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1. Cost-effective multilingual audio transcription at scale with Parakeet-TDT and AWS Batch

   In this post, we walk through building a scalable, event-driven transcription pipeline that automatically processes audio files uploaded to Amazon Simple Storage Service (Amazon S3), and show you how to use Amazon EC2 Spot Instances and buffered streaming inference to further reduce costs.

2. Amazon SageMaker AI now supports optimized generative AI inference recommendations

   Today, Amazon SageMaker AI  supports optimized generative AI inference recommendations. By delivering validated, optimal deployment configurations with performance metrics, Amazon SageMaker AI keeps your model developers focused on building accurate models, not managing infrastructure.

3. Get to your first working agent in minutes: Announcing new features in Amazon Bedrock AgentCore

   Today, we're introducing new capabilities that further streamline the agent building experience, removing the infrastructure barriers that slow teams down at every stage of agent development from the first prototype through production deployment.

4. Company-wise memory in Amazon Bedrock with Amazon Neptune and Mem0

   Company-wise memory in Amazon Bedrock, powered by Amazon Neptune and Mem0, provides AI agents with persistent, company-specific context—enabling them to learn, adapt, and respond intelligently across multiple interactions. TrendMicro, one of the largest antivirus software companies in the world, developed the Trend’s Companion chatbot, so their customers can explore information through natural,...

5. From developer desks to the whole organization: Running Claude Cowork in Amazon Bedrock

   Today, we're excited to announce Claude Cowork in Amazon Bedrock. You can now run Cowork and Claude Code Desktop through Amazon Bedrock, directly or using an LLM gateway. In this post, we walk through how Claude Cowork integrates with Amazon Bedrock and show an example of how knowledge workers use it in practice.

6. End-to-end lineage with DVC and Amazon SageMaker AI MLflow apps

   In this post, we show how to combine DVC (Data Version Control), Amazon SageMaker AI, and Amazon SageMaker AI MLflow Apps to build end-to-end ML model lineage. We walk through two deployable patterns — dataset-level lineage and record-level lineage — that you can run in your own AWS account using the companion notebooks.

7. Accelerate Generative AI Inference on Amazon SageMaker AI with G7e Instances

   Today, we are thrilled to announce the availability of G7e instances powered by NVIDIA RTX PRO 6000 Blackwell Server Edition GPUs on Amazon SageMaker AI. You can provision nodes with 1, 2, 4, and 8 RTX PRO 6000 GPU instances, with each GPU providing 96 GB of GDDR7 memory. This launch provides the capability to use a single-node GPU, G7e.2xlarge instance to host powerful open source foundation...

8. ToolSimulator: scalable tool testing for AI agents

   You can use ToolSimulator, an LLM-powered tool simulation framework within Strands Evals, to thoroughly and safely test AI agents that rely on external tools, at scale. Instead of risking live API calls that expose personally identifiable information (PII), trigger unintended actions, or settling for static mocks that break with multi-turn workflows, you can use ToolSimulator's large...

9. Omnichannel ordering with Amazon Bedrock AgentCore and Amazon Nova 2 Sonic

   In this post, we'll show you how to build a complete omnichannel ordering system using Amazon Bedrock AgentCore, an agentic platform, to build, deploy, and operate highly effective AI agents securely at scale using any framework and foundation model and Amazon Nova 2 Sonic.

10. Introducing granular cost attribution for Amazon Bedrock

    In this post, we share how Amazon Bedrock's granular cost attribution works and walk through example cost tracking scenarios.