Show HN: Cerebellum – small model on the robot, big model for what it can't undo (github.com)

Cerebellum has launched an open-source decision layer designed for robot fleets, enabling each robot to operate effectively both online and offline. This innovative solution allows robots to make rapid decisions using local models, only consulting a larger cloud-based model from NVIDIA, dubbed Nemotron, for irreversible actions or uncertain calls. This hybrid approach ensures that robots can work autonomously, with response times as low as 65 milliseconds on devices like Raspberry Pi, while also maintaining safety and accountability through thorough logging and review by the centralized cloud system. The significance of Cerebellum lies in its ability to seamlessly integrate local and cloud-based decision-making, which addresses the common challenges of robot deployment in environments with unreliable connectivity. By allowing developers to specify the cost of mistakes for various actions, the system intelligently routes decisions based on this cost framework, enhancing operational efficiency and safety. The solution is particularly valuable for applications like sorting and inspecting items, where rapid and accurate decisions are critical. With potential applications in various industries, Cerebellum represents a step forward in the development of autonomous systems that can intelligently navigate both real-time decision-making and connectivity issues.