輝達 (NVDA) 2020 Q1 法說會逐字稿

Good afternoon, my name is Christina, and I will be your conference operator today.

下午好，我叫克里斯蒂娜，今天我將擔任您的會議接線員。

Welcome to NVIDIA's financial results conference call.

歡迎參加 NVIDIA 的財務業績電話會議。

(Operator Instructions)

（操作員說明）

I'll now turn the call over to Simona Jankowski from Investor Relations to begin your conference.

我現在將電話轉給投資者關係部的 Simona Jankowski 開始您的會議。

Thank you.

謝謝你。

Good afternoon, everyone, and welcome to NVIDIA's Conference Call for the First Quarter of Fiscal 2020.

大家下午好，歡迎參加 NVIDIA 2020 財年第一季度電話會議。

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.

NVIDIA 總裁兼首席執行官黃仁勳今天與我通話；和 Colette Kress，執行副總裁兼首席財務官。

I'd like to remind you that our call is being webcast live on NVIDIA's Investor Relations website.

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。

The webcast will be available for replay until the conference call to discuss our financial results for the second quarter of fiscal 2020.

在電話會議討論我們 2020 財年第二季度的財務業績之前，該網絡廣播將可供重播。

The content of today's call is NVIDIA's property.

今天通話的內容是 NVIDIA 的財產。

It can't be reproduced or transcribed without our prior written consent.

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.

在本次電話會議期間，我們可能會根據當前預期做出前瞻性陳述。

These are subject to a number of significant risks and uncertainties, and our actual results may differ materially.

這些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。

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.

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 表格中與證券交易委員會。

All our statements are made as of today, May 16, 2019, based on information currently available to us.

我們所有的聲明都是基於我們目前可獲得的信息，截至今天，2019 年 5 月 16 日。

Except as required by law, we assume no obligation to update any such statements.

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.

在本次電話會議中，我們將討論非 GAAP 財務指標。

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.

您可以在我們的 CFO 評論中找到這些非 GAAP 財務指標與 GAAP 財務指標的對賬，該評論發佈在我們的網站上。

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.

謝謝，西蒙娜。

Q1 revenue was $2.2 billion, in line with our outlook and down 31% year-on-year and up 1% sequentially.

第一季度收入為 22 億美元，符合我們的預期，同比下降 31%，環比增長 1%。

Starting with our gaming business.

從我們的遊戲業務開始。

Revenue of $1.05 billion was down 39% year-on-year and up 11% sequentially, consistent with our expectations.

收入為 10.5 億美元，同比下降 39%，環比增長 11%，符合我們的預期。

We are pleased with the initial ramp of Turing and the reduction of inventory in the channel.

我們對圖靈的初始增長和渠道庫存的減少感到滿意。

During the quarter, we filled out our Turing lineup with the launch of midrange GeForce products that enable us to delight gamers with the best performance at every price point starting at $149.

在本季度，我們推出了中端 GeForce 產品，豐富了我們的 Turing 產品線，這些產品使我們能夠以 149 美元起的每個價位以最佳性能取悅遊戲玩家。

New product launches this quarter included the GeForce GTX 1660 Ti, 1660 and 1650, which bring Turing to the high-volume PC gaming segment for both desktop and laptop.

本季度推出的新產品包括 GeForce GTX 1660 Ti、1660 和 1650，它們將 Turing 帶入了台式機和筆記本電腦的大容量 PC 遊戲領域。

These GPUs deliver up to 50% performance improvement over their Pascal-based predecessors, leveraging new share innovations such as concurrent floating point and integer operations, a unified cache and Adaptive Shading, all with the incredibly power-efficient architecture.

這些 GPU 與基於 Pascal 的前代產品相比，性能提升高達 50%，利用了新的共享創新，例如並發浮點和整數運算、統一緩存和自適應著色，所有這些都具有令人難以置信的節能架構。

We expect continued growth in the gaming laptops this year.

我們預計今年遊戲筆記本電腦將繼續增長。

GeForce gaming laptops are one of the shining spots of the consumer PC market.

GeForce 遊戲筆記本電腦是消費類 PC 市場的亮點之一。

This year, OEMs have built a record of nearly 100 GeForce gaming laptops.

今年，OEM 製造了近 100 台 GeForce 遊戲筆記本電腦，創下了記錄。

GeForce laptops start at $799 and all the way up to an amazing GeForce RTX 2080 4K laptops that are more powerful than even next-generation consoles.

GeForce 筆記本電腦的起價為 799 美元，一直到令人驚嘆的 GeForce RTX 2080 4K 筆記本電腦，甚至比下一代遊戲機更強大。

The content ecosystem for ray-traced games is gaining significant momentum.

光線追踪遊戲的內容生態系統正在獲得顯著的發展勢頭。

At the March Game Developers Conference, ray-tracing sessions were packed.

在 3 月的遊戲開發者大會上，光線追踪會議座無虛席。

Support for ray tracing was announced by the industry's most important game engines, Microsoft DXR, Epic's Unreal Engine and Unity.

業界最重要的遊戲引擎 Microsoft DXR、Epic 的 Unreal Engine 和 Unity 都宣布支持光線追踪。

Ray tracing will be the standard for next-generation games.

光線追踪將成為下一代遊戲的標準。

In March, at our GPU Technology Conference, we also announced more details on our cloud gaming strategies through our GeForce NOW service and the newly announced GFN Alliance.

3 月，在我們的 GPU 技術大會上，我們還通過 GeForce NOW 服務和新宣布的 GFN 聯盟公佈了有關我們雲遊戲戰略的更多細節。

GeForce NOW is a GeForce gaming PC in the cloud for the 1 billion PCs that are not game-ready, expanding our reach well beyond today's 200 million GeForce gamers.

GeForce NOW 是一款雲中的 GeForce 遊戲 PC，適用於 10 億台尚未準備好遊戲的 PC，將我們的覆蓋範圍擴大到今天的 2 億 GeForce 遊戲玩家之外。

It's an open platform that allows gamers to play the games they own instantly in the cloud on any PC or Mac anywhere they like.

這是一個開放平台，允許遊戲玩家在任何他們喜歡的任何地方的任何 PC 或 Mac 上立即在雲中玩他們擁有的遊戲。

The service currently has 300,000 monthly active users with 1 million more on the waitlist.

該服務目前每月有 30 萬活躍用戶，候補名單上還有 100 萬用戶。

To scale out to millions of gamers worldwide, we announced the GeForce NOW Alliance, expanding GFN through partnerships with the global telecom providers.

為了擴展到全球數百萬遊戲玩家，我們宣布成立 GeForce NOW 聯盟，通過與全球電信提供商的合作來擴展 GFN。

Softbank in Japan and LG Uplus in South Korea will be among the first to launch GFN later this year.

日本的軟銀和韓國的 LG Uplus 將率先在今年晚些時候推出 GFN。

NVIDIA will develop the software and manage the service and share the subscription revenue with alliance partners.

NVIDIA 將開發軟件和管理服務，並與聯盟合作夥伴分享訂閱收入。

GFN runs on NVIDIA's edge computing servers.

GFN 在 NVIDIA 的邊緣計算服務器上運行。

As telcos race to offer the new services for their 5G network, GFN is an ideal new 5G application.

隨著電信公司競相為其 5G 網絡提供新服務，GFN 是一個理想的 5G 新應用。

Moving to data center.

搬到數據中心。

Revenue was $634 million, down 10% year-on-year and down 7% sequentially, reflecting the pause in hyperscale spending.

收入為 6.34 億美元，同比下降 10%，環比下降 7%，反映出超大規模支出的暫停。

While demand from some hyperscale customers bounced back nicely, others paused or cut back.

雖然一些超大規模客戶的需求很好地反彈，但其他人則暫停或削減。

Despite the uneven demand drop -- backdrop, the quarter had significant positives consistent with the growth drivers we outlined on our previous earnings call.

儘管需求下降不均衡——背景下，本季度的顯著積極因素與我們在之前的財報電話會議上概述的增長驅動力一致。

First, inference revenue was up sharply both year-on-year and sequentially with broad-based adoption across a number of hyperscale and consumer Internet companies.

首先，隨著許多超大規模和消費互聯網公司的廣泛採用，推理收入同比和環比都大幅增長。

As announced at GTC, Amazon and Alibaba joined other hyperscalers such as Google, Baidu and Tencent in adopting the T4 in their data centers.

正如在 GTC 上宣布的那樣，亞馬遜和阿里巴巴與穀歌、百度和騰訊等其他超大規模企業一起在其數據中心採用了 T4。

A growing list of consumer Internet companies is also adapting our GPUs for inference, including LinkedIn, Expedia, Microsoft, PayPal, Pinterest, Snap and Twitter.

越來越多的消費互聯網公司也在調整我們的 GPU 以進行推理，包括 LinkedIn、Expedia、Microsoft、PayPal、Pinterest、Snap 和 Twitter。

The contribution of inference to our data center revenue is now well into the double-digit percent.

推理對我們數據中心收入的貢獻現在已經達到兩位數的百分比。

Second, we expanded our reach in enterprise, teaming up with major OEMs to introduce the T4 enterprise and edge computing servers.

其次，我們擴大了在企業領域的影響力，與主要 OEM 合作推出 T4 企業和邊緣計算服務器。

These are optimized to run the NVIDIA CUDA-X AI acceleration libraries for AI and data analytics.

它們經過優化，可運行用於 AI 和數據分析的 NVIDIA CUDA-X AI 加速庫。

With an easy-to-deploy software stack from NVIDIA and our ecosystem partners, this wave of NVIDIA edge AI computing systems enables companies in the world's largest industries, transportation, manufacturing, industrial, retail, health care and agricultural, to bring intelligence to the edge where the customers operate.

借助 NVIDIA 和我們的生態系統合作夥伴提供的易於部署的軟件堆棧，這一波 NVIDIA 邊緣 AI 計算系統使世界上最大的行業（運輸、製造、工業、零售、醫療保健和農業）的公司能夠將智能帶到客戶操作的邊緣。

And third, we made significant progress in data center rendering and graphics.

第三，我們在數據中心渲染和圖形方面取得了重大進展。

We unveiled a new RTX Server configuration packing 40 GPUs into an 8 use case and up to 32 servers in a pod, providing unparalleled density, efficiency and scalability.

