Looking at What is a Generative Adversarial Network, A Generative Adversarial Network (GAN) is a deep learning architecture that consists of two neural networks—the generator and the discriminator—competing against each other. The generator creates synthetic data, while the discriminator evaluates its authenticity. Through this adversarial process, GANs improve their ability to generate realistic data, such as images, audio, or text. They have been widely used in applications like image synthesis, deepfake creation, art generation, and data augmentation. GANs represent one of the most creative and dynamic fields in AI research. Understanding GANs is essential for anyone exploring advanced generative AI, where machines are capable of producing entirely new content that mimics real-world data.
popularne posty
