輝達 (NVDA) 2022 Q2 法說會逐字稿

Good afternoon.

午安.

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

我叫梅爾，今天我將擔任你們的會議操作員。

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

此時此刻，我謹歡迎大家參加 NVIDIA 第二季財報電話會議。

(Operator Instructions)

（操作員說明）

Thank you.

謝謝。

Simona Jankowski, you may begin your conference.

Simona Jankowski，您可以開始會議了。

Thank you.

謝謝。

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.

今天與我同在的有 NVIDIA 總裁兼執行長黃仁勳 (Jensen Huang)；執行副總裁兼財務長 Colette Kress。

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

我想提醒您，我們的電話會議正在 NVIDIA 投資者關係網站上進行網路直播。

The webcast will be available for replay until the conference call to discuss our financial results for the third quarter of fiscal 2022.

在討論我們 2022 財年第三季財務業績的電話會議之前，該網路廣播將可供重播。

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

今天電話會議的內容屬於 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.

在這次電話會議中，我們可能會根據目前的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.

這些都受到許多重大風險和不確定性的影響，我們的實際結果可能會有重大差異。

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表現和業務的因素的討論，請參閱今天的收益發布中的披露、我們最新的 10-K 和 10-Q 表格以及我們可能在 8-K 表格上提交的報告證券交易委員會。

All our statements are made as of today, August 18, 2021, based on information currently available to us.

我們的所有聲明均基於我們目前掌握的信息，於今天（2021 年 8 月 18 日）作出。

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，我們將討論非公認會計準則財務指標。

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.

您可以在我們網站上發布的財務長評論中找到這些非 GAAP 財務指標與 GAAP 財務指標的調整表。

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

現在，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%.

第二季度又是一個強勁的季度，營收達 65 億美元，年增 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、資料中心和專業視覺化的記錄。

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

從遊戲開始，營收為 31 億美元，季增 11%，年增 85%。

Demand remained exceptionally strong, outpacing supply.

需求依然異常強勁，超過供應。

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

我們的 Ampere 架構遊戲產品週期現已進入四個季度，並且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，我們宣布推出兩款針對遊戲玩家和創作者的強大全新GPU：GeForce RTX 3080 Ti 和RTX 3070 Ti，其性能比上一代產品快50%，並具有即時回溯、NVIDIA DLSS AI渲染等廣受好評的功能、反射和廣播。

Laptop demand was also very strong.

筆記型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 廠商採用了 Ampere 架構 GPU 以及創紀錄數量的設計，從頂級遊戲筆記型電腦到主流售價低至 799 美元的筆記型電腦，為遊戲玩家、學生和創作者帶來了 GeForce CPU 的強大功能。

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.

採用 Ampere 架構的筆記型電腦採用我們的第三代 Max-Q 功耗優化技術，可實現超薄設計，例如全新 Alienware x15，世界上最強大的 16 毫米以下遊戲筆記型電腦。

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

NVIDIA RTX 技術重置了電腦圖形並刺激了我們有史以來最大規模的刷新週期。

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 是我們在 Steam 上提升最快的遊戲 GPU 架構，而 Turing 和 Ampere RTX GPU 的組合只升級了我們安裝量的約 20%。

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.

全球電競觀眾規模即將接近5億，遊戲直播人數預計將超過7億人。

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

去年，Steam 上的 PC 遊戲玩家數量增加了近 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.

現在有超過 60 款 RTX 遊戲支援 NVIDIA 的 RTX 光線追蹤或 DLSS，其中包括當今最大的遊戲系列，例如 Minecraft、Fortnite 和 Cyber​​punk。

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

本季新推出的 RTX 遊戲包括《荒野大鏢客：救贖 2》（Red Dead Redemption 2），它是有史以來收視率最高的遊戲之一。

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

《虹彩六號：圍攻行動》和（聽不清楚）以及《我的世界》RTX 等熱門遊戲在中國擁有超過 4 億玩家。

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

對於競技遊戲玩家來說，NVIDIA Reflex（包括延遲）現已支援 20 款遊戲。

Let me say a few words on cryptocurrency mining.

讓我談談加密貨幣挖礦。

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 直接提供給遊戲玩家，我們增加了加密貨幣挖礦處理器或 CMP 的供應，並推出了以太坊挖礦能力有限的低算力 GeForce GPU。

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

本季超過 80% 的基於 Ampere 架構的 GeForce 出貨量都是低算力 GPU。

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

加密貨幣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，低於我們最初因採礦盈利能力下降而估計的 4 億美元，並且我們預計 CMP 未來的貢獻很小。

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

GeForce 在本季達到了新的里程碑，PC 遊戲數量超過 1,000 款，超過任何其他雲端遊戲服務。

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.

高級方案的訂閱費用為每月 10 美元，讓玩家即使在動力不足的 PC、Mac、Chromebook、iOS 或 Android 裝置上也能獲得 RTX 等級的效能。

Moving to pro visualization.

