Robbyant Upgrades and Open-Sources LingBot-VLA 2.0 as a Next-Generation Universal Brain for Embodied AI>

(BUSINESS WIRE) -- Robbyant, an embodied AI company within Ant Group, today announced the upgrade and open-source release of LingBot-VLA 2.0. Building upon the foundation of LingBot-VLA 1.0 released in January 2026, this next-generation vision-language-action (VLA) model delivers significant leaps in morphological generalization, degrees of freedom (DoF) support, and deployment efficiency, delivering a more advanced “universal brain” for scalable real-world robotics. While the embodied AI industry is witnessing rapid advancements in hardware and control systems, the lack of a truly universal brain remains a primary bottleneck for industrial-scale deployment. LingBot-VLA 2.0 addresses this critical gap by dramatically expanding its pre-training data and architectural capabilities. LingBot-VLA 2.0 was pre-trained on 60,000 hours of high-quality, real-world physical data. This massive dataset was curated from 50,000 hours of cleaned real-robot interaction data and 10,000 hours of distilled first-person human manipulation data. Sourced from 20 distinct robot morphologies across 17 leading manufacturers—including Leju, AgiBot, Unitree, AgileX, Galaxea, Galbot,...(BUSINESS WIRE) -- Robbyant, an embodied AI company within Ant Group, today announced the upgrade and open-source release of LingBot-VLA 2.0. Building upon the foundation of LingBot-VLA 1.0 released in January 2026, this next-generation vision-language-action (VLA) model delivers significant leaps in morphological generalization, degrees of freedom (DoF) support, and deployment efficiency, delivering a more advanced “universal brain” for scalable real-world robotics. While the embodied AI industry is witnessing rapid advancements in hardware and control systems, the lack of a truly universal brain remains a primary bottleneck for industrial-scale deployment. LingBot-VLA 2.0 addresses this critical gap by dramatically expanding its pre-training data and architectural capabilities. LingBot-VLA 2.0 was pre-trained on 60,000 hours of high-quality, real-world physical data. This massive dataset was curated from 50,000 hours of cleaned real-robot interaction data and 10,000 hours of distilled first-person human manipulation data. Sourced from 20 distinct robot morphologies across 17 leading manufacturers—including Leju, AgiBot, Unitree, AgileX, Galaxea, Galbot,...{}