<p>The Fraunhofer Institute for Integrated Circuits IIS has developed an AI chip for processing Spiking Neural Networks (SNNs). The SENNA spiking neural network inference accelerator, inspired by brain function, consists of artificial neurons and can process electrical impulses (spikes) directly. Its speed, energy efficiency, and compact design enable the use of SNNs directly where data is generated: in edge devices.</p><p>SNNs consist of a network of artificial neurons connected by synapses. Information is transmitted and processed in the form of electrical impulses, allowing pulsing networks to be the next step in artificial intelligence: faster, more energy-efficient, and closer to the processing method of the human brain. To bring these advantages into application, small, efficient hardware that mimics a structure of neurons and synapses is needed. For this, the Fraunhofer IIS has developed the neuromorphic SNN accelerator SENNA as part of the Fraunhofer project SEC-Learn.</p><p>SENNA is a neuromorphic chip for fast processing of low-dimensional time series data in AI applications. The current version consists of 1024 artificial neurons on less than 11 mm² of chip area. Its low reaction time down to 20 nanoseconds ensures precise timing in time-critical applications at the edge. This makes it particularly strong in real-time event-based sensor data processing and in closed control systems, such as the control of small electric motors with AI. With SENNA, AI-optimized data transmission can be realized in communication systems. There, the AI processor can analyze signal streams and adjust transmission and reception methods as needed to improve efficiency and performance.</p>