EETimes - Rain Neuromorphics Tapes Out Demo Chip for Analog AI

Rain Neuromorphics has taped out a demonstration chip for its brain-inspired analog architecture that employs a 3D array of randomly-connected memristors to compute neural network training and inference at extremely low power. Switching to entirely analog hardware for AI computation could allow a massive reduction in the power consumed by AI workloads. While some commercial chips currently use analog processor-in-memory techniques, they require digital conversion between network layers, consuming significant power. The limitations of current analog devices also means they can't be used for training AI models since they are incompatible with back-propagation, the algorithm widely used for AI training. Rain's aim is to build a complete analog chip, solving these issues with a combination of new hardware and a new training algorithm.