NASA’s new dark energy space telescope can also detect killer asteroids
technologyreview.com·1h ago
Cloud & Infrastructure
AWS Blog·Jun 17·5 min read
AWS Blog·Jun 17·5 min readIntroducing Amazon Bedrock Managed Knowledge Base for faster, more accurate enterprise AI applications
TL;DR
Developers face challenges in building enterprise AI applications due to the complexity of managing data retrieval and model selection. Amazon Bedrock Managed Knowledge Base simplifies this process by providing a managed service that automates the retrieval-augmented generation (RAG) pipeline.
✦ Why It Matters
Engineers can leverage Amazon Bedrock Managed Knowledge Base to accelerate the development of AI applications with proprietary data.
Key Takeaways
- Utilize pre-built connectors for seamless data integration.
- Leverage smart parsing for accurate data ingestion.
- Implement Agentic Retriever for complex multi-step queries.
- Optimize model selection for performance and cost efficiency.
How It Works
Amazon Bedrock Managed Knowledge Base simplifies the RAG pipeline by automatically managing components like storage, retrieval, and model selection. It uses native data connectors to pull enterprise data and permissions, while smart parsing optimizes data ingestion based on content type.
The Agentic Retriever enhances query accuracy by inferring user intent and performing multi-hop retrieval, allowing for complex queries to be resolved efficiently.