轉向專業視覺化。

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

第二季營收達到創紀錄的 5.19 億美元，季增 40%，年增 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.

隨著遠距工作成為各行業的常態，桌面工作站帶動了家庭設計辦公室的需求，推動了收入的強勁連續成長。

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

這也是安培架構專業視覺化的第一個大季度。

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

推動第二季需求的主要垂直產業包括汽車、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.

上週在 SIGGRAPH 上，我們宣布了 NVIDIA Omniverse 的擴展，這是我們的模擬和協作平台，為元宇宙奠定了基礎。

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.

透過與世界領先的開源 3D 動畫工具 Blender 和 Adob​​e 的新集成，我們向數百萬額外用戶開放 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.

我們也與 Apple 和 Pixar 合作，將先進的實體功能引入 Pixar 的通用場景描述框架，採用開放標準為數十億設備提供 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 軟體正處於早期訪問階段，將於今年稍後透過 NVIDIA 合作夥伴（包括戴爾、惠普、聯想等）以訂閱方式全面上市。

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 12 月進入公開測試版以來，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.

轉向汽車領域，我們第二季的營收為 1.52 億美元，季減 1%，較去年同期成長 3%。

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

資訊娛樂領域收入的連續下降在很大程度上被自動駕駛領域的成長所抵消。

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，預計這將在未來幾年推動收入的重大變化。

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.

自動駕駛新創公司 AutoX 推出了由 NVIDIA DRIVE 提供支援的最新 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.

軟體定義的 NVIDIA DRIVE 平台的性能和安全功能使 AutoX 成為全球首批提供完全自動駕駛行動服務且無需安全駕駛員的公司之一。

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.

在自動駕駛卡車運輸方面，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套自動駕駛系統。

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

這些系統由 NVIDIA DRIVE 提供支援，可實現高效能、節能和集中式 AI 運算。

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

自動卡車運輸新創公司 Embark 正在 NVIDIA DRIVE 上進行開發。

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，代表了美國絕大多數 8 級或最大尺寸的卡車。車輛到RoboTaxi、卡車運輸和送貨車輛。

We believe everything that moves will be autonomous someday.

我們相信，有一天，所有移動的東西都將自動化。

Moving to data center.

遷移到資料中心。

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.

營收為 24 億美元，季增 16%，季增 35%，這是我們納入 Mellanox 的第一個季度。

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

成長是由超大規模客戶和垂直產業推動的，每個產業的收入都創下了紀錄。

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.

我們的旗艦產品 A100 繼續在超大規模和雲端運算客戶中普及，繼 AWS 和 Google 雲端平台在前幾季度全面上市後，Microsoft 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.

垂直產業需求強勁，金融服務、超級運算和電信客戶帶動環比成長。

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

我們的推理能力也取得了驚人的成長，比去年同期成長了一倍多，創歷史新高。

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

來自專注於推理的處理器的收入包括新的 A30 GPU，它提供的推理性能是 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 工作負載的嚴格效能、延遲和成本要求，客戶也轉向使用 NVIDIA GPU 將 AI 投入生產，並從 CPU 轉向 GPU。

NVIDIA networking products posted solid results.

NVIDIA 網路產品取得了可喜的表現。

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，在我們的技術領先地位的推動下，各地區的發展勢頭不斷增強，包括 ConnectX-6 等高速產品的升級，以及跨雲端服務供應商、企業和高效能運算贏得的新客戶。

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.

我們擴大了在超級運算領域的領先地位，最新的500 強榜單顯示，NVIDIA 技術為全球500 強超級電腦中的342 台提供了支持，其中包括所有新系統的70% 以及前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.

為了幫助企業利用新的工業高效能運算革命，我們透過 NVIDIA DGX SuperPOD 提供交鑰匙人工智慧資料中心解決方案，該技術為我們在英國的新型 Cambridge-1 超級電腦以及其他許多頂級電腦提供了相同的技術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.

我們擴展了人工智慧軟體和訂閱產品，使企業能夠更輕鬆地從最初的開發階段到部署和營運階段採用人工智慧。

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.

我們發布了 NVIDIA Base Command，這是我們的軟體即服務產品，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是分散式訓練叢集的操作和管理系統軟體。

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

我們也宣布全面推出 NVIDIA Fleet Command，這是我們的託管邊緣 AI 軟體即服務產品。

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 協助公司解決在數千個地點安全部署和管理人工智慧應用程式的問題，將中央管理的效率和簡單性與邊緣即時處理的成本、效能和資料主權優勢結合起來。

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其合作的專業軟體公司。

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.

繼上季宣布推出 NVIDIA AI Enterprise 軟體套件後，新的 NVIDIA Base Command 和 Fleet Command 軟體及訂閱產品也隨之推出，該套件目前處於搶先體驗階段，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.

