Enterprise AI doesn’t prove its value through pilots, it proves it through disciplined financial modeling. Here’s how ESG quantified productivity gains, faster deployment, operational efficiency, and ...

At QCon London 2026, Lan Chu, AI Tech Lead at Rabobank, shared lessons from deploying a production AI search system used internally by more than 300 users across 10,000 documents. Her experience shows ...

Anyscale, founded by the creators of Ray, today announced upcoming new capabilities in Ray and the Anyscale platform designed to help teams build and deploy AI workloads at production scale. As more ...

This article introduces practical methods for evaluating AI agents operating in real-world environments. It explains how to ...

Dozens of Telegram channels reviewed by WIRED include job listings for “AI face models.” The (mostly) women who land these ...

Success with agents starts with embedding them in workflows, not letting them run amok. Context, skills, models, and tools are key. There’s more.

Integrating AI into chip workflows is pushing companies to overhaul their data management strategies, shifting from passive storage to active, structured, and machine-readable systems. As training and ...

Out of the box,POMA PrimeCut uses 77% fewer tokens than conventional models. The figure rises to 83% when used in customized ...

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

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 ...