what is the idea behind Generative Adversarial Networks (GANs)? Select anyone. 1. Agents. 2. Neural networks use. 3. LLMs. 4. Pitting 2 Neural networks against each other.

The idea behind Generative Adversarial Networks (GANs) is primarily about **pitting 2 neural networks against each other**. In a GAN, there are two components: a generator and a discriminator. The generator creates fake data, while the discriminator evaluates the authenticity of the data (whether it is real or generated). The generator aims to improve its performance to fool the discriminator, while the discriminator strives to become better at distinguishing real data from fake data. This adversarial process leads to the generator producing increasingly realistic data over time.