How do Generative Adversarial Networks work?
An example of an AI chatbot conversation about how GANs function and their applications.
Can you explain how Generative Adversarial Networks work?
Sure! Generative Adversarial Networks, or GANs, consist of two neural networks: a generator and a discriminator.
What does the generator do?
The generator creates new data instances, while the discriminator evaluates them against real data to determine authenticity.
How do they improve each other?
They engage in a game where the generator tries to produce better fakes, and the discriminator gets better at spotting them.
What are some applications of GANs?
GANs are used in image generation, video creation, and even in enhancing image resolution.
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