What is Natural Language Understanding?

Natural language understanding is a field of natural language processing focused on machines’ comprehension of instructions and input made in text or speech. The field studies artificial intelligence and its ability to interact with humans based on its understanding of language inputs both simple and complex. Natural language understanding is studied both in things as small as one-word or short phrase commands, as well as structures as large as poems, letters, and even literature.

One of the major goals in natural language understanding is the creation of AI tools that can communicate with humans organically for a variety of purposes. The field has already produced important milestones, including Apple’s Siri and Microsoft’s Cortana.

The technology is also seen in chatbots used by companies like Facebook on their messenger platform.

Augmented Analytics

In analytics, natural language understanding is useful for simplifying the querying and modeling process. Whereas traditional analytics require complex parameters and instructions for data discovery, NLP analytics let users pose their queries in a normal, non-scientific language.

How Can I Use Natural Language Understanding?

One of the most popular uses for natural language understanding is in the use of the chatbots that operate on some websites. While it would be inefficient to have a human being staff each chat and help the thousands of clients that click on the chatbox, an AI bot that can communicate with humans at a satisfactory level with zero overhead.

Thanks to natural language understanding, the bots can understand questions and requests made in normal English and respond accurately and quickly. This can expedite on-boarding, sales, support, and more.

Another important use for the field is in database and search-engine querying. Search giants like Google and Bing use natural language understanding to allow users to enter their searches in whatever language they are comfortable in. By breaking down search requests into simpler terms and understanding linguistic and structural cues, AI can return better and more relevant results.

In business intelligence and advanced analytics, natural language understanding allows for easier searches and more actionable results. Instead of having to create complex algorithms to find data in warehouses, individual users can quickly find what they need in a familiar way, and without the assistance of costly specialists.

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