Generative AI Using GAN and Stable Diffusion
Generative Adversarial Networks (GANs) and Stable Diffusion are two powerful techniques that have been used to create realistic images and videos using deep learning. GANs use a two-part neural network, one part to generate images and another to evaluate how realistic they are. Stable Diffusion is a technique for modeling probability distributions using partial differential equations, which allows for the generation of high-quality images and videos. In this session, we will explore how these techniques can be used together to create even more powerful generative AI models.