The first significant breakthrough in the potential of mechanised translation came in the early 1990s when IBM produced a model that abandoned any effort to have the computer 'understand' what was being fed into it and instead approached the task by installing in the computer the comparative versions of as much translated text as possible and having the system compute the probability of meanings of words and phrases based on statistical precedent.

The cold war prompted ambitious efforts by American intelligence agencies to understand the 'code' of the Russian language on an industrial scale. The initial – unsuccessful – attempts were based on the principle that all languages could be distilled into two components: a lexicon of words with specific meanings, and a set of rules of grammar and syntax by which those words were linked together.

What follows is more representative of what the system is capable of.Įver since computers were a reality, the possibility of using their logistical power to break down barriers of language has been something of a holy grail in machine learning.

Somebody has obviously got to the first line of Tolstoy's masterpiece and put it right. The reason for this discrepancy lies in one of the nuances of Google's system that allows interested users to improve translated texts where they can. It's just about explicable, if we know the original, but barely readable. The situation is now lasted three days and were painfully conscious of themselves and their spouses…' Wife found out that my husband was in connection with the former in their house, a French governess, and told my husband that he could not live with him in the same house.

Call in french google translate