InfoWorld

Four agentic AI memory systems for smarter LLMs

These third-party projects greatly expand the ways agents and LLMs can draw on facts, documents, and conversations to deliver ...

Deep learning reveals nanoparticle shape from routine tracking analysis without new hardware

Researchers at the University of Tokyo and the Innovation Center of NanoMedicine (iCONM) have developed an artificial ...
TMCnet

AI-Ready Enterprise Knowledge Graph Market Forecast to Reach USD 6,550.0 Million by 2036 as Enterprise AI Adoption, GraphRAG Infrastructure, and Semantic Data Inte…

According to the latest analysis by Future Market Insights, the AI-Ready Enterprise Knowledge Graph Market is poised for ...

The Web Is Growing A Second Layer – Almost A Third Head

Google shipped two new specs weeks apart. Here's what OKF and ARD actually do, how they differ from LLMs.txt and MCP, and ...
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?
Frontiers

Trustworthy and Resilient AI for Smart Energy Systems: Frontier AI, Reinforcement Learning, and Security

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

Data Scientist Ke Zhang’s Research Explores Homomorphic Encryption for Privacy-Preserving Marketing

A privacy-preserving marketing framework applies homomorphic encryption to perform machine learning on encrypted ...
Tech Xplore

Geospatial upgrade gives TabPFN sharper local predictions on datasets up to 70,000 rows

A new development in data science has given one popular machine learning tool an improved sense of place, enabling it to make ...

Physical AI Hits A Data Labeling Wall That Only Cash Can Fix

Physical AI raised $10B+ in 2025, but robots still train on under 5,000 hours of real-world data. Who's funding the race to ...
IEEE

Adaptive Policy Learning for Connected Autonomous Vehicles Defending Malicious Access Requests by Graph Reinforcement Learning

Abstract: Access requests are used in cooperative tasks among connected and automated vehicles (CAVs). Authorization decisions are determined by dynamic trust values in trust value-based access ...
IEEE

Prior-Boosted GRL: Microarchitecture Design Space Exploration via Graph Representation Learning

Abstract: The design space exploration (DSE) of contemporary microprocessors faces a significant challenge of high-computational cost. In this context, we introduce Prior-boosted graph representation ...