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May 23, 2012

Why you need to befriend the Laplace Demon?

Posted by Manish Srivastava (View Profile | View All Posts) at 9:26 AM


Computers are everywhere. We are entering an age where computing will be embedded everywhere - in products, in places, in things and in people. Pharma companies are testing programmable biodegradable sensors that will be embedded in medicines and will alert you on your iPhone, as per doctor's prescription. Connectivity is getting everywhere. Internet has crossed 25% adoption worldwide and mobile will soon connect every individual with each other. We are moving to an age where everything everywhere will be connected digitally.

Adoption of computers for automating business processes has led to an explosion of information. While we are still learning to manage and leverage that information, a second information big bang is already on its way - powered by sensor networks and social networks. This "new information" is opening up "new possibilities" - ability to understand customer's better, ability to better monitor supply chains and assets. Businesses who can exploit these new possibilities will dramatically alter productivity and the value chain in their favor. The availability of computing, connectivity and information is also opening up possibilities of new business models that were earlier not possible - pay per drive rental insurance, e-books, renting of digital content etc.

However, the nature of this "new information" is quite different than what we are used to - it is more real time and unstructured. In order to extract value from this, we need to learn "new techniques" to derive "new insights" from this "new information". The relational databases may not always scale to manage the volumes and speeds required. We are seeing the evolution and adoption of non-relational or non-SQL databases for managing this "new information". We need "new algorithms" to make sense of this large scale unstructured information that is now available to us. We need better algorithms to understand pictures, not just text but voice, and video as well.

Many of these "new algorithms" will require parallel processing. There have been rapid advances in multi-core, high performance and distributed computing architectures in recent years. However, in order for us to exploit these new capabilities, we will need more programmers who can design for parallel processing.

Not many will be able to scale traditional enterprise datacenters to churn such large scale of information at the required speed. Cloud can provide a much economical model to access such large scale infrastructure using on demand usage and pricing models.

Computational approaches may still prove to be insufficient to analyze this information and we may need to learn "new ways" to engage the very same social networks to sort and make sense of the volumes of information that they are churning. There are several examples of crowd intelligence like Wikipedia which demonstrate the power of such engagement platforms. This new reality is forcing many organizations to rethink how they manage information in the new world - even conservative institutions like World Bank have decided to make its information available through APIs for others to analyze and make sense of. The rise of the app store is further fueling crowd sourcing and one developer is building on top of what the other is providing. It is redefining how applications will be built and delivered in the future.

With information and computing power available, a new breed of information artist like Hans Rosling are making information dance on their fingertips. This coupled with multi-modal interactions are redefining digital experiences. I see the magic of natural interactivity playing out at my home when my kids compete on "Angry Birds". Natural interfaces and augmented reality is helping create engaging digital experiences that will accelerate learning and simulated environments for collaborative decision making. We need to learn to design these interactive experiences.

In 1814, Pierre-Simon Laplace formulated a hypothetical "Laplace's Demon" with infinite computing power that knows exact location and velocity of every particle in the universe. It was speculated that such a demon could predict the past, present and the future - all there is to know, "The Theory of Everything". Today we know that there are physical limits to computation and such a demon is only but a dream. However, with computing getting embedded everywhere, improvement in algorithms and availability of cheap scalable computing power, it may still be possible to build a substantially weaker cousin of the "Laplace's Demon". A friendly demon that can provide us an virtual mockup of the real world where in we can simulate our decisions options collaboratively before letting it play out in this increasingly complex and connected world. 

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