Executive Summary

NVIDIA Corporation (NVDA) has evolved from a niche graphics card manufacturer to the central pillar of the modern AI economy. We view NVIDIA not as a chip stock, but as the primary infrastructure provider for the "Industrial Revolution of Intelligence." As computing shifts from general-purpose CPUs to accelerated GPU workloads, NVIDIA's full-stack approach (Chips + CUDA + Systems) provides a defensible moat against hyperscaler custom silicon.

1. The Accelerated Computing Shift

The fundamental law of computing is changing. Moore's Law for CPUs has slowed, but the demand for compute is exponential.

• Unit of Compute: The data center is becoming the new "unit of compute." NVIDIA's approach treats the entire data center as a single superchip.
• Efficiency: Accelerated computing is orders of magnitude more energy-efficient and cost-effective for AI workloads than traditional CPUs.
• Total Cost of Ownership (TCO): While GPU sticker prices are high, the TCO for training massive models is lowest on NVIDIA hardware due to throughput speed.

2. The CUDA Moat

The software ecosystem remains NVIDIA's strongest competitive advantage.

• Developer Lock-in: Millions of developers have built applications on CUDA. Porting this to AMD's ROCm or other frameworks entails significant friction and refactoring.
• Optimization: Every major AI framework (PyTorch, TensorFlow) is optimized for CUDA first.
• Network Effects: The more researchers use NVIDIA, the more libraries are built, reinforcing the ecosystem dominance.

3. Sovereign AI & Enterprise Demand

Demand is diversifying beyond just the US Hyperscalers (Microsoft, Amazon, Google).

• Sovereign AI: Nations are building their own domestic AI infrastructure to protect data sovereignty (e.g., Japan, France, Middle East). This represents a multibillion-dollar incremental market.
• Enterprise AI: As Global 2000 companies move from "experimentation" to "production" (using RAG on proprietary data), inference demand will explode.

Risks to the Thesis

1. Hyperscaler Vertical Integration: AMZN (Trainium), GOOGL (TPU), and MSFT (Maia) are actively building custom silicon to reduce reliance on NVIDIA.
2. China Restrictions: Increasing export controls could permanently impair ~20% of the addressable market.
3. Cyclicality: If AI monetization trails Capex spending, a "digestion phase" could lead to a sharp cyclical drawdown in GPU orders.

Conclusion

We remain Bullish on NVDA. The transition to accelerated computing is a secular trend that will last a decade. While volatility is expected, NVIDIA's technological lead in the Blackwell era ensures they capture the lion's share of value in the near to medium term.