Machine learning’s impact on technology is significant, but it’s crucial to acknowledge the common issues of insufficient training and testing data.

Training data is a collection of examples that the model learns from to identify patterns and make predictions.

For those looking to get the most out of their AI system, synthetic data proves useful when real historical data is scarce, sensitive or difficult to obtain.

While training and testing in the real world will remain a crucial part of developing autonomous systems, the continued improvement of physics and graphics engine technology means that virtual worlds ...

Our understanding of progress in machine learning has been colored by flawed testing data. The 10 most cited AI data sets are riddled with label errors, according to a new study out of MIT, and it ...

Here’s a full rundown of what data poisoning means, the risks and how to prevent it in your organization. What Is Data Poisoning? Jennifer Glenn, research director for IDC’s security and trust group, ...