Our latest and most advanced technologies — from AI to Industrial IoT, advanced robotics, and self-driving cars — share serious problems: massive energy consumption, limited on-edge capabilities, ...
Dhireesha Kudithipudi (second from right), founding director of MATRIX at UTSA, chats with students during the NSF AI Spring School at UTSA's San Pedro I building. The research is part of a broader ...
Neuromorphic computing -- a field that applies principles of neuroscience to computing systems to mimic the brain's function and structure -- needs to scale up if it is to effectively compete with ...
The transformative power of computing, driven by advances in microelectronics and silicon-based transistors, has reshaped our ...
The UK will establish a new center to develop brain-inspired, neuromorphic computing technologies. The UK Multidisciplinary Center for Neuromorphic Computing is led by Aston University and will ...
Neuromorphic computing, inspired by the brain, integrates memory and processing to drastically reduce power consumption compared to traditional CPUs and GPUs, making AI at the network edge more ...
Los Alamos National Laboratory Researchers Design New Artificial Synapses for Neuromorphic Computing
Tested against a dataset of handwritten images from the Modified National Standards and Technology database, the interface-type memristors realized a high image recognition accuracy of 94.72%. (Los ...
Yiran Chen develops brain-inspired semiconductor hardware to enable faster, greener AI at the edge.
A recent study published in npj 2D Materials and Applications explores hexagonal boron nitride (h-BN) atomristors, highlighting their notable memory window, low leakage current, and minimal power ...
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