[HN Gopher] Self-organising textures from cellular automata
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Self-organising textures from cellular automata
Author : fenomas
Score : 352 points
Date : 2021-02-12 12:34 UTC (10 hours ago)
(HTM) web link (distill.pub)
(TXT) w3m dump (distill.pub)
| gchamonlive wrote:
| This is very interesting
|
| I observed that the more symmetric the basic structures of the
| pattern/texture are, the more stable the result is/the faster the
| automata converges.
|
| I wonder what it would take to stabilize the worst case I saw
| there, the veined leaf texture.
| jonahrd wrote:
| For some reason I find these quite disgusting to look at. I
| wonder why!
| SamBam wrote:
| Besides the organic, slightly bacterial-colony forming nature
| of them, I wonder if you also have trypophobia. I feel like
| some of the images were triggering the same kind of feelings I
| get from that.
| JosephRedfern wrote:
| The way the the images move during evolulution kinda reminds me
| of worms or maggots wriggling around in soil.
| choxi wrote:
| https://en.wikipedia.org/wiki/Trypophobia was mentioned in
| another comment
| f430 wrote:
| is the animation periodically shaking? I was staring at it and it
| seem to quiver.
| samwestdev wrote:
| How does it work?
| soheil wrote:
| What is the significance of this, e.g. can we use this approach
| to build arbitrary material or even living tissue? I can't help
| but think of this video [0], it seems there may be commonalities
| between what's happening in life and simple cellular automata.
|
| [0] https://www.youtube.com/watch?v=7Q9VyHJ1l2Q
| Sebastian_09 wrote:
| Warning for people suffering from trypophobia, some of the
| combinations can be quite disturbing! [0]
|
| Very interesting how the patterns react to disturbances like
| rotation, and the animation is very smooth
|
| [0] https://en.wikipedia.org/wiki/Trypophobia
| udp wrote:
| I usually have a very strong (feeling unbearably itchy)
| trypophobic response to anything "organic" that has clusters of
| protrusions or holes e.g. lotus seed pods, but none of these
| examples have any such effect. I think it's because of the
| bright colours and low resolution.
| hoppla wrote:
| Ditto, it has to be organic for me. Usually holes with stuff
| in it.
| jointpdf wrote:
| What about inorganic physical objects, like a shower head?
| udp wrote:
| No problem if it's inorganic. I expect there must be some
| kind of evolutionary reason for it - the fact that it's an
| itching/crawling feeling strongly suggests it has/had
| something to do with bugs.
| k2enemy wrote:
| If you haven't heard or seen any presentations about the work
| coming out of the Levin lab, it is super interesting. I don't
| really know anything about biology, but the work around modifying
| organisms via changing electrical circuits rather than genes is
| fascinating, and to a lay-person such as myself seems like the
| future of bio.
|
| https://ase.tufts.edu/biology/labs/levin/presentations/
| Moosdijk wrote:
| If you want to see similar work by some of the same authors, see
| [1]. The youtube channel "twominutepapers" has an explanation of
| this work[2].
|
| [1] https://distill.pub/2020/growing-ca/ [2]
| https://www.youtube.com/watch?v=bXzauli1TyU
| hans1729 wrote:
| Shoutout to twominutepapers, it's a wonderful channel.
| [deleted]
| enricozb wrote:
| This reminds me a lot of the WaveFunctionCollapse texture
| generation algorithm [0]. It "generates bitmaps that are locally
| similar to the input bitmap."
|
| Very cool!
|
| [0]: https://github.com/mxgmn/WaveFunctionCollapse
| JackFr wrote:
| This is the first I've ever read about neural cellular automata,
| though I thought I was relatively up to date on both cellular
| automata and deep learning. I think I was able to pick up the
| broad strokes from context, but is there a good introductory
| resource for neural cellular automata?
| [deleted]
| alokdhari wrote:
| Until next trip.
| taneq wrote:
| This reminds me of a shareware program I had way back in '98 or
| something. It let you generate (or evolve?) seamlessly tiling
| textures using a cellular automaton with a bunch of parameters. I
| remember it being really cool at the time but can't for the life
| of me remember what it was called.
| ArtWomb wrote:
| Results resemble common micrographs. But perturbed in such a way
| as to appear alien. Appears we are on the cusp of "neural
| synthetic biology" ;)
|
| Fast differentiable DNA and protein sequence optimization for
| molecular design
|
| https://arxiv.org/abs/2005.11275
|
| Regenerating Soft Robots through Neural Cellular Automata
|
| https://arxiv.org/abs/2102.02579
| enchiridion wrote:
| Is a micrograph the same a motif from network theory?
| EamonnMR wrote:
| This does a good job of illustrating how patterns in nature
| formed by cells can self organize. I haven't dug in to see how
| similar the implementation is, but when you look at the way these
| textures develop it sure looks like it.
| adamhp wrote:
| "It reaches out... it reaches out... it reaches out..."
|
| This is too cool.
