Most developers are trained on CUDA & its documentation & community support are 10x to 20x larger than any alternative.
CUDA has a flywheel which CEO Jensen Huang describes as a seif sustaining cycle where a massive installed base of hundreds of millions of GPUs attract developers, leading to software breakthroughs that further drive hardware sales.
With over 20 years track record, Nvidia has built optimised libraries such as cuDNN, TensorRT that are deeply embedded in production code. Changing this pipeline on other hardware introduces significant operational risk & cost.
NVIDIA also has a full stack strategy, positioning its Vera Rubin platform & NVLink networking as integrated AI Factories which competitors often struggle to match.
@Tiger_comments @TigerStars @Tiger_SG
Modify on 2026-04-23 08:32
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