NVIDIA Corp (NVDA) — Q4 2021 Earnings Call Transcript

Thank you. Good afternoon, everyone, and welcome to NVIDIA's conference call for the fourth quarter of fiscal 2021. With me on the call today from NVIDIA are Jensen Huang, President and Chief Executive Officer; and Colette Kress, Executive Vice President and Chief Financial Officer. I'd like to remind you that our call is being webcast live on NVIDIA's Investor Relations website. The webcast will be available for replay until the conference call to discuss our financial results for the first quarter of fiscal 2022. The content of today's call is NVIDIA's property. It can't be reproduced or transcribed without our prior written consent. During this call, we may make forward-looking statements based on current expectations. These are subject to a number of significant risks and uncertainties, and our actual results may differ materially. For a discussion of factors that could affect our future financial results and business, please refer to the disclosure in today's earnings release, our most recent forms 10-K and 10-Q and the reports that we may file on Form 8-K with the Securities and Exchange Commission. All our statements are made as of today, February 24, 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.

Thanks, Simona. Q4 was another record quarter with revenue exceeding $5 billion and year-on-year growth accelerating to 61%. Full-year revenue was also a record at $16.7 billion, up 53%. Our Gaming business reached record revenue of $2.5 billion in Q4, up 10% sequentially, and up 67% from a year earlier. Full-year gaming revenue was a record at $7.8 billion, up 41%. Demand is incredible for our new GeForce RTX 30 Series products based on the NVIDIA Ampere GPU architecture. In early December, we launched the GeForce RTX 3060 Ti, which joined the previously launched RTX 3090, 3080, and 3070. The entire 30 Series lineup has been hard to keep in stock and we exited Q4 with channel inventories even lower than when we started. Although we are increasing supply, channel inventories will likely remain low throughout Q1. GeForce RTX 30 series graphics cards were a holiday sensation not just due to their amazing performance, but also due to the rich features, including our second-generation RTX ray tracing technologies and DLSS, AI-powered performance accelerator, which massively boost frame rates in graphically demanding titles. Three dozen games now all support RTX, including the top Battle Royale game, Fortnite; the top role-playing game, Cyberpunk 2077; the top massively multiplayer online game, World of Warcraft; and the best-selling game of all time, Minecraft. RTX has clearly set the new standard in gaming. Building on this momentum at CES in January, we introduced a wave of Ampere architecture gaming products, including our biggest ever laptop launch powered by GeForce RTX 3060, 3070, and 3080 laptop GPUs and with our third-generation Max-Q technology. These new thin and lightweight gaming laptops increased performance and energy efficiency by up to 2x from the prior generation. RTX 3060 laptops start at $999 and are faster than the previous generation laptops, which sold for $2,500. The incredible performance, design and price points of these new laptops will delight the growing universe of gamers and creators as well as students and professionals. The gaming laptop market has grown seven-fold in the past seven years and momentum is building. With top OEMs bringing to market a record 70-plus laptop models based on the GeForce RTX 30 series. GeForce laptops as a whole are the fastest-growing and one of the largest gaming platforms. Also at CES, we announced the GeForce RTX 3060 GPU, priced at $329, extending the 30 series desktop lineup further into the mainstream. We expect strong demand when it launches this Friday as 60-class GPUs have traditionally been our most popular products. Starting with the 3060, we're taking an important step to maximize the supply of GeForce GPUs for gamers. Users are constantly discovering new applications for our powerful programmable GPUs and cryptocurrency mining is one of them. With rising Ethereum prices, there are indications that miners are behind GPUs. We would like GeForce GPUs to end up with gamers. So we have created new special software drivers that will detect the Ethereum mining algorithm cutting in half the mining efficiency of the GeForce RTX 3060. We suspect the significant increase in the Ethereum network hash rate observed over the past few months was driven by a combination of previously installed mining capacities that were reactivated as well as new sales of GPUs and ASICs. Since our GPUs are sold to graphics card manufacturers and then onto distribution, we don't have the ability to accurately track or quantify their end use. Analyst estimates suggest that cryptomining contributed $100 million to $300 million to our Q4 revenue, a relatively small portion of our gaming revenue in Q4. Cryptocurrencies have recently started to be accepted by companies and financial institutions and show increased signs of staying power to address industrial Ethereum mining demand. Last week, we announced a new line of NVIDIA CMPs or cryptomining processors. Shipments will start in March. CMPs lack display outputs and have other optimizations that improve cryptomining power efficiency. CMP products will let us gain some visibility into the contribution of cryptomining to our overall revenue. For Q1, we estimate that CMP will contribute approximately $15 million. We plan to sell these products to industrial miners. We will quantify their contribution each quarter for transparency. Over the past year, it has become clear that we've entered a new era in which gaming is an integral part of global culture. The number of concurrent users on Steam has more than doubled since 2018 and continues to hit new records. In 2020 alone, more than 100 billion hours of gaming content was seen on YouTube and 0.5 billion people watched e-sports. Increasingly, we aren't just gaming. We're