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Natural Language Processing and Artificial Intelligence

26/07/2022

Natural Language Processing and Artificial Intelligence

 

Businesses in the modern digital age are buried under an ocean of unstructured data. Businesses would find it nearly hard to assess and process an enormous amount of data without the right technologies. Artificial Intelligence (AI) and Natural Language Processing (NLP) can help in this situation.

 

The broad field of study known as Artificial Intelligence encompasses all aspects of making machines intelligent. If you are constructing something intelligent, whether it be a robot, a refrigerator, a car, or a software program, then it is AI. Natural language processing is the method of analyzing text to discern meaning. Since people utilize slang and acronyms when speaking, accurate results require a thorough computer analysis of spoken language.

 

What is Natural Language Processing?

Machines can now comprehend human language thanks to a field of Artificial Intelligence called natural language processing. Its objective is to create computer programs that can comprehend language and carry out automatic activities, including topic classification, translation, and spell checking.

 

NLP, or natural language processing, enables computers to comprehend human language. 

 

Behind the scenes, NLP examines sentence structure and word meaning individually, then employs algorithms to extract meaning and provide results. In other words, it interprets human language so that it may carry out various activities automatically.

 

The most well-known applications of NLP, a form of Artificial Intelligence, are likely virtual assistants like Google Assist, Siri, and Alexa. In order to make it simple for robots to grasp, NLP converts spoken and written text into numbers, such as, “Hey Siri, where is the closest gas station?”

 

Chatbots are a well-known example of an NLP application. By automatically interpreting queries in everyday language and reacting, they assist support personnel in resolving problems.

You would have used NLP in many more commonplace programs without even realizing it. To filter unwanted promotional emails into your spam folder, offer to translate a Facebook post that is written in a different language, or text recommendations while drafting an email.

 

The purpose of natural language processing is to make it simple for robots to comprehend human language, which is complicated, ambiguous, and immensely diverse.

 

What is Artificial Intelligence?

 

Artificial Intelligence is the application of complex logic or sophisticated analytical techniques to simple jobs at a larger scale, allowing us to do more with the people we already have while they concentrate on their areas of expertise, such as addressing difficult exceptions or evoking empathy. In essence, Artificial Intelligence is a digital replica of human intelligence. With AI, a task can be completed by a computer without ever having been expressly programmed to do so.

 

Building intelligent computers that can carry out tasks that traditionally require human intelligence is the goal of Artificial Intelligence, a broad field of computer science.

 

Importance of NLP and AI

 

The ability of technology to recognize and handle enormous volumes of text data from the digital world, such as social media platforms, online reviews, news reports, and others, is the major advantage of NLP and AI for organizations.

 

Additionally, NLP and AI are able to give organizations useful insights into the performance of their brands by gathering and analyzing business data. Additionally, NLP and AI models are able to identify any faults that continue to exist and implement the appropriate corrective actions to enhance performance.

 

All of this is made possible by training computers to comprehend human language more quickly, precisely, and consistently than human agents. Data can be continuously monitored and processed thanks to technology. Inconsistencies are avoided, and brands are able to maintain an updated internet presence.

Natural Language Processing and Artificial Intelligence- The difference

 

 

Sometimes the terms Natural Language Processing and Artificial Intelligence are used synonymously, making it difficult to distinguish between the two. The first thing to understand is that Natural Language Processing is a division of AI.

 

Artificial intelligence is an umbrella term for devices that can mimic human intelligence. Artificial Intelligence includes programs that imitate cognitive processes like problem-solving and learning from examples. This includes a wide range of applications, including predictive systems and self-driving cars.

 

NLP is the study of how computers interpret and comprehend human language. With NLP, computers can understand spoken or written language and carry out tasks like subject classification, keyword extraction, and translation. For example, NLP is used by AI-enabled chatbots, for instance, to decipher what users say and what they plan to accomplish.

 

Cases of Natural Language Processing and Artificial Intelligence in Businesses

 

Through emails, product reviews, social media posts, surveys, and other forms of communication, NLP and Artificial Intelligence tools assist businesses in understanding how their clients regard them.

