China's Humanoid Robot Race Shifts Focus to 'Brain' Power

Daily Technology

·

06/02/2026

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Chinese companies developing humanoid robots are increasingly prioritizing the advancement of artificial intelligence, or the robots' "brains," over their physical construction. This strategic pivot is driven by investor interest and the pursuit of practical, commercial applications for these advanced machines in real-world scenarios.

Key Takeaways

Chinese humanoid robot developers are focusing on AI and intelligent models to drive commercial viability.
Companies are moving from lab prototypes to industrially produced robots capable of autonomous decision-making.
Innovations in vision-language-action models and large-scale multimodal models are key to this advancement.

From Body to Brain: The New Frontier

Shenzhen-based Dobot has announced the delivery of its third batch of mass-produced, full-size humanoid robots, named Atom. This milestone signifies a transition from conceptual designs to tangible, industrial products. Dobot's self-developed Dobot-VLA, a vision-language-action model, is central to Atom's enhanced capabilities. This model allows the robot to interpret and respond to environmental uncertainties, moving beyond simple pre-programmed actions.

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Autonomous Decision-Making for Real-World Value

The Dobot-VLA model is designed to enable Atom to process complex tasks, understand ambiguous instructions, and make independent decisions to achieve objectives. Previously, Atom was demonstrated serving popcorn in a Shenzhen cinema, showcasing its potential for service-oriented roles. Dobot emphasizes that this autonomous adaptability, grounded in environmental understanding, is crucial for humanoid robots to generate value in industrial settings.

Rival Innovations in AI Models

This development follows closely on the heels of UBTech, a rival company also based in Shenzhen. UBTech recently open-sourced its Thinker model on platforms like GitHub and Hugging Face. Thinker is a large-scale multimodal model specifically engineered for humanoid robots. Built upon a 10 billion parameter foundation, the model aims to address common issues in humanoid robotics, such as operational lag and spatial inaccuracies, paving the way for more responsive and precise robot performance.

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