3D-printed Deep Learning neural network uses light instead of electrons

Traditionally, deep learning systems are implemented on a computer to learn data representation and abstraction and perform tasks, on par with – or better than – the performance of humans. However the team led by Dr. Aydogan Ozcan, the Chancellor's Professor of electrical and computer engineering at UCLA, didn't use a traditional computer set-up, instead choosing to forgo all those energy-hungry electrons in favor of light waves. The result was its all-optical Diffractive Deep Neural Network (D2NN) architecture.