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.

Enterprises seeking to make good on the promise of agentic AI will need a platform for building, wrangling, and monitoring AI agents in purposeful workflows. In this quickly evolving space, myriad ...

The evidence is solid but not definitive, as the conclusions rely on the absence of changes in spatial breadth and would benefit from clearer statistical justification and a more cautious ...

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

Discover how quantitative analysts, or quants, use advanced mathematical models to predict market trends and identify lucrative investment opportunities.

Objective Cardiovascular diseases (CVD) remain the leading cause of mortality globally, necessitating early risk identification to improve prevention and management strategies. Traditional risk ...

Google Search has updated Canvas inside AI Mode, a workspace powered by Gemini that already lets users draft and refine documents, to now support coding projects and interactive tools. With the latest ...

AI is reshaping online search in ways that reduce friction for consumers while increasing it for businesses. Large language ...

You can avoid Google's AI summaries in your search results by simply adjusting your query. Or just switch search engines altogether.

AI-driven discovery depends on semantic depth and retrievable structure. Align language, taxonomy, and schema for modern search visibility.

Behind the AI interface, a staged system narrows tens of thousands of documents to a few, showing that visibility hinges on classic signals.