輝達 (NVDA) 2022 Q2 法說會逐字稿

Good afternoon.

下午好。

My name is Mel, and I will be your conference operator today.

我叫梅爾，今天我將成為您的會議接線員。

At this time, I would like to welcome everyone to the NVIDIA's second quarter earnings call.

在這個時候，我想歡迎大家參加 NVIDIA 第二季度財報電話會議。

(Operator Instructions)

（操作員說明）

Thank you.

謝謝你。

Simona Jankowski, you may begin your conference.

Simona Jankowski，你可以開始你的會議了。

Thank you.

謝謝你。

Good afternoon, everyone, and welcome to NVIDIA's conference call for the second quarter of fiscal 2022.

大家下午好，歡迎參加 NVIDIA 2022 財年第二季度電話會議。

With me today from NVIDIA are Jensen Huang, President and Chief Executive Officer; and Colette Kress, Executive Vice President and Chief Financial Officer.

今天和我一起來自 NVIDIA 的是總裁兼首席執行官 Jensen Huang；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 third quarter of fiscal 2022.

在電話會議討論我們 2022 財年第三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 Form 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 表格中提交的報告證券交易委員會。

All our statements are made as of today, August 18, 2021, 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，即 2021 年 8 月 18 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。

Q2 was another strong quarter, with revenue of $6.5 billion and year-on-year growth of 68%.

第二季度是另一個強勁的季度，收入為 65 億美元，同比增長 68%。

We set records for total revenue as well as for gaming, data center and professional visualization.

我們創造了總收入以及遊戲、數據中心和專業可視化的記錄。

Starting with gaming, revenue was $3.1 billion, was up 11% sequentially and up 85% from a year earlier.

從遊戲開始，收入為 31 億美元，環比增長 11%，同比增長 85%。

Demand remained exceptionally strong, outpacing supply.

需求仍然異常強勁，超過了供應。

We are now 4 quarters into Ampere architecture product cycle for gaming and it continues to be our best ever.

我們現在進入遊戲的安培架構產品週期 4 個季度，它仍然是我們有史以來最好的。

At Computex in June, we announced 2 powerful new GPUs for gamers and creators, the GeForce RTX 3080 Ti and RTX 3070 Ti, delivering 50% faster performance than their prior generation, with acclaimed features such as real-time retracing, NVIDIA DLSS AI rendering, reflex and broadcast.

在 6 月的 Computex 上，我們為遊戲玩家和創作者發布了 2 款功能強大的新 GPU，即 GeForce RTX 3080 Ti 和 RTX 3070 Ti，其性能比上一代產品快 50%，並具有實時回溯、NVIDIA DLSS AI 渲染等廣受好評的功能，反射和廣播。

Laptop demand was also very strong.

筆記本電腦的需求也非常強勁。

OEMs adopted Ampere architecture GPUs and a record number of designs from the top-of-the-line gaming laptops to those to Main Street price points as low as $799 that bring the power of GeForce CPUs to gamers, students and creators on-the-go.

OEM 採用 Ampere 架構 GPU 和創紀錄數量的設計，從頂級遊戲筆記本電腦到價格低至 799 美元的主流遊戲筆記本電腦，為遊戲玩家、學生和創作者帶來 GeForce CPU 的強大功能。走。

Ampere architecture powered laptops feature our third-generation Max-Q power optimization technology that enables ultrathin designs, such as the new Alienware x15, the world's most powerful sub-16-millimeter gaming laptop.

Ampere 架構驅動的筆記本電腦採用我們的第三代 Max-Q 電源優化技術，可實現超薄設計，例如全新 Alienware x15，世界上最強大的 16 毫米以下游戲筆記本電腦。

NVIDIA RTX technology has reset computer graphics and spurred our biggest ever refresh cycle.

NVIDIA RTX 技術重置了計算機圖形並刺激了我們有史以來最大的更新周期。

Ampere has been our fastest ramping gaming GPU architecture on Steam and the combination of Turing and Ampere RTX GPUs have only upgraded about 20% of our installed base.

Ampere 一直是我們在 Steam 上發展最快的遊戲 GPU 架構，而 Turing 和 Ampere RTX GPU 的組合僅升級了我們大約 20% 的安裝基礎。

80% have yet to upgrade to RTX.

80% 尚未升級到 RTX。

And the audience for global e-sports will soon approach 0.5 billion people, while the number of those who livestream games is expected to reach over 700 million.

全球電競觀眾將很快接近5億人，而直播遊戲的人數預計將達到7億以上。

The number of PC gamers on Steam is up almost 20% over the past year.

Steam 上的 PC 遊戲玩家數量在過去一年中增長了近 20%。

More than 60 RTX games now support NVIDIA's RTX ray tracing or DLSS, including today's biggest game franchises such as Minecraft, Fortnite and Cyberpunk.

超過 60 款 RTX 遊戲現在支持 NVIDIA 的 RTX 光線追踪或 DLSS，包括當今最大的遊戲系列，例如 Minecraft、Fortnite 和 Cyberpunk。

New RTX games this quarter include Red Dead Redemption 2, one of the top-rated games of all time.

本季度的新 RTX 遊戲包括 Red Dead Redemption 2，這是有史以來最受好評的遊戲之一。

Popular titles like Rainbow Six Siege and (inaudible) and Minecraft RTX in China with over 400 million players.

在中國擁有超過 4 億玩家的熱門遊戲，如彩虹六號圍攻和（聽不清）和 Minecraft RTX。

To competitive gamers, NVIDIA Reflex, which includes latency is now supported by 20 games.

對於有競爭力的遊戲玩家來說，包含延遲的 NVIDIA Reflex 現在有 20 款遊戲支持。

Let me say a few words on cryptocurrency mining.

讓我談談加密貨幣挖掘。

In an effort to address the needs of miners and direct GeForce to gamers, we increased the supply of cryptocurrency mining processors or CMP, and introduced low hash rate GeForce GPUs with limited Ethereum mining capability.

為了滿足礦工的需求並將 GeForce 引導至遊戲玩家，我們增加了加密貨幣挖礦處理器或 CMP 的供應，並引入了具有有限以太坊挖礦能力的低哈希率 GeForce GPU。

Over 80% of our Ampere architecture-based GeForce shipments in the quarter were low hash rate GPUs.

本季度我們基於 Ampere 架構的 GeForce 出貨量中超過 80% 是低哈希率 GPU。

The combination of crypto to gaming revenue is difficult to quantify.

加密與遊戲收入的結合很難量化。

CMP revenue, which is recognized in OEM, was $266 million, lower than our original $400 million estimate on reduced mining profitability, and we expect a minimal contribution from CMP going forward.

在 OEM 中確認的 CMP 收入為 2.66 億美元，低於我們最初對採礦盈利能力下降的 4 億美元估計，我們預計 CMP 未來的貢獻微乎其微。

GeForce now reached a new milestone this quarter surpassing 1,000 PC games, more than any other cloud gaming service.

GeForce 現在在本季度達到了一個新的里程碑，超過 1,000 款 PC 遊戲，比任何其他雲遊戲服務都多。

The premium tier is available for a subscription of $10 per month, giving gamers access to RTX class performance, even on an underpowered PC, Mac, Chromebook, iOS or Android device.

高級層的訂閱費為每月 10 美元，讓遊戲玩家即使在動力不足的 PC、Mac、Chromebook、iOS 或 Android 設備上也能獲得 RTX 級性能。

Moving to pro visualization.

轉向專業可視化。

Q2 revenue was a record $519 million, up 40% sequentially and up 156% year-on-year.

第二季度收入達到創紀錄的 5.19 億美元，環比增長 40%，同比增長 156%。

Strong sequential revenue growth was led by desktop workstations, driven by demand to outfit design offices at home, as remote work becomes the norm across industries.

隨著遠程工作成為各行各業的常態，桌面工作站帶動了強勁的連續收入增長，這是由在家中配備設計辦公室的需求推動的。

This is also the first big quarter of the Ampere architecture ramp for pro visualization.

這也是用於專業可視化的 Ampere 架構斜坡的第一個大季度。

Key verticals driving Q2 demand include automotive, public sector and health care.

推動第二季度需求的主要垂直領域包括汽車、公共部門和醫療保健。

At SIGGRAPH last week, we announced an expansion of NVIDIA Omniverse, our simulation and collaboration platform that provides the foundation of the metaverse.

在上週的 SIGGRAPH 上，我們宣布擴展 NVIDIA Omniverse，這是我們的模擬和協作平台，它為 Metaverse 奠定了基礎。

Through our new integrations with Blender, the world's leading open source 3D animation tool and Adobe, we're opening the Omniverse platform to millions of additional users.

通過我們與全球領先的開源 3D 動畫工具 Blender 和 Adobe 的新集成，我們正在向數百萬其他用戶開放 Omniverse 平台。

We are also collaborating with Apple and Pixar to bring advanced physics capabilities to Pixar's Universal Scene Description framework, embracing open standards to provide 3D workflows to billions of devices.

我們還與 Apple 和 Pixar 合作，將先進的物理功能引入 Pixar 的通用場景描述框架，採用開放標準，為數十億台設備提供 3D 工作流程。

Omniverse Enterprise software is in the early access stage and will be generally available later this year on a subscription basis from NVIDIA's partners, including Dell, HP, Lenovo and many others.

Omniverse Enterprise 軟件處於早期訪問階段，將於今年晚些時候在 NVIDIA 的合作夥伴（包括戴爾、惠普、聯想等）的訂閱基礎上普遍提供。

Over 500 companies are evaluating Omniverse Enterprise, including BMW, Volvo and Lockheed Martin, and more than 50,000 individual creators have downloaded Omniverse since it entered open beta in December.

超過 500 家公司正在評估 Omniverse Enterprise，包括寶馬、沃爾沃和洛克希德馬丁，自 Omniverse 於 12 月進入公開測試階段以來，已有超過 50,000 名個人創作者下載了 Omniverse。

Moving to automotive, our Q2 revenue was $152 million, down 1% sequentially and up 3% year-on-year.

轉向汽車業務，我們第二季度的收入為 1.52 億美元，環比下降 1%，同比增長 3%。

Sequential revenue declines in infotainment were largely offset by growth in self-driving.

信息娛樂的連續收入下降在很大程度上被自動駕駛的增長所抵消。

Looking further out, we have substantial design wins set to ramp that we expect will drive a major inflection in revenue in the coming years.

