[mathgorges]

This hasn't been my experience with English/Japanese translation with Google Translate. For context I used Google Translate for pair programming with Japanese clients 40 hours per week for about 6 months, until I ponied up for a DeepL subscription.

As long as you're expressive enough in English, and reverse the translation direction every now and again to double check the output then it works fine.

[thrdbndndn]

As I mentioned in another reply, the scenario here is translating "artistic" or "real-world" (for lack of a better term) literature accurately—whether it's a novel, a YouTuber's video, casual conversation, or blog posts/tweets with internet slang and abbreviations. In these cases, getting things 95% right isn’t enough to capture the nuances, especially when the author didn’t create the content with translation in mind (which I believe matches your experience).

Machine translation for instructional or work-related texts has been "usable" for years, way before LLM emerged.

LLM-based translation has certainly made significant progress in these scenarios—GPT-4, for example, is fully capable IMHO. However, it's still not quite fast enough for real-time use, and the smaller models that can run offline still don't deliver the needed quality.

[numpad0]

English -> Japanese machine translations(whether it's GT or DL or GPT) are fairly usable these days in the sense that it reduces interpretation workload to trivial amount especially with typical skillset of a Japanese white collar workers, or not perfect in the sense that the fact that the output is a translation is always apparent to native speakers - but that is the case too even with offline human translators, so could be a moot point.

Anyway, the current state of affairs float somewhere comfortably above "broken clock" and unfortunately below "Babelfish achieved", so opinions may vary.