CloudFactory Blog

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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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.

Mark Sears, founder and CEO, shares how CloudFactory will use its latest round of funding, a Series-C round led by FTV Capital.

Melody Ayeli, who reviews AI projects for Toyota’s CIO, shared insights on common AI failure points in a session at AI Summit in San Francisco.

Azavea's mission is to create advanced geospatial technology and research for civic and social impact. They interviewed a handful of leading data labeling firms, and studiously ...

When you have massive data to label for machine learning, it makes sense to outsource it. But what happens when your data is sensitive, protected, or private? Here’s a quick ...

Your choices about tooling and workforce will be important factors in your success as you design, test, validate, and deploy any ML model.

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.

Cloud workforce solutions and integrations with leading data labeling platforms support higher quality training data for machine learning.

AI is only as good as the data it's trained to analyze. CloudFactory CEO Mark Sears shares in Forbes about how AI bias can arise from people, tools, algorithms, and human ...

What is a data scientist and what do they do? Explore their roles, responsibilities, and contributions to AI and machine learning.

Learn how the operations team for a popular cash-back retail rewards app scaled speed and accuracy for a data-verification process during the busiest season of the year.