Demonstration Data

Demonstration data, crucial for training data-driven models like those used in robotics and AI alignment, is the focus of intense research. Current efforts center on improving the efficiency and quality of data acquisition, exploring methods like augmented reality interfaces to reduce demonstrator burden and leveraging vision-language models and novel view synthesis to generate diverse and robust datasets. These advancements aim to overcome limitations in existing datasets, ultimately enabling more efficient and effective training of complex AI systems for various applications, including robotic manipulation and large language model alignment.