Discover how system messages shape prompt engineering outcomes for the Microsoft AI-900 certification. Learn why specifying constraints ensures accurate model behavior and exam success.
Table of Contents
Question
Which of the following is an example of using system messages in prompt engineering?
A. Fine-tuning the model without training a custom model.
B. Specifying constraints and expectations to set the context for the model.
C. Updating the kernel of the model without redeploying it.
D. Specifying multiple examples to the model for future responses.
Answer
B. Specifying constraints and expectations to set the context for the model.
Explanation
The purpose of using system messages in prompt engineering is to specify constraints and expectations to set the context for the model. This helps the model:
- Understand the desired tone and style: For example, a system message such as “You are an informative and objective assistant” would guide the model to provide factual responses in a neutral tone.
- Avoid generating harmful or offensive content: Including guidelines such as “Avoid making discriminatory or offensive statements” can help mitigate potential biases in the model’s output.
Specifying multiple examples to the model for future responses is not an example of using system messages. System messages focus on contextualizing the model’s behavior, while examples contribute to guiding the model’s understanding of the desired output.
Fine-tuning the model without training a custom model is not an example of using system messages. Fine-tuning is a separate process used to adapt models to specific tasks or domains.
Updating the kernel of the model without redeploying it is not an example of using system messages. System messages do not involve updating the kernel of the model or the underlying code. They are messages that guide the model’s understanding and response context.
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