About NVIDIA Corp
NVIDIA Corporation (NVIDIA) operates as a visual computing company worldwide. The company has leveraged its GPU architecture to create platforms for scientific computing, artificial intelligence (AI), data science, autonomous vehicles (AV), robotics, and augmented and virtual reality (AR and VR). The company has a platform strategy, bringing together hardware, software, algorithms, libraries, systems, and services to create unique value for the markets it serves. While the requirements of these end markets are diverse, the company addresses them with a unified underlying architecture leveraging its GPUs and software stacks. Researchers use the company’s GPUs to accelerate a wide range of important applications, from simulating molecular dynamics to weather forecasting. Segments The company operates through two segments, Graphics; and Compute & Networking. Graphics Graphics segment includes GeForce GPUs for gaming and PCs, the GeForce NOW game streaming service and related infrastructure, and solutions for gaming platforms; Quadro/NVIDIA RTX GPUs for enterprise workstation graphics; virtual GPU (vGPU) software for cloud-based visual and virtual computing; and automotive platforms for infotainment systems. Compute & Networking Compute & Networking segment includes Data Center platforms and systems for AI, high-performance computing (HPC), and accelerated computing; Mellanox networking and interconnect solutions; automotive AI Cockpit, autonomous driving development agreements, and autonomous vehicle solutions; and Jetson for robotics and other embedded platforms. Markets The company specializes in markets in which its computing platforms can provide tremendous acceleration for applications. These platforms incorporate processors, interconnects, software, algorithms, systems, and services to deliver value that is unique in the marketplace. Its platforms address four large markets where its expertise is critical: Gaming, Professional Visualization, Data Center, and Automotive. Gaming The company’s gaming platforms leverage its GPUs and sophisticated software to enhance the gaming experience with smoother, higher quality graphics. This includes GeForce Experience, its gaming application that optimizes the PC user’s settings for each application and enables gamers to record and share gameplay. The company developed NVIDIA RTX bringing next generation graphics and AI to games. The NVIDIA RTX line-up features ray tracing technology for real-time, cinematic-quality rendering. Ray tracing, which has long been used for special effects in the movie industry, is a computationally intensive technique that simulates the physical behavior of light to achieve greater realism in computer-generated scenes. NVIDIA RTX also features deep learning super sampling, or DLSS, the company’s AI technology that boosts frame rates while generating beautiful, sharp images for games. The company’s products for the gaming market include GeForce RTX and GeForce GTX GPUs for PC gaming, SHIELD devices for gaming and streaming, GeForce NOW for cloud-based gaming, as well as platforms and development services for specialized console gaming devices. Professional Visualization The company serves the Professional Visualization market by working closely with independent software vendors to optimize their offerings for NVIDIA GPUs. Its GPU computing solutions enhance productivity and introduce new capabilities for critical parts of the workflow for such major industries as automotive, media and entertainment, architectural engineering, oil and gas, and medical imaging. Designers who build the products the company uses every day need the images that they view digitally to mirror reality. This requires simulating the physical behavior of light and materials, or physically-based rendering. Its DesignWorks software delivers this to designers and enables an architect designing a building with a computer-aided design package to interact with the model in real time, view it in greater detail, and generate photorealistic renderings for the client. It also allows an automotive designer to create a highly realistic 3D image of a car, which can be viewed from all angles. The company’s Professional Visualization platforms are critical enablers in many fields, such as design and manufacturing and digital content creation. Design and manufacturing encompass computer-aided design, architectural design, consumer-products manufacturing, medical instrumentation, and aerospace. Digital content creation includes professional video editing and post-production, special effects for films, and broadcast-television graphics. The NVIDIA RTX platform makes it possible to render film-quality, photorealistic objects and environments with physically shadows, reflections and refractions using ray tracing in real-time. Data Center The NVIDIA computing platform focuses on accelerating the most compute-intensive workloads, such as AI, data analytics, graphics and scientific computing, across hyperscale, cloud, enterprise, public sector, and edge data centers. The platform consists of the company’s energy efficient GPUs, interconnects and systems, its CUDA programming model, and a growing body of software libraries, Software Development Kits, or SDKs, application frameworks and services. In the field of AI, the company’s platform accelerates both deep learning and machine learning workloads. Deep learning is a computer science approach where neural networks are trained to recognize patterns from massive amounts of data in the form of images, sounds and text - in some instances better than humans. Machine learning is a related approach that leverages algorithms as well as data to learn how to make determinations or predictions, often used in data science. HPC, also