LingBot-Video: Embodied Video Foundation Model
aigclink · x · 2026-07-10
LingBot-Video is described as the first open-source MoE video foundation model designed for embodied AI. Instead of focusing on creative content quality, it reimagines video pre-training specifically for robotics, detailing how its architecture, data, and training are tailored for physical interaction and long-horizon modeling.
The model features 30B total parameters with only 3B activated per token. It incorporates 70,000 hours of embodied data and physics-based reward designs. It reportedly leads the public RBench leaderboard and can serve as a foundational component for action-conditioned video generation, data generation, and policy evaluation.
Related event: Ant Group Open-Sources LingBot-Video for Embodied AI(26 posts)→
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