Generative Adversarial Networks, or GANs, are a type of artificial intelligence where two neural networks compete to improve each other’s performance. One network creates new data, such as images or sounds, while the other tries to detect if the data is real or fake. This competition helps both networks get better, resulting in highly realistic…

Diffusion models are a type of machine learning technique used to create new data, such as images or sounds, by starting with random noise and gradually transforming it into a meaningful result. They work by simulating a process where data is slowly corrupted with noise and then learning to reverse this process to generate realistic…