On February 10, Alibaba DAMO Academy formally launched its foundational embodied AI mind mannequin, RynnBrain, together with seven absolutely open-source fashions, together with a 30B MoE mannequin, spanning full-scale base fashions and fine-tuned proprietary fashions. Notably, this contains the business’s first 30B MoE embodied mannequin, considerably reducing the R&D threshold for the embodied intelligence sector and accelerating AI’s transition from digital simulations to bodily environments.
The core breakthrough of RynnBrain is its integration of spatiotemporal reminiscence and physical-space reasoning, addressing long-standing points in conventional embodied fashions equivalent to “forgetfulness” and “hallucinations.” Its spatiotemporal reminiscence permits robots to find objects in historic reminiscence, predict trajectories, and carry out international spatiotemporal retrospection. Bodily-space reasoning makes use of an interleaved technique combining textual and spatial cues, enabling reasoning processes that intently match real-world environments.
Technically, the mannequin is educated on Qwen3-VL and optimized with DAMO Academy’s self-developed RynnScale structure, reaching double the coaching velocity with the identical sources over a dataset of greater than 20 million pairs. Efficiency checks present that RynnBrain has set new data on 16 open-source embodied AI benchmarks, masking atmosphere notion, spatial reasoning, and extra, surpassing high business fashions like Gemini Robotics ER 1.5 and NVIDIA Cosmos Purpose 2.
Remarkably, the 30B MoE mannequin requires solely 3B inference-activated parameters to outperform present 72B fashions, enabling robots to maneuver quicker and extra easily. DAMO Academy additionally concurrently launched a brand new analysis benchmark, RynnBrain-Bench, addressing the dearth of fine-grained spatiotemporal embodied AI process benchmarks within the business.
Supply: CNMO
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