who-owns-nvidia

Who Owns Nvidia?

The top individual shareholder of NVIDIA is Jen-Hsun Huang, founder and CEO of the company, with 87,521,722 shares giving him 3.50% ownership. Followed by Mark A. Stevens, venture capitalist and a partner at S-Cubed Capital, who was part of the NVIDIA board in 2008 and previously served as a director from 1993 to 2006, with 6,258,803 shares. Institutional investors comprise The Vanguard Group, Inc, with 196,015,550, owning 7.83%. BlackRock, Inc., with 177,858,484, owns 7.10%. And FMR LLC (Fidelity Institutional Asset Management) with 158,039,922, owning 6.31%.

AspectDescriptionAnalysisExamples
Products and ServicesNVIDIA specializes in graphics processing units (GPUs), artificial intelligence (AI) hardware, and software solutions. Key products include GPUs for gaming, data centers, and professional visualization; AI hardware such as the NVIDIA A100 and NVIDIA DGX systems; software like NVIDIA CUDA and NVIDIA Deep Learning AI; and platforms for autonomous vehicles and edge computing.NVIDIA’s product portfolio centers around GPUs for various applications, including gaming, data centers, and professional visualization. AI hardware, such as the NVIDIA A100 and DGX systems, supports deep learning and AI workloads. Software solutions like CUDA and Deep Learning AI enable developers to harness GPU power. NVIDIA’s platforms cater to autonomous vehicles and edge computing. The company addresses diverse industries, from gaming to AI research and autonomous transportation.GPUs for gaming, data centers, and professional visualization, AI hardware (e.g., NVIDIA A100, DGX systems), software solutions (e.g., CUDA, Deep Learning AI), platforms for autonomous vehicles and edge computing.
Revenue StreamsNVIDIA generates revenue through the sale of GPUs, AI hardware, and software solutions. Its primary revenue sources include GPU sales for gaming, data centers, and professional visualization, as well as AI hardware and software sales. The company also earns income from licensing its GPU technology to other manufacturers and through partnerships for AI and GPU-powered solutions.Primary revenue sources encompass GPU sales for gaming, data centers, and professional visualization, as well as AI hardware and software sales. Licensing of GPU technology to other manufacturers and partnerships for AI and GPU-powered solutions contribute to revenue. NVIDIA’s diverse revenue streams support its financial stability.Revenue from GPU sales (gaming, data centers, professional visualization), AI hardware and software sales, licensing of GPU technology to other manufacturers, partnerships for AI and GPU-powered solutions.
Customer SegmentsNVIDIA serves a wide range of customer segments, including gamers seeking high-performance graphics cards, data center operators requiring GPU acceleration for AI and scientific workloads, professionals in industries like design and simulation, researchers in AI and deep learning, and automotive companies developing autonomous vehicles. The company’s technology also reaches partners and developers in the AI and GPU ecosystem.NVIDIA’s customer segments encompass gamers seeking high-performance GPUs for gaming experiences, data center operators utilizing GPUs for AI and scientific workloads, professionals in design and simulation industries, researchers in AI and deep learning, and automotive companies working on autonomous vehicles. NVIDIA’s technology extends to partners and developers within the AI and GPU ecosystem, fostering innovation and adoption across various industries.Gamers (seeking high-performance GPUs for gaming), data center operators (utilizing GPUs for AI and scientific workloads), professionals in design and simulation industries, researchers in AI and deep learning, automotive companies (developing autonomous vehicles), partners and developers in the AI and GPU ecosystem.
Distribution ChannelsNVIDIA distributes its products primarily through original equipment manufacturers (OEMs), system integrators, and retailers for gaming GPUs. For data centers and AI hardware, the company collaborates with data center operators and partners. Additionally, NVIDIA offers software and tools for developers through its website and developer community.Distribution channels involve OEMs, system integrators, and retailers for gaming GPUs, enabling broad accessibility to consumers. For data centers and AI hardware, NVIDIA collaborates with data center operators and partners to integrate its solutions. Software and tools for developers are accessible through the company’s website and developer community, fostering a supportive ecosystem.Distribution through OEMs, system integrators, and retailers for gaming GPUs, collaboration with data center operators and partners for data centers and AI hardware, accessibility to software and tools for developers through the website and developer community, fostering a supportive ecosystem.
