Avoid the Challenge of Achieving High-Quality Data

Avoid the Challenge of Achieving High-Quality Data

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

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Seeing the Big Picture with Your AI Data

Seeing the Big Picture with Your AI Data

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®.

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How to Solve the Specialization Challenge

How to Solve the Specialization Challenge

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

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What You Need to Know to Solve Your Data Puzzle

What You Need to Know to Solve Your Data Puzzle

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

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Seizing Your AI Opportunity Requires Quality Data and Partners

Seizing Your AI Opportunity Requires Quality Data and Partners

CloudFactory partner Scientia shares the AI opportunity and the importance of quality data for machine learning.

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CloudFactory Gets $65 Million on Mission to Create Meaningful Work for 1 Million People

CloudFactory Gets $65 Million on Mission to Create Meaningful Work for 1 Million People

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

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When and Why AI Projects Fail (And How to Avoid It)

When and Why AI Projects Fail (And How to Avoid It)

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.

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Azavea and CloudFactory: Partners on Quality Training Data and Social Impact

Azavea and CloudFactory: Partners on Quality Training Data and Social Impact

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 ...

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3 Ingredients for Scaling Quality Data Labeling for Machine Learning

3 Ingredients for Scaling Quality Data Labeling for Machine Learning

Gartner predicts 85% of AI projects will fail. One of the leading reasons is low-quality data labeling. High-performing machine learning algorithms require high-quality data. ...

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How to Take the Security Risk Out of Outsourcing Your Data Labeling

How to Take the Security Risk Out of Outsourcing Your Data Labeling

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 ...

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