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Show HN: High-Res Neural Cellular Automata
Neural CAs model self-organizing pattern formation.
Now they can generate patterns at HD resolution in real-time, enabled by turning each CA cell into a Neural Field.
Try 3 demos: grow a pattern from a seed (and damage it, it heals), synthesize PBR textures that can regenerate, or create 3D textures like clouds.
- WithinReason 4mo agoYou can make the centipede grow longer, which makes sense given how this works. Or grow a 2nd centipede for extra points.
- esychology 4mo agohaha yes, also the same with the worm
- hidelooktropic 4mo agoFor the unfamiliar, could someone explain what I'm looking at? The abstract was a little too concrete (heh) for me to follow.
- esychology 4mo agoIf you're familiar with CAs (e.g. Conway's Game of Life), you can think of a NeuralCA as a CA where the update rule is given by a neural network. Here we optimize the neural net weights so that it behaves a certain way (e.g. grow a lizard from a single seed).
- flir 4mo agoWhat are the inputs to the NN? The whole grid, or just nearby cells? What happens if two NNs overlap on the same grid? (Gonna go read the paper).
- esychology 4mo agoThe input to the NN is just the 3x3 neighborhood around a cell. We can overlap two NNs on the same grid (through interpolation). Checkout https://meshnca.github.io https://meshnca.github.io to see the effect. When the brush is in graft mode, it basically allows you to paint some regions that will follow a different NN rule.
- flir 4mo ago> The input to the NN is just the 3x3 neighborhood around a cell. Well that sounds like black magic. Nice. Thanks for the reply.
- 0xdeadbeefbabe 4mo agoIs each image a NN or is it one NN for all the images?
- esychology 4mo agoOne NN per pattern/image (instance based training).
- hidelooktropic 4mo agoWow. That's fascinating. Thanks for that explanation. So these images come to be consequentially from initial state and weights...
- soraki_soladead 4mo agoThe original NCA is probably a helpful intro: https://distill.pub/2020/growing-ca/ https://distill.pub/2020/growing-ca/
- amelius 4mo agoWhy are the images always generated in the same orientation (upright)? Do the cells have awareness of what is "up"?
- esychology 4mo agoyeah normally NCAs have a sense of up and left. There are some isotropic variants that make the perception fully rotation-invariant.
- WhiteNoiz3 4mo agoIIRC training starts with the initial state and the end state, and the end state is always oriented the same way. It would be interesting to see what would happen if the end state was rotated randomly though I suspect it wouldn't work so well.
- esychology 4mo agoCheckout the Isotropic NCA blog from the Google Zurich team: https://google-research.github.io/self-organising-systems/isonca/ https://google-research.github.io/self-organising-systems/is...
- WhiteNoiz3 3mo agointeresting, thanks!
- jekude 4mo agoThe 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?
- esychology 4mo agoI think performance is not the only issue for scaling to larger grids. CUDA Convolution implementation already utilizes coalescing to improve performance. The main bottleneck is that in larger grids, cells are further apart, and it takes more steps for them to be able to communicate.
- embedding-shape 4mo agoReally 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 :(
- bfmalky 4mo agoYou can, just enable the 'transition' switch.
- embedding-shape 4mo agoThat seems to be something else? It takes the current image and "transforms" it into the new target.
- esychology 4mo agoThat's not possible in the current demo but this sounds like an interesting feature to work on and add!
- whilenot-dev 4mo agoThe 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 https://imgur.com/a/ItZGd5X
- esychology 4mo agoThe NeuralCA both generates and maintains the pattern. Because the NCA was not exposed to damage or erasure during training, its regeneration capability is a purely emergent phenomenon. However, this ability remains somewhat brittle, particularly when the central regions of the pattern are erased.
- mackenney 4mo agoI would love to see two seeds competing for space in the grid
- WhiteNoiz3 4mo agoWith the old model (and I suspect this one too) it's trained to generate from a single 'seed' pixel in the center of the image. If you erase the center of the image, that's when it completely collapses.