展望未來，我們將獲得大量設計勝利，我們預計這將在未來幾年推動收入的重大轉折。

This quarter, we announced several additional wins.

本季度，我們宣布了幾項額外的勝利。

Self-driving start-up, AutoX, unveiled its latest autonomous driving platform for RoboTaxis powered by NVIDIA DRIVE.

自動駕駛初創公司 AutoX 推出了其最新的由 NVIDIA DRIVE 驅動的 RoboTaxis 自動駕駛平台。

The performance and safe capabilities of the software-defined NVIDIA DRIVE platform has enabled AutoX to become one of the first companies in the world to provide full self-driving mobility services without the need for a safety driver.

軟件定義的 NVIDIA DRIVE 平台的性能和安全功能使 AutoX 成為全球首批無需安全駕駛員即可提供完全自動駕駛移動服務的公司之一。

In autonomous trucking, DRIVE ecosystem partner Plus signed a deal with Amazon to provide at least 1,000 self-driving system to Amazon's fleet of delivery vehicles.

在自動卡車運輸方面，DRIVE 生態系統合作夥伴 Plus 與亞馬遜簽署了一項協議，為亞馬遜的送貨車隊提供至少 1,000 個自動駕駛系統。

These systems are powered by NVIDIA DRIVE for high-performance, energy-efficient and centralized AI compute.

這些系統由 NVIDIA DRIVE 提供支持，可實現高性能、高能效和集中式 AI 計算。

An autonomous trucking start-up, Embark, is building on NVIDIA DRIVE.

自動駕駛卡車初創公司 Embark 正在 NVIDIA DRIVE 上構建。

The system is being developed for trucks for 4 major OEMs: Freightliner, Navistar International, PACCAR and Volvo, representing the vast majority of the Class 8 or largest sized trucks in the U.S. The NVIDIA DRIVE platform is being rapidly adopted across the transportation industry from passenger-owned vehicles to RoboTaxi, to trucking and delivery vehicles.

該系統正在為 4 家主要 OEM 的卡車開發：Freightliner、Navistar International、PACCAR 和沃爾沃，它們代表了美國絕大多數 8 級或最大尺寸的卡車 NVIDIA DRIVE 平台正在從客運到整個運輸行業迅速採用- 自有車輛到 RoboTaxi、卡車和送貨車輛。

We believe everything that moves will be autonomous someday.

我們相信，有朝一日，所有移動的東西都將是自主的。

Moving to data center.

搬到數據中心。

Revenue of $2.4 billion grew 16% sequentially and 35% from the year ago quarter, the year ago quarter, which was our first quarter to include Mellanox.

24 億美元的收入環比增長 16%，比去年同期增長 35%，這是我們第一個加入 Mellanox 的季度。

Growth was driven by both hyperscale customers and vertical industries, each of which had record revenues.

增長是由超大規模客戶和垂直行業推動的，每個行業都有創紀錄的收入。

Our flagship A100 continued to ramp across hyperscale and cloud computing customers, with Microsoft Azure announcing general availability in June following AWS and Google Cloud Platform's general availability in prior quarters.

我們的旗艦 A100 繼續在超大規模和雲計算客戶中推廣，在 AWS 和谷歌云平台在前幾個季度全面上市之後，微軟 Azure 於 6 月宣布全面上市。

Vertical industry demand was strong, with sequential growth led by financial services, supercomputing and telecom customers.

垂直行業需求強勁，金融服務、超級計算和電信客戶帶動環比增長。

We also had exceptional growth in inference, which reached a record more than doubling year-on-year.

我們在推理方面也取得了非凡的增長，達到了創紀錄的同比增長一倍多。

Revenue from inference-focused processors includes the new A30 GPU, which provides 4x the inference performance of the G4.

來自推理處理器的收入包括新的 A30 GPU，它的推理性能是 G4 的 4 倍。

Customers are also turning to NVIDIA GPUs to take AI to production and shifting from CPUs to GPUs driven by the stringent performance, latency and cost requirements of deploying and scaling deep learning AI workload.

由於部署和擴展深度學習 AI 工作負載對性能、延遲和成本的嚴格要求，客戶還轉向 NVIDIA GPU 將 AI 投入生產，並從 CPU 轉向 GPU。

NVIDIA networking products posted solid results.

NVIDIA 網絡產品發布了穩健的業績。

We see momentum across regions driven by our technology leadership, with upgrades to high-speed products, such as ConnectX-6 as well as new customer wins across cloud service providers enterprise and high-performance computing.

我們看到了由我們的技術領先地位推動的跨地區發展勢頭，包括對 ConnectX-6 等高速產品的升級，以及在雲服務提供商企業和高性能計算領域贏得的新客戶。

We extended our leadership in supercomputing, the latest top 500 list shows that NVIDIA technologies power 342 of the world's top 500 supercomputers, including 70% of all new systems and 8 of the top 10.

我們擴大了我們在超級計算領域的領先地位，最新的 500 強榜單顯示，NVIDIA 技術為世界 500 強超級計算機中的 342 台提供支持，其中包括 70% 的所有新系統和前 10 名中的 8 台。

To help companies harness the new industrial, high-performance computing revolution, we deliver a turnkey AI data center solution with the NVIDIA DGX SuperPOD, the same technology that powers our new Cambridge-1 supercomputer in the U.K. and a number of others in the top 500.

為了幫助企業駕馭新的工業、高性能計算革命，我們使用 NVIDIA DGX SuperPOD 提供交鑰匙 AI 數據中心解決方案，該技術為我們在英國的新 Cambridge-1 超級計算機和其他一些頂級超級計算機提供支持500。

We expanded our AI software and subscription offerings, making it easier for enterprises to adopt AI from the initial development stage through to deployment and operations.

我們擴展了我們的人工智能軟件和訂閱產品，使企業更容易從最初的開發階段到部署和運營採用人工智能。

We announced NVIDIA Base Command, our Software-as-a-Service offering for operating and managing large-scale, multiuser and multi-team AI development workloads on DGX SuperPOD.

我們宣布推出 NVIDIA Base Command，這是我們的軟件即服務產品，用於在 DGX SuperPOD 上操作和管理大規模、多用戶和多團隊 AI 開發工作負載。

Base Command is the operating and management system software for distributed training clusters.

Base Command 是分佈式訓練集群的運行管理系統軟件。

We also announced general availability of NVIDIA Fleet Command, our managed Edge AI Software-as-a-Service offering.

我們還宣布全面推出 NVIDIA Fleet Command，這是我們的託管 Edge AI 軟件即服務產品。

Fleet Command helps companies solve the problem of securely deploying and managing AI applications across thousands of locations, combining the efficiency and simplicity of central management with the cost, performance and data sovereignty benefits of real-time processing at the edge.

Fleet Command 幫助公司解決在數千個地點安全部署和管理 AI 應用程序的問題，將中央管理的效率和簡單性與邊緣實時處理的成本、性能和數據主權優勢相結合。

Early adopters of Fleet Command includes some of the world's leading retail manufacturing and logistics companies and the specialty software companies that work with them.

Fleet Command 的早期採用者包括一些世界領先的零售製造和物流公司以及與之合作的專業軟件公司。

The new NVIDIA Base Command and Fleet Command software and subscription offerings followed last quarter's announcement of the NVIDIA AI Enterprise software suite, which is in early access with general availability expected soon.

新的 NVIDIA Base Command 和 Fleet Command 軟件和訂閱產品是在上個季度宣布推出 NVIDIA AI Enterprise 軟件套件之後推出的，該套件處於搶先體驗階段，預計很快就會全面上市。

Our enterprise software strategy is supported by the NVIDIA certified system program with server OEMs, which are bringing to market over 55 systems ready to run on NVIDIA's AI software out of the box to help enterprises simplify and accelerate their AI deployment.

我們的企業軟件戰略得到了與服務器 OEM 合作的 NVIDIA 認證系統計劃的支持，該計劃將超過 55 個系統推向市場，可以在 NVIDIA 開箱即用的 AI 軟件上運行，以幫助企業簡化和加速其 AI 部署。

The NVIDIA ecosystem keeps getting stronger.

NVIDIA 生態系統不斷壯大。

NVIDIA Inception, our acceleration platform for AI start-ups just surpassed 8,500 members.

NVIDIA Inception 是我們面向 AI 初創企業的加速平台，其成員剛剛超過 8,500 名。

With cumulative funding of over $60 billion and members in 90 countries, Inception is one of the largest AI start-up ecosystems in the world.

Inception 累積資金超過 600 億美元，成員遍布 90 個國家/地區，是世界上最大的 AI 初創生態系統之一。

CUDA now has been downloaded 27 million times since it launched 15 years ago, with 7 million in the last year alone.

自 15 年前推出以來，CUDA 現在已經下載了 2700 萬次，僅去年一年就下載了 700 萬次。

TensorRT for inference has been downloaded nearly 2.5 million times across more than 27,000 companies.

用於推理的 TensorRT 已被 27,000 多家公司下載近 250 萬次。

And the total number of developers in the NVIDIA ecosystem now exceeds 2.6 million, up 4x in the past 4 years.

NVIDIA 生態系統中的開發者總數現已超過 260 萬，在過去 4 年中增長了 4 倍。

Let me give you a quick update on Arm.

讓我給你一個關於 Arm 的快速更新。

In nearly 1 year since we initially agreed to combine with Arm, we have gotten to know the company, its business and its people much better.

自從我們最初同意與 Arm 合併以來的近 1 年裡，我們對這家公司、它的業務和它的員工有了更好的了解。

We believe more than ever in the power of our combination and the benefits it will deliver for Arm, for the U.K. and for its customers across the world in the era of AI.

在 AI 時代，我們比以往任何時候都更加相信我們的組合的力量以及它將為 Arm、英國及其全球客戶帶來的好處。

Arm has great potential.

Arm有很大的潛力。

We love their business model and commit to keep its open licensing approach.

我們喜歡他們的商業模式，並承諾保持其開放許可方式。

And with NVIDIA's scale and capabilities, Arm will make more IP and sooner for their mobile and embedded customers, while expanding into data center, IoT and other new markets.

憑藉 NVIDIA 的規模和能力，Arm 將更快地為其移動和嵌入式客戶提供更多 IP，同時擴展到數據中心、物聯網和其他新市場。

NVIDIA accelerates computing, which starts with the CPU, whatever new markets are opened with the CPU and our accelerated computing opportunities.

