NVIDIA Corp (NVDA) — Q2 2022 Earnings Call Transcript

Thanks, Simona. Q2 was another strong quarter with revenue of $6.5 billion and year-on-year growth of 68%. We set records for total revenue, as well as for gaming, data center, and professional visualization. Starting with gaming, revenue was $3.1 billion, which was up 11% sequentially, and up 85% from a year earlier. Demand remained exceptionally strong, outpacing supply. We are now four quarters into the Ampere architecture product cycle for gaming, and it continues to be our best effort. At COMPUTEX in June, we announced two powerful new GPUs for gamers and creators, the GeForce RTX 3080 Ti, and RTX 3070 Ti, delivering 50% faster performance than their prior generation with acclaimed features, such as real-time ray tracing, NVIDIA DLSS, AI rendering, Reflex, and broadcast. Laptop demand was also very strong. OEMs adopted Ampere architecture GPUs in a record number of designs. From the top of the line gaming laptops to those at mainstream price points as low as $799 that bring the power of GeForce GPUs to gamers, students, and creators on the go. Ampere architecture-powered laptops feature our third generation Max-Q power optimization technology that enables ultrathin designs, such as the new Alienware X15, the world's most powerful sub-16-millimeter gaming laptop. NVIDIA RTX technology has reset computer graphics and spurred our biggest ever refresh cycle. Ampere has been our fastest ramping gaming GPU architecture on Steam. And the combination of Turing and Ampere RTX GPUs has upgraded about 20% of our installed base. 80% have yet to upgrade to RTX. And the audience for global esports will soon approach 0.5 billion people, while the number of those who livestream games is expected to reach over 700 million. The number of PC gamers on Steam is up almost 20% over the past year. More than 60 RTX games now support NVIDIA's RTX ray tracing or DLSS, including today's biggest game franchises, such as Minecraft, Fortnite, and Cyberpunk. New RTX games this quarter include Red Dead Redemption 2, one of the top-rated games of all time, popular titles like Rainbow Six Siege and Minecraft RTX in China with over 400 million players. To competitive gamers, NVIDIA Reflex, which includes latency reduction, is now supported by 20 games. Let me say a few words on cryptocurrency mining. In an effort to address the needs of miners and direct GeForce to gamers, we increased the supply of cryptocurrency Mining Processors, or CMP, and introduced low hash rate GeForce GPUs with limited Ethereum mining capability. Over 80% of our Ampere architecture base GeForce shipments in the quarter were low hash rate GPUs. The combination of cryptocurrency to gaming revenue is difficult to quantify. CMP revenue, which is recognized in OEM, was $266 million, lower than our original $400 million estimates on reduced mining profitability, and we expect a minimal contribution from CMP going forward. GeForce NOW reached a new milestone this quarter, surpassing 1,000 PC games, more than any other cloud gaming service. The premium tier is available for a subscription of $10 per month, giving gamers access to RTX class performance, even on an underpowered PC, Mac, Chromebook, iOS, or Android device. Moving to pro visualization. Q2 revenue was a record $519 million, up 40% sequentially, and up 156% year-on-year. Strong sequential revenue growth was led by desktop workstations, driven by demand to outfit home design offices as remote work becomes the norm across industries. This is also the first big quarter of the Ampere architecture ramp for pro visualization. Key verticals driving Q2 demand include automotive, public sector, and healthcare. At SIGGRAPH last week, we announced an expansion of NVIDIA Omniverse, our simulation and collaboration platform that provides the foundation of the Metaverse. Through new integrations with Blender, the world's leading open-source 3D animation tool, and Adobe, we're opening the Omniverse platform to millions of additional users. We are also collaborating with Apple and Pixar to bring advanced physics capabilities to Pixar's Universal Scene Description framework, embracing open standards to provide 3D workflows to billions of devices. Omniverse enterprise software is in the early access stage and will be generally available later this year on a subscription basis from NVIDIA's partners, including Dell, HP, Lenovo, and many others. Over 500 companies are evaluating Omniverse Enterprise, including BMW, Volvo, and Lockheed Martin. And more than 50,000 individual creators have downloaded Omniverse since it entered open beta in December. Moving to automotive. Our Q2 revenue was $152 million, down 1% sequentially, and up 3% year-on-year. Sequential revenue declines in infotainment were largely offset by growth in self-driving. Looking further out, we have substantial design wins set to ramp that we expect will drive a major inflection in revenue in the coming years. This quarter, we announced several additional wins. Self-driving startup AutoX unveiled its latest autonomous driving platform for RoboTaxis powered by NVIDIA DRIVE. The performance and safety capabilities of the software-defined NVIDIA DRIVE platform have enabled AutoX to become one of the first companies in the world to provide full self-driving mobility services without the need for a safety driver. In autonomous trucking, DRIVE's ecosystem partner, Plus, signed a deal with Amazon to provide at least 1,000 self-driving systems to Amazon's fleet of delivery vehicles. These systems are powered by NVIDIA DRIVE for high-performance, energy-efficient, and centralized AI compute. An autonomous trucking startup Embark is building on NVIDIA DRIVE. The system is being developed for trucks for four major OEMs: Freightliner, Navistar International, PACCAR, and Volvo, representing the vast majority of class 8 or largest size trucks in the U.S. The NVIDIA DRIVE platform is being rapidly adopted across the transportation industry from passenger-owned vehicles to robotaxis to trucking and delivery vehicles. We believe everything that moves will be autonomous someday. Moving to Data Center. Revenue of $2.4 billion grew 16% sequentially, and 35% from the year-ago quarter. The year-ago quarter, which was our first quarter to include Mellanox. Growth was driven by both hyperscale customers and vertical industries, each of which has record revenues. Our flagship A100 is continuing to ramp across hyperscale and cloud computing customers, with Microsoft Azure announcing general availability in June, following AWS and Google Cloud Platforms' general availability in prior quarters. Vertical industry demand was strong, with sequential growth led by financial services, supercomputing, and telecom customers. We also had exceptional growth in Inference, which reached a record, more than doubling year-on-year. Revenue from inference-focused processors includes the new A30 GPU, which provides four times the inference performance of the T4. Customers are also turning to NVIDIA GPUs to take AI to production and shifting from CPUs to GPUs, driven by the stringent performance, latency, and cost requirements of deploying and scaling deep learning AI workloads, and NVIDIA Networking products posted solid results. We see momentum across regions driven by our technology leadership with upgrades to high-speed products, such as ConnectX-6, as well as new customer wins across cloud service providers, enterprise, and high-performance computing. We extended our leadership in supercomputing. The latest top 500 list shows that NVIDIA technologies power 342 of the world's top 500 supercomputers, including 70% of all new systems and eight of the top 10, helping companies harness the new industrial high-performance computing revolution. We deliver a turnkey AI Data Center solution with the NVIDIA DGX SuperPOD, the same technology that powers our new Cambridge-1 supercomputer in the UK and a number of others in the top 500. We expanded our AI software and subscription offerings, making it easier for enterprises to adopt AIs from the initial development stage through to deployment and operations. We announced NVIDIA Base Command, our software-as-a-service offering for operating and managing large-scale, multi-user, and multi-team AI development workloads on DGX SuperPOD. Base Command is the operating and management system software for distributed training customers. We also announced the general availability of NVIDIA Fleet Command, our managed edge AI software-as-a-service offering. Fleet Command helps companies solve the problem of securely deploying and managing AI applications across thousands of remote locations, combining the efficiency and simplicity of central management with the cost performance and data sovereignty benefits of real-time processing at the edge. Early adopters of Fleet Command include some of the world's leading retail, manufacturing, and logistics companies and the specialty software companies that work with them. The new NVIDIA Base Command and Fleet Command software and subscription offerings followed last quarter's announcements of the NVIDIA AI Enterprise software suite, which is in early access with general availability expected soon. Our enterprise software strategy is supported by the NVIDIA certified system program with server OEMs, who are bringing