referred to as scientific computing, uses numerical computational approaches to solve large and complex problems. For both AI and HPC applications, the NVIDIA accelerated computing platform greatly increases the performance and power efficiency of high-performance computers and data centers. The company engages with thousands of organizations working on AI in a multitude of industries, from automating tasks, such as reading medical images, to enabling fraud detection in financial services, to optimizing oil exploration and drilling. These organizations include the consumer internet and cloud services companies, which are using AI for critical tasks, such as natural language processing and recommendation systems; enterprises that are increasingly turning to AI to improve products and services; and startups seeking to implement AI in transformative ways across multiple industries. The company partnered with industry leaders, such as IBM, Microsoft, Oracle, SAP, and VMware to bring AI to enterprise users. It also has partnerships in transportation, retail, healthcare and manufacturing, among others, to accelerate the adoption of AI. At the foundation of the NVIDIA accelerated computing platform are the company’s GPUs, which excel at parallel workloads, such as the training and inferencing of neural networks. They are available in servers from every major computer maker worldwide, including Cisco, Dell, HP, Inspur, and Lenovo; from every major cloud service provider, such as Alicloud, Amazon Web Services, Baidu Cloud, Google Cloud, IBM Cloud, Microsoft Azure, and Oracle Cloud; as well as in its DGX AI supercomputer, a purpose-built system for deep learning and GPU accelerated applications. To facilitate customer adoption, the company has also built other ready-to-use systems and reference designs around its GPUs, including HGX for hyperscale and supercomputing data centers, EGX for enterprise and edge computing, and AGX for autonomous machines. The company owns Mellanox Technologies, Ltd., or Mellanox, a supplier of high-performance interconnect and networking products that are part of its Data Center market platform. Mellanox interconnects are included in the company’s DGX, HGX and EGX platforms and continue to be available on a standalone basis. While its approach starts with powerful chips, what makes it a computing platform is the company’s large body of software, including the CUDA parallel programming model, the CUDA-X collection of application acceleration libraries, Application Programming Interfaces, or APIs, SDKs and tools, and domain-specific application frameworks. The company also offers the NVIDIA GPU Cloud registry, or NGC, a comprehensive catalog of easy-to-use, optimized software stacks across a range of domains, including scientific computing, deep learning, and machine learning. With NGC, AI developers, researchers and data scientists can get started with the development of AI and HPC applications and deploy them on DGX systems, NGC-ready workstations or servers from the company’s systems partners, or with NVIDIA’s cloud partners such as Amazon Web Services, Google Cloud, Microsoft Azure, or Oracle Cloud. The company also serves the data center market with NVIDIA virtual GPU (vGPU) software products that enable GPU performance for workloads ranging from graphics-rich virtual desktops and workstations to data science and AI. Installed on a physical GPU in a cloud or enterprise data center server, NVIDIA vGPU software creates virtual GPUs that can be shared across multiple virtual machines accessed on any device, anywhere. With companies supporting more offsite workers than ever before, NVIDIA vGPU software products are enabling remote access to professional graphics and accelerated computing for data scientists, researchers, designers, engineers, and creative professionals across industries, such as healthcare, manufacturing, architecture, and media and entertainment. Automotive The company’s Automotive market is comprised of cockpit infotainment solutions, AV platforms, and associated development agreements. Leveraging its technology leadership in AI and building on the company’s long-standing automotive relationships, it is delivering a complete end-to-end solution for the AV market under the DRIVE brand. NVIDIA has demonstrated multiple applications of AI within the car: AI can drive the car itself as a pilot in fully autonomous mode or it can also be a co-pilot, assisting the human driver while creating a safer driving experience. NVIDIA is working with several hundred partners in the automotive ecosystem, including automakers, truck makers, tier-one suppliers, sensor manufacturers, automotive research institutions, HD mapping companies, and startups to develop and deploy AI systems for self-driving vehicles. Its unified AI computing architecture starts with training deep neural networks using its GPUs, and then running a full perception, planning and control stack within the vehicle on the NVIDIA DRIVE computing platform. The in-vehicle platform consists of the high-performance, energy efficient DRIVE AGX computing hardware, and open, modular software, including DRIVE AV for autonomous driving and DRIVE IX for in-vehicle intelligent experience and AI assistants. NVIDIA DRIVE can perceive and understand in real-time what is happening around the vehicle, precisely locate itself on an HD map, and plan a safe path forward. This advanced self-driving car platform combines deep learning, sensor fusion, and surround vision to change the driving experience. The company’s DRIVE platform scales from a palm-sized, energy-efficient module for automated highway-driving capabilities to a configuration with multiple systems aimed at enabling driverless cars. Its Xavier system-on-a-chip, or SoC, which