輝達 (NVDA) 2022 Q1 法說會逐字稿

Good afternoon. My name is Sanedra, and I will be your conference operator today. At this time, I would like to welcome everyone to the NVIDIA Financial Results Conference Call. (Operator Instructions) Thank you.

午安.我叫 Sanedra，今天我將擔任您的會議主持人。現在，我歡迎大家參加 NVIDIA 財務業績電話會議。（操作員指示）謝謝。

Simona Jankowski, you may begin your conference.

Simona Jankowski，您可以開始您的會議了。

Thank you. Good afternoon, everyone, and welcome to NVIDIA's conference call for the first quarter of fiscal 2022. With me on the call today from NVIDIA are Jensen Huang, President and Chief Executive Officer; and Colette Kress, Executive Vice President and Chief Financial Officer.

謝謝。大家下午好，歡迎參加NVIDIA 2022財年第一季電話會議。今天與我一起參加電話會議的還有 NVIDIA 總裁兼執行長黃仁勳；以及執行副總裁兼財務長 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 second quarter of fiscal 2022. 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路直播。網路直播將可重播，直至電話會議討論 2022 財年第二季的財務業績。今天電話會議的內容屬於 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. All our statements are made as of today, May 26, 2021, based on information currently available to us. Except as required by law, we assume no obligation to update any such statements.

在本次電話會議中，我們可能會根據目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會有重大差異。有關可能影響我們未來財務表現和業務的因素的討論，請參閱今天的收益報告中的披露內容、我們最新的 10-K 和 10-Q 表格以及我們可能向美國證券交易委員會提交的 8-K 表格報告。我們所有的聲明都是根據我們目前掌握的資訊截至 2021 年 5 月 26 日做出的。除法律要求外，我們不承擔更新任何此類聲明的義務。

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.

在本次電話會議中，我們將討論非公認會計準則財務指標。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 財務指標的對帳表。

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

說完這些，讓我把電話轉給科萊特。

Thanks, Simona. Q1 was exceptionally strong with revenue of $5.66 billion and year-on-year growth accelerating to 84%. We set a record in total revenue in Gaming, Data Center and Professional Visualization, driven by our best-ever product lineup and structural tailwinds across our businesses.

謝謝，西蒙娜。第一季表現異常強勁，營收達 56.6 億美元，年增 84%。由於我們迄今為止最好的產品陣容和業務結構性的順風，我們在遊戲、資料中心和專業視覺化領域的總收入創下了紀錄。

Starting with Gaming. Revenue of $2.8 billion was up 11% sequentially and up 106% from a year earlier. This is the third consecutive quarter of accelerating year-on-year growth beginning with the fall launch of our GeForce RTX 30 Series GPUs. Based on the Ampere GPU architecture, the 30 Series has been our most successful launch ever, driving incredible demand and setting records for both desktop and laptop GPU sales.

從遊戲開始。營收為 28 億美元，季增 11%，年增 106%。自從秋季推出 GeForce RTX 30 系列 GPU 以來，這是我們連續第三個季度實現同比增長。30 系列基於 Ampere GPU 架構，是我們迄今為止最成功的產品，推動了令人難以置信的需求並創下了桌上型電腦和筆記型電腦 GPU 銷售的記錄。

Channel inventories are still lean, and we expect to remain supply-constrained into the second half of the year. With our Ampere GPU architecture now ramping across the stack in both desktop and laptops, we expect the RTX upgrade cycle to kick into high gear as the vast majority of our GPU installed base needs to upgrade.

通路庫存仍較少，我們預計下半年供應仍將受限。隨著我們的 Ampere GPU 架構在桌面和筆記型電腦中的應用不斷擴大，我們預計 RTX 升級週期將進入高速發展階段，因為我們絕大多數的 GPU 安裝基數都需要升級。

Laptops continue to drive strong growth this quarter as we started ramping the Ampere GPU architecture across our lineup. Earlier this month, all major PC OEMs launched GeForce RTX 30 Series laptops based on the 3080, 3070 and 3060 as part of their spring refresh. In addition, mainstream versions based on the 3050 and 3050 Ti will be available this summer just in time for back to school, starting at price points as low as $799. This is the largest ever wave of GeForce gaming laptops, over 140 in total, as OEMs address the rising demand from gamers, creators and students for NVIDIA's powered laptops.

隨著我們開始在整個產品線中推廣 Ampere GPU 架構，筆記型電腦本季繼續保持強勁成長。本月初，所有主要 PC OEM 廠商均推出了基於 3080、3070 和 3060 的 GeForce RTX 30 系列筆記型電腦，作為其春季更新的一部分。此外，基於 3050 和 3050 Ti 的主流版本將於今年夏天開學前上市，起價低至 799 美元。這是有史以​​來最大規模的 GeForce 遊戲筆記型電腦浪潮，總數超過 140 台，OEM 廠商旨在滿足遊戲玩家、創作者和學生對搭載 NVIDIA 晶片的筆記型電腦日益增長的需求。

The RTX 30 Series delivers our biggest generational leap in performance ever. It also features our second-generation ray tracing technology and frame rate-boosting, AI-powered DLSS. The RTX is a reset for graphics with over 60 accelerated games. This quarter, we added many more, including Call of Duty Modern Warfare, Crysis Remastered and Outriders. We also announced that DLSS is now available in Unreal Engine 4 and soon in the Unity game engine, enabling game developers to accelerate frame rates with minimal effort.

RTX 30 系列實現了我們迄今為止最大的效能飛躍。它還採用了我們的第二代光線追蹤技術和幀率提升、AI 驅動的 DLSS。RTX 是針對圖形的重置，具有超過 60 款加速遊戲。本季度，我們增加了更多遊戲，包括《決勝時刻現代戰爭》、《孤島危機重製版》和《先驅者》。我們還宣布，DLSS 現已在虛幻引擎 4 中推出，並很快將在 Unity 遊戲引擎中推出，使遊戲開發者能夠以最小的努力來提高幀速率。

The RTX 30 Series also offers NVIDIA Reflex, a new technology that reduces system latency. Reflex is emerging as a must-have feature for eSports gamers who play competitive titles like Call of Duty: Warzone, Fortnite, VALORANT and Apex Legends. We estimate that about 75% of GeForce gamers play eSports games, and 99% of eSports pros compete on GeForce.

RTX 30 系列還提供 NVIDIA Reflex，這是一項可降低系統延遲的新技術。對於玩《決勝時刻：戰區》、《堡壘之夜》、《VALORANT》和《Apex 英雄》等競技遊戲的電競玩家來說，Reflex 正在成為一項必備功能。我們估計大約 75% 的 GeForce 遊戲玩家玩電競遊戲，99% 的電競職業選手在 GeForce 上比賽。

We believe gaming also benefited from crypto mining demand, although it's hard to determine to what extent. We've taken actions to optimize GeForce GPUs for gamers while separately addressing mining demand with cryptocurrency mining processors, or CMPs. Last week, we announced that newly manufactured GeForce RTX 3080, RTX 3070 and RTX 3060 Ti graphic cards will have their Ethereum mining capabilities reduced by half and carry a low hash rate, or LHR identifier. Along with the updated RTX 3060, this should allow our partners to get more GeForce cards into the hands of gamers at better prices.

我們相信遊戲也受益於加密挖掘需求，儘管很難確定其程度。我們已採取措施為遊戲玩家最佳化 GeForce GPU，同時使用加密貨幣挖礦處理器（CMP）單獨解決挖礦需求。上週，我們宣布新生產的 GeForce RTX 3080、RTX 3070 和 RTX 3060 Ti 顯示卡的以太坊挖礦能力將降低一半，並且哈希率或 LHR 標識符將較低。連同更新的 RTX 3060，這將使我們的合作夥伴能夠以更優惠的價格將更多的 GeForce 卡送到遊戲玩家手中。

To help address mining demand, CMP products launched this quarter, optimized for mining performance and efficiency. Because they don't need the specifications required of a GeForce GPU, they don't impact the supply of GeForce GPUs to gamers. CMP revenue was $155 million in Q1, reported as part of the OEM and other category. And our Q2 outlook assumes CMP sales of $400 million.

為了滿足採礦需求，本季推出了 CMP 產品，針對採礦性能和效率進行了最佳化。由於它們不需要 GeForce GPU 所需的規格，因此它們不會影響 GeForce GPU 對玩家的供應。第一季 CMP 營收為 1.55 億美元，屬於 OEM 和其他類別的一部分。我們對第二季的預測是 CMP 的銷售額為 4 億美元。

Our GeForce NOW cloud gaming platform passed 10 million registered numbers this quarter. GFN offers nearly 1,000 PC games from over 300 publishers, more than any other cloud gaming service, including 80 of the most popular free-to-play games. GFN expands the reach of GeForce to billions of underpowered Windows PCs, Macs, Chromebooks, Android devices, iPhones and iPads. GFN is offered in over 70 countries with our latest expansions including Australia, Singapore and South America.

我們的GeForce NOW雲端遊戲平臺本季報名人數突破1000萬人。GFN 提供來自 300 多家發行商的近 1,000 款 PC 遊戲，比任何其他雲端遊戲服務都多，其中包括 80 款最受歡迎的免費遊戲。GFN 將 GeForce 的覆蓋範圍擴大到數十億台效能不足的 Windows PC、Mac、Chromebook、Android 裝置、iPhone 和 iPad。GFN 已涵蓋超過 70 個國家/地區，我們最近也擴展了澳洲、新加坡和南美洲等地區。

Moving to Pro Viz. Q1 revenue was $372 million, up 21%, both sequentially and year-on-year. Strong notebook growth was driven by a new sleek and powerful RTX-powered mobile workstations with Max-Q technology, and the enterprises continue to support remote workforce initiatives. Desktop workstations rebounded as enterprise resumed the spending that has been deferred during the lockdown with continued growth likely as offices open. Key verticals driving Q1 demand include manufacturing, health care, automotive and media and entertainment.

