Considering the answers of this question, emulating a human brain with the current computing capacity is currently impossible, but we aren't very far from it.Note, 1 or 2 decades ago, similar calculations had similar results.The clock frequency of the modern CPUs seem to be stopped, currently the miniaturization (-> mobile use), the RAM/cache improvement and the multi-core paralellization are the main lines of the development.Ok, but what is the case with the analogous chips? In case of a NN, it is not a very big problem, if it is not very accurate, the NN would adapt to the minor manufacturing differences in its learning phase. And a single analogous wire can substitute a complex integer multiplication-division unit, while the whole surface of the analogous printed circuit could work parallel.According to this post, software rewirable analogous circuits, essentially analogous FPGAs already exist. Although the capacity of the FPGAs is highly below the capacity of the ASICs with the same size, maybe analogous chips for neural networks could also exist.I suspect, if it is correct, maybe even the real human brain model wouldn't be too far. It would still require a massively parallel system of costly analogous NN chips, but it seems to me not impossible.Could this idea work? Maybe there is even active research/development into this direction?
Emulating human brain - with analogous NN chips
neural networks