The Embodied AI Data Flywheel: Why Physical AI Will Outpace LLMs

The embodied AI training data problem is structurally different from the language model data problem. Language models learned from the internet. Embodied AI must learn from the physical world — and that data does not exist yet at scale. Why language models scaled faster than embodied AI training data Large language models achieved their capability […]
How to Scale Teleop Data Collection Without Losing Quality

Scaling teleop data collection is one of the hardest operational problems in robotics. The volume grows quickly. The quality does not always follow. The teleop data collection quality cliff nobody warns you about Scaling teleoperation data collection sounds straightforward: hire more operators, run more sessions, collect more trajectories. In practice, most teams hit a quality […]