Ask HN: Will CUDA continue to dominate?

Most of us who have played around with deep learning frameworks know that you need a CUDA-enabled GPU to get proper hardware acceleration. And, Nvidia is the only one who produces chips with that proprietary technology.

My question is, why haven't we seen a shift away from this? It seems very limiting and closed for an ecosystem that is otherwise rather open and progressive. Will Tensorflow et al eventually adopt OpenCL / Metal / etc, or is there some reason that we'll still be stuck with CUDA in the near term?

I am just a hobbyist, so my assumptions may be completely off, and maybe these things are already happening. This has just been a question on my mind lately, and I felt that this is a good place to ask.

Thanks!