AI GlossaryGenerative Adversarial Network (GAN)ENTRY — Generative AI
[Generative AI]
Generative Adversarial Network (GAN).
Two neural networks competing against each other to generate realistic synthetic data.
In-depth explanation
01GANs consist of a generator (creates fake data) and discriminator (distinguishes real from fake). They're trained adversarially—the generator tries to fool the discriminator, while the discriminator tries not to be fooled. This competition drives both to improve. GANs excel at image synthesis, style transfer, and data augmentation.
Examples
02EX. 01
StyleGAN for face generation
EX. 02
CycleGAN for style transfer
More in Generative AI
0301Diffusion ModelGenerative models that learn to create data by reversing a gradual noising process.02GPTGenerative Pre-trained Transformer, a family of large language models trained to generate text.03HallucinationWhen AI models generate plausible-sounding but factually incorrect or fabricated information.04Large Language Model (LLM)AI models trained on vast text data that can generate and understand human-like text.05Prompt EngineeringThe practice of crafting effective inputs to get desired outputs from AI models.06RAG (Retrieval-Augmented Generation)Combining retrieval systems with language models to generate responses grounded in external knowledge.
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