Machines Like Us

A Multi-disciplinary Synthesis of Neuroscience, Computer Science, Mathematics, Cognitive Neuroscience, and Information Theory, Cognitive Computing is when computer science meets neuroscience to explain and implement psychology.

We have, in the brain and nervous system, an information processing system unrivalled by artificial means. While it trails machines in accuracy and mathematical computation, it wins on adaptability, flexibility, functionality, and parallelism. The ultimate goal is to reverse engineer enough of this system so that the design principles can be applied to building robust and adaptable computer systems.

Cognitive Computing is different from Artificial Intelligence (AI) and Neural Networks (NN). From the outset, AI ignored neurobiology. While neural networks started from biological motivation, they too quickly discarded biological plausibility. In both cases, the approach has been to focus on a suitable problem, and to offer a "symbolic" or "neural network" solution to it. The brain, however, works in exactly the opposite fashion, it has evolved a solution that allows it to deal with problems as they arise.

AI and NN technologies take one or more cognitive phenomena exhibited by the brain as a starting point and then try to replicate that capability by inventing algorithms/learning rules. In contrast, CC is about learning how the brain operates, about algorithms, about diligent reverse engineering and testing plausible models.

Cognitive Computing is about engineering the mind by reverse engineering the brain.

For more information about the Cognitive Computing Conference (May 2-3, 2007) click here .