•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.
