IBM research still heavily invests on new programs that drives innovation in the Industry. In the recent research to mimic the best parts of human brain function on a highly intelligent computer to decypher tons of data quickly, it got investors.

IBM received $16.1 million to kick start its’ part of a DARPA – Defense Advanced Research Projects Agency research program aimed at “Rapidly and efficiently put brain-like senses into actual hardware and software so that computers can process and understand data more rapidly”.

IBM has now got $21 million to work on the program known as Systems of neuromorphic adaptive plastic scalable electronics (SyNAPSE) which includes researchers from HRL Laboratories, which got $16.2 million in Oct. 2008, and others such as HP.

According to DARPA,

“The SyNAPSE program will create useful, intelligent machines. In DARPA language: the agency is looking to develop electronic neuromorphic machine technology that is scalable to biological levels. The goal is to develop systems capable of analyzing vast amounts of data from many sources in the blink of an eye, letting the military or civilian businesses make rapid decisions in time to have a significant impact on a given problem or situation. Currently, Programmable machines are limited not only by their computational capacity, but also by an architecture requiring (human-derived) algorithms to both describe and process information from their environment. In contrast, biological neural systems such as human brains, autonomously process information in complex environments by automatically learning relevant and probabilistically stable features and associations.”

As compared to biological systems for example, today’s programmable machines are less efficient by a factor of one million to one billion in complex, real-world environments. The SyNAPSE program seeks to break the programmable machine archetype and define a new path forward, DARPA stated.

DARPA goes on to state that realizing this ambitious goal will require the collaboration of numerous technical disciplines such as computational neuroscience, artificial neural networks, large-scale computation, neuromorphic VLSI, information science, cognitive science, materials science, unconventional nanometer-scale electronics, and CMOS design and fabrication.

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