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 ...

The energy sector is becoming a highly connected cyber-physical ecosystem in which distributed energy resources, electric ...

Target built a generative AI system to improve marketing campaign forecasting by retrieving and ranking similar historical ...

Over 70 million people in the U.S. are impacted by hearing loss, and age-related hearing loss is the second most common ...

Image courtesy by QUE.com As we navigate the landscape of 2026, we find ourselves no longer merely using Machine Learning (ML) but ...

Legal AI tools have moved from novelty to necessity. Firms have signed contracts, run pilots, and rolled out generative AI assistants with ...

An employee pulls out a server rack shelf at the rear of a Trainium3 UltraServer at an Amazon Web Services QA lab in Austin, Texas, on February 3, 2026. Tech titan Amazon is working to step out of ...

One of the greatest weaknesses of AI agents that read and understand vast amounts of enterprise data is "hallucination"—the ...

Abstract: Relational machine learning studies methods for the statistical analysis of relational, or graph-structured, data. In this paper, we provide a review of how such statistical models can be ...

A systematic review newly published in the Journal of Pipeline Science and Engineering maps machine learning (ML) advances for pipelines across the full lifecycle: reliability-based design, structural ...

Abstract: The rise of graph-structured data has driven major advances in Graph Machine Learning (GML), where graph embeddings (GEs) map features from Knowledge Graphs (KGs) into vector spaces, ...

ABSTRACT: Cloud infrastructure anomalies cause significant downtime and financial losses (estimated at $2.5 M/hour for major services). Traditional anomaly detection methods fail to capture complex ...