輝達 (NVDA) 2023 Q3 法說會逐字稿

Good afternoon. My name is Emma, and I will be your conference operator today. At this time, I would like to welcome everyone to the NVIDIA's Third Quarter Earnings Call. (Operator Instructions)

下午好。我叫艾瑪，今天我將擔任你們的會議接線員。在這個時候，歡迎大家參加 NVIDIA 第三季度財報電話會議。 （操作員說明）

Simona Jankowski, you may begin your conference.

Simona Jankowski，你可以開始你的會議了。

Thank you. Good afternoon, everyone, and welcome to NVIDIA's conference call for the third quarter of fiscal 2023. With me today from NVIDIA are Jensen Huang, President and Chief Executive Officer; and Colette Kress, Executive Vice President and Chief Financial Officer.

謝謝你。大家下午好，歡迎參加 NVIDIA 2023 財年第三季度電話會議。今天來自 NVIDIA 的是總裁兼首席執行官黃仁勳；執行副總裁兼首席財務官 Colette Kress。

I'd like to remind you that our call is being webcast live on NVIDIA's Investor Relations website. The webcast will be available for replay until the conference call to discuss our financial results for the fourth quarter and fiscal 2023. The content of today's call is NVIDIA's property. It can't be reproduced or transcribed without our prior written consent.

我想提醒您，我們的電話會議正在 NVIDIA 的投資者關係網站上進行網絡直播。在討論我們第四季度和 2023 財年財務業績的電話會議之前，可以重播網絡廣播。今天電話會議的內容是 NVIDIA 的財產。未經我們事先書面同意，不得複製或轉錄。

During this call, we may make forward-looking statements based on current expectations. These are subject to a number of significant risks and uncertainties, and our actual results may differ materially. For a discussion of factors that could affect our future financial results and business, please refer to the disclosure in today's earnings release, our most recent Forms 10-K and 10-Q and the reports that we may file on Form 8-K with the Securities and Exchange Commission.

在此次電話會議中，我們可能會根據當前預期做出前瞻性陳述。這些都受到許多重大風險和不確定性的影響，我們的實際結果可能存在重大差異。有關可能影響我們未來財務業績和業務的因素的討論，請參閱今天的收益發布中的披露、我們最近的 10-K 和 10-Q 表格以及我們可能在 8-K 表格上提交的報告證券交易委員會。

All our statements are made as of today, November 16, 2022, based on information currently available to us. Except as required by law, we assume no obligation to update any such statements. During this call, we will discuss non-GAAP financial measures. You can find a reconciliation of these non-GAAP financial measures to GAAP financial measures in our CFO commentary, which is posted on our website.

我們的所有聲明都是根據我們目前可獲得的信息，截至今天，即 2022 年 11 月 16 日作出的。除非法律要求，否則我們不承擔更新任何此類聲明的義務。在這次電話會議中，我們將討論非 GAAP 財務指標。您可以在我們網站上發布的 CFO 評論中找到這些非 GAAP 財務指標與 GAAP 財務指標的對賬。

With that, let me turn the call over to Colette.

有了這個，讓我把電話轉給科萊特。

Thanks, Simona. Q3 revenue was $5.93 billion, down 12% sequentially and down 17% year-on-year. We delivered record data center and automotive revenue, while our gaming and pro visualization platforms declined as we work through channel inventory corrections and challenging external conditions.

謝謝，西蒙娜。第三季度收入為 59.3 億美元，環比下降 12%，同比下降 17%。我們提供了創紀錄的數據中心和汽車收入，而我們的遊戲和專業可視化平台因我們通過渠道庫存調整和具有挑戰性的外部條件而下降。

Starting with data center. Revenue of $3.83 billion was up 1% sequentially and 31% year-on-year. This reflects very solid performance in the face of macroeconomic challenges, new export controls and lingering supply chain disruptions. Year-on-year growth was driven primarily by leading U.S. cloud providers and a broadening set of consumer Internet companies for workloads such as large language models, recommendation systems and generative AI.

從數據中心開始。收入 38.3 億美元，環比增長 1%，同比增長 31%。這反映出在面對宏觀經濟挑戰、新的出口管制和揮之不去的供應鏈中斷時表現非常穩健。同比增長主要是由美國領先的雲提供商和範圍更廣的消費互聯網公司推動的，這些公司提供大型語言模型、推薦系統和生成人工智能等工作負載。

As the number and scale of public cloud computing and Internet service companies deploying NVIDIA AI grows, our traditional hyperscale definition will need to be expanded to convey the different end market use cases. We will align our data center customer commentary going forward accordingly. Other vertical industries, such as automotive and energy, also contributed to growth with key workloads relating to autonomous driving, high-performance computing, simulations and analytics.

隨著部署 NVIDIA AI 的公共雲計算和互聯網服務公司的數量和規模不斷增長，我們傳統的超大規模定義將需要擴展以傳達不同的終端市場用例。我們將相應地調整我們的數據中心客戶評論。汽車和能源等其他垂直行業也通過與自動駕駛、高性能計算、模擬和分析相關的關鍵工作負載促進了增長。

During the quarter, the U.S. government announced new restrictions impacting exports of our A100 and H-100 based products to China, and any product destined for certain systems or entities in China. These restrictions impacted third quarter revenue, largely offset by sales of alternative products into China. That said, demand in China more broadly remains soft, and we expect that to continue in the current quarter. We started shipping our flagship H-100 data center GPU based on the new Hopper Architecture in Q3. H-100-based systems are available starting this month from leading server makers including Dell, Hewlett Packard Enterprise, Lenovo and Supermicro.

本季度，美國政府宣布了新的限制措施，影響我們基於 A100 和 H-100 的產品出口到中國，以及任何運往中國特定係統或實體的產品。這些限制影響了第三季度的收入，但在很大程度上被替代產品在中國的銷售所抵消。也就是說，中國的需求更廣泛地保持疲軟，我們預計本季度將繼續如此。我們在第三季度開始出貨基於新 Hopper 架構的旗艦 H-100 數據中心 GPU。基於 H-100 的系統從本月起可從包括戴爾、惠普企業、聯想和超微在內的領先服務器製造商處獲得。

Early next year, the first H-100 based cloud instances will be available on Amazon Web Services, Google Cloud, Microsoft Azure and Oracle Cloud Infrastructure. H-100 delivered the highest performance and workload versatility for both AI training and inference in the latest MLPerf industry benchmarks. H-100 also delivers incredible value compared to the previous generation for equivalent AI performance. It offers 3x lower total cost of ownership while using 5x fewer server nodes and 3.5x less energy.

明年初，首批基於 H-100 的雲實例將在 Amazon Web Services、Google Cloud、Microsoft Azure 和 Oracle Cloud Infrastructure 上提供。 H-100 在最新的 MLPerf 行業基準測試中為 AI 訓練和推理提供了最高的性能和工作負載多功能性。與具有同等 AI 性能的上一代產品相比，H-100 還具有令人難以置信的價值。它的總擁有成本降低了 3 倍，同時使用的服務器節點減少了 5 倍，能耗減少了 3.5 倍。

Earlier today, we announced a multiyear collaboration with Microsoft to build an advanced cloud-based AI supercomputer to help enterprises train, deploy and scale AI, including large state-of-the-art models. Microsoft Azure will incorporate our complete AI stack, adding tens and thousands of A100 and H-100 GPUs, Quantum-2 400 gigabit per second InfiniBand networking and the NVIDIA AI enterprise software suite to its platform. Oracle and NVIDIA are also working together to offer AI training and inference at scale to thousands of enterprises.

今天早些時候，我們宣布了與微軟的多年合作，以構建先進的基於雲的 AI 超級計算機，以幫助企業訓練、部署和擴展 AI，包括大型最先進的模型。 Microsoft Azure 將整合我們完整的 AI 堆棧，將數以萬計的 A100 和 H-100 GPU、Quantum-2 每秒 400 GB 的 InfiniBand 網絡和 NVIDIA AI 企業軟件套件添加到其平台。 Oracle 和 NVIDIA 還合作為數千家企業提供大規模的 AI 訓練和推理。

This includes bringing to Oracle Cloud infrastructure, the full NVIDIA accelerated computing stack and adding tens of thousands of NVIDIA GPUs, including the A100 and H-100. Cloud-based high-performance companies, [with scale] is adopting NVIDIA AI enterprise and other software to address the industrial scientific communities' rising demand for AI in the cloud.

這包括將完整的 NVIDIA 加速計算堆棧引入 Oracle 雲基礎架構，並添加數万個 NVIDIA GPU，包括 A100 和 H-100。基於雲的高性能公司，[具有規模] 正在採用 NVIDIA AI 企業和其他軟件來滿足工業科學界對雲中 AI 不斷增長的需求。

NVIDIA AI will bring new capability to rescale high-performance computing as a service offerings, which include simulation and engineering software used across industries. Networking posted strong growth driven by hyperscale customers and easing supply constraints. Our new Quantum-2 40 gigabit per second InfiniBand and Spectrum ethernet networking platforms are building momentum. We achieved an important milestone this quarter with VMware, whose leading server virtualization platform, vSphere, has been rearchitected over the last 2 years to run on DPUs and now supports our BlueField DPUs.

