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  • Secure short-term GPU capacity for ML workloads with EC2 Capacity Blocks for ML and SageMaker training plans

    calendar May 7, 2026 · aws.amazon.com/blogs/machine-learning
    Secure short-term GPU capacity for ML workloads with EC2 Capacity Blocks for ML and SageMaker training plans

    In this post, you will learn how to secure reserved GPU capacity for short-term workloads using Amazon Elastic Compute Cloud (Amazon EC2) Capacity Blocks for ML and Amazon SageMaker training plans. These solutions can address GPU availability challenges when you need short-term capacity for load testing, model …


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  • Overcoming reward signal challenges: Verifiable rewards-based reinforcement learning with GRPO on SageMaker AI

    calendar May 7, 2026 · aws.amazon.com/blogs/machine-learning
    Overcoming reward signal challenges: Verifiable rewards-based reinforcement learning with GRPO on SageMaker AI

    In this post, you will learn how to implement reinforcement learning with verifiable rewards (RLVR) to introduce verification and transparency into reward signals to improve training performance. This approach works best when outputs can be objectively verified for correctness, such as in mathematical reasoning, code …


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  • Agents that transact: Introducing Amazon Bedrock AgentCore payments, built with Coinbase and Stripe

    calendar May 7, 2026 · aws.amazon.com/blogs/machine-learning
    Agents that transact: Introducing Amazon Bedrock AgentCore payments, built with Coinbase and Stripe

    Today, we're announcing a preview of Amazon Bedrock AgentCore Payments, a new set of features in Amazon Bedrock AgentCore that enables AI agents to instantly access and pay for what they use. AgentCore Payments was developed in partnership with Coinbase and Stripe. Link to article: …


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  • Cost effective deployment of vision-language models for pet behavior detection on AWS Inferentia2

    calendar May 6, 2026 · aws.amazon.com/blogs/machine-learning
    Cost effective deployment of vision-language models for pet behavior detection on AWS Inferentia2

    Tomofun, the Taiwan-headquartered pet-tech startup behind the Furbo Pet Camera, is redefining how pet owners interact with their pets remotely. To reduce costs and maintain accuracy, Tomofun turned to EC2 Inf2 instances powered by AWS Inferentia2, the Amazon purpose-built AI chips. In this post, we walk through the …


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  • How Hapag-Lloyd uses Amazon Bedrock to transform customer feedback into actionable insights

    calendar May 5, 2026 · aws.amazon.com/blogs/machine-learning
    How Hapag-Lloyd uses Amazon Bedrock to transform customer feedback into actionable insights

    Hapag-Lloyd's Digital Customer Experience and Engineering team, distributed between Hamburg and Gdańsk, drives digital innovation by developing and maintaining customer-facing web and mobile products. In this post, we walk you through our generative AI–powered feedback analysis solution built using Amazon Bedrock, …


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  • Streamlining generative AI development with MLflow v3.10 on Amazon SageMaker AI

    calendar May 5, 2026 · aws.amazon.com/blogs/machine-learning
    Streamlining generative AI development with MLflow v3.10 on Amazon SageMaker AI

    Today, we’re excited to announce that Amazon SageMaker AI MLflow Apps now support MLflow version 3.10, bringing enhanced capabilities for generative AI development and streamlined experiment tracking to your generative AI workflows. Building on the foundations established with Amazon SageMaker AI MLflow Apps, this …


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  • Introducing OS Level Actions in Amazon Bedrock AgentCore Browser

    calendar May 5, 2026 · aws.amazon.com/blogs/machine-learning
    Introducing OS Level Actions in Amazon Bedrock AgentCore Browser

    We’re announcing OS Level Actions for AgentCore Browser. This new capability unblocks these scenarios by exposing direct OS control through the InvokeBrowser API, so agents can interact with content visible on the screen, not only what's accessible through the browser's web layer. By combining full-desktop screenshots …


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  • Secure AI agents with Amazon Bedrock AgentCore Identity on Amazon ECS

    calendar May 5, 2026 · aws.amazon.com/blogs/machine-learning
    Secure AI agents with Amazon Bedrock AgentCore Identity on Amazon ECS

    AI agents in production require secure access to external services. Amazon Bedrock AgentCore Identity, available as a standalone service, secures how your AI agents access external services whether they run on compute platforms like Amazon ECS, Amazon EKS, AWS Lambda, or on-premises. This post implements Authorization …


