It's interesting that the black art of analog design never really goes away even from computing. I was reading Geoffrey Hinton's "Mortal Computation" where he briefly speculated towards the end on low power (in watts used, not capability) neural networks being embedded in hardware via something like memristor networks. It makes me imagine neural networks being distributed as a template (i.e. a blob of XML describing the topology and the weights) and then the network weights get tuned a little different to each device or device model to get the best performance per watt out of them. Since every device is physically a little bit different from the next, in precision analog applications with discrete components the components have to be matched. This is often the case in assembling differential pairs in analog audio circuits. Similarly with the control system parameters with hard drives. Since each DC motor is a little bit different from the next, the control loop gets tuned at the factory to each drive. So in this case, the neural network gets matched to the circuit it's embedded in. Mortal computation indeed, each neural network becomes truly unique. I could be full of it, but it's fun to imagine at least.