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

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

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 ...

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.

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

Whether you are looking for an LLM with more safety guardrails or one completely without them, someone has probably built it.

Many Qwen LLMs are among the most popular models on Hugging Face (Fig. 1). Qwen is continuously developing the models: after the convincing Qwen3 release in April 2025, the provider introduced a new ...

AI in architecture is moving from experimentation to implementation. An AJ webinar supported by CMap explored how practices are applying these tools to live projects, construction delivery and operati ...

Are AGENTS.md files actually helping your AI coding agents, or are they making them stupider? We dive into new research from ETH Zurich, real-world experiments, and security risks to find the truth ...

Wondering if Linux has AI companions that are as accessible, capable, and easy to use as Microsoft Copilot? Try these AI ...