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Accelerate Generative AI Inference on Amazon SageMaker AI with G7e Instances

Accelerate Generative AI Inference on Amazon SageMaker AI with G7e Instances

As the demand for generative AI continues to grow, developers and enterprises seek more flexible, cost-effective, and powerful accelerators to meet their needs. 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, …

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ToolSimulator: scalable tool testing for AI agents

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 …

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Omnichannel ordering with Amazon Bedrock AgentCore and Amazon Nova 2 Sonic

Omnichannel ordering with Amazon Bedrock AgentCore and Amazon Nova 2 Sonic

Introduction Building a voice-enabled ordering system that works across mobile apps, websites, and voice interfaces (an omnichannel approach) presents real challenges. You need to process bidirectional audio streams, maintain conversation context across multiple turns, integrate backend services without tight coupling, and scale to handle peak traffic. In this post, we’ll show you how to build …

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Introducing granular cost attribution for Amazon Bedrock

Introducing granular cost attribution for Amazon Bedrock

As AI inference grows into a significant share of cloud spend, understanding who and what are driving costs is essential for chargebacks, cost optimization, and financial planning. Today, we’re announcing granular cost attribution for Amazon Bedrock inference. Amazon Bedrock now automatically attributes inference costs to the IAM principal that made the call. An IAM principal …

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Optimize video semantic search intent with Amazon Nova Model Distillation on Amazon Bedrock

Optimize video semantic search intent with Amazon Nova Model Distillation on Amazon Bedrock

Optimizing models for video semantic search requires balancing accuracy, cost, and latency. Faster, smaller models lack routing intelligence, while larger, accurate models add significant latency overhead. In Part 1 of this series, we showed how to build a multimodal video semantic search system on AWS with intelligent intent routing using the Anthropic Claude Haiku model …

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Power video semantic search with Amazon Nova Multimodal Embeddings

Power video semantic search with Amazon Nova Multimodal Embeddings

Video semantic search is unlocking new value across industries. The demand for video-first experiences is reshaping how organizations deliver content, and customers expect fast, accurate access to specific moments within video. For example, sports broadcasters need to surface the exact moment a player scored to deliver highlight clips to fans instantly. Studios need to find …

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Nova Forge SDK series part 2: Practical guide to fine-tune Nova models using data mixing capabilities

Nova Forge SDK series part 2: Practical guide to fine-tune Nova models using data mixing capabilities

This hands-on guide walks through every step of fine-tuning an Amazon Nova model with the Amazon Nova Forge SDK, from data preparation to training with data mixing to evaluation, giving you a repeatable playbook you can adapt to your own use case. This is the second part in our Nova Forge SDK series, building on …

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From hours to minutes: How Agentic AI gave marketers time back for what matters

From hours to minutes: How Agentic AI gave marketers time back for what matters

Your marketing team loses hours to page assembly, coordination emails, and review cycles. These manual workflows keep teams from their most important work: identifying what problems customers face, crafting messages that resonate, and building campaigns that drive meaningful engagement. In this post, we share how AWS Marketing’s Technology, AI, and Analytics (TAA) team worked with …

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

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

Text-to-SQL generation remains a persistent challenge in enterprise AI applications, particularly when working with custom SQL dialects or domain-specific database schemas. While foundation models (FMs) demonstrate strong performance on standard SQL, achieving production-grade accuracy for specialized dialects requires fine-tuning. However, fine-tuning introduces an operational trade-off: hosting custom models on persistent infrastructure incurs continuous costs, even during …

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