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 ...

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 ...

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 ...

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 ...

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

The world is changing rapidly, and if businesses want to keep up, there is no alternative but to change with it. Customer behavior, market conditions, and the technological landscape are in a constant ...