NVIDIA 加速計算，從 CPU 開始，無論 CPU 和我們的加速計算機會打開了什麼新市場。

We've announced accelerated platforms for Amazon Graviton, Ampere Computing, MediaTek and Marvell, spanning cloud computing, AI, cloud gaming, supercomputing, edge AI to Chrome PCs.

我們已經宣佈為 Amazon Graviton、Ampere Computing、MediaTek 和 Marvell 推出加速平台，涵蓋雲計算、人工智能、雲遊戲、超級計算、邊緣人工智能到 Chrome PC。

We plan to invest in the U.K., and we have with the Cambridge-1 supercomputer, and through Arm, making U.K. a global center in science, technology and AI.

我們計劃在英國投資，我們擁有 Cambridge-1 超級計算機，並通過 Arm，使英國成為全球科學、技術和人工智能中心。

We are working through the regulatory process, although some Arm licensees have expressed concerns and objected to the transaction and discussions with regulators are taking longer than initially thought.

我們正在通過監管程序，儘管一些 Arm 被許可人表達了擔憂並反對交易，並且與監管機構的討論花費的時間比最初想像的要長。

We are confident in the deal and that regulators should recognize the benefit of the acquisition to Arm, its licensees and the industry.

我們對這筆交易充滿信心，監管機構應該認識到此次收購對 Arm、其被許可方和整個行業的好處。

Moving to the rest of the P&L.

轉到損益表的其餘部分。

GAAP gross margin of 64.8% for the second quarter was up 600 basis points from a year earlier, reflecting the absence of certain Mellanox acquisition related costs.

第二季度的 GAAP 毛利率為 64.8%，比去年同期增長 600 個基點，這反映出沒有某些 Mellanox 收購相關成本。

GAAP gross margins was up 70 basis points sequentially.

GAAP 毛利率環比上升 70 個基點。

Non-GAAP gross margins was 66.7%, up 70 basis points from a year earlier and up 50 basis points sequentially, reflecting higher ASPs within desktop GeForce GPUs of continued growth in high-end Ampere architectured products, partially offset by a mix shift within data center.

非 GAAP 毛利率為 66.7%，比去年同期增長 70 個基點，環比增長 50 個基點，這反映了桌面 GeForce GPU 中更高的 ASP 以及高端 Ampere 架構產品的持續增長，部分被數據中的混合變化所抵消中央。

Q2 GAAP EPS was $0.94, up 276% from a year earlier.

第二季度 GAAP 每股收益為 0.94 美元，同比增長 276%。

Non-GAAP EPS was $1.04, up 89% from a year earlier, adjusting for the 4-to-1 stock split effective this quarter.

非 GAAP 每股收益為 1.04 美元，比去年同期增長 89%，調整了本季度生效的 4 比 1 股票分割。

Q2 cash flow from operations was a record $2.7 billion.

第二季度運營現金流達到創紀錄的 27 億美元。

Let me turn to the outlook for the third quarter of fiscal 2022.

讓我談談對 2022 財年第三季度的展望。

We expect another strong quarter, with sequential growth driven largely by accelerating demand in data center.

我們預計又一個強勁的季度，其連續增長主要受數據中心需求加速的推動。

In addition, we expect sequential growth in each of our 3 markets -- in each of our 3 other market platforms.

此外，我們預計我們的 3 個市場中的每一個——在我們的其他 3 個市場平台中的每一個中都會出現連續增長。

Gaming demand is continuing to exceed supply as we expect channel inventories to remain below target levels as we exit Q3.

遊戲需求繼續超過供應，因為我們預計隨著我們退出第三季度，渠道庫存將保持在目標水平以下。

The contribution of CMP to our revenue outlook is minimal.

CMP 對我們收入前景的貢獻微乎其微。

Revenue is expected to be $6.8 billion, plus or minus 2%.

收入預計為 68 億美元，正負 2%。

GAAP and non-GAAP gross margins are expected to be 65.2% and 67%, respectively, plus or minus 50 basis points.

GAAP 和非 GAAP 毛利率預計分別為 65.2% 和 67%，上下浮動 50 個基點。

GAAP and non-GAAP operating expenses are expected to be approximately $1.96 billion and $1.37 billion, respectively.

GAAP 和非 GAAP 運營費用預計分別約為 19.6 億美元和 13.7 億美元。

GAAP and non-GAAP other income and expenses are both expected to be an expense of approximately $60 million, excluding gains and losses on equity securities.

GAAP 和非 GAAP 其他收入和支出預計都將是大約 6000 萬美元的支出，不包括權益證券的損益。

GAAP and non-GAAP tax risks are supposed to be expected 11%, plus or minus 1%, excluding discrete items.

GAAP 和非 GAAP 稅收風險預計為 11%，正負 1%，不包括離散項目。

Capital expenditures are expected to be approximately $200 million to $225 million.

資本支出預計約為 2 億至 2.25 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 will be attending the following virtual events: the BMO Technology Summit on August 24; the New Street Big Ideas in Semiconductor's Conference on September 9; the Citi Global Tech Conference on September 13; the Piper Sandler Global Technology Conference on September 14; and the Evercore ISI Auto, Tech & AI Forum on September 21.

我們將參加以下虛擬活動： 8 月 24 日的 BMO 技術峰會； 9 月 9 日半導體大會上的 New Street Big Ideas； 9月13日花旗全球科技大會； 9 月 14 日的 Piper Sandler 全球技術大會；以及 9 月 21 日的 Evercore ISI 汽車、技術和人工智能論壇。

Our earnings call to discuss the third quarter results is scheduled for Wednesday, November 17.

我們討論第三季度業績的財報電話會議定於 11 月 17 日星期三舉行。

We will now open the call up for questions.

我們現在將打開電話提問。

Operator, would you please poll for questions?

接線員，請您投票提問嗎？

(Operator Instructions) First question comes from the line of Vivek Arya of Bank of America.

（操作員說明）第一個問題來自美國銀行的 Vivek Arya。

I actually had a near and longer-term question on the data center.

實際上，我對數據中心有一個近期和長期的問題。

I think near term, you mentioned the possibility of accelerating data center growth from the 35% rate.

我認為在短期內，您提到了從 35% 的速度加速數據中心增長的可能性。

I was hoping if you could give us some more color around that confidence and visibility.

我希望你能給我們更多的信心和知名度。

And then longer term, Jensen, we have seen a lot of announcements from NVIDIA about your enterprise software opportunity.

從長遠來看，Jensen，我們已經看到 NVIDIA 發布了很多關於您的企業軟件機會的公告。

I honestly don't know how to model that.

老實說，我不知道如何建模。

It sounds very promising, but how should we model it?

這聽起來很有希望，但我們應該如何建模呢？

What problem are you trying to solve?

你想解決什麼問題？

Is it cannibalizing demand you have otherwise seen from your public cloud customers?

它是否會蠶食您從公共雲客戶那裡看到的需求？

Or is this incremental to growth?

或者這是增長的增量？

So just any guidance or any just insights into how to think about NVIDIA's enterprise software opportunity longer term?

那麼，對於如何從長遠角度考慮 NVIDIA 的企業軟件機會，是否有任何指導或見解？

Yes, thanks for the question.

是的，謝謝你的提問。

We are seeing accelerated -- as we have already reported that we have record revenues in both hyperscale, cloud and industrial enterprise this last quarter.

我們正在加速——正如我們已經報告過的那樣，上個季度我們在超大規模、雲計算和工業企業方面的收入都創下了紀錄。

And we're seeing accelerated growth.

我們看到了加速增長。

The acceleration in hyperscale and cloud comes from the transition of the cloud service providers in taking their AI applications, which are now heavily deep learning-driven into production.

超大規模和雲計算的加速來自云服務提供商在將其 AI 應用程序引入生產方面的轉變，這些應用程序現在被深度學習驅動到生產中。

There were some of the things that we've spoken about in the past that really makes NVIDIA the ideal platform to scale out with.

我們過去談到的一些事情確實使 NVIDIA 成為橫向擴展的理想平台。

And if my line is a little worse, let me apologize.

如果我的台詞有點糟糕，讓我道歉。

The several platforms -- the several elements of our platform, number one, Ampere GPU, which is now a universal GPU for AI, for training but incredibly good for inference.

幾個平台——我們平台的幾個元素，第一，Ampere GPU，它現在是人工智能的通用 GPU，用於訓練但非常適合推理。

It's terrific in its throughput, it's terrific in its fast response time as well, and therefore, the cost of deployment, the cost of operating AI applications is the lowest.

它的吞吐量非常好，它的快速響應時間也非常好，因此，部署成本，運行人工智能應用程序的成本是最低的。

The second is the introduction of TensorRT, which is our optimizing compiler that makes it possible for us to compile and optimize any AI application to our GPUs.

第二個是引入了 TensorRT，這是我們的優化編譯器，它使我們能夠將任何 AI 應用程序編譯和優化到我們的 GPU 上。

And whether it's computer vision or natural language understanding, conversational AI, recommender systems, the type of applications that are deploying AI is really quite vast.

而且無論是計算機視覺還是自然語言理解、對話式人工智能、推薦系統，部署人工智能的應用程序類型確實非常廣泛。

And then lastly, this software inference server that we offer called Triton, which supports every one of our GPUs.

最後，我們提供的這款名為 Triton 的軟件推理服務器支持我們的每一款 GPU。

It supports CPUs as well as GPUs.

它支持 CPU 和 GPU。

So every Internet service provider could operate their entire data center using Triton.

因此，每個互聯網服務提供商都可以使用 Triton 來運營他們的整個數據中心。

These several things are really accelerating our growth, which is -- so the first element is the deployment, the transition of deep learning AI applications into large-scale deployment.

這幾件事確實在加速我們的增長，那就是——所以第一個要素是部署，將深度學習 AI 應用程序轉變為大規模部署。

In the enterprise, the application that is driving AI, as you know, every enterprise must be -- wants to move and race towards being a tech company and take advantage of connected cloud and connected devices and artificial intelligence to achieve it.

在企業中，驅動人工智能的應用程序，正如你所知，每個企業都必須——想要移動並競相成為一家科技公司，並利用連接的雲和連接的設備以及人工智能來實現它。

We have an opportunity to deploy AI services out of the edge.

我們有機會在邊緣之外部署人工智能服務。

And in order to do so, there are several things that has to happen.

