Exploring the Applications of AI and NLP in Everyday Life

Exploring the Applications of AI and NLP in Everyday Life

Could you have ever imagined talking to your phone and getting things done, or having it respond to you? Thanks to Siri, Alexa, Google Assistant, and other digital assistants, this is now quite common. From asking about the weather to knowing their favorite color, you can inquire about anything to Siri and receive an answer.

These assistants work on Natural Language Processing (NLP), allowing your device to listen, comprehend, and act on your statements. Besides, NLP has numerous other applications, like translation and grammar checking, making tasks quicker and easier. The best part? It all happens in just 5 seconds!

The global revenue from the natural language processing (NLP) market is expected to grow quickly in the next few years. The NLP market is expected to be over 14 times larger in 2025 than it was in 2017, growing from approximately three billion US dollars in 2017 to more than 43 billion in 2025.

But this brings the question, what exactly is Natural Language Processing?  And explore the top 8 Applications of AI and NLP in Everyday Life that are driving change and revolutionizing industries this year. So let’s start with the answer.

What Is NLP?

Natural language processing (NLP) is the area of computer science, specifically, the branch of artificial intelligence, that provides computers the capacity to interpret text and spoken words in the same manner humans do.

NLP combines computational linguistics (human language rule-based modeling) with statistical, machine learning, and deep learning models. When these technologies come together, computers analyze human language in text or audio data and ‘understand’ its whole meaning, complete with the speaker’s or writer’s intent and emotion.

More than 50 years ago, linguistics gave rise to the first NLP models. Today’s most prevalent application of NLP technology can be found in your bag or pocket. Intelligent personal assistants in your home or phone use NLP and AI to provide a voice-driven interface for smart search.

The next time you use Siri, Alexa, Siri, Google, or any other virtual assistant, remember that these systems took decades to create and would not be possible without cutting-edge AI.

Applications and use cases for NLP in the real world include:

  • Voice-activated assistants like Alexa and Siri.
  • Artificial intelligence creates a natural language for chatbot customer service to answer questions.
  • Scanning through people’s listed talents and expertise on websites like LinkedIn to streamline the hiring process.
  • NLP-based tools, like Grammarly, can help correct and suggest simplifying tough writing.
  • The next words in a text can be predicted by language models like autocomplete, which are taught based on the previous characters typed.

The more we write, talk, and communicate with computers, the better they get at these tasks because they are always learning.

8 Applications of AI and NLP in Everyday Life.

Let’s explore the top 8 Applications of AI and NLP in Everyday Life that are driving change and revolutionizing industries this year. 

  1. Smart assistants

Voice recognition enables smArt assistants such as Apple’s Siri and Amazon’s Alexa to recognize patterns in speech, infer meaning, and provide a useful response.

We’ve become accustomed to saying “Hey Siri” and asking a question, and Siri comprehends what we’re saying and replying with contextually relevant answers.

And when we interact with Siri or Alexa through things such as thermostats, light switches, cars, and others, we’re growing accustomed to seeing them pop up around our homes and daily lives.

We now expect personal assistants like Alexa and Siri to understand context signals as they improve our lives and simplify chores like grocery shopping. We even prefer it when they respond with comedy or answer questions about themselves.

  1. Email Filtering

Email filtering is one of the most fundamental uses of NLP online. It started with spam filters, recognizing certain words or phrases in spam messages. Filtering has improved, as have early NLP adaptations.

Gmail’s email classification is among the most widespread and recent NLP applications. The system classifies emails into one of three groups based on their content (main, social, or promotional).

This keeps your inbox manageable for all Gmail users, with crucial, relevant emails you want to read and respond to as soon as possible.

  1. Language Translator

The technique of automatically translating a text from one language to another while keeping its meaning is known as machine translation. Machine translation systems were formerly dictionary and rule-based and were only somewhat successful.

Because of advances in neural network theory, the availability of large quantities of data, and fast processors, machine translation has become fairly precise in converting text from one language to another.

Text translation technologies such as Google Translate simplify converting text from one language to another. These technologies help a significant number of people and companies overcome language obstacles and succeed.

  1. Search Autocorrect and Autocomplete

When you enter 2-3 letters into Google to search for anything, it returns a list of potential search terms. If you search for something with errors, it will rectify them for you while still providing relevant results. Isn’t it amazing?

Everyone uses Google search autocorrect autocomplete regularly but rarely thinks about it. It’s a terrific example of how natural language processing affects millions of people worldwide, including you and me.

  1. Chatbots

Everything has been digitalized as technology has advanced, from education to shopping, buying tickets, and customer service. Instead of waiting a long time for quick and precise responses, the chatbot responds promptly and accurately.

NLP provides these chatbots with conversational capabilities, allowing them to reply correctly to customers’ wants rather than simply bare-bones responses.

Chatbots are also useful in situations when human resources are limited or not accessible around the clock.

Chatbots that use NLP also include emotional intelligence, which allows them to recognize and respond to the customer’s emotional feelings.

  1. Text classification

Text classification is the process of automatically interpreting, analyzing, and categorizing unstructured text, as well as sentiment analysis.

Assume you want to go through hundreds of open-ended responses to your most recent NPS survey. It would take a long time and be prohibitively expensive to do it manually. But what if you could train a natural language processing model to automatically classify your data based on predefined categories and your criteria in seconds?

You may use a topic classifier for NPS survey responses, which automatically tags your data by topics such as Customer Support, Features, Ease of Use, and PrPricing.

  1. Targeted Advertising 

One day, when I was looking for a Mobile phone on Amazon, Google began displaying adverts for relevant mobile phones on numerous websites. I am sure you have experienced it.

Yeah! I told you that it was targeted advertising. Online adverts that are displayed to users based on their online activity are known as targeted advertising.

The majority of internet businesses nowadays utilize this strategy because, first, it helps them save a lot of money, and second, it ensures that only potential clients see advertising that is relevant to them.

Targeted advertising works mainly on Keyword Matching. Only those who search for a keyword similar to the one to which the advertisement is related will see the Ads that are tied to a specific word or phrase.

That’s insufficient additional indicators, such as the most recent websites they visited and the pages they indicated an interest in, are all taken into consideration to display them the most pertinent adverts for goods they could find interesting.

  1. Question-answering

Another prominent use of natural language processing (NLP) is question-answering. Search engines bring the world’s knowledge to our fingertips, yet they fall short when it comes to answering questions presented by people in their language. Large technological businesses, such as Google, are following suit.

Question-answering is a Computer Science issue that falls within the fields of AI and NLP. It focuses on creating systems that can automatically answer human questions in their native language.

A natural language understanding computer system can employ a software system to transform sentences written by individuals into an internal representation, allowing the machine to provide legitimate responses.

These are the eight most practical applications of NLP, and they’re just going to get greater. Understanding NLP will surely be beneficial to you, and your business given its growth trajectory, which has proven to be a lifesaver in this scenario.

Wrapping It Up

Artificial intelligence is revolutionizing several sectors with its applications and support in tackling complicated challenges.

Now that we know,  AI and NLP offer a vast array of applications, spanning across various sectors and effectively reducing the need for manual labor, their integration has significantly enhanced our daily lives.

If you want to leverage these tools to your benefit, various NLP and AI consulting companies help you build perfect, customized AI-based NLP applications leveraging the best out of Natural language processing tools & technologies.

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Within the bustling realm of data science, our editorial team stands as a collective force of learning and exploration. Meet the dynamic minds behind the scenes—Sukesh, Abhishek, and other Authors. As passionate data science learners, they collectively weave a tapestry of insights, discoveries, and shared learning experiences.
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