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给机器人当老师,还能赚外快?“中国版Index”觅蜂派来了

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Merged summary

TL;DR - Mifeng Technology launched Mifeng Pai, a crowdsourced platform that pays people to collect real-world human activity data for training robots. Its integrated capture hardware, data-processing engine, and contributor network aim to address embodied AI’s growing need for diverse, large-scale training data.

  • Mifeng says 20,000 MEgo wearable or gripper-based devices have collected over one million hours of data across 22 scenario categories, including images, depth, motion, touch, and audio.
  • Its MEgo Engine reconstructs hand, body, device, and environment motion; the company claims sub-centimeter trajectory errors and reliable hand reconstruction even under severe occlusion.
  • The ManiEval system grades rather than indiscriminately discards compliant data, matching precise demonstrations, failures, rare cases, and semantically rich recordings to different training and evaluation uses.
  • Contributors receive equipment and payment for approved collection tasks; a pre-launch trial reportedly attracted 20,000 users and 13,000 submissions, while the resulting data is already serving customers including Tencent Robotics X and Ant Lingbo.

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给机器人当老师,还能赚外快?“中国版Index”觅蜂派来了

量子位 林, 方舟 2026-09-25
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Providers: Hugging Face · N/A OpenAlex · N/A Publisher · N/A Semantic Scholar · N/A X · N/A Fetched 2026-09-26 14:13:42.673004 UTC

TL;DR - Mifeng Technology launched Mifeng Pai, a crowdsourced platform that pays people to collect real-world human activity data for training robots. Its integrated capture hardware, data-processing engine, and contributor network aim to address embodied AI’s growing need for diverse, large-scale training data.

  • Mifeng says 20,000 MEgo wearable or gripper-based devices have collected over one million hours of data across 22 scenario categories, including images, depth, motion, touch, and audio.
  • Its MEgo Engine reconstructs hand, body, device, and environment motion; the company claims sub-centimeter trajectory errors and reliable hand reconstruction even under severe occlusion.
  • The ManiEval system grades rather than indiscriminately discards compliant data, matching precise demonstrations, failures, rare cases, and semantically rich recordings to different training and evaluation uses.
  • Contributors receive equipment and payment for approved collection tasks; a pre-launch trial reportedly attracted 20,000 users and 13,000 submissions, while the resulting data is already serving customers including Tencent Robotics X and Ant Lingbo.
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