為了做到這一點，有幾件事必鬚髮生。

First, we have to create a computing platform that allows them to do training in the IT environment that they understand, which is virtualized, which is largely managed by VMware.

首先，我們必須創建一個計算平台，讓他們能夠在他們理解的 IT 環境中進行培訓，該環境是虛擬化的，主要由 VMware 管理。

And our collaboration with VMware, creating a new type of system that could be integrated with enterprise was -- has been quite a significant effort and it's in volume production today.

我們與 VMware 的合作，創建了一種可以與企業集成的新型系統，這是一項相當大的努力，今天它已經投入批量生產。

The second is a server that allows the enterprise customers to deploy their AR models out to the edge.

第二個是允許企業客戶將他們的 AR 模型部署到邊緣的服務器。

And the AI engine, the software suite that we've been developing over the last 10 years now have been integrated into this environment and allows the enterprises to basically run AI out of the box.

人工智能引擎，我們過去 10 年一直在開發的軟件套件，現在已經集成到這個環境中，讓企業基本上可以開箱即用地運行人工智能。

There's 3 elements of our software products there.

我們的軟件產品有 3 個元素。

First is NVIDIA AI Enterprise and that puts -- that basically puts all of the state-of-the-art AI solvers and engines and libraries that we've industrialized and perfected over the years, made it available to enterprise to license.

首先是 NVIDIA AI Enterprise，它基本上將我們多年來工業化和完善的所有最先進的 AI 求解器、引擎和庫都提供給企業進行許可。

Second,is an operating system platform called Base Command that allows for distributed scale up software development in the -- for training and developing models.

其次，是一個名為 Base Command 的操作系統平台，它允許在訓練和開發模型中進行分佈式擴展軟件開發。

And then the third is Fleet Command, which is an operating system software product that lets you operate and deploy and manage the AI models out to the edge.

第三個是 Fleet Command，它是一種操作系統軟件產品，可讓您在邊緣操作、部署和管理 AI 模型。

These 3 software products, in combination with the server called NVIDIA-Certified, taken out through our network of partners, is our strategy to accelerate the adoption of AI by the enterprise customers.

這 3 款軟件產品與通過我們的合作夥伴網絡推出的稱為 NVIDIA 認證的服務器相結合，是我們加速企業客戶採用 AI 的戰略。

And so we're really enthusiastic about entering into the software business model.

所以我們非常熱衷於進入軟件商業模式。

This is an opportunity that could represent, of course, tens of millions of servers.

當然，這是一個可以代表數千萬台服務器的機會。

We believe all of them will be GPU accelerated.

我們相信所有這些都將被 GPU 加速。

We believe that enterprises will be deploying and taking advantage of AI to revolutionize their industry.

我們相信，企業將部署和利用人工智能來徹底改變他們的行業。

And using quite a traditional enterprise software licensing business model, this could represent billions of dollars of business opportunity for us.

使用相當傳統的企業軟件許可商業模式，這對我們來說可能意味著數十億美元的商業機會。

Next question comes from the line of Stacy Rasgon of Bernstein.

下一個問題來自伯恩斯坦的 Stacy Rasgon。

I wanted to go back, Colette, to the sequential guidance.

科萊特，我想回到順序指導。

You gave a little bit of color by segment.

你按段給了一點顏色。

If I look at your gaming revenues, it's kind of like 3 quarters in a row, you've been up, call it, ballpark 10% or 11%.

如果我看一下你們的遊戲收入，就好像連續 3 個季度一樣，你們一直在上升，稱其為 10% 或 11%。

And my understanding is that was sort of a function of your ability to bring on supply.

我的理解是，這在某種程度上取決於您提供供應的能力。

So I guess what does the supply addition look like as you're going from Q2 into Q3?

所以我猜你從第二季度到第三季度的供應增加是什麼樣的？

And do you think you can still maintain that kind of sequential growth?

你認為你還能保持這種連續增長嗎？

Or does it dial down?

還是撥號？

Because I also need to -- I also would play that against your other commentary suggesting that the sequential growth, and I assume on a dollar basis was driven primarily by data centers.

因為我還需要 - 我也將與您的其他評論進行對比，即連續增長，我假設以美元為基礎主要是由數據中心驅動的。

So how do I think about the interplay within those comments of sequential growth of gaming, especially given the trajectory we've had over the last several quarters?

那麼我如何看待這些關於遊戲連續增長的評論之間的相互作用，特別是考慮到我們在過去幾個季度的軌跡？

Yes.

是的。

So let me start, and I'll let Jensen add a bit, Stacy, to your question.

讓我開始吧，讓 Jensen 補充一點，Stacy，你的問題。

I guess we're providing the guidance for Q3 of $6.8 billion in revenue.

我想我們正在為第三季度提供 68 億美元的收入指導。

Now excluding CMP, we expect our revenue to grow over $500 million sequentially.

現在不包括 CMP，我們預計我們的收入將連續增長超過 5 億美元。

The lion's share of that sequential revenue increase will be coming from data center.

連續收入增長的最大份額將來自數據中心。

We do expect gaming to be up slightly on a sequential basis.

我們確實預計遊戲將在連續的基礎上略有上升。

But remember, we are still supply constrained.

但請記住，我們仍然受到供應限制。

Automotive and Pro Viz are also expected to be up slightly quarter-over-quarter.

預計汽車和 Pro Viz 也將環比小幅增長。

And from a CMP perspective, we'll probably just have minimal amounts in Q3.

從 CMP 的角度來看，我們在第三季度可能只會有最少的數量。

So our Q3 results don't have seasonality with them for gaming and are really about the supply that we believe we can have for Q3.

因此，我們第三季度的結果對遊戲沒有季節性，並且實際上與我們認為第三季度可以擁有的供應有關。

I'll see if Jensen wants to add any more color.

我會看看 Jensen 是否想添加更多顏色。

Yes.

是的。

Thanks for the question.

謝謝你的問題。

As you know, RTX is a fundamental reset of computer graphics.

如您所知，RTX 是計算機圖形的基本重置。

This is a technology called ray tracing that has been the holy grail of computer graphics for quite a long time in 35 years.

這是一項稱為光線追踪的技術，35 年來一直是計算機圖形學的聖杯。

In research -- in our NVIDIA research for 10 years, we finally made it possible to do real-time ray tracing with RTX.

在研究中——在我們 NVIDIA 10 年的研究中，我們終於使使用 RTX 進行實時光線追踪成為可能。

RTX demand is quite incredible.

RTX 的需求非常令人難以置信。

And as you know, we have a large install base of PC gamers.

如您所知，我們擁有龐大的 PC 遊戲玩家安裝基礎。

They use an architecture called GTX based on programmable shaders that we invented some 20 years ago.

他們使用基於我們大約 20 年前發明的可編程著色器的稱為 GTX 的架構。

And now we've reset the entire installed base.

現在我們已經重置了整個安裝基礎。

And Ampere is obviously just an incredible selling.

而安培顯然只是一個令人難以置信的銷售。

It's the best-selling GPU architecture in the history of our company.

這是我們公司歷史上最暢銷的 GPU 架構。

And yet we've only upgraded some 20% -- less than 20% of our total installed base.

然而，我們只升級了大約 20%——不到我們總安裝基礎的 20%。

So there's another 80% of the world's PC gaming market that we have yet to upgrade to RTX.

因此，我們還有 80% 的全球 PC 遊戲市場尚未升級到 RTX。

Meanwhile, the number of PC gamers in the world grew substantially, still grew 20% this last year.

與此同時，全球PC遊戲玩家數量大幅增長，去年仍增長了20%。

And so I think the -- we're right at the beginning of our RTX transition.

所以我認為 - 我們正處於 RTX 過渡的開始階段。

Meanwhile, computer graphics has expanded into so many different new markets.

與此同時，計算機圖形學已經擴展到許多不同的新市場。

RTX, we've known -- we've always believed we'll reinvent the way that people do design.

RTX，我們知道——我們一直相信我們會徹底改變人們的設計方式。

And we're seeing that happening right now as we speak, as workstations is growing faster than ever and has achieved record revenues.

我們正在看到這種情況正在發生，因為工作站的增長速度比以往任何時候都快，並且已經實現了創紀錄的收入。

And at the same time, because of all of our work with cloud gaming, we now see public clouds putting the cloud graphics, whether it's workstations or PC or private gaming console up in the cloud.

同時，由於我們在雲遊戲方面的所有工作，我們現在看到公共雲將雲圖形，無論是工作站、個人電腦還是私人遊戲控制台都放在雲中。

So we're seeing strong demand in PCs, in laptops, in workstations and mobile workstations and cloud.

因此，我們看到個人電腦、筆記本電腦、工作站和移動工作站以及雲的需求強勁。

And so RTX is really doing great.

因此，RTX 確實做得很好。

We're -- our challenge there is that demand is just so much great in supply and then as closely we'll do supply constraints.

我們 - 我們面臨的挑戰是供應的需求是如此之大，然後我們將盡可能地限制供應。

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

您的下一個問題來自 Cowen 的 Matt Ramsay。

Yes.

是的。

Before my question, Jensen, I just wanted to say congrats on the nice award.

在我提問之前，Jensen，我只想祝賀你獲得了不錯的獎項。

That's a big honor.

這是一個很大的榮譽。

For my question, I wanted to follow on, on Stacy's question about supply and Colette, maybe you could give us a little bit of commentary around supply constraints in gaming in the different tiers or price tiers of your gaming cards.

對於我的問題，我想繼續討論 Stacy 關於供應和 Colette 的問題，也許您可以就您的遊戲卡的不同層級或價格層級的遊戲供應限制給我們一些評論。

I'm just trying to get a better understanding as to how you guys are managing supply across the different price tiers?

我只是想更好地了解你們如何管理不同價格層的供應？

And I guess it translates into a question of are the gaming ASPs that we're seeing in the October quarter guidance -- are those what you would call sustainable going forward?

而且我想這會轉化為一個問題，即我們在 10 月季度指南中看到的遊戲 ASP 是不是你所說的可持續發展？

Or do you feel like that mix may change as supply comes online?

或者你覺得隨著供應的上線，這種組合可能會發生變化？

So I'll start here.

所以我將從這裡開始。

Thanks for the question on our overall mix as we go forward.

感謝您在我們前進的過程中提出關於我們整體組合的問題。

First, our supply constraint in our gaming business is largely attributed to our desktop and notebook.

