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"This is not entirely true, as there are spiking neuron nets and neuromorphic chips (like IBM's TrueNorth) that emulate what we have so far understood about how

"This is not entirely true, as there are spiking neuron nets and neuromorphic chips (like IBM's TrueNorth) that emulate what we have so far understood about how neurons operate." How is this related to the neural networks we are discussing? (deep ANNs?) As far as I know, the ANN topic in machine learning, apart from its origins, is completely unrelated to the simulation of biological neural network models: https://en.wikipedia.org/wiki/Nervous_system_network_models https://en.wikipedia.org/wiki/Nervous_system_network_models They are often confused because of the name and because ANNs did begin as extremely simplified models of biological neural networks, but the machine learning concept that is setting all the records in vision / speech recognition serves no purpose as a model of a biological neural network.

nl 11y ago
the machine learning concept that is setting all the records in vision / speech recognition serves no purpose as a model of a biological neural network. I think you are overstating this. There are definite links between the two, even if ANNs end up different because of the tools we have available to us. CNNs were explicitly designed to mimic the behavior of the visual cortex. Most of Geoff Hinton's career has been built around thinking very hard about biological computation. One of the major criticisms of back-propegation in neural networks is that it is biologicaly implausible. https://en.m.wikipedia.org/wiki/Convolutional_neural_network#History https://en.m.wikipedia.org/wiki/Convolutional_neural_network...