Source: Slashdot: Hardware
CUDA's dominance as the de facto standard for GPU computing creates switching costs that hardware competitors like AMD and Intel can't easily overcome. Developers have spent years optimizing code for it, and retraining on alternatives carries real friction. This inverts the traditional semiconductor playbook: Nvidia wins not by manufacturing superiority but by making their platform the path of least resistance, which compounds over time as more ML infrastructure gets built on top of it. If competitors can't replicate this ecosystem lock-in, raw chip performance becomes secondary to adoption momentum.