The two output functions that you're training the network to learn, and predict numerically, are such that one of those only depends on two of the inputs. If everything is working, according to our initial theory, then we should see that there's just two parallel paths through the network that don't interact at all. And indeed, that is what you see. One might be one might suspect that those connections you cannot see can actually contribute a lot but that's not the case.

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