Generative Adversarial Networks (GANs)

Generative Adversarial Networks (GANs) are a class of AI models introduced by Ian Goodfellow in 2014. GANs consist of two neural networks: a generator and a discriminator, which compete against each other in a process called adversarial training. The generator attempts to create realistic data (such as images or text), while the discriminator tries to distinguish real data from the generated ones.

GANs have been widely used in image generation, style transfer, and even deepfake technology. They have revolutionized the ability of AI to generate high-resolution, photorealistic visuals, making them a key component in the creative industries.