Synstor circuits for real-time adaptive intelligent systems
The foundation of current AI systems lies in computers that implement learning and inference procedures sequentially, resulting in learning latency, elevated power consumption, and diminished adapbility to unforeseen environmental changes. We overcome these issues by presenting a brain-inspired synaptic resistor (synstor) circuit, enabling concurrent real-time learning and inference. AI systems utilizing synstor circuits, such as those in drones and morphing wings, achieve significantly faster learning, better performance, greater energy efficiency, and improved adaptability compared to computer-based AI systems. Synstor circuits offer a promising path for AI systems to excel in dynamic and unpredictable real-world environments.
Authors
- Yong Chen (ORCID: https://orcid.org/0000-0002-4846-7131)
Institutions
- University of California, Los Angeles (US)
Publication Details
- Journal
- Journal of Intelligent Material Systems and Structures
- Published
- 2025-07-20
- DOI
- https://doi.org/10.1177/1045389x251349347
- Primary Topic
- Advanced Memory and Neural Computing
- Type
- article
- Field-Weighted Citation Impact
- 0.00
Funders
- Air Force Office of Scientific Research