Examples of natural language processing systems in artificial intelligence
Over the last few years, there has been an ongoing conversation about Artificial Intelligence and how it is going to change our lives and how we do business. So, if you’ve been keeping up with the latest technology trends, then you know that artificial intelligence has the potential to be the most disruptive technology ever. Today, we can ask Siri or Google or Cortana to help us with simple questions or tasks, but much of their actual potential is still untapped. The reason why involves language.
This is where natural language processing (NLP) comes into play in artificial intelligence applications. Without NLP, artificial intelligence only can understand the meaning of language and answer simple questions, but it is not able to understand the meaning of words in context. Natural language processing applications allow users to communicate with a computer in their own worlds, i.e. in natural language.
As we have already (see about natural language processing systems), Natural Language Processing (NLP) is a fundamental element of artificial intelligence for communicating with intelligent systems using natural language. NLP helps computers read and respond by simulating the human ability to understand the everyday language that people use to communicate. Today, there are many examples of natural language processing systems in artificial intelligence already at work.
Examples of natural language processing systems in artificial intelligence: list
- Communication: Many communication applications such Facebook Messenger are already using artificial intelligence. On the whole, Facebook looks very interested in AI. Some months ago, Facebook announced its M service that promises to become your personal assistant (with the public launch date tbd): “M can do anything a human can.” When you request something that M can’t do on its own, it sends a message to a Facebook worker and, as they work with the software, the AI begins to learn. Another interesting application of natural language processing is Skype Translator, which offers on-the-fly translation to interpret live speech in real time across a number of languages. Skype Translator uses AI to help facilitate conversation among people who speak different languages. This is great news! Without language barriers, people can communicate using the language they are comfortable with, which will in turn speed up a range of businesses processes.
- Faster diagnosis: Examples of natural language processing systems in artificial intelligence are also in hospitals that use natural language processing to indicate a specific diagnosis from a physician’s unstructured notes. For example, NLP software for mammographic imaging and mammogram reports support the extraction and analysis of data for clinical decisions, as a study published in Cancer affirms. The software is able to determine breast cancer risk more efficiently, decrease the need for unnecessary biopsies and facilitate faster treatment through earlierdiagnosis. According to the study, artificial intelligence reviewed 500 charts in but a few hours, saving over 500 physician hours. “Accurate review of this many charts would be practically impossible without AI,” the author Stephen T. Wong said.
- Customer Review: Natural language processing in artificial intelligence applications makes it easy to gather product reviews from a website and understand what consumers are actually saying as well as their sentiment in reference to a specific product. Companies with a large volume of reviews can actually understand them and use the data collected to recommend new products or services based on customer preferences. This application helps companies discover relevant information for their business, improve customer satisfaction, suggest more relevant products or services and better and understand the customer’s needs.
- Virtual digital assistants: Thanks to smartphone, virtual digital assistant (VDA) technologies (automated software applications or platforms that assist the human user by understanding natural language) are currently the most wellknown type of artificial intelligence. Many companies are understanding the importance of the VDAs for their businesses and are investing significant resources to stay up to date. According to a study published by Research and Markets, VDA users will grow from 390 million in 2015 to 1.8 billion worldwide by 2021, while enterprise VDA users will rise from 155 million in 2015 to 843 million over the same period. VDAs are able to assist the consumers with transaction activities or optimize the call center operations to offer a better customer experience and reduce the operational costs. We will increasingly see these applications in other devices such as PCs programs, smart home systems, automobiles and in the enterprise market.
If these simple examples of natural language processing applications in artificial intelligence are any indication, the next Artificial Intelligence software and applications will improve our ability to transform unstructured data into valuable business insight and make smart automated decision-making part of our everyday lives.