NM500 (coming this summer)

NM500 neuromorphic chip with 576 neurons

The 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.

Non linear classifier

Identify, Classify, Detect  novelty, cope with non linearity and ill defined problems, report cases of unknown and cases of uncertainty.


Model Generator

Real-time learning, high speed clustering, intrinsic deduplication, tracability of the knowledge built by the neurons


High performance

Fixed latency regardless of the number of neurons, order of micro-seconds per pattern, low power consumption (0.5 Watts), low clock frequency, small footprint

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