Tech Xplore

New memristor training method slashes AI energy use by six orders of magnitude

In a Nature Communications study, researchers from China have developed an error-aware probabilistic update (EaPU) method ...
Network World

What are TPUs? Your guide to tensor processing units and AI acceleration

TPUs are Google’s specialized ASICs built exclusively for accelerating tensor-heavy matrix multiplication used in deep learning models. TPUs use vast parallelism and matrix multiply units (MXUs) to ...
Santa Barbara Independent

UC Santa Barbara Computer Scientist Breaking New Ground in Algorithmic Theory

From powering search engines to securing data and optimizing networks, algorithms underpin nearly every aspect of modern technology. Understanding how efficiently they can solve problems — and where ...
Princeton University

In the hallways of Princeton, a fascination with the human mind unlocked the power of deep learning

When Fei-Fei Li arrived in Princeton in January 2007 as an assistant professor, she was assigned an office on the second floor of the computer science building. Her neighbor was Christiane Fellbaum.
Phys.org

AI tensor network-based computational framework cracks a 100-year-old physics challenge

Researchers from The University of New Mexico and Los Alamos National Laboratory have developed a novel computational framework that addresses a longstanding challenge in statistical physics. The ...
Albuquerque Journal

Sandia researchers build AI system to detect anomalies across the electrical grid

The electrical grid is a crucial, sometimes fragile, piece of infrastructure. As connectivity to the grid increases, so too does its vulnerability. Public Service Company of New Mexico, the state’s ...
T&D

Sandia National Laboratories’ Research Team Develop AI Algorithms to Detect Physical Issues, Cyberattacks within Grid

Researchers at Sandia National Laboratories have developed AI algorithms to detect physical problems, cyberattacks and both at the same time within the grid. “As more disturbances occur, whether from ...
IEEE

Face Mask Detection Using Autoencoder Algorithm Comparing with Recurrent Concurrent Neural Network for Improving Accuracy

Abstract: This study aims to evaluate the effectiveness of two classification algorithms-AutoEncoder and Recurrent Convolutional Neural Network (R-CNN)-in predicting face mask detection. To conduct ...
Phys.org

Self-learning neural network cracks iconic black holes

A team of astronomers led by Michael Janssen (Radboud University, The Netherlands) has trained a neural network with millions of synthetic black hole data sets. Based on the network and data from the ...
Frontiers

Enhancing security in 6G-enabled wireless sensor networks for smart cities: a multi-deep learning intrusion detection approach

Introduction: Wireless Sensor Networks (WSNs) play a critical role in the development of sustainable and intelligent smart city infrastructures, enabling data-driven services such as smart mobility, ...
Scientific Research Publishing

Mirjalili, S. (2018) Genetic Algorithm. In: Mirjalili, S., Ed., Evolutionary Algorithms and Neural Networks, Springer, 43-55.

ABSTRACT: Supply chain networks, which integrate nodes such as suppliers, manufacturers, and retailers to achieve efficient coordination and allocation of resources, serve as a critical component in ...