视频模型：从演示到生产的差距仍然很大

The pattern: Multimodal and video models produce stunning thirty-second clips in marketing demos. Production pipelines still collide with latency, weak temporal consistency, limited camera control, and brand-safety review that cannot be skipped. Why it matters: Treating video generation like image generation with a longer timeline underestimates cost and iteration loops. Teams that ship useful multimodal features usually start narrower: understand a clip, caption a meeting, extract frames for search — not "generate the campaign film." Where multimodal already pays rent Understanding — speech-to-text, scene captions, document + screenshot grounding for support and ops. Assisted editing — cut suggestions, B-roll search, style transfer on short clips with human final cut. Synthetic drafts — storyboards and animatics, not final pixels for regulated brands. What still blocks final-pixel shipping Identity consistency across shots, lip sync under noisy audio, and audit trails for every generated asset. Legal and brand review often dominate wall-clock time more than GPU inference. What we'd watch next Tools that expose controllable parameters (camera, duration, subject lock) and evaluation harnesses for temporal artifacts — not another open-ended "make a cool video" prompt box. Originally published on ayraix.com, practical AI for enterprise builders.