Show HN: High-Res Neural Cellular Automata

At a glance it looks like it could be just iterative texture sampling.

The difference is when creating each pixel, there’s no coordinate to look up, instead it’s using only a set of rules like Conway’s game of life.

But the rules come from a neural network trained on the image, so… it’s kind of memorizing enough information to effectively do the same thing as texture sampling, but using only local information.

I’m sure I’m missing something about how it works or what makes it interesting…

The automata just completely destroys the image if I draw too much over the stabilized image with the brush. 5 horizontal swipes are enough to destroy the kitty, is that to be expected?

EDIT: video here: https://imgur.com/a/ItZGd5X

The abstract implies that strictly local updates are a hinderance to high res, however i would have thought there would be an interesting way to get speed up gains from neighbor-only traffic on GPUs CAM-style. am i making that up?

Really interesting demo, nicely done :) Would be fun if switching the "Target Image" when using the second brush mode in the Growing Demo didn't erase/reset the existing canvas, so we could "stamp" new things on top of other images. Small thing perhaps but I got sad when it disappeared when I wanted to merge a kitten on top of the chameleon but couldn't :(

For the unfamiliar, could someone explain what I'm looking at? The abstract was a little too concrete (heh) for me to follow.

You can make the centipede grow longer, which makes sense given how this works. Or grow a 2nd centipede for extra points.

Why are the images always generated in the same orientation (upright)? Do the cells have awareness of what is "up"?

So the goal is to evaporate it with minimum number of shots?