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 ...

As agentic and RAG systems move into production, retrieval quality is emerging as a quiet failure point — one that can ...

MongoDB said additional partners and offerings are expected to be added to the startup program over time.

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 ...

Tabular foundation models are the next major unlock for AI adoption, especially in industries sitting on massive databases of ...

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 ...

Web3 is not just a shiny new buzzword. It is a shift in how value, data, and trust move around the internet. Instead of businesses acting as the central “middle […] ...

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 ...