轉向 Pro Viz。第一季營收為 3.72 億美元，環比和年比均成長 21%。強勁的筆記型電腦成長得益於採用 Max-Q 技術的全新時尚且強大的 RTX 行動工作站，並且企業繼續支持遠端勞動力計劃。隨著企業恢復封鎖期間推遲的支出，桌上型工作站出現反彈，隨著辦公室的開放，桌上型工作站可能會繼續成長。推動第一季需求的關鍵垂直產業包括製造業、醫療保健、汽車業以及媒體和娛樂業。

At GTC, we announced the coming general availability of NVIDIA Omniverse Enterprise, the world's first technology platform that enables global 3D design teams to collaborate in real time in a shared space, working across multiple software speeds. This incredible technology build on NVIDIA's entire body of work and is supported by a large, rapidly growing ecosystem. Early adopters include sophisticated design teams at some of the world's leading companies such as BMW Group, Foster + Partners and WPP.

在 GTC 上，我們宣布即將全面推出 NVIDIA Omniverse Enterprise，這是世界上第一個使全球 3D 設計團隊能夠在共享空間中即時協作並跨多種軟體速度工作的技術平台。這項令人難以置信的技術建立在 NVIDIA 的全部工作基礎上，並得到龐大且快速發展的生態系統的支持。早期採用者包括寶馬集團、Foster + Partners 和 WPP 等一些世界領先公司的成熟設計團隊。

Over 400 companies have been evaluating Omniverse, and nearly 17,000 users have downloaded the open beta. Omniverse is offered as a software subscription on a per user and a per server basis. As the world becomes more digital, virtual and collaborative, we see a significant revenue opportunity for Omniverse.

超過 400 家公司正在評估 Omniverse，近 17,000 名用戶下載了公開測試版。Omniverse 以使用者和伺服器為基礎的軟體訂閱形式提供。隨著世界變得越來越數位化、虛擬化和協作化，我們看到了 Omniverse 的巨大創收機會。

We also announced powerful new Ampere architecture GPUs for next-generation desktop and laptop workstation. The new RTX-powered workstations will be available from all major OEMs.

我們也宣布推出適用於下一代桌上型電腦和筆記型電腦工作站的強大的新型安培架構 GPU。所有主要 OEM 廠商都將推出搭載 RTX 的全新工作站。

Moving to automotive. Q1 revenue was $154 million, up 6% sequentially and down 1% year-on-year. Growth in AI cockpit revenue was partially offset by the expected decline in legacy infotainment revenue.

轉向汽車產業。第一季營收為 1.54 億美元，季增 6%，年減 1%。人工智慧駕駛艙收入的成長被傳統資訊娛樂收入的預期下降部分抵消。

We extended our technology leadership with the announcement of the next-generation NVIDIA DRIVE Atlan SoC. Atlan will deliver an unrivaled 1,000 trillion operations per second of performance and integrate data center class NVIDIA BlueField networking and security technologies to enhance vehicle performance and safety, making it a true data center on wheels. Atlan, which targets automakers' 2025 models, will follow the NVIDIA DRIVE Orin SoC, which delivers 254 TOPS that has been selected by leading vehicle makers for production time lines starting next year.

我們透過發布下一代 NVIDIA DRIVE Atlan SoC 擴展了我們的技術領先地位。Atlan 將提供無與倫比的每秒 1,000 兆次操作的性能，並整合資料中心級 NVIDIA BlueField 網路和安全技術，以增強車輛​​性能和安全性，使其成為真正的行動資料中心。Atlan 的目標是汽車製造商的 2025 年車型，它將採用 NVIDIA DRIVE Orin SoC，該 SoC 可提供 254 TOPS，並已被領先的汽車製造商選用於明年開始的生產時間表。

The NVIDIA DRIVE platform has achieved global adoption across the transportation industry. Our automotive design win pipeline now exceeds $8 billion through fiscal 2027. Most recently, Volvo Cars announced that it will use NVIDIA DRIVE Orin, building on our next great momentum with some of the largest automakers, including Mercedes Benz, SAIC and Hyundai Motor Group.

NVIDIA DRIVE 平台已在全球運輸業得到應用。截至 2027 財年，我們的汽車設計得標金額已超過 80 億美元。最近，沃爾沃汽車宣布將使用 NVIDIA DRIVE Orin，與梅賽德斯奔馳、上汽集團和現代汽車集團等一些最大的汽車製造商攜手，共同打造下一個強勁發展勢頭。

In robotaxis, we added GM Cruise to the growing number of companies adopting the NVIDIA DRIVE platform, which includes Amazon Zoox and DiDi. We've also had a great traction with new energy vehicle makers. Our latest wins include Faraday Future, R Auto, IM Motors and VinFast, which joined previously announced wins with SAIC, NIO, Xpeng and Li Auto. In trucking, Navistar is partnered with TuSimple in selecting NVIDIA DRIVE for autonomous driving, joining previously announced Volvo Autonomous Solutions and Plus.

在自動駕駛計程車領域，我們將 GM Cruise 添加到越來越多採用 NVIDIA DRIVE 平台的公司中，其中包括 Amazon Zoox 和滴滴。我們也與新能源汽車製造商建立了良好的合作關係。我們最近贏得的合約包括法拉第未來 (Faraday Future)、R Auto、IM Motors 和 VinFast，此前我們已贏得上​​汽集團 (SAIC)、蔚來汽車 (NIO)、小鵬汽車 (Xpeng) 和理想汽車 (Li Auto) 的合約。在卡車運輸領域，Navistar 與 TuSimple 合作，選擇 NVIDIA DRIVE 進行自動駕駛，加入先前宣布的 Volvo Autonomous Solutions 和 Plus。

NVIDIA is helping to revolutionize the transportation industry. Our full stack software-defined AV and AI cockpit platform spans silicon, systems, software and AI data center infrastructure, enabling over-the-air upgrades to enhance safety and majority of driving throughout the vehicle's lifetime. Starting with our lead partner, Mercedes-Benz, NVIDIA DRIVE can transform the automotive industry with amazing technologies delivered through new software and services business models.

NVIDIA 正在幫助革新交通運輸產業。我們的全端軟體定義 AV 和 AI 駕駛艙平台涵蓋矽片、系統、軟體和 AI 資料中心基礎設施，可實現無線升級，從而提高車輛整個生命週期內的安全性和大部分駕駛體驗。從我們的主要合作夥伴梅賽德斯-奔馳開始，NVIDIA DRIVE 可以透過新的軟體和服務業務模式提供的驚人技術來改變汽車產業。

Moving to Data Center. Revenue topped $2 billion for the first time, growing 8% sequentially and up 79% from the year ago quarter, which did not include Mellanox. Hyperscale customers led our growth this quarter as they built infrastructure to commercialize AI in their services. In addition, cloud providers have adopted the A100 to support growing demand for AI from enterprises, start-ups and research organizations.

移至資料中心。營收首次突破 20 億美元，季增 8%，較去年同期成長 79%（不包括 Mellanox）。超大規模客戶在本季度引領了我們的成長，因為他們建立了基礎設施以在其服務中實現人工智慧商業化。此外，雲端供應商已採用 A100 來支援企業、新創公司和研究機構對人工智慧日益增長的需求。

Customers are deploying NVIDIA's A100 and DGX platforms to train deep neural networks with rising computational intensity led by 2 of the fastest-growing areas of AI, natural language understanding and deep recommendators. In March, Google Cloud Platform announced general availability of the A100 with early customers, including Square for its cash application and Alphabet's DeepMind. The A100 is deployed across all major hyperscale and cloud service providers globally, and we see strengthening demand in the coming quarters.

客戶正在部署 NVIDIA 的 A100 和 DGX 平台來訓練深度神經網絡，其運算強度不斷提高，其中以人工智慧中成長最快的兩個領域——自然語言理解和深度推薦器為主導。今年 3 月，Google雲端平台宣布向早期客戶全面推出 A100，其中包括 Square 的現金應用程式和 Alphabet 的 DeepMind。A100 已部署在全球所有主要的超大規模和雲端服務供應商中，我們預計未來幾季的需求將會增強。

Every industry is becoming a technology industry and accelerating investments in AI infrastructure, both through the cloud and on-premise. Our vertical industries grew both sequentially and year-on-year, led by consumer Internet companies. For example, Naver, a leading Internet technology company in Korea and Japan, is training giant AI language models at scale on DGX SuperPOD to pioneer new services across e-commerce, search, entertainment and payment applications.

每個行業都在成為科技產業，並透過雲端和本地加速對人工智慧基礎設施的投資。在消費網路公司的帶動下，我們的垂直產業實現了環比和年成長。例如，韓國和日本領先的網路科技公司 Naver 正在 DGX SuperPOD 上大規模訓練大型 AI 語言模型，以開拓電子商務、搜尋、娛樂和支付應用領域的新服務。

We continue to gain traction in inference with hyperscale and vertical industry customers across a broadening portfolio of GPUs. We had record shipments of GPUs used for inference. Inference growth is driving not just the T4, which was up strongly in the quarter, but also the universal A100 Tensor Core GPU as well as the new Ampere architecture-based A10 and A30 GPUs, all excellent at training as well as inferencing.

我們繼續透過不斷擴大的 GPU 產品組合，在超大規模和垂直行業客戶的推理方面獲得青睞。我們用於推理的 GPU 出貨量創下了紀錄。推理成長不僅推動了本季強勁成長的 T4，還推動了通用 A100 Tensor Core GPU 以及基於新型 Ampere 架構的 A10 和 A30 GPU，它們在訓練和推理方面都表現出色。

Customers are increasingly migrating from CPUs to GPUs for AI inference for 2 chief reasons. First, GPUs can better keep up with the exponential growth in the size and the complexity of deep neural networks and respond with the required low latency. In April's MLPerf AI inference benchmark, NVIDIA achieved the top results across every category, spanning computer vision, medical imaging, recommendator systems, speech recognition and natural language processing.

越來越多的客戶將 AI 推理從 CPU 遷移到 GPU，主要有兩個原因。首先，GPU 可以更好地跟上深度神經網路規模和複雜性的指數增長，並以所需的低延遲做出反應。在 4 月的 MLPerf AI 推理基準測試中，NVIDIA 在電腦視覺、醫學影像、推薦系統、語音辨識和自然語言處理等各個類別中均取得了最高成績。

And second, NVIDIA's full stack inference platform, including Triton Inference Server software, simplifies the complexity of deploying AI applications by supporting models for all major frameworks and optimizing from different query types, including batch, real time and streaming. Triton is supported by several partners in their cloud services, including Amazon, Google, Microsoft and Tencent.

