What changed in this filing

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Item 1. Business

2024-02-21 compared with 2023-02-24 · 170 added, 187 removed, 188 unchanged (66% of the section changed)

NVIDIA pioneered accelerated computing to help solve the most challenging computational problems.

Since our original focus on PC graphics, we have expanded to several other large and important computationally intensive fields.

Fueled by the sustained demand for exceptional 3D graphics and the scale of the gaming market, NVIDIA has leveraged its GPU architecture to create platforms for scientific computing, artificial intelligence, or AI, data science, autonomous vehicles, or AV, robotics, metaverse and 3D internet applications.

NVIDIA is now a full-stack computing infrastructure company with data-center-scale offerings that are reshaping industry.

Our full-stack includes the foundational CUDA programming model that runs on all NVIDIA GPUs, as well as hundreds of domain-specific software libraries, software development kits, or SDKs, and Application Programming Interfaces, or APIs.

This deep and broad software stack accelerates the performance and eases the deployment of NVIDIA accelerated computing for computationally intensive workloads such as artificial intelligence, or AI, model training and inference, data analytics, scientific computing, and 3D graphics, with vertical-specific optimizations to address industries ranging from healthcare and telecom to automotive and manufacturing.

Our data-center-scale offerings are comprised of compute and networking solutions that can scale to tens of thousands of GPU-accelerated servers interconnected to function as a single giant computer;

this type of data center architecture and scale is needed for the development and deployment of modern AI applications.

The GPU was initially used to simulate human imagination, enabling the virtual worlds of video games and films.

Today, it also simulates human intelligence, enabling a deeper understanding of the physical world.

Its parallel processing capabilities, supported by thousands of computing cores, are essential to running deep learning algorithms.

Its parallel processing capabilities, supported by thousands of computing cores, are essential for deep learning algorithms.

This form of AI, in which software writes itself by learning from large amounts of data, can serve as the brain of computers, robots and self-driving cars that can perceive and understand the world.

GPU-powered deep learning is being adopted by thousands of enterprises to deliver services and products that would have been immensely difficult with traditional coding.

Some of the most recent applications of GPU-powered deep learning include recommendation systems, which are AI algorithms trained to understand the preferences, previous decisions, and characteristics of people and products using data gathered about their interactions, large language models, which can recognize, summarize, translate, predict and generate text and other content based on knowledge gained from massive datasets, and generative AI, which uses algorithms that create new content, including audio, code, images, text, simulations, and videos, based on the data they have been trained on.

GPU-powered AI solutions are being developed by thousands of enterprises to deliver services and products that would have been immensely difficult or even impossible with traditional coding.

Examples include generative AI, which can create new content such as text, code, images, audio, video, and molecule structures, and recommendation systems, which can recommend highly relevant content such as products, services, media or ads using deep neural networks trained on vast datasets that capture the user preferences.

NVIDIA has a platform strategy, bringing together hardware, systems, software, algorithms, libraries, and services to create unique value for the markets we serve.

While the computing requirements of these end markets are diverse, we address them with a unified underlying architecture leveraging our GPUs and software stacks.

While the computing requirements of these end markets are diverse, we address them with a unified underlying architecture leveraging our GPUs and networking and software stacks.

The programmable nature of our architecture allows us to support several multi-billion-dollar end markets with the same underlying technology by using a variety of software stacks developed either internally or by third-party developers and partners.

The large and growing number of developers across our platforms strengthens our ecosystem and increases the value of our platform to our customers.

The large and growing number of developers and installed base across our platforms strengthens our ecosystem and increases the value of our platform to our customers.

Innovation is at our core.

We have invested over $45.3 billion in research and development since our inception, yielding inventions that are essential to modern computing.

Our invention of the GPU in 1999 defined modern computer graphics and established NVIDIA as the leader in computer graphics.

With our introduction of the CUDA programming model in 2006, we opened the parallel processing capabilities of our GPU for general purpose computing.

This approach significantly accelerates the most demanding high-performance computing, or HPC, applications in fields such as aerospace, bio-science research, mechanical and fluid simulations, and energy exploration.

Today, our GPUs and networking accelerate many of the fastest supercomputers across the world.

In addition, the massively parallel compute architecture of our GPUs and associated software are well suited for deep learning and machine learning, powering the era of AI.

While traditional CPU-based approaches no longer deliver advances on the pace described by Moore’s Law, NVIDIA accelerated computing delivers performance improvements on a pace ahead of Moore’s Law, giving the industry a path forward.

Gamers choose NVIDIA GPUs to enjoy immersive, increasingly cinematic virtual worlds.

GPUs also help underpin the world’s fastest growing spectator sport, eSports, which attracts hundreds of millions of viewers to watch top-quality live video gaming.

In addition to serving the growing number of gamers, the market for gaming GPUs is expanding because of the burgeoning population of live streamers, broadcasters, artists and creators.

Researchers and developers use our GPUs to accelerate a wide range of important applications, from simulating molecular dynamics to climate forecasting.

With support for more than 2,800 applications - including 23 of the top 25 HPC applications - NVIDIA GPUs enable some of the most promising areas of discovery, from climate prediction to materials science and from wind tunnel simulation to genomics.

Our invention of the GPU in 1999 sparked the growth of the PC gaming market and redefined computer graphics.

With our introduction of the CUDA programming model in 2006, we opened the parallel processing capabilities of our GPU to a broad range of compute-intensive applications, paving the way for the emergence of modern AI.

In 2012, the AlexNet neural network, trained on NVIDIA GPUs, won the ImageNet computer image recognition competition, marking the “Big Bang” moment of AI.

We introduced our first Tensor Core GPU in 2017, built from the ground-up for the new era of AI, and our first autonomous driving system-on-chips, or SoC, in 2018.

Our acquisition of Mellanox in 2020 expanded our innovation canvas to include networking and led to the introduction of a new processor class – the data processing unit, or DPU.

Over the past 5 years, we have built full software stacks that run on top of our GPUs and CUDA to bring AI to the world’s largest industries, including NVIDIA DRIVE stack for autonomous driving, Clara for healthcare, and Omniverse for industrial digitalization;

and introduced the NVIDIA AI Enterprise software – essentially an operating system for enterprise AI applications.

In 2023, we introduced our first data center CPU, Grace, built for giant-scale AI and high-performance computing.

With a strong engineering culture, we drive fast, yet harmonized, product and technology innovations in all dimensions of computing including silicon, systems, networking, software and algorithms.

More than half of our engineers work on software.

The world’s leading cloud service providers, or CSPs, and consumer internet companies use our data center-scale accelerated computing platforms to enable, accelerate or enrich the services they deliver to billions of end users, including AI solutions and assistants, search, recommendations, social networking, online shopping, live video, and translation.

