Neural Nets vs. Cellular Automata
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Neural Nets vs. Cellular Automata
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Re: Neural Nets vs. Cellular Automata
#2I know it's not the same idea, but I think it's worth mentioning the adjacent concept of 'neural CA':
https://google-research.github.io/self-organising-systems/di...
https://google-research.github.io/self-organising-systems/is...
I can see why Mordvintsev et al are up to what they are doing, but to be honest I'm struggling with understanding the point of using a neural-net to 'emulate' CAs like OP seems to be doing (and as far as I can gather, only totalistic ones too?).
It sounds a bit like swatting a fly using an H-bomb tbh, but maybe someone who knows more about the project can share some of the underlying rationale?
Re: Neural Nets vs. Cellular Automata
#3intersting idea to do it in a distributed way with people help.
Re: Neural Nets vs. Cellular Automata
#4I think the biggest advantage NNs have over CA is the fact that most CA only provide localized computation. It can take a large number of fixed iterations before information propagates to the appropriate location in the 1d/2d/3d/etc. space. Contrast this with arbitrary NN topology where instant global connectivity is possible between any elements.
Re: Neural Nets vs. Cellular Automata
#5I think the biggest advantage NNs have over CA is the fact that most CA only provide localized computation. It can take a large number of fixed iterations before information propagates to the appropriate location in the 1d/2d/3d/etc. space. Contrast this with arbitrary NN topology where instant global connectivity is possible between any elements.
CNNs are CA if you don't insert fully connected layers, actually.
Re: Neural Nets vs. Cellular Automata
#6I don't get it, does the prediction go backwards or forward along CA generations?
Re: Neural Nets vs. Cellular Automata
#7I think the biggest advantage NNs have over CA is the fact that most CA only provide localized computation. It can take a large number of fixed iterations before information propagates to the appropriate location in the 1d/2d/3d/etc. space. Contrast this with arbitrary NN topology where instant global connectivity is possible between any elements.
CNNs are CA if you don't insert fully connected layers, actually.
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Re: Neural Nets vs. Cellular Automata
#8I don't get it, does the prediction go backwards or forward along CA generations?
it has the signature style of an app generated from the claude web ui. There isn’t necessarily an it to get.
Re: Neural Nets vs. Cellular Automata
#9I know it's not the same idea, but I think it's worth mentioning the adjacent concept of 'neural CA': https://www.neuralca.org/ https://google-research.github.io/self-organising-systems/di... https://google-research.github.io/self-organising-systems/is... I can see why Mordvintsev et al are up to what they are doing, but to be honest I'm struggling with understanding the point of using a neural-net to 'emulate' CAs l…
I'm not involved in this project, but I partially replicated the results from Mordvintsev et al. a few years ago because I found the idea interesting. The key idea for me was learning the possibly unknown rules of a CA from training examples. This sounded to me like something that could be useful in science, to learn about spatially distributed processes. Or in ML as a new idea for image classification or segmentation. The hope was always that a CA could be learned which would have a simple discrete representation which could then be used in inference with much lower computational needs than a full neural net. But unfortunately we never managed to succeed here, and I have the impression that this area is not as active anymore as it was some years ago.
I suppose the idea of this project is the same: show the correspondence between both in order to understand them better.
Anyway, some interesting papers from back then:
Cellular automata as convolutional neural networks: http://arxiv.org/abs/1809.02942
Image segmentation via Cellular Automata: http://arxiv.org/abs/2008.04965
It's Hard for Neural Networks To Learn the Game of Life: http://arxiv.org/abs/2009.01398
Re: Neural Nets vs. Cellular Automata
#10I think the biggest advantage NNs have over CA is the fact that most CA only provide localized computation. It can take a large number of fixed iterations before information propagates to the appropriate location in the 1d/2d/3d/etc. space. Contrast this with arbitrary NN topology where instant global connectivity is possible between any elements.
CNNs are CA if you don't insert fully connected layers, actually.
Yep, see my comment above and especially http://arxiv.org/abs/1809.02942