A novel approach from the Allen Institute for AI enables data to be removed from an artificial intelligence model even after ...

Merit is making its Scholars program widely available. It's a team of experts to fine-tune generative AI models for ...

Efforts to remove, restructure, or completely eliminate public health information from federal websites undermine the ...

One of the most significant risks of poor data quality is bias. If an AI model is trained on incomplete, inconsistent or skewed data, it will replicate and even amplify those biases.

Poor data sabotages AI and strategy despite significant investments. Leaders must act now to build trust and unlock real value.

We talk to Cody David of Syniti about how to ensure data quality in datasets for AI, why a ‘data-first’ attitude is key, and the quick wins an organisation can gain in data quality.

In the hunt for authentic data to train the AI, your corporate data IP is next. As a result, data quality and authenticity will become highly valued - and the demand to prove provenance will soar.

Artificial intelligence startup Kolena Inc. is moving beyond AI model testing and quality control with the launch of its new flagship platform, Restructured. The company says its goal is to help ...

Data governance, data integrity, and data quality are all widely used terms, but what do they actually mean and how are they connected? The purpose of this article is to provide a structured model for ...

This episode of Need to Know covers the importance of data quality and its implications for firms' decision making.