scispace - formally typeset
Open AccessJournal ArticleDOI

Deep learning with coherent nanophotonic circuits

TLDR
A new architecture for a fully optical neural network is demonstrated that enables a computational speed enhancement of at least two orders of magnitude and three order of magnitude in power efficiency over state-of-the-art electronics.
Abstract
Artificial Neural Networks have dramatically improved performance for many machine learning tasks. We demonstrate a new architecture for a fully optical neural network that enables a computational speed enhancement of at least two orders of magnitude and three orders of magnitude in power efficiency over state-of-the-art electronics.

read more

Citations
More filters
Journal ArticleDOI

Experimental Quantum Stochastic Walks Simulating Associative Memory of Hopfield Neural Networks

TL;DR: A good match rate of the associative memory between the experimental quantum scheme and the expected result for Hopfield neural networks is demonstrated and the ability of quantum simulation for an important feature of a neural network provides a primary but steady step towards photonic artificial intelligence devices for optimization and computation tasks of greatly improved efficiencies.
Journal ArticleDOI

Prospects and applications of on-chip lasers

TL;DR: In this paper , the state-of-the-art in different aspects of application-driven on-chip silicon lasers is discussed from device-level and system-wide points of view.
Journal ArticleDOI

Collective and synchronous dynamics of photonic spiking neurons.

TL;DR: In this paper, photonic spiking neurons implemented with paired nonlinear optical oscillators can be controlled to generate two modes of bio-realistic spiking dynamics by changing optical-pump amplitude.
Journal ArticleDOI

Artificial Intelligence Accelerators Based on Graphene Optoelectronic Devices

TL;DR: This work reports a new optoelectronic architecture consisting of spatial light modulators and photodetector arrays made from graphene to perform MVM, and develops a methodology of performing accurate calculations with imperfect components, laying the foundation for scalable systems.
Journal ArticleDOI

Microcomb-based integrated photonic processing unit

TL;DR: In this paper , a parallel convolution based on time-wavelength plane stretching approach is implemented on a microcomb-driven chip-based photonic processing unit (PPU).
References
More filters
Proceedings Article

ImageNet Classification with Deep Convolutional Neural Networks

TL;DR: The state-of-the-art performance of CNNs was achieved by Deep Convolutional Neural Networks (DCNNs) as discussed by the authors, which consists of five convolutional layers, some of which are followed by max-pooling layers, and three fully-connected layers with a final 1000-way softmax.
Journal ArticleDOI

Deep learning

TL;DR: Deep learning is making major advances in solving problems that have resisted the best attempts of the artificial intelligence community for many years, and will have many more successes in the near future because it requires very little engineering by hand and can easily take advantage of increases in the amount of available computation and data.
Journal ArticleDOI

Human-level control through deep reinforcement learning

TL;DR: This work bridges the divide between high-dimensional sensory inputs and actions, resulting in the first artificial agent that is capable of learning to excel at a diverse array of challenging tasks.
Journal ArticleDOI

Reducing the Dimensionality of Data with Neural Networks

TL;DR: In this article, an effective way of initializing the weights that allows deep autoencoder networks to learn low-dimensional codes that work much better than principal components analysis as a tool to reduce the dimensionality of data is described.
Journal ArticleDOI

Deep learning in neural networks

TL;DR: This historical survey compactly summarizes relevant work, much of it from the previous millennium, review deep supervised learning, unsupervised learning, reinforcement learning & evolutionary computation, and indirect search for short programs encoding deep and large networks.
Related Papers (5)