GAN
Full Form: Generative Adversarial Network
Category: AI Architecture
📖 Definition
A GAN consists of two neural networks competing against each other: a generator that creates fake data and a discriminator that tries to distinguish real from fake. This competition improves both networks.
🔑 Key Points
- Consists of generator and discriminator networks
- Generator learns to create increasingly realistic data
- Can produce high-quality images, but training can be unstable
- Pioneered photorealistic image synthesis
💡 Why It Matters
GANs pioneered AI image generation, but have largely been superseded by diffusion models for most applications.