Enterprises and startups across a broad range of industries use our accelerated computing platforms to build new generative AI-enabled products and services, or to dramatically accelerate and reduce the costs of their workloads and workflows.

The enterprise software industry uses them for new AI assistants and chatbots;

the transportation industry for autonomous driving;

the healthcare industry for accelerated and computer-aided drug discovery;

and the financial services industry for customer support and fraud detection.

Researchers and developers use our computing solutions to accelerate a wide range of important applications, from simulating molecular dynamics to climate forecasting.

With support for more than 3,500 applications, NVIDIA computing enables some of the most promising areas of discovery, from climate prediction to materials science and from wind tunnel simulation to genomics.

Including GPUs and networking, NVIDIA powers over 75% of the supercomputers on the global TOP500 list, including 24 of the top 30 systems on the Green500 list.

The world’s leading cloud service providers, or CSPs, and consumer internet companies use our GPUs and broader data center-scale accelerated computing platforms to enable, accelerate or enrich the services they deliver to billions of end-users, including search, recommendations, social networking, online shopping, live video, translation, AI assistants, navigation, and cloud computing.

A rapidly growing number of enterprises and startups across a broad range of industries use our GPUs and software to bring automation to the products and services they build.

The transportation industry is turning to our platforms for autonomous driving;

the healthcare industry is leveraging them for enhanced medical imaging and acceleration of drug discovery;

and the financial services industry is using them for fraud detection.

Professional designers use our GPUs and software to create visual effects in movies and to design buildings and products ranging from cell phones to commercial aircraft.

Gamers choose NVIDIA GPUs to enjoy immersive, increasingly cinematic virtual worlds.

In addition to serving the growing number of gamers, the market for PC GPUs is expanding because of the burgeoning population of live streamers, broadcasters, artists, and creators.

With the advent of generative AI, we expect a broader set of PC users to choose NVIDIA GPUs for running generative AI applications locally on their PC, which is critical for privacy, latency, and cost-sensitive AI applications.

Professional artists, architects and designers use NVIDIA partner products accelerated with our GPUs and software platform for a range of creative and design use cases, such as creating visual effects in movies or designing buildings and products.

In addition, generative AI is expanding the market for our workstation-class GPUs, as more enterprise customers develop and deploy AI applications with their data on-premises.

Headquartered in Santa Clara, California, NVIDIA was incorporated in California in April 1993 and reincorporated in Delaware in April 1998.

Termination of the Arm Share Purchase Agreement

In February 2022, NVIDIA and SoftBank Group Corp., or SoftBank, announced the termination of the Share Purchase Agreement whereby NVIDIA would have acquired Arm Limited, or Arm, from SoftBank.

The parties agreed to terminate because of significant regulatory challenges preventing the completion of the transaction.

We recorded an acquisition termination cost of $1.35 billion in fiscal year 2023 reflecting the write-off of the prepayment provided at signing.

Our Businesses

We report our business results in two segments.

The Compute & Networking segment includes our Data Center accelerated computing platform;

automotive AI Cockpit, autonomous driving development agreements, and autonomous vehicle solutions;

electric vehicle computing platforms;

Jetson for robotics and other embedded platforms;

The Compute & Networking segment is comprised of our Data Center accelerated computing platforms and end-to-end networking platforms including Quantum for InfiniBand and Spectrum for Ethernet;

our NVIDIA DRIVE automated-driving platform and automotive development agreements;

Jetson robotics and other embedded platforms;

NVIDIA AI Enterprise and other software;

and cryptocurrency mining processors, or CMP.

The Graphics segment includes GeForce GPUs for gaming and PCs, the GeForce NOW game streaming service and related infrastructure, and solutions for gaming platforms;

and DGX Cloud software and services.

The Graphics segment includes GeForce GPUs for gaming and PCs, the GeForce NOW game streaming service and related infrastructure;

Quadro/NVIDIA RTX GPUs for enterprise workstation graphics;

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and Omniverse Enterprise software for building and operating metaverse and 3D internet applications.

We specialize in markets in which our computing platforms can provide tremendous acceleration for applications.

We specialize in markets where our computing platforms can provide tremendous acceleration for applications.

These platforms incorporate processors, interconnects, software, algorithms, systems, and services to deliver unique value.

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Data Center, Gaming, Professional Visualization, and Automotive.

The NVIDIA computing platform is focused 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 our energy efficient GPUs, data processing units, or DPUs, interconnects and systems, our CUDA programming model, and a growing body of software libraries, software development kits, or SDKs, application frameworks and services, which are either available as part of the platform or packaged and sold separately.

For both AI and HPC applications, the NVIDIA accelerated computing platform greatly increases computer and data center performance and power efficiency relative to conventional CPU-only approaches.

In the field of AI, NVIDIA’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 - and in turn provide predictions in production use cases.

Machine learning is a related approach that leverages algorithms as well

as data to learn how to make determinations or predictions.

HPC, which includes scientific computing, uses numerical computational approaches to solve large and complex problems.

We are engaged with thousands of organizations working on AI in a multitude of industries, from automating tasks such as consumer product and service recommendations, to chatbots for the automation of or assistance with live customer interactions, to enabling fraud detection in financial services, to optimizing oil exploration and drilling.

These organizations include the world’s leading consumer internet and cloud services companies, enterprises and startups seeking to implement AI in transformative ways across multiple industries.

We partner with industry leaders to help transform their applications or their computing platforms.

We also have 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 our GPUs, which excel at parallel workloads such as the training and inferencing of neural networks.

They are available in industry standard servers from every major computer maker and CSP, as well as in our DGX AI supercomputer, a purpose-built system for deep learning and GPU accelerated applications.

To facilitate customer adoption, we have also built other ready-to-use system reference designs around our GPUs, including HGX for hyperscale and supercomputing data centers, EGX for enterprise and edge computing, IGX for high-precision edge AI, and AGX for autonomous machines.

In fiscal year 2023, we introduced the Hopper architecture of data center GPUs, and started shipping the first Hopper-based GPU – the flagship H100.

Hopper includes a Transformer Engine, designed to accelerate the training of AI transformer models by an order of magnitude over the prior generation.

H100 is ideal for accelerating applications such as large language models, deep recommender systems, genomics and complex digital twins.

NVIDIA will offer enterprise customers NVIDIA AI cloud services directly and through our network of partners.

Examples of these services include NVIDIA DGX Cloud, which is cloud-based infrastructure and software for training AI models, and customizable pretrained AI models.

NVIDIA has partnered with leading cloud service providers to host these services in their data centers.

Our networking solutions include InfiniBand and Ethernet network adapters and switches, related software, and cables.

This has enabled us to architect end-to-end data center-scale computing platforms that can interconnect thousands of compute nodes with high-performance networking.

