Custom silicon for speeding up AI inferencing is here, but IBM wants to go further and use a hybrid computing architecture and elements of resistive computing to also improve the efficiency of training neural networks.
The post IBM Aims To Reduce Power Needed For Neural Net Training By 100x appeared first on ExtremeTech.
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