also watching sports, attending concerts, creating content, and connecting with our friends in virtual environments. Additionally, we are excited about the new experiences like VR. Significantly more content is now available, including arguably the first VR killer app, Beat Saber, and there are now almost 2 million VR users on Steam. And with these powerful structural shifts, we expect our gaming business to remain on a robust growth trajectory. The GeForce RTX 30 Series GPUs have kicked off a powerful upgrade cycle and we estimate only around 15% of GeForce gamers have an RTX-cost GPU, which is needed to experience the beautiful ray trace graphics of modern games. Moreover, the universe of gamers is rapidly expanding and the reach of GeForce has extended beyond gamers to some 45 million creators. In addition, gaming revenue continues to benefit from a favorable mix shift as gamers and creators keep moving to higher-end GPUs. We expect another great year for GeForce. Earlier this month, we celebrated the one-year anniversary of the GeForce NOW cloud gaming platform, which is now over 6 million members strong. GeForce NOW offers 800 PCs from over 300 publishers, more than any other cloud gaming service including any of the most played free-to-play games, starting with support for Windows PCs, Macs, and Android devices. We added support in recent months to Chromebooks, iPhones, and iPads. GFN has grown globally with more than 65 countries on our service and more are added regularly by our GeForce NOW alliance partners. Moving to Pro Visualization, Q4 revenue was $307 million, up 30% sequentially and down 10% year-on-year and ahead of our expectations. Full-year revenue was $1.1 billion, down 13%. Strong sequential growth was driven primarily by a recovery in desktop workstations as some customers returned to the office and enterprises resumed purchases that had been deferred by the pandemic. Notebook GPUs grew sequentially to a record as enterprises continue to support remote workforce initiatives. Looking ahead, the reopening of businesses will benefit desktop workstations, but longer-term workforce trends will likely shift our mix to notebook GPUs and cloud offerings. Healthcare was a standout vertical in the quarter with significant orders from GE, Siemens, and Oxford Nanopore technologies. The public sector and automotive also saw strength. Omniverse, our real-time 3D collaboration and simulation platform is now in open beta. Over 500 creators and professionals have tested Omniverse through our early access program. Omniverse is one of our most important and exciting platforms. We are delighted by its initial acceptance and look forward to sharing more details on its long-term growth opportunity in the coming months. Moving to Automotive; Q4 revenue was $145 million, up 16% sequentially and down 11% year-on-year. Full-year revenue of $536 million, declined 23%. Sequential growth was driven by continued recovery in the global automotive production volumes and growth in AI cockpit revenue. Year-on-year decline reflects the expected ramp-down of legacy infotainment. NVIDIA has emerged as the industry's leading end-to-end full-stack technology provider for self-driving and AI-enabled vehicles. Our SOC that drives the self-driving platform is built on delivers an unrivaled 254 trillion operations per second of performance on industry-leading power efficiency, helping to revolutionize the transportation industry. Our technology leadership has driven a robust rapidly growing set of opportunities. We have great momentum with an expanding list of electric vehicle OEMs, including NIO, SAIC, Li Auto, and Xpeng which are all using the NVIDIA DRIVE platform to power their next generation of vehicles. We look forward to growing with them as they continue to scale. Our software-defined platform is the only solution that spans from the data center for training deep neural nets and running physically accurate simulations to full-stack in-car solutions scaling for ADAS to Level 5 fully autonomous functionality. Autonomous vehicle companies are harnessing this technology. Zoox recently unveiled its Level 5 bi-directional robotaxi powered by NVIDIA, and Waymo launched its next-generation autonomous truck using NVIDIA DRIVE Orin. Earlier this year, Mercedes announced a 56-inch wide MBUX Hyperscreen powered by NVIDIA AI cockpit technology. This builds on our momentum with Mercedes first-generation MBUX system, which is now in 1.8 million cars. We are in the early innings of a significant opportunity. We have built a multi-billion dollar design win pipeline for our self-driving and AI cockpit solutions, which will drive a material inflection in revenue over the next few years. Moving to data centers; revenue was $1.9 billion, which exceeded our expectations, was comparable to last quarter and up 97% from the year-ago period, which did not include Mellanox. Data center compute revenue was up 45% year-on-year. Full-year data center revenue rose 125% to a record $6.7 billion, including almost 70% growth from data center compute. From a sequential perspective, the data center compute's stronger than expected double-digit growth more than offset the anticipated decline in Mellanox revenue, which included a large non-recurring network sale to a single OEM in Q3. Compute growth was led by vertical industries where OEM partners continued ramping up their 100-day 100 base servers and our own DGX system sales were strong. Vertical industries accounted for well over 50% of data center revenue across compute and networking, with particular strength in supercomputing, financial services, higher education, and consumer internet verticals. Additionally, hyperscale customers continued to deploy the A100, driving both sequential growth and exceptionally strong year-on-year growth in data center compute. The A100 has been adopted by all major cloud customers globally and is being deployed by hyperscale customers for internal workloads. Still we are in the early stages of adoption and expect continued growth