Mitsubishi Electric has developed a high-speed training algorithm for deep learning that incorporates necessary inference functions for identification, recognition and prediction of unknown facts based on known facts. The new algorithm is expected to simplify the implementation of deep learning in vehicles, industrial robots and other machinery by drastically reducing memory usage and the computational time for training. It also will enable low-cost solutions in which artificial intelligence (AI) systems with training functions perform high-level inference directly within the embedded system according to the embedded system’s peripheral environment.
The algorithm reduces the training time, computational cost and memory requirements to approximately one-thirtieth of that of conventional AI. Mitsubishi Electric’s system should help expand AI’s range of utilization thanks to its compactness and overall low cost. It will reduce the costs of AI deployment by eliminating needs for servers and network facilities, because of its compactness and high-level inference to be performed directly in embedded systems. Mitsubishi Electric will present its new system at the International Conference on Neural Information Processing (ICONIP2016), which will be held at Kyoto University from October 16 to 21.
