Unlike LLMs that train on the existing internet, robotics lacks a pre-training dataset for the physical world. This forces companies like Encore to build a full-stack solution combining a software platform for data management with human-led operations for data collection, annotation, and even real-time remote robot piloting for exception handling.

China's current advantage in robotics stems from its unparalleled manufacturing supply chain, enabling faster production and lower hardware costs. However, the true bottleneck remains acquiring sufficient physical data for AI training, pushing mass-market humanoid robots to a roughly 10-year timeline.

Instead of deploying thousands of expensive robots to gather manipulation data, Sunday Robotics is distributing cheaper, specialized gloves. This allows them to collect high-quality, diverse data from humans performing tasks in their own homes, accelerating model development.

To bridge the training data gap for robotics, companies are paying gig workers to remotely operate robots in people's homes via VR. This creates a bizarre symbiosis where human labor is directly converted into data to train their future automated replacements.

An Indian company, Objectways, pays thousands of workers to wear headset cameras while performing manual tasks. This footage is sold as training data for humanoid robotics companies like Tesla's Optimus, effectively paying humans to accelerate their own obsolescence.

China's scale in physical hardware like drones and autonomous vehicles generates a vast dataset of multimodal data (sound, vision, LiDAR). This real-world data, underappreciated in the text-focused West, gives Chinese companies a significant advantage in training intelligent physical AI models.

Progress in robotics for household tasks is limited by a scarcity of real-world training data, not mechanical engineering. Companies are now deploying capital-intensive "in-field" teams to collect multi-modal data from inside homes, capturing the complexity of mundane human activities to train more capable robots.

China's booming humanoid robotics market isn't driven by current utility. Instead, the primary buyers are the numerous state-supported training centers, creating a speculative ecosystem where demand for today's limited robots is fueled by the promise of tomorrow's more advanced models.

The surge in China's humanoid robot market isn't from consumer or factory adoption. Government-backed centers are buying robots to generate and sell valuable teleoperation training data back to manufacturers, creating a circular R&D ecosystem that fuels the industry's growth.