Category: Neuromorphic Computing

Modern AI models achieve impressive performance but require enormous amounts of energy when trained and run on conventional GPU hardware. A promising alternative is analog in-memory computing, where neural network computations are performed directly inside memory devices such as resistive crossbar arrays. This approach can dramatically improve the efficiency of AI systems, but it also … full description “Training Neural Networks for Analog AI Hardware (available)”