定匯率計算，分部毛利率成長了 17%，毛利率成長了 15%。毛利率也隨之提高，這再次得益於 M365 商業雲的效率提升，但部分被人工智慧領域的持續投資所抵消，其中包括 Copilot 使用量不斷增長的影響。

Operating expenses increased 6% and 5% in constant currency, and operating income increased 22% and 19% in constant currency. Operating margins increased year over year to 60%, driven by improved operating leverage, as well as the higher gross margins noted earlier.

以固定匯率計算，營業費用增加了 6% 和 5%；以固定匯率計算，營業收入成長了 22% 和 19%。營業利潤率年增至 60%，這主要得益於經營槓桿的改善以及前面提到的毛利率的提高。

Next, the Intelligent Cloud segment. Revenue was $32.9 billion and grew 29% and 28% in constant currency. In Azure and other cloud services, revenue grew 39% and 38% in constant currency, slightly ahead of expectations, with ongoing efficiency gains across our fungible fleet, enabling us to reallocate some capacity to Azure that was monetized in the quarter.

接下來是智慧雲部分。營收達 329 億美元，以固定匯率計算成長 29% 及 28%。在 Azure 和其他雲端服務中，以固定匯率計算，營收分別成長了 39% 和 38%，略高於預期，這得益於我們可互換資產組合的持續效率提升，使我們能夠將部分容量重新分配給 Azure，並在本季度實現了貨幣化。

As mentioned earlier, we continue to see strong demand across workloads, customer segments, and geographic regions. And demand continues to exceed available supply.

如前所述，我們持續看到各種工作負載、客戶群和地理區域的需求強勁。需求持續超過供應。

In our on-premises server business, revenue increased 2% and 1% in constant currency ahead of expectations, driven by demand for our hybrid solutions, including a benefit from the launch of SQL Server 2025, as well as higher transactional purchasing ahead of memory price increases.

在我們的本地伺服器業務中，收入按固定匯率計算增長了 2% 和 1%，超出預期，這主要得益於市場對我們混合解決方案的需求，包括 SQL Server 2025 發布帶來的收益，以及在內存價格上漲之前更高的交易採購量。

Segment gross margin dollars increased 20% and 19% in constant currency. Gross margin percentage decreased year over year, driven by continued investments in AI and sales mix shift to Azure, partially offset by efficiency gains in Azure.

以固定匯率計算，分部毛利率分別成長了 20% 和 19%。受人工智慧持續投資和銷售組合轉移到 Azure 的影響，毛利率年減，但 Azure 的效率提升部分抵銷了這一影響。

Operating expenses increased 3% and 2% in constant currency, and operating income grew 28% and 27% in constant currency. Operating margins were 42%, down slightly year over year as increased investments in AI were mostly offset by improved operating leverage.

以固定匯率計算，營業費用增加了 3% 和 2%；以固定匯率計算，營業收入成長了 28% 和 27%。營業利益率為 42%，年比略有下降，原因是人工智慧投資的增加被營運槓桿的改善所抵消。

Now to More Personal Computing, revenue was $14.3 billion and declined 3%. Windows OEM and devices revenue increased 1% and was relatively unchanged in constant currency. Windows OEM grew 5% with strong execution, as well as a continued benefit from Windows 10 end of support. Results were ahead of expectations as inventory levels remained elevated, with increased purchasing ahead of memory price increases.

現在來看更多個人運算業務，收入為 143 億美元，下降了 3%。Windows OEM 和裝置收入成長了 1%，以固定匯率計算基本上保持不變。Windows OEM 業務成長 5%，這得益於強勁的執行力，以及 Windows 10 停止支援帶來的持續效益。由於庫存水準居高不下，且在記憶體價格上漲之前增加了採購，因此業績超出預期。

Search and news advertising revenue ex-TAC increased 10% and 9% in constant currency, slightly below expectations, driven by some execution challenges. As expected, the sequential growth rate moderated as the benefit from third-party partnerships normalized.

扣除TAC後，搜尋和新聞廣告收入以固定匯率計算分別成長了10%和9%，略低於預期，主要原因是執行上遇到了一些挑戰。正如預期的那樣，隨著第三方合作帶來的收益趨於正常化，連續成長率有所放緩。

And in Gaming, revenue decreased 9% and 10% in constant currency. Xbox content and services revenue decreased 5% and 6% in constant currency and was below expectations driven by first-party content with impact across the platform.

遊戲業務收入以固定匯率計算下降了 9% 至 10%。Xbox 內容和服務收入以固定匯率計算分別下降了 5% 和 6%，低於預期，主要原因是第一方內容對整個平台造成了影響。

Segment gross margin dollars increased 2% and 1% in constant currency, and gross margin percentage increased year over year, driven by sales mix shift to higher margin businesses. Operating expenses increased 6% and 5% in constant currency, driven by the impairment charges in our gaming business noted earlier, as well as R&D investments in compute capacity and AI talent.

以固定匯率計算，分部毛利分別成長了 2% 和 1%，毛利率也較去年同期成長，這主要得益於銷售組合向高利潤業務的轉變。營運費用以固定匯率計算成長了 6% 和 5%，主要原因是先前提到的遊戲業務減損支出，以及對運算能力和人工智慧人才的研發投資。

Operating income decreased 3% and 4% in constant currency. And operating margins were relatively unchanged over a year at 27%, as higher operating expenses were mostly offset by higher gross margins.

以固定匯率計算，營業收入下降了3%和4%。營業利益率一年來基本保持不變，為 27%，因為較高的營運費用基本上被較高的毛利率所抵銷。

Now moving to our Q3 outlook, which unless specifically noted otherwise, is on a US dollar basis. Based on current rates, we expect FX to increase total revenue growth by 3 points. Within the segments, we expect FX to increase revenue growth by 4 points in productivity and business processes, and 2 points in Intelligent Cloud, and More Personal Computing.

現在來看看我們第三季的展望，除非另有特別說明，否則均以美元計價。根據目前的匯率，我們預計外匯將使總收入成長增加 3 個百分點。在各個細分領域中，我們預期 FX 在生產力和業務流程方面的收入成長將提高 4 個百分點，在智慧雲端和更多個人運算方面的收入成長將提高 2 個百分點。

We expect FX to increase COGS and operating expense growth by 2 points. As a reminder, this impact is due to the exchange rates a year ago.

