Artificial Intelligence
Category: Artificial Intelligence
Introducing V-RAG: revolutionizing AI-powered video production with Retrieval Augmented Generation
This post introduces Video Retrieval-Augmented Generation (V-RAG), an approach to help improve video content creation. By combining retrieval augmented generation with advanced video AI models, V-RAG offers an efficient, and reliable solution for generating AI videos.
Enhanced metrics for Amazon SageMaker AI endpoints: deeper visibility for better performance
SageMaker AI endpoints now support enhanced metrics with configurable publishing frequency. This launch provides the granular visibility needed to monitor, troubleshoot, and improve your production endpoints.
Enforce data residency with Amazon Quick extensions for Microsoft Teams
In this post, we will show you how to enforce data residency when deploying Amazon Quick Microsoft Teams extensions across multiple AWS Regions. You will learn how to configure multi-Region Amazon Quick extensions that automatically route users to AWS Region-appropriate resources, helping keep compliance with GDPR and other data sovereignty requirements.
Kick off Nova customization experiments using Nova Forge SDK
In this post, we walk you through the process of using the Nova Forge SDK to train an Amazon Nova model using Amazon SageMaker AI Training Jobs.
Introducing Nova Forge SDK, a seamless way to customize Nova models for enterprise AI
Today, we are launching Nova Forge SDK that makes LLM customization accessible, empowering teams to harness the full potential of language models without the challenges of dependency management, image selection, and recipe configuration and eventually lowering the barrier of entry.
Evaluating AI agents for production: A practical guide to Strands Evals
In this post, we show how to evaluate AI agents systematically using Strands Evals. We walk through the core concepts, built-in evaluators, multi-turn simulation capabilities and practical approaches and patterns for integration.
Build an AI-Powered A/B testing engine using Amazon Bedrock
This post shows you how to build an AI-powered A/B testing engine using Amazon Bedrock, Amazon Elastic Container Service, Amazon DynamoDB, and the Model Context Protocol (MCP). The system improves traditional A/B testing by analyzing user context to make smarter variant assignment decisions during the experiment.
How Bark.com and AWS collaborated to build a scalable video generation solution
Working with the AWS Generative AI Innovation Center, Bark developed an AI-powered content generation solution that demonstrated a substantial reduction in production time in experimental trials while improving content quality scores. In this post, we walk you through the technical architecture we built, the key design decisions that contributed to success, and the measurable results achieved, giving you a blueprint for implementing similar solutions.
Migrate from Amazon Nova 1 to Amazon Nova 2 on Amazon Bedrock
In this post, you will learn how to migrate from Nova 1 to Nova 2 on Amazon Bedrock. We cover model mapping, API changes, code examples using the Converse API, guidance on configuring new capabilities, and a summary of use cases. We conclude with a migration checklist to help you plan and execute your transition.
AWS AI League: Atos fine-tunes approach to AI education
In this post, we’ll explore how Atos used the AWS AI League to help accelerate AI education across 400+ participants, highlight the tangible benefits of gamified, experiential learning, and share actionable insights you can apply to your own AI enablement programs.