其次，NVIDIA 的全端推理平台（包括 Triton Inference Server 軟體）透過支援所有主要框架的模型並針對不同查詢類型（包括批次、即時和串流）進行最佳化，簡化了部署 AI 應用程式的複雜性。Triton 的雲端服務得到了多家合作夥伴的支持，包括亞馬遜、Google、微軟和騰訊。

Examples of how customers use NVIDIA's inference platform include Microsoft for grammar checking in Office, the United States Postal Service for real-time package analytics, T-Mobile for customer service, Pinterest for image search and GE Healthcare for heart disease detection.

客戶使用 NVIDIA 推理平台的範例包括 Microsoft 用於 Office 中的語法檢查、美國郵政服務用於即時包裹分析、T-Mobile 用於客戶服務、Pinterest 用於影像搜尋以及 GE Healthcare 用於心臟病檢測。

We also had strong results with Mellanox networking products. Like our compute business, strong growth was driven by hyperscale customers across both Ethernet and InfiniBand. We achieved key design wins and proof-of-concept trials for the NVIDIA BlueField-2 DPU with cloud service providers and consumer Internet companies.

我們在 Mellanox 網路產品方面也取得了出色的成績。與我們的運算業務一樣，強勁的成長是由乙太網路和 InfiniBand 的超大規模客戶推動的。我們與雲端服務供應商和消費者網路公司合作，為 NVIDIA BlueField-2 DPU 贏得了關鍵設計勝利並完成了概念驗證試驗。

We also unveiled BlueField-3, the first DPU built for AI and accelerated computing with support from VMware, NetApp Splunk, Cloudflare and others. BlueField-3 is the industry's first 400-gig DPU and delivers the equivalent data center services of up to 300 CPU cores. It transforms traditional server infrastructure into zero-trust environment in which every user is authenticated by offloading and isolating data center services from business applications. With BlueField-3, our DPU road map will deliver an unrivaled 100x performance increase over a 3-year period.

我們也推出了 BlueField-3，這是第一款為 AI 和加速運算而建置的 DPU，並獲得了 VMware、NetApp Splunk、Cloudflare 等公司的支援。BlueField-3 是業界首款 400G DPU，可提供相當於多達 300 個 CPU 核心的資料中心服務。它將傳統的伺服器基礎架構轉變為零信任環境，透過卸載和隔離資料中心服務與業務應用程式來對每個使用者進行身份驗證。透過 BlueField-3，我們的 DPU 路線圖將在 3 年內實現無與倫比的 100 倍效能提升。

As we look back at the first full year since closing the Mellanox acquisition, we are extremely pleased with how the business has performed. It has not only exceeded our financial projections, but it has been instrumental in key new platforms like the DGX SuperPOD and the BlueField DPU, enabling our data center scale computing strategy.

回顧完成 Mellanox 收購後的第一個整年，我們對業務表現感到非常滿意。它不僅超出了我們的財務預測，而且在 DGX SuperPOD 和 BlueField DPU 等關鍵新平台中發揮了重要作用，支持了我們的資料中心規模運算策略。

In April, we held our largest ever GPU Technology Conference with more than 200,000 registrants from 195 countries. Jensen's keynote had over 14 million views. At GTC, we announced our first data center CPU, NVIDIA Grace, targeted at processing massive next-generation AI models with trillions of parameters. The Arm-based processor will enable 10x the performance and energy efficiency of today's fastest servers. With Grace, NVIDIA has a 3-chip strategy with GPU, DPU and now CPU. The Swiss National Supercomputing Center and the U.S. Department of Energy's Los Alamos National Laboratory are the first to announce plans to build Grace-powered supercomputers. Grace will be available in early 2023.

今年 4 月，我們舉辦了有史以來規模最大的 GPU 技術大會，來自 195 個國家的註冊人數超過 20 萬人。詹森的主題演講的觀看次數已超過 1400 萬次。在 GTC 上，我們發布了首款資料中心 CPU NVIDIA Grace，旨在處理具有數兆個參數的大量新一代 AI 模型。基於 Arm 的處理器將使當今最快的伺服器的效能和能源效率提高 10 倍。憑藉 Grace，NVIDIA 制定了三晶片策略，包括 GPU、DPU 和現在的 CPU。瑞士國家超級電腦中心和美國能源部洛斯阿拉莫斯國家實驗室率先宣布計劃建造由 Grace 驅動的超級電腦。Grace 將於 2023 年初上市。

GTC is first and foremost for developers. We announced NVIDIA developed and optimized pretrained model availability on the NVIDIA GPU Cloud registry. Developers can choose a pretrained model and adapt it to fit their specific needs using NVIDIA TAO, our transfer learning software. TAO fine tunes the model with customers' own small data set to give models a custom fit without the cost, time and massive data sets required to train a neural network from scratch. Once a model is optimized and ready for deployment, users can integrate it with an NVIDIA application framework that fits their use.

GTC 首先是為開發者服務的。我們宣布 NVIDIA 開發並優化的預訓練模型可在 NVIDIA GPU Cloud 註冊表上使用。開發人員可以選擇預訓練模型，並使用我們的遷移學習軟體 NVIDIA TAO 對其進行調整以滿足他們的特定需求。TAO 使用客戶自己的小型資料集對模型進行微調，使模型能夠自訂適合，而無需從頭開始訓練神經網路所需的成本、時間和大量資料集。一旦模型優化完畢並準備部署，使用者就可以將其與適合其用途的 NVIDIA 應用程式框架整合。

For example, the NVIDIA Jarvis framework for interactive conversational AI is now generally available and used by customers such as T-Mobile and Snap. And the NVIDIA Merlin framework for deep recommendators is an open beta with customers such as Snap and Tencent. With the chosen application framework, users can launch NVIDIA Fleet Command software to deploy and manage the AI application across a variety of NVIDIA GPU-powered devices.

例如，用於互動式對話式 AI 的 NVIDIA Jarvis 框架現已普遍可用，並由 T-Mobile 和 Snap 等客戶使用。針對深度推薦系統的 NVIDIA Merlin 框架目前已向 Snap 和騰訊等客戶開放測試版。透過選擇的應用程式框架，使用者可以啟動 NVIDIA Fleet Command 軟體在各種 NVIDIA GPU 驅動的裝置上部署和管理 AI 應用程式。

For our enterprise customers, we unveiled a new enterprise-grade software offering available as a perpetual license or subscription. NVIDIA AI Enterprise is a comprehensive suite of AI software that speeds development and deployment of AI workloads and simplifies management of enterprise AI infrastructure. Through our partnership with VMware, hundreds of thousands of vSphere customers will be able to purchase NVIDIA AI Enterprise with the same familiar pricing model that IT managers use to procure VMware infrastructure software.

對於我們的企業客戶，我們推出了一款新的企業級軟體產品，可以永久授權或訂閱的方式提供。NVIDIA AI Enterprise 是一套全面的 AI 軟體，可加快 AI 工作負載的開發和部署，並簡化企業 AI 基礎架構的管理。透過與 VMware 的合作，數十萬 vSphere 客戶將能夠以 IT 經理採購 VMware 基礎架構軟體時所使用的相同熟悉的定價模式購買 NVIDIA AI Enterprise。

We also made several announcements at GTC about accelerating the delivery of both NVIDIA AI and accelerated computing to enterprises and edge users among the world's largest industries. Leading server OEMs launched NVIDIA-certified systems, which are industry standard servers based on the NVIDIA EGX platform. They run NVIDIA AI Enterprise software and are supported by the NVIDIA A30 and A10 GPUs. Initial customers include Lockheed Martin and Mass General Brigham.

我們也在 GTC 上發布了多項公告，宣布將加速向全球最大產業的企業和邊緣用戶提供 NVIDIA AI 和加速運算。領先的伺服器 OEM 推出了 NVIDIA 認證的系統，這是基於 NVIDIA EGX 平台的業界標準伺服器。它們運行 NVIDIA AI Enterprise 軟體，並由 NVIDIA A30 和 A10 GPU 支援。最初的客戶包括洛克希德馬丁公司和麻省布萊根綜合醫院。

In addition, we announced the NVIDIA AI-on-5G platform supported on NVIDIA EGX servers to enable high-performance 5G RAM and AI applications. The AI-on-5G platform leverages the NVIDIA Aerial software and the NVIDIA BlueField-2 A100 converged card, which combines our GPUs and DPUs. We are teaming with Fujitsu, Google Cloud, Mavenir, Radisys and Wind River in developing solutions based on our AI-on-5G platform to speed the creation of smart cities and factories, advanced hospitals and intelligent stores.

此外，我們還宣布了在 NVIDIA EGX 伺服器上支援的 NVIDIA AI-on-5G 平台，以實現高效能 5G RAM 和 AI 應用程式。AI-on-5G 平台利用 NVIDIA Aerial 軟體和 NVIDIA BlueField-2 A100 融合卡，結合了我們的 GPU 和 DPU。我們正與富士通、Google雲端、Mavenir、Radisys 和 Wind River 合作，開發基於我們的 AI-on-5G 平台的解決方案，以加快創建智慧城市和工廠、先進醫院和智慧商店。

Another highlight at GTC was the announcement of a broad range of initiatives to strengthen the Arm ecosystem across cloud data centers, HPC, enterprise and edge and PCs. In the cloud, we are bringing together AWS Graviton2 processors and NVIDIA GPUs to provide a range of benefits, including lower-cost support for richer game streaming experiences and greater performance for Arm-based workloads.

GTC 的另一個亮點是宣布了一系列旨在加強 Arm 在雲端資料中心、HPC、企業和邊緣以及 PC 領域的生態系統的舉措。在雲端，我們將 AWS Graviton2 處理器和 NVIDIA GPU 結合在一起，提供一系列優勢，包括以更低成本支援更豐富的遊戲串流體驗和為基於 Arm 的工作負載提供更高效能。

In HPC, we are bringing together an Ampere Altra CPU with NVIDIA GPUs, DPUs and NVIDIA HPC software developer kit. Initial supercomputing centers deploying it include Oak Ridge and Los Alamos National Labs. In the enterprise and edge, we are bringing together Marvell Arm-based OCTEON processors and the NVIDIA GPUs to accelerate video analytics and cybersecurity solutions. And in PCs, we are bringing together MediaTek's Arm-based processors with NVIDIA's RTX GPUs to enable realistic ray trace graphics and cutting-edge AI in a new class of Arm-based laptops.

