Industry Briefing
A single destination for timely, editor-curated robotics news from around the world.
Robbyant Launches LingBot-World 2.0 with Enhanced Real-Time World Generation Features
Robbyant, an embodied AI company under Ant Group, has released LingBot-World 2.0, an open-source interactive world model. This updated version supports hour-long real-time world generation, high-definition output, and enhanced interactive capabilities, marking a significant improvement over LingBot-World 1.0. The new model allows for continuous world generation sessions while maintaining visual quality and enabling real-time user interaction. It produces 720p video at 60 frames per second and is designed to generate, stream, and display content simultaneously, which reduces latency and enhances user engagement with the evolving environment. LingBot-World 2.0 features a dual-agent mechanism for dynamic interaction and supports multiple users in a shared virtual space. Additionally, Robbyant has open-sourced LingBot-Video, a video generation model aimed at robotics applications, which enhances efficiency and realism in AI-generated video for real-world robotic systems. No further timeline was disclosed at the time of publication.
Robot simulation AI models ai simulation Ant Group artificial intelligence embodied ai
Robbyant Launches LingBot-VA 2.0, the First Embodied-Native AI Model for Robotics
Robbyant, a company under China's Ant Group, has introduced LingBot-VA 2.0, touted as the first embodied-native video-action world model specifically designed for robotics. Unlike traditional models adapted from digital content, LingBot-VA 2.0 is built from the ground up for physical-world tasks, enhancing physical accuracy and execution efficiency through its autoregressive architecture. This innovation is significant as it marks a departure from conventional robotics models that often compromise real-world performance by relying on video generation systems. Robbyant's approach allows for better prediction of how robot actions affect their environment, thus improving generalization and operational effectiveness in real-world applications. Looking ahead, Robbyant's LingBot-VA 2.0 is expected to advance the capabilities of robots in various tasks, demonstrated through its performance in complex scenarios such as preparing breakfast and unpacking deliveries. No further timeline was disclosed at the time of publication.
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