NVIDIA Q3 2022 Earnings Call Transcript

Quartr
Provided by Quartr
November 16, 2021

There are 8 speakers on the call.

Operator

Good afternoon. My name is Sadie, and I will be your conference operator today. At this time, I would like to welcome everyone to the NPDES 3rd Quarter Earnings Call. All lines have been placed on mute to prevent any background noise. After this speaker's presentation, there will be a question and answer session.

Operator

S. Thank you. Simone Jarmoski, you may begin your conference.

Speaker 1

Thank you. Good afternoon, everyone, and welcome to NVIDIA's conference call for the Q3 of fiscal 2022. With me today from NVIDIA are Jensen Huang, President and Chief Executive Officer Ann Colette Kress, Executive Vice President and Chief Financial Officer. I'd like to remind you that our call is being webcast live on NVIDIA's Investor Relations website. Webcast will be available for replay until the conference call to discuss our financial results for the Q4 fiscal year 2022.

Speaker 1

The content of today's call is NVIDIA's property. It can be reproduced or transcribed without our prior written consent. During this call, we may make forward looking statements based on current expectations. These are subject to a number of significant risks and uncertainties, and our actual results may differ materially. For a discussion of factors that could affect our future financial results and business, Please refer to the disclosure in today's earnings release, our most recent Forms 10 ks and 10 Q and the reports that we may file on Form 8 ks with the Securities and Exchange Commission.

Speaker 1

All our statements are made as of today, November 17, 2021, based on information currently available to us. Except as required by law, we assume no obligation to update any such statements. During this call, we will discuss non GAAP financial measures. You can find a reconciliation of these non GAAP financial measures to GAAP financial measures in our CFO commentary, which is posted on our website. With that, let me turn the call over to Colette.

Speaker 1

Thanks, Simona. Q3 was an outstanding quarter With revenue of $7,100,000,000 and year on year growth of 50%, we set records for total revenue as well as for gaming, data center and professional visualization. Starting with gaming, revenue of $3,200,000,000 was up 5% sequentially and up 42% from a year earlier. Demand was strong across the board, While we continue to increase desktop GPU supply, we believe channel inventories remain low. Laptop GPUs also posted strong year on year growth led by increased demand for high end RTX laptops.

Speaker 1

NVIDIA RTX technology is driving our biggest effort refresh cycle with gamers and continues to expand our base with creators. RTX introduced groundbreaking real time ray tracing and AI enabled super resolution capabilities, which are getting adopted at an accelerating pace. More than 200 games and applications now support NVIDIA RTX, including 125 with NVIDIA DLSS. This quarter alone, 45 new games shift with DLSS. An NVIDIA Reflex latency reducing technology is in top e sports titles, including Valorant, Fortnite, Apex Legends and Overwatch.

Speaker 1

In addition, the Reflex ecosystem continues to grow with Reflex technology now integrated in almost 50 gaming peripherals. NVIDIA's studio for creators Keeps Expanding. Last month at the Adobe MAX Creativity Conference, Adobe announced 2 powerful AI features for Adobe Lightroom and the Lightroom Classic, accelerated by NVIDIA RTX GPUs. In addition, several of our partners launched new studio systems, including Microsoft, HP and ASUS. We estimate that a quarter of our installed base has adopted RTX GPUs.

Speaker 1

Looking ahead, we expect continued upgrades as well as growth from NVIDIA GeForce users given rapidly expanding RTX support and the growing popularity of gaming, esports, content creation and streaming. Our GPUs are capable of crypto mining, but we don't have visibility into how much This impacts our overall GPU demand. In Q3, nearly all of our Ampere architecture gaming, desktop, GPU shipments Remite Hash rate to help steer GeForce supply to gamers. Crypto mining processor revenue was 105,000,000 which is included in our OEM and other. Our cloud gaming service, GeForce NOW, has 2 major achievements this quarter.

Speaker 1

1st, Electronic Arts brought more of its 5th games to the service. And second, we announced a new GeForce NOW RTX 3,080 membership tier priced at less than $100 for 6 months. GeForce NOW membership has more than doubled in this last year to over 14,000,000 gamers that are streaming content from 30 data centers in more than 80 countries. Moving to pro visualization. Q3 revenue of $577,000,000 was up 11% sequentially and up 144% from the year ago quarter.

Speaker 1

The sequential rise was led by mobile workstations with desktop workstations also growing as enterprise deployed systems to support hybrid work environments. Building on the strong initial ramp in Q2 and Pure Architecture sales continue to grow. Leading verticals including media and entertainment, Healthcare, Public Sector and Automotive. Last week, we announced general availability of Omniverse Enterprise, a platform for simulating physically accurate 3 d worlds and digital twins. Initial market reception to Omniverse has been incredible.

Speaker 1

Professionals at over 700 companies are evaluating the platform, including BMW, Ericsson, Lockheed Martin and some new pictures. More than 70,000 individual creators have downloaded Omniverse since the open beta launch in December. There are approximately 40,000,000 3 d designers and the global market. Moving to automotive, Q3 revenue of 135,000,000 declined 11% sequentially and increased 8% from the year ago quarter. The sequential decline was primarily driven by AI revenue, which has negatively been impacted by automotive manufacturers' supply constraints.

