Grounding
Grounding is the practice of anchoring AI responses to specific, verifiable sources of information such as documents, databases, or real-time data. By providing factual reference material in the prompt, grounding reduces the likelihood of hallucinations and ensures the model's output is based on accurate, up-to-date information.
Example
Instead of asking "What are our Q3 revenue figures?", you paste the actual Q3 financial report into the prompt and ask: "Based on the following report, summarize our Q3 revenue figures." The model now answers from the provided data rather than guessing.
Frequently asked questions
What is Grounding?
- Grounding is the practice of anchoring AI responses to specific, verifiable sources of information such as documents, databases, or real-time data.
Can you give an example of Grounding?
- Instead of asking "What are our Q3 revenue figures?", you paste the actual Q3 financial report into the prompt and ask: "Based on the following report, summarize our Q3 revenue figures." The model now answers from the provided data rather than guessing.
Put this into practice
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