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 ...

Discover how data lake consulting helps organizations design, secure, and optimize scalable data architectures for analytics, AI, and business growth.

It’s a familiar moment in math class—students are asked to solve a problem, and some jump in confidently while others freeze, unsure where to begin. When students don’t yet have a clear mental model ...

When you launch a new product, your vision for its use might differ from how customers actually use it. Ivar Jacobson created the first use case model in 1987 while working at Ericsson. It started as ...

Databricks and Snowflake are at it again, and the battleground is now SQL-based document parsing. In an intensifying race to dominate enterprise AI workloads with agent-driven automation, Databricks ...

This was originally posted in dbt-databricks project and I was asked to cross post i here. Related to: databricks/dbt-databricks#1246 When running dbt in an Azure Devops Agent (for continues ...

Using the right model and the right prompt is only part of the enterprise AI challenge, it's also critical to optimize the prompt. The breakthrough in prompt optimization arrives alongside Databricks' ...