Currently, computers don't have the capacity to learn from past experiences, and rely on preprogrammed code to make decisions. On the other hand, brain cells do not require programming, are high tolerance, can regenerate, and can draw conclusions that computers are not able to reach, said Karlheinz Meier, professor and chair of experimental physics at the University of Heidelberg.
Traditional computers won't go away, meanwhile, as some activities don't require intelligent processing, said Meier, who is also co-director of the European Union-funded Human Brain Project.
"You will always do your text processing and email," Meier said.
But like the brain, neural chips will excel at certain things, like cutting through "noisy" data to make intelligent decisions, said Nabil Imam, a computer scientist and researcher at Cornell University.
The neuromorphic chips will complement, not replace, other processors in a computer, Imam said.
Chips modeled after the human brain have electronic neurons that can dynamically rewire the connections among them, blast information at each other, and forage for relevant data -- a process more power efficient than throwing lots of data to CPUs and other coprocessors like GPUs. IBM's Watson supercomputer made history when it beat participants at the game of Jeopardy, but it threw lots of data at processors to find answers.
"Our brains were wired to do certain things very well like pattern recognition. Computers can't do that. These processors have a different class of applications," Imam said.
Imam is involved in the development of neuromorphic chips as part of the multiphase Synapse (Systems of Neuromorphic Adaptive Plastic Scalable Electronics) project funded by DARPA. The Synapse project, initiated in 2008, involves IBM, Hewlett-Packard, Cornell, Stanford University and other universities.
The first tangible results for Synapse came in early 2011, when IBM demonstrated a prototype chip with 256 digital neurons running at slow speeds of 10MHz. The chip was able to demonstrate navigation and pattern recognition abilities.
One chip core had 262,144 programmable synapses, while another core had 65,536 learning synapses. The connections between digital neurons got stronger depending on the number of signals sent. If an electronic spike from one neuron affects the voltage of another neuron, the two are synaptically connected. In chips, spiking neurons communicate with other neurons when triggers, such as certain values, are reached.
The next big Synapse announcement will come next year, when a new neural chip system that mimics a "very big brain" will be announced, Imam said. The chip will have a novel design of memory arrays so that large numbers of connections can be made among digital neurons. An asynchronous design will ensure communication signals are organized by local circuits. The chip will be made using a new manufacturing process.
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