Those advantages are especially valuable during the artificial intelligence (AI) boom, as speed and efficiency are key points of differentiation. Developers also favor CUDA because they are accustomed to using it and it's a big time-saver for them.
Nvidia released CUDA in 2006 and has continued to upgrade and build an ecosystem around it since then. Other AI companies are still trailing far behind it. Developers don't even need to write code for CUDA because it already has libraries of programs built on it, called CUDA-X libraries.
Overall, CUDA reinforces the GPU ecosystem that has made Nvidia so successful. Moreover, it helps deliver higher performance and accelerated computing.
How CUDA gives Nvidia a competitive advantage
Nvidia popularized the GPU in 1999, and CUDA, which it introduced in 2006, has arguably been its most important step in establishing itself in the GPU market. Recognizing the significant demand for accelerated computing empowered by GPUs, Nvidia developed libraries for applications like deep learning and linear algebra that have helped form the building blocks for its work in AI.