NCA-GENL exam dumps

NCA-GENL practice question 57 of 228

NVIDIA-Certified Associate - Generative AI LLMs. Associate level, NVIDIA. Free question with the correct answer and a full explanation.

NCA-GENL Question 57

Single answer

You are tasked with designing a prompt for a generative AI model to create a detailed product description for an e-commerce website. The description should include the product's features, benefits, and potential use cases. Which prompt would most effectively achieve the desired result based on prompt engineering principles?

  1. A

    Describe this product.

  2. B

    Write a short paragraph about this product, including some details.

  3. C

    Create a product description highlighting the features, benefits, and use cases of this product. Use a professional and engaging tone.

  4. D

    Generate a text about this product with some information.

Show answer and explanation

Correct answer: C

Explanation

Prompt engineering involves designing prompts that guide the AI model effectively to achieve the desired output. In this case, the third option is the most effective because it explicitly specifies the content to include (features, benefits, use cases) and the tone to use (professional and engaging). Specific and well-structured prompts lead to higher-quality and more relevant AI-generated responses.

  • A. Incorrect.

    This option is too vague and lacks specific instructions. The model is unlikely to produce a detailed or structured response based on this prompt.

  • B. Incorrect.

    While this option asks for a description, it does not explicitly specify the structure or key elements (features, benefits, use cases) required in the output.

  • C. Correct.

    This option provides clear and specific instructions, including the desired structure (features, benefits, use cases) and tone (professional and engaging), which aligns with effective prompt engineering principles.

  • D. Incorrect.

    This option is generic and does not provide enough context or instructions for the model to generate a detailed, high-quality response.

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