Researchers have developed a method to compress and encode videos for use in robotics datasets, reducing storage requirements by up to 90% according to the authors. The approach uses a combination of video compression algorithms and data augmentation techniques to create a more efficient dataset. This could enable researchers to work with larger and more complex robotic systems without running out of storage space. --- Why it matters: This matters because robotics datasets are often limited by storage constraints, hindering research progress in areas like autonomous navigation and manipulation. By reducing the size of these datasets, researchers can explore more complex scenarios and improve the performance of their robots. Source: https://huggingface.co/blog/video-encoding