PLANNING AND LEADERSHIP FOR A BETTER WORLD
PLANNING AND LEADERSHIP FOR A BETTER WORLD | Table of Contents: |
Today IBM debuts the world's first cognitive computer chips, which I called cognizers in my book "Cognizers--Neural Networks and Machines that Think" (John Wiley & Sons, October 1988). By replicating the functions of neurons and synapses in the human brain, IBM has crafted the world's first chips aimed at taming the overwhelming wealth of information in multiple sensor data-streams by learning to adapt like human brains. The chips have already beat humans at the game "Pong" and promise to impart humanlike abilities of all sorts of future cognitive computers.
The traditional computers that we all use today are actually based on an antiquated design first proposed by John von Neumann in 1945. The so-called von Neumann architecture artificially separates programming from memory--putting the processor on one core and its memory on others. Unfortunately, this division of labor makes it incredibly difficult to combine the knowledge gleaned from multiple data streams--the No. 1 unsolved problem facing computer systems today. Cognitive computers, on the other hand, replicate the way the human brain distributes processing and memory among the same circuitry, which in the brain is composed of neurons and synapses.
Principal investigator Dharmendra Modha in front of the brain-wall at IBM Research, where the operation of the neurons and synapses in IBM's cognitive computers are visualized.
"Our chip represents a sharp departure in architecture from the tradition von Neumann computers," said Dharmendra Modha, project leader for IBM Research. "All memory functions are integrated with program functions, creating a kind of social network of neurons with all their software stored in synapses."
Neurons are tiny cells that by their very nature integrate inputs from multiple sources, which in the brain are the other neurons, of which there are billions. The brain uses its neurons together to solve problems by integrating the pulses received over dendrites from other neurons until a threshold is exceeded, at which point it fires a pulse down its output axon, then resets and starts integrating anew. Firing rates are typically 10 Hz, with power only being consumed when a pulse is actually produced, thus enabling ultra-low-power operation for brainlike computers even though they using billions of neurons.
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