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Our company is a science-oriented company, and the core belief is that behavior - human or otherwise - can be mathematically expressed. Yes, people make irrational value judgments, but they are driven by common motivation factors, and the math expresses that. I look at the so-called "big data phenomenon" as the instantiation of human experience. Previously, we could not quantitatively measure human experience, because the data wasn't being captured. But Twitter recently announced that they now serve 350 billion tweets a day. What we say and what we do has a physical manifestation now. Once there is a physical manifestation of a phenomenon, then it can be mathematically expressed. And if you can express it, then you can shape business ideas around it, whether that's in government or health care or business.

We are in the early stages of the Internet of Things, the much anticipated era when all manner of devices can talk to each other and to intermediary services. But for this era to achieve its full potential, operators must fundamentally change the way they build and run clouds. Why? Machine-to-machine (M2M) interactions are far less failure tolerant than machine-to-human interactions.

Ontologies are to the Open Semantic Framework what humans were to the Mechanical Turk. The hidden human in the Mechanical Turk was orchestrating all and every chess move. However, to the observers, the automated chess machine was looking just like it: a new kind of intelligent machine. We were in 1770.

AMHERST, Mass. - As computer scientists this year celebrate the 100th anniversary of the birth of the mathematical genius Alan Turing, who set out the basis for digital computing in the 1930s to anticipate the electronic age, they still quest after a machine as adaptable and intelligent as the human brain. Now, computer scientist Hava Siegelmann of the University of Massachusetts Amherst, an expert in neural networks, has taken Turing's work to its next logical step. She is translating her 1993 discovery of what she has dubbed "Super-Turing" computation into an adaptable computational system that learns and evolves, using input from the environment in a way much more like our brains do than classic Turing-type computers. She and her post-doctoral research colleague Jeremie Cabessa report on the advance in the current issue of Neural Computation. "This model is inspired by the brain," she says. "It is a mathematical formulation of the brain's neural networks with their adaptive abilities." The authors show that when the model is installed in an environment offering constant sensory stimuli like the real world, and when all stimulus-response pairs are considered over the machine's lifetime, the Super Turing model yields an exponentially greater repertoire of behaviors than the classical computer or Turing model. They demonstrate that the Super-Turing model is superior for human-like tasks and learning.

Cognitive computing, as the new field is called, takes computing concepts to a whole new level.  Earlier this week, Dharmendra Modha, who works at IBM's Almaden Research Center, regaled a roomful of analysts with what cognitive computing can do and how IBM is going about making a machine that thinks the way we do.  His own blog on the subject is here.

Artificial Intelligence is not yet HAL from the 2001: The Space Odyssey…but we are getting awfully close. Sure enough, one day it could be as similar to the sci-fi potboilers being churned out by Hollywood. If that's your idea of what artificial intelligence is all about, then you aren't far off the mark. In layman's terms, artificial intelligence is about creating intelligent machines through the use of intelligent computer programs. Most, if not all of artificial intelligence (AI) tries to mimic human behavior. The scale of ambition is different, but artificial intelligence programming is a full-fledged field in the cutting edge of science today. If you have some interest in the world of tomorrow, check out these websites to grasp what artificial intelligence is all about.

"Today, we are at the dawn of another epochal shift in the evolution of technology. At IBM Research, we call it the era of cognitive systems. This is a big deal. The changes that are coming over the next 10 to 20 years-building on IBM's Watson technology-will transform the way we live, work and learn, just as programmable computing has transformed the human landscape over the past 60+ years. You could even call this the post-computing era."

"For more than half a century, computers have been little better than calculators with storage structures and programmable memory, a model that scientists have continually aimed to improve. Comparatively, the human brain-the world's most sophisticated computer-can perform complex tasks rapidly and accurately using the same amount of energy as a 20 watt light bulb in a space equivalent to a 2 liter soda bottle. Cognitive computing: thought for the future Making sense of real-time input flowing in at a dizzying rate is a Herculean task for today's computers, but would be natural for a brain-inspired system. Using advanced algorithms and silicon circuitry, cognitive computers learn through experiences, find correlations, create hypotheses, and remember-and learn from-the outcomes. For example, a cognitive computing system monitoring the world's water supply could contain a network of sensors and actuators that constantly record and report metrics such as temperature, pressure, wave height, acoustics and ocean tide, and issue tsunami warnings based on its decision making."

Can computing and science fiction collide to create a true Artificial Intelligence? A.I has been part of our computing landscape for a long time, first as an idea, then taking baby steps, thing started to move in the early days of computers. After that, there was a period of disillusion and with the rise of cloud computing and massively parallel consumer-level chips A.I is more than ever on our lips and in our minds - but how far are we really from the awakening of a digital form of consciousness?