BenchMark Quizzes by MDFT Pro

Identify Prompt Engineering Technique For Context Enhancement

Claire, the AI Prompt Engineering Specialist at MDFT Pro, is optimizing the company’s generative AI tutoring system to provide more accurate and relevant responses to student questions about specific certification programs. MDFT Pro, a well-known training agency, wants the AI tutor to reference current course materials, updated certification requirements, and company-specific learning resources when answering student questions. Claire is implementing techniques to supply the AI system with relevant background information and current course data to ensure responses are aligned with MDFT Pro’s curriculum and contain up-to-date, factually correct information rather than generic or outdated content.

What prompt engineering technique involves providing contextual information to improve the accuracy and relevance of generative AI responses?

Choose the correct answer from the options below.

Explanations for each answer:

Providing examples is incorrect. Providing examples (few-shot learning) gives the model sample inputs and outputs to learn patterns, but doesn't provide broader contextual information.
Fine-tuning is incorrect. Fine-tuning involves retraining a model on specific data, which is a model modification technique rather than a prompt engineering approach.
System messages is incorrect. System messages set the AI's role and behavior instructions but don't provide specific contextual information to improve response accuracy.
Grounding data is correct. Grounding data provides relevant contextual information and facts that help the AI generate more accurate, informed responses based on specific knowledge.

Learn more about grounding data:

Grounding Data

Exam Preparation Quiz

Identify Prompt Engineering Technique For Context Enhancement