NVIDIA Corporation

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

Thank you. Good afternoon, everyone, and welcome to NVIDIA's conference call for the fourth quarter of fiscal 2023. 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 first 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. Through 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 8-K with the Securities and Exchange Commission. All our statements are made as of today, February 22, 2023, 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, the GAAP financial measures in our CFO commentary, which is posted on our website. With that, let me turn the call over to Collette.

Thank you, Simona. Q4 revenue was $6.05 billion, up 2% sequentially, and down 21% year-on-year. Full-year revenue was $27 billion, flat from the prior year. Starting with data center, revenue was $3.62 billion, was down 6% sequentially and up 11% year on year. Fiscal year revenue was $15 billion and up 41%. Hyperscale customer revenue posted strong sequential growth, though short of our expectations as some cloud service providers paused at the end of the year to recalibrate their build plans, though we generally see tightening that reflects overall macroeconomic uncertainty, we believe this is a timing issue. At the end, market demand for GPUs and AI infrastructure is strong. Networking grew, but a bit less than our expected on softer demand for general purpose CPU infrastructure. The total data center sequential revenue decline was driven by lower sales in China, which was largely in line with our expectations. reflecting COVID and other domestic issues. With cloud adoption continuing to grow, we are serving an expanding list of fast-growing cloud service providers, including Oracle and GPU-specialized CSPs. Revenue growth from CSP customers last year significantly outpaced that of data center as a whole, as more enterprise customers moved to a cloud-first approach. On a trailing four-quarter basis, CSP customers drove about 40% of our data center revenue. Adoption of our new flagship H100 data center GPU is strong. In just the second quarter of its ramp, H100 revenue was already much higher than that of A100, which declined sequentially. This is a testament of the exceptional performance on the H100, which is as much as 9x faster than the A100 for training and up 30x faster than inferencing of transformer-based large language models. The transformer engine of H100 arrived just in time to serve the development and scale-out of inference of large language models. AI adoption is at an inflection point. OpenAI's ChatGPT has captured interest worldwide, allowing people to experience AI firsthand showing what's possible with generative AI. These new types of neural network models can improve productivity in a wide range of tasks, whether generating text like marketing copy, summarizing documents like creating images for ads or video games, or answering customer questions. Generative AI applications will help almost every industry do more faster. Generative large language models with over 100 billion parameters are the most advanced neural networks in today's world. NVIDIA's expertise spans across the AI supercomputers, algorithms, data processing, and training methods that can bring these capabilities to enterprise. We look forward to helping customers with generative AI opportunities. In addition to working with every major hyperscale cloud provider, we are engaged with many consumer internet companies, enterprises, and startups. The opportunity is significant and driving strong growth in the data center that will accelerate through the year. During the quarter, we made notable announcements in the financial services sector, one of our largest industry vehicles. We announced a partnership with Deutsche Bank to accelerate the use of AI and machine learning in financial services. Together, we are developing a range of applications, including virtual customer service agents, speech AI, fraud detection, and bank process automation, leveraging NVIDIA's full computing stack, both on-premise and in the cloud, including NVIDIA AI enterprise software. We also know that NVIDIA captured leading results for AI inference in a key financial services industry benchmark for applications such as asset price discovery. In networking, we see growing demand for our latest generation InfiniBand and HPC optimized Ethernet platforms fueled by AI. Generative AI foundation model sizes continue to grow at exponential rates. driving the need for high-performance networking to scale out multi-node accelerated workloads. Delivering unmatched performance, latency, and in-network computing capabilities, InfiniBand is the clear choice for power-efficient cloud-scale generative AI. For smaller-scale deployments, NVIDIA is bringing its full accelerated stack expertise and integrating it with the world's most advanced high-performance Ethernet fabrics. In the quarter, InfiniBand led our growth as our Quantum 2 40 gigabit per second platform is off to a great start, driven by demand across cloud, enterprise, and supercomputing customers. In Ethernet, our 40 gigabit per second Spectrum 4 networking platform is gaining momentum as customers transition to higher speeds, next generation adapters, and switches. We remain focused on expanding our software and services. Released version 3.0 of NVIDIA AI Enterprise with support for more than 50 NVIDIA AI frameworks and pre-trained model and new workflows for contact center, intelligent virtual assistants, audio transcription, and cybersecurity. Upcoming offerings include our NEMO and BioNEMO large language model services. which are currently in early access with customers. Now, to Jensen to talk a bit more about our software and cloud.