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What are Generative Adversarial Networks (GANs)?


ChatGPT and Stable Diffusion are GAN models. But what is a GAN ?


GAN models combine two neural networks, one as generator and another as discriminator, that compete against each other in a game-like setup.


Generator generates synthetic data (e.g., images, text, sound) from random noise, while the discriminator’s has to discriminate between real and fake data.


The generator aims to create increasingly realistic data to deceive the discriminator, while the discriminator improves its ability to differentiate real from generated data.


Through this competition, GANs are capable of generating highly realistic content in images, text and sound.


They are used in text to image generation, image to image translation, photo editing, generate realistic human faces, 3D objects from 2D images and video prediction.




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