我們預期外匯波動將使銷售成本和營運費用成長增加 2 個百分點。需要提醒的是，這種影響是由於一年前的匯率造成的。

Starting with the total company, we expect revenue of USD80.65 billion to USD81.75 billion, or growth of 15% to 17% with continued strong growth across our commercial businesses, partially offset by our consumer businesses. We expect COGS of USD26.65 billion to USD26.85 billion, or growth of 22% to 23% and operating expense of USD17.8 billion to USD17.9 billion, or growth of 10% to 11%, driven by continued investment in R&D, AI compute capacity, and talent, against a low prior-year comparable. Operating margins should be down slightly year over year.

從公司整體來看，我們預計營收將達到 806.5 億美元至 817.5 億美元，成長 15% 至 17%，這主要得益於商業業務的持續強勁成長，但部分會被消費業務的成長所抵銷。我們預計銷售成本為 266.5 億美元至 268.5 億美元，年增 22% 至 23%；營運費用為 178 億美元至 179 億美元，年成長 10% 至 11%，主要得益於對研發、人工智慧運算能力和人才的持續投資，而上年同期基數較低。營業利潤率預計較去年同期略有下降。

Excluding any impact from our investments in OpenAI, other income and expense is expected to be roughly $700 million, driven by a fair market gain in our equity portfolio and interest income, partially offset by interest expense, which includes the interest payments related to data center finance leases. And we expect our adjusted Q3 effective tax rate to be approximately 19%.

不計入我們在 OpenAI 的投資的影響，其他收入和支出預計約為 7 億美元，主要來自我們股權投資組合的公允市場收益和利息收入，部分被利息支出抵消，其中包括與數據中心融資租賃相關的利息支出。我們預計第三季調整後的實際稅率約為 19%。

Next, we expect capital expenditures to decrease on a sequential basis due to the normal variability from cloud infrastructure buildouts and the timing of delivery of finance leases. As we work to close the gap between demand and supply, we expect the mix of short-lived assets to remain similar to Q2.

接下來，由於雲端基礎設施建設的正常波動以及融資租賃交付時間的差異，我們預計資本支出將逐週下降。在我們努力縮小供需差距的同時，我們預期短期資產的組成將與第二季類似。

Now, our commercial business. In commercial bookings, we expect healthy growth in the core business on a growing expiry base when adjusted for the OpenAI contracts in the prior year. As a reminder, the significant OpenAI contract signed in Q2 represents multi-year demand needs from them, which will result in some quarterly volatility in both bookings and RPO growth rates going forward.

現在，我們來說說我們的商業業務。在商業預訂方面，我們預計核心業務將實現健康成長，到期基數不斷擴大，即使扣除上一年 OpenAI 的合同，這一增長也將持續。需要提醒的是，OpenAI 在第二季度簽署的重大合約代表了他們未來多年的需求，這將導致未來預訂量和 RPO 成長率出現一些季度波動。

Microsoft Cloud gross margin percentage should be roughly 65% down year over year driven by continued investments in AI.

受人工智慧領域持續投資的影響，微軟雲端的毛利率預計將年減約 65%。

Now to segment guidance, in Productivity and Business Processes, we expect revenue of USD34.25 billion to USD34.55 billion, or growth of 14% to 15%. In M365 Commercial Cloud, we expect revenue growth to be between 13% and 14% in constant currency with continued stability in year-over-year growth rates on a large and expanding base. Accelerating momentum and ongoing E5 adoption will again drive ARPU growth.

現在來看看細分領域的績效指引，在生產力和業務流程領域，我們預期營收為 342.5 億美元至 345.5 億美元，成長 14% 至 15%。在 M365 商業雲端領域，我們預計以固定匯率計算的營收成長將在 13% 到 14% 之間，在龐大且不斷擴大的基數上，年成長率將保持穩定。加速成長動能和 E5 的持續普及將再次推動 ARPU 成長。

M365 Commercial products revenue should decline in the low-single digits down sequentially, assuming Office 2024 transactional purchasing trends normalize. As a reminder, M365 commercial products include components that can be variable due to in-period revenue recognition dynamics.

假設 Office 2024 的交易購買趨勢正常化，M365 商業產品收入應該會比上季下降個位數百分比。提醒各位，M365 商業產品包含的組件可能會因期間收入確認動態而改變。

M365 Consumer Cloud revenue growth should be in the mid- to high-20% range, driven by growth at ARPU as well as continued subscription volume. For LinkedIn, we expect revenue growth to be in the low-double digits. And in Dynamics 365, we expect revenue growth to be in the high teens, with continued growth across all workloads.

M365 消費者雲端收入成長應在 20% 到 20% 之間，主要得益於 ARPU 的成長以及訂閱量的持續成長。對於 LinkedIn，我們預計營收成長將達到兩位數低點。在 Dynamics 365 方面，我們預計營收成長將達到 10% 以上，所有工作負載都將持續成長。

For Intelligent Cloud, we expect revenue of USD34.1billion to USD34.4 billion, or growth of 27% to 29%. In Azure, we expect Q3 revenue growth to be between 37% and 38% in constant currency against a prior-year comparable that included significantly accelerating growth rates in both Q3 and Q4.

對於智慧雲，我們預計營收為 341 億美元至 344 億美元，成長 27% 至 29%。在 Azure 方面，我們預計第三季營收成長將達到 37% 至 38%（以固定匯率計算），而去年同期營收成長顯著加快，第三季和第四季的成長率均大幅上升。

As mentioned earlier, demand continues to exceed supply, and we will need to continue to balance the incoming supply we can allocate here against other priorities. As a reminder, there can be quarterly variability in year-on-year growth rates depending on the timing of capacity delivery and when it comes online, as well as from end-period revenue recognition, depending on the mix of contracts.