to market over 55 systems ready to run on NVIDIA's AI software out of the box to help enterprises simplify and accelerate their AI deployment. The NVIDIA ecosystem keeps getting stronger. NVIDIA Inception, our acceleration platform for AI startups, just surpassed 8,500 members with cumulative funding of over $60 billion, with numbers in 90 countries. Inception is one of the largest AI startup ecosystems in the world. CUDA has now been downloaded 27 million times since it launched 15 years ago, with 7 million in the last year alone. TensorRT for inference has been downloaded nearly 2.5 million times across more than 27,000 companies. And the total number of developers in the NVIDIA ecosystem now exceeds 2.6 million, up four times in the past four years. Let me give you a quick update on Arm. In nearly one year since we initially agreed to combine with Arm, we have gotten to know the company, its business, and its people much better. We believe more than ever in the power of our combination, and the benefits it would deliver for Arm, for the UK, and its customers across the world in the era of AI. Arm has great potential. We appreciate their business model and commit to keeping its open licensing approach. With NVIDIA's scale and capabilities, Arm will make more IP, and sooner, for their mobile and embedded customers while expanding into Data Center, IoT, and other new markets. NVIDIA accelerates computing, which starts with the CPU. Whatever new markets open with the CPU and our accelerated computing opportunities. We've announced accelerated platforms for Amazon Graviton, Ampere Computing, MediaTek, and more about expanding cloud computing, AI, cloud gaming, Supercomputing, and Edge AI to Chrome PCs. We plan to invest in the U.K., and we have with the Cambridge-1 supercomputer. Through ARM we are making the U.K. a global center in science, technology, and AI. We are working through the regulatory process, although some Arm licensees have expressed concerns and objected to the transaction, and discussions with regulators are taking longer than initially thought. We are confident in the deal and that regulators should recognize the benefits of the acquisition to Arm, its licensees, and the industry. Moving to the rest of the P&L, the GAAP gross margin of 64.8% for the second quarter was up 600 basis points from the year earlier, reflecting the absence of certain Mellanox acquisition-related costs. GAAP gross margins were up 70 basis points sequentially, non-GAAP gross margins were 66.7%, up 70 basis points from a year earlier and up 50 basis points sequentially, reflecting higher ASPs within the desktop GPUs, our continued growth in high end and pure architecture products, partially offset by a mix shift within Data Center. Q2 GAAP EPS was $0.94, up 276% from a year earlier. Non-GAAP EPS was $1.04, up 89% from the year-earlier, adjusting for the 4 to 1 stock split effective this quarter. Q2 cash flow from operations was a record $2.7 billion. Let me turn to the outlook for the Third Quarter of Fiscal 2022. We expect another strong quarter with sequential growth driven largely by accelerating demand in Data Center. In addition, we expect sequential growth in each of our three other market platforms. Gaming demand is continuing to exceed supply as we expect channel inventories to remain below target levels as we exit Q3. The contribution of CMP to our revenue outlook is minimal. Revenue is expected to be $6.8 billion plus or minus 2%, GAAP and non-GAAP gross margins are expected to be 65.2% and 67%, respectively, plus or minus 50 basis points. GAAP and non-GAAP operating expenses are expected to be approximately $1.96 billion and $1.37 billion, respectively. GAAP and non-GAAP other income and expenses are both expected to be an expense of approximately $60 million, excluding gains and losses on equity securities. GAAP and non-GAAP tax rates are expected to be approximately 11%, plus or minus 1%, excluding discrete items. Capital expenditures are expected to be approximately $200 million to $225 million. Further financial details are included in the CFO commentary and other information available on our IR website. In closing, let me highlight upcoming events for the financial community. We will be attending the following virtual events: The BMO Technology Summit on August 24th, the New Street Big Ideas in Semiconductors Conference on September 9th, the Citi Global Tech Conference on September 13, the Piper Sandler Global Technology Conference on September 14th, and the Evercore ISI Auto Check and AI Forum on September 21st. Our earnings call to discuss the third-quarter results is scheduled for Wednesday, November 17th.

