Challenges in Training Advanced Robot Models

Training models like RFM1 for broad robotic applications poses challenges in gathering sufficient data. While large language models like RFM1 show promise in training robots for various tasks, the amount and sources of data required remain uncertain. Researchers are exploring methods to generate training data for robots, including collecting videos of human tasks and simulations featuring robot actions. Covariant's data trove from robot-arm deployments offers valuable insights into physical world interactions, aiding in enhancing AI models' comprehension of real-world physics.