In the past two years, the most significant change in the field of AI video generation is not how much the image quality has improved, but rather that "controllability" has become the main focus of product competition. The first generation of cultural video tools solved the problem of "whether or not there is" - inputting a sentence to get a fairly beautiful picture; The real watershed lies in whether the generated results can be controlled according to the creator's intention.
Control is reflected in several levels. One is the control of camera language: whether the camera position, scene, and camera direction can be accurately specified, rather than relying on repeated card draws and luck. The second is the consistency between the character and the scene: whether the same character can maintain stable appearance, clothing, and temperament in multiple shots and scenes is the key to moving from "single video" to "narrative content". The third is the control of the time dimension: the transition between keyframes and the fine-tuning of action rhythm determine whether the generated material can be edited into the real production process.
For creators, when choosing tools, they may want to ask themselves three questions: Do I want an inspiration draft or a piece of material? How many rounds of trial and error costs can I bear? Can the generated results be smoothly exported to my editing and compositing workflow? It is much more practical to first think clearly about the purpose and then compare the investment of each company in controllability, rather than simply focusing on whether the demonstration clip is stunning.
We also need to pour a bucket of cold water: Currently, AI videos still have obvious shortcomings in physical laws, hand details, and long shot narrative, and commercial materials often require manual post production support. Using AI videos as an "infinitely cheap rehearsal and material generator" rather than a "fully automated filming machine" is a more rational approach at present.
Overall, "controllable" is replacing "generative" as the core benchmark for measuring AI video tools. Whoever makes a real breakthrough in consistency, camera control, and workflow integration first is more likely to get the ticket to the next stage.
Reference: Comprehensive compilation of industry information that has been publicly released.