
Operationalize “Winning The Race” With Results You Can Measure
The Training Data Project
America just took a bold, long-overdue step on AI. The Trump Administration’s Winning the Race: America’s AI Action Plan treats AI as a strategic national asset and sets a practical agenda to innovate, build, and lead...
…READ MORE

A New Day for The Training Data Project: Proof Is the Next Power
Dave Cook
When we launched the Training Data Project website in April 2024, we had no idea how quickly things would take off. Since then, we have worked with and spoken to more groups across industry...
…READ MORE

Roles and Responsibilities in Advancing Public AI: A Multi-Stakeholder Approach
Training Data Project
The landscape of artificial intelligence (AI) development is rapidly evolving, presenting both unprecedented opportunities and challenges for society. As AI becomes increasingly integrated into various aspects...
…READ MORE

The Case for Public AI: Why We Need Alternatives to Commercial AI Development
Training Data Project
Artificial Intelligence (AI) has rapidly become a transformative force in our society, reshaping industries, economies, and daily life. However, the current AI landscape is predominantly driven by commercial interests...
…READ MORE

How AI Regulation Will Impact Businesses and Innovation
The Training Data Project
AI regulation is set to change how businesses innovate and operate. What do these regulations entail, and why are they important now? In this article, we break down the necessity for AI regulation, explore risk-level classifications, and discuss...
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The Importance of Data Labeling: Methods, Uses, and Challenges
The Training Data Project
Data labeling tags raw data with meaningful labels, creating high-quality training data for machine learning models. It’s crucial because model accuracy depends on data quality. This article covers data labeling methods, uses in different industries...
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Where the Bullet Holes Aren’t: Measuring AI’s Real Impact
The Training Data Project
The New York Times recently revisited a problem that has surfaced with nearly every wave of new technology: massive investment without clear returns. In the 1980s, economists called it the productivity paradox. Despite billions spent on personal computers...
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Operationalize “Winning The Race” With Results You Can Measure
The Training Data Project
America just took a bold, long-overdue step on AI. The Trump Administration’s Winning the Race: America’s AI Action Plan treats AI as a strategic national asset and sets a practical agenda to innovate, build, and lead...
…READ MORE

A New Day for The Training Data Project: Proof Is the Next Power
Dave Cook
When we launched the Training Data Project website in April 2024, we had no idea how quickly things would take off. Since then, we have worked with and spoken to more groups across industry...
…READ MORE

Roles and Responsibilities in Advancing Public AI: A Multi-Stakeholder Approach
Training Data Project
The landscape of artificial intelligence (AI) development is rapidly evolving, presenting both unprecedented opportunities and challenges for society. As AI becomes increasingly integrated into various aspects...
…READ MORE

The Case for Public AI: Why We Need Alternatives to Commercial AI Development
Training Data Project
Artificial Intelligence (AI) has rapidly become a transformative force in our society, reshaping industries, economies, and daily life. However, the current AI landscape is predominantly driven by commercial interests...
…READ MORE

How AI Regulation Will Impact Businesses and Innovation
The Training Data Project
AI regulation is set to change how businesses innovate and operate. What do these regulations entail, and why are they important now? In this article, we break down the necessity for AI regulation, explore risk-level classifications, and discuss...
…READ MORE
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