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Source material

As explained in Starting Data Analytics with Generative AI and Python

Reference content supplied to a generative AI system as evidence or context for producing a response.

Source material is reference content supplied with a question or task to give a generative AI system evidence and context for its response. section 1.3.6

Useful source material can include:

  • Context data that clarifies the problem. section 1.3.6
  • Examples that make the desired result more concrete. section 1.3.6
  • Requested reasoning steps that make the solution process more transparent. section 1.3.6

Supplying source material can improve relevance and accuracy, but generated results still require checking, especially for high-stakes decisions. section 1.3.6

How Starting Data Analytics with Generative AI and Python covers it

How deep it goes
Describes context data, examples, and reasoning steps without detailing a formal representation.
Examples
Uses context data, examples, and requested solution steps as supplied inputs.
What you can do after
Apply it via a prompt by adding context, examples, or explicit solution steps, then verify the generated response.
How it connects
Connects source material with prompting, output evaluation, testing, human review, and data privacy.
Cover of Starting Data Analytics with Generative AI and Python
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Related concepts

This explainer was generated by Manning's knowledge graph from the text of Starting Data Analytics with Generative AI and Python. The section links point to the parts of the book it draws on.