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

High-impact AI implementations are more likely to treat data architecture, governance, and operationalization as strategic requirements, according to TDWI's 2026 Blueprint report.

Excel's People Graph add-in turns simple tables into clean, icon-based visuals that automatically update when your data ...

This buzzy sleep system’s temperature regulation is transformative, but the privacy trade-offs and subscription costs are ...

General-purpose models struggle with messy, industry-specific data. A three-layer AI stack from Trunk Tools cut document ...

Part of the SD Times 100 2026 series. See the full SD Times 100 2026 list for every category and honoree. Every conversation ...

Researchers have developed AdapGNN, a novel model-agnostic framework that addresses the oversmoothing problem in graph neural ...

Roese's predictions: stronger AI governance, better data management, agentic AI infrastructure, resilient AI factories, and sovereign AI strategies.

Energy giant Schneider Electric is to acquire Cognite, an industrial data and AI software company, in an all-cash transaction ...

NUS researchers' MRAgent framework reduces LLM agent memory retrieval to 118K tokens per query — vs. 3.26M for LangMem — ...