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 ...

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, ...

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 ...

Data modeling refers to the architecture that allows data analysis to use data in decision-making processes. A combined approach is needed to maximize data insights. While the terms data analysis and ...

Open-source tools have made MMM more accessible, but reliable results still depend on clean data, thoughtful modeling, and ...

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.

Nuance and Judgement are Needed for an AI Resilient Enterprise. While multi-modal AI can ingest vast amounts of data, it ...