 

Artificial intelligence solutions may be used to automate monotonous and time-consuming processes, boost productivity and free up employees to focus on more rewarding work, in addition to helping businesses comprehend online interactions and how customers talk about them.

 

The following are some of the most common NLP and AI business applications:

 

  1. Sentiment analysis through the identification of emotions in texts, opinions are categorized as either positive, negative, or neutral. By pasting words into this free sentiment analysis tool, you can observe how it functions.
    Businesses can learn more about how consumers feel about brands or products by examining social media posts, product reviews, or online polls. For instance, you could instantly identify irate consumer remarks by analyzing tweets mentioning your company.
    To find out how customers feel about your level of customer service, you might wish to send out a survey. You may learn which facets of your customer service elicit favorable or negative feedback by examining open-ended NPS and Artificial Intelligence survey replies.
  2. Language TranslationsOver the past few years, machine translation technology has made significant advancements. Businesses can interact in a variety of languages thanks to translation software, which can help them expand into new markets or strengthen their worldwide communication.
    Additionally, you may teach translation software to comprehend certain jargon used in any industry, such as banking or medicine. Inaccurate translations, which are frequent with generic translation tools, are thus not a concern.
  3. Text ExtractionYou can extract pre-defined information from text using text extraction. This program assists you in identifying and extracting pertinent keywords, features (such as product codes, colors, and specs), and named entities if you work with vast amounts of data (like names of people, locations, company names, emails, etc.).
    Among many other uses, businesses can use text extraction to automatically detect important terms in legal documents, determine the significant terms cited in customer service tickets, or extract product specs from a paragraph of text. That sounds intriguing. You can try the keyword extraction tool provided here.
  4. ChatbotsAI systems known as chatbots are created to communicate verbally or textually with humans. Due to their capacity to provide 24/7 support (speeding up response times), manage several inquiries at once, and free up human agents from answering repetitive questions, chatbots are increasingly being used for customer service.
    You can trust chatbots to complete routine and easy tasks because they actively learn from every contact and get better at interpreting user intent. They will forward a client inquiry to a human representative if they encounter one they are unable to address.
  5. Topic ClassificationYou may classify unstructured text into categories by using topic classification. It’s a terrific approach for businesses to learn from customer feedback.
    Consider that you want to examine hundreds of open-ended NPS and Artificial intelligence survey responses. How many comments refer to your customer service? How many consumers bring up “Pricing” in conversation? Using this topic classifier for NPS feedback, you can quickly tag all of your data. Topic classification can also be used to automatically tag incoming support tickets and forward them to the appropriate individual.
  6.  Email FiltersNLP technology has undoubtedly benefited you if you’ve used an email account in the past ten years. An algorithm may correctly recognize, classify, and label emails as regular emails, spam emails, or malicious emails if it has been adequately trained on textual email data, the latter of which is typically removed from your account before you even see it. According to the email provider, other email filter kinds like social or promotional may be employed.
    Even the business world is beginning to see the advantages of this technology, as evidenced by the fact that 35% of the organizations surveyed use NLP for email or text classification. Strong email filtering can also dramatically lower the chance that someone will click on and open a malicious email at work, minimizing the exposure of critical data.

 

 

Focaloid for NLP and AI

 

With the aid of pre-trained models or the creation of specially designed solutions to meet your needs, Focaloid Technologies is the ideal Artificial Intelligence platform that makes it very easy for you to get started with NLP. Our expertise in building products or applications with text and voice processing capabilities will increase your customer engagement and enhance your customer’s user experience.

 

Conclusion

 

The subset of Artificial Intelligence known as natural language processing investigates how machines interact with human language. NLP improves products we use every day, such as chatbots, spell checkers, and language translators, in the background. NLP and AI work together to produce systems that learn to do tasks on their own and get better with practice using machine learning techniques. Among many other things, NLP and AI-powered solutions can help you categorize social media posts based on their emotion or extract named entities from business correspondence.

 

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