A company has signed up for Amazon Bedrock access to build applications. The company wants to restrict employee access to specific models available on Amazon Bedrock.Which solution meets these requirements?
Answer(s): A
With IAM policies you can grant or deny Bedrock API actions scoped to specific model ARNs, ensuring employees can only invoke the exact models you authorize.
Which feature of Amazon OpenSearch Service gives companies the ability to build vector database applications?
Answer(s): C
The scalable index management and nearest neighbor search capability in Amazon OpenSearch Service enables companies to build vector database applications, which are crucial for tasks like similarity search in AImodels. The other options do not specifically provide the vector search functionality.
A financial company wants to build workflows for human review of ML predictions. The company wants to define confidence thresholds for its use case and adjust the thresholds over time.Which AWS service meets these requirements?
Answer(s): B
Amazon Augmented AI (Amazon A2I) enables you to build workflows for human review of machine learning predictions, allowing you to define and adjust confidence thresholds for when human intervention is required.
HOTSPOT (Drag and Drop is not supported)Select and order the steps from the following list to correctly describe the ML lifecycle for a new custom model.Select each step one time.Hot Area:
HOTSPOT (Drag and Drop is not supported)A company wants to customize a foundation model (FM). The company wants to understand the customization methods and data types that are available.Select the correct customization method from the following list for each description. Select each customization method one time.Hot Area:
Fine-tuning uses labeled data to adapt a foundation model for improved performance on specific tasks.Continued pre-training uses large volumes of unlabeled domain-specific data to adapt a foundation model to a specific domain.Distillation transfers knowledge from a larger, more capable model into a smaller model while retaining performance characteristics.
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