The NVIDIA Data Center platform is focused on accelerating the most compute-intensive workloads, such as AI, data analytics, graphics and scientific computing, delivering significantly better performance and power efficiency relative to conventional CPU-only approaches.

It is deployed in cloud, hyperscale, on-premises and edge data centers.

The platform consists of compute and networking offerings typically delivered to customers as systems, subsystems, or modules, along with software and services.

Our compute offerings include supercomputing platforms and servers, bringing together our energy efficient GPUs, DPUs, interconnects, and fully optimized AI and high-performance computing, or HPC, software stacks.

In addition, they include NVIDIA AI Enterprise software;

our DGX Cloud service;

and a growing body of acceleration libraries, APIs, SDKs, and domain-specific application frameworks.

Our networking offerings include end-to-end platforms for InfiniBand and Ethernet, consisting of network adapters, cables, DPUs, and switch systems, as well as a full software stack.

This has enabled us to architect data center-scale computing platforms that can interconnect thousands of compute nodes with high-performance networking.

While historically the server was the unit of computing, as AI and HPC workloads have become extremely large spanning thousands of compute nodes, the data center has become the new unit of computing, with networking as an integral part.

Beyond GPUs, NVIDIA has expanded its data center processor portfolio to include DPUs, currently shipping in the market, and CPUs with samples planned to ship in the first half of fiscal year 2024.

The NVIDIA Bluefield DPU is supported by foundational data-center-infrastructure-on-a-chip software, or DOCA, that lets developers build software-defined, hardware-accelerated networking, security, storage and management applications for BlueField DPUs.

Partners supporting Bluefield include many of the top security, storage and networking companies.

Our end customers include the world’s leading public cloud and consumer internet companies, thousands of enterprises and startups, and public sector entities.

We work with industry leaders to help build or transform their applications and data center infrastructure.

Our direct customers include original equipment manufacturers, or OEMs, original device manufacturers, or ODMs, system integrators and distributors which we partner with to help bring our products to market.

We also have partnerships in automotive, healthcare, financial services, manufacturing, and retail among others, to accelerate the adoption of AI.

At the foundation of the NVIDIA accelerated computing platform are our GPUs, which excel at parallel workloads such as the training and inferencing of neural networks.

They are available in the NVIDIA accelerated computing platform and in industry standard servers from every major cloud provider and server maker.

Beyond GPUs, our data center platform expanded to include DPUs in fiscal year 2022 and CPUs in fiscal year 2024.

We can optimize across the entire computing, networking and storage stack to deliver data center-scale computing solutions.

The Grace CPU is designed for AI infrastructure and high-performance computing, providing the highest performance and twice the memory bandwidth and energy-efficiency compared to today’s leading server chips.

While our approach starts with powerful chips, what makes it a full-stack computing platform is our 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.

We also offer 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, NVIDIA-Certified systems from our partners, or with NVIDIA’s cloud partners.

In addition to software that is delivered to customers as an integral part of our data center computing platform, we offer paid licenses to NVIDIA AI Enterprise, a comprehensive suite of enterprise-grade AI software;

and NVIDIA vGPU software for graphics-rich virtual desktops and workstations.

While our approach starts with powerful chips, what makes it a full-stack computing platform is our large body of software, including the CUDA parallel programming model, the CUDA-X collection of acceleration libraries, APIs, SDKs, and domain-specific application frameworks.

In addition to software delivered to customers as an integral part of our data center computing platform, we offer paid licenses to NVIDIA AI Enterprise, a comprehensive suite of enterprise-grade AI software and NVIDIA vGPU software for graphics-rich virtual desktops and workstations.

In fiscal year 2024, we launched the NVIDIA DGX Cloud, an AI-training-as-a-service platform which includes cloud-based infrastructure and software for AI, customizable pretrained AI models, and access to NVIDIA experts.

We have partnered with leading cloud service providers to host this service in their data centers.

Gaming is the largest entertainment industry, with PC gaming as the predominant platform.

Many factors propel computer gaming’s growth, including new high production value games and franchises, the continued rise of competitive gaming or eSports, social connectivity and the increasing popularity of game streamers, modders, or gamers who create game modifications, and creators.

Many factors propel its growth, including new high production value games and franchises, the continued rise of competitive gaming, or eSports, social connectivity and the increasing popularity of game streamers, modders, or gamers who remaster games, and creators.

Our gaming platforms leverage our GPUs and sophisticated software to enhance the gaming experience with smoother, higher quality graphics.

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NVIDIA RTX also features deep learning super sampling, or NVIDIA DLSS, our AI technology that boosts frame rates while generating beautiful, sharp images for games.

Our products for the gaming market include GeForce RTX and GeForce GTX GPUs for gaming desktop and laptop PCs, GeForce NOW cloud gaming for playing PC games on underpowered devices, SHIELD for high quality streaming on TV, as well as system-on-chips (SOCs) and development services for game consoles.

In fiscal year 2023, we introduced the GeForce RTX 40 Series of gaming GPUs, based on the Ada Lovelace architecture.

The 40 Series features our third generation RTX technology, third generation NVIDIA DLSS, and fourth generation Tensor Cores to deliver up to 4X the performance of the previous generation.

RTX GPUs will also accelerate a new generation of AI applications.

With an installed base of over 100 million AI capable PCs, more than 500 RTX AI-enabled applications and games, and a robust suite of development tools, RTX is already the AI PC leader.

Our products for the gaming market include GeForce RTX and GeForce GTX GPUs for gaming desktop and laptop PCs, GeForce NOW cloud gaming for playing PC games on underpowered devices, as well as SoCs and development services for game consoles.

Professional Visualization

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Many leading 3D design and content creation applications developed by our ecosystem partners now support RTX, allowing professionals to accelerate and transform their workflows with NVIDIA RTX GPUs and software.

Digital images used in product design need to mirror reality.

This requires simulating the physical behavior of light and materials, or physically-based rendering.

NVIDIA Omniverse is a virtual world simulation and collaboration platform for 3D workflows, such as building and operating metaverse and 3D internet applications, available as a software subscription for enterprise use and free for individual use.

Omniverse, virtual reality, or VR, and augmented reality, or AR, are being incorporated in a growing number of enterprise applications.

Virtual car showrooms, surgical training, architectural walkthroughs, and bringing historical scenes to life all deploy these technologies, powered by our GPUs.

NVIDIA’s Automotive market is comprised of AV, AI cockpit, electric vehicle computing platforms, and infotainment platform solutions.

We offer NVIDIA Omniverse as a development platform and operating system for building virtual world simulation applications, available as a software subscription for enterprise use and free for individual use.

