AI success depends on whether enterprise data is ready, reachable, and close enough to the workloads that need it. In this eSpeaks episode, Dell Technologies’ Vrashank Jain explains why fragmented ...

The AI lifecycle is an iterative, end-to-end process of planning, developing, deploying, monitoring, and retiring artificial intelligence systems. Unlike traditional software development, it is ...

Most projects benefit from having a data model. This article gives an overview of the most common types. At its heart, data modeling is about understanding how data flows through a system. Just as a ...

So-called “unlearning” techniques are used to make a generative AI model forget specific and undesirable info it picked up from training data, like sensitive private data or copyrighted material. But ...