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Exam AWS Certified AI Practitioner AIF-C01 All Questions

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Exam AWS Certified AI Practitioner AIF-C01 topic 1 question 78 discussion

An AI practitioner trained a custom model on Amazon Bedrock by using a training dataset that contains confidential data. The AI practitioner wants to ensure that the custom model does not generate inference responses based on confidential data.
How should the AI practitioner prevent responses based on confidential data?

  • A. Delete the custom model. Remove the confidential data from the training dataset. Retrain the custom model.
  • B. Mask the confidential data in the inference responses by using dynamic data masking.
  • C. Encrypt the confidential data in the inference responses by using Amazon SageMaker.
  • D. Encrypt the confidential data in the custom model by using AWS Key Management Service (AWS KMS).
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Suggested Answer: A 🗳️

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Moon
3 weeks, 1 day ago
Selected Answer: A
A: Delete the custom model. Remove the confidential data from the training dataset. Retrain the custom model. Explanation: If the training dataset contains confidential data, the model may inadvertently learn and generate responses based on that data. The only way to ensure that the model does not generate responses based on the confidential data is to: Remove the confidential data from the training dataset. Retrain the custom model using the updated dataset. This process ensures that the model is not influenced by the sensitive information.
upvoted 2 times
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BhaskarSadineni
3 weeks, 3 days ago
Selected Answer: A
Explanation: Once a model is trained, the data used for training is embedded in its parameters. If confidential data is included in the training dataset, it can influence the responses the model generates. Simply masking or encrypting inference responses will not ensure the model doesn’t generate responses derived from the confidential data; the issue originates in the training process itself.
upvoted 2 times
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may2021_r
3 weeks, 3 days ago
Selected Answer: A
The correct answer is A. Once a model is trained on confidential data, it must be retrained without it.
upvoted 1 times
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AKG85
3 weeks, 4 days ago
Selected Answer: A
Delete the custom model, remove the confidential data, and retrain the model is the best approach because it ensures that the model will not retain or generate responses based on any confidential information
upvoted 2 times
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ap6491
3 weeks, 5 days ago
Selected Answer: A
Once a model is trained on data, its outputs may inherently reflect patterns or details derived from the training dataset, including confidential data. To ensure the custom model does not generate inference responses based on confidential data, the only reliable solution is to: - Remove the confidential data from the training dataset. - Retrain the model with the updated dataset. This approach ensures the model is not influenced by sensitive information during inference. Option B is incorrect. Dynamic data masking hides sensitive information in database query results or outputs but does not prevent the model from generating responses influenced by the confidential data. The model would still "know" the sensitive patterns.
upvoted 2 times
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Dandelion2025
1 month, 2 weeks ago
Selected Answer: B
The company should mask the confidential information
upvoted 2 times
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Amitst
1 month, 2 weeks ago
Selected Answer: B
This is the most efficient method, effectively maintaining data privacy and security.
upvoted 2 times
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