Speaker 1

We announced that self driving truck startup Kodiak Robotics, automaker Lotus, autonomous bus manufacturers, key craft and EV startup WM Motors have adopted the NVIDIA DRIVE Orin platform for their next generation vehicles. They join a large and rapidly growing list of companies adopting and developing on NVIDIA DRIVE, including auto OEMs, Tier 1 suppliers, NABs, trucking companies, robotaxis and Software Startups. Moving to data center, record revenue of $2,900,000,000 grew 24% sequentially and 55% from the year ago quarter with record revenue across both Hyperscale and Vertical Industries. Strong growth is led by hyperscale customers fueled by continued rapid adoption Ampere Architecture Tensor Core GPUs for both internal and external workloads. Hyperscale compute revenue doubled year on year, driven by the scale out of natural language processing and recommender models and cloud computing.

Speaker 1

Vertical industry growth was also strong, led by consumer Internet and broader cloud providers. For example, Oracle Cloud deployed NVIDIA GPUs for its launch of AI services such as text analysis, speech recognition, computer vision and anomaly detection. We continue to achieve exceptional growth in inference, which again outpaced our overall data center growth. We have transitioned our lineup of infants focused processors to the Ampere Arc Sensor, such as the A30 GPU. We also released the latest version of our Triton inference server software, enabling compute intensive inference workloads such as large language models to scale across multiple GPUs and nodes with real time performance.

Speaker 1

Over 25,000 companies worldwide use NVIDIA AI inference. A great new example is Microsoft Teams, which has nearly 250,000,000 monthly active users. It uses NVIDIA AI to convert speech to text real time during video calls in 28 languages and cost effective way. We reached 3 milestones to help drive more mainstream enterprise adoption of NVIDIA AI. First, we announced the general availability of NVIDIA AI Enterprise, comprehensive software suite of AI tools and frameworks that enables the hundreds of thousands of companies running NVIDIA, running vSphere to virtualize AI workloads on NVIDIA certified systems.

Speaker 1

2nd VMware announced a future update to vSphere with Tanzu that is fully optimized for NVIDIA AI. Newest combined with NVIDIA AI Enterprise, enterprises can efficiently manage cloud native AI development and deployment on mainstream data center service and clouds with existing IT tools. And third, we expanded our LaunchPad program globally with Infinix as our first digital infrastructure partner. NVIDIA Launchpad is now available in 9 locations worldwide, providing enterprises with immediate access software and infrastructure to help them prototype and test data science and AI workloads. Launchpad features NVIDIA certified systems and NVIDIA DGX systems running the entire NVIDIA AI software stack.

Speaker 1

In networking, revenue was impacted as demand outstripped supply. We saw momentum toward higher speed and new generation products, including ConnectX 5 and 6. We announced the NVIDIA Quantum2 400 gigabit per second end to end networking platform consisting of the Quantum2 switch, Connectix 7 network adapter and the BlueField 3 EPO. The NVIDIA Quantum 2 which is available from a wide range of leading infrastructure and system vendors around the world. Earlier this week, The latest top 500 list of supercomputers showed continued momentum for our full stack computing approach.

Speaker 1

NVIDIA Technologies accelerate over 70% of the systems on the list, including over 90% of all new systems and 23 of the top 25 most energy efficient systems. Turning to GTC. Last week, we hosted our GPU Technology Conference, which had over 270,000 registered attendees. Jensen's keynote has been viewed 25,000,000 tons over the past 8 days. While our spring GTC focused on new chips and systems, this edition focused on software, demonstrating our full routine staff.

Speaker 1

Let me cover some of the highlights. Our vision for Omniverse came to life at GDC. We significantly expanded its ecosystem and announced new capabilities. Omniverse Replicator is an engine for producing data to train robots. Replicator augments real world data with massive diverse and physically accurate synthetic datasets to both accelerate development of high quality, high performance AI across computing demands.

Speaker 1

NVIDIA Omniverse HAI Computer Vision, Natural Language Understanding, Recommendation Engine, and Simulation. Applications including automated customer service, virtual collaboration and content creation. Replicator and avatar join several other announced features and capabilities for Omniverse, including AI, AR, VR and simulation based technologies. We introduced 65 new and updated Software Development Kit, bringing our total to more than 150, serving industries from gaming and design to AI, Cybersecurity, 5 gs and Robotics. 1 of the SDKs is our first core license AI model, NVIDIA Riva for building conversational AI applications.

Speaker 1

Companies using Riva during the open beta include RingCentral for video conference live captioning and Ping An for customer service chat box. NVIDIA Riva Enterprise will be commercially available early next year remarks page. We introduced the NVIDIA's Numo MEGATRON framework optimized for training large language models on NVIDIA DGX SuperPOD infrastructure. This combination brings together production ready, enterprise grade hardware and software to help vertical industries develop language and industry specific chatbots, Personal Assistance, Content Generation and Summarization. Early adopters include CD, JD.com and VIN Brain.

