Cognitive computing

Cognitive computing refers to the development of computer systems modelled after the human brain. Originally referred to as artificial intelligence, researchers began to use the term cognitive computing instead in the 1990s, to indicate that the science was designed to teach computers to think like a human mind, rather than developing an artificial system. Cognitive computing integrates technology and biology in an attempt to re-engineer the brain, one of the most efficient and effective computers on Earth.

Cognitive computing has its roots in the 1950s, when computer companies first began to develop intelligent computer systems. Most of these systems were limited, however, because they could not learn from their experiences. Early artificial intelligence could be taught a set of parameters, but was not capable of making decisions for itself or intelligently analyzing a situation and coming up with a solution. Enthusiasm for the technology began to wane, as scientists feared that an intelligent computer could never be developed.

However, with major advances in cognitive science, researchers interested in computer intelligence became enthused. Deeper biological understanding of how the brain worked allowed scientists to build computer systems modelled after the mind, and most importantly to build a computer that could integrate past experiences into its system. Cognitive computing was reborn, with researchers at the turn of the 21st century developing computers which operated at a higher rate of speed than the human brain did.

Cognitive computing integrates the idea of a neural network, a series of events and experiences which the computer organizes to make decisions. The neural network contributes to the computer’s body of knowledge about a situation and allows it to make an informed choice, and potentially to work around an obstacle or a problem. Cognitive computing researchers argue that the brain is a type of machine, and can therefore potentially be replicated. The development of neural networks was a large step in this direction.

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As the body of knowledge about the brain grows and scientists experiment more with cognitive computing, intelligent computers are the result. Smart computers which are capable of recognizing voice commands and acting upon them, for example, are used in many corporate phone systems. Cognitive computing is also used in many navigation systems on board aircraft and boats, and while these systems often cannot handle crises, they can operate the craft under normal conditions.

At the turn of the 21st century, many researchers believed that cognitive computing was the hope of a near future. By replicating the human brain in computer form, researchers hope to improve conditions for humans as well as gaining a deeper understanding of the biological reactions that power the brain. Computers capable of reason were beginning to emerge in the late 1990s, with hopes for consciousness following.

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.

Meeting of the minds


Researchers at IBM have been working on a cognitive computing project called Systems of Neuromorphic Adaptive Plastic Scalable Electronics (SyNAPSE). By reproducing the structure and architecture of the brain—the way its elements receive sensory input, connect to each other, adapt these connections, and transmit motor output—the SyNAPSE project models computing systems that emulate the brain’s computing efficiency, size and power usage without being programmed.

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IBM is combining principles from nanoscience, neuroscience and supercomputing as part of a multi-year cognitive computing initiative. .

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