在 HPC 中，我們將 Ampere Altra CPU 與 NVIDIA GPU、DPU 和 NVIDIA HPC 軟體開發套件結合在一起。最初部署此技術的超級運算中心包括橡樹嶺國家實驗室和洛斯阿拉莫斯國家實驗室。在企業和邊緣領域，我們將基於 Marvell Arm 的 OCTEON 處理器和 NVIDIA GPU 結合在一起，以加速視訊分析和網路安全解決方案。在個人電腦方面，我們將聯發科基於 Arm 的處理器與 NVIDIA 的 RTX GPU 結合在一起，在基於 Arm 的新型筆記型電腦中實現逼真的光線追蹤圖形和尖端 AI。

On our Arm acquisition, we are making steady progress in working with the regulators across key regions. We remain on track to close the transaction within our original time frame of early 2022. Arm's IP is widely used, but the company needs a partner that can help it achieve new heights. NVIDIA is uniquely positioned to enhance Arm's capabilities. And we are committed to invest in developing the Arm ecosystem, enhancing R&D, adding IP and turbocharging its development to grow into new markets in the data center, IoT and embedded devices, areas where it only has a light footprint or in some cases, none at all.

在收購 Arm 的過程中，我們與主要地區監管機構的合作正在穩步推進。我們仍有望在原定的 2022 年初期限內完成交易。Arm 的 IP 被廣泛使用，但該公司需要一個能夠幫助其達到新高度的合作夥伴。NVIDIA 擁有獨特的優勢，可增強 Arm 的功能。我們致力於投資開發 Arm 生態系統，加強研發，增加 IP 並加速其發展，以進入資料中心、物聯網和嵌入式設備等新市場，在這些領域，Arm 的影響力很小，在某些情況下甚至沒有影響力。

Moving to the rest of the P&L. GAAP gross margin for the first quarter was down 100 basis points from a year earlier and up 100 basis points sequentially. Non-GAAP gross margin was up 40 basis points from a year earlier and up 70 points sequentially. The sequential non-GAAP increase was largely driven by a more favorable mix within data center and the addition of CMP products.

轉到損益表的其餘部分。第一季 GAAP 毛利率較上年同期下降 100 個基點，較上一季上升 100 個基點。非公認會計準則毛利率較上年同期上升 40 個基點，較上一季上升 70 個基點。非公認會計準則的環比增長主要得益於資料中心內部更有利的組合以及 CMP 產品的增加。

Q1 GAAP EPS was $3.03, up 106% from a year earlier. Non-GAAP EPS was $3.66, up 103% from a year ago. Q1 cash flow from operations was $1.9 billion.

第一季 GAAP EPS 為 3.03 美元，年增 106%。非公認會計準則每股收益為 3.66 美元，較去年同期成長 103%。第一季經營現金流為 19 億美元。

Let me turn to the outlook for the second quarter of fiscal 2022. We expect broad-based sequential year-on-year revenue growth in all of our market platforms. Our outlook includes $400 million in CMP. Aside from CMP, the sequential revenue increase in our Q2 outlook is driven largely by Data Center and Gaming. In Data Center, we expect sequential growth in both compute and networking. In Gaming, with the move to low hash rate GeForce CPUs and increasing the amount of CMP products, we are making a significant effort to serve miners with CMPs and provide more GeForce cards to gamers. If there is additional CMP demand, we have supply flexibility to support it. We believe these actions, combined with strong gaming demand, will drive an increase in our core Gaming business for Q2.

讓我來談談2022財年第二季的展望。我們預計所有市場平台的收入將實現年比全面成長。我們的展望包括 4 億美元的 CMP。除了 CMP 之外，我們第二季展望中的連續營收成長主要受到資料中心和遊戲的推動。在資料中心，我們預計計算和網路都將實現連續成長。在遊戲領域，隨著向低哈希率 GeForce CPU 的轉變以及 CMP 產品數量的增加，我們正在做出巨大努力為礦工提供 CMP 服務，並為遊戲玩家提供更多的 GeForce 卡。如果有額外的 CMP 需求，我們可以靈活地提供供應來支援。我們相信，這些舉措加上強勁的遊戲需求，將推動我們第二季核心遊戲業務的成長。

Now to look at our outlook for Q2. Revenue is expected to be $6.3 billion, plus or minus 2%. GAAP and non-GAAP gross margins are expected to be 64.6% and 66.5%, respectively, plus or minus 50 basis points. GAAP and non-GAAP operating expenses are expected to be approximately $1.76 billion and $1.26 billion, respectively. GAAP and non-GAAP other income and expenses are both expected to be an expense of approximately $50 million. GAAP and non-GAAP tax rates are both expected to be 10%, plus or minus 1%, excluding discrete items. Capital expenditures are expected to be approximately $300 million to $325 million. Further financial details are included in the CFO commentary and other information available on our IR website.

現在來看看我們對第二季的展望。預計營收為 63 億美元，上下浮動 2%。預計 GAAP 和非 GAAP 毛利率分別為 64.6% 和 66.5%，上下浮動 50 個基點。預計 GAAP 和非 GAAP 營運費用分別約為 17.6 億美元和 12.6 億美元。預計 GAAP 和非 GAAP 其他收入和支出均約為 5,000 萬美元。預計 GAAP 和非 GAAP 稅率均為 10%，上下浮動 1%，不包括單一項目。預計資本支出約3億至3.25億美元。進一步的財務細節包含在財務長評論和我們 IR 網站上提供的其他資訊中。

In closing, let me highlight that Jeff Fisher and Manuvir Das will keynote Computex on the evening of May 31 U.S. time as well as several upcoming events for the financial community. We will be virtually attending the Evercore TMT Conference on June 7, the BofA 2021 Global Technology Conference on June 9 and the NASDAQ Virtual Investor Conference on June 16. Our earnings call to discuss our second quarter results is scheduled for Wednesday, August 18.

最後，我要強調的是，Jeff Fisher 和 Manuvir Das 將於美國時間 5 月 31 日晚上在 Computex 上發表主題演講，並出席即將舉行的幾場金融界活動。我們將以虛擬方式參加 6 月 7 日的 Evercore TMT 會議、6 月 9 日的美國銀行 2021 年全球技術會議以及 6 月 16 日的納斯達克虛擬投資者會議。我們將於 8 月 18 日星期三召開收益電話會議，討論第二季業績。

With -- now we will open the call for questions. Operator, would you please poll for questions.

現在我們將開始提問。接線員，請投票詢問問題。

(Operator Instructions) The first question come from Timothy Arcuri with UBS.

（操作員指示）第一個問題來自瑞銀的 Timothy Arcuri。

Colette, I was wondering if you can double-click a little more on the guidance. I know of the 600 to 650 in growth, you said 250 is coming from CMP and both Gaming and Data Center will be up. Can we assume that they're up about equally, so you're getting about 200 roughly from each of those?

科萊特，我想知道您是否可以再雙擊指南。我知道成長量為 600 到 650，您說 250 來自 CMP，遊戲和資料中心都會成長。我們是否可以假設它們的漲幅大致相等，那麼你從每個數字中大約可以獲得 200 左右？

And I guess second part of that is, within Data Center, I'm wondering, can you speak to the networking piece? It sounds like maybe it was up a bit more modestly than it's been up the past few quarters. I'm just wondering what the outlook is there.

我想第二部分是，在資料中心內，我想知道，您能談談網路部分嗎？聽起來，與過去幾季相比，漲幅可能要小一些。我只是想知道那裡的前景如何。

Yes. Thanks so much for the question on our guidance. So I first want to start off with we see demand really across all of our markets. All of our different market platforms, we do plan to grow sequentially. You are correct that we are expecting an increase in our CMP. And outside of our CMP growth, we expect the lion's share of our growth to come from our Data Center and Gaming.

是的。非常感謝您就我們的指導提出的問題。因此，我首先要說的是，我們看到所有市場確實都有需求。我們所有不同的市場平台都計劃逐步成長。您說得對，我們預計 CMP 會增加。除了 CMP 成長之外，我們預計大部分成長將來自資料中心和遊戲。

In our Data Center business, right now, our product lineup couldn't be better. We have a strong overall portfolio, both for training and for inferencing, and we're seeing strong demand across our hyperscales and vertical industries. We've made a deliberate effort on the Gaming perspective to supply to our gamers the cards that they would like, given the strong demand that we see. So that will also support the sequential growth that we're receiving. So you are correct that we do see a growth sequentially coming from Data Center and Gaming, both contributing quite well to our growth.

在我們的資料中心業務中，目前，我們的產品陣容非常出色。我們擁有強大的整體產品組合，包括訓練和推理，我們看到超大規模和垂直行業的需求強勁。鑑於我們看到的強勁需求，我們在遊戲角度做出了刻意的努力，為我們的玩家提供他們想要的卡片。因此這也將支持我們所獲得的連續成長。所以您說得對，我們確實看到資料中心和遊戲業務連續成長，它們都對我們的成長做出了相當大的貢獻。

I didn't answer your second question, my apologies, on Mellanox. Additionally, Mellanox is an important part of our Data Center. It is quite integrated with our overall products. We did continue to see growth this last quarter, and we are also expecting them to sequentially grow as we move into Q2. They are a smaller part of our overall Data Center business, but again, we do expect them to grow.

抱歉，我沒有回答您關於 Mellanox 的第二個問題。此外，Mellanox 是我們資料中心的重要組成部分。它與我們的整體產品相當融合。我們確實在上個季度繼續看到了增長，並且我們預計隨著進入第二季度，它們將繼續增長。它們只是我們整個資料中心業務中較小的一部分，但我們確實預期它們會成長。

And your next question comes from C.J. Muse with Evercore ISI.

您的下一個問題來自 Evercore ISI 的 C.J. Muse。

In your prepared remarks, I think I heard you talk about a vision for acceleration in data center as we go through the year. And as you think about the purchase obligations that you reported, up 45% year-on-year, how much of that is related to long lead time Data Center? And how should we interpret that in terms of what kind of ramp we could see in the second half, particularly as you think about perhaps adding more growth from enterprise on top of what was hyperscale-driven growth in the April quarter?