首先，我們遊戲業務的供應限制主要歸因於我們的台式機和筆記本電腦。

That can mean a lot of different things from our components that are necessary to build so many of our products.

這可能意味著與我們的組件有很多不同的東西，這些都是構建我們這麼多產品所必需的。

But our mix is really important.

但是我們的組合真的很重要。

Our mix as we are also seeing many of our gamers very interested in our higher-end, higher performance products.

我們的組合，因為我們也看到我們的許多遊戲玩家對我們的更高端、更高性能的產品非常感興趣。

We will continue to see that as a driver of that overall lift, both our revenue and can lift our overall gross margins.

我們將繼續看到，作為整體提升的驅動因素，我們的收入和可以提升我們的整體毛利率。

So there's quite a few different pieces into our supply that we have to think about, but we are going to try and make the best solutions for our gamers at this time.

所以我們的供應中有很多不同的部分是我們必須考慮的，但我們現在將嘗試為我們的遊戲玩家製定最佳解決方案。

Next question, we have the line from C.J. Muse from Evercore.

下一個問題，我們有來自 Evercore 的 C.J. Muse 的台詞。

I guess a follow-up question on the supply constraints.

我想是關於供應限制的後續問題。

When do you think that will ease?

你認為什麼時候會緩解？

And how should we think about gaming into the January quarter vis-a-vis typical seasonality, given I would assume you would continue to be supply constrained?

鑑於我假設您將繼續受到供應限制，我們應該如何考慮到 1 月季度的遊戲與典型的季節性？

Colette, I can take it or you can, either one of us.

科萊特，我可以接受，或者你可以，我們中的任何一個。

Go ahead, Jensen and I'll follow up if there's some other things.

繼續，Jensen，如果有其他事情我會跟進。

Okay.

好的。

We're supply constrained in graphics -- we're supply constrained in graphics while we're delivering record revenues in graphics.

我們在圖形方面的供應受到限制——我們在圖形方面的供應受到限制，而我們在圖形方面提供創紀錄的收入。

Cloud gaming is growing, cloud graphics is growing.

雲遊戲正在增長，雲圖形正在增長。

RTX made it possible for us to address the design and the creative workstations.

RTX 使我們能夠處理設計和創意工作站。

Historically, the rendering of ray tracing and photo-realistic images has largely been done on CPUs and for the very first time, and we could actually accelerate it with NVIDIA GPUs and with RTX GPUs.

從歷史上看，光線追踪和照片般逼真的圖像的渲染主要是在 CPU 上完成的，而且是第一次，我們實際上可以使用 NVIDIA GPU 和 RTX GPU 對其進行加速。

And so the workstation market is really doing great.

所以工作站市場確實做得很好。

The backdrop of that, of course, is that people are building offices in their homes.

當然，其背景是人們在家中建造辦公室。

And for many of the designers and creators around the world, some 20 million of them, they have to create -- they have to build a workstation or an office at home as well as they want at work, because remote work is the new norm.

對於世界各地的許多設計師和創作者（其中約有 2000 萬）來說，他們必須創造——他們必須在家裡建造工作站或辦公室，就像他們在工作中想要的那樣，因為遠程工作是新常態.

And meanwhile, of course, RTX has reached all of our consumer graphics, the few hundred million installed base of PC gamers, and it's time to upgrade.

與此同時，當然，RTX 已經覆蓋了我們所有的消費級顯卡，數億安裝的 PC 遊戲玩家群，是時候升級了。

And so there's a whole bunch of reasons we're achieving record revenue as well as supply constrain.

因此，我們實現創紀錄收入和供應限制的原因有很多。

We have enough supply to meet our second half company growth plans.

我們有足夠的供應來滿足我們下半年的公司增長計劃。

And in next year, we expect to be able to achieve our company's growth plans for next year.

並且在明年，我們希望能夠實現我們公司明年的增長計劃。

Meanwhile, we have and are securing a pretty significant long-term supply commitments as we expand into all these different market initiatives that we've set ourselves up for.

同時，隨著我們擴展到我們為自己設定的所有這些不同的市場計劃，我們已經並且正在確保相當重要的長期供應承諾。

And so I think the -- I would expect that we will see a supply constrained environment for the vast majority of next year is my guess at the moment.

所以我認為 - 我預計明年大部分時間我們將看到供應受限的環境是我目前的猜測。

But a lot of that has to do with the time of our demand is just too great.

但這在很大程度上與我們的需求時間太大有關。

RTX is really a once-in-a-generation reset of computer -- modern computer graphics.

RTX 確實是計算機的千載難逢的重置——現代計算機圖形。

Nothing like this has happened.

沒有發生過這樣的事情。

It's so convenient computer graphics.

它是如此方便的計算機圖形。

And so the invention is really quite groundbreaking and you can see us in that.

因此，這項發明確實非常具有開創性，您可以在其中看到我們。

Next question comes from the line of Harlan Sur of JPMorgan.

下一個問題來自摩根大通的 Harlan Sur。

Congratulations on the strong results, outlook and execution.

祝賀強勁的結果、前景和執行力。

The Mellanox networking franchise has been a really strong and synergistic addition to the NVIDIA compute portfolio.

Mellanox 網絡特許經營權是 NVIDIA 計算產品組合的一個非常強大和協同的補充。

I think kind of near to midterm, the team is benefiting from the transition to 200 and 400 gig networking connectivity and cloud and hyperscale.

我認為接近中期，團隊正在從向 200 和 400 gig 網絡連接以及雲和超大規模的過渡中受益。

And then I think in addition to that, you guys are getting some good traction with the BlueField SmartNIC products.

然後我認為除此之外，你們對 BlueField SmartNIC 產品的吸引力也很大。

Can you just give us a sense on how the business is trending year-over-year?

您能否讓我們了解一下該業務的逐年趨勢？

And do you expect continued quarter-over-quarter networking momentum into the second half of this year, especially as the cloud and hyperscalers are going to a server and CapEx spending cycle?

您是否預計今年下半年會繼續保持季度環比的網絡增長勢頭，尤其是在雲計算和超大規模企業進入服務器和資本支出週期的情況下？

Yes, really appreciate that question.

是的，非常感謝這個問題。

Mellanox had a solid growth quarter.

Mellanox 的季度增長穩健。

And the Mellanox networking business is really growing incredibly.

Mellanox 網絡業務的增長確實令人難以置信。

There are 3 dynamics happening all at the same time.

有 3 種動態同時發生。

The first is the transition that you're talking about.

首先是你所說的過渡。

You know that the world's data centers, hyperscale data centers are -- use this form of computing called disaggregated, which basically means that a single application is running on multiple servers at the same time.

你知道世界上的數據中心，超大規模數據中心——使用這種稱為分解的計算形式，這基本上意味著單個應用程序同時在多個服務器上運行。

This is what makes it possible for them to scale out.

這就是使他們能夠向外擴展的原因。

The more users for an AI application or service, just have to add more servers.

人工智能應用程序或服務的用戶越多，只需添加更多服務器。

And so the ease of scale-out that disaggregated computing provides also puts enormous pressure on the networking.

因此，分解計算提供的橫向擴展的便利性也給網絡帶來了巨大的壓力。

And Mellanox has the world's lowest latency and highest bandwidth and performance networking on the planet.

Mellanox 擁有全球最低延遲、最高帶寬和性能網絡。

And so the ability to scale out and the ability to provision disaggregated applications, it is really much, much better with Mellanox networking.

因此，擴展能力和提供分解應用程序的能力，對於 Mellanox 網絡來說真的要好得多。

So that's number one.

所以這是第一名。

Number two, almost every company in the world has to be a high-performance computing company.

第二，世界上幾乎每家公司都必須是高性能計算公司。

You see that the cloud service providers, one after another, are building effectively supercomputers.

您會看到，一個接一個的雲服務提供商正在有效地構建超級計算機。

What historically was InfiniBand and supercomputing data -- supercomputing centers, the cloud service providers have to build supercomputers themselves.

歷史上是 InfiniBand 和超級計算數據——超級計算中心，雲服務提供商必須自己構建超級計算機。

And the reason for that is because of artificial intelligence in turning these gigantic models.

其原因是因為人工智能在轉動這些巨大的模型。

The rate of growth of our network sizes -- AI model sizes is doubling every 2 months.

我們網絡規模的增長速度——人工智能模型規模每 2 個月翻一番。

It's doubling not every year or 2 years, it's doubling every 2 months.

它不是每年或兩年翻一番，而是每兩個月翻一番。

And so you could imagine the size.

所以你可以想像它的大小。

We're now talking about training AI models that are 100 trillion parameters large.

我們現在談論的是訓練具有 100 萬億個參數的 AI 模型。

The human brain has 150-plus trillion synapses and, so -- or neurons.

人腦有 150 多萬億個突觸，因此——或神經元。

And so that gives you a sense of the scale of AI models that people are developing.

這樣一來，您就可以了解人們正在開發的 AI 模型的規模。

And so you will see supercomputers that are built out of Mellanox InfiniBand and the high-speed networking along with NVIDIA GPU computing in more and more cloud service providers.

因此，您將在越來越多的雲服務提供商中看到由 Mellanox InfiniBand 和高速網絡以及 NVIDIA GPU 計算構建的超級計算機。

You're also seeing it in enterprise for use in the discovery of drugs.

您還可以在企業中看到它用於發現藥物。

There's a digital biology revolution going on as the computation is stable.

隨著計算的穩定，一場數字生物學革命正在發生。

At a large-scale computing that we're able to do now and AI, better understand biology and better and better understand chemistry and bringing both of those fields into the field of information sciences.

在我們現在能夠進行的大規模計算和人工智能中，更好地理解生物學，更好地理解化學，並將這兩個領域帶入信息科學領域。

And so you're seeing large supercomputers being built in enterprises around the world as well.

所以你會看到世界各地的企業也在建造大型超級計算機。

And so the second dynamic has to do with our incredibly great networking, InfiniBand networking side as well, de facto standard in high-performance computing.

因此，第二個動態與我們令人難以置信的出色網絡、InfiniBand 網絡方面以及高性能計算的事實上的標準有關。

And the third dynamic, is data centers doing stock work.

第三個動力是數據中心做庫存工作。

In order to orchestrate and run a data center, they're just a few people, essentially running our entire data center, hundreds of thousands of servers as if it's just one computer in front of you, that entire data center is software-defined.

