Showing posts with label decision sciences. Show all posts
Showing posts with label decision sciences. Show all posts

Tuesday, January 21, 2014

My article in IBM Mobile Insights: Three mathematical innovations for mobile data analytics

Mobile Signal Reflector by Wapster.
Shared in Creative Commons license
Mobile data analytics has become the business driven for various digital experience measurements and front office strategies. As mobile becomes the next enterprise ecosystem for global economy, minutest of the mobile data and its trends influence the executive decisions and customer satisfaction. Mobile device management is also overlapping with mobile data management in more number of ways. In this situation, a data science without business value discovery cannot enable the mobile enterprise. Mathematical sciences has the capability to bridge the vaguest of the problems with the most daunting challenges of the day.

Three mathematical innovations to transform mobile data and analytics:
In this article published in IBM Mobile Business Insights blog, I am exploring the role of cognitive, advanced learning and quantum physics in building big data analytics engines that can meet the contextual and the transient nature of data problems and algorithmic challenges. These are not technical revolutions alone, rather the realizations built on the strength of mathematical constructs and clarity.Read more and join me for an exciting discussion:

Thursday, September 26, 2013

How IBM Watson helped me select the right mobile apps: A science fiction


This is a fictional narrative on cognitive mobiles. With Supercomputers like +IBM Watson, cognitive computing has become an immediate reality. Can these cognitive computers solve our real life problems and confused mind? This article presents a dream where a man's misery with mobile app is resolved with the help of a cognitive computer! Please read more and share your thoughts at the IBM Mobile Business Insights blog! ...

Thursday, June 20, 2013

Some Early thoughts on the Boundaries of Circuit Computing

Computational machines, their digital senses are hovering are all around us. We make decisions, we experience and negotiate, we travel and triangulate through their prowess. In other words, we as a collective of social knowledge embed intelligence and knowledge into their circuitry and digital logic. Their arises my question; how is this digital logic grounded in the larger set of mathematical logic. Is this digital logic a linear crystallization of natural computing algorithms? 

As we reach the boundaries of traditional algorithms of natural data set, the emerging frontiers of decision sciences are appearing as the phantom ghosts from nowhere. And at times we think they are coming from nowhere in the past and we call them data explosion and sensor revolution. Where has internet hidden all these Phantoms from the past.

Recently I read that mathematical logic has a lot of formalism derived from the brilliant approaches of the 20th century mathematician Hilbert, who tried to consolidate many of the mathematical problems under the ambit of a unified theory of mathematical theory. Thus we need to understand the formalism and whether their were some limitations on the approaches in the problem solving approaches of Hilbert methodology. 

Why all this question now? It is because of the very reason that the theoretical computational models need to take a new turn as we are seeing cognitive computing as the future approach to the decision making algorithms of future needs. When we shift the gears from circuit computing to cognitive computing, there must be a realization of the underlying mathematical logic and its complexity inherent. Our investigations must begin at the very root of the mathematical logic which derived its powers from the formalist approach.