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The human brain integrates memory and processing together, weighs less than 3 lbs, occupies about a two-liter volume, and uses less power than a light bulb.  It operates as a massively parallel distributed processor.  It is event driven, that is, it reacts to things in its environment, uses little power when active and even less while resting.  It is a reconfigurable, fault-tolerant learning system.  It is excellent at pattern recognition and teasing out relationships.

A computer, on the other hand, has separate memory and processing.  It does its work sequentially for the most part and is run by a clock.  The clock, like a drum majorette in a military band, drives every instruction and piece of data to its next location — musical chairs with enough chairs.  As clock rates increase to drive data faster, power consumption goes up dramatically, and even at rest these machines need a lot of electricity.  More importantly, computers have to be programmed.  They are hard wired and fault prone.  They are good at executing defined algorithms and performing analytics.

Systems of Neuromorphic Adaptive Plastic Scalable Electronics (SyNAPSE)

Notice, I don’t use the term “thinking machines.” That’s because I don’t want to suggest that cognitive systems will think like humans do. Rather, they will help us think and make better decisions.

In cognitive systems, performance improvements will derive from scaling in: moving key components, such as storage, memory, networking and processing onto a single chassis, closer to the data.

The volume of data produced today isn't just increasing—it's getting faster, taking more forms and is increasingly uncertain in nature.

Uncertainty arises from such sources as social media, imprecise data from sensors and imperfect object recognition in video streams. IBM experts believe that by 2015, 80 percent of the world's data will be uncertain.

The real issue is that we don’t understand how human intelligence and “consciousness” work.

We don’t know the principles behind it; we can superficially imitate it but we cannot build something like it, or better – for now.What we need is a “cognitive computing” model (a theory) before we can build machines around it.

The fading ranks of middle management have lost their edge, thanks to revolutions in both technology and globalization. Indeed, the latest wave of technology advances—cloud computing, advanced mobile applications and devices, and rapidly expanding social networks to name a few—have greatly eased access to knowledge work. Nowhere is this change seen more dramatically than with the rapidly ascending workforce in high-growth markets outside the United States. Business writer Seth Godin remarks ominously, “If you're the average person out there doing average work, there's going to be someone else out there doing the exact same thing as you, but cheaper.” The game has shifted to a far more competitive, globally-connected field of play, requiring individuals to differentiate themselves in authentic, compelling ways like never before. Godin concludes, “If you're different somehow and have made yourself unique, people will find you and pay you more.”

How We Will Learn: Technology-Enabled Informal LearningWhen we talk about fostering agility, curiosity and continuous learning, we’re fortunate because today we have a host of Web-based technologies (including social, mobile, video, games, and personalized portals) that can serve as perfect tools to support the self-directed learner.By utilizing technology-enabled informal learning resources, collaborative learners can easily share and exchange knowledge, and self-directed learners can continuously teach themselves. These tools allow us to gain and share knowledge when, where and how we want it.Technology-enabled informal learning (that is, technology-based learning that takes place outside a formal classroom environment) also makes sense for organizations because we know that people learn in a variety of ways, and they usually like to learn on their own terms. This insight is derived from Howard Gardner, the influential educational thinker, who has argued that all of us have multiple intelligences. Adjusting and adapting to this cognitive norm, Gardner explains, will generally result in greater skill development and sharper problem solving.

According to ASTD’s Learning Executive’s Confidence Index for the fourth quarter of 2011, almost 55% of learning executives expect an increase in the use of informal learning and Web 2.0 tools in their organizations over the next 6 months.