In normal NCA cells are pixels and they can perceive their neighboring pixels (cells can't move). In NPA cells are particles and they can perceive all particles in a support radius around them and these particles can move freely. Does this answer your question?
On the outside it looks very similar to what Michael Levin found on electrical communication between living cells. There too, the organism's cells were able to structure and repair their larger-scale morphology: https://www.youtube.com/watch?v=XheAMrS8Q1c
If you look at the texture demo with the zeros, it looks a bit like lipid membranes merging/splitting as they stabilize more or less around a particular size.
Thanks! Yeah I think it should be possible though it requires making the cell division/splitting a differentiable operation. But nontheless, this is indeed a very interesting and promising direction to pursue.
Indeed! The system has good regeneration capabilities but it certainly has limits.
The particles can only grow reliably if they start from the egg-like initial condition. If we switch the rules mid rollout, we would get a messed up morphology.
could something similar be used for texture synthesis ? of course the particles will need to be arranged in a grid and everything, or maybe recreate the texture by interpolating between the particles to exploit low contrast areas in the data
Because the space of people interested in such things is relatively small and so a single article has knock on effects where a reader of the article or a blogger sees it and starts exploring the space and posts more about it, increasing the exposure some more.
How does this relate to https://cells2pixels.github.io/ ?
In normal NCA cells are pixels and they can perceive their neighboring pixels (cells can't move). In NPA cells are particles and they can perceive all particles in a support radius around them and these particles can move freely. Does this answer your question?
On the outside it looks very similar to what Michael Levin found on electrical communication between living cells. There too, the organism's cells were able to structure and repair their larger-scale morphology: https://www.youtube.com/watch?v=XheAMrS8Q1c
Super cool work!!! Do you think it would be possible to do something like cell division here?
If you look at the texture demo with the zeros, it looks a bit like lipid membranes merging/splitting as they stabilize more or less around a particular size.
Thanks! Yeah I think it should be possible though it requires making the cell division/splitting a differentiable operation. But nontheless, this is indeed a very interesting and promising direction to pursue.
Found it much interesting that i could mess up a pattern enough that it couldn't re-form.
Would be fun if selecting a new pattern didn't refresh the image as it is. Although maybe that's a requirement?
Agree! This reminded me of a post that tweaked my brain a few months ago :)
https://open.substack.com/pub/defenderofthebasic/p/why-does-...
Also reminds me of Dr Michael Levin's work, which is living rent free in my brain lately
Indeed! The system has good regeneration capabilities but it certainly has limits.
The particles can only grow reliably if they start from the egg-like initial condition. If we switch the rules mid rollout, we would get a messed up morphology.
This is super cool, great work. Is there a video or demo of the 3D point cloud "gaussian splat" like experiments?
I uploaded the videos here: https://drive.google.com/drive/folders/1V8XFzq2VkZXKG7Tw8ICv...
could something similar be used for texture synthesis ? of course the particles will need to be arranged in a grid and everything, or maybe recreate the texture by interpolating between the particles to exploit low contrast areas in the data
From the original research - self-organizing textures: https://distill.pub/selforg/2021/textures/
thanks ! i feel stupid for only checking out the linked paper lol
Can someone tell me why cellular automata are suddenly everywhere? I've seen ~10 articles regarding them in the last month.
Because the space of people interested in such things is relatively small and so a single article has knock on effects where a reader of the article or a blogger sees it and starts exploring the space and posts more about it, increasing the exposure some more.
Possibly because SIGGRAPH is coming up and these were papers submitted to that conference.
This is the future of scientific publishing, pdf is so boring.
I really loved the distill articles. Too bad it was not continued anymore...