Founder at Recurrent Computing, Inc. - Washington, District of Columbia, United States
Recurrent Computing, Inc. is developing a revolutionary approach to edge-computing based Machine Learning that is ideally suited to complex, time-varying environments, with the ability to make decisions or recommend actions rapidly. The technology is based on neuromorphic electronic designs, especially well-suited for self-sufficient, cognitive systems for remote operations. Our approach drastically reduces training time and is capable of in-field adaptive learning, with solutions that offer low Size, Weight, and Power (SWaP). These solutions do not require continuous connection to the remote processors, and are suitable for solar/battery powered equipment.