Announcements

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Evaluating generative AI models with Amazon Nova LLM-as-a-Judge on Amazon SageMaker AI

Amazon Nova, Amazon SageMaker, Amazon SageMaker AI, Announcements, Artificial Intelligence, Foundation models /

Evaluating the performance of large language models (LLMs) goes beyond statistical metrics like perplexity or bilingual evaluation understudy (BLEU) scores. For most real-world generative AI scenarios, it’s crucial to understand whether a model is producing better outputs than a baseline or an earlier iteration. This is especially important for applications such as summarization, content generation, […]

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Enabling customers to deliver production-ready AI agents at scale

Amazon Bedrock, Amazon Connect, Amazon Nova, Amazon Q, Amazon Simple Storage Service (S3), Announcements, AWS Inferentia, AWS Trainium, AWS Transform, Featured, Thought Leadership /

AI agents will change how we all work and live. Our AWS CEO, Matt Garman, shared a vision of a technological shift as transformative as the advent of the internet. I’m energized by this vision because I’ve witnessed firsthand how these intelligent agent systems are already beginning to solve complex problems, automate workflows, and create

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AWS doubles investment in AWS Generative AI Innovation Center, marking two years of customer success

Announcements, Customer Solutions, Generative AI /

When we launched the AWS Generative AI Innovation Center in 2023, we had one clear goal: help customers turn AI potential into real business value. We’ve already guided thousands of customers across industries from financial services to healthcare—including Formula 1, FOX, GovTech Singapore, Itaú Unibanco, Nasdaq, NFL, RyanAir, and S&P Global—from AI experimentation to full-scale

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Streamline machine learning workflows with SkyPilot on Amazon SageMaker HyperPod

Amazon SageMaker HyperPod, Announcements /

This post is co-written with Zhanghao Wu, co-creator of SkyPilot. The rapid advancement of generative AI and foundation models (FMs) has significantly increased computational resource requirements for machine learning (ML) workloads. Modern ML pipelines require efficient systems for distributing workloads across accelerated compute resources, while making sure developer productivity remains high. Organizations need infrastructure solutions

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New capabilities in Amazon SageMaker AI continue to transform how organizations develop AI models

Amazon Bedrock, Amazon SageMaker AI, Amazon SageMaker HyperPod, Amazon SageMaker JumpStart, Announcements /

As AI models become increasingly sophisticated and specialized, the ability to quickly train and customize models can mean the difference between industry leadership and falling behind. That is why hundreds of thousands of customers use the fully managed infrastructure, tools, and workflows of Amazon SageMaker AI to scale and advance AI model development. Since launching

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Accelerating generative AI development with fully managed MLflow 3.0 on Amazon SageMaker AI

Amazon SageMaker AI, Announcements, Technical How-to /

Amazon SageMaker now offers fully managed support for MLflow 3.0 that streamlines AI experimentation and accelerates your generative AI journey from idea to production. This release transforms managed MLflow from experiment tracking to providing end-to-end observability, reducing time-to-market for generative AI development. As customers across industries accelerate their generative AI development, they require capabilities to

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AWS AI infrastructure with NVIDIA Blackwell: Two powerful compute solutions for the next frontier of AI

Amazon EC2, Announcements, Artificial Intelligence, Compute /

Imagine a system that can explore multiple approaches to complex problems, drawing on its understanding of vast amounts of data, from scientific datasets to source code to business documents, and reasoning through the possibilities in real time. This lightning-fast reasoning isn’t waiting on the horizon. It’s happening today in our customers’ AI production environments. The

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Accelerate AI development with Amazon Bedrock API keys

Amazon Bedrock, Amazon Machine Learning, Announcements, Artificial Intelligence, Foundation models /

Today, we’re excited to announce a significant improvement to the developer experience of Amazon Bedrock: API keys. API keys provide quick access to the Amazon Bedrock APIs, streamlining the authentication process so that developers can focus on building rather than configuration. CamelAI is an open-source, modular framework for building intelligent multi-agent systems for data generation,

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Qwen3 family of reasoning models now available in Amazon Bedrock Marketplace and Amazon SageMaker JumpStart

Advanced (300), Amazon Bedrock, Amazon SageMaker, Amazon SageMaker JumpStart, Announcements, Featured, Technical How-to /

Today, we are excited to announce that Qwen3, the latest generation of large language models (LLMs) in the Qwen family, is available through Amazon Bedrock Marketplace and Amazon SageMaker JumpStart. With this launch, you can deploy the Qwen3 models—available in 0.6B, 4B, 8B, and 32B parameter sizes—to build, experiment, and responsibly scale your generative AI

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Power Your LLM Training and Evaluation with the New SageMaker AI Generative AI Tools

Amazon SageMaker, Amazon SageMaker AI, Announcements, Artificial Intelligence, Generative AI /

Today we are excited to introduce the Text Ranking and Question and Answer UI templates to SageMaker AI customers. The Text Ranking template enables human annotators to rank multiple responses from a large language model (LLM) based on custom criteria, such as relevance, clarity, or factual accuracy. This ranked feedback provides critical insights that help

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