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Universal Containers (UC) wants to use Flow to bring data from unified Data Cloud objects to prompt templates. Which type of flow should UC use?
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Question 2 - Certified AI Specialist discussion

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Universal Containers (UC) recently rolled out Einstein Generative capabilities and has created a custom prompt to summarize case records. Users have reported that the case summaries generated are not returning the appropriate information.

What is a possible explanation for the poor prompt performance?

A.
The data being used for grounding Is incorrect or incomplete.
Answers
A.
The data being used for grounding Is incorrect or incomplete.
B.
The prompt template version is incompatible with the chosen LLM.
Answers
B.
The prompt template version is incompatible with the chosen LLM.
C.
The Einstein Trust Layer is incorrectly configured.
Answers
C.
The Einstein Trust Layer is incorrectly configured.
Suggested answer: A

Explanation:

Poor prompt performance when generating case summaries is often due to the data used for grounding being incorrect or incomplete. Grounding involves feeding accurate, relevant data to the AI so it can generate appropriate outputs. If the data source is incomplete or contains errors, the generated summaries will reflect that by being inaccurate or insufficient.

Option B (prompt template incompatibility with the LLM) is unlikely because such incompatibility usually results in more technical failures, not poor content quality.

Option C (Einstein Trust Layer misconfiguration) is focused on data security and auditing, not the quality of prompt responses.

For more information, refer to Salesforce documentation on grounding AI models and data quality best practices.

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asked 26/09/2024
Franziska Kreuz
36 questions
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