Despite the ubiquity of AI assistants like Siri or Alexa, teaching machines how to understand and wield human language remains a huge stumbling block in the field of artificial intelligence.This field of research—called "natural language processing" (NLP) and a core component of a machine passing the Turing test—got a big leg up in the 80s, when computer scientists began to turn to machine learning to help computers 'understand' human-speak. Now, AI uses even more sophisticated algorithms called neural networks that mimic the structure of the human brain to understand human language when it is encountered in the wild.In the 1970s, researchers had to program computers with a list of words and their meanings, as well as the rules of English grammar. The computer simply obeyed these hand-written rules. Now, with deep learning, we only have to give the computer examples of human language and let it figure out how it works. But NLP wouldn't have gotten to where it is today without a conceptual boost from NASA, which spent two years in the early 70s developing a natural language processing system to help its geologists classify moonrocks.Continue reading on Motherboard.