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Artificial brains could point the way to ultra-efficient supercomputers
Sandia National Labs cajole Intel's neurochips into solving partial differential equations New research from Sandia National ...
Sandia National Labs today released an update on its neuromorphic computing research, reporting that these systems, inspired ...
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Bio-inspired nanochannels provide experimental evidence for uncovering brain memory mechanisms
A research team from the Institute of Modern Physics of the Chinese Academy of Sciences and Lanzhou University has obtained ...
A new technical paper titled “Solving sparse finite element problems on neuromorphic hardware” was published by researchers ...
Cory Merkel, assistant professor of computer engineering at Rochester Institute of Technology, will represent the university as one of five collegiate partners in the new Center of Neuromorphic ...
When it comes to developing faster and smaller chips to power next-generation electronic devices, Silicon is seen as the leading option. This abundant, cheap semiconductor provides acceptable carrier ...
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 ...
July 10, 2024 — The U.S. Department of Energy’s Advanced Scientific Computing Research (ASCR) program has announced a Monday July 22 deadline (11:59 pm ET) for position papers for a workship on ...
It’s estimated it can take an AI model over 6,000 joules of energy to generate a single text response. By comparison, your brain needs just 20 joules every second to keep you alive and cognitive. That ...
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 ...
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, ...
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