Speaker 1

We unveiled BlueField DOCA 1.2, the latest version of our DPU programming label with new cybersecurity capabilities DOCA is to our DPUs as CUDA is to our GPUs. It enables developers to build applications and services on top of our BlueField GPUs. Our new capabilities make BlueField the ideal platform for the industry to build their own 0 Trust security platforms. The leading cybersecurity companies are working with us to provision their next generation firewall service on BlueField, including Check Point, Juniper, Fortinet, F5, Palo Alto Networks and VM WAN. And we released Clara Holoskem, a edge AI computing platform for medical instruments to improve decision making tools in areas such as robo assisted surgery, Interventional Radiology and Radiation Therapy Planning.

Speaker 1

Other new or expanded SDKs or libraries unveiled at GTC, including Reopt for AI optimized logistics, the Quantum for quantum computing, Morpheus for Cybersecurity, Modulus for Physical Based Machine Learning and Coonemaric, a datacenter scale math library to bring accelerated computing to the large and growing Python ecosystem. All in NVIDIA's computing platform continues to expand as a broadening set of SDKs enabled more and more GPU accelerated applications in industry use cases. CUDA has been downloaded 30,000,000 times and our developer ecosystem is now nearing 3,000,000 strong. The applications they develop on top of our SDKs and the cloud to edge computing platform are helping to transform multi $1,000,000,000,000 industries from healthcare to transportation to Texas services, Manufacturing, Logistics and Retail. In Automotive, we announced NVIDIA DRIVE Concierge and DRIVE Chofour, AI software platforms that enhance a vehicle's performance, features and safety.

Speaker 1

Drive Concierge built on Omniverse Avatar functions as an AI based in vehicle personal assistant, but enables automatic parking, summoning capabilities. It also enhanced safety by monitoring the driver throughout the duration of the trip. Drive Chauffeur offers autonomous capabilities, relieving the driver of constantly having to control the car. That will also perform address to address driving when combined with DRIVE criterion, a platform. For robotics, we announced Justin AGX Orin, the world's smallest, most powerful and energy efficient AI supercomputers of robotics, autonomous machines and embedded computing at the edge.

Speaker 1

Built on our Ampere architecture, Judson AGX Forum provides 6x the processing power of its predecessor and delivers $200,000,000,000,000 operations per second, similar to a GPU enabled server that fits into the palm of your hand. Justin AGX Orin will be available in the Q1 of calendar 2022. Finally, We revealed plans to build Earth-two, the world's most powerful AI supercomputer dedicated to confronting climate change. The system would be the climate change counterpart to Cambridge 1, U. K.

Speaker 1

Most powerful AI supercomputer that we built for healthcare research. Earth 2 harnesses all the technologies we've invented up to this moment. Let me discuss ARM. I'll provide you a brief update on our proposed acquisition of ARM. ARM with NVIDIA is a great opportunity for the industry and customers.

Speaker 1

With NVIDIA's scale, capabilities and robust understanding of data center computing, acceleration and AI, we can 5th arm in expanding their reach into data center, IoT and PCs and advanced arms IP for decades to come. The combination of our companies can enhance competition in the industry as we work together on further building the world of AI. Regulators at the USFTC have expressed concerns regarding the transaction, and we are engaged session with them regarding remedies to address those concerns. The transaction has been under review by China's antitrust authority pending the formal case initiation. Regulators in the UK and the EU have declined to production in Phase 1 of the reviews on competition concerns.

Speaker 1

In the U. K, they have also voiced National Security Concerns. We have begun the Phase 2 process in the EU and UK jurisdictions. Despite these concerns and those raised by some ARM licensees, we continue to believe in the merits and the benefits of the acquisition to ARM, to its licensees and the industry. We believe these concerns and those raised by some ARM license team.

Speaker 1

We continue to believe in the merits and benefits of the ARMEN acquisition. Moving to the rest of the P and L. GAAP gross margin for the 3rd quarter was up 260 basis points from a year earlier, primarily due to higher end mix Within Desktop Notebook G4 CPUs. The year on year increase also benefited from a reduced impact of acquisition related costs. GAAP gross margin was up 40 basis points sequentially, driven by growth in our data center and peer architecture products, which is particularly offset by a mix in gaming.

Speaker 1

Non gaming gross margin was up 150 basis points from a year earlier and up 30 basis points sequentially. Q3 GAAP EPS was $0.97 83% from a year earlier, non GAAP EPS was $1.17 up 60% from a year ago, adjusting for our stock split. Q3 cash flow from operations was 1,500,000,000 up from $1,300,000,000 a year earlier and down from $2,700,000,000 in the prior quarter. The year on year increase primarily reflects higher operating income, particularly offset by prepayments for Long Term Supply Agreement. Let me turn to the outlook for the Q4 of fiscal 2022.

Speaker 1

We expect sequential growth to be driven by data center and gaming, more than offsetting client in C&P. Revenue is expected to be $7,400,000,000 plus or minus 2%. GAAP and non GAAP gross margins are expected to be 65.3% and 67%, respectively, plus or minus 50 basis points. GAAP and non GAAP operating expenses are expected to be approximately 2,020,000,000 and $1,430,000,000 respectively. GAAP and non GAAP other income and expenses are both expected to be an expense of approximately $60,000,000 excluding gains and losses on non affiliated investments.