Key PartnershipsNVIDIA forms partnerships with original equipment manufacturers (OEMs) and system integrators to manufacture and distribute GPUs. The company also collaborates with data center operators and cloud providers to integrate its AI hardware solutions. In the AI and deep learning space, NVIDIA partners with universities, research institutions, and software developers to advance the field. Additionally, partnerships with automotive companies support the development of AI-powered autonomous vehicles.Collaborations with OEMs and system integrators facilitate the manufacturing and distribution of GPUs. Partnerships with data center operators and cloud providers enable the integration of AI hardware solutions. In the AI and deep learning domain, NVIDIA collaborates with universities, research institutions, and software developers to advance the field. Partnerships with automotive companies support the development of AI-powered autonomous vehicles. NVIDIA’s partnerships drive innovation and adoption across diverse industries.Collaborations with OEMs and system integrators for GPU manufacturing and distribution, partnerships with data center operators and cloud providers for AI hardware integration, collaborations with universities, research institutions, and software developers in the AI and deep learning space, partnerships with automotive companies for AI-powered autonomous vehicles.
Key ResourcesNVIDIA’s key resources include its GPU technology, AI hardware and software solutions, a vast and engaged developer community, partnerships with OEMs and data center operators, technology infrastructure for data processing and research, a strong brand identity associated with innovation and performance, and a vision for advancing AI and deep learning technologies.GPU technology forms the core resource, supporting various applications. AI hardware and software solutions empower deep learning and AI workloads. A vast developer community contributes to the ecosystem’s vitality. Partnerships with OEMs and data center operators expand NVIDIA’s reach. Technology infrastructure ensures data processing and research capabilities. A strong brand identity fosters trust and loyalty. NVIDIA’s vision for advancing AI and deep learning technologies guides its resources and efforts.GPU technology for diverse applications, AI hardware and software solutions for deep learning and AI workloads, a vast and engaged developer community contributing to ecosystem vitality, partnerships with OEMs and data center operators expanding reach, technology infrastructure for data processing and research capabilities, a strong brand identity associated with innovation and performance, a vision for advancing AI and deep learning technologies guiding resources and efforts.
Cost StructureNVIDIA incurs costs related to research and development (R&D) for GPU and AI technology innovation, manufacturing and production of GPUs and hardware, marketing and advertising expenses to promote products and engage with the developer community, employee salaries and benefits for a diverse workforce, acquisitions and investments in technology companies, and potential regulatory and compliance costs.Costs related to R&D are essential for GPU and AI technology innovation, driving product development. Manufacturing and production costs cover the production of GPUs and hardware solutions. Marketing and advertising expenses promote products and engage with the developer community. Employee salaries and benefits support staff in various roles. Acquisitions and investments in technology companies foster innovation and ecosystem growth. Regulatory and compliance costs may arise to meet legal and industry requirements.Costs related to research and development (R&D) for GPU and AI technology innovation, manufacturing and production of GPUs and hardware solutions, marketing and advertising expenses for product promotion and developer community engagement, employee salaries and benefits covering diverse roles, acquisitions and investments in technology companies for innovation and ecosystem growth, potential regulatory and compliance costs to meet legal and industry requirements.
Competitive AdvantageNVIDIA’s competitive advantage lies in its leadership in GPU technology, a vast and engaged developer community, a strong brand identity associated with innovation and performance, partnerships with OEMs and data center operators, a diverse product portfolio catering to gaming, data centers, and AI, and a vision for advancing AI and deep learning technologies. The company’s technology powers a wide range of industries, from gaming to scientific research, and enables AI-driven innovation across the globe.Leadership in GPU technology ensures high-performance solutions for various applications. A vast developer community fosters innovation and application development. A strong brand identity fosters trust and loyalty among users. Partnerships with OEMs and data center operators expand NVIDIA’s reach and adoption. A diverse product portfolio caters to gaming, data centers, and AI, driving revenue diversification. NVIDIA’s vision for advancing AI and deep learning positions it as a leader in shaping the future of technology and innovation. The company’s competitive advantage lies in powering industries and driving AI-driven progress worldwide.Leadership in GPU technology for high-performance solutions across applications, a vast and engaged developer community fostering innovation and application development, a strong brand identity fostering trust and loyalty, partnerships with OEMs and data center operators expanding reach and adoption, a diverse product portfolio catering to gaming, data centers, and AI driving revenue diversification, a vision for advancing AI and deep learning positioning NVIDIA as a leader in shaping the future of technology and innovation across industries and worldwide.

