NVIDIA Corp (NVDA) — Q3 2020 Earnings Call Transcript

Thank you. Good afternoon, everyone, and welcome to NVIDIA's conference call for the third quarter of fiscal 2020. 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 fourth quarter of fiscal 2020. 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 Form 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, November 14, 2019, 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. Q3 revenue was $3.01 billion, down 5% year-on-year and up 17% sequentially. Starting with our gaming business. Revenue of $1.66 billion was down 6% year-on-year and up 26% sequentially. Results exceeded our expectations driven by strength in both desktop and notebook gaming. Our GeForce RTX lineup features the most advanced GPU for every price point and uniquely offers hardware-based ray tracing for cinematic graphics. While ray tracing launched a little more than a year ago, two dozen top titles have shipped with it or are on the way. Ray tracing is supported by all the major publishers, including all-star titles and franchises such as Minecraft, Call of Duty, Battlefield, Watch Dogs, Tomb Raider, Doom, Wolfenstein, and Cyberpunk. Of note, Call of Duty: Modern Warfare had a record-breaking launch in late October that came on the heels of CONTROL, an action-adventure game with multiple ray trace features. Reviews have praised both for their ray tracing implementation and gameplay performance. With last week's PC release of Red Dead Redemption 2, there is a strong gaming lineup for the holiday season, and our business reflects this growing excitement. RTX GPUs now drive more than two-thirds of our desktop gaming GPU revenue. Gaming laptops were a standout, driving strong sequential and year-on-year growth. This holiday season, our partners are addressing the growing demand for high-performance laptops for gamers, students, and prosumers by bringing more than 130 NVIDIA-powered gaming and studio laptop models to market. This includes many thin and light form factors enabled by our Max-Q technology, tripling the number of Max-Q laptops compared to last year. In late October, we announced the GeForce GTX 1660 Super and the 1650 Super, which refresh our mainstream desktop GPUs with more performance, faster memory, and new features. The 1660 Super delivers 50% more performance than our prior-generation Pascal-based 1060, the best-selling gaming GPU of all time. It began shipping on October 29, priced at just $229. PC World called it the best GPU you can buy for 1080p gaming. We also announced the next generation of our streaming media player with two new models, Shield TV and Shield TV Pro, which launched on October 28. These bring AI to the streaming market for the first time with the ability to upscale video in real-time from high definition to 4K using NVIDIA-trained deep neural networks. Shield TV has been widely recognized as the best streamer on the market. Finally, we made progress in building out our cloud gaming business. Two global service providers, Taiwan Mobile and Russia's Rostelecom with GFN.ru, joined SoftBank and Korea's LG as partners for our GeForce NOW game-streaming service. Additionally, Telefónica will kick off a cloud gaming proof-of-concept in Spain. Moving to the data center, revenue was $726 million, down 8% year-on-year and up 11% sequentially. Our hyperscale revenue grew both sequentially and year-on-year, and we believe our visibility is improving. Hyperscale activity is being driven by conversational AI, the ability for computers to engage in human-like dialogue, capturing context and providing intelligent responses. Google's breakthrough introduction of the BERT model, with its superhuman levels of natural language understanding, is driving a wave of neural networks for language understanding. That, in turn, is driving demand for our GPUs on two fronts. First, these models are massive and highly complex. They have 10 to 20 times, in some cases, 100 times more parameters than image-based models. As a result, training these models requires V100-based compute infrastructure that is an order of magnitude beyond what was needed in the past. Model complexity is expected to grow significantly from here. Second, real-time conversational AI requires very low latency and multiple neural networks running in quick succession, from de-noising to speech recognition, language understanding, text-to-speech, and voice encoding. While conventional approaches fail at these tasks, NVIDIA's GPUs can handle the entire inference chain in less than 30 milliseconds. This is the first AI application where inference requires acceleration. Conversational AI is a major driver for GPU-accelerated inference. In addition to this type of internal hyperscale activity, our T4 GPU continues to gain adoption in public clouds. In September, Amazon AWS announced the general availability of the T4 globally, following the T4 rollout on Google Cloud platform earlier in the year. We shipped a higher volume of T4 inference GPUs this quarter alongside V100 training GPUs, and both were records. Inference revenue more than doubled from last year and continued a solid double-digit percentage of total data center revenue. Last week, the results of the first industry benchmark for AI inference, MLPerf inference, were announced. We won. In addition to demonstrating the best performance among commercially available solutions for both data center and edge applications, NVIDIA accelerators were the only ones that completed all five MLPerf benchmarks. This demonstrates the