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This article explores the evolution of algorithms and how deep learning through convolutional neural networks has revolutionized the way computers recognize objects in photos. It explains how the multilayer neural network works similarly to the six layers present in the mammalian neocortex, organizing raw pixels into edges, shapes, compositions of shapes, and objects. It also discusses how unsupervised learning is used in businesses to identify objects and similarities without explicit direction.
