Innatera’s ultra-efficient neuromorphic processors mimic the brain’s mechanisms for processing sensory data. Based on a proprietary analog-mixed signal computing architecture, Innatera’s processors leverage the computing capabilities of spiking neural networks to deliver ground-breaking cognition performance within a narrow power envelope. With an unprecedented combination of ultra-low power consumption and short response latency, these chips enable high-performance always-on pattern recognition capabilities for power-limited and latency-critical applications.
Innatera's technology relies on the powerful processing capabilities of Spiking Neural Networks (SNN). Closely mimicking the processing mechanisms used in the brain, SNNs are event-based neural networks in which information is represented using simple, precisely timed events. SNN models work by manipulating the timing relationships between these events, leveraging temporal correlations between events to identify patterns. Key to these capabilities is the inherent notion of time built into the neurons and synapses of SNNs, which unlike conventional artificial neural networks, allows powerful temporal processing to be carried out even with small models. SNNs enable rapid recognition of patterns in sensor data, in addition to complex signal processing, just like your brain does.