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  • Cost-efficient custom text-to-SQL using Amazon Nova Micro and Amazon Bedrock on-demand inference

    calendar Apr 16, 2026 · aws.amazon.com/blogs/machine-learning
    Cost-efficient custom text-to-SQL using Amazon Nova Micro and Amazon Bedrock on-demand inference

    In this post, we demonstrate two approaches to fine-tune Amazon Nova Micro for custom SQL dialect generation to deliver both cost efficiency and production ready performance. Link to article: …


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  • Transform retail with AWS generative AI services

    calendar Apr 16, 2026 · aws.amazon.com/blogs/machine-learning
    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 …


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  • How Automated Reasoning checks in Amazon Bedrock transform generative AI compliance

    calendar Apr 16, 2026 · aws.amazon.com/blogs/machine-learning
    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, …


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  • Create rich, custom tooltips in Amazon Quick Sight

    calendar Apr 15, 2026 · aws.amazon.com/blogs/machine-learning
    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 …


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

    calendar Apr 15, 2026 · aws.amazon.com/blogs/machine-learning
    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. Link to article: https://aws.amazon.com/blogs/machine-learning/accelerating-decode-heavy-llm-inference-with-speculative-decoding-on-aws-trainium-and-vllm/


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

    calendar Apr 15, 2026 · aws.amazon.com/blogs/machine-learning
    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 …


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

    calendar Apr 14, 2026 · aws.amazon.com/blogs/machine-learning
    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. Link to article: …


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  • Use-case based deployments on SageMaker JumpStart

    calendar Apr 14, 2026 · aws.amazon.com/blogs/machine-learning
    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 …


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  • Best practices to run inference on Amazon SageMaker HyperPod

    calendar Apr 14, 2026 · aws.amazon.com/blogs/machine-learning
    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 …


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

    calendar Apr 14, 2026 · aws.amazon.com/blogs/machine-learning
    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, …


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  • Spring AI SDK for Amazon Bedrock AgentCore is now Generally Available

    calendar Apr 14, 2026 · aws.amazon.com/blogs/machine-learning
    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, …


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

    calendar Apr 13, 2026 · aws.amazon.com/blogs/machine-learning
    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 …


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