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Comment by dewhelmed | Hacker News Reader

If you don't mind, could you share some resources on existing models that approximate the neuron behaviour more accurately? If you're talking about feedback-driven models like RNNs/LSTMs/GRUs/etc, then I can safely say that there are people working on realising these models on custom computing architectures. The simple feed-forward neural network could be thought of as the low-hanging fruit in this regard, which, nevertheless, is still an impressive feat.

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This is just a smattering of recent articles from the Journal of Computational Neuroscience, but I think something more along the lines of models like these would give us closer approximations of how neurons really behave:

[1] https://link.springer.com/article/10.1007/s10827-017-0667-3

[2] https://link.springer.com/article/10.1007/s10827-017-0668-2

[3] https://link.springer.com/article/10.1007/s10827-017-0655-7

[4] https://link.springer.com/article/10.1007/s10827-017-0646-8

[5] https://link.springer.com/article/10.1007/s10827-017-0658-4

There's a lot of good information on modeling spiking neurons here: http://www.scholarpedia.org/article/Category:Spiking_Network...

Also, I like the papers linked here by Eugene Izhikevich: http://www.izhikevich.org/publications/index.htm

The new links discussing the capsule neural networks are somewhat reminiscent of this polychronous computation paper: http://www.izhikevich.org/publications/polychronous_wavefron....

https://hackernoon.com/what-is-a-capsnet-or-capsule-network-...

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