NVIDIA AI 將帶來重新擴展高性能計算即服務產品的新功能，其中包括跨行業使用的模擬和工程軟件。在超大規模客戶和緩解供應限制的推動下，網絡實現了強勁增長。我們新的 Quantum-2 每秒 40 Gb InfiniBand 和 Spectrum 以太網網絡平台正在蓄勢待發。本季度我們與 VMware 取得了一個重要的里程碑，其領先的服務器虛擬化平台 vSphere 在過去 2 年中經過重新設計以在 DPU 上運行，現在支持我們的 BlueField DPU。

Our joint enterprise AI platform is available first on Dell PowerEdge servers. The BlueField DPU design win pipeline is growing and the number of infrastructure software partners is expanding, including Arista, Checkpoint, Juniper, Palo Alto Networks and Red Hat.

我們的聯合企業 AI 平台首先在 Dell PowerEdge 服務器上可用。 BlueField DPU 設計獲勝管道正在增長，基礎設施軟件合作夥伴的數量也在不斷擴大，包括 Arista、Checkpoint、Juniper、Palo Alto Networks 和 Red Hat。

The latest top 500 list of supercomputers released this week at Supercomputing '22 and has the highest ever number of NVIDIA-powered systems, including 72% of the total and 90% of new systems on the list. Moreover, NVIDIA powers 23 of the top 30 of the Green 500 list, demonstrating the energy efficiency of accelerated computing. The #1 most energy-efficient system is the Flatiron Institute Henry, which is the first top 500 system featuring our H-100 GPUs. At GTC, we announced the NVIDIA Omniverse Computing System, or OVX, reference designs featuring the new L40 GPU based on the ADA Lovelace architecture. These systems are designed to build and operate 3D virtual world using NVIDIA Omniverse enterprise. NVIDIA OVX systems will be available from Inspur, Lenovo and Super Micro by early 2023. Lockheed Martin and Jaguar Land Rover will be among the first customers to receive OVX systems.

本週在 Supercomputing '22 上發布的最新超級計算機 500 強榜單中，搭載 NVIDIA 系統的系統數量創歷史新高，包括總數的 72% 和榜單中 90% 的新系統。此外，NVIDIA 為綠色 500 強榜單前 30 名中的 23 家提供支持，展示了加速計算的能效。排名第一的最節能係統是 Flatiron Institute Henry，它是第一個採用我們的 H-100 GPU 的 500 強系統。在 GTC 上，我們發布了 NVIDIA Omniverse Computing System (OVX) 參考設計，該參考設計採用基於 ADA Lovelace 架構的全新 L40 GPU。這些系統旨在使用 NVIDIA Omniverse Enterprise 構建和操作 3D 虛擬世界。到 2023 年初，浪潮、聯想和超微將提供 NVIDIA OVX 系統。洛克希德馬丁和捷豹路虎將成為首批接收 OVX 系統的客戶。

We are further expanding our AI software and services offerings with NVIDIA and BioNeMo large language model services, which are both entering early access this month. These enable developers to easily adopt large language models and deploy customized AI applications for content generation, tech summarization, chatbox, co-development, protein structure and biomolecular property predictions.

我們正在通過 NVIDIA 和 BioNeMo 大型語言模型服務進一步擴展我們的 AI 軟件和服務產品，這兩個服務都將於本月進入搶先體驗階段。這些使開發人員能夠輕鬆採用大型語言模型並部署定制的 AI 應用程序，用於內容生成、技術摘要、聊天框、共同開發、蛋白質結構和生物分子特性預測。

Moving to gaming. Revenue of $1.57 billion was down 23% sequentially and down 51% from a year ago, reflecting lower sell-in to partners to help align Channel inventory levels with current demand expectations. We believe channel inventories are on track to approach normal levels as we exit Q4.

轉向遊戲。收入 15.7 億美元，環比下降 23%，比一年前下降 51%，反映出對合作夥伴的銷售減少，以幫助使渠道庫存水平與當前需求預期保持一致。我們認為，隨著第四季度的結束，渠道庫存有望接近正常水平。

Sell-through for our gaming products was relatively solid in the Americas and EMEA but softer in Asia Pac as macroeconomic conditions and COVID lockdowns in China continued to weigh on consumer demand. Our new Ada Lovelace GPU architecture had an exceptional launch. The first ADA GPU, the GeForce RTX 4090 became available in mid-October and at a tremendous demand and positive feedback from the gaming community. We sold out quickly in many locations and are working hard to keep up with demand. The next member of the ADA family, RTX 4080 is available today.

我們遊戲產品的銷售在美洲和歐洲、中東和非洲地區相對穩定，但在亞太地區則較為疲軟，因為宏觀經濟狀況和中國的 COVID 封鎖繼續對消費者需求造成壓力。我們新的 Ada Lovelace GPU 架構的推出非常出色。第一款 ADA GPU，即 GeForce RTX 4090 於 10 月中旬上市，受到了遊戲社區的巨大需求和積極反饋。我們在許多地方很快就賣光了，並且正在努力跟上需求。 ADA 系列的下一個成員 RTX 4080 現已上市。

The RTX 4080 Series GPUs features DLSS 3, the neuro rendering technology that uses AI to generate entire frames for faster game play. Our third-generation RTX technology has raised the bar for computer graphics and help supercharge gaming.

RTX 4080 系列 GPU 採用 DLSS 3，這是一種使用 AI 生成整個幀以加快遊戲速度的神經渲染技術。我們的第三代 RTX 技術提高了計算機圖形的標準，有助於增強遊戲體驗。

For example, the 15-year old classic game, Portal, now reimagined with full ray tracing and DLSS 3 has made it on Steam's top 100 most wish-listed games. The total number of RTX games and applications now exceeds 350. There is tremendous energy in the gaming community that we believe will continue to fuel strong fundamentals over the long term. The number of simultaneous users on Steam just hit a record of 30 million, surpassing the prior peak of 28 million in January.

例如，擁有 15 年曆史的經典遊戲《傳送門》現在通過全光線追踪和 DLSS 3 進行了重新構想，已躋身 Steam 最受歡迎遊戲前 100 名。 RTX 遊戲和應用程序的總數現已超過 350。遊戲社區擁有巨大的能量，我們相信這將在長期內繼續推動強勁的基本面。 Steam 同時在線用戶數剛剛創下 3000 萬的紀錄，超過了 1 月份的 2800 萬的峰值。

Activision's Call of Duty: Modern Warfare 2 set a record for the franchise with more than $800 million in opening weekend sales, topping the combined box office openings of movie blockbusters, Top Gun Maverick and Doctor Strange in the Multiverse of Madness. And this month's League of Legends World Championship in San Francisco sold out minutes with 18,000 esports fans packed the arena where the Golden State Warriors play. We continue to expand the GeForce NOW cloud gaming service. In Q3, we added over 85 games to the library, bringing the total to over 1,400. We also launched GeForce NOW on the new gaming devices, including Logitech, CloudG, handheld, cloud gaming Chromebooks and Razr 5G Edge.

Activision 的使命召喚：現代戰爭 2 以超過 8 億美元的首映週末銷售額創下了特許經營權的紀錄，超過了電影大片《壯志凌雲》和《瘋狂多元宇宙》中的奇異博士的總票房。本月在舊金山舉行的英雄聯盟全球總決賽場均售罄，18,000 名電子競技迷擠滿了金州勇士隊比賽的場館。我們繼續擴展 GeForce NOW 雲遊戲服務。在第三季度，我們向庫中添加了超過 85 款遊戲，使總數超過 1,400 款。我們還在新遊戲設備上推出了 GeForce NOW，包括羅技、CloudG、掌上電腦、雲遊戲 Chromebook 和 Razr 5G Edge。

Moving to ProViz. Revenue of $200 million was down 60% sequentially and down 65% from a year ago, reflecting lower sell-in to partners to help align channel inventory levels with the current demand expectations. These dynamics are expected to continue in Q4.

搬到 ProViz。收入 2 億美元，環比下降 60%，比一年前下降 65%，反映出對合作夥伴的銷售減少，以幫助使渠道庫存水平與當前的需求預期保持一致。預計這些動態將在第四季度繼續。

Despite near-term challenges, we believe our long-term opportunity remains intact, fueled by AI simulation, computationally intensive design and engineering workloads. At GTC, we announced NVIDIA Omniverse Cloud Services, our first software and infrastructure-as-a-service offering, enabling artists, developers and enterprise teams to design, publish and operate metaverse applications from anywhere on any device.

儘管存在近期挑戰，但我們相信，在 AI 模擬、計算密集型設計和工程工作負載的推動下，我們的長期機遇依然存在。在 GTC 上，我們發布了 NVIDIA Omniverse 雲服務，這是我們的第一個軟件和基礎設施即服務產品，使藝術家、開發人員和企業團隊能夠在任何設備上的任何地方設計、發布和操作 metaverse 應用程序。

Omniverse Cloud Services runs on Omniverse cloud computer, a computing system comprised of NVIDIA OVX for graphics and physics simulation. NVIDIA HGX for AI workloads and the NVIDIA Graphics delivery network, a global scale, distributed data center network for delivering low-latency metaverse graphics on the edge. Leaders in some of the world's largest industries continue to adopt Omniverse. Home improvement retailer, Lowe's, is using it to help design, build and operate digital twins for their stores. Charter Communications, an advanced analytics company, heavy AI are creating Omniverse power digital twins to optimize Charter's wireless network.

