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

It’s a sunny spring morning and the Grade 9 math students at Milton District High School, in the Halton District School Board, just west of Toronto, are seated in straight rows facing the blackboard.

In the minds of many people, math lives in the classroom—on blackboards, in textbooks, and in tests. New research from Amber Simpson, associate professor in the Department of Teaching, Learning, and ...

A monthly overview of things you need to know as an architect or aspiring architect. Unlock the full InfoQ experience by logging in! Stay updated with your favorite authors and topics, engage with ...

In this video I will help you explore how to use the properties of logarithms to simplify an exponential expression Why do students still make this mistake with logs Exponential and Logarithmic ...

Conclusions: This study represents a pioneering effort in using LLMs, particularly GPT-4.0, to construct a comprehensive sepsis knowledge graph. The innovative application of prompt engineering, ...

Abstract: In the graph signal processing (GSP) literature, graph Laplacian regularizer (GLR) was used for signal restoration to promote piecewise smooth / constant reconstruction with respect to an ...

Abstract: This article presents a graph theory-informed approach to state estimation-based model selection for identifying the operational topology of a power distribution system. The proposed method ...