如前所述，需求持續超過供應，我們需要繼續平衡我們能夠分配到這裡的供應量與其他優先事項之間的關係。需要提醒的是，由於產能交付時間和上線時間以及期末收入確認等因素，同比增速可能會出現季度波動，具體取決於合約組合。

In our on-premises server business, we expect revenue to decline in the low single digits as growth rate normalize following the launch of SQL Server 2025, though increased memory pricing could create additional volatility in transactional purchasing.

在我們的本地伺服器業務中，隨著 SQL Server 2025 的發布，成長率將趨於正常化，我們預計收入將出現個位數百分比的下降，儘管記憶體價格上漲可能會為交易購買帶來額外的波動。

In More Personal Computing, we expect revenue to be USD12.3 billion to USD12.8 billion. Windows OEM and devices revenue should decline in the low teens. Growth rates will be impacted as the benefit from Windows 10 end of support normalizes and as elevated inventory levels come down through the quarter. Therefore, Windows OEM revenue should decline roughly 10%.

在「更多個人計算」領域，我們預計收入將達到 123 億美元至 128 億美元。Windows OEM 和裝置收入預計將下降 10% 左右。隨著 Windows 10 停止支援帶來的好處逐漸顯現，以及本季高企的庫存水準下降，成長率將受到影響。因此，Windows OEM 收入應該會下降約 10%。

The range of potential outcomes remains wider than normal, in part due to the potential impact on the PC market from increased memory pricing. Search and news advertising ex-TAC revenue growth should be in the high-single digits. Even as we work to improve execution, we expect continued share gains across Bing and Edge, with growth driven by volume. And we expect sequential growth moderation as the contribution from third-party partnerships continues to normalize.

由於記憶體價格上漲可能對個人電腦市場造成影響，潛在結果的範圍仍然比正常情況更廣。剔除流量獲取成本後的搜尋和新聞廣告收入成長應為高個位數。即使我們努力提高執行力，我們預計 Bing 和 Edge 的市佔率將繼續成長，成長將由流量驅動。我們預計，隨著第三方合作關係的貢獻逐漸正常化，成長速度將逐步放緩。

And in Xbox content and services, we expect revenue to decline in the mid-single digits against a prior-year comparable that benefited from strong content performance, partially offset by growth in Xbox Game Pass. And hardware revenue should decline year over year.

在 Xbox 內容和服務方面，我們預計收入將比上年同期下降個位數百分比，去年同期受益於強勁的內容表現，但 Xbox Game Pass 的成長部分抵消了這一降幅。硬體收入預計會逐年下降。

Now, some additional thoughts on the rest of the fiscal year and beyond. First, FX: Based on current rates, we expect FX to increase Q4 total revenue and COGS growth by less than 1 point, with no impact to operating expense growth. Within the segments, we expect FX to increase revenue growth by roughly 1 point in Productivity and Business Processes and More Personal Computing, and less than 1 point in Intelligent Cloud.

現在，再補充一些關於本財年剩餘時間和未來發展的想法。首先是外匯：根據目前的匯率，我們預期外匯將使第四季總收入和銷售成本成長增加不到 1 個百分點，對營運費用成長沒有影響。在各個細分市場中，我們預期 FX 將使生產力和業務流程以及更多個人運算領域的收入成長提高約 1 個百分點，而智慧雲端領域的收入成長將不到 1 個百分點。

With the strong work delivered in H1 to prioritize investment in key growth areas and the favorable impact from a higher mix of revenue in our Windows OEM and commercial on-prem businesses, we now expect FY26 operating margins to be up slightly.

由於上半年我們在重點成長領域優先投資方面取得了顯著成效，並且 Windows OEM 和商業本地部署業務的收入佔比提高也帶來了有利影響，我們現在預計 2026 財年的營業利潤率將略有上升。

We mentioned the potential impact on Windows OEM and on-premises server markets from increased memory pricing earlier. In addition, rising memory prices would impact capital expenditures, though the impact on Microsoft Cloud gross margins will build more gradually as these assets depreciate over six years.

我們之前提到記憶體價格上漲可能對 Windows OEM 和本地伺服器市場產生的影響。此外，記憶體價格上漲也會影響資本支出，不過由於這些資產會在六年內逐漸折舊，因此對微軟雲端毛利率的影響會逐漸顯現。

In closing, we delivered strong top-line growth in H1 and are investing across every layer of the stack to continue to deliver high-value solutions and tools to our customers. With that, let's go to Q&A, Jonathan.

綜上所述，我們在上半年實現了強勁的營收成長，並且正在對技術棧的各個層面進行投資，以繼續為客戶提供高價值的解決方案和工具。那麼，接下來進入問答環節，喬納森。

Thanks, Amy. We'll now move over to Q&A. Out of respect for others on the call, we request the participants please only ask one question. Operator, can you please repeat your instructions?

謝謝你，艾米。接下來進入問答環節。出於對其他與會者的尊重，請每位與會者只提一個問題。操作員，請您再重複一次您的指示好嗎？

(Operator Instructions) Keith Weiss, Morgan Stanley.

（操作說明）基斯‧韋斯，摩根士丹利。

Excellent. Thank you, guys, for taking the question. I'm looking at a Microsoft print where earnings is growing 24% year on year, which is a spectacular result, great execution on your part, top-line growing well, margins expanding.

出色的。謝謝各位回答這個問題。我看到微軟的財報顯示，其獲利年增 24%，這是一個非常亮眼的成績，你們執行得非常出色，營收成長良好，利潤率也在擴大。

But I'm looking at afterhours trading and the stock is down. And I think one of the core issues that is weighing on investors is CapEx is growing faster than we expect. And maybe Azure is growing a little bit slower than we expected. And I think that's fundamentally comes down to a concern on the ROI on this CapEx spend over time.

但我查看盤後交易情況時發現，這隻股票下跌了。我認為，令投資人擔憂的核心問題之一是資本支出成長速度超過預期。或許 Azure 的成長速度比我們預期的要慢一些。我認為這從根本上來說是對這項資本支出長期投資報酬率的擔憂。

So I was hoping you guys could help us fill in some of the blindfold a little bit, in terms of how should we think about capacity expansion and what that yield in terms of Azure growth going forward? More to the point, how should we think about the ROI on this investment as it comes to fruition? Thanks, guys.

