3. Generative Adversarial Networks (GANs) – The AI Behind Realistic Images

Generative Adversarial Networks (GANs) are another essential technology for AI image generation. Unlike diffusion models, GANs work through a process of competition between two neural networks:

• The Generator: Creates new images based on learned data.
• The Discriminator: Evaluates whether the generated images look real or artificial.

These two networks continuously improve by challenging each other. If the discriminator detects a fake image, the generator modifies its output to be more realistic. This cycle repeats thousands of times until the generated images become indistinguishable from real photos.

GANs are widely used in:

• Photo-realistic AI avatars
• Deepfake technology
• Artistic style transfer
• Image upscaling and restoration