Omniverse 雲服務運行在 Omniverse 雲計算機上，這是一個由 NVIDIA OVX 組成的計算系統，用於圖形和物理模擬。 NVIDIA HGX 用於 AI 工作負載和 NVIDIA Graphics 交付網絡，這是一個全球範圍的分佈式數據中心網絡，用於在邊緣交付低延遲元宇宙圖形。世界上一些最大行業的領導者繼續採用 Omniverse。家裝零售商 Lowe's 正在使用它來幫助設計、構建和運營其商店的數字雙胞胎。高級分析公司 Charter Communications 和 heavy AI 正在創建 Omniverse 強大的數字雙胞胎，以優化 Charter 的無線網絡。

And Deutsche Bahn, operator of German national railway is using Omniverse to create digital twins of its rail network and train AI models to monitor the network, increasing safety and reliability. Moving to automotive. Revenue of $251 million increased 14% sequentially and 86% from a year ago. Growth was driven by an increase in AI automotive solutions as our customers' DRIVE Orin-based production ramps continue to scale. Automotive has great momentum and is on its way to be our next multibillion-dollar platform. Volvo Cars unveiled the all-new flagship Volvo EX90 SUV powered by the NVIDIA Drive platform.

德國國家鐵路運營商 Deutsche Bahn 正在使用 Omniverse 創建其鐵路網絡的數字雙胞胎，並訓練 AI 模型來監控網絡，從而提高安全性和可靠性。轉向汽車。營收 2.51 億美元，環比增長 14%，同比增長 86%。隨著我們客戶基於 DRIVE Orin 的生產規模不斷擴大，AI 汽車解決方案的增加推動了增長。汽車行業發展勢頭強勁，正在成為我們下一個價值數十億美元的平台。沃爾沃汽車推出了搭載 NVIDIA Drive 平台的全新旗艦沃爾沃 EX90 SUV。

This is the first model to use Volvo's software-defined architecture with a centralized core computer containing both DRIVE Orin and DRIVE Xavier, along with 30 sensors. Other recently announced design wins and new model introductions include Hozon Auto, NIO, Polestar and EX90.

這是第一款使用沃爾沃軟件定義架構的車型，其中央核心計算機包含 DRIVE Orin 和 DRIVE Xavier，以及 30 個傳感器。最近宣布的其他設計勝利和新車型介紹包括 Hozon Auto、NIO、Polestar 和 EX90。

At GTC, we also announced that NVIDIA DRIVE Thor Superchip, the successor to Orin in our automotive SoC road map, DRIVE Thor delivers up to 2,000 TFLOPS of performance and leverages technologies introduced in our Grace Hopper and ADA architectures. It is capable of running both the automated drive and in-vehicle infotainment systems, simultaneously offering a leap in performance while reducing cost and energy consumption. DRIVE Thor will be available for automakers' 2025 models with Geely-owned automaker, ZEEKR, as the first announced customer.

在 GTC 上，我們還宣布 NVIDIA DRIVE Thor Superchip 是我們汽車 SoC 路線圖中 Orin 的繼任者，DRIVE Thor 提供高達 2,000 TFLOPS 的性能，並利用我們的 Grace Hopper 和 ADA 架構中引入的技術。它能夠運行自動駕駛和車載信息娛樂系統，同時提供性能飛躍，同時降低成本和能源消耗。 DRIVE Thor 將可用於汽車製造商的 2025 車型，吉利旗下的汽車製造商 ZEEKR 將作為第一個宣布的客戶。

Moving to the rest of the P&L. GAAP gross margin was 53.6% and non-GAAP gross margin was 56.1%. Gross margins reflect $702 million in inventory charges largely related to lower data center demand in China, partially offset by a warranty benefit of approximately $70 million. Year-on-year, GAAP operating expenses were up 31%. And non-GAAP operating expenses were up 30%, primarily due to higher compensation expenses related to headcount growth and salary increases and higher data center infrastructure expenses.

轉到損益表的其餘部分。 GAAP 毛利率為 53.6%，非 GAAP 毛利率為 56.1%。毛利率反映了 7.02 億美元的庫存費用，這主要與中國數據中心需求下降有關，部分被大約 7000 萬美元的保修收益所抵消。與去年同期相比，GAAP 運營費用增長了 31%。非 GAAP 運營費用增長了 30%，這主要是由於與員工人數增長和工資增長相關的薪酬費用增加以及數據中心基礎設施費用增加。

Sequentially, both GAAP and non-GAAP operating expense growth was in the single-digit percent, and we plan to keep it relatively flat at these levels over the coming quarters. We returned $3.75 billion to shareholders in the form of share repurchases and cash dividends. At the end of Q3, we had approximately $8.3 billion remaining under our share repurchase authorization through December '23.

連續地，GAAP 和非 GAAP 運營費用增長均為個位數百分比，我們計劃在未來幾個季度將其保持在這些水平上相對平穩。我們以股票回購和現金股息的形式向股東返還了 37.5 億美元。在第三季度末，截至 2023 年 12 月，我們的股票回購授權剩餘約 83 億美元。

Let me turn to the outlook for the fourth quarter of fiscal 2023. We expect our data center revenue to reflect early production shipments of the H-100, offset by continued softness in China. In gaming, we expect to resume sequential growth with our revenue still below end demand as we continue to work through the channel inventory correction. And in automotive, we expect the continued ramp of our Orin design wins.

讓我談談 2023 財年第四季度的展望。我們預計我們的數據中心收入將反映 H-100 的早期生產出貨量，但被中國的持續疲軟所抵消。在遊戲方面，隨著我們繼續努力調整渠道庫存，我們預計將恢復連續增長，但我們的收入仍低於最終需求。在汽車領域，我們預計我們的 Orin 設計會繼續取得成功。

All in, we expect modest sequential growth driven by automotive, gaming and data center. Revenue is expected to be $6 billion, plus or minus 2%. GAAP and non-GAAP gross margins are expected to be 63.2% and 66%, respectively, plus or minus 50 basis points. GAAP operating expenses are expected to be approximately $2.56 billion. Non-GAAP operating expenses are expected to be approximately $1.78 billion. GAAP and non-GAAP other income and expenses are expected to be an income of approximately $40 million, excluding gains and losses on nonaffiliated investments.

總而言之，我們預計汽車、遊戲和數據中心將推動適度的連續增長。收入預計為 60 億美元，上下浮動 2%。 GAAP 和非 GAAP 毛利率預計分別為 63.2% 和 66%，上下浮動 50 個基點。 GAAP 運營費用預計約為 25.6 億美元。非 GAAP 運營費用預計約為 17.8 億美元。 GAAP 和非 GAAP 其他收入和支出預計收入約為 4000 萬美元，不包括非附屬投資的收益和損失。

GAAP and non-GAAP tax rates are expected to be 9%, plus or minus 1%, excluding any discrete items. Capital expenditures are expected to be approximately $500 million to $550 million. Further, financial details are included in the CFO commentary and other information available on our IR website. In closing, let me highlight upcoming events for the financial community. We'll be attending the Credit Suisse conference in Phoenix on November 30; the Arete Virtual Tech Conference on December 5 and the JPMorgan Forum on January 5 in Las Vegas. Our earnings call to discuss the results of our fourth quarter and fiscal 2023 are scheduled for Wednesday, February 22. We will now open the call for questions. Operator, could you please poll for questions?

GAAP 和非 GAAP 稅率預計為 9%，正負 1%，不包括任何離散項目。資本支出預計約為 5 億至 5.5 億美元。此外，財務細節包含在首席財務官的評論中以及我們 IR 網站上提供的其他信息中。最後，讓我強調一下金融界即將發生的事件。我們將參加 11 月 30 日在鳳凰城舉行的瑞士信貸會議； 12 月 5 日的 Arete 虛擬技術會議和 1 月 5 日在拉斯維加斯舉行的摩根大通論壇。我們討論第四季度和 2023 財年業績的財報電話會議定於 2 月 22 日星期三舉行。我們現在將開始提問。接線員，可以請你投票提問嗎？

(Operator Instructions) Your first question comes from the line of Vivek Arya with Bank of America Securities.

（操作員說明）您的第一個問題來自美國銀行證券公司的 Vivek Arya。

Colette, just wanted to clarify first, I think last quarter, you gave us a sell-through rate for your gaming business at about $2.5 billion a quarter. I think you said China is somewhat weaker. So I was hoping you could update us on what that sell-through rate is right now for gaming.

科萊特，首先想澄清一下，我認為上個季度，你給我們的遊戲業務銷售率約為每季度 25 億美元。我想你說中國比較弱。所以我希望你能告訴我們目前遊戲的銷售率是多少。

And then Jensen, a question for you. A lot of concerns about large hyperscalers cutting their spending and pointing to a slowdown. So if, let's say, U.S. cloud CapEx is flat or slightly down next year, do you think your business can still grow in the data center and why?

然後 Jensen，有一個問題要問你。很多人擔心大型超大規模企業會削減開支並指出經濟放緩。因此，假設明年美國雲資本支出持平或略有下降，您認為您的業務在數據中心仍然可以增長嗎？為什麼？

Yes. Thanks for the question. Let me first start with the sell-through on our gaming business. We had indicated, if you put 2 quarters together, we would see approximately $5 billion in normalized sell-through for our business. Now during the quarter, sell-through in Q3 was relatively solid. We've indicated that although China lockdowns continue to channel -- excuse me, challenge our overall China business, it was still relatively solid. Notebook sell-through was also quite solid. And desktop, a bit softer, particularly in that China and Asia areas. We expect, though, stronger end demand, though, as we enter into Q4, driven by the upcoming holidays as well as the continuation of the ADA adoption.

