Creating a translation machine has long been seen as one of the toughest challenges in artificial intelligence. For decades, computer scientists tried using a rules-based approach — teaching the computer the linguistic rules of two languages and giving it the necessary dictionaries.
But in the mid-1990s, researchers began favoring a so-called statistical approach. They found that if they fed the computer thousands or millions of passages and their human-generated translations, it could learn to make accurate guesses about how to translate new texts.
Cool article about Google’s Translation Tool. The list of projects that might be easier to takle with billions of data points instead of rules is endless, & probably includes fields like healthcare, meteorology, calling football plays, etc.
via Andy McAfee
