Even with the advancement of artificial intelligence, computers still has its limitations. One major reason is the way memory and processor units traditionally work. It functions separately which means data have to be sent back and forth between the two. This is why a human brain is better than any modern computer since it processes and stores information in the same place.
An international team of researchers from the Universities of Münster (Germany), Oxford and Exeter (both UK), developed a piece of hardware which could pave the way for creating computers to function like a human brain.
They were able to produce a chip that contains a network of artificial neurons that interacts with light and can imitate the behavior of neurons and their synapses. With advanced machine learning technology, this optical neurosynaptic network is able to "learn" information and use this as a basis for computing and recognizing patterns, exactly like a human brain. Now since it utilizes light and not traditional electrons, data processing is several times faster.
The process itself involves the use of optical waveguides that can transmit light and can be fabricated into optical microchips are integrated with so-called phase-change materials -- which are already found today on storage media such as re-writable DVDs. These phase-change materials are characterized by the fact that they change their optical properties dramatically, depending on whether they are crystalline or amorphous. This phase-change can be triggered by light if a laser heats the material up.
"Because the material reacts so strongly, and changes its properties dramatically, it is highly suitable for imitating synapses and the transfer of impulses between two neurons," says lead author Johannes Feldmann.
"This integrated photonic system is an experimental milestone," says Prof. Wolfram Pernice from Münster University and lead partner in the study.
"Our system has enabled us to take an important step towards creating computer hardware which behaves similarly to neurons and synapses in the brain and which is also able to work on real-world tasks," says Wolfram Pernice. "By working with photons instead of electrons we can exploit to the full the known potential of optical technologies -- not only in order to transfer data, as has been the case so far but also in order to process and store them in one place," adds co-author Prof. Harish Bhaskaran from the University of Oxford.
This approach could be very useful in many different fields, especially in scenarios where large quantities of data are being evaluated, for example in medical diagnosis. Though before such applications could be done, further studies and work are needed, foremost to increase the number of artificial neurons (the current number is 4) and synapses (the current number is 60) which would, in turn, increase the depth of neural networks.