為了編排和運行一個數據中心，他們只是幾個人，本質上是運行我們整個數據中心，數十萬台服務器，就好像它只是你面前的一台計算機一樣，整個數據中心是軟件定義的。

And not the software that goes into that software device data center running on today's CPUs, it's the networking stack, the storage stack and now because of Zero Trust the security stack, all of that is putting enormous pressure on the available computing capacity for applications, which is ultimately what data centers are designed to do.

而不是進入在當今 CPU 上運行的軟件設備數據中心的軟件，而是網絡堆棧、存儲堆棧以及現在由於零信任的安全堆棧，所有這些都對應用程序的可用計算能力施加了巨大壓力，這最終是數據中心的設計目的。

And so the software-defined data center needs to have a place to take that infrastructure software and accelerate it, to offload it, to accelerate it and very importantly to isolate it from application plan so that intruders can't jump into the operating system, if you will, of your data center, the fabric of your data center.

所以軟件定義的數據中心需要有一個地方來存放基礎設施軟件並加速它，卸載它，加速它，非常重要的是把它從應用程序計劃中隔離出來，這樣入侵者就不能跳入操作系統，如果你願意，你的數據中心，你的數據中心的結構。

And so the answer to that is BlueField.

所以答案就是 BlueField。

The ability to offload, accelerate and isolate this -- the data center software infrastructure and to free up all of the CPUs to run what they're supposed to run, which is the application.

卸載、加速和隔離數據中心軟件基礎設施的能力，並釋放所有 CPU 以運行它們應該運行的東西，即應用程序。

Just about every data center in the world is moving towards a zero trust model and BlueField has just been incredibly well positioned.

世界上幾乎每個數據中心都在朝著零信任模式邁進，而 BlueField 的定位非常好。

So these 3 dynamics, disaggregated computing, which means really strong with fast networking; every company using high-performance computing; and then lastly, software-defined data centers on zero trust.

所以這 3 個動態，分解計算，這意味著非常強大的快速網絡；每家使用高性能計算的公司；最後是零信任的軟件定義數據中心。

And so these are really important dynamics, and I appreciate the opportunity to tell you on that.

所以這些都是非常重要的動態，我很高興有機會告訴你。

You can just tell how super excited I'm about the prospects of this networking business and the employment that they have in building modern data centers.

你可以說我對這個網絡業務的前景以及他們在建設現代數據中心方面的就業感到非常興奮。

Next question comes from the line of Aaron Rakers of Wells Fargo.

下一個問題來自富國銀行的 Aaron Rakers。

Yes.

是的。

I think you hit on a lot of my question around the data center in that last one.

我想你在最後一個問題中提到了我關於數據中心的很多問題。

So maybe I'll just ask kind of on a P&L basis.

所以也許我會在損益的基礎上詢問。

One of the things that I see in the results or more importantly, the guide, is you're now, Colette, guiding over 67% gross margin potentially.

我在結果中看到的一件事，或者更重要的是，指南，是你現在，科萊特，指導潛在的毛利率超過 67%。

I'm curious as we move forward, how do you think about the incremental operating gross margin upside still from here and how you're thinking about the operating margin leverage for the company from here through the P&L?

我很好奇，隨著我們的前進，您如何看待仍然從這裡開始的增量營業毛利率上升，以及您如何考慮公司從這裡到損益表的營業利潤率槓桿？

Yes.

是的。

Colette, if you don't mind, let me take that and you could just follow-up with the details, that would be great.

Colette，如果你不介意，讓我接受，你可以跟進細節，那太好了。

I think at the highest level -- I really appreciate the question.

我認為在最高級別 - 我真的很感激這個問題。

At the highest level, the important thing to realize is that artificial intelligence, it is the single greatest technology force that the computer industry has ever seen and potentially the world has ever seen.

在最高層面上，重要的是要意識到人工智能，它是計算機行業所見過的最偉大的技術力量，並且可能是世界所見過的。

The automation opportunities, which drives productivity, which translates directly to the cost savings to the company, is enormous.

提高生產力並直接轉化為公司成本節約的自動化機會是巨大的。

And it opens up opportunities for technology and computing companies, like it ever never happened before.

它為技術和計算公司提供了前所未有的機會。

And let me just give you some example.

讓我舉個例子。

The fact that we could apply so much technology to warehouse logistics, retail automation, customer call center automation is really quite unprecedented.

我們可以將如此多的技術應用於倉庫物流、零售自動化、客戶呼叫中心自動化這一事實確實是前所未有的。

The fact that we could automate truck driving and last mile delivery, providing an automated chauffeur.

事實上，我們可以自動化卡車駕駛和最後一英里交付，提供自動司機。

Those kind of services and benefits and products are never imaginable before.

這些服務、福利和產品是以前無法想像的。

And so the size of the IT industry, if you will, the industry that computer companies like ourselves are part of, has expanded tremendously.

因此，IT 行業的規模，如果你願意的話，像我們這樣的計算機公司所屬的行業，已經大大擴展。

And so the thing that we want to do is to invest as smartly, but as quickly as we can to go after the large operating -- large business opportunities where we can make a real impact.

因此，我們要做的就是盡可能明智地進行投資，但要盡可能快地去追求大型運營——我們可以產生真正影響的大型商業機會。

And in doing so, while doing so, to do so in a way that is architecturally sensible, one of the things that is really an advantage of our company, it is the nature of the way that we build products, the nature of the way that we build software, our discipline around the architecture, which allows us to be so efficient while doing -- while addressing climate science on the one hand, digital biology on the other, artificial intelligence and robotics and self-driving cars.

在這樣做的同時，以一種在架構上合理的方式這樣做，這是我們公司真正的優勢之一，這是我們構建產品的方式的本質，方式的本質我們圍繞架構構建軟件，這是我們的學科，它使我們能夠在做事時如此高效——一方面解決氣候科學問題，另一方面解決數字生物學問題，人工智能、機器人技術和自動駕駛汽車。

And of course, we already talked about computer graphics and videos.

當然，我們已經討論過計算機圖形和視頻。

Using one architecture and having the ability to -- and having the discipline now for almost 30 years has given us incredible operating leverage.

使用一種架構並有能力 - 並且現在擁有近 30 年的紀律給了我們令人難以置信的運營槓桿。

That's where the vast majority of our operating leverage comes from, which is architectural.

這就是我們絕大多數運營槓桿的來源，它是架構性的。

The technology is architectural, our products are architectural in that way and the company has been built architecturally in that way.

技術是架構性的，我們的產品就是這樣架構的，而公司就是以這種方式在架構上建立起來的。

And so hopefully, as we go after these large market opportunities that AI has provided us, and we do so in a smart and disciplined way with great leverage through our architecture, we can continue to drive really great operating leverage for this company and for our shareholders.

所以希望，當我們追求人工智能為我們提供的這些巨大的市場機會時，我們以一種聰明而有紀律的方式通過我們的架構發揮巨大的槓桿作用，我們可以繼續為這家公司和我們的股東。

We have the next question, comes from the line of John Pitzer of Crédit Suisse.

我們有下一個問題，來自瑞士信貸的 John Pitzer。

I apologize for the short-term nature of this question.

對於這個問題的短期性質，我深表歉意。

But it's what I get asked most frequently.

但這是我最常被問到的問題。

I kind of want to return to the impact of crypto with the potential impact of crypto, Colette or Jensen, is there any way to kind of gauge the effectiveness of the low hash rate GeForce?

我有點想回到加密的影響以及加密、Colette 或 Jensen 的潛在影響，有沒有辦法衡量低哈希率 GeForce 的有效性？

Why only 80% and not 100%?

為什麼只有 80% 而不是 100%？

And how confident are you that the CMP business being down as a reflection of crypto cooling off versus perhaps LHR not being that effective?

您對 CMP 業務下滑反映加密貨幣降溫與 LHR 可能沒有那麼有效的信心有多大？

And I bring it up because there's a lot of blogs out there that would suggest that there are -- as much as you guys are trying to limit the ability of miners to use GeForce, there are some workarounds.

我提出這個問題是因為有很多博客表明存在——儘管你們試圖限制礦工使用 GeForce 的能力，但還是有一些解決方法。

Yes.

是的。

Go ahead.

前進。

Yes.

是的。

Let me start there and answer a couple of the questions about our strategy that we've put in place in this last couple of quarters.

讓我從這裡開始，回答幾個關於我們在過去幾個季度實施的戰略的問題。

As you recall, what we put in place was the low hash rate cards as well as putting in the CMP cards.

您還記得，我們使用的是低哈希率卡以及 CMP 卡。

The low hash rate cards were to provide for more supply for our GeForce gamers that are out there.

低哈希率卡旨在為我們的 GeForce 遊戲玩家提供更多供應。

We articulated one of the metrics that we were looking is what percentage of those cards.

我們闡明了我們正在尋找的指標之一是這些卡片的百分比。

In Ampere, we were able to sell with lowest hash cost.

在 Ampere，我們能夠以最低的哈希成本進行銷售。

Almost all of our cards in Ampere are low hash rates, but also we are selling other types of cards as well.

我們在 Ampere 中幾乎所有的卡都是低哈希率的，但我們也在銷售其他類型的卡。

But at this time, as we move forward, we're much higher than 80%.

但是此時，隨著我們的前進，我們的比例遠遠高於 80%。

But just at the end of this last quarter, we were approximately 80%.

但就在上個季度末，我們大約是 80%。

So yes, that is moving up.

所以是的，這正在上升。

So the strategy is in place and will continue as we move into Q3.

因此，該戰略已經到位，並將在我們進入第三季度時繼續。

I'll move it to Jensen here to see if he can discuss further.

我會把它移到這裡的 Jensen，看看他是否可以進一步討論。

Yes, I mean, there's the question about the strategy of how we're steering GeForce supply for gaming.

是的，我的意思是，關於我們如何指導 GeForce 遊戲供應的策略存在問題。

We moved incredibly fast this time with GMP and with our LHR settings for GeForce.

這次我們使用 GMP 和 GeForce 的 LHR 設置以驚人的速度前進。

And our entire strategy is about steering GeForce supplies to gamers.

我們的整個戰略是為遊戲玩家提供 GeForce 供應。

And we have every reason to believe that because of the DRIVE and team, which is really a measure of gamers, the rate of growth of our team adoption of Ampere GPUs, there are some others that were successful.

而且我們完全有理由相信，由於 DRIVE 和團隊（這實際上是衡量遊戲玩家的標準），我們團隊採用 Ampere GPU 的增長率，還有其他一些成功的。

But there's several reasons why it's just different this time.