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  • Intelligence-driven message defense and insights using Amazon Bedrock

    calendar May 5, 2026 · aws.amazon.com/blogs/machine-learning
    Intelligence-driven message defense and insights using Amazon Bedrock

    In this post, you will learn how you can use Amazon Nova Foundation Models in Amazon Bedrock to apply generative AI techniques for both business protection and enhancement. You can identify obvious and disguised attempts at direct contact while gaining valuable insights into customer sentiment and service improvement …


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  • Beyond BI: How the Dataset Q&A feature of Amazon Quick powers the next generation of data decisions

    calendar May 4, 2026 · aws.amazon.com/blogs/machine-learning
    Beyond BI: How the Dataset Q&A feature of Amazon Quick powers the next generation of data decisions

    Business leaders across industries rely on operational dashboards as the shared source of truth that their teams execute against daily. But dashboards are built to answer known questions. When teams need to explore further, ad-hoc, multi-dimensional, or unforeseen questions, they hit a bottleneck. They wait hours or …


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  • Introducing the agent performance loop: AgentCore Optimization now in preview

    calendar May 4, 2026 · aws.amazon.com/blogs/machine-learning
    Introducing the agent performance loop: AgentCore Optimization now in preview

    Generate recommendations from production traces, validate them with batch evaluation and A/B testing, and ship with confidence. AI agents that perform well at launch don’t stay that way. As models evolve, user behavior shifts, and prompts get reused in new contexts they were never designed for. Agent quality quietly …


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  • Agent-guided workflows to accelerate model customization in Amazon SageMaker AI

    calendar May 4, 2026 · aws.amazon.com/blogs/machine-learning
    Agent-guided workflows to accelerate model customization in Amazon SageMaker AI

    Amazon SageMaker AI now offers an agentic experience that changes this. Developers describe their use case using natural language, and the AI coding agent streamlines the entire journey, from use case definition and data preparation through technique selection, evaluation, and deployment. In this post, we walk you …


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  • Generate dashboards from natural language prompts in Amazon Quick

    calendar May 4, 2026 · aws.amazon.com/blogs/machine-learning
    Generate dashboards from natural language prompts in Amazon Quick

    Building meaningful dashboards demands hours of manual setup, even for experienced BI professionals. Amazon Quick now generates complete multi-sheet dashboards from natural language prompts, taking you from one or more datasets to a production-ready analysis in minutes. Data analysts building recurring operations …


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  • From data lake to AI-ready analytics: Introducing new data source with S3 Tables in Amazon Quick

    calendar May 4, 2026 · aws.amazon.com/blogs/machine-learning
    From data lake to AI-ready analytics: Introducing new data source with S3 Tables in Amazon Quick

    Amazon Quick introduces Amazon S3 Tables (Apache Iceberg tables) as a new data source. With this feature, customers can directly query and visualize Apache Iceberg tables stored in an Amazon S3 table bucket without the need for intermediate data layers. In this post, we explored how Amazon Quick’s new Amazon S3 Tables …


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  • Introducing Dataset Q&A: Expanding natural language querying for structured datasets in Amazon Quick

    calendar May 4, 2026 · aws.amazon.com/blogs/machine-learning
    Introducing Dataset Q&A: Expanding natural language querying for structured datasets in Amazon Quick

    In this post, you learn how to get started with Dataset Q&A, explore real-world use cases with hands-on examples, and discover advanced capabilities like auto-discovery across all your data assets and multi-dataset querying in a single conversation. Link to article: …


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  • Capacity-aware inference: Automatic instance fallback for SageMaker AI endpoints

    calendar May 4, 2026 · aws.amazon.com/blogs/machine-learning
    Capacity-aware inference: Automatic instance fallback for SageMaker AI endpoints

    Today, Amazon SageMaker AI introduces capacity aware instance pool for new and existing inference endpoints. You define a prioritized list of instance types, and SageMaker AI automatically works through your list whenever capacity is constrained at creation, during scale-out, and during scale-in. Your endpoint …


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  • AWS Transform now automates BI migration to Amazon Quick in days

    calendar May 1, 2026 · aws.amazon.com/blogs/machine-learning
    AWS Transform now automates BI migration to Amazon Quick in days

    In this post, we walk through the full journey, from setting up your migration workspace in AWS Transform to subscribing to partner agents through AWS Marketplace to unlocking Amazon Quick capabilities that change how your organization consumes data. Link to article: …


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