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AI Video Generation

Definition

Using AI to turn a written idea into a finished video. Models write the script, generate the visuals, speak the narration, score the music, and cut it all together. What used to need a writer, a camera, a voice booth, and an editor now runs as one automated pass.

Three model families do the work and they run in order, not all at once. A language model drafts the script and splits it into scenes. A speech model reads the narration aloud. An image or video model renders frames for each scene, sized to how long that narration runs. Music comes from a model or a library, and an assembly pass burns in the captions and cuts everything to length.

The sequence is what separates a usable tool from a demo. The script decides the scene count, the scene count decides how much footage gets generated, and the narration length decides how long each shot has to hold on screen. Break that chain anywhere and you get a video that ends on five seconds of silence over a still image.

Cost follows the same logic. A small flat fee covers the script, the standard voice, the music, and the render, and the visuals are priced on top: by length for video clips, by generated image for photo scenes, with a small extra per scene for the premium voice on Pro and Studio. The exact rates sit on the pricing page, and every video is quoted in credits before the render starts.

The limits are worth knowing before you plan a series around this. Character continuity across scenes is unreliable, so the same person in scene one and scene five can come back with a different jaw. Text rendered inside a generated image is a coin flip on most models, which is why titles get composited afterward instead of prompted in. Anything that has to show a specific real product or a real building needs a reference image rather than a description.

Where it earns its keep is volume. One idea, ten variants, all rendering while you write the next batch.

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