Data-labelling startups want to help improve corporate AI

“Because human data-labelling is labour-intensive, most of it happens in low-wage countries like India, Vietnam and the Philippines” writes The Economist for Data-labelling is the sort of grunt work that corporate -users would prefer someone else to do for them.The market for data-labelling services may triple to $5bn by 2023, reckons Astasia Myers of Redpoint Ventures, a venture-capital firm.Hive has turned data-labelling into something “like playing Candy Crush”, explains its boss, Kevin Guo, referring to a hit tile-matching game.One reason for the slow uptake is the dearth of quality data to teach algorithms to perform useful tasks.

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