是的。謝謝你的問題。讓我首先從我們遊戲業務的銷售情況開始。我們曾表示，如果將兩個季度放在一起，我們將看到我們業務的標準化銷售量約為 50 億美元。現在在本季度，第三季度的銷售量相對穩定。我們已經表示，儘管中國的封鎖繼續進行——對不起，挑戰我們的整體中國業務，但它仍然相對穩固。筆記本電腦的銷售量也相當可觀。和桌面，有點軟，特別是在中國和亞洲地區。不過，我們預計，隨著我們進入第四季度，受即將到來的假期以及 ADA 的持續採用的推動，終端需求將更加強勁。

Vivek, our data center business is indexed to 2 fundamental dynamics. The first has to do with general purpose computing no longer scaling. And so acceleration is necessary to achieve the necessary level of cost efficiency scale and energy efficiency scale so that we can continue to increase workloads while saving money and saving power. Accelerated computing is recognized generally as the path forward as general purpose computing slows.

Vivek，我們的數據中心業務與 2 個基本動態相關。第一個與不再擴展的通用計算有關。因此，加速是實現必要水平的成本效率規模和能源效率規模的必要條件，這樣我們就可以在省錢省電的同時繼續增加工作量。隨著通用計算變慢，加速計算通常被認為是前進的道路。

The second dynamic is AI. And we're seeing surging demand in some very important sectors of AIs, in important breakthroughs in AI. One is called deep recommender systems, which is quite essential now to the best content or item or product to recommend to somebody who's using a device that is like a cellphone or interacting with a computer just using voice. You need to really understand the nature, the context of the person making the request and make the appropriate recommendation to them.

第二個動力是人工智能。我們看到在人工智能的一些非常重要的領域，在人工智能的重要突破中，需求激增。一個叫做深度推薦系統，這對於向使用手機之類的設備或僅使用語音與計算機交互的人推薦最好的內容、項目或產品來說是非常重要的。您需要真正了解提出請求的人的性質和背景，並向他們提出適當的建議。

The second has to do with large language models. This is -- this started several years ago with the invention of the transformer, which led to BERT, which led to GPT-3, which led to a whole bunch of other models now associated with that. We now have the ability to learn representations of languages of all kinds. It could be human language. It could be the language of biology. It could be the language of chemistry. And recently, I just saw a breakthrough called [Genes LM,] which is just one of the first example of learning the language of human genomes.

第二個與大型語言模型有關。這是 - 這始於幾年前變壓器的發明，它導致了 BERT，導致了 GPT-3，這導致了現在與之相關的一大堆其他模型。我們現在有能力學習各種語言的表徵。它可能是人類語言。它可能是生物學的語言。它可能是化學語言。最近，我剛剛看到一個名為 [Genes LM] 的突破，它只是學習人類基因組語言的第一個例子。

The third has to do with generative AI. You know that the first 10 years, we've dedicated ourselves to perception AI. But the goal of perception, of course, is to understand context. But the ultimate goal of AI is to make a contribution to create something to generate product. And this is now the beginning of the era of generative AI. You probably see it all over the place, whether they're generating images or generating videos or generating text of all kinds and the ability to augment our performance to enhance our performance to make productivity enhanced to reduce cost and improve whatever we do with whatever we have to work with. Productivity is really more important than ever.

第三個與生成人工智能有關。你知道，前 10 年，我們一直致力於感知 AI。但感知的目標當然是理解上下文。但人工智能的最終目標是做出貢獻，創造一些東西來產生產品。現在是生成人工智能時代的開始。你可能到處都看到它，無論是生成圖像、生成視頻還是生成各種文本，以及增強我們的性能以提高我們的性能以提高生產力以降低成本並改進我們所做的一切的能力。必須一起工作。生產力確實比以往任何時候都重要。

And so you could see that our company is indexed to 2 things, both of which are more important than ever, which is power efficiency, cost efficiency and then, of course, productivity. And these things are more important than ever. And my expectation is that we're seeing all the strong demand and surging demand for AI and for these reasons.

所以你可以看到我們公司有兩件事，這兩件事比以往任何時候都更重要，那就是能源效率、成本效率，當然還有生產力。這些事情比以往任何時候都更重要。我的期望是，出於這些原因，我們會看到對人工智能的所有強勁需求和激增需求。

Your next question comes from the line of C.J. Muse with Evercore.

你的下一個問題來自 C.J. Muse with Evercore。

You started to bundle NVIDIA enterprise now with the H-100. I'm curious if you can talk about how we should think about timing around software monetization. And how we should kind of see this flow through the model, particularly with the focus on the AI enterprise and Omniverse side of things.

您現在開始將 NVIDIA 企業版與 H-100 捆綁在一起。我很好奇你能否談談我們應該如何考慮軟件貨幣化的時機。以及我們應該如何通過模型來看待這種流動，特別是關注 AI 企業和事物的 Omniverse 方面。

Yes. Thanks, CJ. We're making excellent progress in NVIDIA AI enterprise. In fact, you saw probably that we made several announcements this quarter associated with clouds. You know that NVIDIA has a rich ecosystem. And over the years, our rich ecosystem and our software stack has been integrated into developers and startups of all kinds. But more so -- more than ever, we're at the tipping point of clouds, and that's fantastic. Because if we could get NVIDIA's architecture and our full stack into every single cloud, we could reach more customers more quickly.

是的。謝謝，希傑。我們在 NVIDIA AI 企業方面取得了長足的進步。事實上，您可能已經看到我們在本季度發布了多項與雲相關的公告。你知道 NVIDIA 擁有豐富的生態系統。多年來，我們豐富的生態系統和我們的軟件堆棧已融入各種開發人員和初創公司。但更重要的是——我們比以往任何時候都更處於雲層的臨界點，這太棒了。因為如果我們能夠將 NVIDIA 的架構和我們的完整堆棧應用到每一個雲中，我們就可以更快地接觸到更多的客戶。

And this quarter, we announced several initiatives, one has -- several partnerships and collaborations, one that we announced today, which has to do with Microsoft and our partnership there. It has everything to do with scaling up AI because we have so many start-ups clamoring for large installations of our GPU so that they could do large language model training and building their startups and scale out of AI to enterprise and all of the world's Internet service providers.

本季度，我們宣布了幾項舉措，其中一項是 - 多項合作夥伴關係和合作，我們今天宣布的一項與微軟和我們在那裡的合作夥伴關係有關。它與擴大 AI 密切相關，因為我們有如此多的初創企業要求大量安裝我們的 GPU，以便他們可以進行大型語言模型培訓並建立他們的初創企業，並將 AI 擴展到企業和全世界的互聯網服務供應商。

Every company we're talking to would like to have the agility and the scale, flexibility of clouds. And so over the last year or so, we've been working on moving all of our software stacks to the cloud, all of our platform and software stacks to the cloud. And so today, we announced that Microsoft and ourselves are going to standardize on the NVIDIA stack, for a very large part of the work that we're doing together so that we could take a full stack out to the world's enterprise. That's all software included.

我們正在與之交談的每家公司都希望擁有云的敏捷性和規模、靈活性。因此，在過去一年左右的時間裡，我們一直致力於將我們所有的軟件堆棧遷移到雲端，我們所有的平台和軟件堆棧都遷移到雲端。所以今天，我們宣布微軟和我們自己將在 NVIDIA 堆棧上進行標準化，這是我們共同開展的大部分工作，以便我們可以將完整的堆棧應用於全球企業。這就是包括的所有軟件。

We, a month ago, announced the same similar type of partnership with Oracle. You also saw that rescale, a leader in high-performance computing cloud has integrated NVIDIA AI into their stack. MONAI has been integrated into GCP. And we announced recently NeMo, large language model, and BioNeMo, large language model, to put NVIDIA software in the cloud. And we also announced Omniverse is now available in the cloud. The goal of all of this is to move the NVIDIA platform full stacks to the cloud so that we can engage customers much, much more quickly and customers could engage our software if they would like to use it in the cloud. It's per GPU instance hour if they would like to utilize our software on-prem, they could do it through software license, and so license and subscription. And so in both cases, we now have software available practically everywhere you would like to engage it.

一個月前，我們宣布與 Oracle 建立同樣類型的合作夥伴關係。您還看到高性能計算雲領域的領導者 rescale 已將 NVIDIA AI 集成到他們的堆棧中。 MONAI 已集成到 GCP 中。我們最近宣布了大型語言模型 NeMo 和大型語言模型 BioNeMo，將 NVIDIA 軟件置於雲端。我們還宣布 Omniverse 現在可在雲端使用。所有這一切的目標是將 NVIDIA 平台全棧遷移到雲端，這樣我們就可以更快地吸引客戶，如果客戶願意在雲端使用我們的軟件，他們也可以使用我們的軟件。如果他們想在本地使用我們的軟件，則按 GPU 實例小時計算，他們可以通過軟件許可來實現，因此許可和訂閱。因此，在這兩種情況下，我們現在幾乎可以在任何您想使用的地方使用軟件。

The partners that we work with are super excited about it because NVIDIA's rich ecosystem is global. And this could bring both new consumption into their cloud for both them and ourselves, but also connect all of these new opportunities to the other APIs and other services that they offer. And so our software stack is making really great progress.

