on @axisrobotics when you complete a task, you generate a trajectory, a complete record of how the robot was controlled, what happened in the environment, every step, and whether the task actually succeeded the axis robotics task generation engine uses LLM-driven gen to create diverse manipulation scenarios, from simple pick-and-place tasks to complex multi-stage interactions long runs can be captured in segments and reliably reproduced, making the resulting data much more useful for training and evaluating robotic policies the main idea with axis; ◇ humans perform tasks ◇ trajectories are captured ◇ data improves robot intelligence ◇ better robots can handle more complex tasks instead of collecting robotic data only inside expensive, closed labs, axis hub makes it better with task completion for generating real-world interaction data start completing your trajectories here; https://t.co/FCmvHggTHU