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Generative Adversarial Networks (GANs) are revolutionizing the world of artificial intelligence and data science. These neural networks have gained popularity since their inception in 2014, and for good reason. GANs work by pitting two neural networks against each other - a generator that creates synthetic data and a discriminator that tries to distinguish it from real data. This adversarial process allows the generator to produce increasingly realistic data, making them valuable for applications like image synthesis, video creation, and content generation.
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