Artificial neural networks enabled by nanophotonics

• Published in: Light, science & applications science & applications, 2019-05, Vol.8 (1), p.42-42, Article 42
• Main Authors: Zhang, Qiming, Yu, Haoyi, Barbiero, Martina, Wang, Baokai, Gu, Min
• Format: Article
• Language: English
• Subjects: 142/126; 639/624/1075/1079; 639/624/1075/1080; Applied and Technical Physics; Artificial intelligence; Atomic; Classical and Continuum Physics; Lasers; Molecular; Neural networks; Optical and Plasma Physics; Optical Devices; Optics; Photonics; Physics; Physics and Astronomy; Review; Review Article; Structure-function relationships
• ISSN: 2047-7538; 2095-5545; 2047-7538
• DOI: 10.1038/s41377-019-0151-0

The growing demands of brain science and artificial intelligence create an urgent need for the development of artificial neural networks (ANNs) that can mimic the structural, functional and biological features of human neural networks. Nanophotonics, which is the study of the behaviour of light and the light–matter interaction at the nanometre scale, has unveiled new phenomena and led to new applications beyond the diffraction limit of light. These emerging nanophotonic devices have enabled scientists to develop paradigm shifts of research into ANNs. In the present review, we summarise the recent progress in nanophotonics for emulating the structural, functional and biological features of ANNs, directly or indirectly. Artificial neural networks: tapping in to the power of light Technologies that manipulate light at the nanoscale will help researchers develop artificial neural networks (ANNs) with uses including brain disease research and machine learning. Despite advances in neuroscience, understanding the human brain remains a considerable challenge. Constructing physical or computer-based ANNs can help scientists analyse brain function and harness its power. Min Gu and colleagues at RMIT University in Melbourne, Australia, reviewed research into emerging ANNs enabled by nanophtonics that harness photons’ ability to carry vast amounts of information. Three-dimensional printing and laser writing techniques are allowing researchers to fabricate tiny optical or electronic components for building artificial neurons and ANN scaffolding platforms. Another all-optical ANN design uses multiple layers of diffractive holograms to create a highly efficient machine learning engine. Transplantable ANNs combining nanophotonic technology such as nanosensing with biological tissues could one day help study and treat severe brain disorders or injuries.