但這次不同的原因有幾個。

And the first reason of course is that LHR, which is new and the speed at which we responded with CMP to steer GeForce supply to gamers.

第一個原因當然是 LHR，它是新的以及我們響應 CMP 以引導 GeForce 供應給遊戲玩家的速度。

Second is where at the very beginning of the Ampere and RTX cycles.

其次是安培和 RTX 週期開始時的位置。

As I mentioned earlier, RTX is a complete reinvention of computer graphics.

正如我之前提到的，RTX 是對計算機圖形的徹底改造。

Every evidence is that gamers are incredibly -- and game developers are incredibly excited about ray tracing.

每一個證據都表明遊戲玩家令人難以置信——而遊戲開發者對光線追踪非常興奮。

This form of computer rendering, graphics rendering is just dramatically more beautiful.

這種形式的計算機渲染，圖形渲染簡直美極了。

And we're at the beginning of that cycle and only 20% has been upgraded so far.

我們正處於這個週期的開始，到目前為止只有 20% 已經升級。

So we have 80% to grow in a market that is already quite large and installed base is quite large, but also growing.

所以我們有 80% 的增長空間，這個市場已經很大，安裝基數也很大，而且還在增長。

Last year, gamers grew 20% and just made by (inaudible) The third reason is that our demand is strong in our channel.

去年，遊戲玩家增長了 20%，並且剛剛通過（聽不清）第三個原因是我們的渠道需求強勁。

And you can see that everyday with the shortage of supply as quickly as we're shipping it.

你可以看到每天供應短缺，就像我們發貨一樣快。

It's (inaudible) all over the world.

它（聽不清）遍布世界各地。

And then lastly, we just had more growth drivers today because of RTX than ever.

最後，由於 RTX，我們今天擁有比以往更多的增長動力。

And we have the biggest wave of NVIDIA laptops.

我們擁有最大的 NVIDIA 筆記本電腦浪潮。

Just the laptops is our fastest-growing segment of computing.

只有筆記本電腦是我們增長最快的計算領域。

And we have the largest wave of laptops coming.

我們迎來了最大的筆記本電腦浪潮。

The demand for RTX and workstations, whereas previously, the workstation market was a slow-growing market, it's now a fast-growing market and has achieved record.

對 RTX 和工作站的需求，以前，工作站市場是一個增長緩慢的市場，現在它是一個快速增長的市場，並且已經創紀錄。

And after more than a decade of working on cloud graphics, our cloud graphics is in great demand.

經過十多年的雲圖形工作，我們的雲圖形需求量很大。

And so all of these segments are seeing high demand and we're -- while we continue to be supply limited.

因此，所有這些細分市場的需求都很高，而我們 - 而我們繼續受到供應限制。

And so I think the situations are very different.

所以我認為情況非常不同。

And RTX is making each difference.

RTX 正在發揮各自的作用。

We have the next question comes from the line of Chris Caso of Raymond James.

我們有下一個問題來自雷蒙德詹姆斯的克里斯卡索。

My question is about the split between the hyperscale and the vertical customers and the data center business, and the trends you're seeing in each.

我的問題是關於超大規模和垂直客戶與數據中心業務之間的分歧，以及您在每個方面看到的趨勢。

I think in your prepared remarks, you said both would be up in the October quarter.

我認為在您準備好的講話中，您說兩者都將在 10 月季度上漲。

But I'm interested to see if you're seeing any different trends there, particularly in the vertical business as perhaps business conditions normalize and companies return to the office and they adjust their spending plans accordingly.

但我很想看看你是否看到那裡有任何不同的趨勢，特別是在垂直業務中，因為業務狀況可能正常化，公司返回辦公室並相應地調整他們的支出計劃。

Yes.

是的。

So let me start out with the question, and I'll let Jensen answer the tail.

所以讓我從這個問題開始，然後讓 Jensen 回答問題。

So far with our data center business, with our Q2 results, our vertical industries is still quite a strong percentage, essentially 50% of our data center business is going to our vertical industries.

到目前為止，就我們的數據中心業務而言，根據我們第二季度的業績，我們的垂直行業仍然佔很大比例，基本上我們 50% 的數據中心業務都流向了我們的垂直行業。

Our hyperscales make up the other portion of that, slightly below the 50%.

我們的超大規模構成了其中的另一部分，略低於 50%。

And then we also have our supercomputing business with a very small percentage but doing quite, quite well.

然後我們也有我們的超級計算業務，雖然比例很小，但做得非常非常好。

As we move into Q3, as we discussed, we will see an acceleration of both our vertical industries and our hyperscales as we move into Q3.

正如我們所討論的，隨著我們進入第三季度，隨著我們進入第三季度，我們將看到我們的垂直行業和超大規模的加速發展。

With that backdrop, we'll see if Jensen has additional commentary.

在這種背景下，我們將看看 Jensen 是否有其他評論。

There's a fundamental difference in hyperscale use of HPC or AI versus the industrial use of HPC and AI.

HPC 或 AI 的超大規模使用與 HPC 和 AI 的工業使用存在根本區別。

In the world of hyperscalers and internet service providers, they're making recommendations on movies and songs and articles and search results and so on and so forth.

在超大規模和互聯網服務提供商的世界中，他們正在對電影、歌曲、文章和搜索結果等進行推薦。

And the difference is the improvement in accuracy that deep learning and artificial intelligence, large recommender systems can provide us is really working for them.

不同之處在於深度學習和人工智能，大型推薦系統可以為我們提供的準確性的提高確實為他們工作。

In the world of industries, the reason why artificial intelligence is transformative, recognizing that most of the things I just mentioned earlier, it's not really dynamic in the world's largest industries, whether it's health care or logistics or transportation and retail, the vast majority of the reasons why in some of the physical sciences industries, whether it's energy or transportation and for health care, is the simulation of physics, the simulation of the world was not achievable using traditional first principle simulation approaches.

在工業界，人工智能之所以具有變革性，認識到我剛才提到的大部分事情，在世界上最大的行業中並不是真正動態的，無論是醫療保健還是物流還是運輸和零售，絕大多數的為什麼在一些物理科學行業，無論是能源還是交通運輸和醫療保健，都是物理模擬，使用傳統的第一原理模擬方法無法實現對世界的模擬。

But artificial intelligence or data-driven approaches has completely shaken that up and put it on its head.

但人工智能或數據驅動的方法已經完全改變了這一點，並將其置於首位。

And some examples, whether it's using artificial intelligence, so that you could feed up the simulation of the prediction of the protein structure of -- or the 3D structure of protein, which was recently achieved by a couple of very important networks, it's groundbreaking.

還有一些例子，無論是使用人工智能，這樣你就可以提供對蛋白質結構預測的模擬——或者蛋白質的 3D 結構，這是最近由幾個非常重要的網絡實現的，它是開創性的。

And by understanding the protein structure, 3D structure, we understand its -- we can better understand its function and how it would adapt to other proteins and other chemicals.

通過了解蛋白質結構、3D 結構，我們了解了它——我們可以更好地了解它的功能以及它如何適應其他蛋白質和其他化學物質。

And it's a fundamental step of the process in drug discovery, and that has just taken a giant leap forward.

這是藥物發現過程中的一個基本步驟，並且剛剛取得了巨大的飛躍。

In the areas of clinical science, it is now possible to consider using data-driven approaches to create models that overcome this -- not overcome but accelerate and make it possible for us to simulate much, much larger simulations of multiphysics geometry-aware simulations, which is basically climate science.

在臨床科學領域，現在可以考慮使用數據驅動的方法來創建克服這一問題的模型——不是克服而是加速，使我們能夠模擬更多、更大的多物理場幾何感知模擬，這基本上是氣候科學。

These are really important field of work that wouldn't have been possible for another decade, at least.

這些是非常重要的工作領域，至少再過十年是不可能的。

And just as we made possible using artificial intelligence, the realization of real-time ray tracing in every field of science, whether it's climate simulation, energy discovery, drug discovery, we're starting to see the industry recognizing that the fusion of first principle simulation and data-driven artificial intelligence approaches is going to get a giant leap up.

正如我們使用人工智能實現了實時光線追踪在各個科學領域（無論是氣候模擬、能源發現、藥物發現）成為可能，我們開始看到業界認識到第一原理的融合模擬和數據驅動的人工智能方法將獲得巨大的飛躍。

And that is a second dynamic.

這是第二個動力。

The other dynamic for industry is for the very first time, they could deploy AI model out to the edge to do a better job with agriculture, to do a better job with asset protection and warehouses, to do a better job with automating retail.

行業的另一個動態是第一次，他們可以將人工智能模型部署到邊緣，以更好地處理農業、更好地處理資產保護和倉庫、更好地實現自動化零售。

AI is going to make it possible for all of these types of automation to finally be realized.

人工智能將使所有這些類型的自動化最終得以實現。

And so the dynamics are all very different.

所以動態是非常不同的。

That last one has to do with Edge AI, which was just made possible by putting AI right at the point of data and right at point of action because you need to be low cost, you would need to be high performance and instantly responsive and we can't afford to stream all of the data to the cloud all the time.

最後一個與邊緣人工智能有關，這只是通過將人工智能放在數據點和行動點上才成為可能的，因為你需要低成本，你需要高性能和即時響應，我們不能一直將所有數據流式傳輸到雲端。

And so each one of them has a slightly different (inaudible)

所以他們每個人都有一個稍微不同的（聽不清）

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

您的最後一個問題來自 Truist Securities 的 William Stein。

Jensen, I'm wondering if you can talk for a moment about Omniverse.

Jensen，我想知道你能否談談 Omniverse。

This looks like a really cool technology, but I tend to get very few questions from investors about it, but it looks to me like this could be potentially very meaningful technology for you longer term.

這看起來是一項非常酷的技術，但我往往很少從投資者那裡得到關於它的問題，但在我看來，從長遠來看，這可能是非常有意義的技術。

Can you explain perhaps what capabilities and what markets this is going after?

您能否解釋一下它所追求的能力和市場？

It looks like perhaps this is going to position you very well in augmented and virtual reality, but maybe it's a sort of different market or group of markets, it's a bit confusing to us.

看起來這可能會讓你在增強現實和虛擬現實中獲得很好的定位，但也許這是一個不同的市場或一組市場，這讓我們有點困惑。

So if you could maybe help us understand it, I think would really appreciate it.

