NUS researchers' MRAgent framework reduces LLM agent memory retrieval to 118K tokens per query — vs. 3.26M for LangMem — ...

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

When applied thoughtfully, agentic AI has the potential to turn classrooms into environments where students actively explore complex systems rather than passively absorb information ...

Here's why revenue teams need a "Marketing Engineer" — a systems designer who orchestrates agentic AI workflows — and how to hire and structure the role.

The cloud-based agentic AI platform aims to help human researchers overcome resource constraints and complex data challenges ...

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

Pinterest launches Ask Pinterest, an AI-powered shopping app using its Taste Graph to deliver personalized recommendations ...

One of the greatest weaknesses of AI agents that read and understand vast amounts of enterprise data is "hallucination"—the generation of plausible-sounding but factually incorrect information. KAIST ...

Solutions, a leading software company that is powering enterprise planning and decisioning models across 30-plus industry verticals with its groundbreaking Digital Brain platform, today announced the ...

Artificial Intelligence (AI) agents based on Retrieval-Augmented Generation (RAG) technology are rapidly proliferating. RAG ...

In this article, Firesand explores how specialized cybersecurity, compliance, and threat intelligence solutions are helping ...

Agentic AI moves beyond chatbots into systems that plan, use tools, and act. Learn key terms, architectures, risks, ...