Speaker 1

GAAP and non GAAP tax rates are both expected to be 11%, plus or minus 1%, excluding discrete items. Capital expenditures are expected to be approximately $250,000,000 to 275,000,000 Further financial details are included in the CFO commentary. Other information is also available on our IR website. In closing, let me highlight upcoming events for the financial community who will be attending the Credit Suisse 25th Annual Technology Conference in person. On November 30, we will also be at the Wells Fargo 5th Annual TMT Summit virtually on December 1st, UBS Global PMT Virtual Conference on December 6th and the Deutsche Bank Virtual Auto Tech Conference on December 9th.

Speaker 1

Our earnings call to discuss our Q4 fiscal year 2022 results is scheduled for Wednesday, February 16. With that, we will now open the call for questions. Operator, will you please hold for these questions?

Operator

For our first question, we have Aaron Rakers from Wells Fargo. Iran. Your line is open.

Speaker 2

Yes. Thanks for taking the question and congratulations on the results. I guess I wanted to ask about Omniverse. Obviously, a lot of excitement around that. I guess the simple question is, Jensen, how do you define success in Omniverse as we look out over the next, let's call it 12 months?

Speaker 2

And how do we think about the subscription license opportunity for Omniverse? I know you've talked about 40,000,000 Total of 3 d Designers. I think that actually is double what you talked about back in August. So I'm just curious of how we as financial analysts should start to think about that opportunity materializing.

Speaker 3

Yes, thanks. Omniverse success will be defined by, number 1, developer engagement, connections with developers around the world. 2, applications being developed by Enterprises. 3, the connection of designers and creators among themselves. Those are the nearest term, and I would say that in month, type of definition of success.

Speaker 3

Near term also should be revenues and Omniverse. Omniverse has real immediate applications as I demonstrated at the keynote and I'll highlight a few of them right now. One of them of course is that It serves as a way to connect 3 d and digital design worlds. Think of Adobe as a world. Think of Autodesk as a world because Revit is a world.

Speaker 3

These are design worlds in the sense that People are doing things in it, they're creating things in it and it has its own database. We made it possible for a used world to be connected the very first time and for it to be, shared like a cloud document. That's not been possible ever before. And you can now share work with each other. You can see each other's work.

Speaker 3

You can collaborate. And so in the world of remote working, Omniverse's collaboration capability is going to be really appreciated. And that should happen right away. We would like to see that happen in very near terms. And that drives, Of course, more PC sales, more GPU sales, more workstation sales, more server sales.

Speaker 3

The second use case is digital twins. And you show you used probably examples of how several companies, Ariston using Omniverse to create a digital twin of our city, so that they could optimize radio placements and radio energy used for beamforming. You saw BMW using it for their factories. You're going to see people using it for warehouse, logistics warehouse to plan and to optimize their warehouses and to plan their robots. And so digital twin applications that are absolutely immediate.

Speaker 3

And then Remember, robots has several kinds. There's the physical robots that you saw and A physical robot would be a self driving car. And a physical robot could be the car itself, turning it into a robot, so that it could be an intelligent assistant. But I demonstrated probably In my estimation, the largest application of robots in the future is avatars. We built Omniverse Avatar to make it easy for people to integrate some amazing technology from computer vision to speech recognition, Natural Language Understanding, Gesture Recognition, Facial Animation, Speech Synthesis, Recommender systems, all of that integrated into one system and running in real time.

Speaker 3

That avatar system is essentially a robotic system. And the way that you would use that is, for example, 25,000,000 or so retail stores, restaurants, places like airports and train stations and office buildings and such, where you're going to have intelligent avatars doing a lot of assistance. They might be doing checkout, they might be doing check-in, They might be doing that customer support. And all of that could be done with avatars as I've demonstrated. So the virtual robotics application, digital bots or avatars It is going to be likely the largest robotics opportunity.

Speaker 3

So if you look at our licensing model, The way it basically works is that inside Omniverse, each one of the main users and the names of skipping 1 of the 20,000,000 creatives or 20,000,000 designers, the 40,000,000 creatives and designers around the world. When they share Omniverse, each one of the main users would be $1,000 per user per year. But don't forget that intelligent users or intelligent users that are going to be connected to Omniverse will likely be much larger as digital bots than humans. So I've mentioned 40,000,000, but there are 100,000,000 cars. And these 100,000,000 cars, will all have will all be have the capability to have something like an Omniverse avatar.

Speaker 3

And so those $100,000,000 in cars could be $1,000 per car per year. And in the case of the 25,000,000 or so places where you would have digital avatar as customer support or checkout smart retail or smart warehouse or smart whatever it is. Those avatars Also would each individually be a named account. And so they would be $1,000 per avatar per year. And so those are the immediate tangible opportunities for us and I demonstrated the application using the keynote.

Speaker 3

And then of course, behind all of that, call it a couple of 100,000,000 digital agents, intelligent agents, some of them even in some of them robots, some of them avatars at $1,000 per agent per year. Behind us are NVIDIA's GPU and PC, NVIDIA GPUs and Cloud, and NVIDIA GPUs and Omniverse servers. And My guess would be that the hardware part of it is probably going to be about half and then the licensing Probably about half of the time. And, but this is really going to be one of the largest graphics opportunities that we've ever seen. And the reason why it's taken so long for this to manifest is because that requires 3 fundamental technologies to come together, I guess, 4 fundamental technologies to come together.

