Software to hardware: a multidisciplinary team
- The development of high-performance, low-cost and low-consumption Edge AI solutions requires a broad range of skills in the development of non-volatile memories, sensors and circuits, including the development of advanced algorithms, such as incremental machine learning. CEA-Leti's Edge AI program relies on a multidisciplinary team, from several institutes, capable of providing competitive, made-to-measure solutions that can be industrialized quickly.
- The program brings together some 50 experts from various institutes, such as CEA-Leti and
CEA-List.
Bio-inspired solutions
The research engineers from the Edge AI program are working with biologists and researchers in cognitive psychology to draw inspiration from working mechanisms in the living world that are both energy-efficient and possess an unbelievable capacity to adapt. They are developing neuromorphic hardware systems, equipped with artificial neurons and synapses that optimize energy-consuming interactions. Specifically, the team is exploring three paths of research:
- Impulse data coding, similar to the brain's neurons, that is both efficient and noise-resistant
- The development of dense, non-volatile memory technologies to implement the synapses, in order to bring them and the neurons as close together as possible, and
- The development of impulse sensors, vision sensors and micro-electromechanical systems (MEMS) to take inspiration from the communications mechanisms in the natural world.
Incremental machine learning
The recently developed, bio-inspired hardware will host the incremental machine-learning solutions that the program is also developing. Unlike current AI solutions, which require enormous learning databases, future Edge AI solutions will be able to learn gradually and economically.