DeepL already beat Google Translate years ago.
Specifically, LLMs have a context window larger than a sentence. So can eg infer gender throughout documents. Neither DeepL or Google Translate did that.
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DeepL already beat Google Translate years ago.
Specifically, LLMs have a context window larger than a sentence. So can eg infer gender throughout documents. Neither DeepL or Google Translate did that.
Pretty much all LLMs easily beat Google Translate, this is not news... One of the best yet unplanned features of them imo.
ChatGPT 3 was already far beyond google translate in my attempts, mostly using it between English, Danish and Swedish. Even being able to ask it to translate song lyrics while retaining rhyming structure was sometimes not too bad :)
Pretty much all LLMs easily beat Google Translate, this is not news... One of the best yet unplanned features of them imo.
Earlier quoted context omitted.
Orders of magnitude more energy necessary though.
The GPT 3.5 API is cheaper than Google Translate. And in our testing (over a year ago) was better for translation. So I assume in that case the energy use is less?
Earlier quoted context omitted.
Didn't "Attention Is All you Need" bill transformers primarily as a translation model?
Yes, it was primarly for translation. I don’t know how OP come to the conclusion that it was accidental
Yeah this is old news. When i was in China last year google translate seemed to literally never work (looks of confusion trying to do basic interactions in stores). GPT-4 worked perfectly every time, I think google translate might be another soft abandoned project from google
> I think google translate might be another soft abandoned project from google There are 100+ people working on Google translate and associated stuff (the mobile apps, the serverside stuff, etc). I guess they're all asleep.
DeepL already beat Google Translate years ago.
People trust Google Translate to not go off-topic or "hallucinate" and there is still a lot of value in something semi-deterministic like that. (Edit: To clarify, maintaining semantics is held sacrosanct in classical methods of machine translation)
Then "people" have no idea what they're doing. Google Translate and Deepl "hallucinate" way more than the likes of GPT-4 and Claude 3 for Translation.