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Generative Adversarial Networks and the Rise of Fake Faces: an Intellectual Property Perspective

The tremendous growth in the artificial intelligence (AI) sector over the last several years may be attributed in large part to the proliferation of so-called big data.  But even today, data sets of sufficient size and quality are not always available for certain applications.  That’s where a technology called generative adversarial networks (GANs) comes in.  GANs, which are neural networks comprising two separate networks (a generator and a discriminator network that face off against each another), are useful for creating new (“synthetic” or “fake”) data samples.  As a result, one of the hottest areas for AI research today involves GANs,…