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Running machine learning (ML) models in production requires more than just infrastructure resilience and scaling efficiency. You need nearly continuous visibility into performance and resource utilization. When latency increases, invocations fail, or resources become constrained, you need immediate insight to diagnose and resolve issues before they impact your customers. Until now, Amazon SageMaker AI provided …

Enhanced metrics for Amazon SageMaker AI endpoints: deeper visibility for better performance Read More »

Organizations with users in multiple geographies face data residency requirements such as General Data Protection Regulation (GDPR) in Europe, country-specific data sovereignty laws, and internal compliance policies. Amazon Quick with Microsoft 365 extensions supports Regional routing to meet these requirements. Amazon Quick supports multi-Region deployments so you can route users to AWS Region-specific Amazon Quick …

Enforce data residency with Amazon Quick extensions for Microsoft Teams Read More »

With a wide array of Nova customization offerings, the journey to customization and transitioning between platforms has traditionally been intricate, necessitating technical expertise, infrastructure setup, and considerable time investment. This disconnect between potential and practical applications is precisely what we aimed to address. Nova Forge SDK makes large language model (LLM) customization accessible, empowering teams …

Kick off Nova customization experiments using Nova Forge SDK Read More »

Large language models (LLMs) have transformed how we interact with AI, but one size doesn’t fit at all. Out-of-the-box LLMs are trained with broad, general knowledge and improved for a wide range of use cases, but they often fall short when it comes to domain-specific tasks, proprietary workflows, or unique business requirements. Enterprise customers increasingly …

Introducing Nova Forge SDK, a seamless way to customize Nova models for enterprise AI Read More »

Moving AI agents from prototypes to production surfaces a challenge that traditional testing is unable to address. Agents are flexible, adaptive, and context-aware by design, but the same qualities that make them powerful also make them difficult to evaluate systematically. Traditional software testing relies on deterministic outputs: same input, same expected output, every time. AI …

Evaluating AI agents for production: A practical guide to Strands Evals Read More »

Organizations commonly rely on A/B testing to optimize user experience, messaging, and conversion flows. However, traditional A/B testing assigns users randomly and requires weeks of traffic to reach statistical significance. While effective, this process can be slow and might not fully leverage early signals in user behavior. This post shows you how to build an …

Build an AI-Powered A/B testing engine using Amazon Bedrock Read More »

This post is cowritten with Hammad Mian and Joonas Kukkonen  from Bark.com. When scaling video content creation, many companies face the challenge of maintaining quality while reducing production time. This post demonstrates how Bark.com and AWS collaborated to solve this problem, showing you a replicable approach for AI-powered content generation. Bark.com used Amazon SageMaker and …

How Bark.com and AWS collaborated to build a scalable video generation solution Read More »

If you’re running Amazon Nova 1 models on Amazon Bedrock, you might be looking to expand your context window size, deepen reasoning capabilities, or integrate external tools for web search and code execution. Amazon Nova 2 models address these constraints while improving performance on reasoning, agentic AI, and tool use benchmarks. Amazon Nova 2 Lite …

Migrate from Amazon Nova 1 to Amazon Nova 2 on Amazon Bedrock Read More »

Google is making new investments, building new tools and developing code security to improve open source security. ​ 

We’re expanding Personal Intelligence across AI Mode in Search, the Gemini app and Gemini in Chrome. ​