Industrial enterprises are adopting Omniverse’s 3D and simulation technologies to digitalize their complex physical assets, processes, and environments – building digital twins of factories, real time 3D product configurators, testing and validating autonomous robots and vehicles, powered by NVIDIA accelerated computing infrastructure on-premises and in the cloud.

Automotive market is comprised of platform solutions for automated driving and in-vehicle cockpit computing.

Leveraging our technology leadership in AI and building on our long-standing automotive relationships, we are delivering a complete end-to-end solution for the AV market under the DRIVE Hyperion brand.

NVIDIA has demonstrated multiple applications of AI within the car:

We have 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.

Our unified AI computing architecture starts with training deep neural networks using our GPUs, and then running a full perception, fusion, planning and control stack within the vehicle on the NVIDIA DRIVE Hyperion platform.

The DRIVE Hyperion platform consists of the high-performance, energy efficient DRIVE AGX computing hardware, a reference sensor set that supports full self-driving capability as well as an open, modular DRIVE Software

The DRIVE Software platform includes DRIVE Chauffeur for autonomous driving, mapping and parking services, Drive Concierge for intelligent in-vehicle experiences, and real time conversational AI capability based on NVIDIA Omniverse Avatar software.

We are 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.

Our unified AI computing architecture starts with training deep neural networks using our Data Center computing solutions, and then running a full perception, fusion, planning, and control stack within the vehicle on the NVIDIA DRIVE Hyperion platform.

DRIVE Hyperion consists of the high-performance, energy efficient DRIVE AGX computing hardware, a reference sensor set that supports full self-driving capability as well as an open, modular DRIVE software platform for autonomous driving, mapping, and parking services, and intelligent in-vehicle experiences.

In addition, we offer a scalable data center-based simulation solution, NVIDIA DRIVE Sim, based on NVIDIA Omniverse software, for digital cockpit development, as well as for testing and validating a self-driving platform.

NVIDIA's 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.

Our 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

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Advancing the NVIDIA accelerated computing platform.

NVIDIA’s accelerated computing platform can solve complex problems in significantly less time and with lower power consumption than alternative computational approaches.

Our accelerated computing platform can solve complex problems in significantly less time and with lower power consumption than alternative computational approaches.

Indeed, it can help solve problems that were previously deemed unsolvable.

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Extending our technology and platform leadership in AI.

We provide a complete, end-to-end accelerated computing platform for deep learning and machine learning, addressing both training and inferencing.

This includes GPUs, interconnects, systems, our CUDA programming language, algorithms, libraries, and other software.

We provide a complete, end-to-end accelerated computing platform for AI, addressing both training and inferencing.

This includes full-stack data center-scale compute and networking solutions across processing units, interconnects, systems, and software.

Our compute solutions include all three major processing units in AI servers – GPUs, CPUs, and DPUs.

GPUs are uniquely suited to AI, and we will continue to add AI-specific features to our GPU architecture to further extend our leadership position.

In addition, we offer DGX Cloud, an AI-training-as-a-service platform, and NeMo – a complete solution for building enterprise-ready Large Language Models, or LLMs, using open source and proprietary LLMs created by NVIDIA and third parties.

Our AI technology leadership is reinforced by our large and expanding ecosystem in a virtuous cycle.

Our GPU platforms are available from virtually every major server maker and CSP, as well as on our own AI supercomputer.

There are 3.8 million developers worldwide using CUDA and our other software tools to help deploy our technology in our target markets.

We evangelize AI through partnerships with hundreds of universities and over 13,000 startups through our Inception program.

Our computing platforms are available from virtually every major server maker and CSP, as well as on our own AI supercomputers.

There are over 4.7 million developers worldwide using CUDA and our other software tools to help deploy our technology in our target markets.

We evangelize AI through partnerships with hundreds of universities and thousands of startups through our Inception program.

Additionally, our Deep Learning Institute provides instruction on the latest techniques on how to design, train, and deploy neural networks in applications using our accelerated computing platform.

Extending our technology and platform leadership in computer graphics.

We believe that computer graphics is fundamental to the continued expansion and evolution of computing.

We believe that computer graphics infused with AI is fundamental to the continued expansion and evolution of computing.

We apply our research and development resources to enhance the user experience for consumer entertainment and professional visualization applications and create new virtual world and simulation capabilities.

Our technologies are instrumental in driving gaming forward, as developers leverage our libraries and algorithms to deliver an optimized gaming experience on our GeForce platform.

Our computer graphics platforms leverage not only our industry-leading GeForce and NVIDIA RTX GPUs, but also optimized software stacks.

For example, GeForce Experience enhances each gamer’s experience by optimizing their PC’s settings, as well as enabling the recording and sharing of gameplay.

Our technologies are instrumental in driving the gaming, design, and creative industries forward, as developers leverage our libraries and algorithms to deliver an optimized experience on our GeForce and NVIDIA RTX platforms.

Our computer graphics platforms leverage AI end-to-end, from the developer tools and cloud services to the Tensor Cores included in all RTX-class GPUs.

For example, NVIDIA Avatar Cloud Engine, or ACE, is a suite of technologies that help developers bring digital avatars to life with generative AI, running in the cloud or locally on the PC.

GeForce Experience enhances each gamer’s experience by optimizing their PC’s settings, as well as enabling the recording and sharing of gameplay.

Our Studio drivers enhance and accelerate a number of popular creative applications.

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Advancing the leading autonomous vehicle platform.

We believe the advent of AV will soon revolutionize the transportation industry.

In our view, AI is the key technology enabler of this opportunity, as the algorithms required for autonomous driving - such as perception, localization, and planning - are too complex for legacy hand-coded approaches and will use multiple trained neural networks instead.

Therefore, we provide a full functionally safe AI-based hardware and software solution for the AV market under the DRIVE brand, which we are bringing to market through our partnerships with automotive original equipment manufacturers, or

OEMs, tier-1 suppliers, and start-ups.

We believe the advent of autonomous vehicles, or AV, and electric vehicles, or EV, is revolutionizing the transportation industry.

The algorithms required for autonomous driving - such as perception, localization, and planning - are too complex for legacy hand-coded approaches and will use multiple neural networks instead.

In addition, EV makers are looking for next-generation centralized car computers that integrate a wide range of intelligent functions into a single AI compute platform.

Therefore, we provide an AI-based hardware and software solution, designed and implemented from the ground up based on automotive safety standards, for the AV and EV market under the DRIVE brand, which we are bringing to market through our partnerships with automotive OEMs,

tier-1 suppliers, and start-ups.

Our AV solution also includes the GPU-based hardware required to train the neural networks before their in-vehicle deployment, as well as to re-simulate their operation prior to any over-the-air software updates.

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Our sales and marketing teams, located across our global markets, work closely with end customers and various industry ecosystems through our partner network.