我們的企業軟體策略得到了伺服器OEM 的NVIDIA 認證系統計畫的支持，這些系統向市場推出了超過55 個可在NVIDIA 的AI 軟體上運行的系統，可開箱即用，幫助企業簡化和加速其AI部署。

The NVIDIA ecosystem keeps getting stronger.

NVIDIA 生態系統不斷變得更強大。

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

NVIDIA Inception 是我們針對 AI 新創公司的加速平台，會員人數剛超過 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 累計融資超過 600 億美元，成員遍佈 90 個國家，是全球最大的人工智慧新創生態系統之一。

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 目前已被下載 2,700 萬次，光是去年就下載了 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 已被超過 27,000 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 生態系中的開發者總數現已超過 260 萬，在過去 4 年內成長了 4 倍。

Let me give you a quick update on Arm.

讓我向您簡要介紹 Arm 的最新情況。

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，在近一年的時間裡，我們對這家公司、它的業務和它的員工有了更多的了解。

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.

我們比以往任何時候都更相信我們合併的力量以及它將在人工智慧時代為 Arm、英國及其全球客戶帶來的好處。

Arm has great potential.

Arm擁有巨大的潛力。

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

我們喜歡他們的商業模式，並致力於保持其開放的許可方式。

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 將更快為其行動和嵌入式客戶生產更多 IP，同時擴展到資料中心、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 加速運算，從 CPU 開始，無論 CPU 和我們的加速電腦會開啟什麼新市場。

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.

我們宣布了適用於 Amazon Graviton、AmpereComputing、MediaTek 和 Marvell 的加速平台，涵蓋雲端運算、人工智慧、雲端遊戲、超級運算、邊緣人工智慧和 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，透過 Cambridge-1 超級計算機，並透過 Arm，使英國成為全球科學、技術和人工智慧中心。

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.

我們正在完成監管程序，儘管一些 Arm 授權商表達了擔憂並反對這項交易，而且與監管機構的討論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、其授權商和產業帶來的好處。

Moving to the rest of the P&L.

轉向損益表的其餘部分。

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 GAAP 毛利率為 64.8%，較上年同期成長 600 個基點，反映出不存在某些 Mellanox 收購相關成本。

GAAP gross margins was up 70 basis points sequentially.

GAAP 毛利率較上季成長 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%，較上年同期成長 70 個基點，較上季成長 50 個基點，反映出高階 Ampere 架構產品持續成長導致桌面 GeForce GPU 的平均售價上升，部分被資料內的混合變化所抵消中心。

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

第二季 GAAP 每股盈餘為 0.94 美元，較去年同期成長 276%。

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

根據本季生效的 4 比 1 股票分割調整後，非 GAAP 每股盈餘為 1.04 美元，較上年同期成長 89%。

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

第二季營運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 2022 財年第三季的展望。

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

我們預計另一個季度將表現強勁，環比成長主要是由資料中心需求加速推動的。

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 個市場以及其他 3 個市場平台將持續成長。

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，因為我們預計在第三季結束時渠道庫存將保持在目標水準以下。

The contribution of CMP to our revenue outlook is minimal.

CMP 對我們營收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，上下浮動 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 營運費用預計分別約為 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均為約 6,000 萬美元的支出，不包括股本證券的損益。

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

GAAP 與非 GAAP 稅務風險預估為 11%，正負 1%（不含離散項目）。

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

資本支出預計約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 評論和我們的 IR 網站上提供的其他資訊中。

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

最後，讓我重點介紹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 日舉行的 BMO 技術高峰會； 9 月 9 日半導體會議上的新街大創意； 9 月 13 日舉行的花旗全球技術會議； 9 月 14 日舉行的 Piper Sandler 全球技術大會；以及 9 月 21 日舉辦的 Evercore ISI 汽車、科技與人工智慧論壇。

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

我們定於 11 月 17 日星期三召開財報電話會議，討論第三季業績。

We will now open the call up for questions.

我們現在將開始提問徵集。

Operator, would you please poll for questions?

接線員，請您投票詢問問題嗎？

(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，我對資料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.

我認為近期，您提到了資料中心增速從 35% 加速成長的可能性。

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關於信心和可見度的色彩。

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 發布了許多關於您的企業軟體機會的公告。

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?

聽起來很有希望，但是我們應該如何建模呢？

What problem are you trying to solve?

您想解決什麼問題？

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

它是否會蠶食您從公有雲客戶看到的需求？

Or is this incremental to growth?

或者說這是成長的增量？

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

那麼，對於如何長期考慮 NVIDIA 的企業軟體機會，是否有任何指導或任何見解？

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.

我們看到加速成長——正如我們已經報告的那樣，上個季度我們在超大規模、雲端和工業企業方面的收入都創下了紀錄。

And we're seeing accelerated growth.

我們看到了加速成長。

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.

