New to image generators? Start gently.
You don't need an account, an install, or any prior experience with Midjourney, DALL·E, or the rest — about one in five people arrive here having used none of them, and that's a fine place to begin. Open the Diffusion Step-Through Viewer first and watch an image surface from pure noise; then the mechanisms below will have something to hang on. Everything runs in your browser on frozen examples.
An image is numbers first. Recognition returns cue by cue — colour, outline, texture, context.
The image is refined from pure noise toward a prompt-guided result, step by visible step.
Each added word steers the denoising — and each omitted word leaves a gap the model fills.
Vague prompts reveal what the training data assumes a doctor, classroom, or home looks like.
Welcome & bridge
Session 1 → Session 2: text becomes tokens; images become pixels, features, and learned patterns. Choose a pathway.
Feature / pixel activity
Switch image types and reduce detail until recognition becomes difficult. Which cues return first — colour, outline, texture, context, location?
Diffusion step-through
Move slowly from noise to final image. Describe what appears at each stage: composition, subject, edges, texture, detail.
Default Test
A vague prompt — "a doctor," "a classroom," "a beautiful home." Generate, observe, or critique outputs and fill the Image Default Test Board.
Debrief
What did the system fill in without being asked — and where might those defaults come from? Share one default and one responsible revision; chat shares can be pasted into the Evidence Wall.
Every activity works with the simulated viewers and the pre-generated Image Prompt Pack — no image generator account needed. Critique and teaching-design pathways use the same evidence. Opting out of direct AI use never means opting out of the camp.