AI is ruling the digital world, and there shall be no doubt about it. There are different subsets or, shall we say, branches of artificial intelligence like NLP. Natural language processing (NLP) is a machine’s ability to understand human language and its context. You can easily extract core information and ideas from lengthy drafts using natural language processing.
As an internet user, you have experienced the use of a NLP application. The biggest and most common use of NLP today is by popular search engines such as Google and Bing. Search engines use this technology to propose relevant search results for users. Besides this, voice assistant applications like Bixby and Siri also use NLP to understand voice commands and propose accurate solutions.
You must know that natural language processing is very important and plays an important role in the modern world’s rise and acceptance of artificial intelligence. This article will discuss the most important reasons why NLP is so important for AI-powered resources. But before that, let us discuss the following:
Contents
How Does Artificial Intelligence Relate to Natural Language Processing?
Artificial intelligence and NLP are closely related as the latter is its sub-branch, which uses computers to understand and process large amounts of textual data. NLP helps machines understand and interact with humans more effectively. Because of NLP, modern AI generative tools can recognize patterns in speech and writing.
In addition to employing grammatical rules, classifiers, and other ways to determine what people mean when they interact, artificial language processing includes developing virtual assistants’ algorithms to understand words, phrases, and meanings based on context hints. Based on this understanding, machines can answer queries.
Common Applications of Natural Language Processing!
Here, we have discussed some examples of the use of NLP in different industries, showing you how important it is in the rise of artificial intelligence.
1. Voice Assistants
Natural language processing is used by voice assistants, also known as virtual agents. These utilities can easily analyze and recognize speech and commands and use NLP to respond to them. As mentioned before, the most common examples of NLP in the form of voice assistants are Siri, Bixby, and Alexa.
2. Chatbots
The working of chatbots is quite similar to that of voice assistants. The difference is that in chatbots, the user provides input in the form of text. Chatbots use natural language processing to recognize the context of text in the conversation to provide the most relevant and accurate responses.
3. Language Translation
You might have used digital services like Google Translate to translate content from one language to another. Well you must know that modern translator utilities also use natural language processing to understand the context of one language and convert text to the other.
4. Text Extraction
Natural language processing also enables certain tools to collect important information from drafts such as keywords. Many online keyword analyzer tools use this technology to find and pick the most relevant keywords/phrases.
5. Content Generation
Generative resources such as GPT66X also use natural language processing to generate content in response to a prompt given by users. NLP ensures that the output content is always close to a human writer. There is no way modern AI tools can create human-like content without the power of NLP.
Four Reasons Why NLP is Important for AI-Powered Machines!
Natural language processing is one of the most important reasons behind artificial intelligence’s success and so much acceptance. This is because of many reasons, some of which we have discussed below for your knowledge.
1. NLP Enables Machines to Understand Human Content
Natural language processing is the technology that enables machines and generative tools to understand human written text and speech. NLP bots are trained on huge amounts of data, enabling them to understand the core ideas and underlying meanings of content.
2. NLP Enables Machine to Create Human-Like Text
NLP is what makes machines and tools capable of creating human-like text. It understands how a human writes and can easily create content in a very similar style and tone. Content generator tools would have no value with NLP as their outputs would sound vague and irrelevant.
3. NLP Helps Machines to Analyze Sentiments
You would surely be surprised to know that natural language processing algorithms are also responsible for helping machines analyze sentiments and emotions in human content or speech. This makes the output content natural and emotionally right to the reader.
4. NLP Understands and Fixes Complicated Text
Here, you must also know that natural language processing and the combination of machine learning algorithms can help a machine or online tool like Grammarly to understand the complexities and errors in a piece of text and can also provide alternative solutions to make the new content more understandable.
Is There Any Career in Natural Language Processing?
NLP is growing rapidly and is improving every day. Along with the increased improvement in this technology, there is also a high demand for resources skilled enough to train machines to analyze human content. Some potential careers you can pursue in NLP include:
- NLP Researcher
- NLP Analyst
- NLP Scientist
- NLP Engineer
Leading tech companies from all across the globe employing AI for creating apps such as virtual assistants, chatbots, language translation, autocomplete, and content generation tools are in dire need of professionals with NLP experience.
Not only tech, but you would be surprised to know that healthcare, finance, marketing, and many other sectors have also started to shift their focus on developing AI resources to streamline their little jobs.
Conclusion
NLP, short for natural language processing, is an important AI technology. Without NLP, AI-powered tools cannot give out natural outputs. NLP is what helps machines understand how a human would write. These algorithms are trained on vast amounts of human written data to understand the writing style, emotions, sentiments, core ideas, and much more. Modern tools such as Chat GPT, Amazon 55x, Bard, Paraphrasers, Summarizers, and others are useless without the power of NLP.