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Examining NLP In 2020

CIOInsider Team

While moving forward the carpet of innovation, Artificial Intelligence is leaving no stone unturned affecting the way we work and live. One of the most promising areas that will continue to explore heights of transformation will be Natural Language Processing, NLP in short. The study around NLP has been going on for the last 50 years and now with the developments in the IoT sector it has managed to grow out of the Linguistic field. NLP, as defined by technocrats around the world, is a field that studies interaction between machines and natural languages using the capabilities of AI.

Ever since companies have started realizing the humongous opportunities and lucrative benefits associated with human speech recognition systems, NLP has been in the forefront of operations for machine-aided translations, data

extraction as well as analysis. In the contemporary era where bots are gaining traction for its applicability in business related operations, NLP could ease their functions in an effective way. The enormous opportunities open up to spam filtering functions, auto-completion of text inputs, and many other functions that could be integrated with the customer end platforms.

Given that the number of use cases is large, NLP is expected to reap further heights in the present decade. The rise of Natural Language Understanding, NLU, is one such category that makes use of machine reading comprehension. NLU will power systems that can comprehend the meaning of a speech, reply instant answers, and direct a conversation. This process could take the domain of language interpretation and machine-to-human communication to newer heights.

By coupling unsupervised and supervised learning capabilities together, NLP will be capable in using the AI to enable data scientists in efficiently discovering the patterns in big data and make predictions. This could further extend the possibilities in enveloping the improvement in the decision making capabilities. Having said, one of the major developments with respect to NLP will be its ability to effectively and precisely translate the texts without any human interference. NLP content generation will see heights as it will be able to generate texts after structuring and summarizing through the data fed.

Semantic search being the popular and highly anticipated innovation from NLP is expected to get form and shape in 2020. Utilizing the aforementioned technology of NLU and giving attention to the process of defining a certain text, NLP will be quickly processing through texts in order to gather insights into specific key terms. NLP has started becoming highly recommended and introduced across businesses involved in different verticals. In the years ahead, the technology that powers NLP to its fullest will furnish human-to-machine interactions in an advanced way.

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