Speaker 3

1st of all, is computer graphics. 2nd is physics simulation, Because we're talking about things and, worlds that has to be believable. So it has to abate a lot of physics. And then third is artificial intelligence as I've demonstrated and illustrated just now. And all of it runs on top of an omniverse computer that has to do not just AI, not just physics, not just computer graphics, but all of it.

Speaker 3

And so what long term people why people are so excited about it is, at the highest level, what it basically means is that long term, when we engage the Internet, which is largely 2 d today, long term, Every query would be 3 d. Instead of just, querying information, we would query and interact with people and avatars and things and places and all of these things are in 3 d. So hopefully one of these days, that we will try to realize it as fast as we can, every transaction that goes into the Internet touches a GPU. And today, that's a very small percentage, but hopefully one of these days will be a very, very high percentage.

Operator

For our next question, we have Mark Lipacis from Jefferies. Mark, your line is open.

Speaker 4

Hi. Thanks for taking my question. Jensen, it seems like every year there seems to be a new set of demand drivers for your accelerated platform, accelerated processing ecosystem. There's gaming, then Neural Networking and AI and the blockchain and the ray tracing. And if like 5 or 6 years ago, You guys showed a bunch of virtual reality demos, which are really exciting at your Analyst Day.

Speaker 4

Excitement died down. Now it seems to be resurfacing, particularly with Omniverse capability and Facebook shining a light on opportunity. So the two questions from that are, how close is your omnivarce Avatar to morphing into like a mass market technology that everybody uses daily. If you talk about like you said that everybody is going to be a gamer, is everybody going to be you said everybody is going to be a Omniverse Avatar user. And maybe the bigger picture is, is it reasonable to think about a new killer app coming out every year?

Speaker 4

Is there a parallel that we should think about with previous computing markets that we could think about for the computing era that we're entering right now? Thank you.

Speaker 3

Yes. I really appreciate that. Chips are enablers, but chips don't create markets. Software creates market. I've explained over the years that accelerated computing is very different than general purpose computing.

Speaker 3

And the reason for that is because you can't just write a 2 compiler and compile Quantum Physics into a chip and it doesn't. You can't just compile Astrologers equation and have it distributed across multiple GPUs and multiple nodes and have it be fast. You can't do that for computer graphics, you You can't do that for artificial intelligence, you can't do that for robotics, you can't do that for most of the interesting applications in the world. And because we've really went out of steam with CPEs, I mean, people are saying that not because it's not true, it's Abundantly clear that the amount of instruction level parables that you can squeeze out of the system is although not 0 It's incredibly hard. It's just incredibly hard.

Speaker 3

And there's another approach and We've been advocating accelerated computing for some time and now people really see the benefit of it. But it does require a lot of work and the work Basically, for every domain, for every application, you have for every application in large domain, ideally, You have to have a whole stack. And so whenever you want to open a new market by accelerating those applications or that domain of application, have to come up with a new stack. And the new stack is hard because you have to understand the application, you have to understand the algorithm, the mathematics, You have to understand computer science to distribute across to take something that was single threaded and make it multi threaded and make something that was You've done sequentially and make it process in parallel. You break everything.

Speaker 3

You break storage, you break networking, you break And so, it takes a fair amount of expertise and that's why we say that over the years, over nearly the course of 30 years, we've become a full stack company because we've been trying to solve this problem for practically 3 decades. And so that's one. But the benefit, once you have that ability, then you can open new markets. And we played a very large role in democratizing artificial intelligence and making it possible for anybody to be able to do it. Our greatest contribution is I hope when it's all said and done that we democratize scientific computing so that researchers and scientists, computer scientists, data scientists, scientists of all kinds.

Speaker 3

We're able to get access to this incredibly powerful tool that we call computers to do to Advanced Research. And so every single year, we're coming up with new stats and we got a whole bunch of stacks that we're working on and many of them I'm working on in plain sight, so that you see it coming. You just have to connect it together. One of the areas that that we spoke about this time, of course was Omniverse. And you saw the pieces of it being built, in, over time.

Speaker 3

And it took half a decade to start building Omniverse, but it built on a quarter century of work. In the case of the Omniverse Avatar, you can literally point to Merlin, the recommender, Megatron, the language large language model, Riva, the speech AI, all of our computer vision AIs that have been demonstrating over the years, Natural Speech Synthesis that you see every single year with I'm AI, the opening credits, How we're using, developing an AI to be able to speak in human ways so that people feel more comfortable and more engaged with the AI. Space, eye tracking and, magazine. And all of these technologies all kind of came together. They were all being built in pieces, but we integrated it.

Speaker 3

We had the intentions of integrating it to create what is called Omniverse Avatar. And now you have the question, how quickly will we deploy this? I believe Omniverse Avatar will be in drive thrus of restaurants, fast food restaurants, checkouts of restaurants in retail stores all over the world within less than 5 years. And we're going to use it in all kinds of different applications because there's such a great shortage of labor and there's such a wonderful way that you can now engage and Avatars. And it could it doesn't make mistakes.

