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In the last 20 years, since Google was established, the world has become increasingly digitized and driven by automation. Thus, we've become acclimated to voice assistants, predictive texts, and data analysis, which have infiltrated our lives unnoticed. None of this would be possible if it weren't for Artificial Intelligence and Natural Language Processing (NLP), one of its main branches.
Nowadays, NLP has a vital role within technology and the way people interact with it. Such an approach involves a combination of classical linguistics and statistical methods, resulting in information filtering and how we are changing the fundamentals of digital communication.
Artificial intelligence (AI) is the proven machine-made intellect, in contrast to the natural sense of humans and other animals. Its research refers to all systems that perceive their environment and perform actions to maximize the chances of accomplishing their goals. Accordingly, OpenText's head of technology strategy, AI, and analytics, Zachary Jarvinen, defines it as "a computer simulation of human intelligence that can be programmed to make decisions, perform specific tasks, and learn from the results."
Now that we have the AI definition, we can discuss its focus on human linguistics, NLP. This is the branch of AI that allows computers to understand, interpret and manipulate human language. Thus, a series of sub-branches are embedded in it, including natural language understanding (NLU), i.e. the transformation of data into human words through automatic reading comprehension and natural language generation (NLG).
Although the name "NLP" may sound distant to us, it is present in our daily lives, as it is implemented, for instance, to translate languages, categorize content, extract it, or implement voice or chat-based user interactions. The reason for this is that machines can understand the language intent, extract keywords and even generate a response. This is the branch that interests us the most and that we are about to discuss in this article.
Specifically, Natural Language Processing (NLP) is a field of computational linguistics and the area of study focused on how computers understand, interpret and process human language. As an example of this process, we humans learn to speak in a very basic way from birth, and later on, when we learn to interpret the language, we develop elaborate complex expressions, double meanings...
The goal of this area of study is for machines to be able to understand not only literal texts but also their ironies, idioms, and even jokes. Hence, thanks to NLP we find machines that, on top of understanding the content of our messages, including their contextual nuances, are capable of extracting information and content accurately, as well as categorizing and organizing such information.
An extremely clear illustration of NLP would be the virtual assistant Alexa, who interprets our data both verbally and written. It is also capable of interacting with humans by translating and interpreting our voices and providing spoken output in response. In simple terms, what it does is organize the language into smaller elements to analyze them and understand the relationship between them.
Companies work with massive amounts of unstructured, text-heavy data and are in need of a way to process it accurately and efficiently. Most information created online and stored in databases is natural human language and the companies have not been able to analyze this data effectively until recently. It also happens with individual users, entrepreneurs, and workers with a tied schedule who are used to being bombarded by lots of information and unprocessed text. This is where natural language processing comes in handy.
If a user relies on NLP for searching and receiving notifications or messages, the program will then ensure that this user receives the information in an abbreviated form and according to his/her/they interests and/or priorities. Furthermore, one of NLP and information filtering's greatest advantages is the user's choice of service level, as well as on-demand personalization.
To highlight NPL's importance, it's important to point out its benefits. The main one is the computer's language, which allows the improvement in the way humans and computers communicate with each other. By allowing computers to understand human language, computers become more intuitive for humans and their interaction with them.
Secondary benefits include the ability to understand the spoken and written word of human language, which allows personalized attention to the user; the analysis of filtered information, since this is not so feasible with a large volume of data; and greater accuracy and efficiency of documentation, among many other benefits.
This results both in an improvement in the breadth and depth of the data that is analyzed, as well as in an improvement in attention span, and a better physical and mental health of users, as they are less stressed by information overload. It also reduces screen use and addiction to it, resulting in greater user stability.
Thanks to NLP we can filter information, which occurs due to stop words. These refer to common words that do not contain important information but are necessary to complete a sentence according to each language's grammar. Words such as connectors or prepositions are the ones that we can ignore without losing the full meaning contained in a text.
These stop words make possible the information filtering system, which removes any unnecessary words from the sentence. A system that eliminates redundant or unwanted information from an information flow. The machine performs this filtering before it is communicated to the human being through automated or computerized methods.
Its main objective is information overload management. Thus, stop words and filtering allow preprocessing our text to keep only the essential tokens, ignore irrelevant information and avoid push-notifications.
The benefits of NLP mentioned above are proof that it’s a technology that improves our quality of life by a significant margin, and that it is altering the way humans and machines interact. For this reason, NLP is one of the largest data science areas, in which numerous advances are being made that will increasingly affect our lives in a positive way. One of the innovative changes to 2022 is the following:
By incorporating an information filter in an intelligent device, the user will decide the information that he/she/they want to be notified of. Thus, a smartwatch like Chroneering® will allow the user to continue to receive all notifications on their smartphone, allowing the smartwatch to determine whether the notification deserves to steal the user's attention or not. In other words, if the phone vibrates but the watch doesn’t, it’s conclusive that the user can ignore it.
Through NLP for prioritized notifications based on content, different types of emergencies, hazards, urgent matters, or special requests get highlighted to the user through an analog watch face. This enables the user to take part in revolutionary artificial intelligence to optimize their day-to-day, without compromising on style and self-expression.
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