That admission is what some in the field call recursive self-improvement (RSI), the point at which large language models ...

GraphRAG explains why AI is shifting from isolated text to connected knowledge, and what that means for AI search optimization. Making your brand machine-readable and increasing its chances of being ...

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

Your vault has a graph. But you can only stare at it. Obsidian's graph view is beautiful, but it can't answer questions — "Which notes have the most links?" "How many hops between these two concepts?" ...

Abstract: In several applications the information is naturally represented by graphs. Traditional approaches cope with graphical data structures using a preprocessing phase which transforms the graphs ...

Abstract: Graph neural networks (GNNs) have recently emerged as a promising approach for solving few-shot learning (FSL) problems, enabling generalization to new categories by establishing ...