www.pickl.ai
A Generative Adversarial Network (GAN) is a deep learning model for generating data.
GANs consist of two neural networks: the generator and the discriminator.
The generator creates fake data, aiming to mimic real data from training sets.
The discriminator evaluates data, distinguishing between real and generated samples.
Both networks compete in a zero-sum game, improving each other’s performance over time.
GANs are used in image synthesis, style transfer, and generating realistic media content.
GANs continue to evolve, driving advancements in AI, art, and data generation technologies.