Requiring so little power -- less than that required by a hearing aid -- opens up a vast array of potential uses, especially on devices with limited power sources.
For instance, a processor could be embedded in a mobile device or a sensor, where it could be trained to do object recognition on auditory, visual or multi-sensory data sources, a computationally intensive task that now requires a dedicated server. Such jobs could easily be done on a remote device itself, eliminating the need to stream video to a data center.
"The sensor becomes the computer," Modha said.
The brain-inspired architecture is not designed to replace standard processors, but rather be used in conjunction with them, to tackle jobs that require lots of computation operations to be carried out in parallel.
In the data center, the chips could be used in co-processor acceleration cards for running machine-learning neural networks, Modha said. Many machine learning algorithms now being commercially used could be easily adapted to this architecture, which could carry out highly parallel operations in a more energy-efficient manner, Modha said.
IBM is still investigating how to commercialize this processor, Modha said, and has made no commitments to either manufacture the chip itself or license the design out to others. Modha said that, from early fabrication work, he saw no "fundamental risks" in producing these chips in large volumes.
The company is also developing compilers and related software to make these processors easy to use.
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