Before I show you some examples of machine translation, I would like to talk about the article "Lost in AI translation: growing reliance on language apps jeopardizes some asylum applications".
The article discusses the struggle that arises from the frequent usage of machine translations in asylum applications. It starts with the story of Carlos, who fled Brazil and came to the US after a tragic experience. It is well known that an asylum application is a dreadful process for refugees, especially because of the language barrier and a lack of in person translator that is tried to be covered up by machine translations. Carlos, who speaks Portuguese and has been a victim of this case, has spent six months in Ice detention without his family due to the communication barrier.
I am at awe of the lack of human translators in an institution that is as important as the place where the asylum applications are processed. It is even more concerning that the applications can be denied due to errors that occurred because of the false machine translations that are unable to catch the many nuances of a language. I am also quite interested in how much time has been spent to perfect machine translations, in which, to this day, haven't been able to achieved.
It also made me remember how Japanese machine translations were actually getting accurate a lot faster due to a lot of feedback from users. However, since it is a language with many nuances, words and phrases that do not exist in other languages, I assume that it still has a lot of way to go.
That being said, let's look at some machine translations:



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