As a business leader, you want to learn about new technologies from experienced technical experts (not just talking heads) but also pick up practical Artificial Intelligence and Cyber Security strategies for applying them to your enterprise. With the support of Organizing Committee Mindfire Solutions, TechBhubaneswar (2018) is scheduled to be held in the Hotel Mayfair Convention, Bhubaneswar during December 09, 2018 with the theme “ Artificial Intelligence and Cyber Security “. This TechBhubaneswar Conference will set a platform for most innovative minds, practitioners, experts, thinkers, eminent Researchers, Scientists, Professors, Developers, Analysts, and Newbies globally to discuss an approach to Artificial Intelligence and Cyber Security researchers. It welcomes everyone who is eager to gain more about the intelligent future of Artificial Intelligence and Cyber Security.
Hi, I am Karan Shaw, Cognitive Engineer @ Nexright Software Solutions Pvt Ltd & Founder of Trybotics.com, going to be a speaker of one of the lighting tech session at TechBhubaneswar (2018) on a topic of “Scale Your Business Using Artificial Intelligence And Cognitive Science”. In this session, I am going to convey the interesting facts & challenges of Artificial Intelligence, and how to overcome it. Explore natural language processing for creating a seamless and interactive interface between humans with machines, which will continue to be a top priority for today’s and tomorrow’s increasingly cognitive applications.
As the amount of information available online is growing, the need to access it becomes increasingly important and the value of natural language processing applications becomes clear. Machine translation helps us conquer language barriers that we often encounter by translating technical manuals, support content or catalogs at a significantly reduced cost. The challenge with machine translation technologies is not in translating words, but in understanding the meaning of sentences to provide a true translation.
Manually reviewing documents is time-consuming and prone to errors. Natural language processing (NLP) reduces the need for tedious manual analysis and allows you to more easily identify and extract important patterns in the text. NLP is often the first step in the text analytics process. It performs linguistic analysis to help a machine “read” text. Visual Text Analytics uses NLP to analyze and transform text into formal representations for text processing and understanding. There’s no need to cobble together disparate NLP libraries or custom code to perform word and sentence tokenization, segmentation, stemming, compound decomposition, part-of-speech tagging, named entity recognition and semantic parsing. You spend less time programming the computer how to interpret text and more time to derive business value from textual data.