To create an image-generating model from the beginning, you first need to show a computer a massive library of pictures, each with a description of what it shows. The AI learns through a process of destruction and recreation; it takes a clear image, adds random noise until it's just static, and then is trained to reverse that process, using the text description as its guide to remove the noise step-by-step and rebuild the original image. By repeating this with millions of different images and descriptions, the model learns the connection between words and visual information, eventually gaining the ability to generate a completely new, coherent picture simply from a new text prompt it has never seen before.