this year. The ramp of the A100 has been smoother and accomplished with better visibility than prior generations. Its universal AI training and inference capabilities as well as support for wider sets of applications and outstanding performance are driving customer utilization, a clear sign of the A100's value. Turning to Mellanox. We are seeing continued strong traction and robust momentum across our customer set. Its revenue was up over 30% from Mellanox's Q4 revenue in calendar 2019 when it was still a standalone company. Year-on-year growth in the quarter was led by hyperscale and large consumer internet customers, which grew over 60% from last year with several contributing record revenues. Consistent with our outlook, Mellanox had a sequential decline impacted by a non-recurring sales to a China OEM in Q3. We expect to return to sequential growth in Q1 driven by strong demand for our high-speed networking products, including the ramp of ConnectX adapters with CSPs and all major server OEMs in their upcoming refresh. We also see strong momentum in high-performance computing with HDR InfiniBand products. For example, we won six of the seven supercomputers awarded over the past few months by Euro HPC. Starting next quarter, we will continue to provide color on networking as part of the data center market platform, but we will no longer break out Mellanox revenue separately. Looking forward, we are incredibly excited about the opportunities in data centers. Accelerated computing is not only delivering significant gains in performance but is also an energy-efficient and cost-effective method of computing. Virtually every industry is adopting technology with greater urgency as companies adapt to the new world of more distributed workers and customers. As industries embark on this journey, they are also increasingly focused on combating climate change. To that end, the A100 performed AI computations with one-twentieth the power consumption of CPUs and powers a leading supercomputer, which is number one on the Green500 list of the world's most efficient supercomputers. Indeed, NVIDIA-powered machines recently captured 25 of the top 30 spots on the Green500 list. Accelerated computing is not only serving the exponential growth in demand for compute; it can also help bend the power consumption curve. With accelerated computing, NVIDIA is pioneering a revolution forward in the computing industry. Before I move to the P&L and outlook, let me give you an update on our proposed acquisition of Arm. In September, we announced plans to acquire Arm from SoftBank Group in a transaction that will create the premier computing company for the age of AI. At that time, we said it would take approximately 18 months to secure regulatory approvals in the U.S., the UK, the EU, China, and other jurisdictions. Thorough reviews are typical with deals of this size. This process is moving forward as expected. We are in constructive dialogue with the relevant authorities and are confident that regulators will see the benefits to the entire tech ecosystem. As we have said, this combination will spur competition; together, Arm and NVIDIA will provide greater choice to the data center ecosystem, a compelling alternative CPU architecture for the market, and further enhance Arm's offering in mobile and embedded. Our intention is to increase investment in Arm's existing roadmap, adding resources to stimulate growth in new markets. We love and intend to maintain Arm's open licensing model, a commitment guaranteed both by long-term legally binding contracts as well as our own interest in ensuring this investment is a profitable one for us. We are on the cusp of a new age in which AI fuels industries ranging from healthcare to scientific research to the environment. With this transaction, our vision is to boost Arm's potential so it can thrive in this new era and grow into promising new markets. Moving to the rest of the P&L. Q4 GAAP gross margins were 63.1% and non-GAAP gross margins were 65.5%. GAAP gross margins declined year-on-year due to amortization of developed technology acquired from Mellanox, partially offset by product mix. The sequential increase was due to higher margins for gaming GPU and lower IP related costs, partially offset by lower margin mix in our data center portfolio. Non-GAAP gross margins increased by 10 basis points year-on-year and were flat sequentially in line with our expectations. Q4 GAAP EPS was $2.31, up 51% from a year earlier. Non-GAAP EPS was $3.10, up 64% from a year ago. Q4 cash from operations was a record $2.07 billion. With that, let me turn to the outlook for the first quarter of fiscal 2022. Revenue is expected to be $5.3 billion plus or minus 2% with most of the sequential growth driven by gaming. GAAP and non-GAAP gross margins are expected to be 63.8% and 66% respectively, plus or minus 50 basis points. GAAP and non-GAAP operating expenses are expected to be approximately $1.67 billion, and $1.2 billion respectively. For the full-year we expect to grow non-GAAP OPEX in the mid-20% range. GAAP and non-GAAP other income and expenses are both expected to be an extent of approximately $50 million. GAAP and non-GAAP tax rates are both expected to be 10% plus or minus 1%, excluding discrete items. Capital expenditures are expected to be approximately $300 million to $325 million. Further financial details are included in the CFO commentary and other information on our IR website. In closing, let me highlight upcoming events for the financial community. We will be virtually attending the Raymond James Institutional Investors Conference on March 1st, the Morgan Stanley Technology, Media and Telecom Conference on March 3rd, and the Arete Virtual Semis Conference on March 3rd. In addition, we will be hosting a virtual Investor Day on Monday, April 12th following a live stream of Jensen's opening keynote at our GPU Technology Conference. Our earnings call to discuss our first quarter is scheduled for Wednesday, May 26. We will now open the call for questions.

