Context graphs, graph memory, and ontologies for AI are converging. What does this mean for enterprise AI in 2026?

A privacy-preserving marketing framework applies homomorphic encryption to perform machine learning on encrypted ...

The premise is straightforward — we are awash in biological data. The rapid growth of multiomics datasets (genomics, transcriptomics, proteomics, metabolomics, and radiomics) together with ...

AI agents are your new colleagues - how to get the best results ...

A framework for analyzing single-cell genomics data, in which geometrical properties are harnessed to obtain insights on cellular diversity, including precise clustering, clear visualizations, and ...

A researcher at the Museum of Natural Sciences is using volunteer scientists to probe the universe for a mysterious type of ...

Solutions, a leading software company that is powering enterprise planning and decisioning models across 30-plus industry verticals with its groundbreaking Digital Brain platform, today announced the ...

Solving complex optimization problems is central to many modern technologies, from logistics and financial modeling to chip ...

To capture the world's incredibly faint light, an international research team led by Aneesh Baburaj, a postdoctoral associate ...

A systematic review newly published in the Journal of Pipeline Science and Engineering maps machine learning (ML) advances for pipelines across the full lifecycle: reliability-based design, structural ...