Abstract
The following quote was obtained by the news editors from the background informa tion supplied bythe inventors: “Analog machine learning holds the promise of si gnificant power savings, performanceimprovement, accuracy improvement and noise reduction compared to digital implementations. Generally,machine learning requ ires the implementation of a weighted summer, which may have a linear shift called a bias, as well as an activation or decision means to produce an output. Each output may be connectedto many other weighted summers and these connections ma y need to be dynamically programmable, forexample in recurrent networks, or vir tual neuron schemes, as do the weights and bias values in all networks.
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