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Evaluating RAG applications with Amazon Bedrock knowledge base evaluation

AWS Machine Learning - AI

Although automated metrics are fast and cost-effective, they can only evaluate the correctness of an AI response, without capturing other evaluation dimensions or providing explanations of why an answer is problematic. Human evaluation, although thorough, is time-consuming and expensive at scale.

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5 tips for better business value from gen AI

CIO

Specify metrics that align with key business objectives Every department has operating metrics that are key to increasing revenue, improving customer satisfaction, and delivering other strategic objectives. Below are five examples of where to start. Gen AI holds the potential to facilitate that.

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Why your IT team needs to upgrade its digital employee experience (DEX)

CIO

DEX best practices, metrics, and tools are missing Nearly seven in ten (69%) leadership-level employees call DEX an essential or high priority in Ivanti’s 2024 Digital Experience Report: A CIO Call to Action , up from 61% a year ago. Most IT organizations lack metrics for DEX.

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Introducing guardrails in Knowledge Bases for Amazon Bedrock

AWS Machine Learning - AI

Knowledge Bases for Amazon Bedrock is a fully managed capability that helps you securely connect foundation models (FMs) in Amazon Bedrock to your company data using Retrieval Augmented Generation (RAG). In the following sections, we demonstrate how to create a knowledge base with guardrails.

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Empower your generative AI application with a comprehensive custom observability solution

AWS Machine Learning - AI

Observability refers to the ability to understand the internal state and behavior of a system by analyzing its outputs, logs, and metrics. Evaluation, on the other hand, involves assessing the quality and relevance of the generated outputs, enabling continual improvement.

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

AWS Machine Learning - AI

This post explores the new enterprise-grade features for Knowledge Bases on Amazon Bedrock and how they align with the AWS Well-Architected Framework. AWS Well-Architected design principles RAG-based applications built using Knowledge Bases for Amazon Bedrock can greatly benefit from following the AWS Well-Architected Framework.

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Elevate RAG for numerical analysis using Amazon Bedrock Knowledge Bases

AWS Machine Learning - AI

Amazon Bedrock Knowledge Bases is a fully managed capability that helps you implement the entire RAG workflow—from ingestion to retrieval and prompt augmentation—without having to build custom integrations to data sources and manage data flows. Latest innovations in Amazon Bedrock Knowledge Base provide a resolution to this issue.