Our partner network incorporates each industry's respective OEMs, original device manufacturers, or ODMs, system builders, add-in board manufacturers, or AIBs, retailers/distributors, ISVs, internet and CSPs, automotive manufacturers and tier-1 automotive suppliers, mapping companies, start-ups, and other ecosystem participants.

Our partner network incorporates global, regional and specialized CSPs, OEMs, ODMs, system integrators, independent software vendors, or ISVs, add-in board manufacturers, or AIBs, distributors, automotive manufacturers and tier-1 automotive suppliers, and other ecosystem participants.

Members of our sales team have technical expertise and product and industry knowledge.

We also employ a team of application engineers and solution architects to assist our partner network in designing, testing, and qualifying system designs that incorporate our platforms.

We also employ a team of application engineers and solution architects to provide pre-sales assistance to our partner network in designing, testing, and qualifying system designs that incorporate our platforms.

For example, our solution architects work with CSPs to provide pre-sales assistance to optimize their hardware and software infrastructure for generative AI and LLM training and deployment.

They also work with foundation model and enterprise software developers to optimize the training and fine-tuning of their models and services, and with enterprise end-users, often in collaboration with their global system integrator of choice, to fine-tune models and build AI applications.

We believe that the depth and quality of our design support are key to improving our partner network’s time-to-market, maintaining a high level of customer satisfaction, and fostering relationships that encourage our end customers and partner network to use the next generation of our products within each platform.

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Engineering and marketing personnel engage with key software developers to promote and discuss our platforms, as well as to ascertain individual product requirements and solve technical problems.

Our developer program makes our 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 our platforms.

Our developer program supports the development of AI frameworks, SDKs, and APIs for software applications and game titles that are optimized for our platforms.

Our 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 our platforms.

As NVIDIA’s business has evolved from a focus primarily on gaming products to broader markets, and from chips to platforms, systems and software, so, too, have our avenues to market.

Thus, in addition to sales to customers in our partner network, certain of our products are also sold direct to CSPs, enterprise customers, retail channels and consumers.

Our computing platforms serve a diverse set of markets such as consumer gaming, enterprise and cloud data centers, professional workstations, and automotive.

Our consumer products typically see stronger revenue in the second half of our fiscal year.

In addition, based on the production schedules of key customers, some of our 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.

In fiscal year 2023, our supply exceeded our demand in several areas, and our revenue did not follow historical seasonal patterns.

Our computing platforms serve a diverse set of markets such as data centers, gaming, professional visualization, and automotive.

Our desktop gaming products typically see stronger revenue in the second half of our fiscal year.

Historical seasonality trends may not repeat.

Manufacturing

We do not manufacture semiconductors used for our products.

Instead, we utilize a fabless manufacturing strategy, whereby we employ key suppliers for all phases of the manufacturing process, including wafer fabrication, assembly, testing, and packaging.

This strategy uses the expertise of industry-leading suppliers that are certified by the International Organization for Standardization in such areas as fabrication, assembly, quality control and assurance, reliability, and testing.

We utilize a fabless and contracting manufacturing strategy, whereby we employ and partner with key suppliers for all phases of the manufacturing process, including wafer fabrication, assembly, testing, and packaging.

We use the expertise of industry-leading suppliers that are certified by the International Organization for Standardization in such areas as fabrication, assembly, quality control and assurance, reliability, and testing.

Additionally, we can avoid many of the significant costs and risks associated with owning and operating manufacturing operations.

While we may directly procure certain raw materials used in the production of our products, such as memory, substrates and a variety of components, our suppliers are responsible for procurement of most of the raw materials used in the

production of our products.

As a result, we can focus our resources on product design, additional quality assurance, marketing, and customer support.

We have placed non-cancellable inventory orders for certain product components in advance of our historical lead times, paid premiums and provided deposits to secure future supply and capacity and may need to continue to do so in the future.

We have expanded our supplier relationships to build redundancy and resilience in our operations.

We utilize suppliers, such as Taiwan Semiconductor Manufacturing Company Limited and Samsung Electronics Co.

Ltd, to produce our semiconductor wafers.

We then utilize independent subcontractors and contract manufacturers, such as Amkor Technology, BYD Auto Co.

Ltd., or BYD Auto, Hon Hai Precision Industry Co., or Hon Hai, King Yuan Electronics Co., Ltd., Omni Logistics, LLC, Siliconware Precision Industries Company Ltd., and Wistron Corporation to perform assembly, testing, and packaging of most of our products and platforms.

We use contract manufacturers such as Flex Ltd., Jabil Inc., and Universal Scientific Industrial Co., Ltd., to manufacture our standard and custom adapter card products and switch systems, and Fabrinet to manufacture our networking cables.

We purchase substrates from Ibiden Co.

Ltd., Kinsus Interconnect Technology Corporation, and Unimicron Technology Corporation, and memory from Micron Technology, Samsung Semiconductor, Inc., or Samsung, and SK Hynix.

We often consign key components or materials such as the GPU, SoC, memory, and integrated circuit to the contract manufacturers.

We typically receive semiconductor products from our subcontractors, perform incoming quality assurance and configuration using test equipment purchased from industry-leading suppliers such as Advantest America Inc.

and Chroma ATE Inc., and then ship the semiconductors to contract manufacturers, such as BYD Auto and Hon Hai, distributors, motherboard and add-in card, or AIC, customers from our third-party warehouses in Hong Kong, Israel, and the United States.

Generally, these manufacturers assemble and test the boards based on our design kit and test specifications, and then ship our products to retailers, system builders, or OEMs as motherboard and AIC solutions.

While we may directly procure certain raw materials used in the production of our products, such as memory, substrates, and a variety of components, our suppliers are responsible for procurement of most raw materials used in the production of our products.

As a result, we can focus our resources on product design, quality assurance, marketing, and customer support.

In periods of growth, we may place non-cancellable inventory orders for certain product components in advance of our historical lead times, pay premiums, or provide deposits to secure future supply and capacity and may need to continue to do so.

We have expanded our supplier relationships to build redundancy and resilience in our operations to provide long-term manufacturing capacity aligned with growing customer demand.

Our supply chain is concentrated in the Asia-Pacific region.

We utilize foundries, such as Taiwan Semiconductor Manufacturing Company Limited, or TSMC, and Samsung Electronics Co., Ltd., or Samsung, to produce our semiconductor wafers.

We purchase memory from Micron Technology, Inc., SK Hynix Inc., and Samsung.

We utilize CoWoS technology for semiconductor packaging.

We engage with independent subcontractors and contract manufacturers such as Hon Hai Precision Industry Co., Ltd., Wistron Corporation, and Fabrinet to perform assembly, testing and packaging of our final products.

The market for our products is intensely competitive and is characterized by rapid technological change and evolving industry standards.

