The problem currently, as people like Hotz and many others are discovering, it not the lack of CUDA. Most people use PyTorch and don't care what the underlying software is. Infact most CUDA is hand tuned to nvidia hardware anyways and is optimized to make the most on nvidia. The problem is AMD's drivers - the piece that actually sends the code to run on the GPU, tends to be broken. AMD cannot "sponsor" an outsider to fix this. A legal, but broken, AMDCUDA will not be any better than the current situation; so no, having CUDA on AMD wouldn't change anything.
The problem is not "CUDA is not AMD", the problem is AMD has not, does not, and for some reason will not invest adequately in GPU compute. CUDA is a mirage; if AMD had a similar platform someone would have done the work already to ensure PyTorch works on it. PyTorch already supports ROCm, people don't use it because the performance is bad and it's buggy. When nvidia had this problem, nvidia hired engineers to work on open source projects and debug issues in open source libraries (not even limited to AI, you will find nvidia engineers debugging issues in a wide range of CUDA projects). When AMD has this issue, they barely acknowledge it.
The problem currently, as people like Hotz and many others are discovering, it not the lack of CUDA. Most people use PyTorch and don't care what the underlying software is. Infact most CUDA is hand tuned to nvidia hardware anyways and is optimized to make the most on nvidia. The problem is AMD's drivers - the piece that actually sends the code to run on the GPU, tends to be broken. AMD cannot "sponsor" an outsider to fix this. A legal, but broken, AMDCUDA will not be any better than the current situation; so no, having CUDA on AMD wouldn't change anything.
The problem is not "CUDA is not AMD", the problem is AMD has not, does not, and for some reason will not invest adequately in GPU compute. CUDA is a mirage; if AMD had a similar platform someone would have done the work already to ensure PyTorch works on it. PyTorch already supports ROCm, people don't use it because the performance is bad and it's buggy. When nvidia had this problem, nvidia hired engineers to work on open source projects and debug issues in open source libraries (not even limited to AI, you will find nvidia engineers debugging issues in a wide range of CUDA projects). When AMD has this issue, they barely acknowledge it.