The Quality Quotient in Robot Training

This chapter emphasizes the significance of data quality over volume in robot training, showcasing how expert data collection leads to better robotic performance. The discussion covers challenges in live demonstrations and the limitations of current sensor technologies, while advocating for improved local models and privacy in data management. It also explores recent advancements in robotics, highlighting the potential of open-source practices and the application of modular models to enhance task efficiency.