在您準備好的發言中，我想我聽到您談到了我們今年對資料中心加速發展的願景。當您考慮所報告的購買義務時，其同比增長了 45%，其中有多少與長交貨期資料中心有關？我們該如何解讀下半年可能會出現怎樣的成長，特別是當您考慮在 4 月季度超大規模驅動的成長基礎上，再增加來自企業的成長時？

Let me take the first part of your question regarding our purchasing, our purchasing of inventory and what we're seeing in just both our purchase commitments and our inventory. The market has definitely changed to where long lead times are required to build out our data center products. So we're on a steady stream to both commit longer term so that we can make sure that we can serve our customers with the great lineup of products that we have. So yes, a good part of those purchase commitments is really about the long lead times of the components to create the full systems.

讓我來回答您問題的第一部分，關於我們的採購、庫存採購以及我們在採購承諾和庫存方面看到的情況。市場確實已經發生了變化，需要較長的交付週期來建立我們的資料中心產品。因此，我們正穩步地做出長期承諾，以確保我們能夠透過我們擁有的優質產品陣容為客戶提供服務。所以是的，這些購買承諾的很大一部分實際上與創建完整系統的組件的長期交付週期有關。

I'll turn the second part of the question over to Jensen.

我將把問題的第二部分交給 Jensen。

What was the second part of the question, Colette?

問題的第二部分是什麼，科萊特？

The second part of the question was what do we see in the second half as it relates to the lineup of enterprise and we articulated in our pre-remarks regarding that we see an acceleration.

問題的第二部分是，就企業陣容而言，我們在下半年看到了什麼，我們在預先的評論中明確表示，我們看到了加速。

Yes. Yes. We're seeing strength across the board in data centers, and we're seeing strengthening demand. C.J., our Data Center, as you know, accelerates a range of applications, from scientific computing, both physical and life sciences; data analytics and classical machine learning; cloud computing and cloud graphics, which is becoming more important because of remote work; and very importantly, AI, both for training as well as inferencing for classical machine learning models like XGBoost all the way to deep learning-based models like conversational AI, natural language understanding, recommender systems and so on.

是的。是的。我們看到資料中心全面展現強勁勢頭，需求也不斷增強。C.J.，如您所知，我們的資料中心加速了一系列應用，包括科學運算、物理和生命科學；資料分析和經典機器學習；雲端運算和雲端圖形，由於遠距工作而變得越來越重要；非常重要的是，人工智慧既可以用於訓練，也可以用於推理，從 XGBoost 等經典機器學習模式到基於深度學習的模型，如會話人工智慧、自然語言理解、

And so we have a large suite of applications, and our NVIDIA AI and NVIDIA HPC SDKs accelerate these applications in data centers. They run on systems that range from HGX for the hyperscalers to DGX for on-prem to EGX for enterprise and edge all the way out to AGX autonomous systems. And this quarter at GTC, we announced one of our largest initiatives, and it's taken us several years. You've seen me working on it in open -- out in the open over the course of the last several years. Hence, it's called -- EGX is our enterprise AI platform.

因此，我們擁有大量的應用程序，我們的 NVIDIA AI 和 NVIDIA HPC SDK 可以在資料中心加速這些應用程式。它們運行的系統範圍從用於超大規模的 HGX 到用於本地的 DGX 到用於企業和邊緣的 EGX 一直到 AGX 自治系統。本季在 GTC 上，我們宣布了我們最大的計劃之一，這項計劃耗時數年。你們已經看到我在過去幾年中公開地致力於此事。因此，它被稱為——EGX 是我們的企業 AI 平台。

We're democratizing AI. We're bringing it out of cloud. We're bringing it to enterprises, and we're bringing it out to the edge. And the reason for that is because the vast majority of the world's automation that has to be done has data that has data sovereignty issues or data rate issues that can't move to the cloud easily. And so we got -- we have to move the computing to their premise and oftentimes all way out of the edge.

我們正在使人工智慧民主化。我們正在將其從雲中取出。我們將其帶入企業，並將其推向邊緣。原因在於，世界上絕大多數必須完成的自動化任務的資料都存在資料主權問題或資料速率問題，無法輕易轉移到雲端。因此我們必須將計算轉移到他們的前提下，並且常常要將其全部轉移到邊緣之外。

The platform -- the platform has to be secure, has to be confidential. It has to be remotely manageable. And of course, it has to be high performance and it has to be cloud native and has to be built like the cloud, the modern way of building cloud data centers. And so these stacks has to be modern on the one hand. It has to be integrated into classical enterprise systems on the other hand, which is the reason why we work so closely with VMware and accelerated VMware's operating system, data center operating system and software-defined data center stacks on BlueField.

該平台－該平台必須是安全的、必須是保密的。它必須是可遠端管理的。當然，它必須是高效能的，必須是雲端原生的，並且必須像雲端一樣構建，即構建雲端資料中心的現代方式。因此，一方面，這些堆疊必須是現代化的。另一方面，它必須整合到傳統的企業系統中，這就是我們與 VMware 緊密合作並在 BlueField 上加速 VMware 的作業系統、資料中心作業系統和軟體定義資料中心堆疊的原因。

Meanwhile, we ported NVIDIA AI and NVIDIA HPC onto VMware so that they could run distributed, large-scale, accelerated computing for the very first time. And that partnership -- that partnership was announced at VMworld. It was announced at GTC, and we're in the process of going to market with all of our enterprise partners. They're OEMs, they're value-added resellers, they're service -- they're solution integrators all over the world.

同時，我們將NVIDIA AI和NVIDIA HPC移植到VMware上，使它們首次能夠運行分散式、大規模、加速運算。該合作關係是在 VMworld 上宣布的。它是在 GTC 上宣布的，我們正在與所有企業合作夥伴一起將其推向市場。他們是原始設備製造商 (OEM)、加值經銷商、服務商——他們是遍布全球的解決方案整合商。

And so this is a really large endeavor. And the early indications of it are really exciting. And the reason for that is because, as you know, our data center business is more than 50% vertical industry enterprise already. It's more than 50% vertical industry enterprises already. And by creating this easy-to-adapt and easy-to-integrate stack, it's going to allow them to move a lot faster.

所以這是一項非常艱鉅的任務。早期跡象確實令人興奮。原因在於，如您所知，我們的資料中心業務已經涵蓋了超過 50% 的垂直行業企業。其中垂直產業企業已超過50%。透過創建這個易於適應和易於整合的堆疊，他們可以更快地行動。

And so this is the next major wave of AI. This is a very exciting part of our initiative, and it's something that I've been working on for -- we've been working on for quite a long time. And so I'm delighted with the launch this quarter at GTC.

這就是人工智慧的下一波浪潮。這是我們計劃中非常令人興奮的一部分，也是我一直致力於的事情——我們已經為此努力了很長時間。因此，我很高興看到本季在 GTC 上推出該產品。

The rest of the data center is doing great, too. As Colette mentioned, hyperscale demand is strengthening. We're seeing that for computing and networking You know that the world's cloud data centers are moving to deep learning because every small percentage that they get out of predictive inference drives billions and billions of dollars of economics for them. And so the movement towards deep learning shifts the data center workload away from CPUs because accelerators are so important. And so hyperscale, we're seeing great traction and great demand.

資料中心的其餘部分也運作良好。正如 Colette 所提到的，超大規模的需求正在增強。我們看到，對於運算和網路來說，你知道，世界的雲端資料中心正在轉向深度學習，因為他們從預測推理中獲得的每一個小百分比都會為他們帶來數十億美元的經濟效益。因此，深度學習的趨勢將資料中心的工作負載從 CPU 轉移出去，因為加速器非常重要。因此，我們看到了超大規模的巨大吸引力和巨大的需求。

And then lastly, supercomputing. Supercomputing centers all over the world are building out, and we're really in a great position there to fuse for the very first time simulation-based approaches as well as data-driven based approaches, what is called artificial intelligence. And so across the board, our data center is gaining momentum. And we see -- we just see great strength right now, and it's growing strength. And we've really set up for years of growth in data center. This is the largest segment of computing, as you know. And this segment of computing is going to continue to grow for some time to come.

最後是超級計算。世界各地的超級運算中心正在建設中，我們確實處於一個非常有利的位置，可以首次融合基於模擬的方法以及基於數據驅動的方法，即所謂的人工智慧。因此，我們的資料中心總體上正在獲得發展動力。我們看到——我們現在看到的是巨大的力量，而且還在不斷增長。我們確實為資料中心多年的發展做好了準備。如您所知，這是計算領域最大的部分。而這個計算領域在未來一段時間內也將持續成長。

And your next question comes from Aaron Rakers with Wells Fargo.

您的下一個問題來自富國銀行的 Aaron Rakers。

Congratulations on the results. I'm going to try to slip in 2 of them here. First of all, Colette, I think in the past, you talked about how much of your gaming installed base is kind of on the pre-ray tracing platforms, really kind of context behind the upgrade cycle that's still in front of us. That's kind of question one.

恭喜你取得這樣的成績。我將嘗試在這裡插入其中的 2 個。首先，科萊特，我想在過去，您談到有多少遊戲安裝基礎是在光線追蹤之前的平台上，這實際上是我們面前升級週期背後的背景。這是第一個問題。

And then on the heels of the last question, I'm just curious, things like VMware's Project Monterey, as we think about the BlueField-2 product and BlueField-3, how should we think about those starting to become -- or when should they become really material incremental revenue growth contributors for the company?

然後，緊接著最後一個問題，我很好奇，像 VMware 的 Project Monterey 這樣的產品，當我們考慮 BlueField-2 產品和 BlueField-3 時，我們應該如何看待它們開始成為——或者什麼時候它們應該成為公司真正實質性的增量收入增長貢獻者？

So yes, we have definitely discussed in terms of the great opportunity that we have in front of us of folks moving to our ray-traced GPUs, and we're in the early stages of that. We've had a strong cycle already, but still, we probably have approximately 15% moving up a little bit from that at this time. So it's a great opportunity for us to continue to upgrade a good part of that installed base, not only just with our desktop GPUs, but the RTX laptops are also a great driver of growth and upgrading folks to RTX.