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A significant source of competition comes from companies that provide or intend to provide GPUs, CPUs, DPUs, embedded SoCs, and other accelerated, AI computing processor products, and providers of semiconductor-based high-performance interconnect products based on InfiniBand, Ethernet, Fibre Channel, and proprietary technologies.

Some of our competitors may have greater marketing, financial, distribution and manufacturing resources than we do and may be more able to adapt to customer or technological changes.

Some of our competitors may have greater marketing, financial, distribution and manufacturing resources than we do and may be more able to adapt to customers or technological changes.

We expect an increasingly competitive environment in the future.

Our current competitors include:

• suppliers and licensors of hardware and software for discrete and integrated GPUs, custom chips and other accelerated computing solutions, including solutions offered for AI, such as Advanced Micro Devices, Inc., or AMD, and Intel Corporation, or Intel;

• large cloud services companies with internal teams designing chips and software that incorporate accelerated or AI computing functionality as part of their internal solutions or platforms, such as Alibaba Group, Alphabet Inc., Amazon, Inc., and Baidu, Inc.;

• suppliers of Arm-based CPUs and companies that incorporate CPUs as part of their internal solutions or platforms;

• suppliers of SoC products that are used in servers or embedded into automobiles, autonomous machines, and gaming devices, such as Ambarella, Inc., AMD, Broadcom Inc., or Broadcom, Intel, Qualcomm Incorporated, Renesas Electronics Corporation, and Samsung, or companies with internal teams designing SoC products for internal use, such as Tesla, Inc.;

• suppliers of interconnect, switch cable solutions, and DPUs such as AMD, Applied Optoelectronics, Inc., Arista Networks, Broadcom, Cisco Systems, Inc., or Cisco, Hewlett Packard Enterprise Company, Intel, Juniper Networks, Inc., Lumentum Holdings, and Marvell Technology Group, as well as internal teams of system vendors and large cloud services companies.

Ltd., or Huawei, and Intel Corporation, or Intel;

• large cloud services companies with internal teams designing hardware and software that incorporate accelerated or AI computing functionality as part of their internal solutions or platforms, such as Alibaba Group, Alphabet Inc., Amazon, Inc., or Amazon, Baidu, Inc., Huawei, and Microsoft Corporation, or Microsoft;

• suppliers of Arm-based CPUs and companies that incorporate hardware and software for CPUs as part of their internal solutions or platforms, such as Amazon, Huawei, and Microsoft;

• suppliers of hardware and software for SoC products that are used in servers or embedded into automobiles, autonomous machines, and gaming devices, such as Ambarella, Inc., AMD, Broadcom Inc., or Broadcom, Intel, Qualcomm Incorporated, Renesas Electronics Corporation, and Samsung, or companies with internal teams designing SoC products for their own products and services, such as Tesla, Inc.;

• networking products consisting of switches, network adapters (including DPUs), and cable solutions (including optical modules) include such as AMD, Arista Networks, Broadcom, Cisco Systems, Inc., Hewlett Packard Enterprise Company, Huawei, Intel, Lumentum Holdings, and Marvell Technology Group as well as internal teams of system vendors and large cloud services companies.

Patents and Proprietary Rights

We rely primarily on a combination of patents, trademarks, trade secrets, employee and third-party nondisclosure agreements, and licensing arrangements to protect our IP in the United States and internationally.

Our currently issued patents have expiration dates from March 2023 to June 2045.

Our currently issued patents have expiration dates from February 2024 to August 2043.

We have numerous patents issued, allowed, and pending in the United States and in foreign jurisdictions.

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This decreased protection makes the possibility of piracy of our technology and products more likely.

We continuously assess whether and where to seek formal protection for particular innovations and technologies based on such factors as:

We continuously assess whether and where to seek formal protection for innovations and technologies based on such factors as:

• the location in which our products are manufactured;

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• the commercial significance of our operations and our competitors' operations in particular countries and regions.

We have licensed technology from third parties and expect to continue to enter into such license agreements.

We have licensed technology from third parties and expect to continue entering such license agreements.

Government Regulations

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During the third quarter of fiscal year 2023, the U.S.

government announced new license requirements that impact certain exports to China (including Hong Kong and Macau) and Russia of some of our data center products.

The impact of the new license requirements is difficult to quantify, and it may be challenging for us to manage our operations and forecast our operating results due to these requirements.

government, or the USG, announced licensing requirements that, with certain exceptions, impact exports to China (including Hong Kong and Macau) and Russia of our A100 and H100 integrated circuits, DGX or any other systems or boards which incorporate A100 or H100 integrated circuits.

In July 2023, the USG informed us of an additional licensing requirement for a subset of A100 and H100 products destined to certain customers and other regions, including some countries in the Middle East.

In October 2023, the USG announced new and updated licensing requirements that became effective in our fourth quarter of fiscal year 2024 for exports to China and Country Groups D1, D4, and D5 (including but not limited to Saudi Arabia, the United Arab Emirates, and Vietnam, but excluding Israel) of our products exceeding certain performance thresholds, including A100, A800, H100, H800, L4, L40, L40S and RTX 4090.

The licensing requirements also apply to the export of products exceeding certain performance thresholds to a party headquartered in, or with an ultimate parent headquartered in, Country Group D5, including China.

On October 23, 2023, the USG informed us the licensing requirements were effective immediately for shipments of our A100, A800, H100, H800, and L40S products.

Our competitive position has been harmed, and our competitive position and future results may be further harmed in the long term, if there are further changes in the USG’s export controls.

Given the increasing strategic importance of AI and rising geopolitical tensions, the USG has changed and may again change the export control rules at any time and further subject a wider range of our products to export restrictions and licensing requirements, negatively impacting our business and financial results.

In the event of such change, we may be unable to sell our inventory of such products and may be unable to develop replacement products not subject to the licensing requirements, effectively excluding us from all or part of the China market, as well as other impacted markets, including the Middle East.

While we work to enhance the resiliency and redundancy of our supply chain, which is currently concentrated in the Asia-Pacific region, new and existing export controls or changes to existing export controls could limit alternative manufacturing locations and negatively impact our business.

Refer to “Item 1A.

Risk Factors – Risks Related to Regulatory, Legal, Our Stock and Other Matters” for a discussion of this potential impact.

Additionally, our acquisitions may be subject to government regulatory reviews, and the cost to comply with such regulations or costs incurred where regulatory challenges prevent the completion of an acquisition could have a material impact on our business.

In February 2022, we announced the termination of the Share Purchase Agreement by which we would have acquired Arm due to significant regulatory challenges preventing the completion of the transaction.

We recorded an acquisition termination cost of $1.35 billion in fiscal year 2023 reflecting the write-off of the prepayment provided at signing.

