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Artificial Intelligence Accelerators based on Graphene Optoelectronic Devices.
Weilu Gao,Cunxi Yu,Ruiyang Chen +2 more
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TLDR
In this paper, the authors report a new optoelectronic architecture consisting of spatial light modulators and photodetector arrays made from graphene to perform matrix-vector multiplication (MVM) operations.Abstract:
Optical and optoelectronic approaches of performing matrix-vector multiplication (MVM) operations have shown the great promise of accelerating machine learning (ML) algorithms with unprecedented performance. The incorporation of nanomaterials into the system can further improve the performance thanks to their extraordinary properties, but the non-uniformity and variation of nanostructures in the macroscopic scale pose severe limitations for large-scale hardware deployment. Here, we report a new optoelectronic architecture consisting of spatial light modulators and photodetector arrays made from graphene to perform MVM. The ultrahigh carrier mobility of graphene, nearly-zero-power-consumption electro-optic control, and extreme parallelism suggest ultrahigh data throughput and ultralow-power consumption. Moreover, we develop a methodology of performing accurate calculations with imperfect components, laying the foundation for scalable systems. Finally, we perform a few representative ML algorithms, including singular value decomposition, support vector machine, and deep neural networks, to show the versatility and generality of our platform.read more
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Deep Residual Learning for Image Recognition
TL;DR: In this article, the authors proposed a residual learning framework to ease the training of networks that are substantially deeper than those used previously, which won the 1st place on the ILSVRC 2015 classification task.
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Deep Learning
TL;DR: Deep learning as mentioned in this paper is a form of machine learning that enables computers to learn from experience and understand the world in terms of a hierarchy of concepts, and it is used in many applications such as natural language processing, speech recognition, computer vision, online recommendation systems, bioinformatics, and videogames.
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Neural networks and physical systems with emergent collective computational abilities
TL;DR: A model of a system having a large number of simple equivalent components, based on aspects of neurobiology but readily adapted to integrated circuits, produces a content-addressable memory which correctly yields an entire memory from any subpart of sufficient size.
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Extraordinary optical transmission through sub-wavelength hole arrays
Thomas W. Ebbesen,Thomas W. Ebbesen,Henri J. Lezec,H. F. Ghaemi,Tineke Thio,Peter A. Wolff,Peter A. Wolff +6 more
TL;DR: In this article, the optical properties of submicrometre cylindrical cavities in metallic films were explored and it was shown that arrays of such holes display highly unusual zero-order transmission spectra at wavelengths larger than the array period, beyond which no diffraction occurs.
Journal ArticleDOI
In situ immune response and mechanisms of cell damage in central nervous system of fatal cases microcephaly by Zika virus
Raimunda do Socorro da Silva Azevedo,Jorge Rodrigues de Sousa,Marialva Tereza Ferreira de Araújo,Arnaldo Jorge Martins Filho,Bianca Nascimento de Alcantara,Fernanda Montenegro de Carvalho Araújo,Maria G. L. Queiroz,Ana Cecília Ribeiro Cruz,Beatriz H. Baldez Vasconcelos,Jannifer Oliveira Chiang,Lívia Carício Martins,Livia Medeiros Neves Casseb,Eliana Vieira Pinto da Silva,Valéria Lima Carvalho,Barbara Cristina Baldez Vasconcelos,Sueli Rodrigues,Consuelo Silva de Oliveira,Juarez Antônio Simões Quaresma,Pedro Fernando da Costa Vasconcelos +18 more
TL;DR: The in situ immune response profile and mechanisms of neuronal cell damage in fatal Zika microcephaly cases were investigated and changes found were mainly calcification, necrosis, neuronophagy, gliosis, microglial nodules, and inflammatory infiltration of mononuclear cells.
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