我們推出了一種新的 RTX 服務器配置，將 40 個 GPU 打包到一個 8 個用例中，一個 Pod 中最多包含 32 個服務器，提供無與倫比的密度、效率和可擴展性。

With a complete stack, this server design is optimized for 3 data center graphic workloads: rendering, remote workstations and cloud gaming.

憑藉完整的堆棧，該服務器設計針對 3 個數據中心圖形工作負載進行了優化：渲染、遠程工作站和雲遊戲。

The rendering opportunity is starting to take shape with early RTX Server deployments at leading studios, including Disney, Pixar and Weta.

隨著迪士尼、皮克斯和維塔等領先工作室的早期 RTX 服務器部署，渲染機會開始形成。

In the quarter, we announced our pending acquisition of Mellanox for $125 per share in cash, representing a total enterprise value of approximately $6.9 billion, which we believe will strengthen our strategic position in data center.

在本季度，我們宣布以每股 125 美元的現金收購 Mellanox，企業總價值約為 69 億美元，我們相信這將加強我們在數據中心的戰略地位。

Once complete, the acquisition will unite 2 of the world's leading companies in high-performance computing.

收購完成後，將聯合兩家全球領先的高性能計算公司。

Together, NVIDIA's computing platform and Mellanox's interconnects power over 250 of the world's TOP500 supercomputer and have as customers every major cloud service provider and computer maker.

NVIDIA 的計算平台和 Mellanox 的互連共同為全球 250 多台 TOP500 超級計算機提供動力，並擁有所有主要雲服務提供商和計算機製造商的客戶。

Data centers in the future will be architected as giant compute engines with tens of thousands of compute nodes designed holistically with their interconnects for optimal performance.

未來的數據中心將被構建為巨大的計算引擎，具有數以萬計的計算節點，它們的互連整體設計以實現最佳性能。

With Mellanox, NVIDIA will optimize data center scale workloads across the entire computing, networking and storage stack to achieve higher performance, greater utilization and lower operating cost for customers.

借助 Mellanox，NVIDIA 將在整個計算、網絡和存儲堆棧中優化數據中心規模的工作負載，從而為客戶實現更高的性能、更高的利用率和更低的運營成本。

Together, we can create better AI computing systems for the cloud to enterprise to the edge.

我們可以一起創建更好的人工智能計算系統，從雲到企業到邊緣。

As stated at the time of the announcement, we look forward to closing the acquisition by the end of this calendar year.

如公告時所述，我們期待在本日曆年年底前完成收購。

Moving to pro visualization.

轉向專業可視化。

Revenue reached $266 million, up 6% from the prior year and down 9% sequentially.

收入達到 2.66 億美元，比上年增長 6%，環比下降 9%。

Year-on-year growth was driven by both desktop and mobile workstations, while the sequential decline was largely seasonal.

台式機和移動工作站均推動了同比增長，而環比下降主要是季節性的。

Areas of strength included the public sector, oil and gas and manufacturing.

優勢領域包括公共部門、石油和天然氣以及製造業。

Emerging applications, such as AI, AR, VR, contributed an estimated 38% of pro visualization revenue.

AI、AR、VR 等新興應用貢獻了專業可視化收入的 38%。

The real-time ray-tracing capabilities of RTX are a game changer for the visual effects industry, and we are seeing tremendous momentum in the ecosystem.

RTX 的實時光線追踪功能改變了視覺效果行業的遊戲規則，我們看到了生態系統的巨大發展勢頭。

At GTC, we announced that the world's top 3D application providers have adopted NVIDIA RTX in their product releases set for later this year, including Adobe, Autodesk, Chaos Group, Dassault and Pixar.

在 GTC 上，我們宣布全球頂級 3D 應用程序提供商已在其將於今年晚些時候發布的產品中採用了 NVIDIA RTX，其中包括 Adobe、Autodesk、Chaos Group、Dassault 和 Pixar。

With this rich software ecosystem, NVIDIA RTX is transforming the 3D market.

憑藉這個豐富的軟件生態系統，NVIDIA RTX 正在改變 3D 市場。

For example, Pixar is using NVIDIA RTX ray tracing on its upcoming films.

例如，皮克斯正在其即將上映的電影中使用 NVIDIA RTX 光線追踪。

Weta Digital is using it for upcoming Disney projects and Siemens NX ray-traced studios users will be able to generate rendered images up to 4x faster in their product design workloads.

Weta Digital 將其用於即將推出的迪士尼項目，而 Siemens NX 光線追踪工作室用戶將能夠在其產品設計工作負載中以高達 4 倍的速度生成渲染圖像。

We are excited to see the tremendous value that NVIDIA RTX is bringing to the millions of creators and designers served by ecosystem partners.

我們很高興看到 NVIDIA RTX 為生態系統合作夥伴所服務的數百萬創作者和設計師帶來的巨大價值。

Finally, turning to automotive.

最後，轉向汽車。

Q1 revenue was $166 million, up 14% from a year ago and up 2% sequentially.

第一季度收入為 1.66 億美元，同比增長 14%，環比增長 2%。

Year-on-year growth was driven by growing adoption of next-generation AI cockpit solutions and autonomous vehicle development deals.

同比增長是由越來越多地採用下一代人工智能駕駛艙解決方案和自動駕駛汽車開發交易推動的。

At GTC, we had major customer and product announcements.

在 GTC，我們發布了主要的客戶和產品公告。

Toyota selected NVIDIA's end-to-end platform to develop, train and validate self-driving vehicles.

豐田選擇 NVIDIA 的端到端平台來開發、訓練和驗證自動駕駛汽車。

This broad partnership includes advancements in AI computing, infrastructure using NVIDIA GPUs, simulation using NVIDIA DRIVE Constellation platform and in-car AV computers based on the DRIVE AGX Xavier or Pegasus.

這種廣泛的合作夥伴關係包括人工智能計算的進步、使用 NVIDIA GPU 的基礎設施、使用 NVIDIA DRIVE Constellation 平台的模擬以及基於 DRIVE AGX Xavier 或 Pegasus 的車載 AV 計算機。

We also announced the public availability of DRIVE Constellation, which enables millions of miles to be driven in virtual worlds across the broad range of scenarios with greater efficiency, cost effectiveness and safety than what's possible to achieve in the real world.

我們還宣布了 DRIVE Constellation 的公開可用性，它可以在虛擬世界中跨越廣泛的場景駕駛數百萬英里，比在現實世界中實現的效率、成本效益和安全性更高。

Constellation will be reported in our data center market platform.

星座將在我們的數據中心市場平台上報告。

And we introduced NVIDIA Safety Force Field, a computational defensive driving framework that shields autonomous vehicles from collisions.

我們還推出了 NVIDIA 安全力場，這是一種計算防禦性駕駛框架，可以保護自動駕駛汽車免受碰撞。

Mathematically verified and validated in simulation, Safety Force Field will prevent a vehicle from creating, escalating or contributing to an unsafe driving situation.

在模擬中經過數學驗證和驗證，安全力場將防止車輛產生、升級或促成不安全的駕駛情況。

We continue to believe that every vehicle will have an autonomous capability one day, whether with a driver or driverless.

我們仍然相信，每輛車總有一天會具備自動駕駛能力，無論是有司機還是無人駕駛。

To help make that vision a reality, NVIDIA has created an end-to-end platform for autonomous vehicles from AI computing infrastructure to simulation to in-car computing.

為了幫助實現這一願景，NVIDIA 為自動駕駛汽車創建了一個端到端平台，從人工智能計算基礎設施到模擬再到車載計算。

And Toyota is our first major win that validates this strategy.

豐田是我們第一個驗證這一戰略的重大勝利。

We see this as a $30 billion addressable market by 2025.

我們認為，到 2025 年，這是一個價值 300 億美元的潛在市場。

Moving to the rest of the P&L and balance sheet.

轉到損益表和資產負債表的其餘部分。

Q1 GAAP gross margin was 58.4% and non-GAAP was 59%, down year-on-year to lower gaming margins and mix, up sequentially from Q4, which had $128 million charge from DRAM boards and other components.

第一季度 GAAP 毛利率為 58.4%，非 GAAP 毛利率為 59%，同比下降，以降低遊戲利潤率和組合，高於第四季度的 1.28 億美元來自 DRAM 板和其他組件的費用。

GAAP operating expenses were $938 million, and non-GAAP operating expenses were $753 million, up 21% and 16% year-on-year, respectively.

GAAP運營費用為9.38億美元，非GAAP運營費用為7.53億美元，同比分別增長21%和16%。

We remain on track for high single-digit OpEx growth in fiscal 2020 while continuing to invest in the key platforms driving our long-term growth, namely graphics, AI and self-driving cars.

我們將在 2020 財年保持高個位數的運營支出增長，同時繼續投資於推動我們長期增長的關鍵平台，即圖形、人工智能和自動駕駛汽車。

GAAP EPS was $0.64, and non-GAAP EPS was $0.88.

GAAP EPS 為 0.64 美元，非 GAAP 每股收益為 0.88 美元。

We did not make any stock repurchases in the quarter.

我們在本季度沒有進行任何股票回購。

Following the announcement of the pending Mellanox acquisition, we remain committed to returning $3 billion to shareholders through the end of fiscal 2020 in the form of dividends and repurchases.

在宣布即將進行的 Mellanox 收購後，我們仍致力於在 2020 財年末以股息和回購的形式向股東返還 30 億美元。

So far, we have returned $800 million through share repurchases and quarterly cash dividends.

到目前為止，我們通過股票回購和季度現金股息返還了 8 億美元。

With that, let me turn to the outlook for the second quarter of fiscal 2020.

有了這個，讓我轉向 2020 財年第二季度的展望。

While we anticipate substantial quarter-over-quarter growth, our Q2 outlook is somewhat lower than our expectations earlier in the quarter where our outlook for fiscal 2020 revenue was flat to down slightly from fiscal 2019.

雖然我們預計季度環比大幅增長，但我們的第二季度展望略低於我們在本季度早些時候的預期，我們對 2020 財年收入的展望與 2019 財年持平或略有下降。

The data center spending pause around the world will likely persist in the second quarter, and visibility remains low.

