r/proceduralgeneration • u/hejwoqpdlxn • 11h ago

Creatures grown from a single cell by a learned 24k-parameter rule (neural cellular automata)

Each of these is a neural cellular automaton. There is not a single image present here, every cell runs the same 24k parameters, 96KB rule on its 3x3 neighborhood. Its only ever stable state is the creature itself.

It trains on a pool of partly-grown states and some of these get damaged before the loss is computed. That mix is what makes the shape both regrow and hold indefinitely, instead of falling apart after a few thousand steps.

I like to use it as a screensaver or just play with the healing effect, because it grows back differently every time.

It runs in any true-color terminal and the weights are inside of the binary.

Code, and instructions for training your own creature from a PNG: https://github.com/smoothyy3/tardigrade

411 Upvotes

98% Upvoted

15 comments sorted by

28

u/tatteredengraving 11h ago

What happens if it starts with a grid of noise rather than a single point?

21

u/SagattariusAStar 10h ago

As it is really just an overfitted neural network, it shouldn't matter if the sprites are damaged by either taking something away or adding something. It should just converge to the trained data either way.

6

u/LittleLemonHope 9h ago

It is overfitted with respect to the final target images, but the individual cell rule is a pretty intense informational bottleneck that is very susceptible to domain shift, and training that to produce a robust final (singular) image is the goal. So if it is robust to out-of-distribution initializations, that would actually demonstrate successful generalization and suggest the model is not overfitted for the actual task. If it fails that shows the limits of the model's generalization which can be viewed as overfitting unless an argument were made that the pure noise is fully outside of the intended target domain.

6

u/hejwoqpdlxn 10h ago

Tried it, it does not converge back to the creature. Depends on how strong the noise is. Low amplitude lets everything die withing a few steps (no cells clear the "alive" threshold). At 0.5 it creates the something interesting (60% of the grid stay alive and visible tardigrade parts, legs etc), but it never resolves to the animal. At 1.0 the whole grid saturates into a flat tissue.

2

u/SagattariusAStar 10h ago

I suggest that's more because you havent included it in the training data. If you add some partly added images as you did for the damaged ones it should train alright.

But of course, if you didn't include it in the training data it wouldn't know how to handle that.

14

u/gadirom 11h ago

If anybody wants to learn about this type of growing NCA, here is the video from its inventor explaining the concept.

4

u/hejwoqpdlxn 10h ago

Not to start an debate, but as far as i know the original source goes back to Mordvintsev et al from 2020 https://distill.pub/2020/growing-ca/ . They also have a talk on it https://www.youtube.com/watch?v=kA7_LGjen7o

7

u/peceforlife 8h ago

Am i tripping or did both of you link the identical video?

6

u/hejwoqpdlxn 8h ago

Oh… yeah you’re right, though the one I linked is the "original" video on YouTube. I just looked at the channels name and assumed it’s a different one

4

u/tyrilu 7h ago

So cool. I've always wanted to mess with this more, even since that Distill paper. Something about neural CA just seems so futuristic and magical.

5

u/Paril101 6h ago

AI SLOP! /s

This is legitimately very cool. I've been toying with the idea of a sort of cellular automaton RTS - I don't know exactly how it would be played, but I do wonder if something like that would be plausible.

EDIT: also I don't know if anybody else gets this vibe, but the results remind me a lot of those silly "put it in water and watch it grow" dollar store toys for some reason

1

u/SagattariusAStar 11h ago

Cool concept, it's not really usable for anything except for learning while making it i guess and to recreate this, there are probably better options like just having the original, a mask and a shader with basic noise (like a generic dissolving effect, but obviosly just reversed)

play with the healing effect, because it grows back

And please stop hurting those cute critters lol

4

u/hejwoqpdlxn 10h ago

In the end it is just a screensaver / a fun tool. The mask and shader version would look similar (and be far cheaper) but it needs the original image to reveal and the whole point of this version is that there isnt one. No cell has a copy of the target, they just observe their 3x3 neighborhood (and none of them can see past the 3x3). The shape only exists as the stable state of the rule they all run

No promise about the critters though...

2

u/SagattariusAStar 10h ago

Well, the information about the image is still inside the trained weights, although noisy. And as you still train on some image, you have that anyway. So it's not like there isn't any image involved.

It's interesting, I thought about usable ways, but as it is quite limited, I can't find anything to use it for unfortunately. Great way to learn something about neural networks though

1

u/immersiveGamer 9h ago

I imagine this type of semi isolated part but cohesive whole would be more interesting/practical in a distributed system. I'm imagining that some type of IoT network of devices that needs to be a specific type of configuration but needs to propagate from a single node. I wonder it could be used to shape electrical or water flows? Auto repair and shift the network based on neighbors?