Data Annotation in AI


The booming of data annotation market has stimulated multiple novel players to secure a niche position in the competition. For example, Playment, a data labeling platform for AI, has teamed up with Ouster, a leading LiDAR sensors provider, for annotation and calibration of 3D imagery captured by its sensors in 2018., a data labeling platform, has innovated the industry through its robust tools for real-time workflow management. On ByteBridge’s platform, developers can define and start the data labeling projects and get the results back instantly. It not only improves the efficiency dramatically but also allows clients to customize their task based on their needs. As a fully-managed platform, it enables developers to manage and monitor the overall data labeling process and provides API for data transfer. The platform also allows users to audit the data quality.

Typically, data annotation workers log on to Amazon’s Mechanical Turk or gig-work platforms from data annotation companies like Appen. There they perform tasks contracted out by AI firms that pay the platforms slivers of a cent per minute. In the cutthroat competition for business, these platforms compete on scale, speed, and cost. Appen, for example, boasts a pool of one million contractors who perform tasks such as categorizing medical images or translating text for chatbots.

Appen operates two divisions called Content Relevance and Language Resources. Post Leapforce acquisition, Content Relevance now generates the bulk of revenues. The unit helps improve search engine relevance algorithms with training data and by evaluating specific search results, entire search engine result pages, multimedia, maps, and news functions. Major clients include Google and Microsoft.


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