GANs (Generative Adversarial Networks)

GANs, also known as Generative Adversarial Networks, are artificial intelligence models used to generate new content. They consist of two main components: the generator and the discriminator. The generator creates new data, while the discriminator tries to distinguish between real and generated data. The special feature of GANs is their adversarial approach, in which the generator and the discriminator compete against each other and improve each other. Through this training, GANs achieve the ability to generate realistic and high-quality content, such as images, texts or even entire videos.