A joint research led by City University of Hong Kong (CityU) has built an ultralow-power consumption artificial visual system to mimic the human brain, which successfully performed data-intensive cognitive tasks. Their experiment results could provide a promising device system for the next generation of artificial intelligence (AI) applications.
Their findings have been published in the scientific journal Science Advances.
As the advances in semiconductor technologies used in digital computing are showing signs of stagnation, the neuromorphic (brain-like) computing systems have been regarded as one of the alternatives in future. Scientists have been trying to develop the next generation of advanced AI computers which can be as lightweight, energy-efficient and adaptable as the human brain.
Unfortunately, effectively emulating the brain’s neuroplasticity – the ability to change its neural network connections or re-wire itself – in existing artificial synapses through an ultralow-power manner is still challenging.
Artificial synapse is an artificial version of synapse – the gap across which the two neurons pass through electrical signals to communicate with each other in the brain. It is a device that mimics the brain’s efficient neural signal transmission and memory formation process.
To enhance the energy efficiency of the artificial synapses, the research team has introduced quasi-two-dimensional electron gases (quasi-2DEGs) into artificial neuromorphic systems for the first time. By utilising oxide superlattice nanowires – a kind of semiconductor with intriguing electrical properties, they have designed the quasi-2DEG photonic synaptic devices which have achieved a record-low energy consumption down to sub-femtojoule (0.7fJ) per synaptic event. It means a decrease of 93% energy consumption when compared with synapses in the human brain.
Their experiments have demonstrated that the artificial visual system based on this photonic synapses could simultaneously perform light detection, brain-like processing and memory functions in an ultralow-power manner. The researchers believe their findings can provide a promising strategy to build artificial neuromorphic systems for applications in bionic devices, electronic eyes, and multifunctional robotics in future.
With this quasi-2DEG photonic synapse, the researchers have built an artificial visual system which could accurately and efficiently detect a patterned light stimulus and “memorise” the shape of the stimuli for an hour. It is just like our brain will remember what we saw for some time.
The way the team synthesised the photonic synapses and the artificial visual system did not require complex equipment. And the devices could be made on flexible plastics in a scalable and low-cost manner.
News Source: City University of Hong Kong
