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Maybe it's me reading too deep into it, but that article sounds like the author had strongly held predetermination that simplistic ML translations that generate malignant deformations of English are "obviously objectively better", and could not accept the evaluations from actual first language speakers that they don't even make sense. IOW the fight had already happened and the author won by power. Two points that stuck up to me: > [x] Try some more sentences. Which is better, ML or human translation? In which cases? Any English second language speaker just knows this: There are basically zero cases where ML translation is in any way better or more accurate. That includes DeepL and ChatGPT w/GPT-4 proper. It's just tap water at restaurants. Which is a fantastic choice to pair with actual drinks. It's weird this sentence appears here at all. > [...]and why is TextBlob so good at translation? Well, behind the scenes, it's using Google translate, a sophisticated AI able to parse millions of[...] And this part. Maybe it's just me, but I think it might be showing that the author first tried to hand-roll translation, as seemingly needlessly lengthily elaborated up to this part. It could be that they then either faced technical challenges or failed validation by certified Frenchmen, and had to rewrite the section as a guide to use Google Translate API. There seems to be an endemic misconception, mostly seen among but not limited to American people, that American English is a perfect language that is also completely disconnected from internal thoughts and intents and monologues, that simplifies language translation problem to a simple matter of "convert[ing] the formal grammar rules for one language, such as English, into a non-language dependent structure, and then translate it by converting back to another language" as the author claims, while in reality even the possibility of "non-language dependent structure" is still under debate. This kinds of attitude always existed, but now it's borderline beyond annoying. |