As AI systems evolve from assistants into autonomous collaborators, enterprises will need durable memory, explicit semantics, lineage, governance, and explainability. AllegroGraph and GraphTalker ...

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

Data storage systems have been refined over the years to provide a stable platform onto which organizations can dump their ...

Multiomics data integration with machine learning has become the standard approach for combining genomic, transcriptomic, proteomic, and metabolomic measurements collected from the same biological ...

AI models without strong business context risk costly errors, but vendor approaches to “context” vary. Enterprises must take ...

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 ...

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

Old Saybrook parents raised their concerns about the school district’s literacy rates with the Old Saybrook Board of ...