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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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Marsh McLennan IT reorg lays foundation for gen AI

CIO

The team opted to build out its platform on Databricks for analytics, machine learning (ML), and AI, running it on both AWS and Azure. I want to provide an easy and secure outlet that’s genuinely production-ready and scalable. The biggest challenge is data. Marsh McLennan created an AI Academy for training all employees.

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Unleashing the multimodal power of Amazon Bedrock Data Automation to transform unstructured data into actionable insights

AWS Machine Learning - AI

It often requires managing multiple machine learning (ML) models, designing complex workflows, and integrating diverse data sources into production-ready formats. With Amazon Bedrock Data Automation, enterprises can accelerate AI adoption and develop solutions that are secure, scalable, and responsible.

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