AI

Kick off Nova customization experiments using Nova Forge SDK

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 […]

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

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 »

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

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 »

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

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

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

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

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

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

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