programmability and performance of our computing platform across diverse AI workloads, which is critical for wide-scale data center deployment and is a key differentiator for us. Several product announcements this quarter helped extend our AI computing platform into new markets, the enterprise edge. At Mobile World Congress, Los Angeles, we announced a software-defined 5G wireless RAN solution accelerated by GPUs in collaboration with Ericsson. This opens up the wireless RAN market to NVIDIA GPUs. It enables new AI applications, as well as AR, VR, and gaming to be more accessible to the telco edge. We announced the NVIDIA EGX Intelligent Edge Computing Platform. With an ecosystem of more than 100 technology companies worldwide, early adopters include Walmart, BMW, Procter & Gamble, Samsung Electronics, NTT East, and the cities of San Francisco and Las Vegas. Additionally, we announced a collaboration with Microsoft on intelligent edge computing. This will help industries better manage and gain insights from the growing flood of data created by retail stores, warehouses, manufacturing facilities, and urban infrastructure. Finally, last week, we held our GPU Technology Conference in Washington, D.C., which was sold out with more than 3,500 registered developers, CIOs, and federal employees. At the event, we announced that the U.S. Postal Service, the world's largest delivery service with almost 150 billion pieces of mail delivered annually, is adopting AI technology from NVIDIA, enabling 10 times faster processing of package data and with higher accuracy. Moving to ProVis, revenue reached a record $324 million, up 6% from the prior year and up 11% sequentially, driven primarily by mobile workstations. NVIDIA RTX graphic and Max-Q technology have enabled a new wave of mobile workstations that are powerful enough for design applications yet thin and light enough to carry. We expect this to become a major new category with exciting growth opportunities. Over 40 top creative design applications are being accelerated with RTX GPUs. Just last week, at the Adobe Max Conference, RTX accelerated capabilities were added to three Adobe Creative apps. RTX-accelerated apps are now available to tens of millions of artists and designers, driving demand for our RTX GPUs. We also continue to see growing customer deployment of data science, AI, and VR applications. Strong demand this quarter came from manufacturing, public sector, higher education, and health care customers. Finally, turning to automotive, revenue was $162 million, down 6% from a year ago and down 22% sequentially. The sequential decline was driven by a one-time nonrecurring development services contract recognized in Q2. Additionally, we saw a roll-off of legacy infotainment revenue and general industry weakness. Our AI cockpit business grew driven by the continued ramp of Daimler as they deploy their AI-based infotainment systems across their fleet of Mercedes-Benz vehicles. In August, Optimus Ride launched New York City's first autonomous driving pilot program powered by NVIDIA DRIVE. Urban settings pose unique challenges for autonomous vehicles given the number and density of objects that need to be perceived and comprehended in real-time. Our DRIVE computer and software stack allows these shuttles to safely and effectively provide first- and last-mile transit services. We remain excited about the long-term opportunity in auto. Our offering consists of in-car AV computing platforms as well as GPU servers for all AI development and simulation. We believe we are well positioned in the industry with a leading end-to-end platform that enables customers to develop, test, and safely operate autonomous vehicles, ranging from cars and trucks to shuttles and robo-taxis. Moving to the rest of the P&L, Q3 GAAP gross margins were 63.6%, and non-GAAP was 64.1%, up sequentially, reflecting a benefit from sales of previously written-off inventory, higher GeForce GPUs' average selling prices, and lower component costs. GAAP operating expenses were $989 million, and non-GAAP operating expenses were $774 million, up 15% and 6% year-on-year, respectively. GAAP EPS was $1.45, down 26% from a year earlier. Non-GAAP EPS was $1.78, down 3% from a year ago. Cash flow from operations was a record $1.6 billion. With that, let me turn to the outlook for the fourth quarter of fiscal 2020, which does not include any contribution from the pending acquisition of Mellanox. We expect revenue to be $2.95 billion, plus or minus 2%. This reflects expectations for strong sequential growth in data center, offset by a seasonal decline in notebook GPUs for gaming and Switch-related revenue. GAAP and non-GAAP gross margins are expected to be 64.1% and 64.5%, respectively, plus or minus 50 basis points. GAAP and non-GAAP operating expenses are expected to be approximately $1.02 billion and $805 million, respectively. GAAP and non-GAAP OI&E are both expected to be income of approximately $25 million. GAAP and non-GAAP tax rates are both expected to be 9%, plus or minus 1%, excluding discrete items. Capital expenditures are expected to be approximately $130 million to $150 million. Further financial details are included in the CFO commentary and other information available on our IR website. In closing, let me highlight the upcoming events for the financial community. We will be at the Crédit Suisse Annual Technology Conference on December 3, Deutsche Bank's Auto Tech Conference on December 10, and Barclays Global Technology, Media and Telecommunications Conference on December 11.

