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

Harvey proved vertical AI works in legal at $11B. Agriculture's $500B data gap, a $300M USDA signal, and GrowersTech's agronomic ontology suggest the next category winner scales from the field.

Researchers have developed AdapGNN, a novel model-agnostic framework that addresses the oversmoothing problem in graph neural ...

Incogni Review: Comprehensive and Transparent Data Removals ...

Overview:Discover leading multimodal AI models transforming productivity, software development, research, and enterprise ...

Public input identifying over 100 million trail cameras photos of Wisconsin’s animals has transformed science education and ...

The latest inflation numbers aren’t especially encouraging for Warsh. He's a fan of so‑called trimmed‑mean inflation, which ...

AI agents waste massive cloud space, so block this bloat early with strict policy checks, illustrated using Terraform and ...

AMD's new FSR 4.1 INT8 upscaler gives RDNA 3 GPUs a massive image quality upgrade. We examine visual quality, performance, ...

A framework for analyzing single-cell genomics data, in which geometrical properties are harnessed to obtain insights on cellular diversity, including precise clustering, clear visualizations, and ...

Healthcare coding has fundamentally transformed from volume-driven revenue capture to compliance-first, defensible documentation standards.

As global robotics companies race to build physical AI, India's workers are supplying the human movements that teach machines ...