Thanks for taking my question. I actually had a near and longer-term question on the data center. I think near-term you mentioned the possibility of accelerating data center growth from the 35% rate. I was hoping if you could give us some more color around that confidence and visibility. And then longer-term, Jensen, we've seen a lot of announcements from NVIDIA about your Enterprise software opportunity. I honestly don't know how to model that. It sounds very promising, but how should we model it? What problem are you trying to solve? Is it cannibalizing demand you might have otherwise seen from your public Cloud customers, or is this incremental to growth? So just any guidance or any insights into how to think about NVIDIA's Enterprise software opportunity longer-term? Thank you.

Yes, thanks for the question. We are seeing accelerated growth, as we've already reported that we have record revenues in both hyperscale cloud and industrial enterprise this last quarter. And we're seeing accelerated growth. The exploration in hyperscale and cloud comes from the transitioning of the cloud service providers in taking their AI applications, which are now heavily deep learning-driven into production. There were some things that we've spoken about in the past that make Vinny the ideal partner to scale up with. And there are several elements of our platform. Number one, Ampere GPU, which is now a universal GPU for AI, for training, but incredibly efficient for inference; its throughput is terrific, and it's a fast response client as well. Therefore, the cost of deployment and the cost of operating the AI applications is the lowest. The second is the introduction of TensorRT, which is our optimizing compiler that makes it possible for us to compile and optimize any AI application to our GPUs. Whether it's computer vision or natural language understanding or conversational AI or recommender systems, the types of applications that are deploying AIs are really quite vast. And then lastly, this software Inference server that we offer is called Triton, which supports every one of our GPUs. It supports CPUs as well as GPUs still. So every internet service provider could operate their entire data center using Triton. These several things are really accelerating our growth. So the first element is the deployment and transition of deep learning AI applications into large-scale deployment. In the Enterprise, every enterprise wants to become a tech company and take advantage of connected clouds, connected devices, and artificial intelligence to achieve it. They have an opportunity to deploy AI services at the edge. To do so, several things must happen. First, we must create a computing platform that allows them to do training in the IT environment that they understand, which is virtualized, and is largely managed by VMware. Our collaboration with VMware, creating a new type of system that could be integrated into the Enterprise is a significant effort, and it's in volume production today. Secondly, a server that allows enterprise customers to deploy their AI models to the edge. The AI engine, the software suite that we've been developing over the last 10 years, is now integrated into this environment and allows enterprises to run AI at scale. There are three elements of our product there. For instance, NVIDIA AI Enterprise basically puts all the state-of-the-art AI solvers and engines and libraries that we've industrialized and perfected over the years for Enterprise licensing. The second is an operating system platform called Base Command that allows for distributed software development for training and developing models, and then the third is Fleet Command, which is an operating system software product that lets you operate, deploy, and manage AI models at the edge. These three software products, in combination with the server called NVIDIA Certified, taken out through our network of partners is our strategy to accelerate AI adoption by Enterprise customers. We are enthusiastic about entering into the software business model. This is an opportunity that could represent tens of millions of servers, which we could link with GPU acceleration, and we believe that Enterprises will deploy AI to revolutionize the industry. Using a traditional enterprise software licensing business model, this could represent billions of dollars of profits.

Hi, everyone. Thank you for taking my questions. I wanted to revisit the sequential guidance you provided, offering some insights by segments. I've been reviewing your gaming revenues, which have seen a consistent increase of about 10% or 11% for three consecutive quarters. My understanding is that this is due to your ability to secure supply. Can you explain what the supply situation looks like as you transition from Q2 to Q3? Do you believe you can maintain that level of sequential growth, or will it decrease? I also need to consider your other comments indicating that sequential growth, presumably in dollar terms, will primarily be driven by Data Center. How should I interpret the relationship between your comments on the sequential growth of gaming, especially in light of the trends observed over the last few quarters?

Yeah. Let me start and I'll let Jensen add a bit, Stacy, to your question. I guess we're providing the guidance for Q3 of $6.8 billion in revenue. Now excluding CMP, we expect our revenue to grow over $500 million sequentially. A lion's share of that sequential revenue increase will be coming from Data Center. We do expect gaming to be up slightly on a sequential basis, but remember we are still supply constrained. Automotive and Pro visualization are also expected to be up slightly quarter-over-quarter. From the CMP perspective, we'll probably just have minimal amounts in Q3. So our Q3 results don't have seasonality with them for gaming and are really about the supply that we believe we can have for Q3. I'll see if Jensen wants to add any more details.

Yes, thanks for your questions. As you know, RTX is a fundamental recap of computer graphics. This technology called ray tracing has been the holy grail of computer graphics for quite a long time, and with our NVIDIA research for 10 years, we finally made it possible to do real-time ray tracing with RTX. RTX's demand is quite incredible, and as you know, we have a large install base that uses an architecture called GTX based on programmable shaders that we invented some 20 years ago. Now, we've reset the entire installed base, and Ampere is off to an incredible start, the best-selling GPU architecture in the history of our company. Yet, we've only upgraded some 20% - less than 20% of our total installed base still. There's another 80% of the world's PC gaming market that we have yet to upgrade to RTX. Meanwhile, the number of PC gamers in the world grew substantially. Steam grew 20% this last year. So I think we're right at the beginning of our RTX transition. Meanwhile, computer graphics has expanded into so many different new markets. RTX, we've always believed, would reinvent the way people do design, and we're seeing that happening right now as we speak. Workstations are growing faster than ever and have achieved record revenues. Because of all our work with cloud gaming, we now see public clouds putting in cloud graphics, whether it's workstations or PCs or private gaming consoles up in the Cloud. So we're seeing strong demand in PCs, laptops, workstations, and mobile workstations in the cloud. RTX has been doing really great. Our challenge there is that demand is so much greater than supply.