全球數據中心支出暫停可能會持續到第二季度，可見度仍然很低。

In gaming, the CPU shortages while improving will affect the initial ramp of our laptop business.

在遊戲方面，CPU 短缺在改善的同時將影響我們筆記本電腦業務的初始增長。

For Q2, we expect revenue to be $2.55 billion, plus or minus 2%.

對於第二季度，我們預計收入為 25.5 億美元，上下浮動 2%。

We expect a stronger second half than the first half, and we are returning to our practice of providing revenue outlook one quarter at a time.

我們預計下半年將比上半年更強勁，並且我們正在恢復我們一次提供一個季度的收入前景的做法。

Q2 GAAP and non-GAAP gross margins are expected to be 59.2% and 59.5%, respectively, plus or minus 50 basis points.

第二季度 GAAP 和非 GAAP 毛利率預計分別為 59.2% 和 59.5%，上下浮動 50 個基點。

GAAP and non-GAAP operating expenses are expected to be approximately $985 million, $765 million, respectively.

GAAP 和非 GAAP 運營費用預計分別約為 9.85 億美元和 7.65 億美元。

GAAP and non-GAAP OI&E are both expected to be income of approximately $27 million.

GAAP 和非 GAAP OI&E 預計收入約為 2700 萬美元。

GAAP and non-GAAP tax rates are both expected to be 10%, plus or minus 1%, excluding discrete items.

GAAP 和非 GAAP 稅率預計均為 10%，正負 1%，不包括離散項目。

Capital expenditures are expected to be approximately $120 million to $140 million.

資本支出預計約為 1.2 億至 1.4 億美元。

Further financial details are included in the CFO commentary and other information available on our IR website.

更多財務細節包含在 CFO 評論和我們投資者關係網站上提供的其他信息中。

In closing, let me highlight upcoming events for the financial community.

最後，讓我強調一下金融界即將發生的事件。

We'll be presenting at the Bank of America Global Technology Conference on June 5, at the RBC Future of Mobility Conference on June 6 and at the NASDAQ investor conference on June 13.

我們將出席 6 月 5 日的美國銀行全球技術會議、6 月 6 日的 RBC 未來移動會議和 6 月 13 日的納斯達克投資者會議。

Our next earnings call to discuss financial results for the second quarter of fiscal 2020 will take place on August 15.

我們將在 8 月 15 日召開下一次財報電話會議，討論 2020 財年第二季度的財務業績。

We will now open the call for questions.

我們現在將打開問題的電話。

Operator, will you please poll for questions?

接線員，請您投票提問嗎？

Thank you.

謝謝你。

(Operator Instructions) Your first question comes from the line of Aaron Rakers with Wells Fargo.

（操作員說明）您的第一個問題來自富國銀行的 Aaron Rakers。

Colette, I was wondering if you could give a little bit more color or discussion around what exactly you've seen in the data center segment and whether or not or what you're looking for in terms of signs that we can kind of return to growth or maybe this pause is behind us.

Colette，我想知道您是否可以就您在數據中心領域所看到的確切情況以及您是否或正在尋找什麼我們可以返回的跡象提供更多顏色或討論增長，或者這種停頓已經過去了。

I guess what I'm really asking is kind of what's changed over the last, let's call it, 3 months relative to your prior commentary from a visibility perspective and just demand perspective within that segment.

我想我真正要問的是，從可見性的角度來看，相對於您之前的評論，過去 3 個月發生了變化，並且只是在該細分市場中的需求角度。

Sure.

當然。

Thanks for the question as we start out here.

感謝我們從這裡開始的問題。

I think when we had discussed our overall data center business 3 months ago, we did indicate that our visibility as we turned into the new calendar year was low.

我認為，當我們 3 個月前討論我們的整體數據中心業務時，我們確實表示在進入新日曆年時我們的知名度很低。

We had a challenge in terms of completing some of the deals at the end of that quarter.

我們在該季度末完成一些交易方面遇到了挑戰。

As we moved into Q1, I think we felt solid in terms of how we completed.

當我們進入第一季度時，我認為我們在如何完成方面感覺很穩定。

We saw probably a combination of those moving forward continuing with their CapEx expenditures and building out in terms of what they need for the data centers.

我們可能看到了那些繼續推進資本支出並根據數據中心需求進行建設的人的組合。

Some others are still in terms of the pause.

其他一些人仍然處於停頓狀態。

So as we look in terms of with Q2, I think we see a continuation of what we have in terms of the visibility, not the best visibility going forward but still rock-solid to what we think are benefits of what we provide in terms of a platform.

因此，當我們從第二季度的角度來看，我認為我們看到了我們在可見性方面的延續，而不是未來的最佳可見性，但仍然堅如磐石，我們認為我們提供的好處是一個平台。

Our overall priorities are aligned to what we see with the hyperscalers as well as the enterprises as they think about using AI in so many of their different workloads.

我們的總體優先事項與我們對超大規模企業和企業的看法一致，因為他們考慮在許多不同的工作負載中使用人工智能。

But we'll just have to see as we go forward how this turns out.

但我們只需要看看我們前進的結果如何。

But right now, visibility probably just remains the same about as where we were when we started 3 months ago.

但現在，能見度可能與我們 3 個月前開始時的情況一樣。

Okay.

好的。

And then as a quick follow-up on the gaming side, last quarter, you talked about that being down -- I think it was termed as being down slightly for the full year.

然後作為遊戲方面的快速跟進，上個季度，你談到了下降 - 我認為它被稱為全年略有下降。

Is that still the expectation?

這還是期待嗎？

Or how has that changed?

或者這有什麼變化？

So at this time, we don't plan on giving a full year overall guidance.

因此，目前，我們不打算提供全年的總體指導。

I think our look in terms of gaming, all of the drivers that we thought about earlier in the quarter and we talked about on our Investor Day and we have continued to talk about are still definitely in line.

我認為我們在遊戲方面的看法，我們在本季度早些時候考慮過的所有驅動因素，我們在投資者日討論過並且我們繼續討論的所有驅動因素都絕對符合。

The drivers of our gaming business and Turing RTX for the future are still on track, but we're not providing guidance at this time for the full year.

我們的遊戲業務和 Turing RTX 未來的驅動力仍在正軌上，但我們目前並未提供全年的指導。

And your next question comes from the line of Harlan Sur of JPMorgan.

您的下一個問題來自摩根大通的 Harlan Sur。

On the last earnings call, you'd mentioned China gaming demand as a headwind.

在上次財報電話會議上，您提到中國遊戲需求是不利因素。

At the Analyst Day in mid-March, I think Jensen had mentioned that the team was already starting to see better demand trends out of China maybe given the relaxed stance on gaming bans.

在 3 月中旬的分析師日，我認為 Jensen 曾提到團隊已經開始看到來自中國的更好的需求趨勢，這可能是因為對遊戲禁令的寬鬆立場。

Do you anticipate continued China gaming demand on a go-forward basis?

您是否預計中國遊戲需求將繼續向前發展？

And maybe talk about some of the dynamics driving that demand profile in the China geography.

或許可以談談推動中國地區需求狀況的一些動力。

Sure.

當然。

China looks fine.

中國看起來不錯。

I think China has stabilized.

我認為中國已經穩定了。

The gaming market in China is really vibrant, and it continues to be vibrant.

中國的遊戲市場確實充滿活力，而且還在繼續充滿活力。

Tencent's releasing new games.

騰訊推出新遊戲。

I think you might have heard that Epic stores now are open in Asia, and games are available from the West.

我想你可能聽說過 Epic 商店現在在亞洲開張，而遊戲也可以從西方獲得。

So there are all kinds of positive signs in China.

所以在中國有各種積極的跡象。

There are some 300 million PC gamers in China, and people are expecting it to grow.

中國有大約 3 億 PC 遊戲玩家，人們期待它會增長。

We're expecting the total number of gamers to continue to grow from the 1-plus billion PC gamers around the world to something more than that.

我們預計遊戲玩家總數將從全球超過 10 億的 PC 遊戲玩家繼續增長到更多。

And so things look fine.

所以事情看起來很好。

And then as a follow-up, a big part of the demand profile in the second half of the year for the gaming business is always the lineup of AAA-rated games.

然後作為後續，下半年遊戲業務需求的很大一部分始終是AAA級遊戲的陣容。

Obviously, you guys have a very close partnership with all of the game developers.

顯然，你們與所有遊戲開發商有著非常密切的合作關係。

How does the pipeline of new games look?

新遊戲的流水線如何？

Kind of they get launched October, November time frame, either total number of blockbuster games and also games supporting real-time ray tracing as well as some of your DLSS capabilities.

它們會在 10 月、11 月的時間範圍內發布，包括大片遊戲的總數以及支持實時光線追踪的遊戲以及您的一些 DLSS 功能。

Yes.

是的。

Well, it's seasonal.

嗯，是季節性的。

Second half of the year, we expect to see some great games.

今年下半年，我們期待看到一些精彩的比賽。

We won't preannounce anybody else's games for them, but this is a great PC cycle because it's the end of the console cycle, and PCs is just where the action's at these days with battle royale and eSports and so much social going on, the PC gaming ecosystem is just really vibrant.

我們不會為他們預先宣布其他任何人的遊戲，但這是一個很棒的 PC 週期，因為它是主機週期的結束，而 PC 正是這些天隨著大逃殺和電子競技以及如此多的社交活動發生的地方， PC 遊戲生態系統非常活躍。

Our strategy with RTX was to take a lead and move the world to ray tracing.

我們與 RTX 的戰略是帶頭並推動世界走向光線追踪。

And at this point, it's fairly, fairly safe to say that the leadership position that we've taken has turned into a movement that has turned next-generation gaming ray tracing into a standard.

在這一點上，可以相當、相當肯定地說，我們所佔據的領導地位已經轉變為將下一代遊戲光線追踪轉變為標準的運動。

Almost every single game platform will have to have ray tracing, and some of them already announced it.

幾乎每一個遊戲平台都必須有光線追踪，其中一些已經宣布了。

And the partnerships that we've developed are fantastic.

我們建立的合作夥伴關係非常棒。

Microsoft DXR is supporting ray tracing.

Microsoft DXR 支持光線追踪。

Unity is supporting ray tracing.