所以我希望各位能幫我們撥開一些迷霧，讓我們了解一下我們該如何看待容量擴張，以及這對 Azure 未來的成長會帶來怎樣的收益？更重要的是，我們該如何看待這項投資最終帶來的投資報酬率？謝謝各位。

Thanks, Keith. Let me start, and Satya can add some comments, I'm sure. I think the first thing -- I think you really asked a very direct correlation that I do think many investors are doing, which is between the CapEx spend and seeing Azure revenue number.

謝謝你，基斯。我先來，薩蒂亞肯定也可以補充一些意見。我認為首先——我認為你確實問了一個非常直接的相關性問題，我認為很多投資者都在這樣做，那就是資本支出和 Azure 收入數字之間的關係。

And we tried last quarter and I think again this quarter to talk more specifically about all the places that the CapEx spend, especially the short-lived CapEx spend across CPU and GPU and where that'll show up. Sometimes, I think it's probably better to think about the Azure guidance that we give as an allocated capacity guide about what we can deliver in Azure revenue. Because as we spend the capital and put GPUs specifically, it applies to CPUs, but GPUs more specifically, we're really making long-term decisions.

上個季度我們嘗試過，我認為這個季度我們也會再次嘗試，更具體地討論資本支出的所有領域，特別是 CPU 和 GPU 的短期資本支出，以及這些支出將體現在哪裡。有時，我認為最好將我們提供的 Azure 指導視為分配容量指南，以說明我們可以在 Azure 收入方面實現什麼目標。因為當我們投入資金並專門用於GPU時，這雖然也適用於CPU，但更具體地說是GPU，我們實際上是在做出長期決策。

And the first thing we're doing is solving for the increased usage in sales and the accelerating pace of M365 Copilot as well as GitHub pilot or first-party apps. Then we make sure we're investing in the long-term nature of R&D and product innovation.And much of the acceleration that I think you've seen from us and products over the past a bit is coming because we are allocating GPUs and capacity to many of the talented AI people we've been hiring over the past years.

我們首先要做的就是解決銷售中使用量增加以及 M365 Copilot、GitHub pilot 或第一方應用程式的加速發展所帶來的問題。然後，我們會確保對研發和產品創新進行長期投資。我認為，你們在過去一段時間裡看到的我們和產品方面的加速發展，很大程度上是因為我們將GPU和資源分配給了過去幾年裡我們招募的許多優秀的AI人才。

Then when you end up is that you end up with the remainder going towards serving the Azure capacity that continues to grow in terms of demand. And a way to think about it because I think I get asked this question sometimes is if I had taken the GPUs that just came online in Q1 and Q2 in terms of GPUs and allocated them all to Azure, the KPI would have been over 40.

最終的結果是，剩餘的資金將用於滿足 Azure 容量不斷增長的需求。思考這個問題的一種方式是，因為我有時會被問到這個問題：如果我把第一季和第二季剛剛上線的 GPU 全部分配給 Azure，那麼 KPI 將超過 40。

And I think the most important thing to realize is that this is about investing in all the layers of the stack that benefit customers. And I think that's hopefully helpful in terms of thinking about capital growth, it shows in every piece, it shows in revenue growth across the business and shows as OpEx growth as we invest in our people.

我認為最重要的是要認識到，這關乎投資於所有能讓客戶受益的技術堆疊層面。我認為這對於思考資本成長應該有所幫助，這點體現在方方面面，體現在整個業務的收入成長上，也體現在我們投資員工的營運支出成長。

Yeah, I think you, Amy, covered it. BBut basically, as an investor, I think when you think about our capital and you think about the GM profile of our portfolio, you should obviously think about Azure. But you should think about M365 Copilot, and you should think about GitHub Copilot, you should think about Dragon Copilot, Security Copilot.

是的，我覺得艾米，你已經說得很清楚了。但基本上，作為一名投資者，我認為當你考慮我們的資本以及我們投資組合的通用汽車概況時，你顯然應該考慮 Azure。但你應該考慮一下 M365 Copilot，你應該考慮一下 GitHub Copilot，你應該考慮一下 Dragon Copilot 和 Security Copilot。

All of those have a GM profile and lifetime value. I mean if you think about it, acquiring an Azure customer is super important to us, but so is acquiring an M365 or GitHub or a Dragon Copilot. These are all by the way incremental businesses and TAMs for us.

所有這些都具有通用汽車的概況和終身價值。我的意思是，仔細想想，取得 Azure 客戶對我們來說非常重要，但取得 M365、GitHub 或 Dragon Copilot 也同樣重要。順便一提，這些都是我們新增的業務和潛在市場規模。

And so we don't want to maximize just one business of ours. We want to be able to allocate capacity while we're sort of supply constrained in a way that allow us to essentially build the best LTV portfolio. That's on one side.

因此，我們不想只追求旗下某項業務的最大化。我們希望能夠在供應受到一定限制的情況下合理分配產能，從而建立最佳的LTV投資組合。這是其中一方面。

And the other one that Amy mentioned is also R&D. I mean you got to think about compute is also R&D, and that's sort of the second element of it. And so we are using all of that, obviously, to optimize for the long term.

艾米提到的另一個也是研發部門。我的意思是，你要考慮到計算也是研發的一部分，這算是其中的第二個要素。因此，很顯然，我們正在利用所有這些因素來優化長期發展。

Excellent. Thanks.

出色的。謝謝。

Thanks, Keith. Operator, next question, please.

謝謝你，基斯。接線員，請問下一個問題？

Marc Mordler, Bernstein Research.

馬克‧莫德勒，伯恩斯坦研究公司。

Thank you very much for taking my question, and congrats on the quarter. One of the other questions we believe investors want to understand is how to think about your line of sight from hardware CapEx investment to revenue and margins.

非常感謝您回答我的問題，也恭喜您本季取得佳績。我們認為投資人想要了解的另一個問題是，如何看待硬體資本支出投資與收入和利潤率之間的關係。

The capitalized server is over six years, but the average duration of RPO is 2.5 years, up from two years last quarter. How do investors get that since this is a lot of this CapEx centric, that you'll be able to capture sufficient revenue over the six-year use of life if the hardware delivers solid revenue and gross profit dollars growth, hopefully one similar to the CPU revenue? Thank you.