超大規模和雲端的加速源於雲端服務供應商將人工智慧應用程式轉變為人工智慧應用程序，這些應用程式現在主要由深度學習驅動進入生產。

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.

我們過去討論過的一些事情確實使 NVIDIA 成為理想的橫向擴展平台。

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

如果我的台詞有點糟糕，請容許我道歉。

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——我們平台的幾個要素，第一，Ampere GPU，它現在是人工智慧的通用 GPU，用於訓練，但對於推理來說非常好。

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，回應時間也非常快，因此部署成本、運行人工智慧應用程式的成本是最低的。

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 TensorRT 的引入，它是我們的最佳化編譯器，使我們能夠在 GPU 上編譯和最佳化任何 AI 應用程式。

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.

無論是電腦視覺還是自然語言理解、對話式人工智慧、推薦系統，部署人工智慧的應用程式類型確實非常廣泛。

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

最後，我們提供的這款軟體推理伺服器稱為 Triton，它支援我們的每一款 GPU。

It supports CPUs as well as GPUs.

它支援 CPU 和 GPU。

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

因此每個網路服務供應商都可以使用 Triton 來運作他們的整個資料中心。

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成長，所以第一個要素是部署，深度學習人工智慧應用程式向大規模部署的轉變。

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，驅動人工智慧的應用程序，如您所知，每個企業都必須——希望朝著成為科技公司的目標邁進，並利用互聯雲、互聯設備和人工智慧來實現這一目標。

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

我們有機會在邊緣部署人工智慧服務。

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

為了做到這一點，有幾件事必須發生。

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，我們必須創建一個運算平台，使他們能夠在他們理解的IT環境中進行培訓，這是虛擬化的，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 合作創建了一種可以與企業整合的新型系統，這是一項相當重大的工作，並且現在已投入大量生產。

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

第二個是伺服器，允許企業客戶將其 AR 模型部署到邊緣。

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.

人工智慧引擎，也就是我們過去10年開發的軟體套件，現在已經整合到這個環境中，使企業基本上可以開箱即用地運行人工智慧。

There's 3 elements of our software products there.

我們的軟體產品有 3 個要素。

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，它基本上包含了我們多年來工業化和完善的所有最先進的 AI 解算器、引擎和函式庫，可供企業進行授權。

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 的作業系統平台，允許分散式擴展軟體開發，用於訓練和開發模型。

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，這是一款作業系統軟體產品，可讓您操作、部署和管理邊緣的人工智慧模型。

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.

這三款軟體產品與透過我們的合作夥伴網路推出的名為 NVIDIA 認證的伺服器結合，是我們加速企業客戶採用 AI 的策略。

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

因此，我們非常熱衷於進入軟體商業模式。

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

當然，這是一個代表數千萬台伺服器的機會。

We believe all of them will be GPU accelerated.

我們相信所有這些都將得到 GPU 加速。

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

我們相信，企業將部署並利用人工智慧來徹底改變他們的產業。

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體授權業務模式，這可能為我們帶來數十億美元的商機。

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

下一個問題來自伯恩斯坦的史黛西·拉斯貢（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.

你按片段給了一點顏色。

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，你們的收入大約成長了 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你提供供應的能力。

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

所以我猜當你從第二季進入第三季時，供應增加會是什麼樣子？

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

您認為您還能維持這種持續成長嗎？

Or does it dial down?

還是撥下來了？

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——我也會反對你的其他評論，表明連續成長，我認為以美元為基礎主要是由資料中心驅動的。

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，我如何看待遊戲連續成長的評論中的相互作用，特別是考慮到我們過去幾季的發展軌跡？

Yes.

是的。

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

那麼，讓我開始吧，我會讓 Jensen 對你的問題補充一點，Stacy。

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

我想我們為第三季提供的收入指引為 68 億美元。

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

現在不包括 CMP，我們預計我們的營收將持續成長超過 5 億美元。

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

收入連續增長的大部分將來自數據中心。

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

我們確實預計遊戲業務將環比略有成長。

But remember, we are still supply constrained.

但請記住，我們的供應仍然有限。

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

汽車和 Pro Viz 預計也將環比略有增長。

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

從 CMP 的角度來看，我們在第三季可能只會有很少的數量。

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，我們第三季的業績與遊戲沒有季節性有關，實際上與我們認為第三季可以擁有的供應有關。

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

我看看 Jensen 是否想添加更多顏色。

Yes.

是的。

Thanks for the question.

謝謝你的提問。

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

如您所知，RTX 是電腦圖形學的根本重置。

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

這是一種稱為光線追蹤的技術，35 年來，它在相當長的一段時間內一直是電腦圖形學的聖杯。

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

在研究方面，我們對 NVIDIA 進行了 10 年的研究，最終使使用 RTX 進行即時光線追蹤成為可能。

RTX demand is quite incredible.

