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从模型到生产力:星海图与产业朋友圈共探具身智能的下一站

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Merged summary

TL;DR - Xinghaitu announced upgrades spanning embodied foundation models, distributed robot learning infrastructure, and three production-oriented robot platforms. The releases target the transition from laboratory prototypes to continuously improving, commercially deployed robotic systems.

  • The forthcoming G0.5 MAX builds on G0.5’s unified autoregressive pipeline for visual perception, language, reasoning, and action generation; Xinghaitu also launched a reproduction program providing weights, inference APIs, benchmarks, and fine-tuning tools.
  • Fast-WAM avoids generating future video during inference, reportedly reducing single-step latency from roughly 800 ms to 190 ms; a pretrained model based on the architecture is planned.
  • The new G-Fleet system supports fleet-wide policy deployment, parallel physical rollouts, human correction, distributed reinforcement learning, evaluation, and model releases in a continuous real-world learning loop.
  • Xinghaitu presented the Nexo wheeled dual-arm robot, Kengo biped, and Lemo desktop platform, and reported orders totaling thousands of model-driven robots, with a target of more than 10,000 deliveries next year.

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从模型到生产力:星海图与产业朋友圈共探具身智能的下一站

量子位 henry 2026-08-22
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Providers: Hugging Face · N/A OpenAlex · N/A Publisher · N/A Semantic Scholar · N/A X · N/A Fetched 2026-09-21 14:33:27.584358 UTC

TL;DR - Xinghaitu announced upgrades spanning embodied foundation models, distributed robot learning infrastructure, and three production-oriented robot platforms. The releases target the transition from laboratory prototypes to continuously improving, commercially deployed robotic systems.

  • The forthcoming G0.5 MAX builds on G0.5’s unified autoregressive pipeline for visual perception, language, reasoning, and action generation; Xinghaitu also launched a reproduction program providing weights, inference APIs, benchmarks, and fine-tuning tools.
  • Fast-WAM avoids generating future video during inference, reportedly reducing single-step latency from roughly 800 ms to 190 ms; a pretrained model based on the architecture is planned.
  • The new G-Fleet system supports fleet-wide policy deployment, parallel physical rollouts, human correction, distributed reinforcement learning, evaluation, and model releases in a continuous real-world learning loop.
  • Xinghaitu presented the Nexo wheeled dual-arm robot, Kengo biped, and Lemo desktop platform, and reported orders totaling thousands of model-driven robots, with a target of more than 10,000 deliveries next year.
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