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

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

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

For financial institutions, threat modeling must shift away from diagrams focused purely on code to a life cycle view ...

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 ...

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 ...

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 ...

AI promises a smarter, faster, more efficient future, but beneath that optimism lies a quiet problem that’s getting worse: the data itself. We talk a lot about algorithms, but not enough about the ...

Sophie Bushwick: To train a large artificial intelligence model, you need lots of text and images created by actual humans. As the AI boom continues, it's becoming clearer that some of this data is ...

The tool, called Nightshade, messes up training data in ways that could cause serious damage to image-generating AI models. A new tool lets artists add invisible changes to the pixels in their art ...