Origin Story

Back in 1994, Sony used the term GPU as part of the launch of its PS1. Yet, by 1999 NVIDIA popularized the term with the launch of its GeForce 256.

The launch of the GeForce 256 was highly effective from a marketing standpoint. Indeed, defined as “the world’s first GPU,” it created a category in its own right. 

Eventually, NVIDIA’s GPU would become a standard for various industries (from gaming to AI).

gpu
Graphics processing units (GPUs) were initially conceived to accelerate 3D graphic rendering in video games. However, more recently, they have become popular in artificial intelligence and machine learning (ML) contexts. In fact, GPUs are critical components of AI Supercomputers, like Azure, which are powering up the current AI revolution.

By 2006, NVIDIA launched CUDA, a general-purpose programming model.

This accelerated the development of applications for various industries, from aerospace bio-science research to mechanical and fluid simulations and energy exploration. 

NVIDIA has been the leader in the GPU space, starting with a focus on PC graphics.

The company focuses on 3D graphics due to the exponential growth in the gaming market.

At the same time, NVIDIA also represents the physical platform of entire industries.

From scientific computing, artificial intelligence, AI, data science, autonomous vehicles, AV, robotics, and augmented and virtual reality, NVIDIA gives us an understanding of how tomorrow’s industries will evolve based on the physical capabilities offered by its chips. 

While GPU was initially applied primarily to gaming, running AI/ML algorithms that required massive computing power over the years became increasingly relevant.

Thus, GPU has become the basis for the most promising industries of this decade: AI, autonomous driving, robotics, AR/VR, and more. 

While NVIDIA is a GPU design company, it has followed a platform strategy. In short, it has leveraged hardware and software (with its stack made of algorithms and libraries) with the ability to serve several industries and a few other promising industries of the future. 

Background

Nvidia Corporation is a multinational tech company that specializes in designing and manufacturing graphics processing units (GPUs) and other computer-related hardware and software products. 

Founded in 1993 by Jensen Huang, Curtis Priem, and Chris Malachowsky, the company has become a leader in GPUs for diverse applications such as gaming, entertainment, scientific computing, and artificial intelligence.

Early years

In the early 1990s, Huang, Priem, and Malachowsky were young engineers who laid the foundations for Nvidia at a Denny’s restaurant in San Jose, California. 

Over endless cups of coffee, the trio discussed a shared belief that accelerated, graphics-based computing was the way of the future.

At the time, most chips were designed for scientific and engineering applications, but there was a growing demand for faster and more realistic graphics in consumer products.

As a result, they saw an opportunity to create a new type of chip specifically designed for gaming and multimedia applications. 

Nvidia is founded

Nvidia was started with just $40,000 and the company initially had no name. In an interview with Fortune, Huang explained that “We couldn’t think of one, so we named all of our files NV, as in ‘next version’”. 

But when the company was incorporated, the co-founders were forced to come up with a name.

