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Chinese robotics — Dataset and collection discovery·· 1 days agoSignalEditorial score88

NVIDIA Open Sources Robot Data Engine Flora, Annotation Cost is 1/125 of GPT-6 Astra

一天能肝20万小时机器人数据,英伟达最新开源数据引擎Flora,成本是GPT-6 Astra零头

Summary

NVIDIA has released and open-sourced the robot data engine Flora, which transforms large volumes of robot video into high-quality training data through the collaboration of three models. Flora performs exceptionally well in multiple benchmark tests, achieving an annotation quality score of 57.1% and an estimated cost of $0.72 per hour of source video, which is only 1/125 of GPT-6 Astra's cost.

Editorial context

NVIDIA's Flora data engine demonstrates significant efficiency improvements over GPT-6 Astra in both cost and performance, achieving comparable results in benchmark tests while reducing annotation costs by 125 times.

Source: Chinese robotics — Dataset and collection discovery · Read original article ↗

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What the source reports

Publisher-reported claims, with original evidence. These results have not been independently verified by RoboSignal.

Reported numbers

  • data annotation hours per day

    200,000 hours

    View original evidence
    目前,该数据引擎依托 512块GB300 GPU, 每天可标注 20万小时的数据。
    Open source S8
  • cost per hour of source video

    0.72

    View original evidence
    具体来看,Flora的标注质量得分为 57.1% ,估算成本为 每小时源视频0.72美元; GPT-6 Astra的标注质量得分为 53.7%, 估算成本为每小时源视频 88.49美元。
    Open source S7
  • cost per hour of source video

    88.49

    View original evidence
    具体来看,Flora的标注质量得分为 57.1% ,估算成本为 每小时源视频0.72美元; GPT-6 Astra的标注质量得分为 53.7%, 估算成本为每小时源视频 88.49美元。
    Open source S7
  • Reported accuracy

    64.7%

    View original evidence
    同时,使用公开的纯文本动作描述评分标准,联合匹配则要求预测的动作时间区间,和动作描述均与标注结果相符 Flora的平均分段F1为 50.3%, 平均联合F1为 34.5%, 在人工标注参考区间上的动作描述准确率为 64.7%。
    Open source S22
  • paper: not_reported
  • code: not_reported
  • weights: not_reported
  • dataset: not_reported

What remains unknown

Not established in the collected evidence: Environment, Control, Data origin.

Reported performance applies to the described task. It does not establish general autonomy or deployment readiness.

Source excerpts and review record

Automatically extracted; no manual editorial approval recorded.

目前,该数据引擎依托 512块GB300 GPU, 每天可标注 20万小时的数据。

Open source S8

具体来看,Flora的标注质量得分为 57.1% ,估算成本为 每小时源视频0.72美元; GPT-6 Astra的标注质量得分为 53.7%, 估算成本为每小时源视频 88.49美元。

Open source S7

同时,使用公开的纯文本动作描述评分标准,联合匹配则要求预测的动作时间区间,和动作描述均与标注结果相符 Flora的平均分段F1为 50.3%, 平均联合F1为 34.5%, 在人工标注参考区间上的动作描述准确率为 64.7%。

Open source S22

Source:Chinese robotics — Dataset and collection discovery · tech.ifeng.com

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