One of the biggest risks to any AI tool is data integrity. Cybersecurity is built on the CIA triad of confidentiality, ...

When designing an effective enterprise data strategy, organizations often choose between a top-down and a bottom-up approach. Each method has its unique advantages and is suitable for various ...

When AI models fail to meet expectations, the first instinct may be to blame the algorithm. But the real culprit is often the data—specifically, how it’s labeled. Better data annotation—more accurate, ...

Want smarter insights in your inbox? Sign up for our weekly newsletters to get only what matters to enterprise AI, data, and security leaders. Subscribe Now Data mesh is a hot topic in the data and ...

Google is turning its vast public data trove into a goldmine for AI with the debut of the Data Commons Model Context Protocol ...

At its heart, data modeling is about understanding how data flows through a system. Just as a map can help us understand a city’s layout, data modeling can help us understand the complexities of a ...

A new kind of large language model, developed by researchers at the Allen Institute for AI (Ai2), makes it possible to control how training data is used even after a model has been built.

Sparse data can impact the effectiveness of machine learning models. As students and experts alike experiment with diverse datasets, sparse data poses a challenge. The Leeds Master’s in Business ...

Last fall, after playing around with OpenAI’s GPT-3 text-generating AI model — the predecessor to GPT-4 — former Uber research scientist Jerry Liu discovered what he describes as “limitations” around ...

Actionable product demand and usage feedback must find its way back to portfolio managers for continuous portfolio optimization to occur. Morningstar provides a framework and measurement for matching ...

LinkedIn will use member data to train AI models from Nov 3, 2025, with settings on by default. Users must manually opt out ...