Unity 支持光線追踪。

Epic is supporting ray tracing.

Epic 支持光線追踪。

Leading publishers like EA has adopted RTX and supporting ray tracing.

EA 等領先發行商已採用 RTX 並支持光線追踪。

And movie studios, Pixar has adopted -- announced that they're using RTX and will use RTX to accelerate their rendering of films.

皮克斯已經採用了電影工作室——宣布他們正在使用 RTX，並將使用 RTX 來加速他們的電影渲染。

And so Adobe and Autodesk jumped on top -- jumped onto RTX and will bring ray tracing to their content and their tools.

因此，Adobe 和 Autodesk 躍居榜首——加入了 RTX，並將光線追踪帶到他們的內容和工具中。

And so I think at this point, it's fair to say that ray tracing is the next generation and is going to be adopted all over the world.

所以我認為在這一點上，可以公平地說光線追踪是下一代並且將在世界範圍內被採用。

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

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

I guess the first question is for Colette.

我想第一個問題是給科萊特的。

So what went into the decision to pull full year guidance versus just cutting it?

那麼是什麼決定了取消全年指導而不是僅僅削減它呢？

Is it really to see around how long it could take for data center to come back?

真的要看看數據中心需要多長時間才能恢復嗎？

Yes.

是的。

I'll start off here and kind of go back to where our thoughts were in Q1 and why we provided full year guidance when we were in Q1.

我將從這裡開始，回到我們在第一季度的想法以及為什麼我們在第一季度提供全年指導。

When we looked at Q1 and what we were guiding, we understood that it was certainly an extraordinary quarter, something that we didn't feel was a true representative of our business, and we wanted to get a better view of our trajectory of our business in terms of going forward.

當我們查看第一季度和我們的指導時，我們明白這肯定是一個非凡的季度，我們認為這不是我們業務的真正代表，我們希望更好地了解我們的業務軌跡在前進方面。

We are still experiencing, I think, the uncertainty as a result of the pause in terms of with the overall hyperscale data centers.

我認為，由於整個超大規模數據中心的暫停，我們仍在經歷不確定性。

And we do believe that's going to extend into Q2.

我們確實相信這將延續到第二季度。

However, we do know and expect that our Q2 -- or excuse me, our H2 will likely be sizably larger than our overall H1, and the core dynamics of our business at every level is exactly what we expected.

但是，我們確實知道並期望我們的第二季度 - 或者對不起，我們的 H2 可能會比我們的整體 H1 大得多，我們在各個層面的業務核心動態正是我們所期望的。

Just that said though, we're going to return to just quarterly guidance at this time.

話雖如此，但我們此時將僅返回季度指導。

Okay.

好的。

And then just as a follow-up, can you give us some even qualitative, if not quantitative, sense of the $320 million incremental revenue for July, how that breaks out?

然後，作為後續行動，您能否給我們一些定性的，如果不是定量的，7 月份 3.2 億美元的增量收入的感覺，那是如何爆發的？

Is the thinking sort of that data center is going to be flat to maybe up a little bit and pretty much the remainder of the growth comes from gaming?

該數據中心的思維方式是否會持平或上升一點，而其餘的增長幾乎來自遊戲？

Yes.

是的。

So when you think about our growth between Q1 and Q2, yes, we do expect in terms of our gaming to increase.

因此，當您考慮我們在第一季度和第二季度之間的增長時，是的，我們確實預計我們的遊戲會增加。

We do expect our Nintendo Switch to start again in sizable amounts once we move into Q2, and we do at this time expect probably our data center business to grow.

我們確實預計，一旦進入第二季度，我們的 Nintendo Switch 將大量重新啟動，我們目前確實預計我們的數據中心業務可能會增長。

And your next question comes from the line of Toshiya Hari with Goldman Sachs.

你的下一個問題來自高盛的 Toshiya Hari。

Jensen, I had a follow-up on the data center business.

Jensen，我對數據中心業務進行了跟進。

I was hoping you could provide some color in terms of what you're seeing not only from your hyperscale customers, which you've talked extensively on, but more on the enterprise and HP side of your business and specifically on the hyperscale side.

我希望你能提供一些色彩，不僅從你的超大規模客戶那裡看到，你已經廣泛討論過，而且更多地在企業和惠普方面，特別是在超大規模方面。

You guys talked about this pause that you're seeing from your customer base.

你們談到了從客戶群中看到的這種停頓。

When you're having conversations with your customers, do they give you a reason as to why they're pausing?

當您與客戶交談時，他們是否會向您說明他們暫停的原因？

Is it too much inventory of GPUs and CPUs and so on and so forth?

GPU 和 CPU 等庫存是否過多？

Or is it optimization giving them extra capacity?

或者是優化給了他們額外的容量？

Is it caution on their own business going forward?

對他們自己的業務向前發展是否謹慎？

Or is it a combination of all the above?

或者它是以上所有的組合？

Any color on that would be helpful, too.

上面的任何顏色都會有幫助，也是。

Hyperscalers are digesting the capacity they have.

超大規模企業正在消化他們擁有的能力。

They -- at this point, I think it's fairly clear that in the second half of last year, they took on a little bit too much capacity.

他們——在這一點上，我認為很明顯，在去年下半年，他們承擔了太多的容量。

And so everybody has paused to give themselves a chance to digest.

所以每個人都停下來給自己消化的機會。

However, our business on inference is doing great, and we're working with CSPs all over the world to accelerate their inference models.

但是，我們的推理業務做得很好，我們正在與世界各地的 CSP 合作以加速他們的推理模型。

Now the reason why recently the inference activity has gotten just off the charts is because of breakthroughs in what we call conversational AI.

現在，推理活動最近剛剛從圖表中脫穎而出的原因是我們所謂的對話式人工智能的突破。

In fact, today, I think that -- I just saw it today, but I've known about this work for some time, Harry Shum's group, Microsoft AI research group, today announced their multitask DNN general language understanding model.

事實上，今天我認為——我今天才看到它，但我知道這項工作有一段時間了，Harry Shum 的團隊，微軟 AI 研究組，今天宣布了他們的多任務 DNN 通用語言理解模型。

And it just -- it broke benchmark records all over the place.

它只是 - 它打破了所有地方的基準記錄。

And basically, what this means is the 3 fundamental components of conversational AI, which is speech recognition; natural language understanding, which does multitask DNN is a breakthrough, and it's based on a piece of work that Google did recently called BERT; and then text-to-speech.

基本上，這意味著對話式人工智能的三個基本組成部分，即語音識別；自然語言理解，多任務 DNN 是一個突破，它基於谷歌最近所做的一項工作，稱為 BERT；然後是文字轉語音。

All of the major pieces of a conversational AI are now put together.

對話式 AI 的所有主要部分現在都放在了一起。

Of course, it's going to continue to evolve, but these models are gigantic to train.

當然，它會繼續發展，但這些模型的訓練量很大。

And in the case of Microsoft's network, it was trained Volta GPUs, And these systems require large amounts of memory.

而以微軟的網絡為例，它是訓練有素的 Volta GPU，而這些系統需要大量的內存。

The models are enormous.

模型是巨大的。

It takes an enormous amount of time to train these systems.

訓練這些系統需要花費大量時間。

And so we're seeing a breakthrough in conversational AI.

因此，我們看到了對話式人工智能的突破。

And across the board, internet companies would like to make their AI much more conversational, so that you can access your phones and smart speakers and be able to engage AI practically everywhere.

總的來說，互聯網公司希望讓他們的人工智能更具對話性，這樣你就可以訪問你的手機和智能揚聲器，並且幾乎可以在任何地方使用人工智能。

The work that we're doing in the industries makes a ton of sense.

我們在行業中所做的工作非常有意義。

We're seeing AI adoption in just about all the industries from transportation to health care to retail to logistics, industrials, agriculture.

從交通運輸到醫療保健到零售再到物流、工業、農業，我們看到幾乎所有行業都採用了人工智能。

And the reason for that is because they have a vast amount of data that they're collecting.

其原因是因為他們正在收集大量數據。

And I heard a statistics just the other day from a talk that Satya gave that some 90% of today's data was created just 2 years ago and is being created by and gathered by these industrial systems all over the world.

就在前幾天，我從 Satya 的一次演講中聽到了一個統計數據，即今天大約 90% 的數據是在 2 年前創建的，並且正在由世界各地的這些工業系統創建和收集。

And so if you want to put that data to work -- and you could create the models using our systems, our GPUs for training, and then you can extend that all the way out to the edge.

因此，如果您想讓這些數據發揮作用——您可以使用我們的系統創建模型，我們的 GPU 用於訓練，然後您可以將其一直延伸到邊緣。

This last quarter, we started to talk about our enterprise server based on T4.

上個季度，我們開始談論我們基於 T4 的企業服務器。

This inference engine that has been really successful for us at the CSPs is now going out into the edge, and we call them edge servers and enterprise servers.

這個在 CSP 中對我們非常成功的推理引擎現在正在進入邊緣，我們稱它們為邊緣服務器和企業服務器。

And these edge systems are going to do AI basically instantaneously.

這些邊緣系統基本上會在瞬間完成人工智能。

It's too much data to move all the way to the cloud.

一直移動到雲端的數據太多了。

You might have data sovereignty concerns.

您可能有數據主權問題。

You want to have very, very low latency.

你想要非常非常低的延遲。

Maybe it needs to have multi-sensor fusion capabilities so it understands the context better.

也許它需要具有多傳感器融合能力，以便更好地理解上下文。

For example, what it sees and what it hears has to be harmonious.

例如，它所看到的和所聽到的必須是和諧的。

And so you need that kind of AI, those kind of sensor computing at the edge.

所以你需要那種人工智能，那種邊緣的傳感器計算。

And so we're seeing a ton of excitement around this area.

所以我們在這個地區看到了大量的興奮。

Some people call it intelligent edge, some people call it edge computing.

有人稱之為智能邊緣，也有人稱之為邊緣計算。

And now with 5G networks coming, we're seeing a lot of interest around the edge computing servers that we're making.

現在隨著 5G 網絡的到來，我們看到人們對我們正在製造的邊緣計算服務器產生了濃厚的興趣。

And so those are the activities that we're seeing.