所以，如果你能幫助我們理解它，我想我會非常感激。

I really appreciate the question.

我真的很感激這個問題。

And it's one of the most important things we're doing.

這是我們正在做的最重要的事情之一。

The Omniverse, Omniverse first of all, just what is it?

Omniverse，首先是 Omniverse，它到底是什麼？

It's a simulator.

這是一個模擬器。

It's a simulator that's physically accurate and physically based.

這是一個物理上準確且基於物理的模擬器。

And it was made possible because of 2 fundamental technologies we invest and one of them is, of course, RTX, the ability to physically stimulate light behavior in the world, which is ray tracing.

它之所以成為可能，是因為我們投資了 2 項基礎技術，其中之一當然是 RTX，它能夠以物理方式激發世界上的光行為，即光線追踪。

The second is the ability to compute or simulate the physics of -- simulate the artificial intelligence behavior of agents and objects inside the world.

第二個是計算或模擬物理的能力——模擬世界內部代理和對象的人工智能行為。

So we have the ability now to simulate physics in a realistic way, and we created an architecture that allows us to do it in the cloud, distribute it a computed way and to be able to scale it out to very large business.

所以我們現在有能力以逼真的方式模擬物理，我們創建了一個架構，允許我們在雲中進行，以計算的方式分發它，並能夠將其擴展到非常大的業務。

And the question is what would you do with such a thing?

問題是你會用這樣的東西做什麼？

The simulator, those are simulators and simulation of virtual world with portals, we call them connectors, portals based on an industry standard, open standard that was pioneered by Pixar.

模擬器，那些是模擬器和帶有門戶的虛擬世界模擬，我們稱它們為連接器，基於由皮克斯開創的行業標準、開放標準的門戶。

And as we mentioned earlier, that we're partnering with Pixar and Apple to make it even broadly adopted, get more broadly adopted, it's called UFD, universal feed description.

正如我們之前提到的，我們正在與 Pixar 和 Apple 合作，以使其得到更廣泛的採用，得到更廣泛的採用，它被稱為 UFD，通用提要描述。

They're basically portals or wormholes into virtual worlds.

它們基本上是進入虛擬世界的門戶或蟲洞。

And this virtual world will simulate, could be simulating a -- it could be a concert for consumers, it could be a theme park for consumers.

這個虛擬世界將模擬，可能是模擬——它可能是消費者的音樂會，可能是消費者的主題公園。

In the world of the industries, you could use it for simulating robots, so the robots can learn how to be robots inside these virtual worlds before they're downloaded from the simulated to the real world.

在工業世界中，你可以用它來模擬機器人，這樣機器人就可以在從模擬世界下載到現實世界之前，學習如何在這些虛擬世界中成為機器人。

You could use it to stimulate factories, which is one of the early works that we've done with BMW that I showed at GTC.

你可以用它來刺激工廠，這是我在 GTC 上展示的與寶馬合作的早期作品之一。

Factory of the future that is designed completely in Omniverse, simulated in Omniverse, robots trained in Omniverse with goods and materials that are its original, CAD data, put into the battery, the logistics plan like an ERP system, except this is an ERP system of physical goods and physical simulation simulated through this Omniverse world, and you could plan the entire factory in Omnivere.

完全在 Omniverse 中設計、在 Omniverse 中模擬的未來工廠、在 Omniverse 中使用原始貨物和材料訓練的機器人、CAD 數據、放入電池、物流計劃就像 ERP 系統，但這是一個 ERP 系統通過這個 Omniverse 世界模擬實物商品和物理模擬，您可以在 Omnivere 中規劃整個工廠。

This entire factory now becomes what is called a digital tool.

這整個工廠現在變成了所謂的數字工具。

This -- it could be a factory, it could be a stadium, it could be an airport, it could be an entire city which could include the cars.

這——它可能是一個工廠，它可能是一個體育場，它可能是一個機場，它可能是一個包括汽車在內的整個城市。

These digital twins would allow us to simulate new algorithms, new AI, new -- and optimization algorithms before we deploy it into the physical world.

這些數字雙胞胎將允許我們在將其部署到物理世界之前模擬新算法、新人工智能、新算法和優化算法。

And so what is Omniverse?

那麼什麼是 Omniverse？

Well, Omniverse is going to be an overlay, if you will, of virtual worlds that increasingly people call the metaverse.

好吧，如果你願意的話，Omniverse 將成為虛擬世界的疊加，越來越多的人稱之為元宇宙。

And you've now heard several companies talk about the metaverse.

您現在已經聽到幾家公司談論元宇宙。

We all come from different perspectives, some of it from a social perspective, some of it from a gaming perspective, some of it, in our case, from an industrial and design and engineering perspective.

我們都來自不同的角度，其中一些來自社會的角度，一些來自遊戲的角度，在我們的例子中，一些來自工業、設計和工程的角度。

But the Omniverse is essentially an overlay of the Internet and overlay of the physical world is going to fuse all these different worlds together long term.

但 Omniverse 本質上是互聯網的疊加，物理世界的疊加將長期將所有這些不同的世界融合在一起。

And you'll be able to -- if you mentioned VR and AR, you'll be able to go into the Omniverse worlds using virtual reality, and so you wormhole into the virtual world using VR.

你將能夠——如果你提到了 VR 和 AR，你將能夠使用虛擬現實進入 Omniverse 世界，因此你可以使用 VR 進入虛擬世界。

You could have an AI or an object portal into our world using augmented reality so you could have a digital piece of art that you've somehow purchased and belongs to you because of NFC.

你可以擁有一個人工智能或一個使用增強現實進入我們世界的對象門戶，這樣你就可以擁有一件你以某種方式購買並因為 NFC 而屬於你的數字藝術品。

And it's only enjoyed in the virtual world, and you can overlay it into your physical world with an AI.

而且它只能在虛擬世界中享受，您可以使用 AI 將其疊加到您的物理世界中。

And so I'm fairly sure that at this point, that Omniverse or the metaverse is going to be a new economy that is larger than our current economy.

所以我相當肯定，在這一點上，Omniverse 或 Metaverse 將成為一個比我們當前經濟更大的新經濟體。

And we'll have -- we'll enjoy a lot of our time in the future in Omnivere and in metaverse.

我們將擁有 - 我們將在 Omnivere 和 Metaverse 中享受未來的大部分時間。

And we'll do a lot of our work there.

我們將在那裡做很多工作。

And we'll have a lot of robots.

我們會有很多機器人。

They're doing a lot of the work on our behalf.

他們正在代表我們做很多工作。

And we wake at morning as they show us results.

當他們向我們展示結果時，我們會在早上醒來。

And so Omniverse to us is an extension of our AI strategy, is an extension of our high-performance computing strategy, and it makes it possible for companies and industries to be able to create digital tools that simulate their physical version before they deploy it and while they're operating.

因此，Omniverse 對我們來說是我們 AI 戰略的延伸，是我們高性能計算戰略的延伸，它使公司和行業能夠創建數字工具，在部署之前模擬其物理版本，並在他們運作的時候。

Thank you.

謝謝你。

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

我現在將把電話轉給黃仁勳先生做閉幕詞。

Thank you.

謝謝你。

We had an excellent quarter fueled by surging demand for NVIDIA computing.

由於對 NVIDIA 計算的需求激增，我們度過了一個出色的季度。

Our pioneer work and accelerated computing continues to (inaudible) computing and AI, enabled by NVIDIA Accelerated computing, developers are creating the most impactful technologies of our time, from natural language understanding and recommender systems to autonomous vehicles and logistics centers to digital biology and climate science research, the metaverse world that obeys the laws of physics.

我們的開創性工作和加速計算繼續（聽不清）計算和人工智能，在 NVIDIA 加速計算的支持下，開發人員正在創造我們這個時代最具影響力的技術，從自然語言理解和推薦系統到自動駕駛汽車和物流中心，再到數字生物學和氣候科學研究，遵循物理定律的虛擬世界。

This quarter, we announced NVIDIA Base Command and Fleet Command to develop, deploy, scale and orchestrate the AI workloads that run on the NVIDIA AI enterprise software fleet.

本季度，我們宣布推出 NVIDIA Base Command 和 Fleet Command，以開發、部署、擴展和協調在 NVIDIA AI 企業軟件艦隊上運行的 AI 工作負載。

With our new enterprise software, a wide range of NVIDIA powered systems and global network of systems and integration partners, we can accelerate the world's largest industry as they raise the benefit from the transformative power of AI.

借助我們新的企業軟件、廣泛的 NVIDIA 驅動系統以及全球系統和集成合作夥伴網絡，我們可以加速這個世界上最大的行業，因為它們可以從 AI 的變革力量中獲益。

We are thrilled to have launched NVIDIA Omniverse, a simulation platform nearly 5 years in the making that runs physically realistic virtual world and connects to other digital platforms.

我們很高興推出 NVIDIA Omniverse，這是一個經過近 5 年製作的模擬平台，可運行物理上逼真的虛擬世界並連接到其他數字平台。

We imagine engineers, designers and even autonomous machines connecting to Omniverse to create digital twin simulated worlds that help train robots, operate autonomous factory, simulate fleets of autonomous vehicle, and even predict human impact on earth's climate.

我們想像工程師、設計師甚至自動機器連接到 Omniverse 來創建數字雙胞胎模擬世界，幫助訓練機器人、運營自主工廠、模擬自動駕駛車隊，甚至預測人類對地球氣候的影響。

The future will have artificial intelligence augmenting our phones and the metaverse augmenting our physical world.

未來將有人工智能增強我們的手機和虛擬世界增強我們的物理世界。

It will be populated by real and AI visitors, and open new opportunities for artists, designers, scientists, and new businesses a whole new digital economy that will emerge.

它將由真實的和人工智能的訪問者居住，並為藝術家、設計師、科學家和新企業開闢新的機會，一個全新的數字經濟將會出現。

Omniverse is a platform that's building the Metaverse vision.

Omniverse 是一個構建 Metaverse 願景的平台。

We're doing some of our best work and most impactful work in our history.

我們正在做一些我們歷史上最好的工作和最有影響力的工作。

And I want to thank all of NVIDIA's employees for their amazing work and the exciting future we are inventing together.

我要感謝 NVIDIA 的所有員工，感謝他們出色的工作以及我們共同創造的激動人心的未來。

Thank you.

謝謝你。

See you next time.

下次見。

Thank you.

謝謝你。

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。