Can you explain the concept of generative adversarial networks (GANs) and their applications in AI?

GANs consist of two neural networks, a generator and a discriminator, which are trained together in a competitive manner. The generator creates synthetic data samples, while the discriminator distinguishes between real and fake samples. GANs have various applications, including image generation, style transfer, and data augmentation.