Good afternoon. Thank you for taking the question. I guess, Jensen, higher-level question for you on the enterprise side. You're now a couple of quarters into the ramp of A100. And curious if you could speak to whether you've seen any surprises here, any areas of specific strength worth calling out? And any changes to how you're thinking about the size of this opportunity?

Yes. Thanks a lot. It's Jensen. As you know, the A100 is a very different type of GPU. This is our first universal computing GPU. It's great at high-performance computing. It's great at data analytics. It's great at training. And also for our highest GPU, it’s also the first time that it is incredible for inference. It's some 20 times faster than the previous generation. We may introduce some really exciting new computational formats like TF32, TensorFloat-32 for training. And with a multi-instance GPU, turning our GPU from one instance into a whole bunch of smaller GPUs, autonomous GPUs to improve performance and reduce latency. The capability is really quite exciting. We're seeing strength in hyperscalers as they continue to accelerate their adoption of AI. Some of the new applications we've spoken about a couple of times before, include the transition to deep learning, conversational AI, speech recognition to natural language understanding all the way to speech synthesis, which is now based on AI – based on deep learning. The other area that's growing incredibly fast is the deep learning recommender models. Just about everything you do on the Internet is based on recommenders. There are hundreds of different recommenders out there, whether you're shopping or recommending music or recommending news or recommending search, and so all of these different types of applications are driving that. For the first time, we saw our industrial application - industrial data center growing to be larger than hyperscale. And we're seeing industrial applications across scientific computing where simulation-based approaches are now being fused with AI approaches for weather simulation, genomics, molecular dynamics simulation, quantum chemistry, and even simulating quantum computing, which is one of the really exciting areas. We're seeing AI being deployed for big data analytics, RAPIDS, which is NVIDIA’s created open-source platform for data analytics of Spark 3.0, which NVIDIA really led and is now GPU-accelerated. So now you could have big data in the cloud while doing big data analytics in the cloud on all of the CSP platforms. We're seeing a lot of excitement around financial services and consumer internet services are all really growing nicely. The A100 adoption is just starting. I mean, we're going to see several years of continued growth ahead of us while as AI gets adopted in clouds and industries.

