The Potential of Generative Adversarial Networks (GANs) in Data Science

Generative Adversarial Networks (GANs), introduced in 2014, have significantly advanced AI by creating realistic images and data, impacting fields from art to medical imaging. GANs consist of two neural networks, the Generator and the Discriminator, competing in a sophisticated ‘cat and mouse’ game, enhancing machine learning and prompting ethical discussions about their use. As GANs evolve, they promise to further revolutionize technology and society.