A New Route to Optimize AI Hardware: Homodyne Gradient Extraction

A new route to optimize AI hardware: Homodyne gradient extraction

A team led by the BRAINS Center for Brain-Inspired Computing at the University of Twente has demonstrated a new way to make electronic materials adapt in a manner comparable to machine learning. Their study, published in Nature Communications, introduces a method for physical learning that does not require software algorithms such as backpropagation. Backpropagation—the optimization method popularized in the 1980s by Nobel Prize winner Geoffrey …

University of Twente Advances Neuromorphic Computing with Hardware-Based Learning Method Free of Backpropagation

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