5/24/2023

speaker
David
Conference Operator

Good afternoon. My name is David, and I'll be your conference operator today. At this time, I'd like to welcome everyone to NVIDIA's first quarter earnings call. Today's conference is being recorded. All lines have been placed on mute to prevent any background noise. After the speaker's remarks, there'll be a question and answer session. If you'd like to ask a question during this time, simply press the star key followed by the number one on your telephone keypad. If you'd like to withdraw your question, press star one once again. Thank you. Simona Jankowski, you may begin your conference.

speaker
Simona Jankowski
Host

Thank you. Good afternoon, everyone, and welcome to NVIDIA's conference call for the first quarter of fiscal 2024. With me 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 second quarter of fiscal 2024. The content of today's call is NVIDIA's property. It can be reproduced or transcribed without our prior written consent. During this call, we may make forward-looking statements based on current expectations. These are subject to a number of significant risks and uncertainties, and our actual results may differ materially. For a discussion of factors that could affect our future financial results in 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 8K with the Securities and Exchange Commission. All our statements are made as of today, May 24th, 2023, based on information currently available to us. Except it's 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. And with that, let me turn the call over to Collette.

speaker
Colette Kress
Executive Vice President and Chief Financial Officer

Thanks, Simona. Q1 revenue was $7.19 billion, up 19% sequentially and down 13% year on year. Strong sequential growth was driven by record data center revenue, with our gaming and professional visualization platforms emerging from channel inventory corrections. Starting with data center, Record revenue of $4.28 billion was up 18% sequentially and up 14% year on year on strong growth of our accelerated computing platform worldwide. Generative AI is driving exponential growth in compute requirements and a fast transition to NVIDIA accelerated computing, which is the most versatile, most energy efficient, and the lowest TCO approach to train and deploy ai generative ai drove significant upside in demand for our products creating opportunities and broad-based global growth across our markets let me give you some color across our three major customer categories cloud service providers or csps consumer internet companies and enterprises first CSPs around the world are racing to deploy our flagship Hopper and Ampere architecture GPUs to meet the surge in interest from both enterprise and consumer AI applications for training and inference. Multiple CSPs announced the availability of H100 on their platforms, including private previews at Microsoft Azure, Google Cloud, and Oracle Cloud Infrastructure. Upcoming offerings at AWS, and general availability at emerging GPU-specialized cloud providers like CoreWeave and Lambda. In addition to enterprise AI adoption, these CSPs are serving strong demand for H100 from generative AI pioneers. Second, consumer internet companies are also at the forefront of adopting generative AI and deep learning-based recommendation systems, driving strong growth. For example, Meta has now deployed its H100-powered Grand Teton AI supercomputer for its AI production and research teams. Third, enterprise demand for AI and accelerated computing is strong. We are seeing momentum in verticals such as automotive, financial services, healthcare, and telecom, where AI and accelerated computing are quickly becoming integral to customers innovation roadmaps and competitive positioning. For example, Bloomberg announced it has a 50 billion parameter model, Bloomberg GPT, to help with financial natural language processing tasks, such as sentiment analysis, named entity recognition, news classification, and question answering. Auto insurance company, CCC Intelligence Solutions, is using AI for estimating repairs. And AT&T is working with us on AI to improve fleet dispatches so their field technicians can better serve customers. Among other enterprise customers using NVIDIA AI are Deloitte for logistics and customer service, and Amgen for drug discovery and protein engineering. This quarter, we started shipping DGX H100, our hopper, generation AI system, which customers can deploy on-prem. And with the launch of DGX Cloud through our partnership with Microsoft Azure, Google Cloud, and Oracle Cloud Infrastructure, we deliver the promise of NVIDIA DGX to customers from the cloud. Whether the customers deploy DGX on-prem or via DGX Cloud, They get access to NVIDIA AI software, including NVIDIA Base Command, end-to-end AI frameworks, and pre-trained models. We provide them with a blueprint for building and operating AI, spanning our expertise across systems, algorithms, data processing, and training methods. We also announced NVIDIA AI Foundations, which are model foundry services available on DGX Cloud. that enable businesses to build, refine, and operate custom large language models and generative AI models trained with their own proprietary data, created for unique domain-specific tasks. They include NVIDIA Nemo for large language models, NVIDIA Picasso for images, video, and 3D, and NVIDIA BioNemo for life sciences. Each service has six elements. pre-trained models, frameworks for data processing and curation, proprietary knowledge-based vector databases, systems for fine-tuning, aligning, and guardrailing, optimized