Fraunhofer Institute for Integrated Circuits IIS
Spiking neurons with a sense of time
With spiking neural networks (SNNs), Artificial Intelligence becomes even more similar to the human brain. Unlike traditional artificial neural networks, where signals are exchanged continuously, SNNs only transmit relevant data in the form of short electrical pulses. Like their biological counterparts, the artificial neurons have their own sense of time: they only become active when a critical threshold of signals is exceeded.
While classical AI models increasingly demand more computing power, spiking neural networks resolve the tension between energy efficiency and real-time capability. Their structure allows for the processing of massive amounts of data in a power-saving and fast manner, without losing performance. SNNs particularly showcase their strengths when Artificial Intelligence needs to be directly integrated into end devices.
We aim to bring SNNs to breakthrough and implement them in practice. Therefore, we not only explore their topology but also develop customized hardware designs for ultra-low-power and ultra-low-latency applications.