For my first one, you mentioned that you were seeing strong sequential growth in the data center going into Q4. Jensen, I was wondering if you could give us some color on what's driving that and just how you think about the sustainability of data center growth going into next year and what markets do you think will drive that. Is it more enterprise, more hyperscale, more HPC? Just some color on near and longer term on data center. And then I have a follow-up for Colette.

Yes. Thanks a lot, Vivek. We had a strong Q3 in hyperscale data centers. As Colette mentioned earlier, we shipped a record number of V100s and T4s. For the very first time, we shipped more T4s than V100s. Most of the T4s are driven by inference. In fact, our inference business is now a solid double-digit percentage and it doubled year-over-year. That is really driven by several factors. As you know, we've been working on deep learning for some time, and people have been developing deep learning models. It started with computer vision. However, image recognition doesn't require that much of the data center capacity. Over the last couple of years, a couple of very important developments have happened. One development is a breakthrough in using deep learning for recommendation systems. Recommendation systems are the backbone of the Internet. Whenever you shop, watch movies, look at news, and perform searches, all personalized web pages, all of your entire experience on the Internet is made possible by recommendation systems. There is just so much data out there putting the right data in front of you based on your social profile, personal use patterns, interests, or connections, all of that is vitally important. For the very first time, we're seeing recommendation systems based on deep learning throughout the world. So increasingly, you're going to see people roll this out. The backbone of the Internet is now going to be based on deep learning. The second part is conversational AI. Conversational AI has been coming together in pieces. At first, speech recognition required some amount of noise processing or beamforming. Then you go into speech recognition, followed by natural language understanding, which then connects to a recommendation system, which then connects to text-to-speech and a speech encoder. This has to be done in real-time. While images could be processed offline, conversation has to be done in real-time. Without acceleration and without NVIDIA's accelerators, it is really not possible to do it in real time. It used to take seconds to process those handful of deep learning models, but now, we're able to do that efficiently on our accelerator in real time. The combination of these various breakthroughs from deep learning-based recommenders, the speech stack, as well as natural language understanding, is quite significant. Since then, derivative works have emerged from that approach. Natural language understanding is performing incredibly well. We’re seeing hyperscalers around the world adopting these technologies. This area of work is complicated, with large models that continue to grow. That's one large category: hyperscalers. The second, which we introduced this quarter, is taking AI out to the edge. Many applications, whether they involve video or sensors, require real-time processing at the point of action. Low latency matters. If you’re controlling gates, vehicles, or drones, it has to happen immediately. One issue is data sovereignty. Your company may not own all of the data you're processing, and therefore you must do that processing at the edge, and you can't afford to send it to the cloud. Industries like retail, warehouse, logistics, and smart cities are showing enthusiasm around this. We built a platform called the EGX, which is cloud-native, completely secure, and utilizes NVIDIA's full-stack capabilities. We've seen great adoption. Walmart is using our platform, BMW is for logistics, Procter & Gamble for manufacturing, Samsung Electronics for manufacturing, and visual inspection. Last week, we announced probably the largest logistics operation in the world, the United States Postal Service. These various industries—retail, logistics, and transportation—open new opportunities that could save an immense amount of money.

