Materials research generates vast amounts of data, but the information often exists in manufacturer-specific formats and the terminology is inconsistent, making it difficult to aggregate, compare, and ...

Why today’s AI systems struggle with consistency, and how emerging world models aim to give machines a steady grasp of space ...

The project for which Hulsebos received the grant is called DataLibra, which runs from 2024 to 2029. Over those five years, ...

Two major milestones: finalizing my database choice and successfully running a local model for data extraction.

Overview: MongoDB continues to power modern applications, but analytics requires structured, reliable pipelines.ETL tools ...

For years, companies have been moving their most valuable customer data into countless different systems used by marketing, ...

The world tried to kill Andy off but he had to stay alive to to talk about what happened with databases in 2025.

A single server setup is where everything runs on one machine—your web application, database, cache, and all business logic.

Split your metadata from your files, and suddenly your sluggish document system becomes fast, scalable and surprisingly cheap to run. When I was tasked with modernizing our enterprise document ...

Document databases are an increasingly important type of technology in the gen AI era. A document database is a type of NoSQL database that doesn't rely on rows and columns like a traditional ...

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, ...

DataStax announced its acquisition by IBM is officially closed, allowing the companies to “scale to new heights” and accelerate production AI and NoSQL data at scale. With Langflow and watsonx.ai, ...