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Optical neural networks for ultra-fast, low-latency machine intelligence

Optical neural networks for ultra-fast, low-latency machine intelligence
用于超快、低延迟机器智能的光神经网络
批准号:
10043476
负责人:
金额:
$120.58万
依托单位:
依托单位国家:
英国
项目类别:
Collaborative R&D
财政年份:
2023
资助国家:
英国
项目状态:
未结题
起止时间:
2023 至 --

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中文摘要
翻译
以人工神经网络为动力的机器智能正在迅速发展,并进入我们生活的方方面面。光学在这一领域提供了一个新的范例,其中光子而不是电子扮演信息载体和计算代理的角色。光神经网络有望将神经网络的功率效率和速度提高1000 -100,000倍。从电子神经网络转向光学神经网络将使机器智能更容易获得,更环保,从而为社会带来直接利益。更高效、更节能的人工智能系统将使机器学习民主化,使其对社会弱势群体更有价值。OxONN正在与牛津大学合作,为下一代先进的光学神经网络奠定基础。该联盟在光学计算方面拥有世界领先的专业知识,并在光学计算方法和硬件方面开发了改变游戏规则的技术。在该项目中,该联盟将专注于开发任何神经网络主要组件的光学实现-光学矩阵矢量乘法器,该乘法器将在生产力和可扩展性方面优于竞争产品,并成为OxONN的第一个MVP。此外,还将开发一种概念新颖的计算机视觉深度光学神经网络系统。该系统将允许神经网络直接“看到”并解释物体,而无需将图像转换为电子形式。这样的系统将具有超低延迟,并在自动驾驶汽车、遥感和智能机器人中得到应用。这个高度创新的项目旨在将英国置于全光计算技术的前沿,并将英国定位为人工智能系统众多应用的下一个全球技术领导者。
英文摘要
Machine intelligence, powered by artificial neural networks, is developing rapidly and entering all aspects of our lives. A novel paradigm in this field is offered by optics, where photons, rather than electrons, play the role of information carriers and computational agents. Optical neural networks promise to enhance both the power efficiency and speed of neural networks by a factor of 1,000-100,000\. Switching from electronic to optical neural networks will make machine intelligence much more accessible and environmentally friendly, thereby delivering direct benefits to society. More productive and energy efficient AI systems will democratise machine learning, making it more of value to socially-vulnerable groups.OxONN in collaboration with the University of Oxford are creating the foundations for the next-generation of advanced optical neural networks. This consortium possesses world-leading expertise in optical computing and has developed game-changing technologies in optical-computing methodologies and hardware. In this project, the consortium will focus on developing the optical implementation of a primary component of any neural network - the optical matrix-vector multiplier, which will be superior to competing products in terms of productivity and scalability, and become OxONN's first MVP. In addition, a conceptually novel deep optics neural network system for computer vision will be developed. This system will allow a neural network to "see" and interpret objects directly, bypassing the need for converting an image into an electronic form. Such a system will have ultra-low latency and find applications in autonomous vehicles, remote sensing and intelligent robotics.This highly innovative project aims to put the UK at the forefront of all-optical computing technology and position our country as the next global technology leader in AI systems for a plethora of applications.
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