NVIDIA: The Unstoppable Force in the Tech World. You’d be a fool to bet against it.

Elie Douna
6 min readJun 8, 2024

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NVIDIA Corporation, founded in 1993 by Jensen Huang, Chris Malachowsky, and Curtis Priem, has grown from a small startup into a tech behemoth with a market capitalisation exceeding $3 trillion as of mid-2024. The company’s journey from its humble beginnings to becoming a dominant force in the technology sector is a testament to its relentless innovation, strategic foresight, and ability to adapt to changing market dynamics.

The Early Years: Pioneering GPU Technology

NVIDIA’s initial focus was on graphics-based computing and video games, a niche that would become a significant competitive advantage. The company’s breakthrough came in 1997 with the launch of the RIVA 128 GPU, which established NVIDIA as a key player in the graphics market. This was followed by the release of the GeForce 256 in 1999, which introduced onboard transformation and lighting (T&L) to consumer-grade hardware, further solidifying NVIDIA’s reputation as a pioneer in GPU technology[¹].

Diversification and Expansion

While NVIDIA initially gained recognition in the gaming industry, it successfully diversified its market reach over the years. The company expanded into data centers, professional visualization, automotive, and edge computing, capitalizing on the growing demand for high-performance computing in these sectors[²]. This diversification has broadened NVIDIA’s customer base and revenue streams, making it less reliant on any single market segment.

Dominance in the AI Market

NVIDIA’s strategic pivot towards artificial intelligence (AI) has been a game-changer. The company’s GPUs, originally designed for rendering graphics, proved to be exceptionally well-suited for the demanding computational tasks required in AI and machine learning. The introduction of CUDA (Compute Unified Device Architecture) in 2006 enabled developers to harness the immense parallel processing power of GPUs for a wide range of computational tasks, making NVIDIA GPUs the preferred choice for AI researchers and data scientists[³].

NVIDIA’s leadership in AI is further underscored by its dominant market share. As of 2024, NVIDIA controls between 70% and 95% of the market for AI chips used for training and deploying models like ChatGPT[⁴]. The company’s GPUs have become the backbone of AI infrastructure, powering applications across various industries, from healthcare and finance to automotive and manufacturing.

The Competitive Edge: Innovation and Ecosystem

NVIDIA’s success can be attributed to several key factors:

1. Technological Innovation: NVIDIA consistently invests in research and development, pushing the boundaries of what GPUs can achieve. The company’s focus on real-time ray tracing, deep learning, and AI has led to breakthroughs in visual computing, enabling more realistic graphics, accelerated data processing, and enhanced computational capabilities[²].

2. Strong Developer Ecosystem: NVIDIA has cultivated a robust developer ecosystem around its GPUs. The company provides software development kits (SDKs), libraries, and frameworks that enable developers to harness the power of GPUs for their applications. This support has fostered a vibrant community of developers who create cutting-edge applications, further driving the adoption of NVIDIA’s GPUs[³].

3. Strategic Partnerships and Collaborations: NVIDIA has formed strategic partnerships and collaborations with leading technology companies and industry players. These partnerships have allowed NVIDIA to integrate its GPU technology into a wide range of products and services, expanding its reach and influence. Notable collaborations include working with major cloud service providers to offer GPU-accelerated cloud computing and collaborating with automotive manufacturers for autonomous driving solutions[²].

Market Dominance and Lack of Competition

NVIDIA’s dominance in the GPU market is unparalleled. As of Q1 2024, the company holds an 88% market share in the desktop graphics card market, a significant increase from 80% in the previous quarter[⁴]. This near-monopoly position is a result of NVIDIA’s continuous innovation and ability to stay ahead of its competitors, primarily AMD and Intel.

While AMD and Intel continue to compete in the GPU market, they have struggled to match NVIDIA’s technological advancements and market penetration. AMD’s focus on the mid-range segment and Intel’s limited presence in the GPU market have allowed NVIDIA to maintain its leadership position. Moreover, NVIDIA’s strong financial performance, with consistently high gross margins and robust cash flow generation, further cements its competitive edge[²].

The Future of AI and NVIDIA’s Role

The ever-increasing sizes of AI models and the growing demand for high-performance computing will only intensify the need for NVIDIA’s chips. AI models are becoming more complex, with the current state-of-the-art models like GPT-4 packing more than a trillion parameters. This complexity requires immense computational power, which NVIDIA’s GPUs are uniquely positioned to provide[³].

