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 ...

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 ...

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

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 ...

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.

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 ...

Companies spent the last two years trying to get AI into production. Now, a different conversation is starting to happen ...

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 ...

AI R&D runs on a cycle of hypothesis, experiment, and analysis — each step demanding substantial manual engineering effort. A new framework from researchers at SII-GAIR aims to close that bottleneck ...