與我們合作的合作夥伴對此非常興奮，因為 NVIDIA 豐富的生態系統是全球性的。這可以為他們和我們自己帶來新的消費到他們的雲中，而且還將所有這些新機會連接到他們提供的其他 API 和其他服務。因此，我們的軟件堆棧正在取得巨大進步。

Your next question comes from the line of Chris Caso with Credit Suisse.

你的下一個問題來自瑞士信貸的 Chris Caso。

Wonder if you could give some more color about the inventory charges you took in the quarter and then internal inventory in general. In the documentation, you talked about that being a portion of inventory on hand plus some purchase obligations. And you also spoke in your prepared remarks that some of this was due to China data centers. So if you can clarify what was in those charges. And then in general, for your internal inventory, does that still need to be worked down? And what are the implications if that needs to be worked down over the next couple of quarters?

想知道您是否可以更多地說明本季度的庫存費用以及一般的內部庫存。在文檔中，您談到這是手頭庫存的一部分加上一些採購義務。你還在準備好的發言中說，其中一些是由於中國數據中心造成的。所以，如果你能澄清這些指控中的內容。然後一般來說，對於您的內部庫存，是否還需要進行處理？如果需要在接下來的幾個季度內解決這個問題，會有什麼影響？

Thanks for the question, Chris. So as we highlighted in our prepared remarks, we booked an entry of $702 million for inventory reserves within the quarter. Most of that, primarily, all of it is related to our data center business, just due to the change in expected demand looking forward for China. So when we look at the data center products, a good portion of this was also the A100, which we wrote down.

謝謝你的問題，克里斯。因此，正如我們在準備好的評論中強調的那樣，我們在本季度內為庫存儲備登記了 7.02 億美元。其中大部分，主要是所有這些都與我們的數據中心業務有關，只是由於對中國的預期需求發生變化。因此，當我們查看數據中心產品時，其中很大一部分也是我們記下的 A100。

Now looking at our inventory that we have on hand and the inventory that has increased, a lot of that is just due to our upcoming architectures coming to market, our ADA architecture, our Hopper architecture and even more in terms of our networking business. We have been building for those architectures to come to market and which you see.

現在看看我們手頭的庫存和增加的庫存，其中很多只是由於我們即將上市的架構，我們的 ADA 架構，我們的 Hopper 架構，甚至更多是因為我們的網絡業務。我們一直在構建這些架構以推向市場以及您所看到的。

We are always looking at our inventory levels at the end of each quarter for our expected demand going forward. But I think we've done a solid job, at least in this quarter, just based on that expectation going forward.

我們總是在每個季度末查看我們的庫存水平，以了解我們未來的預期需求。但我認為我們做得很好，至少在本季度，只是基於對未來的預期。

Your next question comes from the line of Timothy Arcuri with UBS.

你的下一個問題來自瑞銀集團的蒂莫西·阿庫裡 (Timothy Arcuri)。

Colette, can you -- I have a 2-part question. First, is there any effect of stockpiling in the data center guidance? I ask because you now have the A800 that is sort of a modified version of the A100 with the lower data transfer rate. So one could imagine that customers might be stocking that while they can still get it. And I guess the second part of that is related to the inventory charge.

Colette，你能-- 我有一個由兩部分組成的問題。第一，數據中心指引中的囤貨有沒有影響？我問是因為您現在擁有的 A800 是 A100 的改良版，具有較低的數據傳輸速率。因此，人們可以想像，客戶可能會在仍然可以買到的時候囤積這些東西。我猜第二部分與庫存費用有關。

Can you just go into that a little bit more? Because last quarter, it made sense that you took a charge because revenue was less than you thought, but revenue came in pretty much in line. And it sounded like China was a net neutral. So is the charge related to just working A100 inventory down faster? Is that what the charges relate to?

你能再深入一點嗎？因為上個季度，你收取費用是有道理的，因為收入比你想像的要少，但收入幾乎符合預期。聽起來中國是網絡中立的。那麼收費是否與 A100 庫存下降得更快有關？指控與此有關嗎？

Sure. So let me talk about the first statement that you indicated. Most of our data center business that we see is we're working with customers specifically on their needs to build out accelerated computing and AI. It's just not a business in terms of where units are being held for that. They're usually for very, very specific products and projects that we see. So I'm going to answer no. Nothing that we can see.

當然。那麼讓我談談你指出的第一個聲明。我們看到的大部分數據中心業務都是與客戶合作，專門滿足他們構建加速計算和人工智能的需求。就為此持有單位而言，這不是一項業務。它們通常用於我們看到的非常非常具體的產品和項目。所以我要回答不。我們看不到任何東西。

Your second question regarding the inventory provisions. At the end of last quarter, we were beginning to see softness in China. We've always been looking at our needs long term. It's not a statement about the current quarter in inventory, as you can see. It usually takes 2 or 3 quarters for us to build product for the future demand. So that's always a case of the inventory that we are ordering. So now looking at what we've seen in terms of continued lockdowns, continued economy challenges in China, it was time for us to take a hard look at what do we think we'll need for data center going forward and not led to a write-down.

你關於庫存規定的第二個問題。上個季度末，我們開始看到中國經濟疲軟。我們一直在關注我們的長期需求。如您所見，這不是關於當前季度庫存的聲明。我們通常需要 2 或 3 個季度來為未來需求構建產品。所以這始終是我們訂購的庫存的情況。因此，現在看看我們在中國持續的封鎖、持續的經濟挑戰方面所看到的情況，是時候認真審視我們認為數據中心向前發展需要什麼，而不是導致減記。

Your next question comes from the line of Stacy Rasgon with Bernstein.

你的下一個問題來自 Stacy Rasgon 與 Bernstein 的對話。

Colette, I had a question on the commentary you gave on the sequentials. It kind of sounded like data center maybe had some China softness issues. You said gaming resumed sequential growth. But then you said sequential growth for the company driven by auto gaming and data center.

科萊特，我對你對連續劇的評論有疑問。聽起來數據中心可能有一些中國軟性問題。你說遊戲恢復連續增長。但後來你說公司的連續增長是由汽車遊戲和數據中心驅動的。

How can all 3 of those grow sequentially if the overall guidance is kind of flattish? Are they all just like growing just a little bit? Or is one of them actually down? Like how do we think about the segments into Q4 given that commentary?

如果整體指導有點持平，這三者怎麼能依次增長呢？他們都只是喜歡成長一點點嗎？還是其中之一實際上已關閉？鑑於該評論，我們如何看待進入第四季度的細分市場？

Yes. So your question is regarding the sequentials from Q3 to our guidance that we provided for Q4. As we are seeing the numbers in terms of our guidance, you're correct, is only growing about $100 million. And we've indicated that 3 of those platforms will likely grow just a little bit. But our Pro Visualization business we think is going to be flattish and likely not growing as we're still working on correcting the channel inventory levels to get to the right amount. It's very difficult to say which will have that increase. But again, we are planning for all 3 of those different market platforms to grow just a little bit.

是的。所以你的問題是關於從第三季度到我們為第四季度提供的指導的順序。正如我們在指導方面看到的數字，你是對的，只增長了大約 1 億美元。我們已經指出，其中 3 個平台可能會略有增長。但我們認為我們的 Pro Visualization 業務將持平並且可能不會增長，因為我們仍在努力糾正渠道庫存水平以達到正確的數量。很難說哪個會增加。但同樣，我們計劃讓所有 3 個不同的市場平台都增長一點點。

Your next question comes from the line of Mark Lipacis with Jefferies.

你的下一個問題來自 Mark Lipacis 與 Jefferies 的合作。

Jensen, I think for you. You've articulated a vision for the data center, where a solution -- with an integrated solution set of a CPU, GPU and DPU is deployed for all workloads or most workloads, I think. Could you just give us a sense of or talk about where is this vision in the penetration cycle? And maybe talk about Grace's importance for realizing that vision. What will Grace deliver versus an off-the-shelf x86 where -- do you have a sense of whether Grace will get embraced first or the fastest within that vision?

詹森，我為你著想。你已經闡明了數據中心的願景，我認為，其中一個解決方案 - 為所有工作負載或大多數工作負載部署了 CPU、GPU 和 DPU 的集成解決方案集。您能否讓我們了解一下或談談這種願景在滲透週期中的位置？或許可以談談 Grace 對於實現這一願景的重要性。與現成的 x86 相比，Grace 將交付什麼——您是否知道 Grace 將首先被接受還是在該願景中最快被接受？

Grace's data moving capability is off the charts. Grace also is memory coherent to our GPU, which allows our GPU to expand its effective GPU memory, fast GPU memory by a factor of 10. That's not possible without special capabilities that are designed between Hopper and Grace and the architecture of Grace. And so it was designed, Grace is designed for very large data processing at very high speeds. Those applications are related to, for example, data processing is related for recommender systems, which operates on petabytes of live data at a time.

Grace 的數據移動能力出類拔萃。 Grace 還與我們的 GPU 保持內存一致，這允許我們的 GPU 將其有效 GPU 內存、快速 GPU 內存擴展 10 倍。如果沒有在 Hopper 和 Grace 以及 Grace 架構之間設計的特殊功能，這是不可能的。 Grace 就是這樣設計的，專為以非常高的速度處理非常大的數據而設計。例如，這些應用程序與推薦系統相關的數據處理相關，推薦系統一次處理數 PB 的實時數據。

It's all hot. It all needs to be fast, so that you can make a recommendation within milliseconds to hundreds of millions of people using the service. It is also quite effective at AI training, Machine Learning. And so those kind of applications are really terrific. We -- Grace, I think I've said before that we will have production samples in Q1, and we're still on track to do that.

