Amazing. Thank you .@fchollet
Looks like the complexity of the dependency graph between the GitHub repos of the OpenWorm project will soon be comparable to that of the nervous system of the actual wormpic.twitter.com/m1Wq2hUQ1Y
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Just like any other state-of-the-art MNIST digit recognition network...
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Whoa nice. Reminds me of the belief that the early general AIs will be designed and developed following nature [or at least elegant pragmatism] with ML and self-assmebling algos for specific purposes like CV and novel-problem approaches. Everything needs a little curarion eh?
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Sure we can plot it, but do we really _understand_ the dependency graph?
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Great you are diving into it! I have been working on pose estimation of C. elegans (challenging coiled poses) using Keras/TF2, with a synthetic training dataset. Approaching release, I would love to have your opinion!https://github.com/iteal/wormpose/
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Ah, a connoisseur. Doesn't C. elegans have about 32 neurons? So it's the "same" complexity already?
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Conway’s Law, but for biological simulations…
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@fchollet May I ask how you visualized this repo dependency graph? I’ve been searching for tools to do this but haven’t been able to find any.Thanks. Twitter will use this to make your timeline better. UndoUndo
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