這些就是我們看到的活動。

As a quick follow-up on the gaming site, Colette, can you characterize product mix within gaming?

作為對遊戲網站 Colette 的快速跟進，您能否描述遊戲中的產品組合？

You saw in the current quarter -- you cited mix is one of the key reasons why gross margins were down year-over-year, albeit off a high base.

你在本季度看到了——你提到的混合是毛利率同比下降的主要原因之一，儘管基數很高。

Going into Q2 in the back half, would you expect SKU mix within gaming to improve or stay the same?

進入後半季度的第二季度，您認為遊戲中的 SKU 組合會改善還是保持不變？

I asked because it's important for gross margins obviously.

我問是因為這顯然對毛利率很重要。

Yes, when you look at our sequential gross margin increase, that will be influenced by our larger revenue -- our larger revenue and better mix, which you are correct, is our largest driver of our overall gross margin.

是的，當您查看我們的連續毛利率增長時，這將受到我們更大收入的影響——我們更大的收入和更好的組合，您是正確的，是我們整體毛利率的最大驅動力。

However, we will be beginning the Nintendo Switch backup, and that does have lower gross margins than the company average, influencing therefore Q2 gross margin guidance that we had provided.

但是，我們將開始備份 Nintendo Switch，其毛利率確實低於公司平均水平，因此影響了我們提供的第二季度毛利率指導。

As we look forward towards the rest of the year, we think mix and the higher revenue again will influence and likely rise our overall gross margins for the full year.

隨著我們對今年剩餘時間的展望，我們認為混合和更高的收入將再次影響並可能提高我們全年的整體毛利率。

And your next question comes from the line of Joe Moore with Morgan Stanley.

你的下一個問題來自摩根士丹利的喬摩爾。

You talked quite a bit about GeForce NOW in the prepared remarks and at the Analyst Day.

您在準備好的評論和分析師日中談到了很多關於 GeForce NOW 的內容。

It seems like cloud gaming is going to be a big topic at E3.

似乎雲遊戲將成為 E3 的一個大話題。

Is that going to be your preferred way to go to market with cloud gaming?

這會是您進入雲遊戲市場的首選方式嗎？

And do you expect to sell GPUs to sort of traditional cloud vendors in non-GeForce NOW fashion?

您是否希望以非 GeForce NOW 的方式將 GPU 出售給某種傳統的雲供應商？

Yes.

是的。

Our strategy for cloud gaming is to extend our PC position for GeForce gamers into the cloud, and our strategy for building out our network is partnerships with telcos around the world.

我們的雲遊戲戰略是將我們為 GeForce 遊戲玩家提供的 PC 地位擴展到雲端，而我們構建網絡的戰略是與世界各地的電信公司建立合作夥伴關係。

And so we'll build out some of it.

因此，我們將構建其中的一些。

And on top of the service, we have our entire PC gaming stack.

除了服務之外，我們還擁有整個 PC 遊戲堆棧。

And when we host the service, we'll move to a subscription model.

當我們託管服務時，我們將轉向訂閱模式。

And with our telcos around the world who would like to provision the service at their edge servers, and many of them would like to do so in conjunction with our 5G telco services to offer cloud gaming as a differentiator.

我們世界各地的電信公司希望在他們的邊緣服務器上提供服務，其中許多人希望與我們的 5G 電信服務一起這樣做，以提供雲遊戲作為差異化因素。

And all of these different countries where PC exposure has been relatively low, we have an opportunity to extend our platform out to that billion PC gamers.

在所有這些 PC 曝光率相對較低的不同國家/地區，我們有機會將我們的平台擴展到十億 PC 遊戲玩家。

And so that's our basic strategy.

這就是我們的基本策略。

We also offer our edge server platform to all of the cloud service providers.

我們還向所有云服務提供商提供我們的邊緣服務器平台。

Google has NVIDIA GPU graphics in the cloud, amazon has NVIDIA GPU graphics in the cloud and Microsoft has NVIDIA GPU graphics in the cloud.

谷歌在雲端擁有 NVIDIA GPU 圖形，亞馬遜在雲端擁有 NVIDIA GPU 圖形，微軟在雲端擁有 NVIDIA GPU 圖形。

And these GPUs will be fantastic also for cloud gaming and workstation graphics and also ray tracing.

這些 GPU 也非常適合雲遊戲和工作站圖形以及光線追踪。

And so the platform is capable of running all of the things that NVIDIA runs, and we try to put it in every data center, in every cloud from every region that's possible.

因此，該平台能夠運行 NVIDIA 運行的所有東西，我們嘗試將它放置在每個數據中心、每個可能區域的每個雲中。

And your next question comes from the line of Vivek Arya with Bank of America Merrill Lynch.

您的下一個問題來自美銀美林的 Vivek Arya。

I actually had a clarification for Colette and a question for Jensen.

實際上，我向 Colette 澄清了一個問題，並向 Jensen 提出了一個問題。

Colette, are you now satisfied that the PC gaming business is operating at a normal level when you look at the Q2 guidance?

Colette，當您查看第二季度的指引時，您現在對 PC 遊戲業務在正常水平上運營感到滿意嗎？

Like are all the issues regarding inventory and other issues, are they over?

就像所有關於庫存和其他問題的問題一樣，它們都結束了嗎？

Or do you think that the second half of the year is more the normalized run rate for your PC gaming business?

還是您認為下半年更適合您的 PC 遊戲業務的正常運行率？

And then Jensen, on the data center, NVIDIA has dominated the training market.

然後是 Jensen，在數據中心上，NVIDIA 已經主導了訓練市場。

Inference sounds a lot more fragmented and competitive.

推理聽起來更加分散和競爭。

There's a lot of talk of software being like more at the framework level.

有很多關於軟件更像是在框架級別的討論。

How should we get the confidence that your lead in training will help you maintain a good lead in inference also?

我們應該如何確信您在訓練中的領先地位也將幫助您在推理方面保持良好的領先地位？

Thanks for the question.

謝謝你的問題。

So let's start with your first part of the question regarding how we reach overall normalized gaming levels.

因此，讓我們從關於我們如何達到整體標準化遊戲水平的問題的第一部分開始。

When we look at our overall inventory in the channel, we believe that this is relatively behind us and moving forward that it will not be an issue.

當我們查看我們在渠道中的整體庫存時，我們認為這已經相對落後，並且向前發展不會成為問題。

Going forward, we will probably reach normalized level for gaming somewhere between Q2 and Q3 similar to our discussion that we had back at Analyst Day, at the beginning of the quarter.

展望未來，我們可能會在第二季度和第三季度之間達到遊戲的正常化水平，類似於我們在本季度初分析師日的討論。

NVIDIA's strategy is accelerated computing.

NVIDIA 的戰略是加速計算。

It is very different than an accelerator strategy.

它與加速器策略非常不同。

For example, if you were building a smart microphone, you need an accelerator for speech recognition, ASR.

例如，如果您正在構建智能麥克風，則需要一個用於語音識別的加速器 ASR。

Our company is focused on accelerated computing, and the reason for that is because the world's body of software is really gigantic, and the world's body of software continues to evolve.

我們公司專注於加速計算，原因是世界上的軟件體非常龐大，而且世界上的軟件體還在不斷發展。

And AI is nowhere near done.

人工智能還遠未完成。

We're probably at the first or a couple of innings of AI at that.

我們可能處於人工智能的第一局或幾局。

And so the amount of the software and the size of the models are going to have to continue to evolve.

因此，軟件的數量和模型的大小將不得不繼續發展。

Our accelerated computing platform is designed to enable the computer industry to bring forward into the future all the software that exists today, whether it's TensorFlow or Caffe or PyTorch or it could be classical machine learning algorithms like XGBoost, which is actually right now the most popular framework and machine learning overall.

我們的加速計算平台旨在使計算機行業能夠將當今存在的所有軟件推向未來，無論是 TensorFlow、Caffe 還是 PyTorch，也可以是 XGBoost 等經典機器學習算法，這實際上是目前最流行的整體框架和機器學習。

And there's so many different types of classical algorithms and not to mention all of the handwritten engineered algorithms by programmers.

而且有很多不同類型的經典算法，更不用說程序員的所有手寫工程算法了。

And those algorithms and those hand-engineered algorithms also would like to be mixed in with all of the deep learning or otherwise classical machine learning algorithms.

這些算法和那些手工設計的算法也希望與所有深度學習或其他經典機器學習算法混合在一起。

This whole body of software doesn't run on a single function accelerator.

這整套軟件不能在單一功能加速器上運行。

If you would like that body of software to run on something, it would have to be sufficiently general purpose.

如果您希望該軟件主體在某些東西上運行，那麼它必須具有足夠的通用性。

And so the balance that we made was we invented this thing called a Tensor Core that allows us to accelerate deep learning to the speed of light.

所以我們做出的平衡是我們發明了這個叫做張量核心的東西，它可以讓我們將深度學習加速到光速。

Meanwhile, it has the flexibility of CUDA so that we can bring forward everything in classical machine learning as people have started to see with RAPIDS and is being announced, being integrated into machine learning pipelines, in the cloud and elsewhere, and then also all of the high-performance computing applications or computer vision algorithms, image processing algorithms that don't have deep learning or machine learning alternatives.

同時，它具有 CUDA 的靈活性，因此我們可以推出經典機器學習中的所有內容，正如人們已經開始看到的 RAPIDS 並正在發布，被集成到機器學習管道、雲和其他地方，然後還有所有沒有深度學習或機器學習替代方案的高性能計算應用程序或計算機視覺算法、圖像處理算法。

And so our company is focused on accelerated computing.

所以我們公司專注於加速計算。

And speaking of inference, that's one of the reasons why we're so successful in inference right now.

說到推理，這就是我們現在推理如此成功的原因之一。

We're seeing really great pickup.

我們看到了非常棒的皮卡。

And the reason for that is because the type of models that people want to run on one application, and let's just use one application, one very, very exciting one, conversational AI, you would have to do speech recognition.

原因是人們想要在一個應用程序上運行的模型類型，讓我們只使用一個應用程序，一個非常非常令人興奮的，對話式人工智能，你必須做語音識別。

You would have to then do natural language understanding to understand what the speech is.