都是熱的。這一切都需要快速，以便您可以在幾毫秒內向使用該服務的數億人提出建議。它在人工智能訓練、機器學習方面也非常有效。所以這些應用程序真的很棒。我們 - 格蕾絲，我想我之前說過我們將在第一季度提供生產樣品，而且我們仍在按計劃進行。

Your next question comes from the line of Harlan Sur with JPMorgan.

你的下一個問題來自摩根大通的 Harlan Sur。

Your data center networking business, I believe, is driving about $800 million per quarter in sales, very, very strong growth over the past few years. Near term, as you guys pointed out, and the team is driving strong NIC and Bluetooth attached to your own compute solutions like DGX and more partner announcements like VMware, but we also know that networking has pretty large exposure to general purpose cloud and hyperscale compute spending trends. So what's the visibility and growth outlook for the networking business over the next few quarters?

我相信，您的數據中心網絡業務每季度的銷售額約為 8 億美元，在過去幾年中增長非常非常強勁。近期，正如你們指出的那樣，團隊正在推動強大的 NIC 和藍牙連接到您自己的計算解決方案（如 DGX）和更多合作夥伴公告（如 VMware），但我們也知道網絡對通用雲和超大規模計算有很大的影響消費趨勢。那麼未來幾個季度網絡業務的知名度和增長前景如何？

Yes. If I could take that. First, thanks for your question. Our networking, as you know, is heavily indexed to high-performance computing. We're not -- we don't serve the vast majority of commodity networking. All of our network solutions are very high end, and they're designed for data centers that move a lot of data.

是的。如果我能接受的話。首先，感謝您的提問。如您所知，我們的網絡與高性能計算密切相關。我們不是——我們不為絕大多數商品網絡提供服務。我們所有的網絡解決方案都非常高端，專為傳輸大量數據的數據中心而設計。

Now if you have a hyperscale data center these days, and you are deploying a large number of AI applications, it is very likely that the network bandwidth that you provision has a substantial implication on the overall throughput of your data center. So the small incremental investment they make in high-performance networking translates to billions of dollars of savings frankly, in provisioning the service or billions of dollars more throughput, which increases their economics.

現在，如果您現在擁有超大規模數據中心，並且正在部署大量 AI 應用程序，那麼您提供的網絡帶寬很可能會對數據中心的整體吞吐量產生重大影響。因此，坦率地說，他們在高性能網絡方面所做的小額增量投資轉化為數十億美元的節省，用於提供服務或數十億美元的更多吞吐量，從而增加了他們的經濟效益。

And so these days, with disaggregated and AI application, AI provisioning and data centers, high-performance networking is really quite fantastic and it pays for itself right away. But that's where we are focused, in high-performance networking and provisioning AI services in -- well, the AI applications that we focus on. You might have noticed that NVIDIA and Microsoft are building one of the largest AI infrastructures in the world. And it is completely powered by NVIDIA's InfiniBand 400 gigabits per second network. And the reason for that is because that network pays for itself instantaneously.

因此，如今，隨著分解和 AI 應用程序、AI 供應和數據中心的出現，高性能網絡真的非常棒，它會立即收回成本。但這正是我們關注的重點，在高性能網絡和提供人工智能服務方面——好吧，我們關注的人工智能應用程序。您可能已經註意到 NVIDIA 和 Microsoft 正在構建世界上最大的 AI 基礎設施之一。它完全由 NVIDIA 的 InfiniBand 每秒 400 吉比特的網絡提供支持。這樣做的原因是因為該網絡會立即收回成本。

The investment that you're going to put into the infrastructure is so significant that if you were to be dragged by slow networks, obviously, the efficiency of the overall infrastructure is not as high. And so in the places where we focus, networking is really quite important. It goes all the way back to when we first announced the acquisition of Mellanox. I think at the time, they were doing about a few hundred million dollars a quarter, about $400 million a quarter. And now we're doing what they used to do in the old days, in a year, practically coming up in a quarter. And so that kind of tells you about the growth of high-performance networking. It is an indexed to overall enterprise and data center spend but it is highly indexed to AI adoption.

你要投入基礎設施的投資是如此巨大，如果你被慢速網絡拖累，顯然，整體基礎設施的效率不會那麼高。因此，在我們關注的地方，網絡真的非常重要。這可以追溯到我們首次宣布收購 Mellanox 時。我想當時，他們每個季度大約做幾億美元，大約一個季度 4 億美元。現在我們正在做他們過去在一年內做的事情，實際上是在一個季度內完成。因此，這可以告訴您高性能網絡的發展。它與企業和數據中心的總體支出掛鉤，但與人工智能的採用高度掛鉤。

Your next question comes from the line of Aaron Rakers with Wells Fargo.

你的下一個問題來自 Aaron Rakers 與 Wells Fargo 的合作。

I want to expand on the networking question a little bit further. When we look at the Microsoft announcement today, we think about what Meta is doing on the AI footprint that they're deploying. Jensen, can you help us understand like where your InfiniBand networking sits relative to like traditional data center switching? And maybe kind of build on that, how you're positioning Spectrum for in the market, does that compete against a broader set of opportunities in the Ethernet world for AI fabric networking?

我想進一步擴展網絡問題。當我們今天看到微軟的公告時，我們會想到 Meta 在他們正在部署的 AI 足跡上做了什麼。 Jensen，你能幫助我們了解你的 InfiniBand 網絡相對於傳統數據中心交換的位置嗎？也許在此基礎上，你如何在市場上定位 Spectrum，這是否會與以太網世界中更廣泛的 AI 結構網絡機會競爭？

Yes. Thanks, Aaron. The math is like this. If you're going to spend $20 billion on an infrastructure and the efficiency of that overall data center is improved by 10%, the numbers are huge. And when we do these large language models and recommender systems, the processing is done across the entire data center. And so we distribute the workload across multiple GPUs, multiple nodes and it runs for a very long time. And so the importance of the network can be over-emphasized.

是的。謝謝，亞倫。數學是這樣的。如果您打算在基礎設施上花費 200 億美元，並且整個數據中心的效率提高 10%，那麼這個數字是巨大的。當我們做這些大型語言模型和推薦系統時，處理是在整個數據中心完成的。因此，我們將工作負載分佈在多個 GPU、多個節點上，並且它會運行很長時間。因此，可以過分強調網絡的重要性。

And so the difference of 10% in overall improvement in efficiency, which is very easy to achieve. The difference between NVIDIA's InfiniBand, the entire software stack with what we call Magnum IO, which allows us to do computing in the network itself. A lot of software is running in the network itself, not just moving data around. We call it in-network computing because a ton of software is done at the edge of the -- within the network itself.

因此，10% 的整體效率提升差異非常容易實現。 NVIDIA InfiniBand 與我們稱之為 Magnum IO 的整個軟件堆棧之間的區別，它允許我們在網絡本身中進行計算。許多軟件在網絡本身中運行，而不僅僅是移動數據。我們稱之為網絡內計算，因為大量軟件是在網絡本身的邊緣完成的。

We achieved significant differences in overall efficiency. And so if you're spending billions of dollars on the infrastructure, or even hundreds of millions of dollars on the infrastructure, the difference is really quite profound.

我們在整體效率上取得了顯著差異。因此，如果您在基礎設施上花費數十億美元，甚至數億美元，那麼差異就非常大了。

Your next question comes from the line of Ambrish Srivastava with BMO.

您的下一個問題來自 BMO 的 Ambrish Srivastava 系列。

I actually had a couple of clarifications. Colette, in the data center side, is it a fair assumption that compute was down Q-over-Q in the reported quarter because the quarter before, Mellanox or the networking business was up as it was called out? And again, you said it grew quarter-over-quarter. So is that a fair assumption? And then I had a clarification on the USG ban. Initially, it was supposed to be a $400 million, really going to what the government was trying to firewall. Is the A800 -- I'm just trying to make sure I understand it. Isn't that against the spirit of what the government is trying to do, i.e., firewall, high-performance compute? Or is A800 going to a different set of customers?

我實際上有幾個澄清。 Colette，在數據中心方面，是否可以公平地假設報告季度的計算量環比下降，因為前一個季度，Mellanox 或網絡業務在被調用時處於上升狀態？再一次，你說它環比增長。那麼這是一個公平的假設嗎？然後我對 USG 禁令進行了澄清。最初，它應該是 4 億美元，真正用於政府試圖阻止的事情。是 A800——我只是想確保我理解它。這不是違背了政府正在努力做的事情的精神，即防火牆、高性能計算嗎？還是 A800 將面向不同的客戶群？

Thank you for the question. So looking at our compute for the quarter is about flattish. Yes, we're seeing also growth in terms of our networking. But you should look at our Q3, compute is about flattish with last quarter.

