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AWS Certified Cloud Practitioner

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A university wants its chatbot to use general AI knowledge plus internal research papers stored in S3. Which Bedrock approach provides this capability?

Real Exam
Community
RRitesh



Explanation:

Amazon Bedrock Knowledge Bases is the correct approach for this use case. Here's why:

  • Knowledge Bases allow you to connect foundation models to your company's data sources, including S3 buckets
  • They can ingest documents from S3 and create vector embeddings for retrieval-augmented generation (RAG)
  • This enables the chatbot to combine general AI knowledge with specific information from the university's internal research papers
  • The chatbot can then provide responses that are grounded in both the foundation model's general knowledge and the specific research content

Other options:

  • Agents: Used for multi-step tasks and tool use, not specifically for connecting to knowledge sources
  • Guardrails: Focus on safety and content filtering
  • Model evaluation: Used for testing and comparing model performance

Knowledge Bases is specifically designed for the scenario described - augmenting foundation models with custom data sources like S3-stored documents.

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