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AI today rests on three pillars – ML algorithms, the hardware on which they’re run, and the data for training and testing the models. But obtaining high-quality up-to-date data at scale remains a challenge. One of the ways to resolve this is to adopt the data-centric approach to data labeling that entails building human-in-the-loop pipelines, i.e. hybrid pipelines that include both machine and human efforts. Crowdsourcing is an online activity where individuals perform tasks assigned on a platform that’s becoming more popular.
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