Thanks for taking my question. Just a clarification and then a question for Jensen. On the clarification, Colette, I was hoping you could give a little more color around Q1? Do you still expect data center to grow sequentially in Q1? I know you said that most of the growth will come from gaming, but any color on the data center would be useful? And then, Jensen, the question for you is, in your press release you used the phrase AI driving the smartphone moment for every industry. Could you help us quantify what that means? And where I'm going with that is, is there a number in terms of what percentage of servers are shipping today with your accelerators? And where can that ratio go over time? Is that a fair way of looking at the adoption of your technology and AI?

So thank you, Vivek. Your question regarding the guidance as we head into Q1. We had indicated that, yes, a good percentage of our growth between Q4 and Q1 would come from gaming, but we also do expect the data center to grow. Most of our sequential growth will come from gaming, but keep in mind, we also expect all of our market platforms will likely be able to grow quarter-over-quarter.

Because we are entering the third phase of AI. The first phase of AI was when we invented the computing platforms, the new chips, the new systems, the new system software, the new middleware, the new way of working, the new way of developing software, which the industry, the world is now starting to call MLOps. The way that software is developed and the way that it is deployed is completely different than in the past. In fact, I heard a great term, Software 2.0, and it makes a lot of sense. It's a computer that is writing software. The way that you develop software is completely different; the way you compute is different. And that was our first phase, and that started a journey that was some eight, nine years ago now. The second phase was the adoption of using this in an industrial way for clouds. And we saw it revolutionize new services; whether it's speech-oriented services or search-oriented services, recommended services, the way you shop, the way you use the Internet is completely different today. And so that's really the second phase and those two phases are still continuing to grow, and you're still seeing the growth associated with that. The third phase is the industrialization of AI. And some great examples, when I say in terms of smartphone moment, I mean that it's a device with AI, it’s autonomous, and it's connected to a cloud service and it's continuously learning. Some of the exciting examples that I've seen and we're working with companies all over the world include some 7,000 AI startups that we're collaborating with, and almost all of them are developing something like this. And large industrial companies, whether it's John Deere or Walmart, they're all developing applications kind of like this. This includes an autonomous system, an autonomous machine. In our case, it's called Jetson. In the automotive space, it’s called DRIVE. These systems are running AI applications and connected to cloud services for continuous improvement. The industries I'm so excited about give an opportunity to change the way that they interact with their customers. Rather than selling something once, they sell something and provide service that's on top of it. And they can stay engaged with the customers. The customers could get a product that's improving all the time, just like your smartphone. That's kind of the reason why I've been calling it a smartphone moment for all these industries. We've seen what happened to the smartphone revolution and the smart speaker revolution, and you're going to see smart lawnmowers, smart tractors, smart air conditioners, smart elevators, smart buildings, smart warehouses, robotic retail storage, and entire store – virtually all of them will have autonomous capability driven by AI. What’s new for the industry is that all of the enterprises in the world use to have computers for IT to facilitate their employees and their supply chain. But in the future, all of these industries, whether it's in medical imaging or lawnmowers, will have data centers that host their products just like the cloud service providers. This is a brand new industry and we have a platform that we call EGX, which consists of 5G Edge AI systems. We have the autonomous systems we call AGX, which is utilized in Jetson and DRIVE. Between those two systems and the software stack that we have on top of it, we're in a great position to help these industries transform their business model from a product-oriented approach to a connected device model.

