Think of a GAN as two machine learning models that work against one another (creating what some would call a basic Ai). We start with a pre-made GAN and feed it input (images and text prompts), we then tweak the code and train it to produce a "correct" result. Feel free to join the community where you'll find all kinds of GAN tips, as well as free advice from peers. Alternatively, sign up for the waitlist below and we'll be in touch when the time is right.