Machine Intelligence on Wireless Edge Networks with RF Analog Architecture (MIT, Duke)

Machine Intelligence on Wireless Edge Networks with RF Analog Architecture (MIT, Duke)

A new technical paper titled “Machine Intelligence on Wireless Edge Networks” was published by researchers at MIT and Duke University. Abstract “Deep neural network (DNN) inference on power-constrained edge devices is bottlenecked by costly weight storage and data movement. We introduce MIWEN, a radio-frequency (RF) analog architecture that “disaggregates” memory by streaming weights wirelessly and performing classification in the analog front e…