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On November 2, 2026, UBTECH released Thinker-Sim, an embodied intelligence simulation platform centered on Real2Sim2Real, covering the digitization of real-world scenarios, large-scale synthetic simulation data generation, and robot capability evaluation. According to a Sina Tech report, the platform's rendering efficiency has improved by 67.3%, a single node (8 GPUs) can synthesize an average of 390 hours of simulation data per day, and the efficiency of the self-developed communication module has increased by more than 400%; the platform comes with built-in standardized task templates, and its visual workflow can adapt to more than 90% of target simulation scenarios with zero code. The Beijing News reported the same day that the platform has built-in standardized simulation task templates, through which users can launch simulations simply by selecting templates and configuring parameters, and that it supports real-time video streaming and task status monitoring; based on the self-developed Ulab-Agent, the platform uses natural language as its unified interaction entry point and can adapt to more than 90% of target simulation scenarios. No further developments have been disclosed at present.
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Nov 2
The Beijing News
UBTECH releases Thinker-Sim embodied intelligence simulation platform
UBTECH has officially released Thinker-Sim, an embodied intelligence simulation platform centered on Real2Sim2Real, covering digitization of real-world scenarios, large-scale synthetic simulation data, and robot capability evaluation. The platform comes with built-in standardized simulation task templates; users can launch simulations simply by selecting templates and configuring parameters, and it supports real-time video streaming and task status monitoring. Based on the self-developed Ulab-Agent, the platform uses natural language as a unified interaction entry point and can adapt to more than 90% of target simulation scenarios.
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Sina Tech
UBTECH Releases Thinker-Sim, an Embodied Intelligence Simulation Platform
UBTECH has released Thinker-Sim, an embodied intelligence simulation platform centered on Real2Sim2Real, covering the digitization of real-world scenarios, large-scale synthetic simulation data generation, and robot capability evaluation. The platform improves rendering efficiency by 67.3%, can synthesize an average of 390 hours of simulation data per day on a single node (8 GPUs), and its self-developed communication module improves efficiency by more than 400%. The platform comes with built-in standardized task templates, and its visual workflow can adapt to more than 90% of target simulation scenarios with zero code.
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