RTX 的需求相當令人難以置信。

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

如您所知，我們擁有大量的電腦遊戲玩家。

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

他們使用一種名為 GTX 的架構，該架構基於我們大約 20 年前發明的可程式著色器。

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.

安培顯然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.

它是我們公司史上最暢銷的 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%——不到總安裝量的 20%。

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

因此，全球還有 80% 的 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.

同時，全球PC遊戲玩家數量大幅成長，去年仍成長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 轉型的開始。

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

同時，電腦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——我們一直相信我們將重塑人們的設計方式。

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

就在我們說話的時候，我們正在看到這種情況正在發生，因為工作站的成長速度比以往任何時候都快，而且收入創歷史新高。

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，由於我們在雲端遊戲方面的所有工作，我們現在看到公有雲將雲端圖形（無論是工作站、PC 還是私人遊戲控制台）放在雲端。

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

因此，我們看到對個人電腦、筆記型電腦、工作站、行動工作站和雲端的強勁需求。

And so RTX is really doing great.

所以 RTX 確實表現出色。

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

我們面臨的挑戰是，供應的需求非常大，然後我們將盡可能嚴格地限制供應。

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

你的下一個問題來自 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，詹森，我只想祝賀你獲得了這個獎項。

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，我想繼續回答史黛西關於供應和科萊特的問題，也許您可以給我們一些關於遊戲卡不同級別或價格級別的供應限制的評論。

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?

我想這轉化為一個問題，即我們在 10 月季度指導中看到的遊戲 ASP 是否是您所謂的可持續發展？

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

或者您認為隨著供應上線，這種組合可能會改變？

So I'll start here.

那我就從這裡開始吧。

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

感謝您提出有關我們前進過程中整體組合的問題。

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桌上型電腦和筆記型電腦。

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

這可能意味著我們的組件有很多不同的含義，而這些組件是構建我們許多產品所必需的。

But our mix is really important.

但我們的組合確實很重要。

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

我們的組合也看到許多遊戲玩家對我們更高端、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力，我們的收入和毛利率都可以提升。

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.

因此，我們的供應中有很多不同的部分需要考慮，但我們目前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.

下一個問題是 Evercore 的 C.J. Muse 的台詞。

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

我想後續問題是關於供應限制的。

When do you think that will ease?

您認為這種情況什麼時候會緩解？

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，我們應該如何考慮一月季度相對於典型季節性的遊戲？

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.

繼續吧，Jensen，如果還有其他事情，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.

我們的圖形供應受到限制——我們在圖形方面的供應受到限制，而我們在圖形方面的收入卻創下了紀錄。

Cloud gaming is growing, cloud graphics is growing.

雲端遊戲正在成長，雲端圖形正在成長。

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

RTX 讓我們能夠解決設計和創意工作站的問題。

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，光線追蹤和逼真影像的渲染大部分是在 CPU 上完成的，而且還是第一次，我們實際上可以使用 NVIDIA GPU 和 RTX GPU 來加速它。

And so the workstation market is really doing great.

因此，工作站市場確實表現出色。

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

當然，其背景是人們正在家裡建造辦公室。

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來說，大約有2000 萬設計師和創作者，他們必須創造——他們必須在家中建立一個工作站或辦公室，就像他們在工作中想要的那樣，因為遠距工作是新常態。

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.

當然，同時，RTX 已經涵蓋了我們所有的消費性顯示卡、數億個 PC 遊戲玩家的安裝基礎，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，我們實現創紀錄的收入以及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下半年公司的成長計畫。

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

明年，我們預計能夠實現公司明年的成長計畫。

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制定的所有這些不同的市場計劃，我們已經並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.

因此，我認為，我目前的猜測是，明年的大部分時間我們將看到供應受限的環境。

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

但這很大程度上與我們的需求太大有關。

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

RTX 確實是一次千載難逢的電腦重置——現代電腦圖形學。

Nothing like this has happened.

還沒有發生過這樣的事情。

It's so convenient computer graphics.

電腦圖形學真是太方便了。

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

因此，這項發明確實具有開創性，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.

祝賀強勁的業績、前景和執行力。

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

Mellanox 網路特許經營權對 NVIDIA 運算產品組合來說是一個真正強大且具有協同作用的補充。

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.

我認為接近中期時，團隊將受益於向 200 和 400 gig 網路連接以及雲端和超大規模的過渡。

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

我認為除此之外，你們也從 BlueField SmartNIC 產品中獲得了一些很好的吸引力。

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網路將繼續保持季度環比成長勢頭，特別是在雲端和超大規模企業即將進入伺服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 的季度成長穩健。

And the Mellanox networking business is really growing incredibly.

Mellanox 網路業務確實正在以驚人的速度成長。

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.

第一個是你所說的轉變。

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.

