What is wrong with back-propagation?
		• It requires labeled training data. – Almost all data is unlabeled. • We need to fit about 10^14 connection weights in only about 10^9 seconds. – Unless the weights are highly redundant, labels cannot possibly provide enough information. • The learning time does not scale well – It is very slow in networks with more than two or three hidden layers. • The neurons need to send two different types of signal – Forward pass: signal = activity = y – Backward pass: signal = dE/dy