Our -enhanced abilities to decode languages have reached a point where they could start to parse languages not spoken by anyone alive.
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Each time any of us uses a tool, such as Gmail, where there’s a powerful agent to help correct our spellings, and suggest sentence endings, there’s an machine in the background, steadily getting better and better at understanding language. Sentence structures are parsed, word choices understood, idioms recognised.
That exact capability could, in 2020, grant the ability to speak with other large animals. Really. Maybe even faster than brain-computer interfaces will take the stage.
Our -enhanced abilities to decode languages have reached a point where they could start to parse languages not spoken by anyone alive. Recently, researchers from MIT and Google applied these abilities to ancient scripts – Linear B and Ugaritic (a precursor of Hebrew) – with reasonable success (no luck so far with the older, and as-yet undeciphered Linear A).
First, word-to-word relations for a specific language are mapped, using vast databases of text. The system searches texts to see how often each word appears next to every other word. This pattern of appearances is a unique signature that defines the word in a multidimensional parameter space. Researchers estimate that languages – all languages – can be best described as having 600 independent dimensions of relationships, where each word-word relationship can be seen as a vector in this space. This vector acts as a powerful constraint on how the word can appear in any translation the machine comes up with. […]