Yes. Thank you very much. Good afternoon, everybody. Before my questions, Jensen, I just wanted to say congrats on the Noyce Award, that's a big honor. For my question, I wanted to follow on Stacy's question about supply. Colette, maybe you could give us a little bit of commentary around supply constraints in gaming in the different tiers or price tiers of your gaming cards. I'm just trying to get a better understanding of how you guys are managing supply across the different price tiers. I guess it translates into a question of, are the gaming ASPs that we're seeing in the October quarter guidance, are those what you would call sustainable going forward, or do you feel like that mix may change as supply comes online? Thank you.

I'll start here. Thanks for the question on our overall mix as we go forward. First, our supply constraint in our gaming business is largely attributed to our desktop and notebook products. That can mean a lot of different factors, including the components that are necessary to build our products. Our mix is really important. Many gamers are very interested in our higher-end, higher performance products. We will continue to see that as a driver for overall lifts in both our revenue and overall gross margins. There are quite a few different considerations regarding our supply that we need to think about, but we are going to try and make the best solutions for our gamers at this time.

Yes, thank you. Good afternoon. I guess a follow-up question on the supply constraints. When do you think that they'll ease? And how should we think about gaming into the January quarter vis-a-vis typical seasonality, given that I would assume you would continue to be supply constrained? Thank you.

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

Go ahead, Jensen, and I'll follow up if there are some other points to address.

We're supply constrained in graphics while we're delivering record revenues in graphics. Cloud gaming is growing, and cloud graphics is growing. RTX has made it possible for us to address the design in the creative workstations. Historically, the rendering of ray tracing and photorealistic images have largely been done on CPUs; for the very first time, this can be accelerated with NVIDIA GPUs and with RTX GPUs. The workstation market is really doing great. The backdrop of that, of course, is that people are building offices in their homes. For many designers and creators, they have to create a workstation or an office at home as well as one at work. RTX has changed that landscape significantly. Meanwhile, RTX has reached all our consumer graphics with a 200 million installed base of PC gamers, and it's time to upgrade. We expect to have enough supply to meet our second-half Company growth plans and to achieve our growth plans for next year. Meanwhile, we're securing significant long-term supply commitments to expand into our different marketing initiatives. Therefore, I would expect that we will see a supply-constrained environment for the vast majority of next year. A lot of that has to do with our overwhelming demand.

Good afternoon and congratulations on the strong results, outlook, and execution. The Mellanox networking franchise has been a really strong and synergistic addition to the video compute portfolio. I think near to midterm, the team is benefiting from the transition to 200 and 400-gig networking connectivity and Cloud and Hyperscale. In addition, you guys are getting some good traction with the Bluefield smart tech products. Can you just give us a sense of how the business is trending year-over-year, and do you expect continued quarter-over-quarter networking momentum into the second half of this year, especially as the cloud and hyperscalers are going through a server and Capex spending cycle?

I really appreciate that question. The Mellanox networking business has grown incredibly. There are three dynamics happening all at the same time. The first is the transition you're talking about. The world's data centers are now users for computing costs just aggregated, which enables a single application to run on multiple servers simultaneously. This makes it possible for them to scale up effectively. The more users there are for an AI application or service, you just have to add more servers. The ease of scaling out that this aggregated computing provides also puts enormous pressure on networking. Mellanox has the world's lowest latency and the highest bandwidth and performance networking on the planet. So the ability to scale out and provide this aggregation is much better with Mellanox networking. The second dynamic is that almost every company in the world needs to be a high-performance computing company now. Cloud service providers are building effective supercomputers. Historically, that was the realm of supercomputing firms, but now the cloud-service providers are building supercomputers themselves because of the requirements of deploying deep learning and artificial intelligence applications. The rate of growth of network sizes AI models is doubling every two months. You're seeing supercomputers grow in enterprises around the world. The third dynamic is the software-defined data center. To orchestrate and run a data center, just a few people are essentially running thousands of servers. That entire data center is software-defined. The amount of software that goes into that data center is extreme, and it's putting enormous pressure on the available computing capacity for applications. Data centers are moving towards a zero-trust model, and Bluefield is incredibly well-positioned. I appreciate this opportunity to share and I am very excited about the prospects in the networking business and the essential role they play in creating modern data centers.

