Professor Zdenka Kuncic in the Sydney Nanoscience Hub.

An international research team has created a synthetic neural network using nanotechnology, with potential to develop new systems in machine learning and artificial intelligence.

The team is led by the International Centre for Materials Nanoarchitectonics at the National Institute of Materials Science in Japan, in collaboration with the University of Sydney Nano Institute and School of Physics, and the California NanoSystems Institute at the University of California at Los Angeles.

The team found that when electrically stimulated, this “neuromorphic network” exhibited emergent brain-like behaviour resembling cognitive functions such as learning, memorisation and forgetting. A neuromorphic network is an artificial, large-scale system that mimics the biological functions of the nervous system, particularly its neurons.

Professor Zdenka Kuncic from Sydney Nano and the School of Physics was part of the team. She said: “This is exciting because it opens up the possibility of processing dynamically changing data that existing machine learning and AI methods can’t handle.”

The research was recently published in Springer Nature’s Scientific Reports.

The discovery has implications for the development of artificial intelligence (AI) networks. Although AI is brain-inspired, the underlying mechanism by which the brain processes information remains elusive. Therefore, creating novel materials and systems that mimic functions similar to the brain and understanding the mechanisms of those functions may open up new possibilities for neuromorphic information processing technologies.