HOW A BRAIN-INSPIRED THEORY MAY
SOLVE PROBLEMS OF BIG DATA
Vast quantities of "big data" are posing major challenges for today's computers. But there are some potential answers, inspired by the human brain. They are described in a new article published in the journal "IEEE Access".
Anglesey, UK, June 20, 2014 /PressReleasePing/ - We think of supercomputers as
being super-powerful. But they can be overwhelmed by the floods of information now produced in science, commerce, government, meteorology, social media, and other areas. And compared with the human brain, they gobble up lots of energy and take up lots of space.
But the human brain may provide some answers in the shape of anSP machine , based on theSP theory of intelligence, which is itself based on research into the workings of brains and nervous systems. This new thinking about “Big data and the SP theory of intelligence”—developed by Dr Gerry Wolff of CognitionResearch.org—has now been published in the journalIEEE Access [Note 1].
“We can save a lot of energy by using probabilities” said Dr Wolff. “Instead of doing computations mechanically, we can concentrate our efforts where answers are most likely to be found. We don’t need some special process for gathering information about probabilities because, as a by-product of how the SP system works, it creates a statistical model of its environment.”
Big savings may also be possible in transmitting things like TV programmes. With some further development, the SP system may learn general rules and patterns from that kind of information. If the transmitter of a TV programme, and TV sets, all know those rules and patterns, then a TV programme can be transmitted economically by sending only the parts that are different from the general rules and patterns.
The SP system may help to bring some order into the chaos of different ways in which knowledge is represented in computer systems. In just one area—the representation of...
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