The MEM-Scales neuromorphic project included researchers from Leti in France, IMEC in Belgium, IBM Zurich and the Chinese-backed Swiss startup SynSense.
The MeM-Scales researchers plan to build novel memory and device technologies and autonomous learning algorithms to support on-chip learning for both synapses and neurons. This would be done with a view to merging biological and electronic sensing and computation in such applications as distributed environmental monitoring, implantable medical diagnostic microchips, wearable electronics and human-computer interaction.
The results will be used to build neuromorphic computing systems that can process efficiently real-world sensory signals and natural time-series data in real-time and to demonstrate this with a practical laboratory prototype. This will enable low-power and always-on IoT and edge-computing computing processing systems for applications do not need to, or cannot afford to, connect to the cloud.
The significance of multi-timescale in the naming of the project comes from biological neural processing that can occur over time-scales ranging from milliseconds (axonal transmission) to seconds (spoken phrases) and much longer intervals (motor learning).