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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).
Which feature of Amazon OpenSearch Service gives companies the ability to build vector database applications?
A. Integration with Amazon S3 for object storage
B. Support for geospatial indexing and queries
C. Scalable index management and nearest neighbor search capability
D. Ability to perform real-time analysis on streaming data
An accounting firm wants to implement a large language model (LLM) to automate document processing. The firm must proceed responsibly to avoid potential harms. What should the firm do when developing and deploying the LLM? (Select TWO.)
A. Include fairness metrics for model evaluation.
B. Adjust the temperature parameter of the model.
C. Modify the training data to mitigate bias.
D. Avoid overfitting on the training data.
E. Apply prompt engineering techniques.