No. It definitely has resulted in practical improvements to attention. One practical improvement is that kernel smoothing is vastly easier to explain than "attention", which I think I have already demonstrated here.

Aside from that, kernel smoothing has roughly 70 years of literature devoted to every practical aspect you could imagine: approximation, accuracy, pedagogy, behavior under sparsity, relationship to other well-known theories like Bayeisan learning, and so on. Variants like Performer and elliptical attention, all directly arose from the knowledge that attention is intro-grad-stats kernel smoothing. A large portion of our understanding of ICL is directly or indirectly resultant from the fact of this correspondence.