I definitely buy that there is a use case for this kernel. Whenever I see this kind of optimization, I feel like it's at least flirting with classical feature engineering. Not that there's necessarily anything wrong with that. You could probably say the same thing about Relu if you wanted. I just think the "it responds better to certain features" argument, which is how I'm understanding this, can quickly throw you back into some classical computer vision work where you're trying to hand optimize instead of relying on gradient descent to find your features