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A company is building a chatbot using Amazon Bedrock. They want to ensure the model's responses are grounded in company-specific data and that harmful content is filtered out. Which two services or features should they use? (Choose TWO.)
Amazon Kendra (A) is correct because it is an ML-powered enterprise search service that can index company-specific documents and be integrated with Amazon Bedrock via Knowledge Bases for Amazon Bedrock, providing retrieval-augmented generation (RAG) so the chatbot's responses are…Read full explanation
A company uses Amazon Bedrock to generate summarizations of lengthy reports. Users report that the summaries are too verbose and include excessive detail. Which prompt engineering technique should the team apply to address this issue?
Adding explicit constraints like 'Provide a concise summary in two sentences' directly instructs the model to limit verbosity and detail. This prompt engineering technique uses clear, specific instructions to control output length and style, which is the most effective way to add…Read full explanation
Which THREE statements about Amazon SageMaker Ground Truth are correct? (Choose three.)
Option B is correct because Amazon SageMaker Ground Truth ships with built-in labeling task templates and workflows for common job types, including image classification and object detection (as well as text, semantic segmentation, and bounding boxes). Option C is correct because …Read full explanation
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