Hardware
While artificial intelligence (AI) models are becoming increasingly advanced, training and running these models on conventional computer hardware is very energy consuming. Engineers worldwide have thus been trying to create ...
Electronics & Semiconductors
Over the past few decades, the performance of machine learning models on various real-world tasks has improved significantly. Training and implementing most of these models, however, still requires vast amounts of energy ...
Electronics & Semiconductors
Memristors, or resistive memory devices (RRAM) are nanometer-sized electronic components that can serve as memories for portable computers and other devices. When they are organized in a cross-bar structure, these tiny memories ...
Electronics & Semiconductors
Researchers at the University of Massachusetts and the Air Force Research Laboratory Information Directorate have recently created a 3-D computing circuit that could be used to map and implement complex machine learning algorithms, ...
Engineering
Researchers at Technion and TowerJazz in Israel have recently built a low-power, two-terminal floating-gate transistor that could have useful applications in neuromorphic computing. This transistor, presented in a paper in ...
Electronics & Semiconductors
Reservoir computing (RC) is an approach for building computer systems inspired by current knowledge of the human brain. Neuromorphic computing architectures based on this approach are comprised of dynamic physical nodes, ...
Engineering
A new way of arranging advanced computer components called memristors on a chip could enable them to be used for general computing, which could cut energy consumption by a factor of 100.
Jul 30, 2018
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Electronics & Semiconductors
While we embrace the way the Internet of Things already is making our lives more streamlined and convenient, the cybersecurity risk posed by millions of wirelessly connected gadgets, devices and appliances remains a huge ...
Apr 25, 2018
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Computer Sciences
(Phys.org)—A team of researchers working at the University of California (and one from Stony Brook University) has for the first time created a neural-network chip that was built using just memristors. In their paper published ...
Electronics & Semiconductors
Artificial neural networks may soon be able to process time-dependent information, such as audio and video data, more efficiently. The first memristor with a "relaxation time" that can be tuned is reported today in Nature ...
May 20, 2024
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