Is Poorly Labelled Data the Culprit for Failed AI Projects?


In this talk we will examine the key phases on AI solution development and the critical aspects of humans in the loop (HITL) to ensure their success. From data cleansing to annotation to quality control, HITL has been shown to improve ML/AI project quality, while improving efficiency and accelerating time to value across multiple industries, including finance, retail, agriculture and more. We will share how the right combination of people and technology can be effectively paired with insight from an experienced CloudFactory tooling partner, and share an actual use case of this having been applied to a recent medical AI project.


Ulrik Stig Hansen is the co-founder and CEO of Encord, a London-based computer vision training data platform. The company’s platform is used by businesses to make unstructured data readable by machines. Its tools include data annotation, evaluation, and management of training data.

Open Data Science




Open Data Science
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Cambridge, MA 02142

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