This is really useful, thanks. In my other (top-level) comment, I mentioned some vague dissatisfactions around how in explanations of attention the Q, K, V matrices always seem to be pulled out of a hat after being motivated in a hand-wavy metaphorical way. The kernel methods treatment looks much more mathematically general and clean - although for that reason maybe less approachable without a math background. But as a recovering applied mathematician ultimately I much prefer a "here is a general form, now let's make some clear assumptions to make it specific" to a "here's some random matrices you have to combine in a particular way by murky analogy to human attention and databases."

I'll make a note to read up on kernels some more. Do you have any other reading recommendations for doing that?