Yes, they share "parallelism" in the most abstract sense, but beyond that, they are completely different approaches in almost every other way.

You might try to use them to accelerate the same specific task but they have very different capabilities and performance limitations/advantages. Also one is fairly generalised and one is intended to be very domain specific, so don't share all the same types of potential application.

I'm still not sure why you insist they are not comparable. GPU compute vs CPU SIMD is a very standard comparison and image recognition applications, like the one discussed, frequently support both.

Well you've added some context in which they are comparable (some types of image processing), and I agree they are comparable given that specific context. I think that probably was your point that everyone else didn't get, but your original comment was void of context and implied some level of interchangeability, but you have to keep in mind that they are used for far more than image processing (even GLSL is), and will have very different results and very different implementations for the subset of tasks that can be accelerated by both.