Literature DB >> 33268862

Inference in artificial intelligence with deep optics and photonics.

Gordon Wetzstein1, Aydogan Ozcan2, Sylvain Gigan3, Shanhui Fan4, Dirk Englund5, Marin Soljačić5, Cornelia Denz6, David A B Miller4, Demetri Psaltis7.   

Abstract

Artificial intelligence tasks across numerous applications require accelerators for fast and low-power execution. Optical computing systems may be able to meet these domain-specific needs but, despite half a century of research, general-purpose optical computing systems have yet to mature into a practical technology. Artificial intelligence inference, however, especially for visual computing applications, may offer opportunities for inference based on optical and photonic systems. In this Perspective, we review recent work on optical computing for artificial intelligence applications and discuss its promise and challenges.

Year:  2020        PMID: 33268862     DOI: 10.1038/s41586-020-2973-6

Source DB:  PubMed          Journal:  Nature        ISSN: 0028-0836            Impact factor:   49.962


  39 in total

1.  Optical network for real-time face recognition.

Authors:  H Y Li; Y Qiao; D Psaltis
Journal:  Appl Opt       Date:  1993-09-10       Impact factor: 1.980

2.  Optical implementation of the Hopfield model.

Authors:  N H Farhat; D Psaltis; A Prata; E Paek
Journal:  Appl Opt       Date:  1985-05-15       Impact factor: 1.980

3.  Holography in artificial neural networks.

Authors:  D Psaltis; D Brady; X G Gu; S Lin
Journal:  Nature       Date:  1990-01-25       Impact factor: 49.962

4.  Design of optical neural networks with component imprecisions.

Authors:  Michael Y-S Fang; Sasikanth Manipatruni; Casimir Wierzynski; Amir Khosrowshahi; Michael R DeWeese
Journal:  Opt Express       Date:  2019-05-13       Impact factor: 3.894

5.  60  dB high-extinction auto-configured Mach-Zehnder interferometer.

Authors:  C M Wilkes; X Qiang; J Wang; R Santagati; S Paesani; X Zhou; D A B Miller; G D Marshall; M G Thompson; J L O'Brien
Journal:  Opt Lett       Date:  2016-11-15       Impact factor: 3.776

6.  All-optical machine learning using diffractive deep neural networks.

Authors:  Xing Lin; Yair Rivenson; Nezih T Yardimci; Muhammed Veli; Yi Luo; Mona Jarrahi; Aydogan Ozcan
Journal:  Science       Date:  2018-07-26       Impact factor: 47.728

7.  Neural networks and physical systems with emergent collective computational abilities.

Authors:  J J Hopfield
Journal:  Proc Natl Acad Sci U S A       Date:  1982-04       Impact factor: 11.205

8.  Hybrid optical-electronic convolutional neural networks with optimized diffractive optics for image classification.

Authors:  Julie Chang; Vincent Sitzmann; Xiong Dun; Wolfgang Heidrich; Gordon Wetzstein
Journal:  Sci Rep       Date:  2018-08-17       Impact factor: 4.379

9.  Parallel photonic information processing at gigabyte per second data rates using transient states.

Authors:  Daniel Brunner; Miguel C Soriano; Claudio R Mirasso; Ingo Fischer
Journal:  Nat Commun       Date:  2013       Impact factor: 14.919

10.  Imaging with nature: compressive imaging using a multiply scattering medium.

Authors:  Antoine Liutkus; David Martina; Sébastien Popoff; Gilles Chardon; Ori Katz; Geoffroy Lerosey; Sylvain Gigan; Laurent Daudet; Igor Carron
Journal:  Sci Rep       Date:  2014-07-09       Impact factor: 4.379

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  23 in total

Review 1.  Artificial Intelligence in Meta-optics.

Authors:  Mu Ku Chen; Xiaoyuan Liu; Yanni Sun; Din Ping Tsai
Journal:  Chem Rev       Date:  2022-06-24       Impact factor: 72.087

2.  Materials for emergent silicon-integrated optical computing.

Authors:  Alexander A Demkov; Chandrajit Bajaj; John G Ekerdt; Chris J Palmstrøm; S J Ben Yoo
Journal:  J Appl Phys       Date:  2021-08-19       Impact factor: 2.877

3.  Polarization multiplexed diffractive computing: all-optical implementation of a group of linear transformations through a polarization-encoded diffractive network.

Authors:  Jingxi Li; Yi-Chun Hung; Onur Kulce; Deniz Mengu; Aydogan Ozcan
Journal:  Light Sci Appl       Date:  2022-05-26       Impact factor: 20.257

4.  Homeostatic neuro-metasurfaces for dynamic wireless channel management.

Authors:  Zhixiang Fan; Chao Qian; Yuetian Jia; Zhedong Wang; Yinzhang Ding; Dengpan Wang; Longwei Tian; Erping Li; Tong Cai; Bin Zheng; Ido Kaminer; Hongsheng Chen
Journal:  Sci Adv       Date:  2022-07-06       Impact factor: 14.957

Review 5.  Exploiting unique features of the gut-brain interface to combat gastrointestinal cancer.

Authors:  Alyssa Schledwitz; Guofeng Xie; Jean-Pierre Raufman
Journal:  J Clin Invest       Date:  2021-05-17       Impact factor: 14.808

6.  Deep physical neural networks trained with backpropagation.

Authors:  Logan G Wright; Tatsuhiro Onodera; Martin M Stein; Tianyu Wang; Darren T Schachter; Zoey Hu; Peter L McMahon
Journal:  Nature       Date:  2022-01-26       Impact factor: 69.504

7.  Imaging through diffuse media using multi-mode vortex beams and deep learning.

Authors:  Ganesh M Balasubramaniam; Netanel Biton; Shlomi Arnon
Journal:  Sci Rep       Date:  2022-01-28       Impact factor: 4.996

8.  An optical neural network using less than 1 photon per multiplication.

Authors:  Tianyu Wang; Shi-Yuan Ma; Logan G Wright; Tatsuhiro Onodera; Brian C Richard; Peter L McMahon
Journal:  Nat Commun       Date:  2022-01-10       Impact factor: 14.919

9.  Computer-free computational imaging: optical computing for seeing through random media.

Authors:  Yunzhe Li; Lei Tian
Journal:  Light Sci Appl       Date:  2022-02-14       Impact factor: 17.782

10.  Harnessing optoelectronic noises in a photonic generative network.

Authors:  Changming Wu; Xiaoxuan Yang; Heshan Yu; Ruoming Peng; Ichiro Takeuchi; Yiran Chen; Mo Li
Journal:  Sci Adv       Date:  2022-01-21       Impact factor: 14.136

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