資本化伺服器的使用年限超過六年，但平均 RPO 持續時間為 2.5 年，高於上季的兩年。鑑於該專案以資本支出為主，投資者如何確信，如果硬體能夠帶來穩定的收入和毛利成長（希望與 CPU 收入的成長類似），那麼在六年的使用壽命內，您將能夠獲得足夠的收入？謝謝。

Thanks, Mark. Let me start with a high level, and Satya, you can add as well. I think, when you think about average duration, I think what you're getting to is -- and we need to remember, is that average duration is a combination of broad set of contract arrangements that we have, a lot of them around things like M365 or a GitHub portfolio, are shorter dated, right, three-year contracts? And so they have quite frankly a short duration.

謝謝你，馬克。我先從高層次的層次談起，薩蒂亞，你也可以補充一些內容。我認為，當你考慮平均持續時間時，你最終會明白——我們需要記住，平均持續時間是我們各種合約安排的組合，其中很多都是圍繞 M365 或 GitHub 作品集之類的，期限較短，對吧，三年合約？因此，坦白說，它們的持續時間很短。

The majority then that's remaining are Azure contracts that are longer duration. And you saw that this quarter when we saw the extension of that duration from around 2 years to 2.5. And the way to think about that is the majority of the capital that we're spending today, and a lot of the GPUs that we're buying, are already contracted for most of their useful life.

那麼，剩下的大部分就是期限較長的 Azure 合約。正如您在本季所看到的，我們看到合約期限從大約 2 年延長至 2.5 年。理解這一點的方式是，我們今天花費的大部分資金，以及我們購買的許多 GPU，其大部分使用壽命都已經簽訂了合約。

And so a way to think about that is, much of that risk that I think you're pointing to isn't there, because they're already sold for the entirety of their useful life. And so part of it exists because you have this shorter-dated RPO, because of some of the M365 stuff. If you look at the Azure only, RPO is a little bit more extended. A lot of that is CPU basis. It's not just GPU.

因此，我們可以這樣理解：你指出的許多風險並不存在，因為它們的使用壽命已經全部售出。部分原因是由於 M365 的一些內容，導致 RPO 的期限縮短。如果只看 Azure，RPO 的範圍會稍微寬一點。很多都與CPU有關。不只是GPU的問題。

And on the GPU contracts that we've talked about, including for some of our largest customers, those are sold for the entire useful life of the GPU. And so there's not the risk to which I think you may be referring. Hopefully, that's helpful.

在我們討論過的 GPU 合約中，包括我們一些最大客戶的合約，合約期限涵蓋 GPU 的整個使用壽命。因此，不存在你可能指的是的那種風險。希望這能有所幫助。

Yeah. And just one other thing I would add to it is in addition to sort of what Amy mentioned, which is it's already contracted for the useful life, is we do use software to continuously align even the latest models on the fleet that is aging, if you will.

是的。我還要補充一點，除了 Amy 提到的已經簽訂了使用壽命合約之外，我們還使用軟體來不斷調整我們車隊中那些正在老化的最新型號。

So that's sort of what gives us that duration. And so at the end of the day we want to have -- that's why we even think about aging the fleet constantly. It's not about buying a whole lot of gear one year. It's about each year you write the Moore's law, you add, you use software, and then you optimize across all of it.

這就是持續時間的由來。所以歸根結底，我們想要的是——這就是為什麼我們甚至不斷考慮讓艦隊老化。重點不在於一年內購買大量裝備。每年你都會寫摩爾定律，不斷增加新功能，使用軟體，然後對所有這些進行最佳化。

And Mark, maybe to state this in case it's not obvious, is that as you go through the useful life, actually, you get more and more and more efficient at delivery. So where you've sold the entirety of its life, the margins actually improved with time. And so I think that may be a good reminder to people as we see that, obviously, in the CPU fleet all the time.

馬克，或許我應該說明一下，以免你沒意識到，隨著你職涯的推進，你的交付效率實際上會越來越高。所以，如果你賣掉了它的整個生命週期，利潤率實際上會隨著時間的推移而提高。所以我覺得這或許能給人們一個好的提醒，因為我們顯然經常在 CPU 叢集中看到這種情況。

That's a great answer. I really appreciate it, and thank you.

這是一個很好的答案。我非常感激，謝謝。

Thanks, Mark. Operator, next question, please.

謝謝你，馬克。接線員，請問下一個問題？

Brent Thill, Jefferies.

布倫特‧蒂爾，傑富瑞集團。

Thanks, Amy. On 45% of the backlog being related to OpenAI, I'm just curious if you can comment. There's obviously concern about the durability. And I know maybe there's not much you can say in this. But I think everyone's concerned about the exposure. And if you could maybe talk through your perspective and what both you and Satya are seeing.

謝謝你，艾米。關於積壓工作中有 45% 與 OpenAI 相關這一點，我很好奇您是否能發表一下看法。顯然，人們對其耐用性有擔憂。我知道在這件事上你可能沒什麼好說的。但我認為大家都很擔心曝光問題。如果你能談談你的看法，以及你和薩蒂亞都看到了什麼，那就太好了。

I think maybe I would have thought about the question quite differently, Brent. The first thing to focus on is the reason we talked about that number is because 55% or roughly $350 billion is related to the breadth of our portfolio, a breadth of customers across solutions, across Azure, across industries, across geographies.

布倫特，我想我可能會以完全不同的方式思考這個問題。首先要關注的是，我們之所以談到這個數字，是因為 55% 或大約 3500 億美元與我們產品組合的廣度有關，即客戶遍布各個解決方案、Azure、各個行業、各個地區。

That is a significant RPO balance, larger than most peers, more diversified than most peers. And frankly, I think we have super high confidence in it. And when you think about that portion alone growing 28%, it's really impressive work on the breadth as well as the adoption curve that we're seeing, which is I think what I get asked most frequently, it's grown by customer segment, by industry and by geo.

