One more step up the ladder takes us to an MCU augmented with a neural processing unit (NPU). These NPUs process data in a batch mode, performing matrix computations (e.g., matrix multiplication) on large datasets, which can be resource-intensive. The third type of sparsity is data sparsity. Since the real-world data being fed into the networkis being generated in real-time “on the fly,” data sparsity isn’t something that can be handled by a preprocessor. So, rather than going event-based data (from the camera) to frame-based data, and then frame-based data to event-based data (to the Akida processor), the folks from Prophesee and brainchip can simply feed the event-based data from the camera directly to the event-based Akida processor, thereby cutting latency and power consumption to a minimum.