[nomailing]

What I remember from my neuromorphic engineering course (or analog VLSI course) is that we designed the silicon layout (with n and p doping regions) in a way that the transistors are operating in the subthreshold regime in the IV characteristics. If I remember correctly the IV characteristic is linear in the subthreshold region? In contast in normal digital chips only the super-threshold region is used (voltage above a certain saturation threshold switches the transistor completely on). Using the subthreshold region it is possible to implement spiking neuons with only very few transistors. It works completely different than digital circuits. The connections between the transistors don't transmit just 0's and 1's. Instead all wires transmit analogue signals where the exact voltage matters. This makes these chips extremely energy and space efficient. These chips can also work much faster even in comparison to biological neurons (obviously using some assumptions and simplifications, such as neglecting certain special kinds of ion channels found in real neurons).

[petra]

Theoretically , Analog is by far the best for neural networks. But why aren't we starting to see chips offered ? Heck even an old process like 130nm could have some practical uses .

[alexmlamb2]

Could you implement an approximate matrix multiplication in a direct analogue way? If so, I wonder why it hasn't been used for graphics cards.

[p1esk]

Yes: https://arxiv.org/abs/1610.02091