這是一個相當可觀的RPO平衡，比大多數同行規模更大，也比大多數同行更加多元化。坦白說，我認為我們對此非常有信心。光是這一部分就成長了 28%，這確實令人印象深刻，無論是在覆蓋率還是採用率方面，我們都看到了顯著的成長。這也是我被問到最多的問題：它是否以客戶群、產業和地理劃分而成長？

And so it's very consistent. And so then if you're asking about, how do I feel about OpenAI and the contract and the health, listen, it's a great partnership. We continue to be their provider of scale. We're excited to do that. We sit under one of the most successful businesses built, and we continue to feel quite good about that. It's allowed us to remain a leader in terms of what we're building and being on the cutting edge of app innovation.

所以它非常一致。所以，如果你問我對 OpenAI、合約和健康狀況有何感想，聽著，這是一個很棒的合作關係。我們將繼續為他們提供規模化解決方案。我們很樂意這樣做。我們身處一家非常成功的企業旗下，對此我們感到非常自豪。這使我們能夠在產品開發方面保持領先地位，並始終處於應用程式創新的前沿。

Karl Kirsted, UBS.

卡爾‧基爾斯特德，瑞銀集團。

Okay, thank you very much. Amy, regardless of how you allocate capacity between first-party and third-party, can you comment qualitatively on the amount of capacity that you have coming on? I think the 1 gigawatt added in the December quarter was extraordinary and hints that the capacity ads are accelerating.

好的，非常感謝。艾米，無論你如何分配第一方和第三方的產能，你能否定性地評估一下你即將獲得的產能量？我認為12月季度新增的1吉瓦裝置容量非同尋常，這暗示著裝機容量的成長正在加速。

But I think a lot of investors have their eyes on Fairwater Atlanta, Fairwater Wisconsin, and would love some comments about the magnitude of the capacity as regardless of how they're allocated in the coming quarters. Thank you.

但我認為很多投資者都在關注亞特蘭大費爾沃特和威斯康辛州費爾沃特，他們很想了解這些項目的產能規模，無論未來幾季如何分配。謝謝。

Yeah, Karl, I think we've said a couple of things. We're working as hard as we can to have capacity as quickly as we can. You've mentioned specific sites like Atlanta or Wisconsin. Those are multi-year deliveries, so I wouldn't necessarily on specific locations.

是的，卡爾，我想我們已經說過一些事情了。我們正竭盡全力盡快提升產能。您曾提及一些具體地點，例如亞特蘭大或威斯康辛州。這些都是多年交付的訂單，所以我不一定會指定特定的交貨地點。

The real thing we've got to do, and we're working incredibly hard at doing it, is adding capacity globally. A lot of that will be added in the United States, the two locations you've mentioned. It also needs to be added across the globe to meet the customer demand that we're seeing and the increased usage.

我們真正必須做的事情，也是我們正在努力做的事情，就是在全球範圍內增加產能。其中很多將在美國新增，也就是你提到的那兩個地方。此外，還需要在全球範圍內推廣，以滿足我們看到的客戶需求和不斷增長的使用量。

We'll continue to add both long-lived infrastructure. The way to think about that is we need to make sure we've got power and land and facilities available. And we'll continue to put GPUs and CPUs in them when they're done as quickly as we can.

我們將繼續增加長期基礎設施。思考這個問題的方式是，我們需要確保我們有足夠的電力、土地和設施。我們會在它們組裝完成後儘快繼續為其安裝 GPU 和 CPU。

And then finally, we'll try to make sure it is efficient as we possibly can on the pace at which we do that and how we operate them so that they can have the highest possibility utility. And so I think, it's not really about, two places, Karl. I would distract away from that.

最後，我們將盡力確保我們在推進這項工作的速度和操作方式上盡可能高效，從而使其發揮最大的效用。所以我覺得，卡爾，這其實不是關於兩個地方的問題。我會轉移注意力。

Those are multi-year delivery timelines. But really, we just need to get it done every location where we're currently in a build or starting to do that. We're working as quickly as we can.

這些都是需要數年才能完成的交付計畫。但實際上，我們只需要在我們目前正在建造或即將開始建造的每個地方完成這項工作。我們正在盡最大努力加快速度。

Okay, got it. Thank you.

好的，明白了。謝謝。

Thanks, Karl. Operator, next question, please.

謝謝你，卡爾。接線員，請問下一個問題？

Mark Murphy, JPMorgan.

馬克墨菲，摩根大通。

Thank you so much. Satya, the performance achievements of the Maia 200 accelerator for inference look quite remarkable, especially in comparison to TPUs in Trainium and Blackwell which have just been around a lot longer.

太感謝了。Satya，Maia 200 加速器在推理方面的性能表現相當出色，尤其是與 Trainium 和 Blackwell 中那些已經存在了更長時間的 TPU 相比。

Could you put that accomplishment in perspective in terms of how much of a core competency you think silicon might be coming from Microsoft? And Amy, are there any ramifications worth mentioning there in terms of supporting your gross margin profile for inference costs going forward?

您能否從微軟在矽晶片領域的核心競爭力角度來看待這項成就？艾米，就未來推斷成本而言，這是否會對你的毛利率水準產生任何值得一提的影響？

Yeah, no. Thanks for the question. So a couple of things. One is, we've been at this in a variety of different forms for a long, long time in terms of building our own silicon. And so we're very thrilled about the progress with Maia 200.

不，不是。謝謝你的提問。有兩件事。一方面，我們在自主研發矽晶片方面，已經以各種不同的形式進行了很長時間。因此，我們對 Maia 200 的進展感到非常興奮。

And especially, when we think about running a GPT-5.2 and the performance we're able to get in the [GEMS] at FP4, just proves a point that when you have a new workload, a new shape of a workload, you can start innovating end to end between the model and silicon and the entire system. It's just not even about just silicon; the way the networking works at rack scale that's optimized with memory for this particular workload.

