Engineering researchers at the University of Minnesota Twin Cities have demonstrated a state-of-the-art hardware device that could reduce energy consumption for artificial intelligent (AI) computing applications by a factor of at least 1,000.This post was […]
Large-scale neural network models form the basis of many AI-based technologies such as neuromorphic chips, which are inspired by the human brain. Training these networks can be tedious, time-consuming, and energy-inefficient given that the model […]
A 28GHz time-division multiple-input multiple-output (MIMO) receiver with eight radio frequency elements, each occupying just 0.1 mm2, has been developed by researchers at Tokyo Tech using 65nm CMOS technology. This innovative design reduces chip size […]
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