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The Perceptron was real. It learned from examples. It had a hard limit, and that limit was real too.
But the conclusion the field drew was wrong. The limit of one neuron was not the limit of the approach.
In the next chapter, we'll follow that small group and see what they found. How do you trace an error backwards through a network? How do you know which weights to blame? And once you can train a network, what can it actually do?