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Copper free: two Münster researchers compare a prototype optical chip to a one-cent coin. (Courtesy: University of Münster)

 

Topics: Artificial Intelligence, Computer Engineering, Neuromorphic Devices


A prototype artificial neural network (ANN) that uses only light to function has been unveiled by researchers at the University of Münster in Germany and the University of Exeter and University of Oxford in the UK. Their system can learn how to recognize simple patterns and its all-optical design could someday be exploited to create ANNs that can process large amounts of information rapidly while consuming relatively small amounts of energy.

ANNs mimic the human brain by using artificial neurons and synapses. A neuron receives one or more input signals and then uses this information to decide whether to output its own signal to the network. Synapses are the connections between neurons and can be “weighted” to favor signal propagation between certain neurons. An ANN can be trained to perform a task such as recognizing a pattern by sending multiple examples of the target pattern through the ANN while tweaking the synaptic weights until all examples of the target pattern elicit the same output from the ANN.

Relatively simple ANNs can be implemented on a computer. However, the conventional computer architecture of having a separate processor and memory makes it very difficult to implement the large numbers of neurons and synapses required to perform practical tasks.

One alternative is to create an ANN in which signals flows in the form of light pulses through an optical network. This is attractive because unlike electronic signals in a silicon chip, large amounts of light-encoded data can move quickly through optical materials without generating much heat. Furthermore, large amounts of information can be sent through an optical system by multiplexing the data using several different colors of light.

 

All-optical network mimics the brain’s neurons and synapses
Hamish Johnston, Physics World

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