How agencies can use on-premises AI models to detect fraud faster, prove control effectiveness and turn overwhelming data ...

Database optimization has long relied on traditional methods that struggle with the complexities of modern data environments. These methods often fail to efficiently handle large-scale data, complex ...

Forbes contributors publish independent expert analyses and insights. Chief Analyst & CEO, NAND Research. In an era where artificial intelligence is reshaping industries, Oracle has once again ...

As agentic and RAG systems move into production, retrieval quality is emerging as a quiet failure point — one that can ...

The data inputs that enable modern search and recommendation systems were thought to be secure, but an algorithm developed by ...

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.

Over the years, the field of data engineering has seen significant changes and paradigm shifts driven by the phenomenal growth of data and by major technological advances such as cloud computing, data ...

Occasionally one may hear that a data model is “over-normalized,” but just what does that mean? Normalization is intended to analyze the functional dependencies across a set of data. The goal is to ...

MongoDB said additional partners and offerings are expected to be added to the startup program over time.

When developing machine learning models to find patterns in data, researchers across fields typically use separate data sets for model training and testing, which allows them to measure how well their ...