Spam detection: NLP can use a number of rules to clear out emails and texts that (hopefully) are spam, weeding out messages that include poor spelling, bad grammar, inappropriate urgency, and other common features of nuisance messages.
Machine translation: Translating words from one language into another isn't always a straightforward proposition. IBM notes, for example, that the English phrase, "The spirit is willing, but the flesh is weak," was originally translated into Russian as "The vodka is good, but the meat is rotten." The Google (GOOG -2.25%) (GOOGL -2.01%) Translate service remains the standard.
Virtual agents and chatbots: As better algorithms are developed, chatbots are becoming slightly less aggravating than automated telephone customer service responses. Likewise, virtual agents like Siri and Alexa continue to improve, recognizing context and providing better answers.
Social media sentiment: NLP is not only becoming a defense against disinformation and hate speech on social media but can also tell companies how their customers truly feel about their products, promotions, and events. Sentiment analysis can help companies design better products and advertising.
Text summarization: This uses NLP to synthesize and summarize large volumes of text. Some applications can even use rudimentary reasoning to generate context to the summaries, as well as conclusions.
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