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

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

Abstract: Efficient Multi-Agent Path Finding (MAPF) is pivotal for warehouse logistics. While existing learning-based methods primarily rely on computationally intensive grid-based representations, ...

Deep learning variant calling has transformed genomic accuracy. Discover how DeepVariant works, outperforms classical tools, ...

Indianapolis-based Selflessly rebuilt its corporate giving platform around Phil, an AI assistant built for every ...

Abstract: The pathfinding problem in a graph has been solved using several classical algorithms, notably Dijkstra’s and A* algorithms. However, most classical algorithms are most effective on static ...

This repository is the official implementation of Guidance Graph Optimization for Lifelong Multi-Agent Path Finding, accepted to IJCAI 2024. The repository builds on top of the repository of ...

We introduce the heat method for solving the single- or multiple-source shortest path problem on both flat and curved domains. A key insight is that distance computation can be split into two stages: ...

You need to pivot to stay competitive. Technical excellence is no longer enough; you have to be demonstrably useful. You need a strategy that’s more than just formatting, that looks deeper into the ...

The speakers discuss Netflix’s architecture for surviving extreme traffic spikes. They explain the mechanics of prioritized ...

Your vault has a graph. But you can only stare at it. Obsidian's graph view is beautiful, but it can't answer questions — "Which notes have the most links?" "How many hops between these two concepts?" ...

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 ...