Part 5/15:
In the 1950s, the perceptron was introduced as the first neural network capable of learning simple patterns. The subsequent decades saw breakthroughs like backpropagation (1986, Hinton et al.), allowing multi-layer neural networks to learn more complex representations. Yet, initial neural network enthusiasm waned due to computational limitations—leading to the AI winter caused by insufficient computing power and data.