At the 2026 Inclusion·Bund Conference, held from September 9 to 12 in Shanghai's Huangpu District under the theme "Co-creating the New AI Economy," Wang Qian, founder and CEO of Autonomous Agent Robotics, shared his firm belief that the essence of intelligence lies embedded within data itself.

Wang highlighted that a portion of a model's capabilities originates from the evaluation process. During training, the model acts as a distillation apparatus, while in deployment, it functions as a container. To engineer cutting-edge AI systems, the sheer weight of the model itself has become a diminishing factor.

He observed that recent performance gains from successive language model versions are only partially attributed to an increase in model size; a more significant driver has been the consistently improving quality of the underlying data. In his experience building language models, the vast majority of effort is poured into data production, filtering, validation, and labeling. It is precisely this relentless focus on the data layer that fuels tangible progress in AI system effectiveness.

Wang noted that code-based capabilities were the first to be conquered, simply because code data is the easiest to generate and verify. Mathematics followed, and now the industry is extending into 3D and video generation. While validating 3D and video data is more challenging, these fields are comparatively simpler for annotation purposes, so the sector has largely advanced in this sequential order.

This raises a pertinent question: if a frontier lab like OpenAI or Anthropic were to pivot toward embodied intelligence, would it not require the exact same data infrastructure and validation scaffolding? Such a venture would necessitate collecting real-world data, building simulators, developing world models, and conducting evaluations while interfacing with physical hardware in authentic environments.

If none of these stages can be bypassed, Wang argued, then, in his view, such an organization is, at its core, simply another embodied intelligence enterprise. The advantages conferred by possessing a foundational model do not lower the difficulty of these engineering hurdles. Conversely, dedicated players entrenched in the embodied intelligence sector will hold substantive advantages; the ceiling of their intelligent capabilities and the velocity of their iteration cycles will not be noticeably amplified simply because a rival owns a base model.