Currently, the humanoid robotics industry is riding a wave of optimistic developments and is entering a phase of rapid technological progress, akin to the transformative period following the advent of AlexNet in 2012. Presently, the cognitive capabilities of robot "brains" have not yet matched those of GPT-2, indicating that the industry is still some distance away from experiencing explosive growth. Concurrently, the industry is exploring three technological avenues: Vision-Language-Action (VLA) integration, world modeling, and simulation-based reinforcement learning. However, the primary bottleneck lies in the scarcity of high-quality data. To trigger a virtuous cycle of iterative data enhancement, the accumulation of millions of hours of effective data is imperative.

On the hardware front, a pivotal moment of design convergence is gradually approaching, with significant growth anticipated in key components such as actuators and dexterous hands. The true breakthrough in the industry will not be heralded by the launch of a single model. Rather, it will emerge quietly, only after five core operational metrics—including the continuous, uninterrupted working duration of robots and factory operation precision—are achieved. This will be coupled with the concurrent establishment of a closed-loop computing power data system, an operational data flywheel, and consistent hardware manufacturing processes.