There's a deep, forbidding moat that surrounds Nvidia, and it has nothing to do with hardware.
CUDA is the software platform that lets developers write code for Nvidia GPUs. It launched in 2006, and since then, millions of developers have built their careers around it. Every AI framework, every machine learning library, every research project has been optimized for CUDA first.
That's why competitors struggle to break in, even when they build faster or cheaper chips. The switching cost isn't just buying new hardware. It's rewriting years of code, retraining teams, and risking compatibility issues with the entire AI stack.
For anyone building AI products, this matters because your infrastructure choices compound over time. The tools you pick today determine what's easy and what's painful three years from now. CUDA's dominance means Nvidia can charge premium prices because the alternative is rebuilding your entire development workflow.
This is why Nvidia keeps winning even as AMD, Intel, and startups throw billions at the AI chip market. They're not just competing with silicon. They're competing with two decades of software lock-in and a developer ecosystem that's already made its choice.
