Artificial Intelligence Now

Chapter 14. Three Three Tips for Getting Started with NLU

Alyona Medelyan

What makes a cartoon caption funny? As one algorithm found: a simple readable sentence, a negation, and a pronoun—but not “he” or “she.” The algorithm went on to pick the funniest captions for thousands of the New Yorker’s cartoons, and in most cases, it matched the intuition of its editors.

Algorithms are getting much better at understanding language, and we are becoming more aware of this through stories like that of IBM Watson winning the Jeopardy quiz. Thankfully, large corporations aren’t keeping the latest breakthroughs in natural language understanding (NLU) for themselves. Google released the word2vec tool, and Facebook followed by publishing its speed-optimized deep learning modules. Since language is at the core of many businesses today, it’s important to understand what NLU is, and how you can use it to meet some of your business goals. In this article, you will learn three key tips on how to get into this fascinating and useful field.

But first things first: what does “natural language understanding” actually mean? Whenever a computer understands written language—or in other words, derives the meaning of words, sentences, or text—we call it natural language understanding. When understanding spoken language, such as voice commands or recorded speech, a process called automatic speech recognition transforms it first into written words.

NLU is technically a sub-area of the broader area of natural ...