The oscillating elements don't map directly to pixels. Conventional models also have n^2 parameters.

Well image generators work differently…

Do you mean that they may get away with less oscillators because of the decoder layer? Well there’s the rub isn’t it, the more work you have done by a software layer the less power you’ve proportionally saved by having it be done by physical computing.

But let’s spitball here what would you estimate would be needed in number of oscillators and interconnects for a 4K image?

	▲	fc417fc802 2 hours ago \| parent [-]
		Conventional image generators still have to process n^2 connections so I don't think that observation is a valid objection in and of itself. One thing I'm unclear on is that their total parameter count scales similarly to conventional models but many of those conventional models incorporate convolutions. I wonder how interconnect count (as opposed to unique parameters) compares to performance? As to 4k images, I'm not clear how much farther their current architecture would be expected to scale. Single layer networks aren't parameter efficient compared to deep networks; I'd naively assume that to also apply here. That said given their results so far with what amounts to a single layer the naive assumption begins to seem questionable.