DBX-GENAI study notes

• Matching a chunking method to document structure

  Which chunking method suits which kind of document.

• AI Search endpoints: standard or storage-optimized?

  What decides between the two endpoint types for an index.

• The role of re-ranking in retrieval

  What a reranker adds to retrieval, and what it costs.

• LangChain, LangGraph, DSPy or a plain client?

  How to choose a framework for a generative AI application.

• MLflow signatures and input examples

  What signatures and input examples do when logging a model.

• Batch inference with ai_query()

  Which workloads suit ai_query(), and how to run them.

• Which MLflow judges need ground truth?

  The built-in judges that need expected answers, and those that don't.

• Evaluation and monitoring phases compared

  How the evaluation and monitoring phases of a generative AI application differ.

About the book · DBX-GENAI terms in the glossary