NM500 neuromorphic chip with 576 neurons

NM500 is a neuromorphic chip opening new frontiers for smart sensors and cognitive computing applications. It can solve pattern recognition problems from text and data analytics, vision, audition, and multi-sensory fusion with orders of magnitude less energy and complexity than modern microprocessors.

NM500 features 576 interconnected neurons working in parallel and capable of learning and recognizing patterns in a few microseconds. The neurons behave collectively as a K-Nearest Neighbor classifier or a Radial Basis Function and are trainable. They are especially suitable to cope with ill-defined and fuzzy data, high variability of context and even novelty detection. Last, but not least, multiple NM500 chips can be daisy-chained to scale a network from thousands to millions of neurons with the same simplicity of operation as a single chip.

NeuroMem | NM500
Neuron capacity 576
Neuron memory size 256 bytes
Category register 15 bits
Distance register 16 bits
Context register 7 bits
Recognition status Identified, Uncertain or Unknown
Classifiers Radial Basis Function (RBF), K-Nearest Neighbor (KNN)
Distance Norms L1 (Manhattan), Lsup


NeuroTile is a unique combination of sensors, microcontroller, FPGA and a NeuroMem® neuromorphic chip in a miniature module perfect for wearable and low-power IoT applications.


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