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EE Times Current, 19 April 2024
Dr. Elisa Donati of the Institute of Neuroinformatics in Zurich talks to Dr. Sunny Bains about neuromorphic circuits for prosthetics, drug delivery, and more. Discussion follows with Dr. Giulia D’Angelo from the Fortiss research institute in Munich, and Professor Ralph Etienne-Cummings of Johns Hopkins University. You are listening to EE Times On Air, and this is EE Times Current. I’m Eric Singer. Welcome to Brains and Machines,…
EBRAINS Neuromorphic platform BrainScaleS-2 adds new interface for high-speed robotics
EBRAINS, 17 April 2024
Their work, detailed in a recent paper published in Frontiers in Neuroscience, introduced a real-time spike interface to the neuromorphic platform BrainScaleS-2 (BSS-2). This innovation enables advancements in high-speed robotics applications, due to a 1,000-fold acceleration of the emulated nerve cells. The biological brain shows very high speed and efficiency when processing…
Using sound waves for photonic machine learning: Study lays foundation for reconfigurable neuromorphic building blocks
Tech Xplore, 16 April 2024
Optical neural networks may provide the high-speed and large-capacity solution necessary to tackle challenging computing tasks. However, tapping their full potential will require further advances. One challenge is the reconfigurability of optical neural networks. A research team in the Stiller Research Group at the Max Planck…
Vietnam Neuromorphic Computing Market Embarking on the Uncharted Mastering Deep Understanding through Observational Prowess
Taiwan News, 10 April 2024
We are excited to unveil the newest edition of our exhaustive market research report “Vietnam Neuromorphic Computing Market,” crafted by Report Ocean, a leading provider of industry insights. This report offers a plethora of invaluable insights and analysis regarding the prevailing trends, growth opportunities, competitive dynamics, and strategic directives within the [specific industry/market]….
Photonic neuromorphic architecture for tens-of-task lifelong learning
EurekAlert!, 7 April 2024
Artificial intelligence (AI) tasks become increasingly abundant and complex fueled by large-scale datasets. With the plateau of Moore's law and end of Dennard scaling, energy consumption becomes a major barrier to more widespread applications of today's heavy electronic deep neural models, especially in terminal/edge systems. The community is imminently looking for next-generation computing modalities to break thr…
New Ultra-Low Power Memory for Neuromorphic Computing
SciTechDaily, 7 April 2024
KAIST researchers have created a low-power, cost-efficient phase change memory device, setting a new standard in memory technology. A team of Korean researchers is making headlines by developing a new memory device that can be used to replace existing memory or used in implementing neuromorphic computing for next-generation artificial intelligence hardware for its low processing costs and ultra-low power consumption….
Choosing the Right Technologies for Hybrid AI Chips
EE Times Current, 4 April 2024
In this podcast, Dr. Sunny Bains discusses neuromorphic chips with Dr. Amirreza Yousefzadeh, who most recently worked at imec and the University of Twente. He has a broad background in electronics, starting with digital and then moving into neuromorphic, and he’s spent time both in industry and research. This sets him up neatly to work on hybrid AI SoCs. Discussion follows with Dr. Giulia D’Angelo from the Fortiss research insti…
KAIST Develops Ultra-Low Power Memory for Neuromorphic Computing
the MIRAGE, 4 April 2024
A team of Korean researchers is making headlines by developing a new memory device that can be used to replace existing memory or used in implementing neuromorphic computing for next-generation artificial intelligence hardware for its low processing costs and its ultra-low power consumption. KAIST (President Kwang-Hyung Lee) announced on April 4th that Professor Shinhyun Choi's research team in the Schoo…
Photonic neuromorphic architecture for tens-of-task lifelong learning
newswise, 3 April 2024
Artificial intelligence (AI) tasks become increasingly abundant and complex fueled by large-scale datasets. With the plateau of Moore’s law and end of Dennard scaling, energy consumption becomes a major barrier to more widespread applications of today's heavy electronic deep neural models, especially in terminal/edge systems. The community is imminently looking for next-generation computing modalities to…
Using neuromorphic engineering to reinvent visual processing systems with a biological inspiration
NEWS MEDICAL LIFE SCIENCES, 1 April 2024
As computer vision (CV) systems become increasingly power and memory intensive, they become unsuitable for high-speed and resource deficit edge applications – such as hypersonic missile tracking and autonomous navigation – because of size, weight, and power constraints. At the University of Pittsburgh, engineers are ushering in the next generation of computer vision systems by…
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