Personally, I decided using a local LLM was acceptable for generating translation strings in my open source application. It had already been manually translated into a bunch of different languages by various contributors over the years, but I just did a major UI rework and so most of the existing translations now had a ton of missing entries. Qt6’s translation tool had an AI Translation function so I decided to try it out after setting up ollama and the recommended qwen3 model. It did a pretty decent job as far as I can tell, I am only fluent in English but I did some cross checking by translating back to English via Google Translate and it seemed to do a decent job. It at least got all the strings translated to something usable, once it’s merged then I expect native speakers will contribute cleanups and rewordings if needed.
I don’t really consider translation purely generative as it is more of a conversion task. I think AI is pretty useful for this. Same for things like automatic captioning and even mundane text to speech (if not being used to replace voice acting).
My Reolink cameras have pretty good AI detection, I think that is a decent use of AI if it runs locally. I like seeing the “Animal” detections from my doorbell camera, it’s usually a cat or a rabbit investigating the front steps.