Scientists May Have Found A Missing Piece for 'Artificial Brains'

In a breakthrough that could usher in a new era of artificial intelligence (AI), scientists at the US National Institute of Standards and Technology (NIST) in Colorado have created a neuromorphic superconducting switch that "learns" to mimic neuro-biological architectures present in the human brain. In a paper published in Science Advances on January 26, the NIST research team headed by physicist Mike Schneider, said the synthethic switch they called a'superconducting synapse' – just like the structure in the brain that permits neurons to communicate with each other – has been shown to process synapse-like properties in a completely inorganic device. Researchers also note the new neuromorphic hardware, which has the shape of a metallic cylinder that's 10 micrometres in diameter, is designed to process incoming flows of electricity it receives and produce appropriate output signals. NIST further explains that multiple artificial synapses could be 3D stacked so that three-dimensional interconnectivity, high-device density and flexibility can be achieved. Another advantage of this technique is that by processing multi-dimensional information through a fault-tolerant computation process or learning through experience – or even from the surrounding environment, synthetic synapses, which can also connect processors and store memories of neuromorphic systems in units of magnetic flux, could offer a viable solution to mitigate the barriers of interconnect scaling in advanced computer systems.