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Amap Releases λ0 Whole-Body Model Trained on Human Actions

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Amap released λ0, a whole-body foundation model trained on human action data to learn coordinated movement, posture, and two-handed manipulation, and reported zero-shot transfer across 7 real-robot tasks. In an Amap-provided report republished by QbitAI, the team said its wearable data collection pipeline improved collection efficiency by approximately 3.4x and that λ0 improved real-robot task success by 22.5% over the strongest comparison baseline. The team built the 500-hour HumanVerse-500 dataset; hardware configuration code and sample data are available on GitHub and Hugging Face.

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Latest development10/23 16:40 (UTC+8)
Amap releases λ0, a whole-body foundation model trained on human actions量子位

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10/23
  1. 量子位
    Amap releases λ0, a whole-body foundation model trained on human actions

    Amap announced λ0, a whole-body foundation model that learns coordinated movement, posture, and two-handed manipulation from human action data. According to the Amap-provided report republished by QbitAI, its wearable collection pipeline improves data collection efficiency by approximately 3.4x, while real-robot task success improves by 22.5% over the strongest comparison baseline. The team built the 500-hour HumanVerse-500 dataset and reports zero-shot transfer across 7 real-robot tasks; hardware configuration code and sample data are available on GitHub and Hugging Face.

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