AIF-C01 exam dumps

AIF-C01 practice question 80 of 231

AWS Certified AI Practitioner. Associate level, Amazon Web Services. Free question with the correct answer and a full explanation.

AIF-C01 Question 80

Select 3

A retail company wants to use a generative AI model to create personalized product descriptions for their e-commerce platform. They require a model that can handle multilingual output, ensure compliance with data privacy regulations, and generate responses in near real-time. Which factors should the company prioritize when selecting a generative AI model?

  1. A

    Multilingual capabilities of the model

  2. B

    Latency and performance of the model

  3. C

    The model's ability to produce creative and fictional content

  4. D

    Compliance with relevant privacy and data protection regulations

  5. E

    The size of the model's training dataset

Show answer and explanation

Correct answers: A, B, D

Explanation

To meet the company’s requirements, the chosen generative AI model must support multilingual output to cater to a diverse customer base, ensure low latency for near real-time responses, and comply with privacy regulations to avoid legal and reputational risks. These factors directly align with the company’s goals, while other considerations like creativity or dataset size are less critical for this scenario.

  • A. Correct.

    Multilingual capabilities are critical for the company’s need to generate product descriptions in multiple languages.

  • B. Correct.

    Latency and performance are important as the company requires near real-time generation of responses.

  • C. Incorrect.

    While creativity is valuable in some contexts, the company’s goal is to create accurate and personalized product descriptions, not fictional content.

  • D. Correct.

    Ensuring compliance with privacy and data protection regulations is essential for any application that handles customer data, especially in a commercial environment.

  • E. Incorrect.

    The size of the model's training dataset is less relevant here compared to the model's capabilities and performance for the specific use case.

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