They reviewed a list of words with the letters “n” and “v” and eventually settled on Nvidia – inspired by the Latin word for envy invidia.

NV1

Since video games were one of the most computationally challenging problems, the initial focus was on the gaming industry as a way to reach large markets, drive sales, and fund subsequent research and development. 

After a $10 million investment from Sequoia and others in 1995, Nvidia released the NV1 multimedia card for personal computers.

Despite the fact that 3D games were starting to gain traction, the NV1 was a commercial failure.

Graphics and audio performance were lackluster, and the various hardware components made it more expensive than competitors.

However, Nvidia refined the card over four subsequent releases which enabled it to narrowly avert bankruptcy.

One release in particular, the RIVA 128, proved to be a breakout success because it was 400% faster than any GPU on the market.

IPO and GeForce 256

Nvidia went public on January 22, 1999, at $12 per share. By the end of the day, however, the company’s share price had increased 64% to close at $19.68.

This gave Nvidia a market value of $626.1 million

Revenue growth was also substantial which reflected growth in the graphics industry and also wider acceptance of Nvidia’s RIVA processors.

The company posted revenue of $158.2 million for the fiscal year 1999 compared to just $13.3 million in 1998.

The GeForce 256 was released later in 1999. Billed as the world’s first GPU, it earned Nvidia more industry clout but put it in direct competition with 3dfx Interactive and its popular Voodoo technology.

Nvidia ultimately triumphed and acquired the rapidly declining 3dfx and its assets on December 15, 2000. 

Microsoft deal 

Later that year, Microsoft selected Nvidia to develop graphic cards for its Xbox video game consoles. The company earned a $200 million advance from Microsoft to develop a media communications processor (MCP) that many considered to be a “super-chip”. 

While Nvidia developed the MCP to be used in Xbox consoles, it was designed to be used in future PC architecture and information-appliance components.

In 2001, the completed MCP became known as the GeForce 3 GPU.

In the next few years, Nvidia aggressively protected its patents and made several acquisitions. Sony then announced in December 2004 that Nvidia would assist with its graphics processors for use in PlayStation 3 consoles.

In 2007, Forbes magazine named Nvidia its company of the year. The 2010s were marked by a multi-billion dollar deal with Intel and the company’s decision to focus on the three markets of mobile devices, video gaming, and automotive electronics.

NVIDIA and the AI revolution

Thus, NVIDIA has found itself incredibly well-positioned for the AI revolution, which was spurred again by the meteoric rise of ChatGPT.

chatgpt-growth
ChatGPT’s meteoric rise saw the app grow from almost 37 million global searches per month in December to over 83 million global searches in January. By February, it passed almost 154 million searches.

Indeed, already by early 2023, the company has shifted most of its revenue generation from graphics (gaming) to computing and to network (AI).

nvidia-revenue-breakdown
NVIDIA generated almost $27 billion in revenue in 2023, of which $15 billion came from computing and networking and $11 billion from graphics. Opposite to 2022, where of $27 billion in revenue, over $15.8 billion came from Graphics and $11 billion from computing and networking. With the explosion of AI, the computing segment has become the main driver of NVIDIA’s growth.

This shift has happened because the current AI systems are built on top of AI supercomputers (capable of parallel computations), where the GPU has become the key ingredient.

current-AI-paradigm

In fact, a powerful AI supercomputer might require thousands of GPUs at once to enable the pre-training of large language models.

Below is the entire workflow of how ChatGPT went from pre-training to production, thanks to NVIDIA’s AI supercomputer, which the main component (the GPU) was provided.

how-does-chat-gpt-work
ChatGPT leverages GPT-3.5 as the underlying model, while it uses an additional layer, a model called InstructGPT, which has become a standard within the OpenAI large language models. InstructGPT optimizes conversational abilities and improves on top of the existing GPT models.

