AMD and OpenCL have fallen desperately behind NVidia and CUDA in terms of industry adoption. CIDA is so far the industry standard for machine learning on GPUs. For example tensor flow had a GPU backend using CUDA. Last time I looked OpenCL support was in alpha stages.

This software platform dominance fueled a lot of hype around NVidia, but I'm not sure how much it contributed to revenue. Research and specialized data centers may still be a small percentage of sales compared to mass market. But Intel and AMD both understand that if they don't catch up they will never recover. They are gearing up for a future where every customer device needs some efficient machine learning inference hardware. Then data centers will need to purchase mind boggling amounts of throughput computing for training from streams of incoming data. I'm sure each company is planning hardware derived from current GPUs but more power efficient for the type of number crunching ML algorithms.