Right. And Jensen, as a quick follow-up, on PC gaming, how are you looking at growth going forward in that you had a very good quarter in October? I think in January, you're probably guiding to some seasonal declines, but I imagine a lot more of that is due to console decline. Just how are you looking at PC gaming growth going into January and then next year as you get competition from two new consoles that are also supposed to come out?

Yes. During Q4 and Q1, we see normal seasonal declines of console builds, and we also see a normal seasonal decline of notebook builds. The notebook vendors have to line up all their manufacturing in Q3 to meet the hot selling season in Q4. So what we see in the Q4 and Q1 timeframe are just normal seasonal declines for these systems. Overall, for PC gaming—RTX is doing fantastic. I think it's fairly clear that ray tracing is the future and that RTX is a home run. Just about every major game developer has signed on to ray tracing. Even the next-generation consoles have included ray tracing in their design. The photorealistic look of ray tracing is so compelling that it's hard to go back. We have several hundred million PC gamers in the world who still need to upgrade to RTX and ray tracing technology. Notebook PC gaming is another exciting area for growth. Our second-generation Max-Q innovations have turbocharged this segment, leading to over 100 new laptops available for PC gaming. It’s likely going to become the largest new gaming platform that will emerge. Upgrading the installed base of gamers to RTX and establishing notebook PC gaming is quite exciting and will drive our continued growth for the foreseeable future.

I have a follow-up if I can as well. Just thinking about the trajectory of gross margin here, solid gross margin upside in the quarter. You also noted that you had the benefit of selling through some written-off components. So I guess first question is what was that impact in this most recent reported quarter? And how do we think about the trajectory of gross margin here even beyond the January quarter? What should we be thinking about in terms of that gross margin trend? And again, I have a quick follow-up.

Sure. Thanks for the question. In the current quarter, the net benefit, which we refer to as the net release of our inventory provisions primarily associated with our components, was about 1 percentage point to our overall gross margin. As you know, going forward, mix is still the largest driver of our gross margin over time. Over the long term, we do expect gross margins to improve, and we'll continue to see, outside of the benefit that we received, gross margin improvement for the long term.

Yes. To add to that, NVIDIA has really become a software company. If you take a look at almost all of our products, the GPU—having the world's best GPU, of course, is the starting point. But almost everything we do, whether it's in artificial intelligence, data analytics, healthcare, robotics, or self-driving cars, starts from a rich stack of software. You cannot just put a chip in these scenarios and expect it to work. Most of our businesses are now highly software-intense and focus on vertical markets. We are also a platform company. Our platform is available from all the OEMs and cloud providers. As a platform company with a great deal of software intensity, it's natural that our margins will be higher over time.

Yes. Very helpful. And then you mentioned that you've seen hyperscale—your hyperscale business within the data center grow both quarter-over-quarter and year-over-year in this last print. You also mentioned that your visibility is improving. Can you just help us understand what exactly you're seeing in the hyperscale market? It feels like there are some mixed data points out there? What underpins your improved visibility? Or what are you seeing in that piece of your business?