Yeah. Thanks for taking my question. I think you hit on a lot of my questions around the Data Center in that last. So maybe I will just ask the kind of on a P&L basis, one of the things that I see in the results, or more importantly, the guidance, is you're now, Colette, guiding over a 67% gross margin, potentially. I'm curious as we move forward, how do you think about the incremental operating gross margin upside still from here, and how you're thinking about the operating margin leverage for the Company from here through the P&L? Thank you.

Let me take that and then you could just follow up with details. I think at the highest level, the important thing to realize is that artificial intelligence is the single greatest technology force that the computer industry has ever seen and potentially the world's ever seen. The automation opportunities that drive productivity translate directly into cost savings for companies and open up opportunities for technology and computing companies. Let me just give you some examples. The fact that we can apply technology in warehouse logistics, retail automation, and customer call center automation is unprecedented. The fact that we can automate truck driving and provide an automated chauffeur is something that was unimaginable before. The size of the IT industry has expanded like never before, and we want to invest as smartly and as quickly as we can to address large business opportunities where we can make a real impact while doing so in an architecturally sensible way. One of the great advantages of our company is the way we build products, our software discipline, our architectural efficiency. This enables us to address a wide range of areas like climate science, digital biology, artificial intelligence, robotics, and self-driving cars, while maintaining operating leverage. As we pursue these massive market opportunities offered by AI in a smart, disciplined way, we can keep driving great operating leverage for the company and our shareholders.

Yeah. Good afternoon, guys. Thanks for letting me ask a question. I apologize for the short-term nature of the question, but it's what I get asked most frequently. I want to return to the impact of crypto or the potential impact of crypto. Colette or Jensen, is there any way to gauge the effectiveness of the low hash rate GeForce? Why only 80% and not 100%? And how confident are you that the CMP business being down is a reflection of crypto cooling off versus perhaps the LHR not being that effective? There are a lot of discussions about workarounds.

Yes, please continue.

Let me start there and answer a couple of the questions about our strategy that we've put in place in this last couple of quarters. As you recall, what we put in place was the low hash rate cards, along with industry mandates on cards. The low hash rate cards were designed to provide more supply for our GeForce gamers that are out there. We articulated one of the metrics that we're looking at is what percentage of those cards in Ampere we were able to sell with low hash rate cards. Almost all our cards in Ampere are low hash rates, but we're also selling other types of cards as well. At this time, as we move forward, we're much higher than 80%, but just at the end of this last quarter, we were approximately at 80. So yes, that is moving up, so the strategy is in place, and we'll continue as we move into Q3. I'll move it to Jensen here to see if he can discuss it further.

There's a question about the strategy of how we're scaling GeForce supply to gamers. We moved incredibly quickly this time with CMPs, and with our LHR settings for GeForce. Our entire strategy is to steer GeForce supply to the industry. We have good reason to believe that the drive in gaming is really a measure of gamers and the adoption rate of our GPUs. There are several reasons why the situation is different this time. The first is that the LHR, which is new, and the speed at which we responded with CMPs, effectively pointed GeForce toward our gaming business. The second is that we are at the beginning of the Ampere and RTX graphics cycle. RTX was a complete reinvention of computer graphics, and every evidence indicates that gamers and game developers are incredibly excited about ray tracing and rendering. Most significantly, we've only upgraded a small fraction of our installed base and there remains a large number yet to be upgraded. The PC gaming market is large, and the number of gamers is still increasing. We have a large backlog, which reflects strong demand. Ultimately, RTX is making a huge difference.

Thank you. Good evening. My question is about the split between the Hyperscale and the vertical customers in the Data Center business and the trends you see in each. I think in your prepared remarks, you said both would be up in the October quarter. But I'm interested to see if you're seeing any different trends there, particularly in the vertical business, as perhaps business conditions normalize and companies return to the office, and they adjust their spending plans accordingly.