Compliance with laws, rules, and regulations has not otherwise had a material effect upon our capital expenditures, results of operations, or competitive position and we do not currently anticipate material capital expenditures for environmental control facilities.

climate change, cryptocurrency, and consumer laws, could increase our costs, impact our competitive position, and otherwise may have a material adverse impact on our business, financial condition and results of operations in subsequent periods.

Compliance with existing or future governmental regulations, including, but not limited to, those pertaining to IP ownership and infringement, taxes, import and export requirements and tariffs, anti-corruption, business acquisitions, foreign exchange controls and cash repatriation restrictions, data privacy requirements, competition and antitrust, advertising, employment, product regulations, cybersecurity, environmental, health and safety requirements, the responsible use of AI, climate change, cryptocurrency, and consumer laws, could increase our costs, impact our competitive position, and otherwise may have a material adverse impact on our business, financial condition and results of operations in subsequent periods.

Refer to “Item 1A.

Risk Factors” for a discussion of these potential impacts.

Environmental, Social and Corporate Governance

Sustainability and Governance

NVIDIA invents computing technologies that improve lives and address global challenges.

Our goal is to integrate sound environmental, social and corporate governance, or ESG, principles and practices into every aspect of the Company.

The Nominating and Corporate Governance Committee of our Board of Directors is responsible for reviewing and discussing with management our practices related to ESG.

Our goal is to integrate sound environmental, social, and corporate governance principles and practices into every aspect of the Company.

The Nominating and Corporate Governance Committee of our Board of Directors is responsible for reviewing and discussing with management our practices related to sustainability and corporate governance.

We assess our programs annually in consideration of stakeholder expectations, market trends, and business risks and opportunities.

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The following section and the Human Capital Management Section below provide an overview of our principles and practices.

More information can be found on the Corporate Responsibility section of our website and in our annual Corporate Responsibility Report, or CR Report.

Information contained on our website or in our annual CR Report is not incorporated by reference into this or any other report we file with the Securities and Exchange Commission, or the SEC.

More information can be found on our website and in our annual Sustainability Report.

Information contained on our website or in our annual Sustainability Report is not incorporated by reference into this or any other report we file with the Securities and Exchange Commission, or the SEC.

Refer to “Item 1A.

Risk Factors” for a discussion of risks and uncertainties we face related to ESG.

Risk Factors” for a discussion of risks and uncertainties we face related to sustainability.

Climate Change

In the area of sustainability, we address our climate impacts across our product lifecycle and assess risks, including current and emerging regulations and market impacts.

In our CR Report published in July 2022, we published metrics related to our environmental impact for fiscal year 2022.

In the area of environmental sustainability, we address our climate impacts across our product lifecycle and assess risks, including current and emerging regulations and market impacts.

In May 2023, we published metrics related to our environmental impact for fiscal year 2023.

Fiscal year 2024 metrics are expected to be published in the first half of fiscal year 2025.

There has been no material impact to our capital expenditures, results of operations or competitive position associated with global sustainability regulations, compliance, or costs from sourcing renewable energy.

By the end of fiscal year 2025, our goal is to purchase or generate enough renewable energy to match 100% of our global electricity usage for our offices and data centers.

There has been no material impact to our capital expenditures, results of operations or competitive position associated with global environmental sustainability regulations, compliance, or costs from sourcing renewable energy.

By the end of fiscal year 2025, our goal is to purchase

or generate enough renewable energy to match 100% of our global electricity usage for our offices and data centers.

In fiscal year 2023, we increased the percentage of our total electricity use matched by renewable energy purchases to 44%.

By fiscal year 2026, we aim to engage manufacturing suppliers comprising at least 67% of NVIDIA’s scope 3 category 1 GHG emissions with goal of effecting supplier adoption of science-based targets.

Whether it is creation of technology to power next-generation laptops or designs to support high-performance supercomputers, improving energy efficiency is important in our research, development, and design processes.

GPUs are inherently more energy efficient than other forms of computing because they are optimized for throughput, performance per watt, and certain AI workloads.

GPU-accelerated computing is inherently more energy efficient than traditional computing for many workloads because it is optimized for throughput, performance per watt, and certain AI workloads.

The energy efficiency of our products is evidenced by our continued strong presence on the Green500 list of the most energy-efficient systems.

We powered 23 of the top 30 most energy efficient systems, including the top supercomputer, on the November 2022 Green500 list.

We powered 24 of the top 30 most energy efficient systems, including the top supercomputer, on the Green500 list.

We plan to build Earth-2, a digital twin of the Earth on NVIDIA AI and NVIDIA Omniverse platforms.

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We believe that our employees are our greatest assets, and they play a key role in creating long-term value for our stakeholders.

As of the end of fiscal year 2023, we had 26,196 employees in 35 countries, 19,532 were engaged in research and development and 6,664 were engaged in sales, marketing, operations, and administrative positions.

As of the end of fiscal year 2024, we had approximately 29,600 employees in 36 countries, 22,200 were engaged in research and development and 7,400 were engaged in sales, marketing, operations, and administrative positions.

The Compensation Committee of our Board of Directors assists in the oversight of policies and strategies relating to human capital management.

To be competitive and execute our business strategy successfully, we must recruit, develop, and retain talented employees, including qualified executives, scientists, engineers, and technical and non-technical staff.

As the demand for global technical talent continues to be competitive, we have grown our technical workforce and have been successful in attracting top talent to NVIDIA.

We have attracted strong talent globally with our differentiated hiring strategies for university, professional, executive and diverse recruits.

The COVID-19 pandemic created expanded hiring opportunities in new geographies and provided increased

flexibility for employees to work from locations of their choice.

Our workforce is about 80% technical and about 50% hold advanced degrees.

Earlier in fiscal year 2023, we slowed our hiring to focus on our current employees and manage costs.

We maintain a connection for global talent from universities through on-campus collaborations with professors and student organizations, as well as engagement with technical organizations and participation at industry conferences.

We have attracted talent globally through our strong employer brand and differentiated hiring strategies for college, professional, and leadership talent.

Our workforce is 83% technical and 49% hold advanced degrees.

Additionally, we have increased focus on diversity recruiting, resulting in an increase in global female hiring in each channel.

Our own employees help to surface top talent, with over 40% of our new hires in fiscal year 2024 coming from employee referrals.

Development and Retention

To support employee development, we provide opportunities to learn on-the-job through training programs, one on one coaching and ongoing feedback.

To support employee development, we provide opportunities to learn on-the-job through training courses, targeted development programs, mentoring and peer coaching and ongoing feedback.

We have a library of live and on-demand learning experiences that include workshops, panel discussions, and speaker forums.

We curate learning paths focused on our most common development needs and constantly upgrade our offerings to ensure that our employees are exposed to the most current programs and technologies available.

