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

General-purpose models struggle with messy, industry-specific data. A three-layer AI stack from Trunk Tools cut document review cycles from 60 days to 10.

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

Rigorous study of 2,900+ startups shows AI native firms are different. It gives executives strategic ideas for innovation & ...

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 ...

Generic messaging, awkward over-familiarities, convoluted messaging — aggressive sales pitches never seem to end. But, ...

A new big-data analysis of the U.S. pinpoints how urban design aids the health of city residents—especially when cities provide walking opportunities, greenery and mixed-use streets with a blend of ...

Workers who handle graphene as a dry powder can be exposed to airborne concentrations far above any proposed safety benchmark ...

GraphRAG explains why AI is shifting from isolated text to connected knowledge, and what that means for AI search ...

AMD's new FSR 4.1 INT8 upscaler gives RDNA 3 GPUs a massive image quality upgrade. We examine visual quality, performance, ...

Gemini personalized image generation is now free for US users, pulling data from Gmail, Photos, and YouTube to tailor results ...

A major driver of age-related health decline is inflammation. Inflammation is our immune system’s response to injury, ...