感謝你的提問。因此，看看我們本季度的計算結果是持平的。是的，我們也看到了網絡方面的增長。但是你應該看看我們的第三季度，計算與上一季度持平。

Ambrish, A800, the hardware of A800 ensures that it always meets U.S. government's clear test for export control. And it cannot be customer reprogrammed or application reprogrammed to exceed it. It is hardware limited. It is in the hardware that determines A800's capabilities. And so it meets the clear test in letter and in spirit. We raised the concern about the $400 million of A100s because we were uncertain about whether we could execute the introduction of A800 to our customers and through our supply chain in time.

Ambrish，A800，A800的硬件確保它始終滿足美國政府對出口管制的明確測試。並且不能通過客戶重新編程或應用程序重新編程來超過它。它受硬件限制。硬件決定了 A800 的功能。因此，它在文字和精神上都經受了明確的考驗。我們對價值 4 億美元的 A100 提出了擔憂，因為我們不確定是否可以及時向我們的客戶並通過我們的供應鏈推出 A800。

The company did remarkable feeds to swarm this situation and make sure that our business was not affected and our customers were not affected. But A800 hardware surely ensures that it always meets U.S. government's clear tests for export control.

公司做了出色的反饋來應對這種情況，確保我們的業務不受影響，我們的客戶不受影響。但 A800 的硬件肯定能確保它始終滿足美國政府對出口管制的明確測試。

Your next question comes from the line of William Stein with Truist Securities.

你的下一個問題來自 Truist Securities 的 William Stein。

I'm hoping you can discuss the pace of H-100 growth as we progress over the next year. We've gotten a lot of questions as to whether the ramp in this product should look like a sort of traditional product cycle where there's quite a bit of pent-up demand for this significant improved performance product and that there's supply available as well. So does this rollout sort of look relatively typical from that perspective? Or should we expect a more, perhaps, delayed start of the growth trajectory where we see maybe substantially more growth in, let's say, second half of '23?

我希望你能討論 H-100 的增長速度，因為我們明年會取得進展。我們收到了很多關於該產品的增長是否應該看起來像一種傳統產品週期的問題，在這種週期中，對這種性能顯著提高的產品有相當多的被壓抑的需求，而且也有供應。那麼從這個角度來看，這種推出看起來相對典型嗎？或者我們是否應該期望增長軌蹟的開始時間可能會更晚一些，比方說，23 年下半年我們可能會看到更多的增長？

H-100 ramp is different than the A100 ramp in several ways. The first is that the TCO, the cost benefits, the operational cost benefits because of the energy savings because every data center is now power limited, and because of this incredible transformer engine that's designed for the latest AI models. The performance over Ampere is so significant that I -- and because of the pent-up demand for Hopper because of these new models that are -- that I spoke about earlier, deep recommender systems and large language models and generative AI models.

H-100 斜坡在幾個方面不同於 A100 斜坡。首先是 TCO、成本收益、運營成本收益，因為每個數據中心現在都受到功率限制，因此節省了能源，而且因為這個令人難以置信的變壓器引擎專為最新的 AI 模型設計。與 Ampere 相比的性能是如此重要，以至於我——並且由於這些新模型對 Hopper 的需求被壓抑——我談到了早期的深度推薦系統和大型語言模型以及生成 AI 模型。

Customers are clamoring to ramp Hopper as quickly as possible, and we are trying to do the same. We are all hands on deck to help the cloud service providers stand up the supercomputers. Remember, NVIDIA is the only company in the world that produces and ships semi-custom supercomputers in high volume. It's a miracle to ship 1 supercomputer every 3 years. It's unheard of to ship supercomputers to every cloud service provider in a quarter.

客戶要求盡快推出 Hopper，我們也在努力做到這一點。我們全力以赴幫助雲服務提供商建立超級計算機。請記住，NVIDIA 是世界上唯一一家大批量生產和運輸半定制超級計算機的公司。每 3 年出貨 1 台超級計算機是一個奇蹟。在一個季度內向每個雲服務提供商運送超級計算機的情況聞所未聞。

And so we're working hand in glove with every one of them, and every one of them are racing to stand up Hoppers. We expect them to have Hopper cloud services stood up in Q1. And so we are expecting to ship some volume, we're expecting to ship production in Q4, and then we're expecting to ship large volumes in Q1. That's a faster transition than Ampere. And so it's because of the dynamics that I described.

因此，我們正在與他們中的每一個人密切合作，他們中的每一個人都在競相支持 Hoppers。我們預計他們將在第一季度推出 Hopper 雲服務。因此，我們預計會出貨一些，我們預計會在第四季度出貨，然後我們預計會在第一季度出貨。這比安培更快。所以這是因為我描述的動態。

Your next question comes from the line of Matt Ramsay with Cowen.

你的下一個問題來自 Matt Ramsay 與 Cowen 的對話。

I guess, Colette, I heard in your script that you had talked about maybe a new way of commenting on or reporting hyperscaler revenue in your data center business. And I wonder if you could maybe give us a little bit more detail about what you're thinking there and what sort of drove the decision? And I guess the derivative of that, Jensen, how -- that decision to talk about the data center business to hyperscalers differently.

我想，科萊特，我在你的劇本中聽說你談到了可能是一種新的方式來評論或報告你的數據中心業務中的超大規模收入。我想知道您是否可以向我們提供更多詳細信息，說明您在那裡的想法以及是什麼推動了這個決定？我猜 Jensen 的衍生結果如何 - 決定以不同的方式與超大規模討論數據中心業務。

I mean what does that mean for the business? Is that just a reflection of where demand is and you're going to break things out differently? Or is something changing about the mix of I guess, internal properties versus vertical industry demand within the hyperscale customer base?

我的意思是這對企業意味著什麼？這是否只是需求所在的反映，您將以不同的方式解決問題？或者我猜，超大規模客戶群中的內部屬性與垂直行業需求的組合是否發生了變化？

Yes, Matt, thanks for the question. Let me clarify a little bit in terms of what we believe we should be looking at when we go forward in discussing our data center business. Our data center business is becoming larger and larger and our customers are complex. And when we talk about hyperscale, we tend to talk about 7, 8 different companies. But the reality is there's a lot of very large companies that we could add to that discussion based on what they're purchasing. Additionally, looking at the cloud, looking at our cloud purchases and what our customers are building for the cloud is an important area to focus on because this is really where our enterprise is, where our research is, where our higher education is also purchasing.

是的，馬特，謝謝你的提問。讓我澄清一下我們認為在繼續討論我們的數據中心業務時應該關注的內容。我們的數據中心業務越來越大，我們的客戶也越來越複雜。當我們談論超大規模時，我們傾向於談論 7、8 家不同的公司。但現實是，有很多非常大的公司，我們可以根據他們購買的產品加入討論。此外，查看雲、查看我們的雲採購以及我們的客戶正在為雲構建什麼是一個需要關注的重要領域，因為這確實是我們的企業所在、我們的研究所在、我們的高等教育也在採購的所在。

So we're trying to look for a better way to describe the color of what we're seeing in the cloud and also give you a better understanding of some of these large installments that we're seeing in the hyperscalers.

因此，我們正在努力尋找一種更好的方式來描述我們在雲中看到的顏色，並讓您更好地理解我們在超大規模應用程序中看到的一些大型分期付款。

Yes. Let me double click on what Colette just said, which is absolutely right. There are 2 major dynamics that's happening. First, the adoption of NVIDIA AI in Internet service companies around the world, the number and the scale by which they're doing it has grown a lot, internet service companies. And these are Internet service companies that offer services, but they're not public cloud computing companies.

是的。讓我雙擊科萊特剛才說的話，這是絕對正確的。有兩種主要的動態正在發生。首先，NVIDIA AI 在全球互聯網服務公司中的採用，他們這樣做的數量和規模已經增長了很多，互聯網服務公司。這些是提供服務的互聯網服務公司，但他們不是公共雲計算公司。

The second factor has to do with cloud computing. We are now at the tipping point of cloud computing. Almost every enterprise in the world has both a cloud-first and a multi-cloud strategy. It is exactly the reason why all of the announcements that we made this year -- this quarter, this last quarter since GTC about all the new platforms that are now available in the cloud. A CSP, a hyperscaler is both -- are 2 things to us, therefore, a hyperscaler can be a sell to customer. They are also a sell with partner on the public cloud side of their business.

第二個因素與雲計算有關。我們現在正處於雲計算的轉折點。世界上幾乎每個企業都有云優先和多雲戰略。這正是我們今年發布所有公告的原因——本季度，自 GTC 以來的最後一個季度，關於現在在雲中可用的所有新平台。一個 CSP，一個 hyperscaler 都是——對我們來說是兩件事，因此，一個 hyperscaler 可以賣給客戶。他們還在其業務的公共雲方面與合作夥伴一起銷售。

Because of the richness of NVIDIA's ecosystem, because we have so many Internet service customers and enterprise customers using NVIDIA's full stack, the public cloud side of their business really enjoys and values the partnership with us and the sell-with relationship they have with us. And it's pretty clear now that for all of the hyperscalers, the public cloud side of their business will likely, would very likely be the vast majority of their overall consumption.

由於 NVIDIA 生態系統的豐富性，因為我們有如此多的互聯網服務客戶和企業客戶使用 NVIDIA 的全棧，他們業務的公共雲方面真正享受並重視與我們的合作夥伴關係以及他們與我們的銷售關係。現在很明顯，對於所有超大規模企業來說，他們業務的公共雲方面很可能佔他們整體消費的絕大部分。

And so because the world CSPs, the world's public clouds is only at the early innings of their enterprise to lifting enterprise to the cloud world it's very, very clear that the public cloud side of the business is going to be very large. And so increasingly, our relationship with CSPs, our relationship with hyperscalers will include, of course, continuing to sell to them for internal consumption but very importantly, sell with for the public cloud side.

