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Creating a translation machine has long been seen as one of the toughest challenges in artificial intelligence.
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In 2010, a startup called Quest Visual created a translation app called "Word Lens".
The ultimate goal was to create a translation process where content validity and other measurement properties are comparable to the original language version.
Once this is done and a vector representation is created, a translation can be outputted one word at a time until it's complete.
The idea is to create a translation product that allows wearers to actively engage one another through eye contact and body language — which remain important insight even when you don't share a language.
The industry standard uses software that creates a "translation memory".
This process requires translation by two independent translators and subsequent reconciliation to reach consensus, creating a "harmonized" translation.
He mentioned the prospect of creating a great translation service, so the entire Internet would have a lingua franca that anyone could use.
Inexperienced translators can see how other learners have rendered a given text and evaluate each other's work, thus creating an optimised translation through sheer force of numbers.
After Dylan moved back to New York City, in the late sixties, he was dogged by a man named A. J. Weberman, who created a peculiar translation system to "decode" Dylan's lyrics — "in Dylan's language Texas might mean 'Europe' " — and even went through his trash.
We show that translation in vitro and in vivo is initiated exclusively from the AUG of this motif, and that the AUG flanking sequences create a strong translation initiation context.
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Since I tried Ludwig back in 2017, I have been constantly using it in both editing and translation. Ever since, I suggest it to my translators at ProSciEditing.

Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com