siliconindia | | January 20179teractions are driven by language and communications.3. Business Decision Making: NLP and NLG together can actually ana-lyze and present high volumes of data enabling simpler and more efficient decision making.The Macro PerspectiveLet's take a step back and look at things from a different perspective. Let's explore the example of the now popular Terminator Age. Prima Facie, the conversation revolves around the potential impact of a machine learning process driven by software and neural modeling handling gazillion data packets. Now what use are data packets? Where do they take us? Why do this entire thing at all?A simple use case demonstrates the potential ­ over 800 million Indians do not even have access to hospitals and clinics with sufficient hardware. The impact is not just in their health-care opportunities but also the loss of extraordinary amounts of data & knowledge that in times of epidemics could prove to be game changers for the country. Upon applying NLG and NLP, the use case becomes even more robust. In a Punjabi village, a Punja-bi speaking doctor can now converse with a Hebrew speaking specialist residing in Israel to resolve a serious medical issue in the back and the be-yond. None of this would even be pos-sible without machine learning and application of NLP. Critical data on symptoms, diseas-es and chronic conditions accumulate continuously and are neither being collected nor used constructively to lead to any potential short term bene-fit ­ leave alone the long term benefits. Consider this use case ­ A simple ma-chine learning algorithm can analyze, predict and recommend the MRI scan-ners while the scan of a patient is go-ing on! This will land up fast tracking the process of remedies the doctors or the clinics can recommend. In times of crisis, this simple measure can be the difference between life and death of a patient!India & NLPI am often asked this question when talking about NLP ­ Why do I feel India can actually crack the NLP mod-el? Of all the divisions of artificial in-telligence, I personally believe that the next generation evolution in NLP will come from India. It brings me to what I fundamentally believe; if a country with 1652 mother tongues and mul-tiple other dialects cannot crack the NLP model, then perhaps few others can. And work is already underway with more and more talented Indians setting their eyes on it ­ like MIH-UP. India has always been a research hub of NLP, and organizations such as Owler are great, but the mantle to crack NLP for 22 languages by voice to text, and augment voice commands to machines via key lexicon datasets on universal remotes and many more use cases is taken by an organization called MIHUP. Funded by Accel and backed by a diverse team with a deep understanding of language and lin-guistics, MIHUP is able to crack 22 languages and ensures that machines and device commands are getting aug-mented through their algorithms. What Can We Expect This To Do For Society?For instance, uneducated farmers talking on platforms on crop remedy, tackling farmer suicides, medical aid or support, and many more never ending opportunities exist. The idea is to identify them, identify barriers, and then work on creating a robust model; one that bridges back to society and social benefit ­ an objective that all players in the NLP field should aim for with good reason. After all, a technology that focuses on a 90 percent consumption pattern should be the first one to actually carve that path and ensure that humankind keeps talking to each other! Sauvik Banerjjee
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