inference engines, and support from NVIDIA experts to help enterprises fine-tune models for their custom use cases. ServiceNow, a leading enterprise services platform, is an early adopter of DGX Cloud and MIMO. They're developing custom large language models trained on data specifically for the ServiceNow platform. Our collaboration will let ServiceNow create new enterprise-grade generative AI offerings for the thousands of enterprises worldwide running on the ServiceNow platform, including for IT departments, customer service teams, employees, and developers. Generative AI is also driving a step function increase in inference workloads. Because of their size and complexities, these workloads require acceleration. The latest MLPerf industry benchmark released in April showed NVIDIA's inference platforms deliver performance that is orders of magnitude ahead of the industry with unmatched versatility across diverse workloads. To help customers deploy generative AI applications of scale, at GTC, we announced four major new inference platforms that leverage the NVIDIA AI software stack. These include L4, Tensor Core GPU for AI video, L40 for omniverse and graphics rendering, H100 and VL for large language models, and the Grace Hopper Superchip for LLMs, and also recommendation systems and vector databases. Google Cloud is the first CSP to adopt our L4 inference platform with the launch of its G2 virtual machines for generative AI inference and other workloads, such as Google Cloud Dataproc, Google AlphaFold, and Google Cloud Immersive Stream, which render 3D and AR experiences. In addition, Google is integrating our Triton inference server with Google Kubernetes Engine and its cloud-based Vertex AI platform. In networking, we saw strong demand at both CSPs and enterprise customers for generative AI and accelerated computing, which require high-performance networking, like NVIDIA's Mellanox networking platforms. Demand relating to general-purpose CPU infrastructure remains soft. As generative AI applications grow in size and complexity, high performance networks become essential for delivering accelerated computing at data center scale to meet the enormous demands of both training and inferencing. Our 400 gig Quantum II InfiniBand platform is the gold standard for AI dedicated infrastructure with broad adoption across major cloud and consumer Internet platforms such as Microsoft Azure. With a combination of in-network computing technology and the industry's only end-to-end data center scale optimized software stack, customers routinely enjoy a 20% increase in throughput for their sizable infrastructure investment. For multi-tenant cloud transitioning to support generative AI, our high-speed Ethernet platform with Bluefield 3 DPUs and Spectrum 4 Ethernet switching offers highest available Ethernet network performance. Bluefield 3 is in production and has been adopted by multiple hyperscale and CSP customers, including Microsoft, Azure, Oracle Cloud, PowerWeave, Baidu, and others. We look forward to sharing more about our 400-gig Spectrum 4 accelerated AI networking platform next week at the Computex conference in Taiwan. Lastly, Our GRACE Data Center CPU is sampling with customers. At this week's International Supercomputing Conference in Germany, the University of Bristol announced a new supercomputer based on the NVIDIA GRACE CPU Superchip, which is 6x more energy efficient than the previous supercomputer. This adds to the growing momentum for GRACE with both CPU only and CPU GPU opportunities across AI and cloud and supercomputing applications. The coming wave of Bluefield 3, Grace, and Grace Hopper Superchips will enable a new generation of super energy efficient accelerated data centers. Now, let's move to gaming. Gaming revenue of $2.24 billion was up 22% sequentially and down 38% year-on-year. Strong sequential growth was driven by sales of the 40-series GeForce RTX GPUs for both notebooks and desktops. Overall, end demand was solid and consistent with seasonality, demonstrating resilience against a challenging consumer spending backdrop. The GeForce RTX 40 series GPU laptops are off to a great start, featuring four NVIDIA inventions, RTX Path Tracing, DLSS3 AI rendering, Reflex ultra-low latency rendering, and Max-Q energy efficient technologies. They deliver tremendous gains in industrial design, performance, and battery life for gamers and creators. And like our desktop offerings, 40 series laptops support the NVIDIA Studio platform of software technologies, including acceleration for creative data science and AI workflows, and Omniverse, giving content creators unmatched tools and capabilities. In desktop, we ramped the RTX 4070, which joined the previously launched RTX 4090, 4080, and the 4070 Ti GPUs. The RTX 4070 is nearly 3x faster than the RTX 2070 and offers our large installed base a spectacular upgrade. Last week, we launched the 60 family, RTX 4060 and 4060 Ti, bringing our newest architecture to the world's core gamers, starting at just $299. These GPUs for the first time provide 2x the performance of the latest gaming console at mainstream price points. The 4060 Ti is available starting today, while the 4060 will be available in July. Generative AI will be transformative to gaming and content creation from development to runtime. At the Microsoft Build Developer Conference earlier this week, we showcased how Windows PCs and workstations with NVIDIA RTX GPUs will be AI-powered at their core. NVIDIA and Microsoft have collaborated on end-to-end software engineering spanning from the Windows operating system to the NVIDIA graphics drivers and NEMO LLL framework to