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 shift toward AI-driven decision frameworks is not simply a technological trend but a fundamental necessity for life ...

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 ...

A team of computer scientists at UC Riverside has developed a method to erase private and copyrighted data from artificial intelligence models—without needing access to the original training data.

The AI industry stands at an inflection point. While the previous era pursued larger models—GPT-3's 175 billion parameters to PaLM's 540 billion—focus has shifted toward efficiency and economic ...

After two years of maxxing out on AI tools, many organizations are confronting an uncomfortable reality: AI costs don't scale linearly with adoption.

This article is part of a VB Lab Insights series paid for by Capital One. For cloud-based companies, the ability to leverage nearly unlimited amounts of data can unlock possibilities that lead to more ...

Artificial intelligence (AI) is playing a huge role in heat rate optimization. In some cases, AI-driven models have analyzed operational data to recommend control settings that reduce heat rates by ...

Chances are, you’ve seen clicks to your website from organic search results decline since about May 2024—when AI Overviews launched. Large language model optimization (LLMO), a set of tactics for ...

LLM training data mixture optimization breaks when training pools shift — every prior proxy experiment becomes stale.