Speaker 3

It never gets tired and it's always on. And we made it so that it's cloud native. And so when you saw the keynote, I hope you'd agree That the interaction is instantaneous and the conversational forum that's so enjoyable. And so anyways, I think What you highlighted is true. 1, it's already continuing as a full stack challenge.

Speaker 3

2, it takes software to open new markets. Chips don't open new markets. You build another chip, you can steal somebody's share, but you can't open new markets. And it takes software to open the market. NVIDIA is rich with software and that's one of the reasons why we think we could engage such large market opportunities.

Speaker 3

And then lastly, with respect to Omniverse, I believe it's a near term opportunity that we've been working on for some 3, 4, 5 years.

Operator

For our next question, we have CJ Muse from Evercore ISI. CJS. Your line is open.

Speaker 5

Yes, good afternoon. Thank you for taking the question. And I guess not an omniverse question, But I guess, Jensen, I'd like your commitment that you will not use Omniverse to target the sell side research industry. As my real question, can you speak to your data center visibility into 2022 and beyond? And within this outlook, Can you talk to traditional cloud versus industry verticals and then perhaps emerging opportunities like Omniverse and others?

Speaker 5

Would love to get a sense of kind of what you're seeing today. And then as part of that, how you're planning to secure foundry and other supply Yes, to support that growth. Thank you.

Speaker 3

Thank you, CJ. First of all, we have secured guaranteed supply, very large amounts of it, quite a spectacular amount of it from the world's leading foundry and substrate and packaging and testing companies that are integral part of our supply chain. So we have done that and feel very good about our supply situation, particularly starting the second half of next year and going forward. I think this whole last year was a wake up call for everybody to be much more mindful about not taking the supply chain for granted. And we were fortunate to have such great partners, but nonetheless we've secured our future.

Speaker 3

With respect to data center, about half of our data center business comes from the cloud and cloud service providers and the other half comes from enterprise, what we call company enterprise companies. And they're all in all kinds of industries. And about 1% of it comes from supercomputing centers. So 50% or so cloud, 50% or so enterprise and 1% supercomputing. And We expect next year the cloud service providers to scale out Their deep learning and their AI, workload really aggressively.

Speaker 3

And we're seeing that right now. We built a really fantastic platform and number 1. Number 2, the work that we've been doing with TensorRT, which is the runtime that goes into the server that's called Triton. It's one of our best pieces of work. I'm just so proud of it.

Speaker 3

And We said nearly 4 years ago, three and a half years ago, that inference is going to be one of the great computer science challenges and really proving to be tough. And the reason for that is because sometimes it's due to price, sometimes it's latency, sometimes it's interactivity and the type of models we get to influence is just all over the map. It's not just computer vision or image recognition. It's all over the map. And the reason for that is because there's so many different types of architectures.

Speaker 3

There's so many different ways to build different applications. And so the application is complicated. And in front of me is just a wonderful people working. AI. We're now on our 8th generation on that.

Speaker 3

It's adopted all over the world. Some 25,000 companies are now using NVIDIA and recently as DTC, we announced 2 very, very big things. One, we reminded everybody that we Just a month before, we had Triton support not just in every generation of NVIDIA computers, of which there are so many versions. Could you imagine Without Triton, how would you possibly deploy AI across the entire fleet of NVIDIA servers, GPU servers that are all over the world. And so it's almost an essential tool just to operating and take advantage of all of NVIDIA's GPUs that are in datacenter.

Speaker 3

Q, we support GPUs. And so it's no longer necessary for someone to have 2 inference servers. You can just have 1 inference server. And because the NVIDIA version is already essential, Now everybody could just use Triton and every single server in the data center could be part of the inference capacity. And then we did something else that was a really big deal, as you could see, which is this thing called Forest Infrared Library, it's called SIL.

Speaker 3

So basically, The most popular machine learning systems and inference models are based on trees and decision trees and Boosted Gradient Tree. And people might know it as XGBoost. And it's used all over the place in fraud detection and recommender systems and they're utilizing companies all over the world because it's just It's self explanatory. You can build upon it. You don't worry about aggressions.

Speaker 3

It could build bigger and bigger treason. And we risk GPC we announced and we support that as well. And so all of a sudden, all of that workload that runs on GPUs, not only did it run on Triton, It becomes accelerated. I mean, the last the next deal we announced, with the tremendous interest in large language models, Triton Model also supports multi GPU and multi memory inference, so that we can take something like and OpenAI GPT-three, a NVIDIA MEGATRON 530e or anybody's giant model that's being developed all over the world in all these different languages and all these different domains and all these different fields of science and what's in the industry. We can now inference it in real time.

Speaker 3

And I demonstrated it in one of the demos. There was a toy gentleman that the team built and was able to basically answer questions in real time. And so that is just a giant breakthrough. And these are the type of workloads That's going to make it possible for us to continue to scale out in data centers. So back to your original question, I think next year is going to be quite a big year for data centers.