是的，我們確實討論過我們面前的巨大機遇，即人們轉向我們的光線追蹤 GPU，而且我們正處於這一領域的早期階段。我們已經經歷了一個強勁的周期，但目前我們可能仍會比那時略有上升，約為 15%。因此，這對我們來說是一個很好的機會，可以繼續升級很大一部分已安裝的基礎產品，不僅僅是我們的桌上型電腦 GPU，而且 RTX 筆記型電腦也是成長和用戶升級到 RTX 的巨大推動力。

Colette, do you want me to take the second one?

科萊特，你想讓我拿第二個嗎？

Yes, please.

是的，請。

Yes. Aaron, great question on BlueField. First of all, the modern data center has to be rearchitected for several reasons. There are several fundamental reasons that makes it very, very clear that the architecture has to change. The first is it's cloud native, which means that a data center is shared for everybody. It's multi-tenant. You don't know who's coming and going, and it's exposed to everybody on the Internet.

是的。Aaron，關於 BlueField 的問題問得真好。首先，由於多種原因，現代資料中心必須重新架構。有幾個根本原因清楚地表明架構必須改變。首先是雲端原生，這意味著資料中心是供所有人共享的。它是多租戶的。你不知道誰來誰去，而且這些資訊在網路上對每個人都是公開的。

Number two, you have to assume that it's a zero-trust environment because you don't know who's using it. It used to be that we have perimeter security, but those days are gone because it's cloud native, it's remote access, it's multi-tenant, it's public cloud, the infrastructure is used for internal and external applications. So number two, it has to be zero trust.

第二，你必須假設這是一個零信任環境，因為你不知道誰在使用它。我們過去有周邊安全，但那些日子已經一去不復返了，因為它是雲端原生的，是遠端存取的，是多租戶的，是公有雲的，基礎設施用於內部和外部應用程式。所以第二點，它必須是零信任。

The third reason is something that started a long time ago, which is software-defined in every way because you don't want a whole bunch of bespoke custom gear inside the data center. You want to operate the data center with software. You want to be software-defined. The software-defined data center movement enabled this one pane of glass, a few IT managers orchestrating millions and millions of nodes of computers at one place.

第三個原因是很久以前就開始了的，即在各個方面都由軟體定義，因為你不希望在資料中心內放置一大堆客製化的設備。您想要使用軟體來操作資料中心。您希望實現軟體定義。軟體定義資料中心運動實現了這一單一玻璃窗格，少數 IT 經理可以在一個地方協調數百萬個電腦節點。

And the software runs what used to be storage, networking, security, virtualization, and all of that -- all of those things have become a lot larger and a lot more intensive. And it's consuming a lot of the data center. In fact, the estimate, depending on how you want to think about it, how much security you want to put on it, if you assume that is a zero-trust data center, probably half of the CPU cores inside that data center is running not applications. And that's kind of strange because you created the data center to run services and applications, which is the only thing that makes money.

該軟體運行著以前的儲存、網路、安全、虛擬化等功能——所有這些東西都變得更大、更密集。而且它消耗了大量的資料中心資源。事實上，這個估計取決於你如何思考，你想在它上面投入多少安全，如果你假設這是一個零信任資料中心，那麼該資料中心內可能有一半的 CPU 核心運行的不是應用程式。這有點奇怪，因為你創建資料中心是為了運行服務和應用程序，而這是唯一能賺錢的東西。

The other half of the computing is completely soaked up running the software-defined data center just to provide for those applications. And then you could imagine even accepting, if you like, as the cost of doing business. However, it co-mingles the infrastructure, the security plane and the application plane, and it exposes the data center to attackers.

另一半計算完全用於運行軟體定義的資料中心，只是為了滿足這些應用程式的需求。然後，如果你願意的話，你甚至可以想像接受它作為做生意的成本。然而，它混合了基礎設施、安全平面和應用平面，並將資料中心暴露給攻擊者。

And so you fundamentally want to change the architecture as a result of that to offload the software-defined virtualization and the infrastructure operating system, if you will, and the security services to accelerate it because Moore's Law has ended and moving software that was running on one set of CPUs, which is really, really good already, to another set of CPUs isn't going to make it more effective. Separating it doesn't make it more effective. And so you want to offload that and take that application and software and accelerate it using accelerators, a form of accelerated computing.

因此，你從根本上想要改變架構，以卸載軟體定義的虛擬化和基礎設施作業系統（如果你願意的話），以及安全服務來加速它，因為摩爾定律已經結束，將在一組 CPU 上運行的軟體（這已經非常非常好了）移動到另一組 CPU 上並不會使其更有效。將其分開並不會使其更有效。因此，您需要卸載該應用程式和軟體，並使用加速器（一種加速計算形式）對其進行加速。

And so that's -- these things are fundamentally what BlueField is all about. And we created the processor that allows us to -- BlueField-2 replaces approximately 30 CPU cores. BlueField-3 replaces approximately 300 CPU cores just to put -- give you a sense of it. And then BlueField-4, we're in the process of building already. And so we've got a really aggressive pipeline to do this.

這就是 —— 這些從根本上來說就是 BlueField 的意義所在。我們創建的處理器可以讓我們——BlueField-2 取代大約 30 個 CPU 核心。BlueField-3 取代了大約 300 個 CPU 核心，只是為了讓您了解一下。然後，我們已經開始建造 BlueField-4 了。因此，我們有一個非常積極的管道來實現這一目標。

Now how big is this market? The way to think about that is every single networking chip in the world -- every single networking chip in the world will be a smart networking chip. It will be a programmable accelerated infrastructure processor. And that's what the DPU is. It's a data center on a chip. And I believe every single server node will have it. It will replace today's mix with something like BlueField. And it will offload about half of the software processing that's consuming data centers today. But most importantly, it will enable this future world where every single packet, every single application is being monitored in real time all the time for intrusion.

那麼這個市場到底有多大呢？可以這樣想：世界上的每一個網路晶片——世界上的每一個網路晶片都將是一個智慧網路晶片。它將是一個可編程的加速基礎設施處理器。這就是 DPU。它是一個晶片上的數據中心。我相信每個伺服器節點都會有它。它將用 BlueField 之類的東西取代目前的混合物。它將卸載目前資料中心大約一半的軟體處理任務。但最重要的是，它將使未來的世界變得可能：每個資料包、每個應用程式都隨時受到即時監控，以防入侵。

And so how big is that application? How big is that market? Just 25 million servers a year, that's the size of the market. And we know that servers are growing, and so that will give you a feeling for that. And then in the future, servers are going to move out to the edge. And all of those edge devices will have something like BlueField.

那麼該應用程式有多大？這個市場有多大？每年僅 2500 萬台伺服器，這就是市場的規模。我們知道伺服器正在不斷增長，因此這將讓您感受到這一點。將來，伺服器將會移至邊緣。所有這些邊緣設備都會有類似 BlueField 的東西。

And then how are we doing? We're doing POCs now with just about every Internet company. We're doing really exciting work there. We've included it in high-performance computing so that it's possible for supercomputers in the future to be cloud native, to be zero trust, to be secured and still be a super computer.

那我們做得怎麼樣？我們現在正在與幾乎所有網路公司進行 POC。我們在那裡做著非常令人興奮的工作。我們將其納入高效能運算，以便未來的超級電腦能夠實現雲端原生、零信任、安全，並且仍然是超級電腦。

And then we expect next year to have a meaningful, if not significant, revenues contribution from BlueField, and this is going to be a really large growth market for us. You can tell I'm excited about this, and I put a lot of my energy into it. The company is working really hard on it. And this is a form of accelerated computing that's going to really make a difference.

我們預計明年 BlueField 的營收貢獻即便不顯著，也是有意義的，這對我們來說將是一個非常大的成長市場。你可以看出我對此感到很興奮，並且我為此投入了大量的精力。公司正在為此努力。這是一種真正能帶來改變的加速運算形式。

And your next question comes from Vivek Arya with Bank of America Securities.

您的下一個問題來自美國銀行證券的 Vivek Arya。

Jensen, is NVIDIA able to ring-fence this crypto impact in your CMP product? So even if, let's say, crypto goes away for whatever reason, the decline is a lot more predictable and manageable than what we saw in the 2018-'19 cycle. And then kind of part B of that is, how do you think about your core PC gamer demand? Because when we see this kind of 106% year-on-year growth rate, it brings questions of sustainability. So give us your perspectives on these 2 topics. Just how does one ring-fence kind of the crypto effect? And what do you think about the sustainability of your core PC gamer demand?

Jensen，NVIDIA 能否在你的 CMP 產品中隔離這種加密影響？因此，即使加密貨幣因某種原因消失，其跌幅也比我們在 2018-2019 年周期中看到的要預測和可控得多。那麼 B 部分是，您如何看待核心 PC 遊戲玩家的需求？因為當我們看到這種106%的年成長率時，我們就會對其永續性產生疑問。請就這兩個主題談談你的看法。那麼，加密圍欄究竟是如何發揮作用的呢？您認為核心 PC 遊戲玩家的需求是否具有永續性？

Sure. Thanks. First of all, it's hard to estimate exactly how much and where crypto mining is being done. However, we can only assume that the vast majority of it is contributed by professional miners, especially when the amount of mining increases tremendously like it has. And so we created CMP, and CMP and GeForce are not fungible. You could use GeForce for mining, but you can't use CMP for gaming. CMP is -- yields better, and producing those doesn't take away from the supply of GeForce. And so it protects our GeForce supply for the gamers.

當然。謝謝。首先，很難準確估計加密挖掘的數量和地點。然而，我們只能假設其中絕大部分是由專業礦工貢獻的，尤其是當挖礦量像現在這樣大幅增加的時候。因此我們創建了 CMP，並且 CMP 和 GeForce 是不可替代的。您可以使用 GeForce 進行挖礦，但不能使用 CMP 進行遊戲。CMP 的產量更高，而且生產 CMP 不會影響 GeForce 的供應。這樣它就可以保護我們為遊戲玩家提供的 GeForce 供應。

And the question that you have is what happens when -- on the tail end of this. There are several things that we hope. And we learned a lot from the last time, but you never learn enough about this dynamic. What we hope is that the CMPs will satisfy the miners and will stay in mines -- in the professional mines. And we're trying to produce a fair amount of them, and we have -- we've secured a lot of demand for the CMPs, and we'll fulfill it.