尤其是當我們考慮在 FP4 的 [GEMS] 上運行 GPT-5.2 以及我們能夠獲得的性能時，這正好證明了一點：當你有一個新的工作負載，一個新的工作負載形式時，你可以開始在模型、晶片和整個系統之間進行端到端的創新。這不僅是矽晶片的問題；而是機架級網路的工作方式，以及針對這種特定工作負載優化的記憶體。

Then the thing is we're obviously round tripping and working very closely with our own superintelligence team with all of our models, as you can imagine, whatever we build will be all optimized for Maia. So we feel great about it.

那麼問題在於，我們顯然要與我們自己的超級智慧團隊密切合作，開發我們所有的模型，正如你所想，我們建立的任何東西都將針對 Maia 進行最佳化。所以我們對此感到非常滿意。

And I think to think about all up is being such early innings. I mean, even just look at the amount of silicon innovation and systems innovation. Even since December, I think the new thing is everybody's talking about low-latency inference, right? And so one of the things we want to make sure is we're not locked in any one thing. If anything, we have a great partnership with NVIDIA, AMD. They're innovating; we're innovating.

我覺得現在考慮所有因素還為時過早。我的意思是，即使只看矽晶片創新和系統創新的數量。自去年 12 月以來，我認為大家都在談論低延遲推理，對吧？因此，我們想要確保的一件事就是不要被任何單一的模式所束縛。如果有什麼合作的話，那就是我們與英偉達和AMD建立了良好的合作關係。他們在創新；我們也在創新。

We want to flee at any given point in time to have access to the best TCO. And it's not a one-generation game. I think a lot of folks just talk about who's ahead. It's just, remember, you have to be ahead for all the time to come. And that means you really want to think about having a lot of innovation that happens out there to be in your fleet, so that your fleet is fundamentally advantaged at the TCO level.

我們希望隨時都能逃離，以便獲得最佳的整體擁有成本 (TCO)。而且它不是一款只能玩一代的遊戲。我覺得很多人只會討論誰領先。記住，你必須時刻保持領先。這意味著你真的應該考慮將市場上大量的創新應用到你的艦隊中，從而使你的艦隊在總體擁有成本 (TCO) 層面上具有根本優勢。

So that's kind of how I look at it, which is we are excited about Maia, we're excited about Cobalt, we're excited about our DPU, our NIX. So we have a lot of systems capability. That means we can vertically integrate. And because we can vertically integrate doesn't mean we just only vertically integrate. And so we want to be able to have the flexibility here and that's what you see us do.

所以，我的看法就是這樣，我們對 Maia 感到興奮，我們對 Cobalt 感到興奮，我們對我們的 DPU 和 NIX 感到興奮。所以我們擁有強大的系統能力。這意味著我們可以進行垂直整合。能夠進行垂直整合並不代表我們只能進行垂直整合。所以我們希望能夠擁有這種靈活性，而你也看到了我們正在這樣做。

Thanks, Mark. Operator, next question, please.

謝謝你，馬克。接線員，請問下一個問題？

Brad Zelnick, Deutsche Bank.

布拉德‧澤爾尼克，德意志銀行。

Great, thank you very much. Satya, we heard a lot about frontier transformations from Judson and Ignite. And we've seen customers realize breakthrough benefits when they adopt the Microsoft AI stack. Can you help frame for us the momentum and enterprise marking on these journeys? And any expectation for how much their spend with Microsoft can expand in becoming frontier firms? Thanks.

太好了，非常感謝。Satya，我們從 Judson 和 Ignite 那裡聽到了很多關於前沿轉型的事情。我們已經看到，客戶在採用微軟人工智慧技術堆疊後獲得了突破性的收益。您能否幫助我們整理一下這些旅程的發展動能和企業發展策略？那麼，對於這些公司作為前沿企業，它們在微軟的支出規模會有怎樣的成長，我們有什麼預期呢？謝謝。

Yeah, thank you for that. So I think one of the things that we are seeing is the adoption across the three major suites of ours, right? So if you take M365, you take what's happening with security, and you take GitHub. In fact, it's fascinating.

是的，謝謝你。所以我認為我們看到的一個現像是，我們的三大主要套件都得到了廣泛採用，對吧？所以，如果你考慮 M365，你就會了解安全方面的狀況，還會考慮 GitHub。事實上，這很迷人。

I mean, these three things had effectively compounding effects for our customers in the past, like something like Entra as an identity system or Defender as the protection system across all three was sort of super helpful. But so what now you're seeing is something like Work IQ, right?

我的意思是，這三件事過去對我們的客戶產生了有效的疊加效應，例如 Entra 作為身份系統或 Defender 作為這三者的保護系統，都非常有幫助。所以你現在看到的是類似工作智商（Work IQ）的東西，對吧？

So I mean, just to give you a flavor for it, the most important database underneath for any company that uses Microsoft today is the data underneath Microsoft 365. And the reason is because it has all this tacit information, right? Who are your people? What are the relationships? What are the projects they're working on? What are their artifacts, their communications?

所以我的意思是，舉個例子來說，對於當今任何使用微軟產品的公司而言，最重要的底層資料庫就是 Microsoft 365 底層的資料。原因就在於它包含了所有這些隱性訊息，對吧？你們的人民是誰？它們之間是什麼關係？他們正在進行哪些專案？他們的文物是什麼？他們的溝通方式是什麼？

So that's a super important asset for any business process business, workflow context. In fact, the scenario I even had in my transcript around, you can now take Work IQ as an MCP server, and you know you have report and say, hey, please look at my design meetings for the last month in Teams and tell me if my report reflects it. I mean, that's a pretty high-level way to think about how -- what is happening previously perhaps with our tools, business, and our get-out business, are suddenly being transformative, right?

所以，這對於任何業務流程、工作流程環境來說都是極為重要的資產。事實上，我甚至在我的成績單上寫過這樣一個場景：你現在可以把 Work IQ 作為 MCP 伺服器，你知道你有一份報告，然後說：“嘿，請看看我上個月在 Teams 中的設計會議，告訴我我的報告是否反映了這一點。”我的意思是，這是一種相當高層次的思考方式，可以理解為什麼以前我們的工具、業務和退出業務正在發生變革，對吧？

That agent black plane is really transforming companies in some sense. So that's I think the most magical thing, which is you deploy these things and suddenly the agents are helping you coordinate, bring more leverage to your enterprise.