Speaker 3

Customers are very mindful of securing their supply for their scale out. So, we have a fair amount of visibility and more visibility probably than ever of data centers. But in addition to that, Triton is just seeing adoption everywhere. And then finally, our brand new workload, which is built on top of AI and graphics and simulation, which is Omniverse. And you saw in the examples that I made.

Speaker 3

These are real companies doing real work. And And one of the areas that has severe shortages around the world is customer support, just genuine severe shortages all over the world. And we think that the answer is Omniverse Avatar and its, it runs in data centers. You could adapt Omniverse Avatar to do on drive throughs or retail checkout or customer service and I demonstrated that with Tokyo talking kiosk. You could use it for a teleoperated customer service, We demonstrated that with Maxine.

Speaker 3

We demonstrated how you could use it even for video conferencing. And then lastly, we demonstrated how you can use Omniverse Avatar for robotics and for example, to create a concierge, what we call drive concierge for your car, turning it into an intelligent and quality customer support in Intelligent Asia. I mean Omniverse Avatar is going to be a really exciting driver for enterprises next year. And so next year, it's going to be a we're seeing up for

Operator

and we have Stacy Rasgon from Bernstein Research. Stacy, your line is open.

Speaker 6

Hi, guys. Thanks for taking my questions. I wanted to ask 2 of them on data center, both near term and then maybe a little longer term. On the near term, Colette, You suggested guidance into Q4 be driven by data center and gaming, and you mentioned data center first. Does that mean that it's bigger?

Speaker 6

I think you could just help us like parse The contribution of each of those into Q4. And then into next year, given the commentary for the last question, Again, it sounds like you've got like a very strong outlook for data center, both from hyperscale and enterprise. And if I look at sort of the implied guidance, because our data center for you is probably likely to 50% year over year in this fiscal year. Would it be crazy to think given all those drivers that

Speaker 3

it could grow by a similar amount next year as well? How should I be thinking about that given all of the drivers that you've been laying out?

Speaker 1

Okay. Thanks, Stacy, for the question. Let's first focus in terms of our guidance for Q4. Our statements that we made were, yes, about driven by revenue growth from data center and gaming sequentially. You could probably expect our data center to grow faster than our gaming, probably both in terms of percentagewiseandabsolutedollars.

Speaker 1

We also expect our CMP product to decline quarter on quarter to very negligible levels in Q4. So I hope that gives you a color on Q4. Now in terms of next year, we'll certainly turn the corner into the new fiscal year. We certainly provide guidance 1 quarter out. We've given you some great discussion here about the opportunities in front of us, opportunities with the hypersales, the opportunities with the verticals.

Speaker 1

Omniverse is a full stop opportunity in front of us. We are securing supply for next year, not just for the current year in Q4 to allow us to really grow into so much of this opportunity going forward. But at this time, we're going to wait until next year to provide guidance.

Speaker 6

Got it. That's helpful. I appreciate it. Thank you.

Operator

For the next question, we have Vivek Arya from Bofa Securities. Vivek, your line is open.

Speaker 7

Thanks for taking my question. Actually, I had 2 quick ones. So Colette, you suggested the inventory purchase and supply agreements are up, I think almost 68% year on year. Does that provide some directional correlation with how you are preparing for growth over the next 12 months to 24 months. So that's one question.

Speaker 7

And then the bigger question, Jensen, that I have for you is, where are we in the AI Adoption Cycle. What percentage of servers are accelerated in hyperscale and vertical industry today and where can those ratios get to?

Speaker 1

Thanks for the question. So let's first start in terms of supply or our supply purchase agreements. You have noted that we or discussing that we had made payments towards some of those commitments. Not only are we procuring for what we need in the quarter, what we need next year. And again, we are planning for growth next year.

Speaker 1

So we have been planning, that supply purchases. We are also doing long term supply purchases. These are areas of capacity agreements and or many of our different suppliers. We made a payment within this quarter of approximately 1,600,000,000 out of total long term capacity agreement of about $3,400,000,000 So we still have more payments to make and we will likely continue to be purchasing longer term to support our growth that we are planning for many years to come.

Speaker 3

Every single server will be GPU accelerated someday. Today, of all the clouds and all the enterprise, less than 10%. That kind of gives you a sense of where you are. In terms of the workloads, it is also consistent with that in the sense that, a lot of the workloads still only run on CPUs. And which is the reason why in order for us to grow, we have to be a full stack company.

Speaker 3

And we have to go find applications in order to find them very cleanly, right, focus on applications that require acceleration or benefits tremendously from acceleration that if they were to get a 1,000,000 x speed up, which sounds insane, but it's not. And mathematically, I can prove it to you. And historically, I can even demonstrate to you that in many, many areas we have seen 1,000,000 ex beat ups and has completely revolutionized those industries. Computer graphics is of course one of them. Omniverse would not be possible without it.

Speaker 3

And so, the work that we're doing with Digital Biology Protein Synthesis, which is likely going to be one of the large industries of the world that doesn't exist today at all, Protein Engineering, right? And the protein economy is likely going to be very, very large. You can't do that unless you are able to get a 1,000,000 x speed up in, super relation of protein dynamics. And so Those are and not to mention some of the most imperative problems that we have to go and engage. Climate science needs a millionx billionx speed up.

