As well the percentage of games using every last new feature and technology that comes along shrinks progressively with time. You could add matrix only units, but competitive e-sorts games aren't going to use those very meaningfully, if at all. Adding those isn't going to get fps up in Valorant or Dota 2 at low settings; and since you at least theoretically want precisely accurate per pixel information in those games, then are people buying GPUs really going to use AI upscaling which by it's nature is going to give you false information from a bad guess?
I don't know the answer to that. But I do see the use case for such units as at least semi limited for the next seven+ years. Is it worth it for AMD to add those units to a GPU? I'd be unsure it is at the moment. Nvidia has successfully driven the niche high end GPU market crazy for "Raytracing", but their TPUs have gone largely unnoticed at the moment, and with something that abstract I'm not sure how successful a PR campaign in that direction would work.
Yea, there are definitely niches for different markets here and it does look like AMD is aiming for hitting maximum framerates (eSports scene) while Nvidia is trying to spearhead new rendering methods.
Neither is wrong, it's just catering to different markets. Nvidia took a huge risk to lead this charge on their own. And other companies will be more than willing to dive in to compete after nvidia has done the heavy lifting. There's no reason for AMD to enter the scene unless they must, I suppose is the best way to look at it.
I still think there is a future for accelerators in the AI space, there's a lot more than can be used there with Deep Learning than just super resolution. It could be used for animation, simulations, AI, etc that, it has the potential to provide some very good benefits without necessarily increasing cost on studios to support those AIs. I think that's still something that could be appreciated by eSports players etc. Not everyone wants to play on the lowest of low settings.