• Professor Simon Brown's paper published in prestigious peer-reviewed journal Science Advances proves signals on the chips are remarkably like those that pass through the network of neurons in the brain. Photo credit: The University of CanterburyProfessor Simon Brown's paper published in prestigious peer-reviewed journal Science Advances proves signals on the chips are remarkably like those that pass through the network of neurons in the brain. Photo credit: The University of Canterbury

University of Canterbury scientist develops brain-like computer chip

A team lead by Professor Simon Brown at the University of Canterbury (UC) has developed computer chips with brain-like functionality that could lead to significantly reducing the global carbon emissions produced from computing. 

The chips are based on self-organisation of nanoparticles – taking advantage of physical principles at unimaginably small scales, a hundred thousand times smaller than the thickness of a human hair, to make brain-like networks.

This is important for building new kinds of computers because the brain is incredibly good at processing information using very small amounts of energy. So these brain-like computing chips could enable “edge computing” and in the long term begin to address the ever-increasing energy consumption of computers.

The components of this new chip are at the atomic level and are so small they cannot be seen with the naked eye or conventional microscopes, and can only be seen in electron microscopes.  The team’s research has shown that the nanoparticles act like the neurons of the brain sending similar cascades of voltage pulses to pass instructions.  This means that more of the processing can occur “on-chip” and consumes less power than standard processors.

Professor Brown explained how: “These chips might provide a different kind of artificial intelligence. By understanding the underlying fundamental physical processes, we believe we can design these chips and control their behaviour to do things like pattern or image recognition. The key is that processing on-chip and with low power consumption opens up new applications that are not currently possible.”

Potential applications of this technology could be on cell phones, robotics, autonomous vehicles and biomedical devices.  It is possible that by allowing more data processing to take place on cell phones, the technology might by-pass concerns about sharing sensitive data with big companies like Facebook and Google. The team is conscious of concerns about AI and is working alongside social scientists to understand the ethical considerations of using applying this new technology.

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