UNTIL now they have been a thing of science fiction - like C3PO, The Terminator and Agent Smith from The Matrix.

But computers that function like the human brain could soon become a reality thanks to research using optical fibres made of speciality glass.

The research, published in Advanced Optical Materials, has the potential to allow faster and smarter optical computers capable of learning and evolving.

Researchers have demonstrated how neural networks and synapses in the brain can be reproduced, with optical pulses as information carriers, using special fibres made from glass that are sensitive to light, known as chalcogenides.

Research was carried out at the Optoelectronics Research Centre (ORC) at the University of Southampton and Centre for Disruptive Photonic Technologies (CDPT) at the Nanyang Technological University (NTU), Singapore.

Professor Dan Hewak, from the ORC, said: ''Since the dawn of the computer age, scientists have sought ways to mimic the behaviour of the human brain, replacing neurons and our nervous system with electronic switches and memory. Now instead of electrons, light and optical fibres also show promise in achieving a brain-like computer. The cognitive functionality of central neurons underlies the adaptable nature and information processing capability of our brains.''

In the last decade, neuromorphic computing research has advanced software and electronic hardware that mimic brain functions and signal protocols, aimed at improving the efficiency and adaptability of conventional computers.

But current computers are more than a million times less efficient than biological systems with five seconds of brain activity taking 500 seconds and using up substantially more power than the few calories required by the human brain.

Co-author Dr Behrad Gholipour said: ''By going back to biological systems for inspiration and using mass-manufacturable photonic platforms, such as chalcogenide fibres, we can start to improve the speed and efficiency of conventional computing architectures, while introducing adaptability and learning into the next generation of devices