Why should we care about Natural Language Disambiguation?

Natural language processing (NLP) is one of the latest applications of artificial intelligence (AI). NLP allows computers to process and understand the complexities of human language, and derive knowledge from it that can be used for a broad range of tasks.

Quite literally, the ability of computers to "hear" humans and make sense of what they say, NLP is used for translations, transcriptions, speech recognition, sentiment analysis, named entity recognition, pattern analysis, and much more. (Read How Natural Language Processing Can Improve Business Insights.)

Other than being used for practical applications, together with computer vision, this technology is a turning point in providing next-gen intelligent computers with the senses they need to perceive their surroundings and interact with the environment. (Read Computer Vision: Revolutionizing Research in 2020 and Beyond.)

Personal digital assistants (PDA) are probably one of the most immediate use of NLP. Alexa, Cortana, Siri, and OK Google couldn't "talk" or interact with us if they weren't able to understand what we say. A rather complex task, if we keep in mind that a computer cannot grasp all the subtle (but fundamental) non-verbal cues that so heavily characterize human language.

Even a slight tilt of an eyebrow or the tone of our voice can be used to convey irony, humor or disappointment — and completely subvert the meaning of a sentence. NLP is therefore critical to make these assistant smarter and more reactive.

This technology is going to become the new market standard soon enough, as it was already projected that by 2020, over 3.3 billion mobile users will have a virtual assistant installed on their smartphones.

And intelligent virtual assistants are becoming part of a much broader evolution of the marketing industry — a revolution that has already begun and that is changing the way we purchase and consume our products.

NLP is used for topic extraction, relationship extraction, automatic text summarization, and ultimately sentiment analysis.

All these uses are part of the larger field of behavioral analytics, which allow marketers and corporations to understand our individual needs to customize their offer. Data coming from virtual assistants is integrated with search engine queries, social media interactions, email text, and... well, probably even the conversations recorded by our IoTs.

In a nutshell, the more we talk and write, the better the machines will know us, and the more personalized our products and shopping experience will be.

But shopping is just the tip of the iceberg. NLP can be used to extract information from everything we say and write, and determine, for example, if we're committing a fraud, or perpetrating an act of terrorism that could be therefore stopped or prevented.