AGIBOT Launches GO-3 Preview, Achieving Top Rankings in Embodied AI Benchmarks
- Published
AGIBOT has introduced GO-3 Preview, an embodied foundation model that enhances robots' learning capabilities throughout their lifecycle, from pre-training to post-deployment. This model has achieved first-place rankings on three significant embodied AI benchmarks: RoboDojo, RoboTwin, and RoboColiseum, and is set to be fully open-sourced by the end of 2026.
The importance of GO-3 Preview lies in its ability to unify task understanding, future-state prediction, and action generation, enabling robots to generalize across various tasks and perform precise manipulations. This model, built on AGIBOT's proprietary WRAM architecture, is part of a broader integrated learning system that includes Genie Evolver and Genie Master, aimed at fostering continuous improvement through real-world interactions.
AGIBOT's approach emphasizes the need for robots to learn not only during pre-training but also through post-training interactions and after deployment. This principle is crucial for tasks requiring adaptability, such as grasping objects in diverse environments. No further timeline was disclosed at the time of publication.
Original report
AGIBOT unveils GO-3 Preview and takes top spot on three embodied AI benchmarks
RoboticsAndAutomationNews.com · Abdul MontaqimThis briefing is an independently written summary based on publicly available reporting and is provided for industry information and news discovery. The original report and source publication are credited and linked where applicable. RobotToday does not claim ownership of third-party source material.
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