Circular Reasoning: Spiraling Circuits for More Efficient AI

University of Tokyo create a new integrated three-dimensional circuit architecture for artificial intelligence applications with spiraling stacks of memory modules. Researchers at the University of Tokyo Institute of Industrial Science in Japan stacked resistive random-access memory modules for artificial intelligence (AI) applications in a novel three-dimensional spiral. The modules feature oxide semiconductor access transistors, which boost the efficiency of the machine learning training process. The team further enhanced energy efficiency via a system of binarized neural networks, which restricts the parameters to be either 1 or -1, rather than any number, to compress the volume of data to be stored. In having the device interpret a database of handwritten digits, the researchers learned that increasing the size of each circuit layer could improve algorithmic accuracy to approximately 90%.