AI Video, Explained
What a Video Diffusion Model Actually Does
Diffusion models learn to turn random noise into a realistic image by reversing a process of gradually adding noise. Video versions do the same thing across time as well as space.
Start from noise
The model begins with a field of random static and step by step removes it, guided toward an image that matches the prompt and the input photo.
Do it for a whole sequence
A video model denoises many frames together, with an added constraint that consecutive frames must look like natural motion, not a slideshow.
Why the first frame matters so much
Your photo anchors the sequence. Everything the model generates afterward is trying to stay consistent with that starting point, which is why a clear source image gives a cleaner clip.
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