Hi guys. Thanks for taking my question. First, I don't want to be pedantic, I suppose, but I guess on the Q1 guide, you say that gaming is the majority of the growth. Was that an absolute statement or was that a percentage statement? Can you give us some idea of how you'd sort of rank the sequential percentage growth of say gaming versus data center versus other, especially since it sounds like you've got 50 OEMs focusing on crypto-specific products that will go into the other? And then I guess just briefly, could you give us some indication of where your supply situation and lead times are on your Ampere parts within the data center? I think you said last quarter, they were many months on six months plus, are they still looking like that? And is that sort of a limiting factor at this point in terms of what you can actually ship on the compute side and data center?

Colette, you will take one and I'll take the one.

Sure. Let me start off Stacy in terms of our guidance for Q1. As you know, we're still in the early innings of our Ampere architecture. Both our Ampere architecture related to gaming and what it relates to data center have seen uplifting adoption. As we articulated in our call, we have been really seeing continued uplift in the adoption of A100 and it's going quite smoothly compared to what we had seen in prior overall versions. So when we think about our guidance for Q1, there are many different types of conclusions that will happen at the end of the quarter in terms of growth across all platforms. But the majority of the growth from Q4 to Q1 will likely be from gaming.

Thanks, Colette. You asked the question about normal time; at the company level, we are supply constrained as demand is greater than our supply. However, for data centers, as customers engage more closely with us, and we do a good job in planning, there shouldn't be a supply issue for data centers. We just need to do an excellent job in planning, and we have direct relationships with all the key players. We shouldn't have a supplier issue there. But at the company level, we're supply constrained. Demand exceeds supply, yet we have enough supply to achieve the outlook. We had that situation in Q4, and we expect that situation in Q1 and have enough supply to grow through the year. But we are supply constrained at the company level, and demand is significant. So we have to do a good job in planning. We have the world's best operations team. Our company has an exceptional operations team. We build the most complex products in the world, the most complex chips, packages, and systems. During Q4, they improved our cycle time, and we expect them to improve our cycle time again in Q1. We're lucky to have such a terrific operations team. During these times, it really proves to be beneficial. Overall, at the company level, we expect demand to be greater than supply, but we do have enough supply to meet our outlook, and we can sustain this within Q1 as well.

Hi, thanks. I had a question on crypto. I guess Jensen, I know that the CMP stuff and the software drivers that you're doing for the 3060 will help a lot, but I think there are four or five major cryptocurrencies moving or at least changing from a proof of work to proof of stake, which is going to be a lot less compute intensive. So I guess the question that I get a lot is how do you assess the degree to which that drives GPUs back into the secondary market? Is there any way to quantify that?