您知道世界上的資料中心、超大規模資料中心都使用這種稱為分解的計算形式，這基本上意味著單一應用程式同時在多個伺服器上運行。

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

這使得它們能夠橫向擴展。

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

人工智慧應用程式或服務的用戶越多，只需添加更多伺服器即可。

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

因此，分解運算提供的橫向擴展便利性也給網路帶來了巨大的壓力。

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

Mellanox 擁有世界上延遲最低、頻寬和效能最高的網路。

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，Mellanox 網路的橫向擴展能力和提供分類應用程式的能力確實要好得多。

So that's number one.

所以這是第一。

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效能運算公司。

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

您會看到，雲端服務供應商紛紛建立有效的超級電腦。

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

歷史上的 InfiniBand 和超級運算資料——超級運算中心、雲端服務供應商必須自行建置超級電腦。

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

原因是人工智慧正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.

我們的網路規模的成長率－人工智慧模型的規模每兩個月就翻倍。

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.

我們現在討論的是訓練具有 100 兆個參數的 AI 模型。

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

人類大腦有超過 150 兆個突觸以及神經元。

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

這讓你了解人們正在開發的人工智慧模型的規模。

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端服務供應商中看到基於 Mellanox InfiniBand 構建的超級電腦以及高速網路以及 NVIDIA GPU 運算。

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

您也可以在企業中看到它用於藥物發現。

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

隨著計算的穩定，數位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慧中，可以更好地理解生物學，更好地理解化學，並將這兩個領域帶入資訊科學領域。

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

因此，您會看到世界各地的企業也在建造大型超級電腦。

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路、InfiniBand 網路方面有關，這是高效能運算的事實上的標準。

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

第三個動態是資料中心進行庫存工作。

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資料中心，他們只是幾個人，基本上運行我們整個資料中心，幾十萬台伺服器，就好像它只是你面前的一台電腦一樣，整個資料中心是軟體定義的。

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 上運行的軟體設備資料中心的軟體，而是網路堆疊、儲存堆疊，現在由於零信任安全堆疊，所有這些都給應用程式的可用運算能力帶來了巨大的壓力，這最終就是資料中心設計的目的。

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.

因此，軟體定義的資料中心需要有一個地方來容納基礎設施軟體並加速它，卸載它，加速它，非常重要的是將其與應用程式計劃隔離，以便入侵者無法跳入作業系統，如果您願意的話，您的資料中心的結構。

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.

能夠卸載、加速和隔離資料中心軟體基礎設施，並釋放所有 CPU 來運行它們應該運行的內容，即應用程式。

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

世界上幾乎每個資料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.

因此，這 3 個動態，分解計算，這意味著快速網路的真正強大；每家使用高效能運算的公司；最後，軟體定義的資料以零信任為中心。

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

因此，這些都是非常重要的動態，我很高興有機會向您介紹這一點。

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.

你可以看出我對這個網路業務的前景以及他們在建立現代資料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.

我想你在上一篇文章中提到了我關於資料中心的許多問題。

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

所以也許我會在損益表的基礎上問一些問題。

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，或更重要的是，指南中的內容是，Colette，您現在的毛利率可能超過 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，您如何看待從現在開始的增量營業毛利率上升，以及您如何看待公司從現在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.

科萊特，如果你不介意的話，讓我來處理，你可以跟進細節，那就太好了。

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

我認為在最高層面上——我真的很欣賞這個問題。

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，需要認識到的重要一點是人工智慧，它是電腦產業所見過的、甚至可能是世界所見過的最強大的技術力量。

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

自動化的機會是巨大的，它可以提高生產力，直接轉化為公司的成本節約。

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帶來了前所未有的機會。

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.

事實上，我們可以將如此多的技術應用於倉儲物流、零售自動化、客戶呼叫中心自動化，這確實是前所未有的。

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

事實上，我們可以實現卡車駕駛和最後一英里交付的自動化，提供自動化司機。

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 產業的規模，如果你願意的話，像我們這樣的電腦公司所屬的產業，已經大大擴大了。

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，我們想做的事情就是盡可能明智地、盡快地進行投資，以追求我們能夠產生真正影響的大型營運——大型商機。

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，這種方式的本質我們圍繞架構構建軟體，我們的學科，這使我們能夠在工作時如此高效，同時一方面解決氣候科學，另一方面解決數位生物學，人工智慧、機器人和自動駕駛汽車。

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

當然，我們已經討論過電腦圖形和視訊。

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——並且擁有近 30 年的紀律給了我們令人難以置信的營運槓桿。

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

這就是我們絕大多數營運槓桿的來源，即建築槓桿。

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，我們的產品也是架構性的，公司也是架構性的。

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.

因此，希望當我們抓住人工智慧為我們提供的這些巨大的市場機會時，我們透過我們的架構以智慧和有紀律的方式，透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公司帶來真正巨大的營運槓桿。

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

我們有下一個問題，來自瑞士信貸銀行的約翰‧皮策 (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?

