Hiddenite: A new AI processor for reduced computational power consumption based on a cutting-edge neural network theory

A new accelerator chip called Hiddenite that can achieve state-of-the-art accuracy in the calculation of sparse hidden neural networks with lower computational burdens has now been developed by Tokyo Tech researchers. By employing the proposed on-chip model construction, which is the combination of weight generation and supermask expansion, the Hiddenite chip drastically reduces external memory access for enhanced computational efficiency.