Yes. We had a strong Q3. We're going to see an even stronger Q4. The foundation of that is AI, specifically deep learning inference. This area is expected to be one of the largest computer industry opportunities, primarily due to computation intensity. Aside from computer graphics, this mode of software wouldn't be practical without accelerators. I mentioned earlier the large-scale movement to deep learning recommendation systems. Those models are intricate and hard to train. Conversational AI represents a challenging domain, as real-time processing is a necessity. After years of labor, those workloads are now moving into production. I am optimistic and looking forward to what's to come.

I guess I'd love to follow on that last question. So clearly, your commentary, Jensen, here is much more bullish than I've heard you, I think, before on inference, particularly as it relates to this first benchmark. Can you talk a bit about how you see mix within data center looking out over the next 12 to 24 months as you see kind of training versus inference as well as cloud versus enterprise, considering that inference over time could be a large opportunity there?

Yes. C.J., that's a great question. When we think about hyperscale, there are three components: training, inference, and public cloud. Training, as you may have seen, has recently been monitored with advances in computation necessary for training large models. These models are getting larger at an increasing rate. Training computations are now doubling every three months. The rise of natural language understanding marks a watershed moment. We expect to see significant installations of GPU systems for this purpose. The inference segment remains an untapped market for us, far larger than anticipated. Our recent success in MLPerf demonstrates the high complexity of inference challenges and our capabilities to address them. As AI companies proliferate, we continue to see high growth in our public cloud and AI start-ups, which represents a major opportunity for us. Establishing intelligent edge networks is promising. Our EGX platform offers secure cloud-native capabilities that have seen traction with numerous early adopters.

There are a lot of concerns around China trade tensions and economic slowdown. History has shown that gamers tend to be less sensitive to these macro trends and, in fact, also somewhat insensitive to price changes, at least at the enthusiast level. Given that China is such a big part of the gaming segment, can you just discuss the gaming demand trends out of this geography?

Gaming is solid in China, and it is the fastest adopter of our gaming notebooks. The RTX notebooks or GeForce notebooks is a brand new category. This category never existed before because we couldn't encapsulate the technology to ensure it was exceptionally enjoyable to own. We saw great success with RTX and GeForce notebooks in China, and RTX adoption has accelerated. Most games today are free-to-play, and the primary games are esports, where gear matters immensely, as well as mobile gaming that is largely free-to-play. One area we've excelled in, especially in China, is social. Our platform called GeForce Experience includes several features that enhance social sharing and content creation through AI.

I wanted to ask on automotive. Colette, in your prepared remarks, you talked about your legacy infotainment business being down in the quarter. Just curious, what percentage of automotive revenue at this point is legacy infotainment versus the newer AI/ADAS solutions? And more importantly, Jensen, if you can speak to the growth trajectory in automotive over the next 1.5 to 2 years, that would be appreciated. I do ask the question because it feels like we've heard many, many customer announcements and collaborations yet we haven't quite seen a hockey-stick inflection that some of us were expecting a couple of years ago. So just curious how we should set our expectations going forward.

Yes, Toshiya. Regarding our legacy infotainment systems in the automotive business, they still represent about half or more of our overall revenue in the automotive segment. Our AI cockpit solutions are developing well both sequentially and year-over-year, notably in AI-based infotainment systems.

We remain on track to deploy our autonomous vehicles. In fact, the Volvo is probable to be the first passenger-owned vehicle on the road powered by us, with expectations for deployment in late 2020 or early 2021. The development of passenger-owned vehicles remains solid, while robot taxis are progressing across the globe. We work with major companies in the autonomous vehicle space and are very pleased with their progress. Additionally, we focus on trucks, shuttles, and non-passenger vehicles. We're continuously developing logistics solutions and have announced major collaborations for grocery and goods delivery. Advanced capabilities will eventually be integrated throughout every vehicle. Our strategy encompasses in-car AV computing systems as well as AI development and simulation systems.

