Natural language processing is a key part of artificial intelligence and computer science that enables machines to understand and infer meaning from human language. It involves teaching AI applications to analyze language by breaking it down into smaller semantic units, classifying words as nouns, verbs, adjectives, etc., and developing complex algorithms to represent these rules. This process allows AI apps to carry out tasks such as language generation, answering questions, sentiment analysis, text classification, and machine translation. Human trainers feed massive amounts of training data to the computer, label it with language rules, and fine-tune the model with reinforcement feedback to enable it to generate coherent responses and understand user intent. The process involves tokenization, part-of-speech-tagging, stemming, dialogue management, and deep learning algorithms that form the basis of its language model.