然後，您必須進行自然語言理解才能理解語音是什麼。

You might have to convert -- you have to translate to another language.

你可能需要轉換——你必須翻譯成另一種語言。

Then you have to do something related to maybe making a recommendation or making a search.

然後你必須做一些與推薦或搜索相關的事情。

And then after that, you have to convert that recommendation and search and the intent into speech.

然後在那之後，您必須將該推薦和搜索以及意圖轉換為語音。

While some of it could be 8-bit integers, some of it really wants to be 16-bit floating point.

雖然其中一些可能是 8 位整數，但其中一些確實希望是 16 位浮點。

And some of it because of development state of it may want to be in 32-bit floating point.

其中一些由於它的開發狀態可能希望處於 32 位浮點。

And so the mixed precision nature and the computational algorithm nature or flexibility nature of our approach make it possible for cloud providers and people who are developing AI applications to not have to worry about exactly what model it runs or not.

因此，我們方法的混合精度性質和計算算法性質或靈活性性質使雲提供商和正在開發 AI 應用程序的人不必擔心它運行或不運行什麼模型。

We run every single model.

我們運行每一個模型。

And if it doesn't currently run, we'll help you make it run.

如果它當前沒有運行，我們將幫助您使其運行。

And so the flexibility of our architecture and the incredible performance in deep learning is really a great balance and allows customers to deploy it easily.

因此，我們架構的靈活性和深度學習中令人難以置信的性能確實是一個很好的平衡，允許客戶輕鬆部署它。

So our strategy is very different than an accelerator.

因此，我們的策略與加速器非常不同。

I think the only accelerators that I really see successful at the moment are the ones that go into smart speakers.

我認為目前我真正看到成功的唯一加速器是用於智能揚聲器的加速器。

And surely, there are a whole bunch being talked about, but I think the real challenge is how to make it run real, real workloads.

當然，有很多人在談論，但我認為真正的挑戰是如何讓它運行真實的、真實的工作負載。

And we're going to keep cranking along in our current strategy and keep raising the bar as we have in the past.

我們將繼續按照我們目前的戰略前進，並像過去一樣繼續提高標準。

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

您的下一個問題來自 Bernstein Research 的 Stacy Rasgon。

This is a question for Colette.

這是科萊特的問題。

Colette, so you said inference and rendering within data center were both up very strongly.

Colette，所以你說數據中心內的推理和渲染都非常強勁。

But I guess that has to imply that like the training/acceleration pieces is quite weak, even weaker than the overall.

但我想這意味著訓練/加速部分非常弱，甚至比整體弱。

And given those should be adding to efficiency, I'm just surprised it's down that much.

考慮到這些應該會提高效率，我只是對它下降了這麼多感到驚訝。

I mean is this truly just digestion?

我的意思是這真的只是消化嗎？

I mean is it share?

我的意思是分享嗎？

I mean like your competitor is now shipping some parts here.

我的意思是你的競爭對手現在在這裡運送一些零件。

I mean I guess how do we get confidence that just we haven't seen the ceiling on this?

我的意思是，我想我們如何才能確信我們還沒有看到這個上限？

I mean do you think given the trajectory, you can exit the year above the prior peaks?

我的意思是你認為考慮到軌跡，你可以在之前的峰值之上退出一年嗎？

I guess you kind of have to given at least the qualitative outlook in the second -- I guess maybe just any color you can give us on any of those trends would be super helpful.

我想你至少必須在第二個中給出定性展望——我想你可以給我們任何這些趨勢的顏色可能會非常有幫助。

Sure.

當然。

As we discussed, Stacy, we are seeing many of the hyperscalers definitely purchasing in terms of the inferencing into the installment that it continues, also in terms of the training instances that they will need for their cloud or for internal use absolutely.

正如我們所討論的那樣，Stacy，我們看到許多超大規模用戶肯定會購買它繼續進行的分期付款，也包括他們絕對需要的雲或內部使用的訓練實例。

But we have some that have paused and are going through those periods.

但是我們有一些已經暫停並正在經歷這些時期。

So that -- we do believe this will come back.

所以 - 我們確實相信這會回來。

We do believe as we look out into the future that they will need that overall deep learning for much of their research as well as many of their workloads.

我們確實相信，當我們展望未來時，他們的大部分研究以及許多工作負載都需要全面的深度學習。

So no concern on that, but right now, we do see a pause.

所以不用擔心，但現在，我們確實看到了暫停。

I'll turn it over to Jensen to see if he has any additional comments.

我會把它交給 Jensen 看看他是否還有其他意見。

Let's see.

讓我們來看看。

I think that when it comes down to training, if your infrastructure team tells you not to buy anything, the thing that suffers is time to market and some amount of experimentation that allows you to get better comps and waiting longer.

我認為，當涉及到培訓時，如果您的基礎架構團隊告訴您不要購買任何東西，那麼受影響的就是上市時間和一些實驗，這些實驗可以讓您獲得更好的組合併等待更長的時間。

And I think that for computer vision type of algorithms and recommendation type of algorithms, those -- that posture may not be impossible.

而且我認為對於計算機視覺類型的算法和推薦類型的算法，那些——那種姿勢可能不是不可能的。

However, the type of work that everybody is now jumping on top of, which is natural language understanding and conversational AI and the breakthrough that Microsoft just announced, if you want to keep up with that, you're going to have to buy much, much larger machines.

但是，現在每個人都在跳槽的工作類型，即自然語言理解和對話式人工智能以及微軟剛剛宣布的突破，如果你想跟上它，你將不得不買很多，更大的機器。

And I'm looking forward to that, and I expect that that's going to happen.

我很期待，我希望這會發生。

But in the latter part of last year, Q4 and Q1 of this year, we did see pause from the hyperscalers and -- but I don't expect it to last.

但是在去年下半年，今年的第四季度和第一季度，我們確實看到了超大規模企業的停頓——但我預計它不會持續下去。

Got it.

知道了。

Just as a quick follow-up, I just wanted to ask about the regulatory around Mellanox in the context of what we're seeing out of China now.

作為快速跟進，我只是想在我們現在在中國看到的情況下詢問有關 Mellanox 的監管情況。

How do we sort of gauge the risk of, I guess, potential for the deterioration in relationships sort of spilling over on the regulatory front around that deal?

我想，我們如何衡量關係惡化的風險可能會蔓延到圍繞該交易的監管方面？

We've seen that obviously with some of the other large deals in the space.

我們在該領域的其他一些大宗交易中顯然已經看到了這一點。

What are your thoughts on that?

你對此有何看法？

Well, on first principles, the acquisition is going to enable data centers around the world, whether it's U.S. or elsewhere in China, to be able to advance much, much more quickly.

嗯，首先，此次收購將使世界各地的數據中心，無論是美國還是中國其他地方，都能夠更快地發展。

We're going to invest and building infrastructure technology.

我們將投資和建設基礎設施技術。

And as a combined company, we'll be able to do that much better.

作為一家合併後的公司，我們將能夠做得更好。

And so this is good for customers, and it's great for customers in China.

所以這對客戶有好處，對中國的客戶也很好。

The 2 matters, whether it's -- the 2 matters that we're talking about are just -- are different.

兩個問題，無論是 - 我們正在談論的兩個問題只是 - 是不同的。

And one is related to competition in a -- with respect to our acquisition, the competition in the market, and the other one is related to trade.

一個與競爭有關——關於我們的收購，市場競爭，另一個與貿易有關。

And so the 2 matters are just different.

所以這兩個問題是不同的。

And in our particular case, we bring so much value to the marketplace in China, and I'm confident that the market will see that.

在我們的特殊情況下，我們為中國市場帶來瞭如此多的價值，我相信市場會看到這一點。

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

您的下一個問題來自 C.J. Muse 與 Evercore ISI 的系列。

I guess a question on the noncloud part of your data center business.

我想關於您的數據中心業務的非雲部分的問題。

So if you think about the trends you're seeing in enterprise virtualization, in HPC and all the work you're doing around RAPIDS, rendering, et cetera, can you kind of talk through the visibility you have today for that part of your business?

因此，如果您考慮一下您在企業虛擬化、HPC 以及您圍繞 RAPIDS、渲染等所做的所有工作中看到的趨勢，您能否談談您今天對這部分業務的可見性?

I think that's roughly 50% of the mix.

我認為這大約是 50% 的組合。

So is that a piece that you feel confident you can grow in 2019?

那麼，你有信心在 2019 年成長嗎？

And any color around that would be appreciated.

周圍的任何顏色都將不勝感激。

We expected to grow in 2019.

我們預計 2019 年將增長。

The -- a lot of our T4 inference work is related to what people call edge computing.

我們的很多 T4 推理工作都與人們所說的邊緣計算有關。

And it has to be done at the edge because of the amount of data that otherwise would be transferred to the cloud is just too much.

並且必須在邊緣完成，因為否則將傳輸到雲的數據量太多了。

It has to be done at the edge because of data sovereignty issues and data privacy issues.

由於數據主權問題和數據隱私問題，它必須在邊緣完成。

And it has to be done at the edge because the latency requirement is really, really high.

它必須在邊緣完成，因為延遲要求非常非常高。

It has to respond basically like a reflex and to make a prediction or make a suggestion or stop a piece of machinery instantaneously.

它必須像反射一樣做出基本反應，做出預測或提出建議或立即停止機器。

And so a lot of that work, a lot of the work that we're doing in T4 inference is partly in the cloud, a lot of it is at the edge.

因此，我們在 T4 推理中所做的很多工作，很多工作都在雲端，很多都在邊緣。

T4 servers for enterprise were announced, I guess, about halfway through the quarter.

我猜，大約在本季度中途發布了面向企業的 T4 服務器。

And the OEMs are super excited about that because the number of companies in the world who want to do data analytics, predictive analytics is quite large, and the size of the data is growing so significantly.

OEM 對此感到非常興奮，因為世界上想要進行數據分析、預測分析的公司數量非常多，而且數據的規模也在顯著增長。

And with Moore's Law ending, it's really hard to power through terabytes of data at a time.

隨著摩爾定律的終結，一次處理數 TB 的數據真的很困難。

And so we've been working on building the software stack from the new memory architectures and storage architectures all the way to the computational middleware, and it's called RAPIDS.

