NVIDIA: The Heart of the AI Era, Designing the Future

Architects of a New Industrial Revolution

In July 2025, NVIDIA surpassed a market capitalization of $4 trillion, reaching the pinnacle of the tech industry. This remarkable achievement is the culmination of a 30-year epic journey, marked by bold bets when others overlooked opportunities and overcoming countless crises. NVIDIA’s growth signifies not just corporate success but a fundamental shift in computing and the core engine of the generative AI era.

• NVIDIA’s 30-year growth story: From niche gaming chip company to AI giant
• The technological moat dominating the AI era: The formidable power of the CUDA ecosystem
• Ambitious vision for the future: Sovereign AI and embodied AI (robotics)

Part 1: Birth of a Giant – From Graphics Chips to GPUs

Founders’ Vision (1993)

NVIDIA was founded on April 5, 1993, by Jensen Huang, Chris Malachowsky, and Curtis Priem. Their core vision targeted the then-overlooked PC gaming market.

They accurately recognized that video games were one of the most computationally demanding yet potentially high-volume markets. Their great journey began with just $40,000 in capital.

Moment of Trial: NV1 and Bankruptcy Threat

NVIDIA’s first product, NV1, released in 1995, was an innovative design integrating 2D/3D graphics and audio but failed commercially. It was rejected by game developers because it insisted on an unfamiliar technology instead of the then-standard polygon method.

This failure nearly drove the company to bankruptcy and became a crucial “trial moment” that forged NVIDIA’s resilience.

First Victory: RIVA 128 and TSMC

Released in 1997, the RIVA 128 was NVIDIA’s first commercial success, establishing the company as a leader in the 3D graphics market. In 1998, a pivotal partnership with TSMC was formed.

The legendary story of CEO Jensen Huang’s desperate letter to TSMC Chairman Morris Chang during the bankruptcy crisis is well known. Morris Chang boldly bet on this struggling startup, providing a lifeline that allowed NVIDIA to focus solely on its core competency: chip design.

Invention of the GPU: GeForce 256 (1999)

Launched in 1999, the GeForce 256 was marketed as the “world’s first GPU.” This was a strategic redefinition of the market. The key innovation was moving geometric calculations from the CPU to an on-chip “Transform and Lighting (T&L)” engine.

This product fundamentally changed the concept of graphics processing architecture, instantly making competitors’ technologies obsolete. NVIDIA coined the term ‘GPU,’ demonstrating a long-term vision to establish a technology standard rather than seeking short-term wins.

Part 2: AI Inflection Point – AlexNet and the CUDA Moat

Pioneer of GPGPU and CUDA

NVIDIA’s AI revolution materialized with the launch of the CUDA (Compute Unified Device Architecture) platform in 2006. This was a deliberate and strategic bet to utilize GPUs for general-purpose computing (GPGPU) long before the AI boom.

NVIDIA foresaw early on that its parallel processing engines had the potential to solve far more complex problems beyond graphics.

The “Big Bang” of Modern AI: AlexNet (2012)

The 2012 ImageNet competition is recorded as the “big bang” of modern AI. The AlexNet model won with overwhelming performance, revealing the potential of deep learning to the world.

This historic achievement was made possible by training the model for 5–6 days using two NVIDIA GTX 580 3GB GPUs. AlexNet’s victory proved NVIDIA’s GPGPU strategy correct and opened the dawn of AI competition.

CUDA: An Impregnable Software Fortress

CUDA is not just an API but NVIDIA’s core competitive advantage—an impregnable “moat.” NVIDIA’s true dominance comes from the CUDA software ecosystem.

As a developer, I recall being amazed by the vast libraries and community support when first encountering CUDA. It offers a powerful developer experience beyond simple technical documentation.

Decades of optimization, thousands of community libraries, and the collective knowledge of an entire generation of AI researchers form this ecosystem. For competitors to catch up, they would need to replicate not just a chip but an entire developer nation.

Part 3: AI Engine Room – Architecture and Strategic Alliances

Symbiosis with TSMC: Decades of Partnership

The NVIDIA-TSMC partnership has evolved beyond manufacturing into joint development. Thanks to this relationship, NVIDIA gains priority access to TSMC’s most advanced custom process technologies, such as the 4NP node used in the Blackwell architecture.

