To feed the endless appetite of generative artificial intelligence (gen AI) for data, researchers have in recent years increasingly tried to create "synthetic" data, which is similar to the ...

Join the event trusted by enterprise leaders for nearly two decades. VB Transform brings together the people building real enterprise AI strategy. Learn more Shutterstock is reshaping how AI companies ...

The end goal of database design is to be able to transform a logical data model into an actual physical database. A logical data model is required before you can even begin to design a physical ...

Enterprises have spent the last 15 years moving information technology workloads from their data centers to the cloud. Could generative artificial intelligence be the catalyst that brings some of them ...

Artificial intelligence (AI) models—specifically, generative AI (GenAI) models—are becoming increasingly relevant for today’s businesses, yet many questions remain about how such models work and how ...

AI researchers at Google have developed VaultGemma, a small-scale AI model specially designed to prevent memorization and potential leakage of specific training data. With businesses using potentially ...

AI thrives on data but feeding it the right data is harder than it seems. As enterprises scale their AI initiatives, they face the challenge of managing diverse data pipelines, ensuring proximity to ...

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.

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 ...

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 ...