NLP or Natural Language Processing is one of the most interesting and exciting features of data science that aims to analyse the human language and facilitate human – machine interaction. It can be safely said the future of NLP is bright and promising and it is going to rule AI and machine learning in the coming days.
What is NLP?
In simple words, NLP uses computational and mathematical approaches to analyse the human language and helps machines to engage in human interaction through conversational language. This is achieved by machine learning. It focuses on natural language narratives. For example, imagine an intelligent application that can call and reserve a table for you and your family conversing with a human being on the other side. IBM’s Debater Project Debater is another path breaking innovation in the field of AI that has the capability of arguing with human beings on complex subjects. It has been only possible through leveraging NLP.
The foundation of NLP was laid back many decades ago when human being first started exploring with it. Over the years it has been researched upon to a great extent. Today, NLP is creating ripple in the AI industry and we can say that NLP has a promising future in the coming days.
Roadmap of NLP – The future is promising
Every industry is now leveraging the power of NLP to delight their customers. Whether you’re on an ecommerce portal or business utilities, NLP is getting used extensively. Alexa and Siri are some of the best examples where NLP is used. NLP is not just restricted to that, but we see it in every day chatbot interaction at ecommerce platforms, virtual assistants answering complicated human questions, emotional analysis and lot more. With so much progress already made in NLP, all we can say is the future of NLP is really promising.
At present NLP can be trained to answer a series of questions, a bit complicated question. But soon there will be time when NLP can be trained not only to answer a question but to provide more complex solution to the intent of the question. For example, right now NLP can be trained to answer a question like “Is my network connection working?” But in future, NLP can understand the intent behind the question, like do you want it to be fixed?
The future of NLP and chatbots
Chatbots are used extensively in customer service where customers chat with the bot as they would do with human agents. In the coming days, NLP can be further trained and integrated with semantic and other cognitive technologies to enable the bot to respond to more complex human queries.
NLP for better search
Just like chatbots, NLP can be used to give a user better search results with “search like you talk” feature instead of giving a search result based on keywords.
NLP in extracting information from unstructured information
No matter where NLP is used, it will form a critical bridge to extract the useful information from unstructured and complicated information.
NLP and enterprise AI
Leveraging NLP, businesses are now focusing more on how it can be used in future to read, analyse and extract useful information from the vast pool text and data available.
The opportunities with NLP are limitless. Soon, NLP could be trained to understand more complex human emotions. Further, it could be linked with other technologies like facial recognition and gesture recognition to perform more complicated tasks making businesses more customer centric. The possibilities are immense. Only time will tell what the future has in store for us. Till then let’s wait and watch!
