Researchers from The Hong Kong University of Science and Technology (HKUST) have developed the world’s first all-optical neural network for deep machine learning – bringing artificial intelligence a step closer to matching human brains in tackling complex problems such as pattern recognition or risk management, and at much lower energy consumption at the speed of light.
For a long time, optical computation has been limited to linear multiplication*. With only linear multiplication, a neural network cannot be used for deep machine learning which simulates human brain functions. Deep machine learning in AI requires a multilayer neural network in which nonlinear activation functions are necessary components. But in a conventional hybrid optical neural network, nonlinear activation functions – which simulate the way neurons response in human brains, are implemented electronically, thereby restricting both the speed and power. Now, a research team led by Professor DU Shengwang and Assistant Professor LIU Junwei from HKUST’s Department of Physics, demonstrated the first-of-its-kind multilayer all-optical artificial neural network, making large-scale optical neural networks a step closer to reality.
Credit: “HKUST researchers build the world’s first all-optical multilayer neural network paving way for next generation of AI hardware”, The Hong Kong University of Science and Technology
