personalization

The Videoclaw beta pairs an ordinary AI generation stack — talking avatars, cloned voices, images, video, captions and music — with a much less ordinary claim: a trainable style layer its makers describe as built-in taste you can train. This article separates the two, reads Humeo’s five published research areas to see where the personalization work actually sits, counts how many of the nineteen launch templates encode somebody else’s style rather than yours, sets out the four properties any style memory has to get right, names the lock-in and provenance risks, and gives a seven-day test that produces a real answer.