Beijing-based startup Dexmal has launched its first embodied native large model, DM0, along with the embodied native development framework Dexbotic 2.0 and the embodied native application mass production workflow, DFOL.
The company's CEO Tang Wenbin noted that 2026 will not be the dawn of embodied intelligence, but rather the dawn of embodied nativeness.
The company’s newly released DFOL (Distributed Field Online Learning) workflow is designed to enable robots to maintain high efficiency and certainty while also achieving human-like flexibility and adaptability. The core concept is the "hardware universality + model intelligence" approach.
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Insights
What are the core concepts behind embodied native large models?
What is the origin of Dexmal and its mission in the tech industry?
What technical principles underpin the DFOL workflow?
How is the market responding to Dexmal's DM0 model?
What trends are emerging in the field of embodied intelligence?
What recent updates have been announced regarding Dexmal's technology?
What policies might impact the development of embodied native technologies?
What are the potential future directions for embodied intelligence?
What long-term impacts could Dexmal's technology have on robotics?
What challenges does Dexmal face in the development of DM0?
What controversies surround the concept of embodied intelligence?
How does Dexmal's DM0 compare to other large models in the market?
What historical cases influenced the development of embodied models?
What similar concepts exist in the field of artificial intelligence?
