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Home/News

News & Analysis

Editorial coverage, in-depth analysis, and developer guides — 38 articles.

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  • NewsNewsAmazon (AWS)

    Transform retail with AWS generative AI services

    Online retailers face a persistent challenge: shoppers struggle to determine the fit and look when ordering online, leading to increased returns and decreased purchase confidence. The cost? Lost revenue, operational overhead, and customer frustration. Meanwhile, consumers increasingly expect immersive, interactive shopping experiences that bridge the gap between online and in-store retail. Retailers implementing virtual try-on […]

    Amazon (AWS)Official RSSOriginal article ↗Feed source ↗Trust notes →
    Apr 16, 2026Bhavya Chugh
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  • NewsNewsAmazon (AWS)

Tags

#AWS Lambda#AWS Trainium#Advanced (300)#Amazon API Gateway#Amazon Bedrock#Amazon Bedrock AgentCore#Amazon Elastic Kubernetes Service#Amazon Machine Learning#Amazon Nova#Amazon OpenSearch Service
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How Automated Reasoning checks in Amazon Bedrock transform generative AI compliance

In this post, you'll learn why probabilistic AI validation falls short in regulated industries and how Automated Reasoning checks use formal verification to deliver mathematically proven results. You'll also see how customers across six industries use this technology to produce formally verified, auditable AI outputs, and how to get started.

Amazon (AWS)Official RSSOriginal article ↗Feed source ↗Trust notes →
Apr 16, 2026Nafi Diallo
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  • NewsNewsAmazon (AWS)

    Create rich, custom tooltips in Amazon Quick Sight

    Today, we're announcing sheet tooltips in Amazon Quick Sight. Dashboard authors can now design custom tooltip layouts using free-form layout sheets. These layouts combine charts, key performance indicator (KPI) metrics, text, and other visuals into a single tooltip that renders dynamically when readers hover over data points.

    Amazon (AWS)Official RSSOriginal article ↗Feed source ↗Trust notes →
    Apr 15, 2026Meshan Khosla
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  • NewsNewsAmazon (AWS)

    Accelerating decode-heavy LLM inference with speculative decoding on AWS Trainium and vLLM

    In this post, you will learn how speculative decoding works and why it helps reduce cost per generated token on AWS Trainium2.

    Amazon (AWS)Official RSSOriginal article ↗Feed source ↗Trust notes →
    Apr 15, 2026Yahav Biran
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  • NewsNewsAmazon (AWS)

    Rede Mater Dei de Saúde: Monitoring AI agents in the revenue cycle with Amazon Bedrock AgentCore

    This post is cowritten by Renata Salvador Grande, Gabriel Bueno and Paulo Laurentys at Rede Mater Dei de Saúde. The growing adoption of multi-agent AI systems is redefining critical operations in healthcare. In large hospital networks, where thousands of decisions directly impact cash flow, service delivery times, and the risk of claim denials, the ability […]

    Amazon (AWS)Official RSSOriginal article ↗Feed source ↗Trust notes →
    Apr 15, 2026Renata Salvador Grande
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  • NewsNewsAmazon (AWS)

    Navigating the generative AI journey: The Path-to-Value framework from AWS

    In this post, we introduce the Generative AI Path-to-Value (P2V) framework, a structured approach to help you move generative AI initiatives from concept to production and sustained value creation.

    Amazon (AWS)Official RSSOriginal article ↗Feed source ↗Trust notes →
    Apr 14, 2026Nitin Eusebius
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  • NewsNewsAmazon (AWS)

    Use-case based deployments on SageMaker JumpStart

    We're excited to announce the launch of Amazon SageMaker JumpStart optimized deployments. SageMaker JumpStart improved deployments address the need for rich and straightforward deployment customization on SageMaker JumpStart by offering pre-defined deployment configurations, designed for specific use cases. Customers maintain the same level of visibility into the details of their proposed deployments, but now deployments are optimized for their specific use case and performance constraint.

