Cuda is great, but it's not strictly necessary for much of the latest AI / ML developments.
Something like the way chrome vs chromium is, or even a foundation like the linux foundation, where you have multiple distros contributing packages/etc back into the ecosystem.
I think cloud providers love exclusivity(Nvidia MSRP is significantly higher than it is available to clouds) and based on pricing compared to competitors like lambdalabs they have highest profit margin on GPU instances. Also based on availability, they likely have the highest utilisation. They definitely wouldn't want to commoditize the space. Google already has TPU that they could scale and sell to everyone but it would make the margins significantly smaller if they do it.
It may be possible to use it with consumer GPUs anyway, but many won't try because it's not officially supported.
https://rocm.docs.amd.com/en/latest/release/gpu_os_support.h... https://developer.nvidia.com/cuda-gpus