The new techniques boasted a more organic performance. For example, neural networks exhibited the property of “graceful degradation”: a small amount of damage to a neural network typically resulted in a small degradation of its performance, rather than a total crash. Even more importantly, neural networks could learn from experience, finding natural ways of generalizing from examples and finding hidden statistical patterns in their input.23 This made the nets good at pattern recognition and classification problems.
