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Evaluating RAG applications with Amazon Bedrock knowledge base evaluation

AWS Machine Learning - AI

Amazon Bedrock has recently launched two new capabilities to address these evaluation challenges: LLM-as-a-judge (LLMaaJ) under Amazon Bedrock Evaluations and a brand new RAG evaluation tool for Amazon Bedrock Knowledge Bases.

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Building scalable, secure, and reliable RAG applications using Knowledge Bases for Amazon Bedrock

AWS Machine Learning - AI

As successful proof-of-concepts transition into production, organizations are increasingly in need of enterprise scalable solutions. This post explores the new enterprise-grade features for Knowledge Bases on Amazon Bedrock and how they align with the AWS Well-Architected Framework.

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Use RAG for drug discovery with Knowledge Bases for Amazon Bedrock

AWS Machine Learning - AI

Knowledge Bases for Amazon Bedrock allows you to build performant and customized Retrieval Augmented Generation (RAG) applications on top of AWS and third-party vector stores using both AWS and third-party models. If you want more control, Knowledge Bases lets you control the chunking strategy through a set of preconfigured options.

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Build an end-to-end RAG solution using Knowledge Bases for Amazon Bedrock and AWS CloudFormation

AWS Machine Learning - AI

An end-to-end RAG solution involves several components, including a knowledge base, a retrieval system, and a generation system. Solution overview The solution provides an automated end-to-end deployment of a RAG workflow using Knowledge Bases for Amazon Bedrock. Choose Sync to initiate the data ingestion job.

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Amazon Bedrock Marketplace now includes NVIDIA models: Introducing NVIDIA Nemotron-4 NIM microservices

AWS Machine Learning - AI

Organizations can use these models securely, and for models that are compatible with the Amazon Bedrock Converse API, you can use the robust toolkit of Amazon Bedrock, including Amazon Bedrock Agents , Amazon Bedrock Knowledge Bases , Amazon Bedrock Guardrails , and Amazon Bedrock Flows. You can find him on LinkedIn.

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Empower your generative AI application with a comprehensive custom observability solution

AWS Machine Learning - AI

We have built a custom observability solution that Amazon Bedrock users can quickly implement using just a few key building blocks and existing logs using FMs, Amazon Bedrock Knowledge Bases , Amazon Bedrock Guardrails , and Amazon Bedrock Agents.

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Introducing AWS MCP Servers for code assistants (Part 1)

AWS Machine Learning - AI

Whether youre an experienced AWS developer or just getting started with cloud development, youll discover how to use AI-powered coding assistants to tackle common challenges such as complex service configurations, infrastructure as code (IaC) implementation, and knowledge base integration.

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