A New Link to an Old Model Could Crack the Mystery of Deep Learning

In the machine learning world, the sizes of artificial neural networks -- and their outsize successes -- are creating conceptual conundrums. When a network named AlexNet won an annual image recognition competition in 2012, it had about 60 million parameters. These parameters, fine-tuned during training, allowed AlexNet to recognize images that it had never seen before. Two years later, a network named VGG wowed the competition with more than 130 million such parameters. Some artificial neural networks, or ANNs, now have billions of parameters. These massive networks -- astoundingly successful at tasks such as classifying images, recognizing speech and translating text from one language to another -- have begun to dominate machine learning and artificial intelligence.