Yeah, for backprop you need an error signal (probably not a rope now because it's signed), and to multiply it by the activation (which suggests another seesaw f

Yeah, for backprop you need an error signal (probably not a rope now because it's signed), and to multiply it by the activation (which suggests another seesaw for the multiply), and to bump the connection horizontally proportional to the product. Then fan out the product into the previous layer's error. I have no experience at mechanical design -- I got to thinking about this out of irritation at a pop-science explanation of neural networks in the New York Times magazine which explained nothing. Could you help people to a real understanding (a basic one) by letting them play with a tiny network in tangible form, where you can see the activations and feel the forces? I guess making it work with all the details and practicalities would probably end up with the basic parts too complicated, and too many of them for this purpose of learning, but it'd be cool to try.