因此，我們一直致力於構建從新的內存架構和存儲架構一直到計算中間件的軟件堆棧，它被稱為 RAPIDS。

And I appreciate you saying that, and that's being put together.

我很欣賞你這麼說，並且正在整合。

And the activity in GitHub is just fantastic.

GitHub 中的活動非常棒。

And so you can see all kinds of companies jumping in to make contributions because they would like to be able to take that open-source software and run it in their own data center on our GPUs.

所以你可以看到各種各樣的公司加入進來做出貢獻，因為他們希望能夠採用開源軟件並在他們自己的數據中心在我們的 GPU 上運行它。

And so I expect the enterprise side of our business, both for enterprise big data analytics or for edge computing, to be a really good growth driver for us this year.

因此，我預計我們業務的企業方面，無論是企業大數據分析還是邊緣計算，都將成為今年我們的一個非常好的增長動力。

And a follow-up real quickly on auto.

並在汽車上快速跟進。

It's a business that you talked about, more R&D focused, but clearly I think has surprised positively.

這是您談到的一項業務，更側重於研發，但顯然我認為這令人驚訝。

What's the visibility like there?

那裡的能見度如何？

And how should we think about growth trajectory into the second half of the year?

我們應該如何看待下半年的增長軌跡？

Our automotive strategy has several components.

我們的汽車戰略有幾個組成部分。

There's the engineering component of it where we -- our engineers and their engineers have to codevelop the autonomous vehicles.

它的工程部分是我們——我們的工程師和他們的工程師必須共同開發自動駕駛汽車。

And then there's 3 other components.

然後還有其他 3 個組件。

There's the component of AI computing infrastructure we call DGX and/or any of the OEM service that include our GPUs that are used for developing the AIs.

有我們稱為 DGX 的 AI 計算基礎設施組件和/或任何 OEM 服務，包括我們用於開發 AI 的 GPU。

The cars are collecting a couple of terabytes per day per test car, and all of that data has to be powered through and crunched through in the data center.

這些汽車每天每輛測試汽車收集幾 TB 的數據，所有這些數據都必須在數據中心進行供電和處理。

And so we have an infrastructure of what we call DGX that people could use, and we're seeing a lot of success there.

所以我們有一個人們可以使用的我們稱之為 DGX 的基礎設施，我們在那裡看到了很多成功。

We just announced this last quarter, a new infrastructure called Constellation that lets you essentially drive thousands and thousands of test cars in your data center, and they're all going through pseudo-directed random or directed scenarios that allows you to either test untestable scenarios or regress against previous scenarios, and we call that Constellation.

我們剛剛在上個季度宣布了一個名為 Constellation 的新基礎架構，它可以讓您在數據中心內駕駛成千上萬輛測試汽車，它們都在經歷偽定向隨機或定向場景，您可以測試不可測試的場景或者回歸到以前的場景，我們稱之為星座。

And then lastly, after working on a car for several years, we would install the computer inside the car, and we call that DRIVE.

最後，在汽車上工作了幾年之後，我們將電腦安裝在車內，我們稱之為 DRIVE。

And so these are the 4 components of opportunities that we have in the automotive industry.

因此，這些是我們在汽車行業擁有的機會的 4 個組成部分。

We're doing great in China.

我們在中國做得很好。

There's a whole bunch of electric vehicles being created.

有一大堆電動汽車正在被創造出來。

The robotaxis' developments around the world largely use NVIDIA's technology.

世界各地的自動駕駛出租車開發主要使用 NVIDIA 的技術。

We recently announced the partnership with Toyota.

我們最近宣布與豐田合作。

There's a whole bunch of stuff that we're working on, and I'm anxious to announce them to you.

我們正在處理一大堆東西，我急於向你宣布。

But this is an area that is the tip of the iceberg of a larger space we call robotics and computing at the edge.

但這是一個我們稱之為機器人和邊緣計算的更大空間的冰山一角的領域。

But if you think about the basic computational pipeline of a self-driving car, it's no different essentially than a smart retail or the future of computational medical instruments, agriculture, industrial inspection, delivery drones, all basically use essentially the same technique.

但是，如果您考慮自動駕駛汽車的基本計算管道，它與智能零售或計算醫療器械、農業、工業檢查、交付無人機的未來本質上沒有什麼不同，它們基本上都使用相同的技術。

And so this is the foundational work that we're going to do for a larger space that people call the intelligent edge or computing at the edge.

所以這是我們要為更大的空間做的基礎工作，人們稱之為智能邊緣或邊緣計算。

Your next question comes from the line of Chris Caso with Raymond James.

您的下一個問題來自 Chris Caso 和 Raymond James。

First question is on notebooks and just to clarify what's been different from your expectations this year.

第一個問題是關於筆記本的，只是為了澄清今年與您的預期不同的地方。

Is it simply that the OEMs didn't launch the new models you'd expected given the shortage?

僅僅是因為短缺，原始設備製造商沒有推出您預期的新型號嗎？

Or is it more just about unit volume?

或者更多的是單位體積？

And then just following up on that, what's your level of confidence in that coming back to be a driver as you go into the second half of the year?

然後只是跟進這一點，你對進入下半年成為一名車手的信心如何？

In Q2, we were -- we had to deal with some CPU shortage issues at the OEMs.

在第二季度，我們不得不處理 OEM 的一些 CPU 短缺問題。

It's improving, but the initial ramp will be affected.

它正在改善，但最初的斜坡會受到影響。

And so the CPU shortage situation has been described fairly broadly, and it affected our initial ramp.

所以 CPU 短缺的情況已經被相當廣泛地描述了，它影響了我們最初的斜坡。

We don't expect it to affect our ramp going forward.

我們預計它不會影響我們前進的坡道。

And the new category of gaming notebooks that we created called Max-Q has made it possible for really amazing gaming performance to fit into a thin and light.

而我們創建的名為 Max-Q 的新型遊戲筆記本電腦使真正驚人的遊戲性能成為可能，適合輕薄。

And these new generations of notebooks with our Max-Q design and the Turing GPU, which is super energy efficient, in combination, made it possible for OEMs to create notebooks that are both affordable all the way down to $799, thin and really delightful, all the way up to something incredible with RTX 2080 and a 4K display.

這些新一代筆記本電腦採用我們的 Max-Q 設計和超節能的 Turing GPU 相結合，使 OEM 能夠創造出價格低至 799 美元、輕薄且令人愉悅的筆記本電腦，一直到 RTX 2080 和 4K 顯示器令人難以置信的東西。

And these are thin notebooks that are really beautiful that people would love to use.

這些是人們喜歡使用的非常漂亮的薄筆記本。

And this -- the invention of the Max-Q design method and all the software that went into it that we announced last year, we had -- I think last year, we had some 40 notebooks or so, maybe a little bit less than that.

而這個——Max-Q 設計方法的發明以及我們去年宣布的所有軟件，我們有——我想去年，我們有大約 40 台筆記本電腦，也許比那。

And this year, we have some 100 notebooks that are being designed at different price segments by different OEMs across different regions.

今年，我們有大約 100 款筆記本電腦，由不同地區的不同 OEM 以不同價格段設計。

And so I think this year is going to be quite a successful year for notebooks.

所以我認為今年對於筆記本來說將是非常成功的一年。

And it's also the most successful segment of consumer PCs.

它也是消費類 PC 中最成功的部分。

It's the fastest-growing segment.

這是增長最快的部分。

It is very largely underpenetrated because until Max-Q came along, it wasn't really possible to design a notebook that is both great in performance and experience and also something that a gamer would like to own.

它的滲透率非常低，因為在 Max-Q 出現之前，實際上不可能設計出一款性能和體驗都很好的筆記本電腦，同時也是遊戲玩家想要擁有的東西。

And so finally, we've been able to solve that difficult puzzle and created powerful gaming machines that are inside a notebook that's really wonderful to own and carry around.

所以最後，我們已經能夠解決這個難題，並創造出功能強大的遊戲機，這些遊戲機裝在一個非常適合擁有和隨身攜帶的筆記本電腦中。

And so this is going to be a really -- this is a fast-growing segment, and all the OEMs know it.

所以這將是一個真正的 - 這是一個快速增長的細分市場，所有 OEM 都知道這一點。

And that's why they put so much energy into creating all these different types of designs and styles and sizes and shapes.

這就是為什麼他們投入如此多的精力來創造所有這些不同類型的設計、風格、尺寸和形狀。

And we have 100 Turing GPU notebooks, gaming PCs ramping right now.

我們有 100 台 Turing GPU 筆記本電腦，遊戲 PC 正在迅速發展。

That's very helpful.

這很有幫助。

As a follow-up, I just want to follow up on some of the previous questions on the automotive market.

作為後續，我只想跟進之前關於汽車市場的一些問題。

And we've been talking about it for a while.

我們已經討論了一段時間了。

Obviously, the design cycles are very long, so you do have some visibility, and I guess the question is when can we expect an acceleration of auto revenue.

顯然，設計週期很長，所以你確實有一些可見性，我想問題是我們什麼時候可以期待汽車收入的加速。

Is next year the year?

明年是一年嗎？

And then what will be the driver of that in terms of dollar contribution?

那麼，就美元貢獻而言，驅動因素是什麼？

I presume some of the Level 2+ things you've been talking about would probably mean most likely they're given the amount of volume there.

我想你一直在談論的一些 2 級以上的事情可能意味著他們很可能在那裡獲得了音量。

If you can confirm that and just give some color on expectations for drivers.

如果你能確認這一點，並就對司機的期望給出一些顏色。

Yes.

是的。

Level 2+, call it 2020, late 2021 or like 2022-ish.

2+ 級，稱之為 2020 年、2021 年末或類似 2022 年。

So that's Level 2+.

所以這是2級以上。

I would say 2019, very, very early for robotaxis; next year, substantially more volume for robotaxis; 2021, bigger volumes for robotaxis.

我想說的是 2019 年，對於機器人出租車來說非常非常早；明年，自動駕駛出租車的銷量將大幅增加； 2021 年，機器人出租車的銷量會更大。

The ASP differences, the amount of computation you put into a robotaxi because of sensor resolutions, sensor diversity and redundancy, the computational redundancy and the richness of the algorithm, all of it put together, it's probably an order of magnitude plus in computation.

