Artificial neural networks, etc. are an abstraction that is inspired on a biological neural ensemble. With many differences... Neurons are families of cells th

Artificial neural networks, etc. are an abstraction that is inspired on a biological neural ensemble. With many differences... Neurons are families of cells that come in many shapes and most of the time get oversimplified for didactic purposes. The processes involved in neuroscience are also oversimplified most of the time. It is often said that dendrites are the input, axons the output, and that spikes are fired when a threshold is met... but that's not always true. The biological situation is full of special cases. Then you have the way the network is formed. The amount of neurons and layers in a deep neural networks are just hardcoded in advance. That's not the case in biology. Then you have volume: biological neural networks have many more neurons, and many more connections between those. For example each Purkinje cell (in the cerebellum) can have over 200k dentritic connections.