King.

I’d say we need an /r/VXJunkies equivalent for statistical learning theory, but the real deal is close enough.

I don’t know who was the first to use the analogy to bird flight, but it’s a somewhat common refutation used in philosophy of AI. That’s just to say, it’s been used before.

Sometimes I consider retracting my very first paper because of this.

I would start with the illustrated stable diffusion for a high level overview. Then I would suggest reading the annotated diffusion model which goes over implementing the original diffusion paper by Ho et al.

For those curious, like I was, see section 4.8 "Convolution as a matrix operation" in A guide to convolution arithmetic for deep learning.