Yes. Let me start, and I'll let Jensen follow up. So far with our Data Center business, with our Q2 results, our vertical industries still make up a strong percentage. Essentially, 50% of our data center business is going to our vertical industries, while our Hyperscale makes up the other portion, slightly below 50%. We also have our supercomputing business with a very small percentage doing quite well. As we move into Q3, as we've discussed, we will see an acceleration of both our vertical industries and our hyperscales as we move into Q3. With that backdrop, I'll see if Jensen has additional thoughts.

There is a fundamental difference in the Hyperscale using HPC or AI versus the industrial use of HPC Internet. In the world of hyperscalers and internet service providers, they're making recommendations based on data and need deep learning for large-scale prediction tasks. In contrast, the industrial applications are shaking things up and using AI for logistics, transportation, and healthcare. The majority of the industry's AI will assist processes that were previously inefficient or possible only through traditional simulation. In simulation and modeling AI applications for drug discovery and climate science, you’re gaining significant advantages. This fusion of traditional and AI-based methods allows for enhancements that are groundbreaking. Each industry is recognizing the power of integrating AI into their operations, resulting in significantly increased efficiency.

Great, thanks so much for taking my question. Jensen, I'm wondering if you can talk for a moment about Omniverse. This looks like really cool technology, but I tend to get very few questions from investors about it. It looks to me like this could be potentially very meaningful technology for you longer-term. Can you explain perhaps what capabilities and what markets this is going after? It looks like, perhaps this is going to position you very well in augmented and virtual reality, but maybe it's a different market or group of markets. It's a bit confusing to us, so if you could maybe help us understand it, I think we'd really appreciate it. Thank you.

I really appreciate the question. Omniverse is a simulator. It's a simulator that's physically accurate and physically based. It was made possible because of two fundamental technologies we invented: RTX, which allows us to physically simulate light behavior in the world, and the ability to simulate the AI behaviors of agents and objects in the simulated environments. The simulator enables virtual worlds with portals based on an industry-standard, open standard that was pioneered by Pixar, and as we mentioned earlier, we are partnering with Pixar and Apple to make it even more widely adopted. These virtual worlds can be used for various applications such as concert simulations for consumers, and in the industrial space, you could use it for simulating robots. In fact, you could simulate factories entirely in Omniverse, which we have done with BMW. This factory becomes a digital twin to explore new algorithms and AIs to optimize operations. Omniverse presents an opportunity for an overlay of virtual and physical worlds, a vision that aligns with what many companies are calling the Metaverse. In our case, this extends into industrial design and engineering space. You'll be able to wormhole into these worlds using VR and collapse the boundaries of traditional design and engineering, creating a significant new economy that will become larger than our current economy. Omniverse is an extension of our AI and high-performance computing strategies and enhances how industries create digital tools to simulate their physical world. Thank you. We had an excellent quarter fueled by surging demand for NVIDIA computing. Our pioneering work in accelerated computing continues to impact graphics and scientific computing with AI. Enabled by NVIDIA accelerated computing, developers create the most impactful technologies of our time. From natural language understanding to autonomous vehicles and logistics centers to climate science research, the Metaverse obeys the laws of physics. This quarter we announced NVIDIA Base Command and Fleet Command to develop, deploy, scale, and orchestrate AI workflows on the NVIDIA AI Enterprise software suite. With our new Enterprise Software, a wide range of NVIDIA-powered systems, and a global network of system and integration partners, we can accelerate the world's largest industry as they reap the benefits of the transformative power of AI. We launched NVIDIA Omniverse, a simulation platform nearly five years in the making that runs physically realistic virtual worlds and connects to other digital platforms. We imagine engineers, designers, and autonomous machines connecting to Omniverse to create digital twin simulated worlds that help train robots, operating autonomous factories, simulating fleets of autonomous vehicles, and even predicting the human impact on Earth’s climate. The future will have artificial intelligence augmenting our own and the Metaverse augmenting our physical world. It will be populated by real and AI visitors, and open new opportunities for artists, designers, scientists, and businesses—a whole new digital economy. Omniverse is a platform for building the Metaverse vision, and we are working on some of our best and most impactful projects in our history. Thank you to all NVIDIA's employees for their hard work and the exciting future we're inventing together. See you next time.