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AI Associate AI Fundamentals Practice Question

Which THREE factors can affect the accuracy of an Einstein GPT response?

⚠ Common exam trap

Salesforce often tests the misconception that output length or interface settings affect model accuracy, when in fact only prompt clarity, grounding data quality, and model hyperparameters like temperature are the true determinants.

Answer choices

Why each option matters

Answer the question above first, then reveal the full breakdown to understand why each option is right or wrong.

Correct answer & explanation

Model temperature setting

The model temperature setting directly controls the randomness of the output. A higher temperature (e.g., 0.9) produces more creative but potentially less accurate responses, while a lower temperature (e.g., 0.1) makes the model more deterministic and factual. This parameter is a core hyperparameter in large language models like those powering Einstein GPT, and it significantly influences response accuracy.

Answer analysis

Option-by-option breakdown

For each option: why learners choose it and why it is or isn't the right answer here.

  • Brightness of the user interface

    Why it's wrong here

    Interface brightness has no impact on AI response accuracy.

  • Model temperature setting

    Why this is correct

    Higher temperature increases creativity but may reduce factual accuracy.

  • Clarity and specificity of the prompt

    Why this is correct

    Vague prompts cause ambiguous or irrelevant answers.

  • Quality of the grounding data provided

    Why this is correct

    Inaccurate or incomplete grounding data leads to hallucinated or incorrect responses.

  • Length of the response generated

    Why it's wrong here

    Response length does not directly correlate with accuracy; it can be long but wrong.

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This AI Associate practice question is part of Courseiva's free Salesforce certification practice question bank. Courseiva provides original exam-style practice questions with explanations, topic-based practice, mock exams, readiness tracking, and study analytics to help learners prepare for the AI Associate exam.