ASP 差異、由於傳感器分辨率、傳感器多樣性和冗餘度、計算冗餘度和算法的豐富性而導致的自動駕駛出租車的計算量，所有這些放在一起，可能是計算量的一個數量級。

And so the economics would reflect that.

所以經濟學會反映這一點。

And so that robotaxi is kind of like next year, the year after, ramp.

所以機器人出租車有點像明年，後年，坡道。

And then think of Level 2+ as 2021, 2022.

然後將 2+ 級視為 2021 年、2022 年。

Overall, remember that our economics come from 4 different parts.

總的來說，請記住，我們的經濟學來自 4 個不同的部分。

And so there's the NRE components of it, there's the AI development infrastructure, computing infrastructure part of it, the simulation part of it called Constellation and then the economics of the car.

所以有它的 NRE 組件，有人工智能開發基礎設施，它的計算基礎設施部分，它的模擬部分稱為星座，然後是汽車的經濟性。

And so we just announced Constellation.

所以我們剛剛宣布了星座。

The enthusiasm around it is really great.

周圍的熱情真是太棒了。

Nobody should ever ship anything they don't simulate.

任何人都不應該運送他們不模擬的任何東西。

And my expectation is that billions of miles will get simulated inside a simulator long before they'll ship it.

我的期望是，數十億英里將在他們發貨之前在模擬器中進行模擬。

And so that's a great opportunity for Constellation.

所以這對星座來說是一個很好的機會。

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

下一個問題來自 Matt Ramsay 和 Cowen 的對話。

I have a few questions, one for Jensen and one for Colette.

我有幾個問題，一個問 Jensen，一個問 Colette。

I guess, Jensen, you've done -- you said in many forums that the move down to the new process node at 7-nanometer across the business was not really sufficient to have a platform approach, and I agree with that.

我想，Jensen，你已經做到了——你在許多論壇上說過，在整個業務中向下移動到 7 納米的新工藝節點並不足以擁有平台方法，我同意這一點。

But maybe you could talk a little bit about your product plans at least in general terms around a 7-nanometer franchise in the gaming business and also in your training accelerator program.

但也許你可以談談你的產品計劃，至少籠統地圍繞遊戲業務中的 7 納米特許經營權以及你的培訓加速器計劃。

And I wonder if that might be waiting for some of those products or at least anticipation of those might be the cause of a little bit of a pause here.

我想知道這是否可能正在等待其中一些產品，或者至少對這些產品的預期可能是這裡有點停頓的原因。

And secondly, Colette, maybe you could talk us through your expectations.

其次，科萊特，也許你可以告訴我們你的期望。

I understand there's a lack of visibility in certain parts of the business on revenue, but maybe you could talk about OpEx trends through the rest of the year where you might have a little more visibility.

我知道業務的某些部分在收入方面缺乏可見性，但也許你可以在今年餘下的時間裡談論運營支出趨勢，這樣你可能會有更多的可見性。

The entire reason for Q4 and Q1 is attributed to oversupply in the channel as a result of cryptocurrency.

第四季度和第一季度的全部原因歸因於加密貨幣導致渠道供過於求。

It has nothing to do with Turing.

這與圖靈無關。

In fact, Turing is off to a faster start than Pascal was, and it continues to be on a faster pace than Pascal was.

事實上，圖靈的起步比帕斯卡更快，而且它繼續比帕斯卡更快。

And so the pause in gaming is now behind us.

所以遊戲的停頓現在已經過去了。

We're in a growth trajectory with gaming.

我們正處於遊戲的增長軌跡。

RTX has -- took the lead on ray tracing and has now become the standard for next-generation gaming, support from basically every major platform and software provider on the planet.

RTX 在光線追踪方面處於領先地位，現已成為下一代遊戲的標準，得到了地球上幾乎所有主要平台和軟件提供商的支持。

And our notebook growth is going to be really great because of the Max-Q design that we invented.

由於我們發明的 Max-Q 設計，我們的筆記本電腦的增長將會非常好。

And the last couple of quarters would also intersect it with -- overlap with the seasonal slowdown that -- not sell but build -- the seasonal builds of the Nintendo Switch, and we're going to go back to the normal build cycle.

最後幾個季度也將與 - 與季節性放緩重疊 - 不是銷售而是構建 - Nintendo Switch的季節性構建，我們將回到正常的構建週期。

And as Colette said earlier, somewhere between Q2 and Q3, we'll get back to normal levels for gaming.

正如 Colette 之前所說，在 Q2 和 Q3 之間的某個時間點，我們將恢復到正常的遊戲水平。

And so we're off to a great start in Turing, and I'm super excited about that.

所以我們在圖靈有了一個很好的開端，我對此感到非常興奮。

And in the second half of the year, we would have fully ramped up from top to bottom our Turing architecture, spanning everything from 179 to as high performance as you like.

而在下半年，我們將從上到下全面提升圖靈架構，涵蓋從 179 到高性能的所有內容。

And we have the best price, best performance and best GPU at every single price point.

我們在每個價位都擁有最優惠的價格、最佳性能和最佳 GPU。

And so I think we're in a pretty good shape.

所以我認為我們的狀態非常好。

In terms of process nodes, we tend to design our own process with TSMC.

在工藝節點方面，我們傾向於與台積電一起設計自己的工藝。

If you look at our process and you measure its energy efficiency, it's off the charts.

如果您查看我們的流程並衡量其能源效率，就會發現它是超乎想像的。

And in fact, if you take our Turing and you compare it against a 7-nanometer GPU on energy efficiency, it's incomparable.

事實上，如果你拿我們的 Turing 和 7 納米 GPU 的能效進行比較，它是無法比擬的。

In fact, the world's 7-nanometer GPU already exists.

事實上，世界上的 7 納米 GPU 已經存在。

And it's easy to go and pull that and compare the performance and energy efficiency against one of our Turing GPUs.

並且很容易將其與我們的一款圖靈 GPU 進行比較性能和能源效率。

And so the real focus for our engineering team is to engineer a process that makes sense for us and to create an architecture that is energy efficient.

因此，我們工程團隊的真正重點是設計一個對我們有意義的流程，並創建一個節能的架構。

And the combination of those 2 things allows us to sustain our leadership position.

這兩件事的結合使我們能夠維持我們的領導地位。

Otherwise, buying off the shelf process is something that we can surely do, but we want to do much more than that.

否則，我們當然可以購買現成的流程，但我們想做的遠不止這些。

Okay.

好的。

And to discuss your question regarding OpEx trajectory for the rest of the year, we're still on track to our thoughts on leaving the fiscal year with a year-over-year growth and overall OpEx on a non-GAAP basis in the high single digits.

為了討論您關於今年餘下時間的運營支出軌蹟的問題，我們仍然在按照非公認會計原則在高單價的基礎上使本財年實現同比增長和整體運營支出的想法步入正軌位數。

We'll see probably an increase sequentially quarter-to-quarter along there, but our year-over-year growth will start to decline as we will not be growing at the speed that we did in this last year.

我們可能會看到那裡的季度環比增長，但我們的同比增長將開始下降，因為我們不會以去年的速度增長。

But I do believe we're on track to meet that goal.

但我確實相信我們正在實現這一目標。

And I'll now turn back over to Jensen for any closing remarks.

現在，我將請 Jensen 做任何結束語。

Thanks, everyone.

感謝大家。

We're glad to be returning to growth.

我們很高興能夠恢復增長。

We are focused on driving 3 growth strategies.

我們專注於推動 3 種增長戰略。

First, RTX ray tracing.

首先，RTX 光線追踪。

It's now clear that ray tracing is the future of gaming and digital design, and video RTX is leading the way.

現在很明顯，光線追踪是遊戲和數字設計的未來，而視頻 RTX 正在引領潮流。

With the support of Microsoft DXR, Epic, Unity, Adobe and Autodesk, game publishers like EA, movie studios like Pixar, industry support has been fantastic.

在 Microsoft DXR、Epic、Unity、Adobe 和 Autodesk、EA 等遊戲發行商、皮克斯等電影工作室的支持下，行業支持非常出色。

Second, accelerated computing and AI computing.

二是加速計算和AI計算。

The pause in hyperscale spending will pass.

超大規模支出的停頓將會過去。

Accelerated computing in AI are the greatest forces in computing today, and NVIDIA is leading these movements.

AI 中的加速計算是當今計算領域最強大的力量，而 NVIDIA 正在引領這些運動。

Whether cloud or enterprise or AI at the edge for 5G or industries, NVIDIA's one scalable architecture from cloud to edge is the focal point platform for the industry to build AI upon.

無論是雲、企業還是 5G 或行業邊緣的 AI，NVIDIA 的一種從雲到邊緣的可擴展架構都是行業構建 AI 的焦點平台。

Third, robotics.

第三，機器人。

Some call it an embedded AI, some edge AI or autonomous machines.

有人稱其為嵌入式人工智能、一些邊緣人工智能或自主機器。

The same computing architecture is used for self-driving cars, pick-and-place robotics arms, delivery drones and smart retail stores.

相同的計算架構用於自動駕駛汽車、拾放機器人手臂、交付無人機和智能零售店。

Everything machine -- every machine that moves or machines that watch other things that move, whether with driver or driverless, will have robotics and AI capabilities.

一切機器——每台移動的機器或觀察其他移動物體的機器，無論是驅動還是無人駕駛，都將具有機器人技術和人工智能功能。

Our strategy is to create an end-to-end platform that spans NVIDIA's DGX AI computing infrastructure to NVIDIA Constellation simulation to NVIDIA AGX embedded AI computing.

我們的戰略是創建一個端到端平台，涵蓋 NVIDIA 的 DGX AI 計算基礎架構、NVIDIA Constellation 模擬和 NVIDIA AGX 嵌入式 AI 計算。

And finally, we are super excited about the pending acquisition of Mellanox.

最後，我們對即將收購的 Mellanox 感到非常興奮。

Together, we can advance cloud and edge architectures for HPC and AI computing.

我們可以一起推進用於 HPC 和 AI 計算的雲和邊緣架構。

See you next quarter.

下個季度見。

And this concludes today's conference call.

今天的電話會議到此結束。

You may now disconnect.

您現在可以斷開連接。