I have two data center questions for Colette. The first question, I want to return to your outlook for strong sequential data center growth in Q4. Now this business grew 11% sequentially in Q3, and you didn't call out strong growth as we were going into the quarter. You are calling it out for Q4. Does that suggest to me that you expect sequential growth in Q4 to be stronger than Q3 given you're calling it out in Q4 and you didn't call it out in Q3? Or would you define what you saw in Q3 as already being strong sequential growth?

Sure, Stacy. When we provided guidance in Q3 and how we finished that quarter, we indicated that our growth would stem from both gaming and data center, which we completed. We experienced stronger-than-expected results in both segments during Q3. Moving to Q4, it is a sequential decrease in totality versus Q3, hence the need for emphasis on data center. We are expecting strong growth there.

So to ask the question again, would you define what you saw in Q3 as being strong growth as well?

I would believe our growth of 17% was higher than we expected for Q3. Again, when we get into Q4, we'll see how the quarter concludes, but we do anticipate strong data center growth. Thank you, Stacy.

Your next question comes from the line of Mitch Steves with RBC.

I apologize for any background noise, but I just have one question for Jensen. Given what was in 2018, can you give us a rough update on what the GPU utilization was for deep learning applications? What it is today? I'm just wondering how that has advanced over the last couple of years.

Let's see. I would say in 2018, it was nearly all related to training. This year, we've started to see the growth of inference to the point where we sold more T4 GPUs for inference than V100s used for training, and both were record highs. The previous year comparison of the deep learning systems is influenced by a large DGX system sale that we don't have this year. Without that, both the V100s and T4s are performing greatly at record levels. The inference segment is taking off, and I expect continued growth in that area.

I wonder if you could talk a little bit more about the 5G opportunity that you announced at Mobile World. You spoke about AI and IoT services in a C-RAN environment. But how big is that opportunity? And can you address the core compute aspect to C-RAN with the GPU?

Yes. If you look at the world of mobile today, there are players building DRAMs and their radio heads in the baseband units. In the data center, moving the software for radio networks is an untapped market. The CPU cannot support the level of performance needed for 5G, while ASICs are too rigid for data centers. We need a programmable solution that fits into a data center environment. We're creating a software stack for 5G, called Aerial, which will allow us to run the entire 5G stack in software and deliver the highest performance with incredible flexibility. Our strategy is to create a new world of C-RAN, vRAN, and software-defined networking. The low latency capability of 5G allows you to shift traffic computation among regional data centers, resulting in cost reduction. Telcos see value in leveraging data center compute at the edge for AI and IoT applications, ensuring that we continue to create robust partnerships.

I apologize for the background noise. But Colette, maybe you could give us an idea of gaming. In the guidance, it's down. I was wondering if you could give us the impact of the console business versus the laptop business, and give us an idea of what might be the bigger driver there.

For Q4, I would say both are expected to be seasonally down. In the case of the consoles, we will have to wait for Nintendo to assist in terms of what they need. But in both cases, in totality, these businesses have ranged, maybe over the two, about $500 million in a quarter. We'll see both of them decline sequentially. Thank you.

Thanks, everyone. We had a good quarter driven by strong gaming growth and hyperscale demand. We're making great strides in three big impact initiatives: The world of computer graphics is moving to ray tracing, and our business reflects that. Some of the biggest blockbuster games this holiday season and beyond are RTX-enabled, including Call of Duty: Modern Warfare and the best-selling game of all time, Minecraft. Design applications used by millions of artists and creators are rapidly adopting RTX ray tracing. We're reinventing computer graphics and look forward to upgrading the hundreds of millions of PC gamers to RTX. Hyperscale demand was strong this quarter, and our visibility continues to improve. The race is on for conversational AI, which will be a powerful catalyst for us in both training and inference. Lastly, we have extended our computing platform beyond the cloud to the edge, where GPU-accelerated 5G, AI, and IoT will revolutionize the world's largest industries. We look forward to updating you on our progress in February.