Yes. If you look at the recent hash rates, first of all, the transition is going to take some time. It can't happen overnight. People have to build trust in the new versions, and it takes a little bit of time, but I hope it does. I hope that proof of stake becomes predominant over time. I don’t have the optimism that it will be all proof of stake; I think that proof of work is a very legitimate way of securing the currency. In the beginning, while any currency builds its reputation, it likely needs proof of work to do so. I think proof of work will be around for a bit. We developed CMP for this very reason. We have different versions of our products for gaming, professional visualization, high-performance computing, and deep learning. It stands to reason that we should also create a different version for CMP. Our go-to-market strategy would be to address industrial miners directly – and that’s a great benefit to them, as they won’t have to chase around spot markets. It’s also a benefit to gamers who want to play games – and the game demand is really off the charts. The recent hash rate growth was really a result of several dynamics. The first dynamic is the install base. Most people thought that once the mining stopped, GPUs would come back into the aftermarket. Some people do that, but the vast majority do not keep them. The reason is that they believe in Ethereum and they are industrial miners; they keep GPUs for when profitability returns and they can kickstart their mining gear. We saw that happen in the latter part of last year when we noticed the hash rates starting to grow, primarily driven by reactivated mining capacity. It wasn't until earlier this year that we started to see a strong demand for our GPUs. There are different dynamics for demand these days coming from powerful ASICs and also some from our GPUs and other GPUs in the marketplace. I think this aspect will remain a part of our business, but it won't grow extremely large, regardless of what happens. When it starts to grow larger, more ASICs enter the market to meet demand. Conversely, if the market becomes smaller, it's harder for ASICs to sustain R&D. We expect this to be a small part of our business moving forward. One important thing to realize is that in the near term, due to the early stages of our Ampere ramp – just two quarters into a multi-year cycle – this is also the first time that we've completely revolutionized computer graphics. RTX using ray tracing is fundamentally different from virtualization in the past. The results have been spectacular. There is approximately a 200 million install base on desktops and 50 million in laptops. A large majority of them have yet to be upgraded – I believe it’s something like 50% of the install base has upgraded to RTX. Overall, there is a vast install base and it continues to grow. We aim to upgrade the next generation of computer graphics going forward.

Yes, guys. Thanks for letting me ask questions. I want to go back to data center. You've been very kind over the last couple of quarters to call out Mellanox both when it was a positive driver and when it was a headwind. I'm curious if there is anything notable around Mellanox versus core data center as you look into fiscal first quarter? Additionally, I'm interested in the key metric that many investors are looking for: when does the core data center business year-over-year growth start to reel in? Some of that is simply math as you’re comping hard compared to last year, but how should we interpret data center year-over-year growth in the context of a reopening trade or any sort of AI applications that are emerging?

We're expecting – Mellanox was down this last quarter. Our compute business grew double digits and more than offset the decline in Mellanox. We expect Q1 to be a growth quarter for Mellanox and this coming year to be quite an exciting growth year for Mellanox. The business is growing; ethernet is expanding for CSPs and it’s growing in InfiniBand for high-performance computing. Furthermore, the switch business grew 50% year-over-year. So, we are seeing excellent growth there. One of the new initiatives is the BlueField DPUs, which are used for virtualization in hyperscalers and for security. As you know quite well, the future of computing and cloud is multi-tenant, and there is no VPN front door to the cloud. Millions are using every aspect of computing, which means distributed firewalls are necessary. We expect our Mellanox networking business to grow very nicely this year, and we expect Q1 to be a great growth quarter not only for compute but also for Mellanox. In terms of compelling AI-driven applications, last year saw natural language understanding and the transformer model play a massive role. Currently, we’re seeing deep learning-based conversational AI expand with speech recognition and synthesis now also reliant on deep learning, elevating accuracy compared to conventional models. This burgeoning area indicates strong demand and growth for high-performance computing.

Yes. Thanks for taking the questions. I wanted to go back again on the data center business that you just mentioned, Jensen, which is that the BlueField-2 product is poised to ramp in the back half of the calendar year. How do you see that in terms of attach rate? There have been discussions in the past about – all servers could potentially over time incorporate this layer of acceleration. How quickly should we think about that ramp? And then the second question is, can you just at a high level talk about how CPU – how a CPU strategy is shaping up in the context of the broader data center market?

