Even as large language models have been making a splash with ChatGPT and its competitors, another incoming AI wave has been quietly emerging: large database models. Even as large language models have ...

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, ...

The team's SynthSmith data pipeline develops a coding model that overcomes scarcity of real-world data to improve AI models ...

1. The "quarantine" pattern is mandatory: In many modern data organizations, engineers favor the "ELT" approach. They dump raw data into a lake and clean it up later. For AI Agents, this is ...

How agencies can use on-premises AI models to detect fraud faster, prove control effectiveness and turn overwhelming data ...

Distributed database consistency models form the backbone of reliable and high-performance systems in today’s interconnected digital landscape. These models define the guarantees provided by a ...

When developing machine learning models to find patterns in data, researchers across fields typically use separate data sets for model training and testing, which allows them to measure how well their ...

Artificial intelligence (AI) is transforming a variety of industries, including finance, manufacturing, advertising, and healthcare. IDC predicts global spending on AI will exceed $300 billion by 2026 ...

Researchers at Los Alamos National Laboratory have developed a new approach that addresses the limitations of generative AI models. Unlike generative diffusion models, the team's Discrete Spatial ...

Last month, destructive wildfires blazed across Maui, Hawaii, killing at least 100 individuals and destroying some 3,200 acres of land. Residents critici zed government leaders, especially those ...