Key takeaways:

  • Nvidia Corporation is a multinational tech company that specializes in designing and manufacturing graphics processing units (GPUs) and other computer-related hardware and software products. 
  • Since video games were one of the most computationally challenging problems of the time, Nvidia’s initial focus was on the gaming industry as a way to reach large markets, drive sales, and fund subsequent research and development. 
  • The increase in revenue was substantial in 1999 which reflected growth in the graphics industry and also wider acceptance of Nvidia’s RIVA processors. The GeForce 256 was released later in 1999. Billed as the world’s first GPU, the GeForce 256 earned Nvidia more industry clout and set it on a path to sustained success.

Key Highlights

  • Founder and Top Shareholder: Jen-Hsun Huang is the founder and CEO of NVIDIA, owning 3.50% of the company’s shares.
  • Major Shareholders: Mark A. Stevens, a venture capitalist, and institutional investors like The Vanguard Group, BlackRock, and FMR LLC own significant portions of NVIDIA’s stocks.
  • GPU Popularization: NVIDIA popularized the term “GPU” with the launch of its GeForce 256 in 1999, creating a new category in computer graphics.
  • Diverse Applications: Initially focused on gaming, NVIDIA’s GPUs are now essential in industries like AI, scientific computing, and autonomous vehicles.
  • Platform Strategy: NVIDIA follows a platform strategy, leveraging hardware and software to serve multiple industries and promising future sectors.
  • Early Years: Founded in 1993 by Jensen Huang, Curtis Priem, and Chris Malachowsky, NVIDIA aimed to create chips for gaming and multimedia applications.
  • Rise to Success: After overcoming challenges with early products, NVIDIA’s RIVA 128 GPU was a breakout success and led to the IPO in 1999.
  • Acquisitions and Growth: Acquiring 3dfx Interactive and partnering with Microsoft for Xbox consoles fueled NVIDIA’s growth in the 2000s.
  • AI Revolution: NVIDIA’s GPUs became key components in AI supercomputers, driving the company’s shift from gaming to computing and networking.
  • ChatGPT Impact: The success of OpenAI’s ChatGPT, powered by NVIDIA’s AI supercomputer, accelerated the shift towards computing and networking.
  • Revenue Growth: In 2023, NVIDIA generated almost $27 billion in revenue, with computing and networking surpassing graphics as the main driver of growth.

Connected To NVIDIA

NVIDIA Business Model

nvidia-business-model
NVIDIA is a GPU design company, which develops and sells enterprise chips for industries spacing from gaming, data centers, professional visualizations, and autonomous driving. NVIDIA serves major large corporations as enterprise customers, and it uses a platform strategy where it combines its hardware with software tools to enhance its GPUs’ capabilities.

Who Owns NVIDIA

who-owns-nvidia
The top individual shareholder of NVIDIA is Jen-Hsun Huang, founder, and CEO of the company, with 87,521,722 shares giving him 3.50% ownership. Followed by Mark A. Stevens, venture capitalist and a partner at S-Cubed Capital, who was part of the NVIDIA board in 2008 and previously served as a director from 1993 to 2006, with 6,258,803 shares. Institutional investors comprise The Vanguard Group, Inc, with 196,015,550, owning 7.83%. BlackRock, Inc., with 177,858,484, owns 7.10%. And FMR LLC (Fidelity Institutional Asset Management) with 158,039,922, owning 6.31%.

NVIDIA Revenue

nvidia-revenue
NVIDIA generated almost $27 billion in revenue in 2023, compared to the same revenue value in 2022 and over $16.6 billion in 2021.

NVIDIA Revenue Breakdown

nvidia-revenue-breakdown
NVIDIA generated almost $27 billion in revenue in 2023, of which $15 billion came from computing and networking and $11 billion from graphics. Opposite to 2022, where of $27 billion in revenue, over $15.8 billion came from Graphics and $11 billion from computing and networking. With the explosion of AI, the computing segment has become the main driver of NVIDIA’s growth.

