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

LLVM powers the core development tools, operating systems, and most applications at Apple Computer, where it long ago ...

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

A monthly overview of things you need to know as an architect or aspiring architect. Unlock the full InfoQ experience by logging in! Stay updated with your favorite authors and topics, engage with ...

Learn about solving a system of equations by graphing. A system of equations is a set of more than one equation that is to be solved simultaneously. To solve a system of equations graphically, we ...

This repository contains code for our SPAA paper "Theoretically Efficient Parallel Graph Algorithms Can Be Fast and Scalable" (SPAA'18). It includes implementations of the following parallel graph ...

@article{article, author = {Chen, Yu and Shen, Shuhan and Chen, Yisong and Wang, Guoping}, year = {2020}, month = {07}, pages = {107537}, title = {Graph-Based ...

Accurate traffic prediction is crucial for an intelligent traffic system (ITS). However, the excessive non-linearity and complexity of the spatial-temporal correlation in traffic flow severely limit ...

Abstract: Graph neural networks (GNNs) are among the most powerful tools in deep learning. They routinely solve complex problems on unstructured networks, such as node classification, graph ...