你的問題是，當這一切結束時，會發生什麼事。我們希望有幾件事。我們從上次的經驗中學到了很多，但你對這種動態的了解永遠不夠。我們希望CMP能夠讓礦工滿意並且留在礦場－專業礦場。我們正在嘗試生產相當數量的 CMP，我們已經確保了大量 CMP 的需求，我們將滿足這一需求。

And what makes it different this time is several things. One, we're in the beginning of our RTX cycle, whereas Pascal was the last GTX. And not only that, it was at the tail end of the GTX cycle. That was the last GTX and that was the tail end of the GTX cycle. We're at the very beginning of the RTX 30 cycle. And because we've reinvented computer graphics, we reset the computer industry. And after 3 years, the entire graphics industry has followed. Every game developer has moved to ray tracing. Every content developer and every content tool has moved to ray tracing. And so if you move to ray tracing, these applications are so much better, and they simply run too slow on GTX.

而這次的不同之處在於幾件事。首先，我們正處於 RTX 週期的開始階段，而 Pascal 是最後一款 GTX。不僅如此，它還處於 GTX 週期的末期。那是最後一個 GTX，也是 GTX 週期的尾聲。我們正處於 RTX 30 週期的開始階段。因為我們重新發明了電腦圖形學，所以我們重置了電腦產業。三年後，整個圖形產業也紛紛效法。每個遊戲開發商都已轉向光線追蹤。每個內容開發人員和每個內容工具都已轉向光線追蹤。因此，如果轉向光線追踪，這些應用程式會好得多，但它們在 GTX 上運行速度太慢了。

And so we're seeing a reset of the installed base, if you will. And at a time when the gaming market is the largest ever, we've got this incredible installed base of GeForce users. We've reinvented computer graphics, and we've reset the installed base and created an upgrade opportunity that's really exciting at a time when the market is -- the gaming market -- the gaming industry is really large. And what's really exciting on top of that is that gaming is no longer just gaming. But it's infused into sports, eSports. It's infused into art. It's infused into social.

因此，如果你願意的話，我們將看到安裝基礎的重置。在遊戲市場達到有史以來最大規模的當下，我們擁有了令人難以置信的 GeForce 用戶群。我們徹底改造了電腦圖形學，重置了安裝基礎，並創造了升級機會，這在遊戲市場（遊戲市場）規模龐大的時代確實令人興奮。而真正令人興奮的是，遊戲不再只是遊戲。但它融入了運動、電競。它融入了藝術之中。它融入了社交。

And so gaming has such a large cultural impact now. It's the largest form of entertainment. And I think that the experience we're going through is going to last a while. And so one, I hope that crypto will -- the CMP will steer our GeForce supply to gamers. We see strong demand, and I expect to see strong demand for quite some time because of the dynamics that I've described. And hopefully, in the combination of these 2, we'll see strong growth in -- through -- strong growth in our core game business through the year.

因此遊戲現在具有如此大的文化影響力。這是最大的娛樂形式。我認為我們正在經歷的這段經歷將會持續一段時間。因此，我希望加密貨幣——CMP 將引導我們向遊戲玩家提供 GeForce。我們看到了強勁的需求，根據我所描述的動態，我預計在相當長的一段時間內還會看到強勁的需求。希望透過這兩者之間的結合，我們的核心遊戲業務能夠在今年實現強勁成長。

And your next question comes from John Pitzer with Credit Suisse.

您的下一個問題來自瑞士信貸的約翰‧皮策 (John Pitzer)。

Jensen, I have 2 hopefully quick questions. First, I harken back to the mantra you guys put out a couple of analyst days ago, "The more you spend, the more you save." And you've always been very successful as you brought down the cost of doing something to really drive penetration growth. And so I'm curious with the NVIDIA enterprise AI software stack. Is there a sense that you can give us as to how much that brings down the cost of deployment in AI inside the enterprise? And do you think whether COVID lockdown related or cost related, there's pent-up demand that this unlocks?

詹森，我有兩個問題，希望是簡短的。首先，我回想起幾天前你們分析師提出的口頭禪：「花得越多，省得越多。」而且，你們一直都非常成功，因為你們降低了做某事的成本，真正推動了滲透率的增長。所以我對 NVIDIA 企業 AI 軟體堆疊很好奇。您能否告訴我們，這將在多大程度上降低企業內部部署人工智慧的成本？您是否認為，無論是與新冠疫情封鎖有關還是與成本有關，這都會釋放出被壓抑的需求？

And then my second question is just around government subsidies. A lot of talks out of Washington about subsidizing the chip industry. A lot of that goes towards building fabs domestically. But when I look at AI, I can't think of anything more important to maintain sort of leadership in relative to national security. How do we think about NVIDIA and kind of the impact that these government subsidies might have on either you or your customers or your business trends?

我的第二個問題是關於政府補貼。華盛頓有很多關於補貼晶片產業的討論。其中很大一部分用於在國內建造晶圓廠。但當我審視人工智慧時，我想不出還有什麼比維持國家安全的領導地位更重要。我們如何看待 NVIDIA 以及這些政府補貼可能會對您、您的客戶或您的業務趨勢產生什麼影響？

The more you buy, the more you shall save. There's no question about that. And the reason for that is because we're in the business of accelerated computing. We don't accelerate every application. However, for the applications we do accelerate, the acceleration is so dramatic. And because we sell a component, the entire system, the TCO, the TCO of the entire system and all the services and all the people and the infrastructure and the energy cost has been reduced by X factors, sometimes 10x, sometimes 15x, sometimes 5x.

買得越多，省得越多。毫無疑問。原因在於我們從事的是加速運算業務。我們不會加速每個應用程式。然而，對於我們確實加速的應用程式來說，加速是如此顯著。因為我們銷售一個組件，所以整個系統、TCO、整個系統、所有服務、所有人員、基礎設施和能源成本的 TCO 都降低了 X 倍，有時是 10 倍，有時是 15 倍，有時是 5 倍。

And so the -- but when we set our minds on excelling a certain class of applications -- and recently, we worked on quantum so that we could help the quantum industry -- quantum computing industry, accelerate their simulators so that they could discover new algorithms and embed future computers. Even though it won't happen until 2030, for the next 20 years, we're going to -- 15 years, we're going to have some really, really great work that we can do using NVIDIA GPUs to do quantum simulations.

所以 — — 但當我們下定決心要超越某一類應用程式時 — — 最近，我們致力於量子研究，以便我們可以幫助量子產業 — — 量子運算產業，加速他們的模擬器，以便他們能夠發現新的演算法並嵌入未來的電腦。儘管這要到 2030 年才能實現，但在接下來的 20 年裡，我們將——15 年裡，我們將利用 NVIDIA GPU 進行量子模擬，完成一些非常非常偉大的工作。

We recently did a lot of work in natural language understanding, in computational biology so that we could decode biology and understand how biology is -- to infer, to understand it and to predictably improve upon it and design new proteins. Those words are so vital, and that's what accelerated computing is all about.

我們最近在自然語言理解和計算生物學方面做了大量工作，以便我們能夠解讀生物學並了解生物學是如何進行的——推斷、理解它並可預見地改進它並設計新的蛋白質。這些話非常重要，這就是加速運算的意義。

Our enterprise software -- and I really appreciate the question. Our enterprise software used to be just about the vGPU, which is virtualizing the GPU inside the VMware environment or inside the Red Hat environment and makes it possible for multiple users to use one GPU, which is the nature of enterprise virtualization. But now with NVIDIA AI, NVIDIA Omniverse, NVIDIA Fleet Command, whether you're doing collaboration or virtual simulations for robotics and digital twins, designing your factory, or you're doing data analytics, learning what the predictive features are that could create an AI model, predictive model, then you can deploy out at the edge using Fleet Command.

我們的企業軟體—我非常感謝這個問題。我們的企業軟體以前只是關於vGPU，它是在VMware環境或是Red Hat環境裡面把GPU虛擬化，讓多個使用者可以使用一個GPU，這是企業虛擬化的本質。但現在有了 NVIDIA AI、NVIDIA Omniverse 和 NVIDIA Fleet Command，無論您是在進行機器人和數位孿生的協作或虛擬模擬、設計工廠，還是進行資料分析，了解可以建立 AI 模型、預測模型的預測功能，​​然後您就可以使用 Fleet Command 在邊緣進行部署。

We now have an end-to-end suite of software that is consistent with today's enterprise service agreements. It's consistent with today's enterprise business models and allows us to support customers directly and provide them with the necessary service promises that they expect because they're delivering -- they're trying to build a mission-critical application on top.

我們現在擁有與當今企業服務協議一致的端到端軟體套件。它與當今的企業業務模式一致，使我們能夠直接支援客戶並為他們提供他們期望的必要服務承諾，因為他們正在交付 - 他們正在嘗試在其上建立關鍵任務應用程式。

And more importantly, by creating this -- productizing our software, we provide the ability for our large network of partners, OEM partners, value-added resellers, system integrators, solution providers. For this large network of hundreds of thousands of IT sales professionals that we are connected to through our network, we give them a product that they can take to market.

更重要的是，透過將我們的軟體產品化，我們為龐大的合作夥伴網路、OEM 合作夥伴、加值經銷商、系統整合商、解決方案供應商提供了能力。對於我們透過網路連接的數十萬 IT 銷售專業人員所組成的龐大網絡，我們為他們提供可以推向市場的產品。

And so the distribution channel, the sales channel of VMware, the sales channel of Cloudera, the sales channel of all of our partners in EDA and design, Autodesk, Dassault, so on and so forth, all of these sales channels and all of these partners are now partners in taking our stacks to market. And we have a fully integrated system that are open to the OEMs so that they could create systems that run the stack. And it's all certified, all tested, all benchmarked and, of course, very importantly, all supported.

