SAfER Instruct

SAfER (Safe and Efficient Reinforcement/Robotics/etc.) research focuses on enhancing the safety and reliability of various AI systems, particularly in robotics and language models. Current efforts concentrate on developing methods for aligning language models with human preferences using automated data generation and improving robot navigation and control through techniques like control barrier functions and reinforcement learning, often incorporating real-time perception and dynamic obstacle prediction. This work is significant for mitigating risks associated with AI deployment in safety-critical applications, improving human-robot collaboration, and advancing the development of more trustworthy and robust AI systems.