Now, NVIDIA’s cuLitho platform accelerates TSMC’s chip manufacturing process. NVIDIA’s technology improves TSMC’s manufacturing, which in turn enhances next-generation NVIDIA GPU performance, creating a virtuous symbiotic cycle.

Blackwell Revolution: Breaking Physical Limits

The most decisive feature of Blackwell is its multi-die design that connects two massive dies with an ultra-high-speed 10 TB/s interface, making them operate as a single integrated GPU. This is a direct architectural solution to the physical size limits of a single chip (reticle limit).

Hopper H100 vs. Blackwell B200 Comparison

Next Bottleneck: Interconnect and Silicon Photonics

As chip performance grows stronger, bottlenecks have shifted to data movement between GPUs. NVIDIA offers 5th generation NVLink with 1.8 TB/s bandwidth and is advancing toward silicon photonics technology.

This technology transmits data using light instead of electrical signals, drastically reducing power consumption and latency, which is critical for building massive AI factories.

Part 4: AI Kingdom – Market Dominance and Financial Rise

NVIDIA’s Monopoly in Numbers

NVIDIA’s market dominance is clear in numbers. Especially in the most important and profitable data center GPU segment, it held an estimated 98% market share in 2023.

This 98% market share is the single most important number defining NVIDIA’s power.

Nation-Level Valuation and Its Meaning

NVIDIA’s roughly $4 trillion valuation surpasses Microsoft and Apple and exceeds the GDP of France or the UK. As of July 2025, it is nearly twice the market capitalization of the entire Korean stock market (KOSPI) at about $2.18 trillion.

This valuation reflects investors’ consensus that AI is a fundamental technological shift comparable to the internet and that NVIDIA holds an almost exclusive tollgate to this transition.

Part 5: Competition and Geopolitics – Navigating a Complex Landscape

Multi-Front Competitive Landscape

NVIDIA faces challengers on multiple fronts: traditional competitors (AMD), radical architectures (Cerebras), geopolitical rivals (Huawei), and even its largest customers (hyperscalers).

Geopolitical Chessboard: US-China Chip War

US export controls on China directly impacted NVIDIA, but the company responded diversely. It developed compliant chips like the lower-performance H20 and turned geopolitical risks into business opportunities through its ‘Sovereign AI’ strategy.

Part 6: Horizon of the Future – The Next Decade of AI

Sovereign AI: A New Geopolitical Frontier

‘Sovereign AI’ is NVIDIA’s core strategy to help countries build AI infrastructure while maintaining control over their own data. Through this, NVIDIA elevates itself from a mere component supplier to a strategic partner realizing national technological ambitions.

Betting on Embodied AI: Project GR00T

Project GR00T (Generalist Robot 00 Technology) is an ambitious challenge to advance AI into its next phase: physical, or ’embodied’ intelligence.

GR00T is a general foundation model designed to be the ‘mind’ of humanoid robots, capable of understanding diverse commands and learning complex tasks through human demonstrations.

This means NVIDIA is massively expanding its market from the data center’s “bit” world into the “atom” world of robotics and automation. NVIDIA aims to secure the essential platform for the embodied AI era with GR00T and Omniverse.

AI Factory Vision: The Ultimate Goal

All the elements mentioned converge on NVIDIA’s ultimate vision of becoming a turnkey provider of the ‘AI factory.’ Beyond selling chips, it aims to offer a fully vertically integrated stack covering hardware, software, systems, and data center management.

Conclusion: Key Takeaways and Next Steps

NVIDIA’s journey from a gaming chip startup to a $4 trillion AI giant is a narrative forged by long-term vision, strategic ecosystem building, and relentless execution.

Three Key Points

1. Victory of Long-Term Vision: Early investment in CUDA a decade before the AI market opened created today’s monopoly.
2. Impregnable Ecosystem: Beyond hardware performance, the decades-built CUDA software ecosystem is the true moat.
3. Expansion Toward the Future: Preparing for the next decade by expanding markets beyond data centers to sovereign AI and embodied AI (robotics).

Do you think NVIDIA’s dominance will continue, or will new competitors emerge to change the landscape? We look forward to your thoughts.