Databricks has released KARL, an RL-trained RAG agent that it says handles all six enterprise search categories at 33% lower ...

Despite widespread industry recommendations, a new ETH Zurich paper concludes that AGENTS.md files may often hinder AI coding agents. The researchers recommend omitting LLM-generated context files ...

Databricks' KARL agent uses reinforcement learning to generalize across six enterprise search behaviors — the problem that breaks most RAG pipelines.

AT&T's chief data officer shares how rearchitecting around small language models and multi-agent stacks cut AI costs by 90% at 8 billion tokens a day.

Bottom line: You can build a working RAG chatbot on Azure UK South in a single day using Azure AI Foundry's guided setup. The three services you need are Azure AI Search (retrieval), Azure OpenAI ...

Abstract: This paper presents a secure question answering framework for financial compliance using a graph-based retrieval-augmented generation (Graph-RAG) model. The system constructs a multi-layer ...

In this tutorial, we build an elastic vector database simulator that mirrors how modern RAG systems shard embeddings across distributed storage nodes. We implement consistent hashing with virtual ...

After installation, run /create-site and describe what you want to build. For the full walkthrough, see Get started with the Power Pages plugin for GitHub Copilot CLI and Claude Code. Tip: New to ...

Abstract: Environmental, Social and Governance (ESG) criteria have emerged as fundamental pillars for evaluating corporate sustainability, ethical stewardship and governance practices, increasingly ...

Memgraph, a leader in open-source, in-memory graph databases, is introducing a new capability designed to accelerate business adoption of graph-based retrieval-augmented generation (GraphRAG), Atomic ...