• Marcbmann@lemmy.world
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    10 months ago

    I mean, I don’t think it’s an easy thing to fix. How do you eliminate bias in the training data without eliminating a substantial percentage of your training data. Which would significantly hinder performance.

    • bamboo@lemmy.blahaj.zone
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      10 months ago

      Rather than eliminating the some of the training data, you could add more training data to create an even balance.

      • kromem@lemmy.world
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        10 months ago

        Indeed - there’s a very good argument for using synthetic data to introduce diversity as long as you can avoid model collapse.