因此，分銷管道、VMware 的銷售管道、Cloudera 的銷售管道、我們在 EDA 和設計領域的所有合作夥伴的銷售管道、Autodesk、Dassault 等等，所有這些銷售管道和所有這些合作夥伴現在都是將我們的堆疊推向市場的合作夥伴。我們擁有一個完全整合的系統，該系統向 OEM 開放，以便他們可以創建運行堆疊的系統。而且它全部經過認證、全部經過測試、全部經過基準測試，當然，非常重要的是，全部都得到支持。

And so this new way of taking our products to market, whereas our cloud business is going to continue to grow and that part of AI is going to continue to grow, that business is direct. We sell components directly to them. We support them directly. But there are 10 of those customers in the world. For enterprises, there are thousands, industries far and wide. And so I think there's -- we now have a great stack and a great software stack that allows us to take it to the world's market so that everybody could buy more and save more.

因此，這種將我們的產品推向市場的新方式，以及我們的雲端業務將繼續成長和人工智慧部分將繼續成長，都是直接的業務。我們直接向他們銷售零件。我們直接支持他們。但世界上有 10 個這樣的客戶。對企業來說，有千萬個，產業廣泛。所以我認為——我們現在有一個很棒的堆疊和一個很棒的軟體堆棧，可以讓我們將其推向全球市場，以便每個人都可以購買更多並節省更多。

And your final question comes from Stacy Rasgon with Bernstein.

最後一個問題來自伯恩斯坦的史黛西‧拉斯貢 (Stacy Rasgon)。

I guess for Colette. So Colette, last quarter, you had kind of suggested that Q1 would be the trough, I guess, for the Gaming as well as the rest of the company, but Gaming in particular. And it would grow sequentially through the year. I guess given the strength we're seeing in the first half, do you still believe that, that is the case? And I kind of heard you guys, I think, kind of dance around that point a little bit in response to one of the other questions. But could you clarify that? Is that still your belief that, that core Gaming business can grow sequentially through the rest of the year?

我猜是為了 Colette。所以科萊特，上個季度，你曾暗示第一季將是遊戲部門以及公司其他部門的低谷，尤其是遊戲部門。而這一數字將在全年持續成長。我想，考慮到我們在上半年看到的強勁勢頭，你仍然相信情況確​​實如此嗎？我想，我聽到你們在回答另一個問題時，有點圍繞著這一點展開討論。但你能澄清一下嗎？您是否仍相信核心遊戲業務能夠在今年剩餘時間內持續成長？

And I guess same question as well for Data Center, especially since it sounds like hyperscale is now coming back like after a few quarters of digestion and then all of the other tailwinds you've talked about. I mean is there any reason to think the Data Center itself shouldn't also grow sequentially like through the rest of the year?

我想對於資料中心來說這也是同樣的問題，特別是因為聽起來超大規模現在正在回歸，就像經過幾個季度的消化以及您談到的所有其他順風之後一樣。我的意思是，有什麼理由認為資料中心本身不應該像今年剩餘時間一樣連續成長？

Yes. Stacy, thanks for the question. So first, I'll start with when we talked about our Q1 results and when we're looking at Q1, we were really discussing a lot about what we expected between Q4 and Q1. Given what we knew was still high demand for Gaming, we believe we will continue to grow between Q4 and Q1, which often we don't. And we absolutely have the strength of overall demand to grow. What that then led was, again, continued growth from Q1 to Q2 as we are working hard to provide more supply for the strong demand that we see. We have talked about that we have additional supply coming. We expect to continue to grow as we move into the second half of the year as well as for Gaming.

是的。史黛西，謝謝你的提問。首先，我將從我們談論第一季業績開始，當我們回顧第一季時，我們確實討論了很多關於第四季度和第一季度之間的預期。鑑於我們知道遊戲需求仍然很高，我們相信我們將在第四季度和第一季之間繼續成長，而通常情況並非如此。我們絕對擁有整體需求成長的實力。由於我們正在努力為強勁的需求提供更多的供應，因此這再次導致了從第一季到第二季的持續成長。我們已經討論過我們將有額外的供應。我們預計，隨著進入下半年，遊戲業務將繼續成長。

Now we only guide 1 quarter at a time, but our plan is to take the supply, serve the overall gamers, work on building out the channel. As we know, the channel is quite lean. And so yes, we do and still expect growth in the second half of the year, particularly when we see the lineup of games, the Holiday overall coming, the back-to-school, all very important cycles for us. And there's a great opportunity to upgrade this RTX installed base.

現在我們每次只指導一個季度，但我們的計劃是抓住機會，服務全球玩家，並努力拓展管道。我們知道，該頻道相當精簡。是的，我們確實預計下半年會成長，特別是當我們看到遊戲陣容、假期即將到來、返校季到來等對我們來說非常重要的周期時。這是一個很好的機會來升級這個 RTX 安裝基礎。

Now in terms of Data Center, we'll work in terms of our guidance here. We have growth from Q1 to Q2 planned in our overall guidance. And we do see as things continue to open up a time to accelerate in the second half of the year for Data Center. We have, again, a great lineup of products here, couldn't be a better lineup now that we've also added the inferencing products and the host of overall applications that are using our software that we have. So this could be an opportunity as well to see that continued growth. We'll work in terms of serving the supply that we need for both of these markets. But yes, we can see definitely growth in the second half of the year.

現在就資料中心而言，我們將按照此處的指導進行工作。我們的總體指導中計劃從第一季到第二季實現成長。我們確實看到，隨著事態的持續發展，資料中心在下半年將迎來加速發展的時刻。我們再次擁有一系列出色的產品，現在我們還添加了推理產品和使用我們現有軟體的大量整體應用程序，因此產品陣容再好不過了。因此，這也可能是實現持續成長的機會。我們將努力為這兩個市場提供所需的供應。但是的，我們確實可以看到下半年的成長。

There are no further questions at this time. CEO Jensen Huang, I'll turn the call back over to you.

目前沒有其他問題。首席執行官黃仁勳，我將把電話轉回給您。

Well, thank you. Thank you for joining us today. NVIDIA computing platform is accelerating. Launched at GTC, we are now ramping new platforms and initiatives. There are several that I'll mention.

好的，謝謝你。感謝您今天加入我們。NVIDIA運算平台正在加速發展。我們在 GTC 上推出了新的平台和計劃。我將提到其中的幾個。

First, enabled by the fusion of NVIDIA RTX, NVIDIA AI, NVIDIA [DGX], we built Omniverse, a platform for virtual collaboration and virtual worlds to enable tens of millions of artists and designers to create together in their own metaverses.

首先，透過 NVIDIA RTX、NVIDIA AI、NVIDIA [DGX] 的融合，我們建構了 Omniverse，這是一個虛擬協作和虛擬世界的平台，使數千萬藝術家和設計師能夠在自己的元宇宙中共同創作。

Second, we laid the foundation to be a 3-chip data center scale computing company with GPUs, DPUs and CPUs.

第二，我們奠定了成為擁有GPU、DPU、CPU的三晶片資料中心規模運算公司的基礎。

Third, AI is the most powerful technology force of our time. We partner with cloud and consumer Internet companies to scale out and commercialize AI-powered services. And we're democratizing AI for every enterprise and every industry. With NVIDIA EGX-certified systems, the NVIDIA enterprise AI suite, pre-trained models for conversational AI, language understanding, recommender systems and our broad partnerships across the IT industry, we are removing the barriers for every enterprise to access state-of-the-art AI.

第三，人工智慧是我們這個時代最強大的科技力量。我們與雲端和消費者互聯網公司合作，擴展和商業化人工智慧服務。我們正在讓人工智慧普及到每一個企業和每一個產業。借助 NVIDIA EGX 認證系統、NVIDIA 企業 AI 套件、對話式 AI 預訓練模型、語言理解、推薦系統以及我們在 IT 行業的廣泛合作夥伴關係，我們正在消除每個企業獲取最先進 AI 的障礙。

Fourth, the work of NVIDIA Clara in using AI to revolutionize genomics and biology is deeply impactful for the health care industry, and I look forward to telling you a lot more about this in the future.

第四，NVIDIA Clara 利用 AI 徹底改變基因組學和生物學的工作對醫療保健產業產生了深遠的影響，我期待在未來向大家介紹更多相關內容。

And fifth, the electric, self-driving and software-defined car is coming. With NVIDIA DRIVE, we are partnering with the global transportation industry to reinvent the car architecture, reinvent mobility, reinvent driving and reinvent the business model of the industry. Transportation is going to be one of the world's largest technology industries.

第五，電動、自動駕駛、軟體定義車即將到來。透過 NVIDIA DRIVE，我們正在與全球交通運輸業合作，重塑汽車架構、重塑移動性、重塑駕駛並重塑產業商業模式。交通運輸將成為世界上最大的技術產業之一。

From gaming, metaverses, cloud computing, AI, robotics, self-driving cars, genomics, computational biology, NVIDIA is doing important work in innovating in the fastest-growing markets today. As you can see, on top of our computing platforms that span PC, HPC, cloud, enterprise to autonomous edge, we've also transformed our business model beyond chips. NVIDIA vGPU, NVIDIA AI Enterprise, NVIDIA Fleet Command and NVIDIA Omniverse adds enterprise software license and subscription to our business model. And NVIDIA GeForce NOW and NVIDIA DRIVE with Mercedes-Benz as the lead partner are end-to-end services on top of that.

從遊戲、元宇宙、雲端運算、人工智慧、機器人、自動駕駛汽車、基因組學到運算生物學，NVIDIA 正在當今成長最快的市場中進行重要的創新工作。如您所見，在涵蓋 PC、HPC、雲端、企業到自主邊緣的運算平台上，我們也將我們的商業模式轉變為晶片以外的業務模式。NVIDIA vGPU、NVIDIA AI Enterprise、NVIDIA Fleet Command 和 NVIDIA Omniverse 為我們的商業模式添加了企業軟體授權和訂閱。而以賓士為主要合作夥伴的NVIDIA GeForce NOW和NVIDIA DRIVE則是在此基礎上提供的端對端服務。

I want to thank all of the NVIDIA employees and partners for the amazing work you're doing. We look forward to updating you on our progress next quarter. Thank you.

我要感謝所有 NVIDIA 員工和合作夥伴所做的出色工作。我們期待下個季度向您通報我們的進展。謝謝。

This concludes today's conference call. You may now disconnect.

今天的電話會議到此結束。您現在可以斷開連線。