Detecting ‘Aggressive Driving’ With Machine Learning And Edge Computing

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A recent patent application has proposed a system for identifying ‘aggressive driving behavior’ at junctions using machine learning algorithms deployed in civic edge computing devices.In contrast to recent innovations of AI research into in-vehicle ‘road rage’ analytics (primarily intended for the benefit of insurance companies), the system proposed is instead municipal in nature, and could be aimed at facilitating penalties for drivers that are not conforming to the ambient norms of ‘safe’ driver behavior. It is also specifically intended to provide bad drivers with related in-car audiovisual alerts.The patent was filed at the US Patent and Trademark Office on 29th April 2021 on behalf of the Board Of Regents of the University of Michigan, and the Denso corporation, a Japanese automotive components manufacturer owned by Toyota.The...

In-sensor reservoir computing for language learning via two-dimensional memristors

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AbstractThe dynamic processing of optoelectronic signals carrying temporal and sequential information is critical to various machine learning applications including language processing and computer vision. Despite extensive efforts to emulate the visual cortex of human brain, large energy/time overhead and extra hardware costs are incurred by the physically separated sensing, memory, and processing units. The challenge is further intensified by the tedious training of conventional recurrent neural networks for edge deployment. Here, we report in-sensor reservoir computing for language learning. High dimensionality, nonlinearity, and fading memory for the in-sensor reservoir were achieved via two-dimensional memristors based on tin sulfide (SnS), uniquely having dual-type defect states associated with Sn and S vacancies. Our in-sensor reservoir...

In-sensor reservoir computing for language learning via two-dimensional memristors

1621020876 F1.large
AbstractThe dynamic processing of optoelectronic signals carrying temporal and sequential information is critical to various machine learning applications including language processing and computer vision. Despite extensive efforts to emulate the visual cortex of human brain, large energy/time overhead and extra hardware costs are incurred by the physically separated sensing, memory, and processing units. The challenge is further intensified by the tedious training of conventional recurrent neural networks for edge deployment. Here, we report in-sensor reservoir computing for language learning. High dimensionality, nonlinearity, and fading memory for the in-sensor reservoir were achieved via two-dimensional memristors based on tin sulfide (SnS), uniquely having dual-type defect states associated with Sn and S vacancies. Our in-sensor reservoir...

Cambridge Quantum Computing Pioneers Quantum Machine Learning Methods for Reasoning

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Scientists at Cambridge Quantum Computing (CQC) have developed methods and demonstrated that quantum machines can learn to infer hidden information from very general probabilistic reasoning models. These methods could improve a broad range of applications, where reasoning in complex systems and quantifying uncertainty are crucial. Examples include medical diagnosis, fault-detection in mission-critical machines, or financial forecasting for investment management. In this paper published on the pre-print repository arXiv, CQC researchers established that quantum computers can learn to deal with the uncertainty that is typical of real-world scenarios, and which humans can often handle in an intuitive way. The research team has been led by Dr. Marcello Benedetti with co-authors Brian Coyle, Dr. Michael Lubasch, and Dr. Matthias Rosenkranz, and is...

Earn IT Certifications in Cloud Computing, Project Management, Blockchain, and More With This Online Learning Library

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Get certified in cloud computing, digital marketing, Linux, and much more. April 4, 2021 2 min read Disclosure: Our goal is to feature products and services that we think you'll find interesting and useful. If you purchase them, Entrepreneur may get a small share of the revenue from the sale from our commerce partners. Entrepreneurs should always be learning new things. Becoming a lifelong learner is one of the best success habits you can implement into your life. Times change, the world adapts, and it's vital that you, as a leader, understand how to adapt with it. You can learn in many ways, from churning through books and articles, watching documentaries, or accessing a treasure trove of online learning...

Worldwide Edge Computing Technology Trends Report 2021: Distributed Cloud, SD-WAN, Micro-Datacenter Network, DSS, Tiny Edge-Chain, Federated Learning for Edge, O-RAN Edge Server, Edge AI Chipsets

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The "Recap and Outlook of Worldwide Edge Computing Industry and Technology in 2021" report has been added to ResearchAndMarkets.com's offering.The development of the worldwide edge computing industry diversified in 2020 with clearer information on applicable technology and application areas. Cloud service providers have tried to meet telecommunication service providers; needs with distributed cloud solutions; telecom equipment manufacturers have focused on services extending from 5G mobile edge computing such as network slicing; information hardware manufacturers have attempted to create distributed database systems using software-defined networking technology.This report provides an overview of the development of edging computer and looks into eight emerging technology trends including distributed cloud, SD-WAN, and data distribution services for...

CrownBio and JSR Life Sciences Partner with Cambridge Quantum Computing to Leverage Quantum Machine Learning for Novel Cancer Treatment Biomarker Discovery

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SUNNYVALE, Calif. & CAMBRIDGE, England--(BUSINESS WIRE)--Crown Bioscience (CrownBio), JSR Life Sciences and Cambridge Quantum Computing (CQC) today announced a partnership agreement to explore the application of quantum technology to drive the identification of multi-gene biomarker discovery for oncology drug discovery. The partnership will combine CrownBio’s domain expertise and vast data sets generated from 15 years of preclinical and translational research and CQC’s advanced capabilities in quantum algorithms, quantum machine learning, and quantum computing. Utilizing quantum machine algorithms and CQC’s software development framework for execution on NISQ (Noisy Intermediate-Scale Quantum) computers, the initial approach will focus on deriving insight from the analysis of genetic data to identify cancer treatment biomarkers and...