Machine learning has been used to automatically translate long-lost languages

The big idea behind machine translation is the understanding that words are related to each other in similar ways, regardless of the language involved. So the process begins by mapping out these relations for a specific language. This requires huge databases of text. A machine then searches this text 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. Indeed, the word can be thought of as a vector within this space. And this vector acts as a powerful constraint on how the word can appear in any translation the machine comes up with. These vectors obey some simple mathematical rules.