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Explained: NLP in artificial intelligence

Explained: NLP in artificial intelligence

NLP in artificial intelligence is one of the aspects people wonder about, and this article will concentrate on its explanation while giving a couple of examples. It is a very important subject in the future of AI development, and a few aspects must be covered to understand the basics of it.

Artificial intelligence has become a trend in today’s technology world. Some of the biggest companies and the ones that have gained fame lately are racing with each other to build the best AI tool for different needs. The needs of humanity are taken into consideration, and making simple jobs easier is the most basic goal for the projects that aim to have an influence on the majority of the community. NLP in artificial intelligence is one of the aspects that these companies tend to concentrate on. Bear with us if you want to know the basics of it!

What is NLP in artificial intelligence?

NLP in artificial intelligence is the abbreviated version of “natural language processing.” It is a subdivision of artificial intelligence concentrated on landing a hand on computers to understand how humans write and speak. According to the University of York, it is a difficult task because it involves a lot of unstructured data. Almost every one of us has a unique way of speaking and writing with different languages and a tone of voice, and in a way, NLP in artificial intelligence helps computers act as one of us.

There is a vast amount of unique natural language data, which is why the University of York states it is a difficult task. However, technology has evolved to a point where AI chatbots or voice-controlled assistants interact with us like normal humans. Of course, they are not perfect and sometimes make obvious mistakes but considering their current state, it would be harsh to say that they are nowhere near decent.

Areas that use NLP

As mentioned above, chatbots and voice-controlled assistants are some of the most used areas that need NLP in artificial intelligence. However, the list continues and doesn’t end with the two areas. According to the University of York, below are the real-world applications and use cases of NLP:

  • Voice-controlled assistants like Siri and Alexa.
  • Natural language generation for question answering by customer service chatbots.
  • Streamlining the recruiting process on sites like LinkedIn by scanning through people‚Äôs listed skills and experience.
  • Tools like Grammarly which use NLP to help correct errors and make suggestions for simplifying complex writing.
  • Language models like autocomplete which are trained to predict the next words in a text, based on what has already been typed.

Grammarly is a highly-used tool that corrects grammar mistakes and helps you write something more professional with fewer mistakes. NLP in artificial intelligence provides assistance and lets the process happen so people can use the service. All of the above have a learning capacity, and the more we use them, the more they learn, including Google Translate. It is one of the most popular translation tools worldwide, with millions of users. It uses a special system that helps increase translation fluency using a large artificial network.

Relation between AI and NLP

People who are unfamiliar with the current state of AI are often surprised by the capabilities of some AI tools. It mainly relies on the tool’s ability to interact closer to the human level. NLP in artificial intelligence helps the tool claim its intellect and act accordingly. To help AI reach higher levels and act more like one of us, NLP must be applied, which is why it is a field that companies concentrate on.

How does it work?

It is difficult to execute and understand as it requires multiple complex techniques. Most simply, the process starts with formulating an algorithm. There are different machine learning methods that could be used in the process. The Natural Language Toolkit, which was written in Python, could help NLP in artificial intelligence, in the means of tokenization, part of speech tagging, and more. Syntax analysis is the step used to understand what the mentioned information means exactly, taking the grammar rules into consideration. Sentiment analysis is also done to measure the tone in social media comments and such. It is used by businesses to monitor customer feelings.

NLP in artificial intelligence has different important roles and aspects if you dive a little deeper into it. The information above mainly covers the basics. All the structured ways have a lot more, and if you are interested in them, we recommend you search them one by one to understand better how NLP in artificial intelligence works.

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