High-Quality Data — Challenge Accepted

High-Quality Data — Challenge Accepted

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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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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The 3 Hidden Costs of Crowdsourcing for Data Labeling

The 3 Hidden Costs of Crowdsourcing for Data Labeling

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.

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Global Partnerships Reflect AI’s Immense Power and Potential Risks

Global Partnerships Reflect AI’s Immense Power and Potential Risks

Realizing AI’s potential benefits - and mitigating its challenges - will require collaboration. As partnerships form and critical questions arise across the globe in government, ...

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Scaling Quality Training Data: The Hidden Costs of the Crowd

Scaling Quality Training Data: The Hidden Costs of the Crowd

Anonymous crowdsourcing is a common alternative to an in-house team for AI development. It can be a cheap option for training machine learning algorithms but it’s rarely as ...

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3 Steps Toward Data Responsibility in the Digital Age

3 Steps Toward Data Responsibility in the Digital Age

Even before the Facebook–Cambridge Analytica story broke, the World Economic Forum proposed the need for a new era of data responsibility. Here’s how we can contribute to a world ...

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