started shipping in 2018, enables vehicles to use deep neural networks to process data from multiple cameras and sensors. It powers the DRIVE AutoPilot, NVIDIA’s Level 2+ automated driving solution, combining the DRIVE AV self-driving solution with the DRIVE IX cockpit software, including a visualization system for allowing the driver to see what the car sees and plans to do. In 2020, the company announced its next-generation SoC, Orin. In addition, the company offers a scalable data center-based simulation solution, NVIDIA DRIVE Constellation running DRIVE Sim software, for testing and validating a self-driving platform before commercial deployment. Its unique end-to-end, software-defined approach is designed for continuous innovation and continuous development, enabling cars to receive over-the-air updates to add new features and capabilities throughout the life of a vehicle. Business Strategies The key elements of the company’s strategy include advancing the NVIDIA accelerated computing platform; extending its technology and platform leadership in AI; extending its technology and platform leadership in visual computing; advancing the leading autonomous vehicle platform; and leveraging its intellectual property. Sales and Marketing The company’s partner network incorporates each industry's respective OEMs, original device manufacturers, or ODMs, system builders, add-in board manufacturers, or AIBs, retailers/distributors, internet and cloud service providers, automotive manufacturers and tier-1 automotive suppliers, mapping companies, start-ups, and other ecosystem participants. The company’s developer program makes its products available to developers prior to launch in order to encourage the development of AI frameworks, SDKs, and APIs for software applications and game titles that are optimized for its platforms. Its Deep Learning Institute provides in-person and online training for developers in industries and organizations around the world to build AI and accelerated computing applications that leverage its platforms. Seasonality The company’s computing platforms serve a diverse set of markets, such as enterprise and cloud data centers, consumer gaming, professional workstations, and automotive. Its consumer products typically see stronger revenue in the second half of its fiscal year (year ended January 31, 2021). In addition, based on the production schedules of key customers, some of its products for notebooks and game consoles typically generate stronger revenue in the second and third quarters, and weaker revenue in the fourth and first quarters. Manufacturing The company utilizes suppliers, such as Taiwan Semiconductor Manufacturing Company Limited and Samsung Electronics Co. Ltd, to produce its semiconductor wafers. The company then utilizes independent subcontractors, such as Amkor Technology, BYD Auto Co. Ltd.; Hon Hai Precision Industry Co.; King Yuan Electronics Co., Ltd.; Omni Logistics, LLC; and Siliconware Precision Industries Company Ltd. to perform assembly, testing, and packaging of most of its products and platforms. The company uses contract manufacturers, such as Flex Ltd. to manufacture its standard and custom adapter card products and switch systems, and Fabrinet to manufacture its cables. The company purchases substrates from Ibiden Co. Ltd., Kinsus Interconnect Technology Corporation, and Unimicron Technology Corporation, and memory from Micron Technology, Samsung Semiconductor, Inc., and SK Hynix. The company also utilizes contract manufacturers, or CMs, such as Flex Ltd. and Fabrinet; and ODMs, such as Wistron Corporation to manufacture some of its products for sale directly to end customers. Competition The company’s competitors include suppliers and licensors designing discrete and integrated GPUs and other accelerated computing solutions, including chipsets that incorporate 3D graphics, or HPC, such as Advanced Micro Devices, or AMD, Intel Corporation, and Xilinx, Inc.; large internet services companies with internal teams designing chips that incorporates HPC or accelerated computing functionality as part of their internal solutions or platforms, such as Alphabet Inc. and Amazon, Inc.; suppliers of SoC products that are embedded into automobiles, autonomous machines, and gaming devices, such as Ambarella, Inc., AMD, Broadcom Inc., Intel, Qualcomm Incorporated, Renesas Electronics Corporation, Samsung, and Xilinx or companies with internal teams designing SoC products for internal use, such as Tesla Motors; and suppliers of interconnect, switch and cable solutions such as Applied Optoelectronics, Inc., Arista Networks, Broadcom, Cisco Systems, Inc., Hewlett Packard Enterprise Company, Intel, Juniper Networks, Inc., Lumentum Holdings, Marvell Technology Group, and Xilinx, as well as internal teams of system vendors and large internet services companies such as Alphabet and Amazon. Patents and Proprietary Rights The company’s issued patents have expiration dates from March 2021 to June 2045. It has numerous patents issued, allowed, and pending in the United States and in foreign jurisdictions. Its patents and pending patent applications primarily relate to its products and the technology used in connection with its products. Trademarks The company’s trademarks and/or registered trademarks include NVIDIA, the NVIDIA logo, GeForce, Quadro, Tegra, CUDA, CUDA-X AI, GeForce, GeForce Experience, GeForce GTX, GeForce NOW, GeForce RTX, Jetson, Mellanox, NGC, NVIDIA AGX, NVIDIA DesignWorks, NVIDIA DGX, NVIDIA DRIVE, NVIDIA DRIVE Constellation, NVIDIA GRID, NVIDIA HGX, NVIDIA RTX, NVIDIA VRWorks, Quadro, Quadro RTX, SHIELD, vGPU and Xavier. History NVIDIA Corporation was founded in 1993. The company was incorporated in California in 1993 and reincorporated in Delaware in 1998.