We leverage “evolution” in ideal biological systems, including a wealth of research information available for a honeybee neurology, to build 10-100x lower mass, volume, power, and latency vision sensing and robotics operations under noisy conditions at the extreme edge.
We are developing a bottom-up bio-inspired vision sensor AI platform with multiple model neural networks, for our evolutionary analog-AI architecture and software implementation, operating under noisy conditions at the extreme edge.
Our roadmap includes developing a low power and latency bottom-up Nuromorphic Evolutionary Analog-AI Architecture and Software for autonomous sensors, drones, and robotics operations utilizing a honeybee emulation of an autonomous vision sensor platform and its applications.
