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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?
A
Knowledge base
B
Agents
C
Guardrails
D
Model evaluation
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.