We create learning paths focused on our most common development needs and constantly upgrade our offerings to ensure that our employees are exposed to the most current content and technologies available.

We offer tuition reimbursement programs to subsidize educational programs and advanced certifications.

We encourage internal mobility through career coaching that advises employees on developmental activities and internal transfer opportunities.

We implemented a career coaching service to provide one-on-one guidance to employees, and encourage internal job mobility.

We have implemented specifically designed mentoring and development programs for women and employees from traditionally underrepresented groups to ensure widespread readiness for future advancement.

To evaluate employee sentiment and engagement, we use pulse surveys, a suggestion box, and an anonymous third-party platform.

Pulse surveys help us gain insight into employee experience and provide ideas so that we can prioritize areas to take action.

Pulse surveys help us gain insight into employee experience and provides employee-generated ideas so that we can take targeted action.

The suggestion box is an always-on, interactive tool where employees share their thoughts about making our company a better place to work.

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Employees receive equity, except where unavailable due to local regulations, that is tied to the value of our stock price and vests over time to retain employees while simultaneously aligning their interests with those of our shareholders.

We offer comprehensive benefits to support our employees’ and their families’ physical health, well-being and financial health, including 401(k) programs in the U.S., statutory pension programs outside the U.S., our employee stock purchase program, flexible work hours and time off, and programs to address mental health, stress, and time-management challenges.

We offer comprehensive benefits to support our employees’ and their families’ physical health, well-being, and financial health.

Programs include 401(k) programs in the U.S., statutory and supplemental pension programs outside the U.S., our employee stock purchase program, flexible work hours, and time off policies to address mental health, stress, and time-management challenges.

We evaluate our benefit offerings globally and aim to provide comparable support across the regions where we operate.

We are committed to providing tailored benefits based on community needs, including assistance for military members, additional mental health benefits, and support for new birth parents, and those who wish to become parents.

Diversity and Inclusion

We are committed to providing tailored benefits based on the needs of our Community Resource Groups and continuing our support for parents, both new birth parents and those who wish to become parents.

Our support is enhanced during times of crisis, such as war or economic volatility, to take care of our existing team of world-class talent and their families.

Diversity, Inclusion, and Belonging

We believe that diverse teams fuel innovation, and we are committed to creating an inclusive culture that supports all employees.

When recruiting for new talent or managing current talent, we focus on recruiting, developing, and retaining a more diverse workforce with a focus on those historically underrepresented in the technology field, including women, Black/African American, and Hispanic/Latino candidates.

When recruiting for new talent or developing our current employees, we strive to build a diverse talent pipeline that includes those underrepresented in the technology field, including women, Black/African American, and Hispanic/Latino candidates.

To this end, we have been:

• Partnering with institutions and professional organizations serving historically underrepresented communities;

• Assigning dedicated recruiting teams to shepherd underrepresented candidates through the interview process;

• Embedding inclusion recruiting partners throughout the business to help align candidates with internal opportunities;

• Embedding dedicated recruiting teams to business areas to shepherd underrepresented candidates through the interview process and find internal opportunities;

• Supporting the development of women employees through programs aimed at building a pipeline of future leaders;

• Providing peer support and executive sponsors for nine internal community resource groups;

• Providing peer support and executive sponsors for our internal community resource groups;

• Providing training and education to managers and peers on fostering supportive environments and recruiting for diversity;

• Ensuring we have and review a diverse pool of candidates for requisitions;

• Track equity and parity in retention, promotions, pay, and employee engagement scores;

• Measuring year over year progress and providing leadership visibility on diversity efforts.

As of the end of fiscal year 2024, our global workforce was 79% male, 20% female, and 1% not declared, with 6% of our workforce in the United States composed of Black or African American and Hispanic or Latino employees.

Health and COVID-19

We supported our people and their families in making their health and safety a top priority during fiscal year 2023 and throughout the COVID-19 pandemic to keep our workforce safe.

Hybrid Working Environment

We support a hybrid work environment, understanding that many employees want the flexibility to work in the office or from home, and make that decision based on the conditions around them at any point in time.

Steps we took to support employees working from home include:

• Home-focused health and well-being programs;

• Learning and development resources on how to work, lead and manage remotely;

• Opportunities for employees to socially connect with one another virtually.

During fiscal year 2024, we will continue a flexible work environment and have instituted Company-wide “rest days” for employees to recharge.

Flexible Working Environment

We support a flexible work environment, understanding that many employees want the ability to work from home under certain conditions.

This flexibility supports diverse hiring, retention, and employee engagement, which we believe makes NVIDIA a great place to work.

During fiscal year 2025, we will continue to have a flexible work environment and maintain our company wide 2-days off a quarter for employees to rest and recharge.

Information About Our Executive Officers

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At Cisco, Ms.

Kress was responsible for financial strategy, planning, reporting and business

development for all business segments, engineering and operations.

Kress was responsible for financial strategy, planning, reporting and business development for all business segments, engineering and operations.

From 1997 to 2010 Ms.

Kress held a variety of positions at Microsoft Corporation, or Microsoft, a software company, including, beginning in 2006, Chief Financial Officer of the Server and Tools division, where Ms.

Kress was responsible for financial strategy, planning, reporting and business development for the division.

Kress held a variety of positions at Microsoft, a software company, including, beginning in 2006, Chief Financial Officer of the Server and Tools division, where Ms.

Kress was responsible for financial

strategy, planning, reporting and business development for the division.

Prior to joining Microsoft, Ms.

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Prior to NVIDIA, he held positions in sales, marketing, and general management over a 22-year career at Sun Microsystems, Inc., a computing systems company.

Puri previously held marketing, management consulting, and product development positions at Hewlett-Packard Company, an information technology company, Booz Allen Hamilton Inc., a management and technology consulting company, and Texas Instruments Incorporated.

Puri previously held marketing, management consulting, and product development positions at Hewlett-Packard, an information technology company, Booz Allen Hamilton Inc., a management and technology consulting company, and Texas Instruments Incorporated.

Puri holds a B.S.E.E.

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She served from 2002 to 2004 as Senior Vice President and General Manager of the Electro-Optics business at Coherent, Inc., a manufacturer of commercial and scientific laser equipment.

Previously, she worked at Quantum Corp., a data protection company, as President of the Personal Computer Hard Disk Drive Division, and at Hewlett-Packard Corp.

Previously, she worked at Quantum Corp., a data protection company, as President of the Personal Computer Hard Disk Drive Division, and at Hewlett-Packard.

Shoquist holds a B.S.

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Compared sentence by sentence after normalising whitespace, quotation marks, case and digits, so re-formatting and restated figures do not read as changed language. Wording changes appear as one removal and one addition. The current filing and the prior one are authoritative.

What changed 10-K

Item 1. Business