Sure. If I could just work backwards, I believe that every single data center node will be outfitted with a GPU someday. And that someday is probably in about five years from now. The fundamental driver is security. Every single application in the data center and every single node has to be secured individually; zero trust computing, or confidential computing. These initiatives are going to drive every data center to have every single application and every single node secured, which means each of those computers must have a control plane, isolated from the application plane. No application could access the control plane, as it could include malware or intrusions. Today, software-defined data centers, networking, and storage technologies run on the same processors as the applications. That hasn’t changed. I believe we are seeing cloud service providers moving in this direction; every data center must adapt. Thus, each node will have a DPU to facilitate software for the infrastructure. This represents our next multi-billion dollar opportunity. We support every CPU in the world, and we are the only accelerated computing platform enhanced for every CPU. The irony is that ARM is the only CPU we currently do not accelerate for AI, yet we would like to change that. ARM has an exciting future due to its business model and architecture's fit for the future of hyperscalers and data centers. Energy efficiencies are crucial as every data center is power constrained. We would love to work on our processor and build a thriving ecosystem around it, ensuring all systems and applications can work with any of the CPUs available today. We will start with high-performance computing and building around our expertise to create a robust platform. Many industry leaders have already embraced ARM, which I find terrific, but we need to energize it with broad ecosystem support. This cannot be confined to vertical applications alone; it must encompass a comprehensive ARM ecosystem.

Hi, thanks for taking my question. Jensen, if you look at past computing eras, typically, there’s one ecosystem that captures 80% of the value, such as mainframes with IBM, minicomputers with DEC, PCs with Wintel, and smartphones with Nokia and Apple. If you don't develop an ecosystem correctly, you are left splitting 20% with a handful of players. So in this next era of computing centered around parallel processing and AI, you’ve outlined a compelling architectural vision for future data centers with integrated CPUs, GPUs, and DPUs serving all workloads in a virtualized environment. Can you help us understand the market's position in adopting that vision and NVIDIA's role in building that ecosystem?

Yes. I believe we've done an excellent job building platforms for various ecosystems worldwide. We excel in expedited computing, having pioneered this approach. We started in high-performance computing, accelerating scientific computation and democratizing supercomputing for all researchers—now anyone can access supercomputing capabilities to enhance innovation. We replicated this success for artificial intelligence and visualization as well; we've expanded gaming tremendously. GeForce today is the largest gaming platform. The recent expansion of our market has helped us significantly. Our goal is to do the same for data center-scale computing as it applies to virtualizing these applications. Yet, they still require dedicated systems but slowly transition into a virtualized environment. We are best positioned to do that. Every application would be virtualized and hosted in data centers, making them readily available. We are currently in the process of creating this architecture and making it accessible to cloud service providers and OEMs, thereby establishing the accelerated computing platform for everyone. Our journey continues as we build an ecosystem around it.

Thanks for joining us today. Q4 has truly been a breakout year for NVIDIA. The two biggest engines of our business, gaming and data center, posted powerful growth. Gaming has become the world's largest media and entertainment industry, and will grow to be much larger. Our gamers will create, play, learn, and connect. The medium of gaming has the capacity to host any type of game and will eventually evolve into countless metaverses. Gaming serves as both a stellar technology and a significant driver of our business. This year, we also completed our Mellanox acquisition and successfully united the incredible talent of our companies. Together, we possess deep expertise in all aspects of computing and networking, driving modern data center architectures. Cloud computing and hyperscalers have transformed the data center into a new unit of computing. Chips on servers are just elements of data center-scale computers now. With our expertise in AI, accelerated computing, and our cloud-edge platforms, NVIDIA is helping to drive a vital transformation in the computing industry. Our planned acquisition of Arm, the world's most popular and energy-efficient CPU company, will position NVIDIA to lead in the age of AI. This year has been extraordinary. The pandemic will eventually pass, but the world has changed forever. Technology adoption is accelerating across every industry. Companies and products need to be more remote and autonomous. This will drive demand for data centers, AI, and robotics. This urgency to digitize, automate, and accelerate innovations has never been more pressing. We are ready. We look forward to updating you on our progress next quarter. Thanks a lot.