    Amazon (AWS)Official RSSOriginal article ↗Feed source ↗Trust notes →
    Apr 14, 2026Dan Ferguson
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  • NewsNewsAmazon (AWS)

    Best practices to run inference on Amazon SageMaker HyperPod

    This post explores how Amazon SageMaker HyperPod provides a comprehensive solution for inference workloads. We walk you through the platform’s key capabilities for dynamic scaling, simplified deployment, and intelligent resource management. By the end of this post, you’ll understand how to use the HyperPod automated infrastructure, cost optimization features, and performance enhancements to reduce your total cost of ownership by up to 40% while accelerating your generative AI deployments from concept to production.

    Amazon (AWS)Official RSSOriginal article ↗Feed source ↗Trust notes →
    Apr 14, 2026Vinay Arora
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  • NewsNewsAmazon (AWS)

    How Guidesly built AI-generated trip reports for outdoor guides on AWS

    In this post, we walk through how Guidesly built Jack AI on AWS using AWS Lambda, AWS Step Functions, Amazon Simple Storage Service (Amazon S3), Amazon Relational Database Service (Amazon RDS), Amazon SageMaker AI, and Amazon Bedrock to ingest trip media, enrich it with context, apply computer vision and generative AI, and publish marketing-ready content across multiple channels—securely, reliably, and at scale.

    Amazon (AWS)Official RSSOriginal article ↗Feed source ↗Trust notes →
    Apr 14, 2026David Lord, Taylor Lord, Shiva Prasad, Anup Banasavalli Hiriyanagowda, Nikhil Chandra
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  • NewsNewsAmazon (AWS)

    Spring AI SDK for Amazon Bedrock AgentCore is now Generally Available

    With the new Spring AI AgentCore SDK, you can build production-ready AI agents and run them on the highly scalable AgentCore Runtime. The Spring AI AgentCore SDK is an open source library that brings Amazon Bedrock AgentCore capabilities into Spring AI. In this post, we build an AI agent starting with a chat endpoint, then adding streaming responses, conversation memory, and tools for web browsing and code execution.

    Amazon (AWS)Official RSSOriginal article ↗Feed source ↗Trust notes →
    Apr 14, 2026Andrei Shakirin
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  • NewsNewsAmazon (AWS)

    How to build effective reward functions with AWS Lambda for Amazon Nova model customization

    This post demonstrates how Lambda enables scalable, cost-effective reward functions for Amazon Nova customization. You'll learn to choose between Reinforcement Learning via Verifiable Rewards (RLVR) for objectively verifiable tasks and Reinforcement Learning via AI Feedback (RLAIF) for subjective evaluation, design multi-dimensional reward systems that help you prevent reward hacking, optimize Lambda functions for training scale, and monitor reward distributions with Amazon CloudWatch. Working code examples and deployment guidance are included to help you start experimenting.

    Amazon (AWS)Official RSSOriginal article ↗Feed source ↗Trust notes →
    Apr 13, 2026Manoj Gupta
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  • NewsNewsAmazon (AWS)

    Understanding Amazon Bedrock model lifecycle

    This post shows you how to manage FM transitions in Amazon Bedrock, so you can make sure your AI applications remain operational as models evolve. We discuss the three lifecycle states, how to plan migrations with the new extended access feature, and practical strategies to transition your applications to newer models without disruption.

    Amazon (AWS)Official RSSOriginal article ↗Feed source ↗Trust notes →
    Apr 9, 2026Saurabh Trikande
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  • #Amazon Quick Sight
    #Amazon RDS
    #Amazon Rekognition
    #Amazon SageMaker
    #Amazon SageMaker Autopilot
    #Amazon SageMaker HyperPod
    #Amazon SageMaker JumpStart
    #Amazon Simple Notification Service (SNS)
    #Announcements
    #Artificial Intelligence
    #Best Practices
    #Business Intelligence
    #Compute
    #Customer Solutions
    #Foundational (100)
    #Generative AI
    #Healthcare
    #Intermediate (200)
    #Java
    #Responsible AI
    #Technical How-to