Optical Neural Networks: The 3D connection

Abstract

We motivate a new canonical strategy for integrating photonic neural networks (NNs) by leveraging 3D printing. Our believe is that a NN's parallel and dense connectivity is not scalable without 3D integration. 3D additive fabrication complemented with photonic signal transduction can dramatically augment the current capabilities of 2D CMOS and integrated photonics. Here we review some of our recent advances made towards such a breakthrough architecture.

Cited by in corpus (9)

• The physics of optical computing
• Prospects and applications of photonic neural networks
• Direct (3+1)D laser writing of graded-index optical elements
• Understanding and mitigating noise in trained deep neural networks
• Programmable metasurfaces for future photonic artificial intelligence
• Additive 3D photonic integration that is CMOS compatible
• Noise mitigation strategies in physical feedforward neural networks
• Impact of internal noise on convolutional neural networks
• Internal noise in hardware deep and recurrent neural networks helps with learning