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From weeks to minutes: How Formula 1® uses agentic AI on AWS to accelerate data operations

From weeks to minutes: How Formula 1® uses agentic AI on AWS to accelerate data operations

Formula 1® (F1) engages an audience of over 800 million fans globally across digital platforms, F1 TV, social media, ticketing, and merchandise year-round. Races happen every two weeks. Fan engagement windows are measured in minutes and commercial decisions need to move at the speed of the grid. Behind the scenes, F1’s marketing technology (MarTech) platform, Customer

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Automated Reasoning policy refinement in Amazon Bedrock

Automated Reasoning policy refinement in Amazon Bedrock

Refining an Automated Reasoning policy in Amazon Bedrock has been a manual cycle of diagnose, hand-edit, retest, and repeat. Today, we are announcing automatic policy refinement, which automates the diagnose-and-fix work in that cycle. The refinement engine diagnoses failing tests and proposes formal-logic fixes. You approve every change before it takes effect. Automated Reasoning checks

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Announcing the Agentic Catalog Experience in Amazon Quick

Announcing the Agentic Catalog Experience in Amazon Quick

As organizations embrace AI-powered analytics, the value of a natural language (Text2SQL) answer is only as good as the business context behind it. We’re entering a phase where semantic richness (table and column descriptions, and relationships) must flow directly from where it’s authored in upstream data catalogs and semantic tools into the AI products that

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Optimizing production agents with Amazon Bedrock AgentCore Observability

Optimizing production agents with Amazon Bedrock AgentCore Observability

As your AI agents move from prototype to production, the challenges shift from getting them to work to keeping them fast and efficient. In Part 1 of this series, we walked through debugging two common agent failures: infinite loops and tool invocation errors. Those scenarios dealt with agents that were broken. In this post, we

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Deploying Kimi K3 on AWS

Deploying Kimi K3 on AWS

Open weight models have become powerful enough to handle complex tasks such as multi-step agentic workflows, advanced reasoning, and long-horizon coding. However, as these models grow in capability, they also grow in size and hosting multi-trillion parameter architectures requires purpose-built infrastructure, high-end GPU compute, and optimized serving frameworks. On July 27, 2026, Moonshot AI released

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How Yahoo enhances search retargeting using Amazon Bedrock

How Yahoo enhances search retargeting using Amazon Bedrock

Connecting user search intent with relevant ad experiences across channels is a longstanding challenge in digital advertising. Advertisers need sophisticated ways to reach audiences based on their demonstrated interests and behaviors, particularly their search activity, which is one of the strongest signals of user intent. Traditional keyword expansion approaches often struggle with outdated vocabulary, limited

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Inference meta-monitoring for Amazon SageMaker AI endpoints with Amazon Quick

Inference meta-monitoring for Amazon SageMaker AI endpoints with Amazon Quick

Without the ability to track machine learning (ML) model prediction quality, organizations only realize they have issues when their customers complain or when they conduct spot checks, which jeopardizes customer trust. This post introduces inference meta-monitoring for Amazon SageMaker AI endpoints. It provides a governance layer that sits above production ML inference pipelines to continuously

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Introducing explicit prompt caching for OpenAI GPT-5.6 models on Amazon Bedrock

Introducing explicit prompt caching for OpenAI GPT-5.6 models on Amazon Bedrock

This post is co-written with Chris Dickens from OpenAI. OpenAI GPT-5.6 Sol, Terra, and Luna are now generally available on Amazon Bedrock. With GPT-5.6 on Amazon Bedrock, you get the newest generation of OpenAI frontier models with pay-per-token pricing, AWS security and governance controls, and usage that counts toward your existing AWS commitments. The family

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