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.

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

Databricks, Snowflake, Amazon Redshift, Google BigQuery, and Microsoft Fabric – to see how they address rapidly evolving ...

Research reveals that LeapLogic delivers significantly higher conversion accuracy, faster transformation and time ...

Prophecy v4 brings an agent-driven, human-in-the-loop workflow to data prep & analysis. Users describe business intent, agents generate workflows as code, validate results by compiling and running ...

Every data engineering team right now is being asked the same question: "How do we build a chatbot that talks to our data?" The prototypes are deceptively simple. A developer connects GPT-5.1 to a ...

I’m encountering difficulties setting up Sedona 1.8 on Databricks (DBR 17.3 LTS). Is it a known compatibility issue between Sedona and Databricks DBR 17.3 LTS ? I used the following jars for spark 4.0 ...

Managing SQL Server across hybrid and multi-cloud environments has long posed a challenge for database administrators. With data sprawled across on-premises infrastructure, cloud platforms, and edge ...

Hi team/ maintainers, I love the work you're doing on Data API Builder. We’ve adopted it in different areas because it gives us a unified, secure, and standards-based API layer on top of multiple data ...

Abstract: Based on the big data processing engine Spark SQL technology, this paper studies and analyzes the agricultural recommendation data set in the Kaggle data science and machine learning ...