While purpose-built chips (ASICs) like Google's TPU are efficient, the AI industry is still in an early, experimental phase. GPUs offer the programmability and flexibility needed to develop new algorithms, as ASICs risk being hard-coded for models that quickly become obsolete.

By funding and backstopping CoreWeave, which exclusively uses its GPUs, NVIDIA establishes its hardware as the default for the AI cloud. This gives NVIDIA leverage over major customers like Microsoft and Amazon, who are developing their own chips. It makes switching to proprietary silicon more difficult, creating a competitive moat based on market structure, not just technology.

New AI models are designed to perform well on available, dominant hardware like NVIDIA's GPUs. This creates a self-reinforcing cycle where the incumbent hardware dictates which model architectures succeed, making it difficult for superior but incompatible chip designs to gain traction.

While known for its GPUs, NVIDIA's true competitive moat is CUDA, a free software platform that made its hardware accessible for diverse applications like research and AI. This created a powerful network effect and stickiness that competitors struggled to replicate, making NVIDIA more of a software company than observers realize.

Top-tier kernels like FlashAttention are co-designed with specific hardware (e.g., H100). This tight coupling makes waiting for future GPUs an impractical strategy. The competitive edge comes from maximizing the performance of available hardware now, even if it means rewriting kernels for each new generation.

The massive demand for GPUs from the crypto market provided a critical revenue stream for companies like NVIDIA during a slow period. This accelerated the development of the powerful parallel processing hardware that now underpins modern AI models.

The exponential growth in AI required moving beyond single GPUs. Mellanox's interconnect technology was critical for scaling to thousands of GPUs, effectively turning the entire data center into a single, high-performance computer and solving the post-Moore's Law scaling challenge.

The current AI landscape mirrors the historic Windows-Intel duopoly. OpenAI is the new Microsoft, controlling the user-facing software layer, while NVIDIA acts as the new Intel, dominating essential chip infrastructure. This parallel suggests a long-term power concentration is forming.

A key component of NVIDIA's market dominance is its status as the single largest buyer (a monopsony) for High-Bandwidth Memory (HBM), a critical part of modern GPUs. This control over a finite supply chain resource creates a major bottleneck for any potential competitor, including hyperscalers.