Despite its dominance over the past three decades, model-centric AI has recently come under heavy criticism in favor of data-centric AI. Indeed, both promise to improve performance systems, yet with converse points focus. While former successively upgrades a devised model (algorithm/code), holding amount and type data used training fixed, latter enhances quality deployed continuously, paying le...
