The process typically begins with a neural network trained on vast datasets of images and their corresponding textual descriptions. These datasets help the AI understand the relationship between words and visual elements, such as shapes, colors, and objects.
Stable Diffusion specifically uses a technique called "diffusion," which involves progressively adding noise to an image in multiple steps, then learning how to reverse this process. Initially, the model takes a random noise pattern and, through iterative steps, refines it into an image that matches the text description. At each step, the model “denoises” the image, improving its clarity and structure, until it finally produces a coherent and detailed image that reflects the input prompt. This process allows the AI to generate highly creative and detailed images based on even vague or complex text inputs, providing impressive flexibility and realism.
I have one section on my website (Work) where I show a selection of AI generated images. I use Adobe Firefly or Midjourney, but not exclusively. For videos I use Runway.
Images: AI generated