Cognitive computer

From Wikipedia, the free encyclopedia
Jump to: navigation, search

A cognitive computer combines artificial intelligence and machine-learning algorithms, in an approach which attempts to reproduce the behaviour of the human brain.[1]

An example is provided by the IBM company's Watson machine. A subsequent development by IBM is the TrueNorth microchip architecture, which is designed to be closer in structure to the human brain that the von Neumann architecture used in conventional computers.[1]

The IBM cognitive computers implement learning using Hebbian theory. Instead of being programmable in a traditional sense within machine language or a higher level programming language such a device learns by inputting instances through an input device that are aggregated within a computational convolution or neural network architecture consisting of weights within a parallel memory system. An early instantiation of such a device has been developed in 2012 under the Darpa SyNAPSE program at IBM directed by Dharmendra Modha.[citation needed]


There are many approaches and definitions for a cognitive computer,[2] and other approaches may be more fruitful.[3]

See also[edit]


  1. ^ a b Dharmendra Modha (interview), "A computer that thinks", New Scientist 8 November 2014, Pages 28-29
  2. ^ Schank, Roger C.; Childers, Peter G. (1984). The cognitive computer: on language, learning, and artificial intelligence. Addison-Wesley Pub. Co. ISBN 9780201064438. 
  3. ^ Wilson, Stephen (1988). "The Cognitive Computer: On Language, Learning, and Artificial Intelligence by Roger C. Schank, Peter Childers (review)". Leonardo. 21 (2): 210. ISSN 1530-9282. Retrieved 13 January 2017.