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    Kled V3 is said to deploy custom data-collection tasks within 72 hours

    A user says labs can specify the data they need for collection by a network of 500,000-plus opt-in contributors.

    EL
    1 Source, 6h ago, first seen 6h ago

    TLDR

    A user says Kled V3 can deploy tasks to its network of 500,000-plus opt-in contributors within 72 hours. The post describes 108 configurable templates across image, video, audio, text and annotation, with contributors capturing examples on their phones. The user argues that repeatedly collecting examples where a model fails could help labs train and evaluate it again.

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    1 Source, first seen 6h ago

    Combined views

    8.1K

    1 Source, first seen 6h ago

    52 likes
    52 likes
    8 comments
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    8 comments
    19 saves

    Sentiment

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    1 Source

    @omarsar0You can't scrape a dataset that doesn't exist yet. Think about training a model on people performing a specific task, in a specific environment, from a specific camera angle. Someone has to go and capture those examples. This is what makes Kled V3 interesting. Labs can specify the data they need, and Kled can deploy collection tasks to its network of 500,000+ opt-in contributors within 72 hours. 108 configurable templates across image, video, audio, text, and annotation. Contributors capture the data on their phones, with instructions and examples of what qualifies. The opportunity here is a much tighter feedback loop: Identify where a model fails. Turn that failure into a collection task. Get new examples from the real world. Train and evaluate again. The ability to repeatedly collect the exact data a model is missing could be very powerful.6h

    1 Source

    @omarsar0You can't scrape a dataset that doesn't exist yet. Think about training a model on people performing a specific task, in a specific environment, from a specific camera angle. Someone has to go and capture those examples. This is what makes Kled V3 interesting. Labs can specify the data they need, and Kled can deploy collection tasks to its network of 500,000+ opt-in contributors within 72 hours. 108 configurable templates across image, video, audio, text, and annotation. Contributors capture the data on their phones, with instructions and examples of what qualifies. The opportunity here is a much tighter feedback loop: Identify where a model fails. Turn that failure into a collection task. Get new examples from the real world. Train and evaluate again. The ability to repeatedly collect the exact data a model is missing could be very powerful.6h