Databricks built a RAG agent it says can handle every kind of enterprise search

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

“Reinforcement Learning” Fuels the Rise of Adaptive Controllers

More engineers are turning to reinforcement learning to incorporate adaptive and self-tuning control into industrial systems. It aims to strike a balance between traditional ...

Board Approves Higginsville Expansion Plan

Westgold Resources Limited (ASX: WGX) (TSX: WGX) (Westgold or the Company) is pleased to announce that its Board has approved ...

The AI engine pipeline: 10 gates that decide whether you win the recommendation

AI recommendations are decided upstream. Understand the 10-gate pipeline, where brands fail, and how small improvements ...

I built my own movie recommendation system with NotebookLM, and it beats Netflix's algorithm

NotebookLM learned my movie taste better than streaming apps ...
AHA/ASA Journals

Calcific Aortopathy in Response to Aging and Injury

The arterial vasculature is the second most frequently calcified structure in the human body after the skeleton. Calcification of the aorta and aortic valves occurs in most individuals in westernized ...
WinBuzzer

New Databricks KARL RAG Agent Promises 33% Cost Reduction vs. Claude Opus 4.6

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

Hard Fork

“The Pentagon and OpenAI are saying to the public, You’re just going to have to trust us. And the public is saying, Well, we don’t.” By Kevin RooseCasey NewtonRachel CohnWhitney JonesVjeran PavicChris ...