Aiconomy

Generative Adversarial Network (GAN)

A deep learning architecture where two neural networks — a generator and a discriminator — compete against each other, with the generator learning to create increasingly realistic synthetic data.

GANs were introduced by Ian Goodfellow in 2014 and dominated AI image generation until diffusion models overtook them around 2022. The generator creates fake data while the discriminator tries to distinguish it from real data, creating a competitive dynamic that improves both networks. StyleGAN produced photorealistic human faces that are indistinguishable from real photos. GANs remain widely used for data augmentation, super-resolution, and style transfer, though they are notoriously difficult to train due to mode collapse and training instability.

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