What does the acronym GAN stand for in the context of generative AI?

The acronym GAN stands for Generative Adversarial Network, which is a key concept in the field of generative artificial intelligence. A Generative Adversarial Network consists of two neural networks—the generator and the discriminator—that work together, with one generating data and the other evaluating it. This adversarial process allows the generator to learn and improve by receiving feedback from the discriminator on the quality of the generated outputs, effectively enabling the model to produce high-quality synthetic data that closely resembles real data.

Understanding GANs is crucial for applications in image synthesis, video generation, and various other AI-driven creative tasks, making this concept foundational in generative AI. The other options do not accurately represent the well-established terminology or functionality associated with GANs, as they either mislabel the network or describe unrelated concepts within the domain of machine learning.