Chris Albon — ML Models and Infrastructure at Wikimedia
Gradient Dissent: Conversations on AI
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The Implications of Modeling
The team is the idea that any kind of ml that we do is not neutral at the end of the day. Our gold standard when we are making models is that the model reflects the training data from the particular community that is served by that model. So, like say train something on English Wikipedia and then apply it to, you know, Vietnamese Wikipedia by gathering the trainingdata from that original community and then serving back. It's not possible all the times, because some models have to be like you need to be global scalable there isn't like enough training data.
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