Generative Adversarial Networks (GANs) are at the core of deepfake technology, providing a flexible and adaptable approach to generating realistic images. GAN is a neural network architecture that consists of two parts: a generator and a discriminator. The former learns to create fake photos, while the latter learns to differentiate between real and fake content. Through a competitive process, these networks train together, with the generator constantly improving its ability to produce more convincing deepfakes and the discriminator enhancing its ability to detect them.