NVIDIA’s ability to scale its GPU systems to supercomputing heights, combined with its comprehensive software stack for AI, ensures that it remains at the forefront of AI innovation. The company’s latest GPUs, such as the H100, are designed to handle the most demanding AI workloads, making them indispensable for AI research and deployment[⁴].

The Dependence of Big Tech on NVIDIA

Despite efforts by major tech companies to develop their own AI chips, NVIDIA remains the cornerstone of AI infrastructure for giants like Microsoft, OpenAI, Meta, Amazon, and Anthropic. These companies have invested heavily in NVIDIA’s GPUs to power their AI models and services. For instance, OpenAI’s ChatGPT relies on thousands of NVIDIA GPUs to function, and Amazon’s Project Ceiba uses NVIDIA’s latest Blackwell GPUs to enhance computational power[²].

While these companies are exploring in-house chip development to reduce costs and dependency, the transition is slow and fraught with challenges. NVIDIA’s 14-year head start with its CUDA platform and its continuous innovation make it difficult for competitors to catch up. Even as companies like Meta and Google develop their own AI chips, they still rely heavily on NVIDIA for their most demanding AI workloads[²].

Challenges in Sourcing NVIDIA Chips

For regular users, sourcing NVIDIA chips has become increasingly difficult due to the high demand from AI companies and the limited production capacity. The waitlist for NVIDIA’s top-of-the-line AI chips, such as the H100, can be months long, and the prices are steep, often reaching tens of thousands of dollars per chip[²]. This scarcity has led to a competitive market where only the largest tech companies can secure the necessary hardware to advance their AI initiatives.

The Impact of ChatGPT on NVIDIA

The release of ChatGPT models, such as ChatGPT-3.5 and ChatGPT-4, has had a profound impact on NVIDIA’s market position and stock performance. Research indicates that the launch of these models led to a significant positive cumulative abnormal return in NVIDIA’s stock price during the event window around their release[⁵]. The underlying technologies of artificial intelligence, such as machine learning, natural language processing, and deep learning, heavily rely on the computational performance and parallel processing capabilities of GPUs. Therefore, the release of ChatGPT models, which are significant advancements in natural language processing and AI, leads to a surge in demand for high-performance GPUs[⁵].

This increased demand directly benefits NVIDIA, as the company is a leading manufacturer of graphics processing units, and their GPUs are integral for training and running large-scale AI models like ChatGPT. This fosters a positive outlook for NVIDIA’s future revenue streams, which would increase the value of the stock and generate positive abnormal returns[⁵]. The launch of GPT and its application marked a significant milestone, bringing AI to the forefront of industry and academia[⁵].

Conclusion: Bet on NVIDIA

NVIDIA’s journey from a small startup to a tech giant is a story of relentless innovation, strategic foresight, and market dominance. The company’s leadership in GPU technology, strong developer ecosystem, and strategic partnerships have positioned it as a key player in the AI revolution. As AI models continue to grow in complexity and demand for high-performance computing increases, NVIDIA’s chips will remain essential.

Betting against NVIDIA would be a mistake. The company’s ability to adapt to changing market dynamics, coupled with its technological prowess and market leadership, ensures that it will continue to thrive in the years to come. NVIDIA is not just a leader in the tech industry; it is a force that is shaping the future of computing and AI.

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[¹]: [Graphic Cards (GPUs),NVidia and the AI Boom — LinkedIn](https://www.linkedin.com/pulse/graphic-cards-gpusnvidia-ai-boom-anurag-john)
[²]: [Nvidia grew from gaming to A.I. giant and now powering ChatGPT](https://www.cnbc.com/2023/03/07/nvidia-grew-from-gaming-to-ai-giant-and-now-powering-chatgpt.html)
[³]: [Why GPUs Are Great for AI — NVIDIA Blog](https://blogs.nvidia.com/blog/why-gpus-are-great-for-ai/)
[⁴]: [No, Nvidia Is Not A Bubble — Global X ETFs — Australia](https://www.globalxetfs.com.au/no-nvidia-is-not-a-bubble/)
[⁵]: [Impact of ChatGPT Release on High-tech Company, Evidence of NVIDIA’s Stock](https://www.clausiuspress.com/assets/default/article/2024/04/20/article_1713624768.pdf)

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Elie Douna
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Wollongong, Australia based Property Developer and Investor