因此，因為世界 CSP，世界的公共雲只是在他們的企業將企業提升到雲世界的早期階段，所以非常非常清楚，業務的公共雲方面將非常龐大。因此，我們與 CSP 的關係，我們與超大規模的關係將越來越多地包括，當然，繼續向他們出售內部消費，但非常重要的是，與公共雲方面一起出售。

Your next question comes from the line of Joseph Moore with Morgan Stanley.

你的下一個問題來自摩根士丹利的約瑟夫摩爾。

Wonder if you could talk to looking backward at the crypto impact. Obviously, that's gone from your numbers now. But do you see any potential for liquidation of GPUs that are in the mining network, any impact going forward? And do you foresee blockchain being an important part of your business at some point down the road?

想知道您是否可以回顧一下加密貨幣的影響。顯然，這已經從你的數字中消失了。但是您是否看到清算挖礦網絡中的 GPU 的任何可能性，對未來有什麼影響嗎？您是否預見到區塊鏈會在未來的某個時候成為您業務的重要組成部分？

We don't expect to see blockchain being an important part of our business down the road. There is always a resell market. If you look at any of the major resell sites, eBay, for example, there are secondhand graphics cards for sale all the time. And the reason for that is because a 3090 that somebody bought today, is upgraded to a 4090 or 3090 by a couple of years ago, was upgraded to 4090 today. That 3090 could be sold to somebody and enjoyed it sold at the right price.

我們不希望看到區塊鏈成為我們未來業務的重要組成部分。轉售市場總是存在的。如果您查看任何主要的轉售網站，例如 eBay，就會一直有二手顯卡出售。其原因是因為有人今天購買的 3090 幾年前升級到 4090 或 3090，今天升級到 4090。那個 3090 可以賣給某人並享受以合適的價格出售。

And so the volume of -- the availability of secondhand and used graphics cards has always been there. And the inventory is never 0. And when the inventory is larger than usual, like all supply demand, it would likely drift lower price and affect the lower ends of our market. But my sense is that where we're going right now with ADA is targeting very clearly in the upper range, the top half of our market. And early signs are, and I'm sure you're also seeing it, that the ADA launch was a home run.

因此，二手和用過的顯卡的數量一直存在。而且庫存永遠不會為 0。當庫存比平時大時，就像所有的供應需求一樣，它可能會降低價格並影響我們市場的低端。但我的感覺是，我們現在與 ADA 一起去的地方非常明確地瞄準了我們市場的上半部分。早期跡像是，我相信您也看到了，ADA 的發布是一個本壘打。

That 4090, we shipped a large volume of 4090s because as you know, we were prepared for it. And yet within minutes, they were sold out around the world. And so the reception of 4090 and the reception of 4080 today has been off the charts. And that says something about the strength and the health and the vibrancy of the gaming market. So we're super enthusiastic about the ADA launch. We have many more ADA products to come.

那個 4090，我們運送了大量的 4090，因為如你所知，我們已經做好了準備。然而幾分鐘之內，它們就在世界各地銷售一空。因此，今天 4090 和 4080 的接收量已經超出了圖表。這說明了遊戲市場的實力、健康和活力。所以我們對 ADA 的發布非常熱情。我們將推出更多 ADA 產品。

Your last question today comes from the line of Toshiya Hari with Goldman Sachs.

你今天的最後一個問題來自高盛的 Toshiya Hari。

I had 2 quick ones for Colette. On supply, I think there was some mixed messaging in your remarks. I think you talked about supply being a headwind at 1 point. And then when you were speaking to the networking business, I think you talked about supply easing. So I was hoping you can kind of speak to supply if you're caught up to demand at this point. And then secondly, just on stock-based compensation, pretty mundane topic I realize, but it is -- I think in the quarter, it was about $700 million. It's becoming a bigger piece of your OpEx. So curious how we should be modeling that going forward.

我為科萊特准備了 2 個快速的。在供應方面，我認為您的言論中有一些混合信息。我想你談到供應是 1 點的逆風。然後當你在與網絡業務交談時，我想你談到了供應放鬆。所以我希望如果你此時趕上需求，你可以談談供應。其次，僅關於基於股票的薪酬，我意識到這是一個非常平凡的話題，但它是——我認為在本季度，它大約是 7 億美元。它在您的運營支出中所佔的比重越來越大。很好奇我們應該如何對未來進行建模。

Sure. When we look at our supply constraints that we have had in the past, each and every quarter, this is getting better Networking was one of our issues probably a year ago, and it has taken us probably to this quarter and next quarter to really see our supply improve, so that we can support the pipeline that we have for our customers. That's our supply. We've also made a discussion regarding our customers' supply constraints issues when setting up a data center. Even getting data center capacity has been very difficult. And therefore, that challenges them in their purchasing decisions as they're still looking for certain parts of that supply chain to come through.

當然。當我們審視過去每個季度的供應限制時，情況正在好轉網絡可能是一年前我們的問題之一，我們可能要到本季度和下個季度才能真正看到我們的供應得到改善，因此我們可以支持我們為客戶提供的管道。那是我們的供應。我們還討論了客戶在建立數據中心時的供應限制問題。甚至獲得數據中心容量也非常困難。因此，這對他們的採購決策提出了挑戰，因為他們仍在尋找供應鏈的某些部分。

So that hopefully clarifies what we were talking about regarding 2 areas of supply. In our stock-based compensation, what we'll see, it's very difficult to predict what our stock-based compensation would be when it arrives. We have provided to our incoming employees but also once a year to our employees, and it's a single date in terms of when that is priced. So it's difficult to determine.

因此，這有望澄清我們所談論的關於 2 個供應領域的內容。在我們的基於股票的薪酬中，我們將看到，很難預測我們的基於股票的薪酬在到達時會是多少。我們已經向我們的新員工提供了服務，但也每年向我們的員工提供一次服務，而且就定價時間而言，這是一個單一的日期。所以很難確定。

But stock-based compensation is an important part of our employees' compensation and will continue to be. So we look at it from an overall compensation perspective. So up until now and when we do the focal, we'll see about the same size with a few additions for the reduced level of employee hiring that we have right now.

但基於股票的薪酬是我們員工薪酬的重要組成部分，並將繼續如此。所以我們從整體薪酬的角度來看。因此，到目前為止，當我們進行焦點時，我們將看到與現在相同的規模，並增加了一些以減少我們現在的員工招聘水平。

I will now turn the call back over to Jensen Huang for closing remarks.

我現在將把電話轉回給黃仁勳作結束語。

Thanks, everyone. We are quickly adapting to the macro environment. Correcting inventory levels, offering alternative products to data center customers in China and keeping our OpEx flat for the next few quarters. Our new platforms are off to a great start and formed the foundation for our resumed growth.

感謝大家。我們正在快速適應宏觀環境。調整庫存水平，為中國的數據中心客戶提供替代產品，並在接下來的幾個季度保持我們的運營支出持平。我們的新平台開局良好，為我們恢復增長奠定了基礎。

NVIDIA RTX is reinventing 3D graphics with ray tracing and AI. The launch of ADA Lovelace is phenomenal. Gamers waited in long lines around the world, 4090 stocks sold out quickly. Hopper, with its revolutionary transformer engine is just in time to meet the surging demand for recommender systems, large language models and generative AI. NVIDIA Networking is synonymous with the highest data center throughput and enjoying record results. Orin is the world's first computing platform designed for AI-powered autonomous vehicles and robotics, and putting automotive on the road to be our next multibillion-dollar platform.

NVIDIA RTX 正在通過光線追踪和 AI 重塑 3D 圖形。 ADA Lovelace 的推出是非凡的。全球玩家大排長龍，4090股迅速售罄。 Hopper 憑藉其革命性的 transformer 引擎及時滿足了對推薦系統、大型語言模型和生成 AI 的激增需求。 NVIDIA Networking 是最高數據中心吞吐量和創紀錄成果的代名詞。 Orin 是世界上第一個專為 AI 驅動的自動駕駛汽車和機器人技術設計的計算平台，並使汽車成為我們下一個價值數十億美元的平台。

These computing platforms run NVIDIA AI and NVIDIA Omniverse, software libraries and engines that help the companies build and deploy AI to products and services. NVIDIA's pioneering work in accelerated computing is more vital than ever. Limited by [business], general purpose computing has slowed to a crawl just as AI demands more computing. Scaling through general purpose computing alone is no longer viable, both from a cost or power standpoint. Accelerated computing is the path forward. We look forward to updating you on our progress next quarter.

這些計算平台運行 NVIDIA AI 和 NVIDIA Omniverse，這些軟件庫和引擎可幫助公司構建 AI 並將其部署到產品和服務中。 NVIDIA 在加速計算方面的開創性工作比以往任何時候都更加重要。受[商業]的限制，通用計算已經放慢了速度，就像人工智能需要更多的計算一樣。從成本或功耗的角度來看，僅通過通用計算進行擴展已不再可行。加速計算是前進的道路。我們期待在下個季度向您通報我們的進展情況。

This concludes today's conference call. Thank you for attending. You may disconnect.

今天的電話會議到此結束。感謝您的出席。您可能會斷開連接。