Is There Hope?
Is there any hope for learning functions that are
not linearly separable?
Yes, but a perceptron network isn't enough.
One needs more than one layer of units between
inputs and outputs to compute other functions.
With enough "hidden" units (units within), any
boolean function is computable, and any
continuous function is approximable.