AGIBOT's GO-3 Preview Model Achieves 85% Success Rate in Real-World Trials
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- InterestingEngineering.com
AGIBOT has introduced the GO-3 Preview, an embodied AI model that utilizes a World Reasoning Action Model (WRAM) architecture. This innovative model connects reasoning, prediction, and action generation, enabling robots to learn from human videos, simulations, and real-world experiences. The GO-3 Preview has achieved first place on three key embodied AI benchmarks: RoboDojo, RoboTwin, and RoboColiseum.
The significance of the GO-3 Preview lies in its ability to facilitate continuous learning and skill acquisition for robots, allowing them to adapt to new tasks and environments without extensive retraining. By leveraging diverse training data, including first-person human videos and robot trajectories, AGIBOT aims to enhance the model's learning capacity, enabling robots to perform complex activities with minimal demonstrations.
AGIBOT plans to open-source the complete GO-3 Preview model by the end of 2026, which will provide broader access to its advanced technology. This initiative is expected to foster innovation in the robotics field, as developers and researchers can utilize the model to enhance robotic capabilities across various applications.
Original report
Humanoid robot achieves 85% success rate in real-life trial with AGIBOT’s GO-3 model
InterestingEngineering.com · Jijo MalayilThis 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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