Scientists have succeeded in developing a piece of hardware which could pave the way for creating computers resembling the human brain. They produced a chip containing a network of artificial neurons that works with light and can imitate neurons and their synapses. This network is able to 'learn' information and use this as a basis for computing. The approach could be used later in many different fields for evaluating patterns in large quantities of data.
A technology that functions like a brain? In these times of artificial intelligence, this no longer seems so far-fetched -- for example, when a mobile phone can recognise faces or languages. With more complex applications, however, computers still quickly come up against their own limitations. One of the reasons for this is that a computer traditionally has separate memory and processor units -- the consequence of which is that all data have to be sent back and forth between the two. In this respect, the human brain is way ahead of even the most modern computers because it processes and stores information in the same place -- in the synapses, or connections between neurons, of which there are a million-billion in the brain. An international team of researchers from the Universities of Münster (Germany), Oxford and Exeter (both UK) have now succeeded in developing a piece of hardware which could pave the way for creating computers which resemble the human brain. The scientists managed to produce a chip containing a network of artificial neurons that works with light and can imitate the behaviour of neurons and their synapses.
The researchers were able to demonstrate, that such an optical neurosynaptic network is able to "learn" information and use this as a basis for computing and recognizing patterns -- just as a brain can. As the system functions solely with light and not with traditional electrons, it can process data many times faster. "This integrated photonic system is an experimental milestone," says Prof. Wolfram Pernice from Münster University and lead partner in the study. "The approach could be used later in many different fields for evaluating patterns in large quantities of data, for example in medical diagnoses." The study is published in the latest issue of the "Nature" journal.