- cl3misch 4mo agoHave you actually tried that? If you specifically erase the center, the image does change a lot at first, but rebuilds itself eventually (albeit to a slightly different final state). It's uncanny how "biological" is feels!
- Mithriil 4mo agoIf you hold the eraser for a second at the center, I find that it destroys the image more often than not.
- WhiteNoiz3 4mo ago
- mirekrusin 4mo agoSo the goal is to evaporate it with minimum number of shots?
- WhitneyLand 4mo agoAt 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…
- oersted 4mo agoTo me, it is intriguing as a toy model for how cells are able to grow into complex tissue and organisms based only on local information, and how they are able to repair and recover harmed tissue. Of course, this is as close to cells, as neurons from neural networks are to real neurons. And I have no idea what it could be applied to (inpainting/outpainting?), but it’s interesting as exploratory research.
- menno-sh 4mo agoOooh, this made it click for me. Thank you
- esychology 4mo agoTexture sampling retrieves pixels by coordinate, while NCA grows them from local rules with no global lookup. The weights are actually ~3× smaller than JPEG-compressed texture maps, so it's not just memorizing the image either. The more interesting part is that it's a dynamic process, you can damage the pattern while it forms and it repairs itself.
- zcw100 4mo agoI've always loved the original work and it's nice to see they're still working on it. I've always wondered if there was a way to connect this back to infrastructure rather than images. Something you could run on a cluster and if portions of it failed it would regenerate the system. Like a bio inspired Kubernettes.....Bionettes.
- bjourne 4mo agoI found your previous work here: https://distill.pub/2020/growing-ca/ https://distill.pub/2020/growing-ca/ For someone (like me) who wants to understand the basics its probably better. It's very well written.
- moralestapia 4mo ago@esychology this is phenomenal work, thank you so much for sharing it. I am working in a similar thing and might reach out about it soon. Also, what's going on? Why would the community flag and kill this comment[1], from the creator itself. If you're jealous of what the guy built, take it elsewhere. HN will implode with that attitude. 1: https://news.ycombinator.com/item?id=48571171 https://news.ycombinator.com/item?id=48571171
- esychology 4mo agoThank you for the kind comment! Please reach out, I'm happy to have a chat.
- bjourne 4mo agoIt's the stupid spam filter going haywire: https://news.ycombinator.com/item?id=48321198 https://news.ycombinator.com/item?id=48321198
- yorwba 4mo agoIf it says [flagged], a human pressed the "flag" button. Most likely because OP is commenting too much.
- CamperBob2 4mo agoI don't believe that's the case. HN is running some kind of automated slop detector that classifies any suspected LLM output as "slop" even if it's entirely in-context for the conversation (e.g., a conversation about LLM output.) The comment gets autoflagged the moment it's posted. This has been the case for a while now, I've run afoul of it myself. It sucks, and I can only imagine they implemented it because they felt they had no other option to deal with the onslaught of bots that's appeared lately. One thing they could do to improve the situation is to weight vouching heavily by karma. I have plenty of karma but I don't think I've ever successfully pulled a comment out of the [dead] state by vouching for it. Legitimate comments that get flagged by mistake tend to stay that way for the duration of the discussion.
- hyqzz8 4mo ago[dead]
- _menelaus 4mo agoFascinating. A glimpse into the mathematics of life and living tissue. A toy example like this might herald self-healing machines, in the same way that the first perceptrons heralded Fable and nude deepfakes.
- IvanLudvig 4mo agoincredible work! I love seeing progress in this field. I've recently built a WebGPU implementation of the original growing neural CAs: https://github.com/IvanLudvig/neural-ca-webgpu https://github.com/IvanLudvig/neural-ca-webgpu
- EstanislaoStan 4mo agoManaged to get a stable loop with the worm!
- Akimsa3 4mo agoThat's really impressive i've been thinking that we have using technologies cause they were a breakthrough but we actual resources we can implement technollogy that was relegated time ago, like when implementing 3d there were many other until the one who was more consistent is how we visualize 3d today. Cause this looks pretty simillar to metaballs. An idea that is not longer that hard pursued but i just saw the similarity.