Remove 2013 Remove Data Pipeline Remove Database
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Designing generative AI workloads for resilience

AWS Machine Learning Blog

Data pipelines In cases where you need to provide contextual data to the foundation model using the RAG pattern, you need a data pipeline that can ingest the source data, convert it to embedding vectors, and store the embedding vectors in a vector database.

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Architect a mature generative AI foundation on AWS

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A generative AI foundation can provide primitives such as models, vector databases, and guardrails as a service and higher-level services for defining AI workflows, agents and multi-agents, tools, and also a catalog to encourage reuse. Considerations here are choice of vector database, optimizing indexing pipelines, and retrieval strategies.

AWS 140
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How SnapLogic built a text-to-pipeline application with Amazon Bedrock to translate business intent into action

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The SnapLogic Intelligent Integration Platform (IIP) enables organizations to realize enterprise-wide automation by connecting their entire ecosystem of applications, databases, big data, machines and devices, APIs, and more with pre-built, intelligent connectors called Snaps.

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