help make Windows on NVIDIA RTX Tensor Core GPUs a supercharged platform for generative AI. Last quarter, we announced a partnership with Microsoft to bring Xbox PC games to GeForce Now. The first game from this partnership, Gears 5, is now available, with more set to be released in the coming months. There are now over 1,600 games on GeForce Now, the richest content available on any cloud gaming service. Moving to Pro Visualization. Revenue of $295 million was up 31% sequentially and down 53% year-on-year. Sequential growth was driven by stronger workstation demand across both mobile and desktop phone factors, with strength in key verticals such as public sector, healthcare, and automotive. We believe the channel inventory correction is behind us. The ramp of our Ada Lovelace GPU architecture in workstations kicks off a major product class. At GTC, we announced six new RTX GPUs for laptops and desktop workstations, with further rollouts planned in the coming quarters. Generative AI is a major new workload for NVIDIA-powered workstations. Our collaboration with Microsoft transforms Windows into the ideal platform for creators and designers harnessing generative AI to elevate their creativity and productivity. At GTC, we announced NVIDIA Omniverse Cloud, an NVIDIA fully managed service running in Microsoft Azure that includes the full suite of Omniverse applications and NVIDIA OVX infrastructure. Using this full stack cloud environment, customers can design, develop, deploy, and manage industrial metaverse applications. NVIDIA Omniverse Cloud will be available starting in the second half of this year. Microsoft NVIDIA will also connect Office 365 applications with Omniverse. Omniverse Cloud is being used by companies to digitalize their workflows from design and engineering to smart factories and 3D content generation for marketing. The automotive industry has been a leading early adopter of Omniverse, including companies such as BMW Group, Unilotus, General Motors, and Jaguar Land Rover. Moving to automotive. Revenue was $296 million, up 1% sequentially and up 114% from a year ago. Our strong year-on-year growth was driven by the ramp of the NVIDIA Drive Orin across a number of new energy vehicles. As we announced in March, our automotive design wind pipeline over the next six years now stands at $14 billion. up from 11 billion a year ago, giving us visibility into continued growth over the coming years. Sequentially, growth moderated, as some NEV customers in China are adjusting their production schedules to reflect slower-than-expected demand growth. We expect this dynamic to linger for the rest of the calendar year. During the quarter, we expanded our partnership with BID, the world's leading manufacturer of NEVs, Our new design win will extend BYD's use of the Drive Oren to its next-generation high-volume Dynasty and Ocean series of vehicles set to start production in calendar 2024. Moving to the rest of the P&L, GAAP gross margins were 64.6%. Non-GAAP gross margins were 66.8%. Gross margins have now largely recovered to prior peak levels and we have absorbed higher costs and offset them by innovating and delivering higher valued products as well as products incorporating more and more software. Sequentially, GAAP operating expenses were down 3% and non-GAAP operating expenses were down 1%. We have held OPEX at roughly the same level over the last past four quarters. while working through the inventory corrections in gaming and professional visualization. We now expect to increase investments in the business while also delivering operating leverage. We returned $99 million to shareholders in the form of cash dividends. At the end of Q1, we have approximately $7 billion remaining under our share repurchase authorization through December 2023. Let me turn to the outlook for the second quarter of fiscal 24. Total revenue is expected to be 11 billion, plus or minus 2%. We expect this sequential growth to largely be driven by data center, reflecting a steep increase in demand related to generative AI and large language models. This demand has extended our data center visibility out a few quarters, and we have procured substantially higher supply for the second half of the year. GAAP and non-GAAP gross margins are expected to be 68.6% and 70% respectively, plus or minus 50 basis points. GAAP and non-GAAP operating expenses are expected to be approximately 2.71 billion and 1.9 billion respectively. Gap and non-gap other income and expenses are expected to be an income of approximately 90 million, excluding gains and losses from non-affiliated investments. Gap and non-gap tax rates are expected to be 14%, plus or minus 1%, excluding any discrete items. Capital expenditures are expected to be approximately 300 to 350 million. Further financial details are included in the CFO commentary and other information available on our IR website. In closing, let me highlight some of the upcoming event. Jensen will give the Computex keynote address in person in Taipei this coming Monday, May 29th, local time, which will be Sunday evening in the US. In addition, we will be attending the B of A Global Technology Conference in San Francisco on June 6th, and Rosenblatt Virtual Technology Summit on the Age of AI on June 7th, and the New Street Future of Transportation Virtual Conference on June 12th. Our earnings call to discuss the revolts of our second quarter, fiscal 24, is scheduled for Wednesday, August 23rd. Well, as covers our opening remarks, we're now going to open the call for questions. Operator, would you please pull for questions?

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