Loss of plasticity in deep continual learning.

Artificial neural networks, deep-learning methods and the backpropagation algorithm form the foundation of modern machine learning and artificial intelligence. These methods are almost always used in two phases, one in which the weights of the network are updated and one in which the weights are held constant while the network is used or evaluated. This contrasts with natural learning and many applications, which require continual learning.