Amazon SageMaker Lakehouse

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Build secure RAG applications with AWS serverless data lakes

Amazon Machine Learning, Amazon SageMaker, Amazon SageMaker Data & AI Governance, Amazon SageMaker Lakehouse, Amazon Simple Storage Service (S3), Best Practices, Customer Solutions, Generative AI, Technical How-to /

Data is your generative AI differentiator, and successful generative AI implementation depends on a robust data strategy incorporating a comprehensive data governance approach. Traditional data architectures often struggle to meet the unique demands of generative such as applications. An effective generative AI data strategy requires several key components like seamless integration of diverse data sources, […]

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Optimize RAG in production environments using Amazon SageMaker JumpStart and Amazon OpenSearch Service

Amazon OpenSearch Service, Amazon SageMaker Lakehouse, Best Practices, Intermediate (200) /

Generative AI has revolutionized customer interactions across industries by offering personalized, intuitive experiences powered by unprecedented access to information. This transformation is further enhanced by Retrieval Augmented Generation (RAG), a technique that allows large language models (LLMs) to reference external knowledge sources beyond their training data. RAG has gained popularity for its ability to improve

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