news 2022

A CEA-Leti tutorial presented at IEDM 2022 highlighted promising advantages that resistive random-access memory (RRAM) technologies hold for implementing novel neuromorphic/in-memory computing systems for massively parallel, low-power and low-latency computation. In a presentation titled "Resistive Memories-Based Concepts for Neuromorphic Computing" , Elisa Vianello, CEA-Leti's edge AI program manager, said RRAMs, aka memristors, offer advantages in energy efficiency and computing power when processing AI workloads.

GRENOBLE, France - July 7, 2022 - Inspired by the barn owl's neuroanatomy, CEA-Leti has developed an event-driven, object-localization system that couples state-of-the-art piezoelectric, ultrasound transducer sensors to a neuromorphic, resistive memories-based computational map. Presented in a paper published recently in Nature Communications , the research team describes development of an auditory-processing system that increases energy efficiency by up to five orders of magnitude compared to conventional localization systems.

When we implement complex cognitive processes, for example when making decisions, we are subject to cognitive bias. But what about simpler processes, such as those involved in the most basic learning? In a new study analyzing data from all previous research in the field, researchers from Inserm and ENS-PSL show that not only are positivity and confirmation biases present even in the simplest human and animal cognitive processes, but also that incorporating them into learning algorithms would enhance their performance.