We expect a lot from our computers these days. They should talk to us, recognize everything from faces to flowers, and hopefully in the near future do the driving. All this artificial intelligence requires an enormous amount of computing power, stretching the limits of even the most modern machines.

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Now, some of the world’s largest tech companies are taking a cue from biology as they respond to these growing demands. They are rethinking the very nature of computers and have began building machines that look more like the human brain.

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After years of stagnation, the computer is evolving again, and this behind-the-scenes migration to a new kind of machine will have broad and lasting implications. It will allow work on artificially intelligent systems to accelerate, so the dream of machines out of sci-fi movies will one day come true.

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“This is an enormous change,” said John Hennessy, the former Stanford University president who wrote an authoritative book on computer design in the mid-1990s and is now a member of the board at Alphabet, Google’s parent company. “The existing approach is out of steam, and people are trying to re-architect the system.”

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The existing approach has had a pretty nice run. For about half a century, computer were engineered to be built with systems around a single, do-it-all chip- the central processing unit.

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Now, computer engineers are fashioning more complex systems, turning Intel on its head. Rather than funneling all tasks through one beefy chip made by Intel, newer machines are dividing work into tiny pieces and spreading them among vaster systems of simpler, specialized chips that consume less power.

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The idea has made its way to smaller developers as well. Using components pulled off store shelves, researchers at the University of Tennessee, Knoxville, have made a chip for intelligent computers that can learn. The chips are structured to discover patterns through probabilities and association, helping with decision-making much like the human brain.

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The researchers are using off-the-shelf, reprogrammable circuits called FPGAs (field programmable gate arrays) to simulate the way neurons and synapses in a brain operate. The chip was made as part of the university’s neuromorphic software project. Their technology excels at doing specific tasks and can be easily reprogrammed for other applications.

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Researchers are developing neuromorphic chips since It’s becoming difficult to further shrink the chips that power PCs and mobile devices. In response to this, researchers are trying to apply the brain’s structure to computing.

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Brains have 100 billion neurons that process and transmit information, and can compute in parallel via trillions of connections, called the synapses. The researchers are creating a mesh network of neurons and synapses that deal with input, output, and connections. Researchers are also establishing software models that can be applied to this neural network.

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While this shift is happening mostly inside the massive data centers that underpin the Internet, it is probably a matter of time before it permeates the broader industry. The hope is that this new breed of mobile chip can help devices handle more complex tasks on their own.

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This means we will live in a world where phones will recognize spoken commands without accessing the internet; driverless cars can recognize the world around them with a speed and accuracy that is not possible now.