NVIDIA Revenue By Segment

nvidia-revenue-by-segment
NVIDIA generated almost $27 billion in revenue in 2023, of which over $15 billion came from competing & networking and $11.9 billion from graphics. NVIDIA, through its GPU, is powering up the AI supercomputing revolution, which is part of the current AI paradigm.

NVIDIA Profits

nvidia-profitability
NVIDIA generated $4.37 billion in net profits in 2023, compared to over $9.7 billion in profits in 2022, and $4.3 billion in 2021.

NVIDIA Employees

nvidia-rd-employees
In 2023, of 26,196 employees, 19,532 employees were engaged in R&D (74.5% of the total workforce). In 2022, 16,242 NVIDIA employees (72% of the workforce) were involved in R&D.

NVIDIA Revenue Per Employee

nvidia-revenue-per-employee
In 2023, NVIDIA generated $1,029,699 per employee, compared to almost $1.2 million in revenue per employee in 2022.

Connected AI Visual Stories

AI Supercomputer

ai-supercomputer

Transformer

transformer-architecture
The transformer architecture – sometimes referred to as the transformer neural network or transformer model – is an architecture that endeavors to solve sequence-to-sequence tasks while easily handling long-range dependencies.

GPU vs. TPU

GPU-vs-TPU

OpenAI Business Model

how-does-openai-make-money
OpenAI has built the foundational layer of the AI industry. With large generative models like GPT-3 and DALL-E, OpenAI offers API access to businesses that want to develop applications on top of its foundational models while being able to plug these models into their products and customize these models with proprietary data and additional AI features. On the other hand, OpenAI also released ChatGPT, developing around a freemium model. Microsoft also commercializes opener products through its commercial partnership.

OpenAI/Microsoft

openai-microsoft
OpenAI and Microsoft partnered up from a commercial standpoint. The history of the partnership started in 2016 and consolidated in 2019, with Microsoft investing a billion dollars into the partnership. It’s now taking a leap forward, with Microsoft in talks to put $10 billion into this partnership. Microsoft, through OpenAI, is developing its Azure AI Supercomputer while enhancing its Azure Enterprise Platform and integrating OpenAI’s models into its business and consumer products (GitHub, Office, Bing).

Stability AI Business Model

how-does-stability-ai-make-money
Stability AI is the entity behind Stable Diffusion. Stability makes money from our AI products and from providing AI consulting services to businesses. Stability AI monetizes Stable Diffusion via DreamStudio’s APIs. While it also releases it open-source for anyone to download and use. Stability AI also makes money via enterprise services, where its core development team offers the chance to enterprise customers to service, scale, and customize Stable Diffusion or other large generative models to their needs.

Stability AI Ecosystem

stability-ai-ecosystem

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who-owns-nvidia
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Who Owns Snapchat

who-owns-snapchat
Evan Spiegel and Robert Cornelius Murphy are the co-founders and, respectively, CEO and CTO of Snapchat. Evan Spiegel owns 3% of Class A stocks, 25.7% of Class B stocks, and 53.4% of Class C stocks for a 53.2% voting power, whereas Robert Murphy owns 6% of Class A stocks, 25.7% of Class B stocks, and 46.6% of Class C stocks for a 46.6% voting power. Snapchat runs an advertising-based business model.

Who Owns Coinbase

who-owns-coinbase
Main individual shareholders comprise co-founders Brian Armstrong (59.5% voting power), Frederick Ernest Ehrsam (26.1% voting power), and other individual investors such as Surojit Chatterjee (current CPO “poached” from Google), Paul Grewal (former magistrate who joined Coinbase as Chief Legal Officer), and venture capitalists who early on invested on Coinbase, like Marc Andreessen (founder of a16z) and Fred Wilson (founder of Union Square Ventures), together with venture capital firms like Andreessen Horowitz, Paradigm, Ribbit Capital and Union Square Ventures.

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