Understand What is a Generative Adversarial Network, and its role in creating synthetic data. A Generative Adversarial Network (GAN) is a revolutionary AI model comprising two neural networks—a generator and a discriminator—working in tandem. While the generator creates synthetic data, the discriminator evaluates its authenticity. This adversarial process results in highly realistic outputs, such as images, videos, or audio. GANs have found applications in diverse fields, including art generation, image editing, and deepfake technology. They also enhance data augmentation for machine learning by generating synthetic datasets. Understanding GANs unlocks a deeper appreciation of how AI can mimic human creativity and innovation. Explore the significance of GANs in advancing AI capabilities and their transformative impact on industries reliant on high-quality data and realistic simulations.