我有點想回到加密貨幣的影響以及加密貨幣的潛在影響，Colette 或 Jensen，有什麼方法可以衡量低哈希率 GeForce 的有效性嗎？

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 業務的下滑是否是加密貨幣降溫的反映以及 LHR 可能沒有那麼有效有多大信心？

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.

我之所以提出這個問題，是因為有很多部落格都表明，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一些有關我們在過去幾個季度製定的策略的問題。

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

正如你所記得的，我們放置的是低算力卡以及 CMP 卡。

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

低算力卡旨在為我們的 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 的幾乎所有卡片都是低哈希率的，但我們也銷售其他類型的卡片。

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

但此時，隨著我們前進，我們已經遠高於80%。

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

但就在上個季度末，我們的進度約為 80%。

So yes, that is moving up.

所以是的，它正在上升。

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

因此，該策略已經到位，並將在進入第三季時繼續下去。

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

我會將其移交給 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，我們如何引導 GeForce 遊戲供應的策略有問題。

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

這次我們在 GMP 和 GeForce 的 LHR 設定方面進展得非常快。

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

我們的整個策略就是將 GeForce 供應引導給遊戲玩家。

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.

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）以及我們團隊採用 Ampere GPU 的成長率，還有其他一些產品取得了成功。

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

但這次情況有所不同有幾個原因。

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，以及我們透過 CMP 回應以引導 GeForce 向遊戲玩家提供的速度。

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

第二個是 Ampere 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 是對電腦圖形學的徹底重塑。

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

所有證據都表明，遊戲玩家對光線追蹤非常感興趣，而遊戲開發人員也對光線追蹤感到非常興奮。

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

這種形式的電腦渲染、圖形渲染更加美麗。

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

我們正處於該週期的開始階段，到目前為止僅升級了 20%。

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

因此，我們有 80% 的成長空間，這個市場已經相當大，安裝基礎也相當大，而且還在持續成長中。

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

去年，遊戲玩家成長了 20%，並且剛剛由（聽不清楚）第三個原因是我們的頻道需求強勁。

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

您可以看到，每天我們出貨時都出現供應短缺。

It's (inaudible) all over the world.

它（聽不清楚）遍佈世界各地。

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

最後，由於 RTX，我們今天比以往任何時候都擁有更多的成長動力。

And we have the biggest wave of NVIDIA laptops.

我們擁有最大規模的 NVIDIA 筆記型電腦。

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

筆記型電腦是我們成長最快的運算領域。

And we have the largest wave of laptops coming.

我們將迎來最大規模的筆記型電腦浪潮。

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成長緩慢的市場，現在是一個快速成長的市場，並創下了歷史新高。

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

經過十多年的雲端圖形工作，我們的雲端圖形需求量很大。

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，而我們的供應仍然有限。

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 正在發揮作用。

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

我們的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以及資料中心業務之間的劃分，以及您在每個業務中看到的趨勢。

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，您說過兩者都會在十月季度上漲。

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.

但我很想知道您是否看到了任何不同的趨勢，特別是在垂直業務中，因為業務狀況可能會正常化，公司會回到辦公室，並相應地調整支出計劃。

Yes.

是的。

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

那麼讓我從這個問題開始，然後讓 Jensen 來回答尾部。

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，就我們的資料中心業務而言，從我們第二季的業績來看，我們的垂直產業仍然佔有相當大的比例，基本上我們資料中心業務的50%都流向了我們的垂直產業。

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.

然後我們還有超級運算業務，雖然比例很小，但做得相當非常好。

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，當我們進入第三季時，我們將看到垂直產業和超大規模的加速發展。

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

在此背景下，我們將看看詹森是否有更多評論。

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 的工業使用有根本區別。

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.

在超大規模供應商和網路服務供應商的世界中，他們正在對電影、歌曲、文章和搜尋結果等進行推薦。

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慧、大型推薦系統可以為我們提供的準確性的提高確實對他們有用。

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.

在工業領域，人工智慧之所以具有變革性，要認識到我剛才提到的大多數事情，在世界上最大的行業中並不是真正充滿活力，無論是醫療保健還是物流還是運輸和零售，絕大多數在一些物理科學產業，無論是能源、交通或醫療保健，原因在於物理模擬，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.

但人工智慧或數據驅動的方法已經完全動搖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.

舉一些例子，無論是使用人工智慧，這樣你就可以提供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路實現的，這是開創性的。

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.

透過了解蛋白質結構、3D 結構，我們可以更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，並且剛剛邁出了巨大的一步。

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模型來克服這個問題——不是克服而是加速，並使我們能夠模擬更大規模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.

這些都是非常重要的工作領域，至少在未來十年是不可能實現的。

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.

正如我們使人工智慧成為可能，在每個科學領域實現即時光線追踪，無論是氣候模擬、能源發現、藥物發現，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慧方法將取得巨大飛躍。

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.

