2012: The rise of Deep Learning

Deep Learning is a type of Machine Learning algorithm that uses multilayer neural networks and back propagation techniques to train neural networks. This field was virtually pioneered by Geoffrey Hinton. As early as 1986, Hinton and his colleagues published a groundbreaking paper on Deep Neural Networks (DNNs), introducing the concept of back propagation, a weight adjustment algorithm that allows the neural network to approach the correct output faster than before each time you change the weights. This easily implements multilayer neural networks, breaking the curse of the perceptron limitation written by Minsky in 1966.