Just a decade ago, artificial neural networks (NNs) were considered by most researchers as an unpromising branch of computer science. But as computational power grew, and efficient algorithms to train NNs on GPUs were found, the situation changed dramatically. The latest discoveries in the field have achieved unprecedented results, such as tracking objects in video; synthesizing realistic speech, paintings, and music, automatic translation from one language to another; and extracting meaning from text, images, and video. NNs were rebranded as deep learning and they've set all kinds of records in computer vision and natural language processing, beating almost all other ML approaches over the last few years (2014-2018). Deep NNs caused a new machine learning boom, raising a wave of discussions and predictions about the artificial general...
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