Speaker 3

And we're going to we are at a point where we can actually tackle it. And So in each one of these cases, we have to find we have to focus our resources to go and Accelerators Applications and that translates to growth. Until then, they learn in 2 years. And If you look at a lot of today's speech synthesis and speech recognition systems, And you still use a fairly traditional or mixture of traditional and deep learning approaches for speech AI. NVIDIA Viva is the world's first, I believe.

Speaker 3

That is end to end deep neural network. And we've worked with many companies in helping them advance there so that they could move their clouds to a narrow based approaches. But that's one of the reasons why we do it, so that we could provide as a reference, but we can also license it to enterprises around the world so that they could adapt For their own use cases. And so one application after another, we have to get it Accelerated 1 domain after I might have said it accelerated. One of the ones that I was very excited about and something that we've been working on for so long EDA, even our own industry, electronic design automation.

Speaker 3

For the very first time, you announced the EDA using using 2Q Accelerated Computing, whether it's because of the artificial intelligence capability, because EDA is a very large combinatorial optimization program. And using artificial intelligence, you could really improved the design quality and design timing. So we're seeing from all the major EDA vendors from chip design to simulation, to PCB design and optimization, design synthesis, moving towards artificial intelligence and GPU acceleration in a very significant way. And then we see that with mechanical CAD and traditional CAD application. Now also jumping on to GPU acceleration and getting very significant speed ups.

Speaker 3

And So I'm super excited about the work that we're doing in each one of these domains because every time you do it, you open up brand new market. And customers that never used NVIDIA GPUs now can because ultimately people don't buy chips. They're trying to solve problems. And without a full stack, without software to keep, we can't really command the enabling technology where the chip provides and ultimately solving the customer's problem.

Operator

Your final question comes from the line of Timothy Arcuri from UBS. Timothy, your line is open.

Speaker 3

Thanks a lot. Colette, I had

Speaker 4

a question about gross margin. Are there any margin headwinds maybe on the wafer pricing side that We should sort of think about normalizing out, because gross margin is pretty flat between fiscal Q4 and fiscal Sorry, between fiscal Q2 and fiscal Q4, but I imagine that's kind of masking a strong underlying margin growth, especially as data center has been actually driving that growth. So I'm wondering if maybe there are some underlying factors that are sort of gating gross margin. Thanks.

Speaker 1

Yes. So we have always been working on our gross margin and being able to absorb a lot of the cost changes along the way, architecture to architecture year to year. So that's always based in to our gross margins. Our gross margins right now are largely stable. Our incremental revenue, for example, what we're expecting next quarter will likely align to our current gross margin levels that we finished in terms of Q3.

Speaker 1

Our largest driver always continues to be mix. We have a lot of different mix that has risen related to high end AI and RTX solutions, for example, and the software that's embedded in solutions have allowed us to increase our gross margin. As we look forward long term, software, if sold separately, can be another driver of gross margin increases in the future. But cost changes, cost increases are generally been a part of that gross margin for years.

Operator

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

Speaker 3

Thank you. We had an outstanding quarter. Demand for NVIDIA AI is strong with hyperscalers and cloud services deploying at scale and enterprises broadening adoption. We now count more than 25,000 companies that are using NVIDIA AI. And with NVIDIA AI Enterprise Software Suite, collaboration with VMware and our collaboration with Equinix to place NVIDIA LaunchPads across the world.

Speaker 3

Every enterprise has an easy on ramp to NVIDIA AI. Gaming and ProVis are surging. RTX opportunity continues to expand with the growing markets of gamers, creators, designers and now professionals building home workstations. We are working hard to increase supply for the overwhelming demand this holiday season. Last week, GTC showcased expanding universe of NVIDIA accelerated computing.

Speaker 3

In combination with AI and data center scale computing, The model we pioneered is on the cusp of producing 1,000,000x speedups that will revolutionize many important fields, already AI and upcoming robotics, Digital Biology and what I hope, Climate Science. GTC highlighted full stack expertise in action built on CUDA and our acceleration libraries in Data Processing, in Simulation, Graphics, Artificial Intelligence, market and domain specific software is needed to solve customer problems. We also showed how software opens new growth opportunities for us. The chips are the enablers, but it's the software that opens new growth opportunities. NVIDIA has 150 SDKs now, addressing many of the world's largest end markets.

Speaker 3

1 of the major themes of this GPP was Omniverse, our simulation platform for Virtual Worlds and Digital Twins. Our body of work and expertise in graphics, physics simulation, AI, Robotics and Fullstack Computing made Omniverse possible. At GTC, we showed how Omniverse is used to reinvent collaborative design, customer service avatars and video conferencing and digital twins of factories, processing plants and even entire cities. This is just the tip of the iceberg of what's to come. We look forward to updating you on our progress next quarter.

Speaker 3

Thank you.

Operator

Thank you. I will now turn over to Jensen for closing remarks.

Speaker 1

Well, I think we just heard the closing remarks. Thank you so much for joining us. We look forward to seeing everybody at the conferences that we have planned over the next 2 months, and I'm sure we'll talk before the end of next earnings. Thanks again, everybody.

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Earnings Conference Call
NVIDIA Q3 2022
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