If AI truly wanted to excel in the world of communication, and many more areas, then engineers should’ve devoted all of their time into translating langauges. Because Learning a new language is fucking hard, it’s difficult because you have to not only understand different forms of grammar but also sentence structure, dialect, how to articulate sentences and phrases automatically from one another.
Some words andhow they are spelled could mean from a different mark and abrasion to a whole different meaning and to a whole different context.
Perfect Example; Japanese Katakana is IMMENSELY different than Kanji and Hiragana, yes they do mean similar but if you fucking translate it to english, there’s no ACTUAL ONE TO ONE EQUIVALENT.
Yoroshiku onegaishimasu CAN mean: Nice to meet you, I’m counting on you, pelase take care of me, thanks in advance or I appreciate your cooperation.
It can literally mean several tons of things. But meanwhile English; there’s nothing we can say that can equal to that besides those translations. There’s no blanket words for context situations.
Another example; German gives us Schadenfreude: pleasure at someone else’s misofrtune, but we borrow the word because translating it into English takes a whole ass sentence.
Many different words in general arabic, mandarin, navajo, finnish, turkish each language encodes how we see things completely different. But what did we do with a tool that can make our lives easier?
We obsess over AI making Art, Music, and Videos. Meanwhile, the crux of the barrier of one of the hardest things in our society and existence is literally right there. God what a waste.
They have been focussing on translation — and translation has long been held as one of the jobs that is most likely to be fully automatable; back in 2025, Microsoft published research that argued this, and news media has frequently argued that translators are at particular risk to job loss due to AI.
In practice, as has often been the case with AI, these promises have largely failed to materialise. Although the jobs market has gotten a lot worse for translators, we’ve seen time and time again that AI just isn’t anywhere close to being able to fully replace human translators. Projects that rely entirely on AI end up producing awful translations that just aren’t up to scratch, and projects that use human translators but force them to use AI just end up causing those humans to spend longer cleaning up a terrible translation than it would’ve taken to just do it themselves.
The journalist Brian Merchant (author of “Blood in the Machine”) has an excellent article covering a variety of perspectives from translators. If you want an in depth perspective from someone close to the ground, Lucile Danilov is a games translator who has written an excellent piece here that I’d highly recommend.
The fact that they’ve been trying pretty damn hard to make AI capable of fully replacing translators but are still having such mediocre results leads me to believe that we’re not going to see it happen any time soon. All of the nuance and complexity in language that makes it tricky to translate for humans is why it’s even harder for a stochastic parrot.