那架黑色飛機確實在某種程度上改變了公司。所以我覺得最神奇的地方在於，當你部署這些東西之後，代理商就會幫助你協調，為你的企業帶來更大的優勢。

Then on top of it, of course there is the transformation, which is what businesses are doing, how should we think about customer service? How should we think about marketing? How should we think about finance? How should we think about that and build our own agents? That's where all the services in Fabric and Foundry, and of course, with GitHub tooling is helping them. Or even the local-code, no-code tools, I had some stats so much that's being used.

此外，當然還有轉型，也就是企業正在做的事情，我們該如何看待客戶服務？我們該如何看待行銷？我們該如何看待金融？我們應該如何思考這個問題並建立我們自己的代理？這正是 Fabric 和 Foundry 中的所有服務，當然還有 GitHub 工具可以幫助他們的地方。甚至對於本地程式碼、無程式碼工具，我有一些統計數據顯示它們的使用量非常大。

But one of the more exciting things for me is these new systems M365 Copilot, GitHub Copilot, Security Copilot, all coming together to compound the benefits of all the data and all the deployment, I think, is probably the most transformative effect right now.

但對我來說，更令人興奮的事情之一是這些新系統 M365 Copilot、GitHub Copilot、Security Copilot 全部結合在一起，增強了所有數據和所有部署的優勢，我認為，這可能是目前最具變革性的影響。

Thank you, very helpful.

謝謝，很有幫助。

Thanks, Brad. Operator, we have time to ask questions.

謝謝你，布拉德。操作員，我們有時間提問。

Raimo Lenschow, Barclays.

雷莫·倫肖，巴克萊銀行。

Perfect. Thanks for squeezing me in. The last few quarters we talked -- besides the GPU side, we talked about CPU as well on the other side. And you have some operational changes at the beginning of January last year.

完美的。謝謝你擠出時間幫我。過去幾個季度，除了GPU方面，我們也討論了CPU方面的問題。去年一月初，你們進行了一些營運上的調整。

Can you speak what you saw there? And maybe put it more in the bigger picture in terms of clients realizing that they can move to cloud is important if you want to deliver proper AI. So what are you seeing in terms cloud transitions? Thank you.

你能說說你在那裡看到了什麼嗎？或許應該從更宏觀的角度來看這個問題：如果想要提供真正的人工智慧，讓客戶意識到他們可以遷移到雲端就非常重要。那麼，您在雲端遷移方面看到了哪些情況？謝謝。

I didn't quite -- sorry about that. You were asking about the SMC, CPU side, or can you just repeat the question, please?

我沒能完全做到——對此我感到抱歉。您問的是關於SMC和CPU方面的問題，還是可以再重複一次您的問題？

Yeah, sorry, I was wondering about the CPU side of Azure because we had some operational changes there. And we also hear from the fields a lot that people are realizing they need to be in the cloud if you want to do proper AI and that kind of provide the momentum. Thank you.

是的，抱歉，我問的是 Azure 的 CPU 方面的問題，因為我們那方面有一些營運上的變動。我們也常聽到業內人士說，他們意識到如果想要真正實現人工智慧，就必須使用雲端技術，這為人工智慧的發展提供了動力。謝謝。

Yeah, I think -- I think I get it. So first of all, I had mentioned in my remarks that when you think about AI workloads, you shouldn't think of AI workload as just AI accelerator compute, right?

是的，我想我明白了。首先，我在發言中提到過，在考慮人工智慧工作負載時，不應該僅僅將人工智慧工作負載視為人工智慧加速器運算，對吧？

Because in some sense, if you take any agent, the agent will then spawn through tools used, maybe a container which runs obviously on compute. In fact, we have -- whenever we think about even the building out of the fleet, we think ratios. Or even for a training job, by the way, an AI training job requires a bunch of compute and a bunch of storage, very close to compute.

因為從某種意義上說，如果你選擇任何代理，該代理將透過使用的工俱生成，例如運行在計算資源上的容器。事實上，每當我們考慮擴建艦隊時，我們都會想到比例。或者說，即使是訓練任務，人工智慧訓練任務也需要大量的計算和存儲，與計算非常接近。

So therefore, and the same thing in inferencing as well. So the inferencing with agent mode would require you to essentially provision a computer or computing resources to the agent, so they don't need GPUs. They're running on GPUs, but they need computers, which are computing storage. So that's what's happening even in the new world.

因此，推理中也是如此。因此，使用代理模式進行推理實際上需要為代理提供電腦或計算資源，所以它們不需要 GPU。它們在 GPU 上運行，但它們需要計算機，而計算機是計算儲存設備。所以，即使在新世界裡，這種情況也在發生。

The other thing you mentioned is the cloud migrations are still going on. In fact, one of the stats I had was SQL -- latest SQL Server growing as an IaaS service in Azure. And so that's one of the reasons why we have to think about commercial cloud and keep it balanced with the rest of our AI cloud, because when clients bring their workloads and bring workloads, they need all of these infrastructure elements in the region in which they're deploying.

您提到的另一點是，雲端遷移仍在進行中。事實上，我掌握的統計數據之一是 SQL——最新的 SQL Server 作為 Azure 中的 IaaS 服務正在成長。所以，這也是我們必須考慮商業雲端並使其與我們的 AI 雲端保持平衡的原因之一，因為當客戶將他們的工作負載遷移到我們的 AI 雲端時，他們需要在部署區域內擁有所有這些基礎設施元素。

Okay, thank you.

好的，謝謝。

Thanks, Raimo. That wraps up the Q&A portion of today's earnings call. Thank you for joining us today, and we look forward to speaking with you all soon.

謝謝你，雷莫。今天的財報電話會議問答環節到此結束。感謝各位今天蒞臨，我們期待很快能與大家再次交流。

Thank you, all.

謝謝大家。

Thank you.

謝謝。

Thank you. This conference has now ended. You may disconnect your lines at this time. And we thank you for your participation. Have a great night.

謝謝。本次會議已經結束。您可以在此時斷開線路。感謝您的參與。祝你有個美好的夜晚。