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Robots do not improve through code alone They also need large volumes of diverse, high-quality interaction data and that is the problem @axisrobotics is trying to solve 🤖 WHAT AXIS DOES Axis turns everyday users into contributors for Physical AI training Through browser-based simulations, users control robotic arms and complete practical manipulation tasks such as: • Placing one object beside another • Moving items into a specific position • Following spatial instructions • Completing multi-step interaction scenarios Each valid task creates a trajectory containing useful behavioral data for robotics training WHY THESE TASKS MATTER A task may look simple from the outside, but the generated data can help models learn: • Spatial reasoning • Object recognition • Robotic arm control • Instruction following • Motion planning • Real-world task execution This kind of data is especially valuable for imitation learning and Vision-Language-Action models HOW CONTRIBUTIONS ARE VALUED Axis does not reward users only for the time they spend on the platform Points depend on: • The number of valid tasks completed • The difficulty of each task • The quality of signed submissions • The diversity of scenarios and skills covered • Genuine referrals That means one accurate and challenging trajectory can be more valuable than several low-quality attempts WHY THE MODEL IS INTERESTING Collecting robotics data through physical machines is expensive and difficult to scale Axis creates a community-driven alternative where thousands of contributors can help generate useful training data through simulation Users are not simply completing tasks for points They are helping build the datasets needed for the next generation of intelligent robots For more updates, task discussions and community support, join the Axis Robotics Discord 👇 discord.gg/C4sVCXBz