If Sora is used to generate cinematic sequences dynamically (e.g. in games, interactive media, or storyline branching), systems need the ability to retrieve stylistically consistent clips or interpolate between clips seamlessly. A vector database can store clip-level embeddings (e.g. average embedding of a multi-frame shot) and allow rapid lookup: given a current shot embedding, you can query for the next shot embedding that matches style, mood, or transition coherence. This enables continuity in sequencing or smooth transitions.
Furthermore, interpolation is possible: by querying nearest neighbors in embedding space, you can blend or morph between two stylized clips, using their embeddings as control points. This supports smooth transitions or hybrid visual effects. Because embedding retrieval is fast, it can be done in real time as user choices drive which clip to show next. The vector DB becomes part of the dynamic generation control logic: linking scene graphs, embedding navigation, and generation steering. In short, vector databases unlock intelligent, coherent sequencing and interpolation in cinematic AI video pipelines.