As an emerging technology in the field of artificial intelligence (AI), graph neural networks (GNNs) are deep learning models ...
A decentralized cloud security framework uses attribute-based encryption to enable fine-grained access control without centralized vulnerabilities. By combining cryptographic policy enforcement, third ...
Aiomics announces the integration of a Hybrid GraphRAG engine into its clinical platform. By anchoring artificial ...
Keyrus, a global consulting firm specializing in data strategy, artificial intelligence and digital transformation with nearly three decades ...
Knowledge Graph, Large Language Model, BERT, Knowledge Management, Small and Medium-Sized Enterprises, Accounting, Supply Chain Management Zheng, Y. (2026) Knowledge Graph Application in KM for ...
Explore the 2026 AI trends in India, including the transition from experimental AI to scalable applications, the evolving ...
Discover what context graphs are, why they're revolutionizing AI systems, and who's building this trillion-dollar technology that transforms how machines understand relationships and reasoning.
Knowledge graphs are a powerful tool for bringing together information from biological databases and linking what is already known about genes, diseases, treatments, molecular pathways and symptoms in ...
Abstract: Knowledge graphs (KGs), representing multi-relational data as a semantic graph from structured information stored in triples, have attracted wide attention in industrial and academic ...
Abstract: Large Language Models (LLMs) excel at general-purpose reasoning by leveraging broad commonsense knowledge, but they remain limited in tasks requiring personalized reasoning over ...
AI agent fervor has permeated the software development world. But, we’re no longer talking about a singular, all-knowing AI. Rather, emerging agentic workflows rely on multiple specialized agents ...
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