Scientists have made a crucial step towards unlocking the ‘holy grail’ of computing – microchips that mimic the way the human brain works to store and process information.
Originally published by the Oxford University
The research team has made the pioneering breakthrough of the development of photonic computer chips that imitate the way the brain’s synapses operate.
The work, conducted by researchers from Oxford, Münster and Exeter universities, combined phase-change materials – commonly found in household items such re-writable optical discs – with specially designed integrated photonic circuits to deliver a biological-like synaptic response.
Crucially, their photonic synapses can operate at speeds a thousand times faster than those of the human brain.
The team believes that the research could pave the way for a new age of computing, where machines work and think in a similar way to the human brain, while at the same time exploiting the speed and power efficiency of photonic systems.
The research is published in Science Advances.
Professor Harish Bhaskaran from the Department of Materials at Oxford University, who led the team, said: ‘The development of computers that work more like the human brain has been a holy grail of scientists for decades. Via a network of neurons and synapses the brain can process and store vast amounts of information simultaneously, using only a few tens of watts of power. Conventional computers can’t come close to this sort of performance.’
Professor C David Wright, co-author from the University of Exeter, said: ‘Electronic computers are relatively slow, and the faster we make them the more power they consume. Conventional computers are also pretty «dumb», with none of the in-built learning and parallel processing capabilities of the human brain. We tackle both of these issues here – by developing not only new brain-like computer architectures, but also by working in the optical domain to leverage the huge speed and power advantages of the upcoming silicon photonics revolution.’
Professor Wolfram Pernice, a co-author of the paper from the University of Münster, added: ‘Since synapses outnumber neurons in the brain by around 10,000 to one, any brain-like computer needs to be able to replicate some form of synaptic mimic. That is what we have done here.’
The work was supported by the UK’s Engineering and Physical Sciences Research Council.