Google’s Open Knowledge Format Could Work For Websites, Too

Markdown has been readable by machines since 2004. OKF adds structure and relationships. Together, they're the foundation ...
KMWorld

2026 The KMWorld AI 100: The Impact of AI on KM is Inescapable

While AI holds the promise of radically transforming KM, human oversight takes on intensified responsibilities for ensuring the knowledge provided is accurate, timely, and relevant as well as guarding ...
Search Engine Land

GraphRAG: What entity-first retrieval means for SEO

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 ...
HackerNoon

The Race to Build AI’s Context Layer Is Really About Meaning

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

Cochlea network model reveals how inner ear may sort sound from noise

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

Yehey.com - Machine Learning in 2026: Building the Future of Intelligent Systems

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

Why Many Legal AI Tools Fail to Deliver ROI (And How to Fix It)

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

Enterprise AI Agent Security Gets New Architecture: AWS Continuum and Context

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 ...
EurekAlert!

A review of machine learning advances in reliability-based design, integrity assessment, inspection and maintenance of pipelines

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 ...
IEEE

Improving Graph Embeddings in Machine Learning Using Knowledge Completion with Validation in a Case Study on COVID-19 Spread

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, ...
Scientific Research Publishing

Mitropoulou, K., Kokkinos, P., Soumplis, P. and Varvarigos, E. (2024) Anomaly Detection in Cloud Computing Using Knowledge Graph Embedding and Machine Learning Mechanisms ...

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 ...
Diginomica

Blue Yonder aims for ‘one speed’ supply chains with new AI and knowledge graph updates

Blue Yonder’s latest product updates are a culmination of work that’s been happening behind the scenes. The foundations are now in place for buyers to reconsider how they think about their supply ...