| unparadoxed wrote:
| Very nice! The results look similar to my experiments in applying
| feedback to style transfer networks
| (https://www.youtube.com/watch?v=fGSXbYDpI9c), though the self-
| healing properties of CA make this more interesting!
| eyvindn wrote:
| Authors here. If you have any questions we'll do our best to
| answer them! Glad to see people find our work interesting thus
| far.
|
| We also encourage anyone interested to play with the linked
| Google Colabs [1][2] and read the other articles in the Distill
| thread. In the Colabs you'll find a bunch more pre-trained
| textures as well as a workflow to train on your own images, plus
| some of the scaffolding to recreate figures.
|
| [1] https://colab.sandbox.google.com/github/google-
| research/self... [2]
| https://colab.sandbox.google.com/github/google-research/self...
| blacksmith_tb wrote:
| Very interesting work. The bottom of the article has links[1]
| to the GH repo, but I take it that it's a private repo?
|
| 1: https://github.com/distillpub/post--selforg-textures
| teenbear wrote:
| there's links to the basic collab implementations at the top
| JackFr wrote:
| This is the first I've ever read about neural cellular
| automata. I think I was able to pick up the broad strokes from
| context, but is there a good introductory resource for neural
| cellular automata?
| mysterEFrank wrote:
| I love all you guys' work. Keep it up.
| layer8 wrote:
| How large is the state space for each cell? Full 8-bit RGB (=
| 24 bits)?
| zzznah wrote:
| Each cell has 12 8-bit channels, including rgb, so it is 96
| bits.
| [deleted]
| [deleted]
| yorwba wrote:
| The article says "our NCA model contains 16 channels. The
| first three are visible RGB channels and the rest we treat
| as latent channels which are visible to adjacent cells
| during update steps, but excluded from loss functions."
| eyvindn wrote:
| Thanks for noticing. This is a typo stemming from early
| experiments. We started out with 16 channels, but
| switched to 12 channels of state when this worked just as
| well. I've submitted a correction.
| eyvindn wrote:
| EDIT: Alex replied below. For more details on quantisation
| see footnotes in our seminal work [1]
|
| [1] https://distill.pub/2020/growing-ca/
| phreeza wrote:
| Is it common to describe ones own work as seminal?
| munificent wrote:
| In typical parlance today, "seminal" means "from which a
| bunch of important things have sprung" but I think there
| is an older definition which is simply "first".
| eyvindn wrote:
| Apologies, not my intention. I was also under the
| impression seminal could be used to mean "first" in the
| succession of our works and this is what I had intended
| to communicate.
| jderick wrote:
| Where do the original textures come from?
| ciaranby wrote:
| Great post, thanks! I saw Growing Neural Cellular Automata
| document you describe a strategy to get the model to learn
| attractor dynamics. I was kind of reminded of Deep Equilibrium
| Models (https://arxiv.org/abs/1909.01377).
|
| Is there a relationship between these models and do you think
| these root finding and implicit differentiation techniques
| could be used to train Cellular Automata too?
| toss1 wrote:
| Wow!!
|
| Really impressive work - in seconds, I see so much both
| richness of ideas and potential!
|
| And, as is so often the case, the really interesting work
| happens on the intersection of two fields - neural nets and
| cellular automata here. I've got tons of new reading to do now!
|
| Any plans to extend it to generation in 3D space?
| jsilence wrote:
| Question? Yes: Why do I love you so much? I don't even know
| you!
| teenbear wrote:
| Thanks for the write up! Just a note: at least in the pytorch
| collab there are missing includes (numpy and the imread
| function)
| zitterbewegung wrote:
| The textures remind me of the beginning of once in a lifetime
| by talking heads. https://www.youtube.com/watch?v=5IsSpAOD6K8
| danans wrote:
| > In the same way that cells form eye patterns on the wings of
| butterflies to excite neurons in the brains of predators, our
| NCA's population of cells has learned to collaborate to produce a
| pattern that excites certain neurons in an external neural
| network.
|
| I know there has been other work on adversarial networks, but
| this analogy (along with the photo of the butterfly) really
| communicates the idea well. And although I'm generally skeptical
| of claims that ANN "x" is the true model of how the human brain
| works, it makes a lot of sense to me that this is how adversarial
| self-organizing biological structures interact.
|
| Also, it's a powerful example because of just how effective the
| butterfly wing's "eye" is. Despite understanding that it's a
| decoy, I still can't look at it and not be unnerved a bit by it.
| willis936 wrote:
| Nice approximation of nature. You can see both growth and
| statistical mechanics in the same demonstration.
| hardmath123 wrote:
| See also: using differentiable approximations of cellular
| automata in PyTorch to reverse Conway's Game of Life; in some
| cases, you can get striking Turing patterns similar to what's
| described in this paper! http://hardmath123.github.io/conways-
| gradient.html
| March_f6 wrote:
| This is amazing. As a complete ML/AI neophyte can someone
| suggests some books/resources to help me understand the basics of
| what is going on here?
| colordrops wrote:
| This is awesome. Not sure why, but I was kinda disappointed to
| find our that it uses ML.
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