工業界的另一個動態是，他們第一次可以將人工智慧模型部署到邊緣，以便更好地完成農業工作，更好地完成資產保護和倉庫工作，更好地完成零售自動化。

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

人工智慧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.

因此，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慧有關，透過將人工智慧放在數據點和行動點上，邊緣人工智慧才成為可能，因為你需要低成本，你需要高效能和即時回應，我們無法始終將所有數據傳輸到雲端。

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

所以他們每個人都有輕微的不同（聽不清楚）

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

你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，我想知道你是否可以談談 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，這可能是對你來說非常有意義的技術。

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

您能解釋一下它所追求的功能和市場嗎？

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.

看起來也許這會讓你在擴增實境和虛擬實境中處於很好的位置，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.

因此，如果您能幫助我們理解它，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?

全方位宇宙，首先，全方位宇宙，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.

它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，是因為我們投資了兩項基本技術，其中之一當然是 RTX，即物理刺激世界中光行為的能力，即光線追蹤。

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物件的人工智慧行為。

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.

因此，我們現在有能力以現實的方式模擬物理，並且我們創建了一個架構，允許我們在雲端中執行此操作，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，我們稱之為連接器，基於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，我們正在與皮克斯和蘋果合作，使其得到更廣泛的採用，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，可能模擬——它可能是消費者的音樂會，也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，您可以使用它來模擬機器人，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 上展示的我們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進行訓練的機器人、CAD 數據、放入電池、像 ERP 系統一樣的物流計劃，只不過這是一個 ERP 系統通過這個Omniverse 世界模擬實體商品和實體模擬，您可以在Omnivere 中規劃整個工廠。

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

整個工廠現在變成了所謂的數位工具。

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.

這可能是一家工廠，可能是體育場，可能是機場，也可能是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.

這些數位孿生將使我們能夠在將新演算法、新人工智慧、新演算法和最佳化演算法部署到實體世界之前對其進行模擬。

And so what is Omniverse?

那麼全宇宙是什麼呢？

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

嗯，如果你願意的話，Omniverse 將是虛擬世界的疊加，越來越多的人稱之為虛擬世界。

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，有些是從社會角度，有些是從遊戲角度，有些，就我們而言，是從工業、設計和工程角度。

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.

但全方位宇宙本質上是互聯網的覆蓋，而物理世界的覆蓋將從長遠來看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.

如果您提到 VR 和 AR，您將能夠使用虛擬實境進入 Omniverse 世界，因此您可以使用 VR 蟲洞進入虛擬世界。

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.

您可以使用擴增實境技術讓人工智慧或物件入口網站進入我們的世界，這樣您就可以擁有一件您以某種方式購買的數位藝術品，並且由於 NFC 而屬於您。

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

它只能在虛擬世界中享受，你可以透過人工智慧將其覆蓋到你的物理世界中。

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.

因此，我相當確定，在這一點上，全宇宙或元宇宙將成為一個比我們當前經濟更大的新經濟。

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

未來我們將在 Omnivere 和虛擬宇宙中度過很多時光。

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.

我們將會有許多機器人。

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

他們代表我們做了很多工作。

And we wake at morning as they show us results.

我們早上醒來，他們向我們展示結果。

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 對我們來說是我們人工智慧策略的延伸，也是我們高效能運算策略的延伸，它使公司和行業能夠創建數位工具，在部署之前模擬其實體版本，當他們在操作時。

Thank you.

謝謝。

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

現在我將把電話轉回給黃仁勳先生做總結發言。

Thank you.

謝謝。

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

由於 NVIDIA 運算需求的激增，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.

我們的先驅工作和加速運算繼續致力於（聽不清楚）運算和人工智慧，在NVIDIA 加速運算的支援下，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，再到數位生物學和氣候科學研究，遵守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，用於開發、部署、擴展和編排在 NVIDIA AI 企業軟體群上運行的 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.

透過我們的全新企業軟體、廣泛的 NVIDIA 支援的系統以及全球系統和整合合作夥伴網絡，我們可以加速世界上最大的產業的發展，因為它們可以從人工智慧的變革力量中獲益。

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 年開發的類比平台，可運行物理真實的虛擬世界並連接到其他數位平台。

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、設計師甚至自主機器連接到 Omniverse，創造數位孿生模擬世界，幫助訓練機器人、營運自主工廠、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.

未來將有人工智慧增強我們的手機，虛擬宇宙將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.

它將充滿真實的和人工智慧的訪客，並為藝術家、設計師、科學家和新企業以及即將出現的全新數位經濟帶來新的機會。

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

Omniverse 是一個建立 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 的所有員工所做的出色工作以及我們共同創造的令人興奮的未來。

Thank you.

謝謝。

See you next time.

下次見。

Thank you.

謝謝。

This concludes today's conference call.

今天的電話會議到此結束。

You may now disconnect.

您現在可以斷開連線。