It takes a lot of time and resources to prepare and label data. Learn why outsourcing the data preparation to a managed workforce partner is a good business decision.

The level of data quality you'll receive from data labeling providers depends on several workforce, QA and tooling factors. Here are 6 ways some data labeling providers put your ...

The people, processes, and tools used by outsourced data labeling partners make a big difference in final data quality. Here are 3 signs that you'll receive quality work from your ...

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Data quality is clearly paramount for a successful AI project, but how difficult is it to achieve?

Achieving a high level of accuracy in data labeling is vital. This concept can be understood if we think about a mural of Rubik’s Cubes®.

Any problem (like a Rubik’s cube®) is solvable with a documented process.

How solving a Rubik’s cube® is like labeling your unstructured data.

Deep learning platform MissingLink and the MIT Media Lab brought together AI innovators in Boston last month for a meetup about how AI is changing the world for the better.

Crowdsourcing seems to offer a cheap option for training machine learning models, but it’s rarely as inexpensive as it seems. Here are some of the hidden costs of the crowd.