Part 5/15:
Cutress emphasizes that Nvidia’s dominance in AI hardware remains largely undisputed due to several factors:
Software ecosystem lock-in: Nvidia’s CUDA platform has decades of industry momentum, with over 5,000 internal engineers and a vast external developer base. The software’s maturity and compatibility make migration costly and complex, creating a significant barrier for competitors.
Ecosystem and developer familiarity: Developers are trained in Nvidia’s tools, and frameworks like TensorFlow and PyTorch optimize heavily for Nvidia hardware. Transitioning entails software re-engineering and retraining, which startups and even large AI companies are hesitant to undertake.