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Category: Machine learning

March 30, 2026Machine learning

Deliver hyper-personalized viewer experiences with an agentic AI movie assistant using Amazon Bedrock AgentCore and Amazon Nova Sonic 2.0

Deliver hyperpersonalized viewer experiences with an agentic AI movie assistant using Amazon […]

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March 30, 2026Machine learning

Build a solar flare detection system on SageMaker AI LSTM networks and ESA STIX data

The effective monitoring and characterization of solar flares demands sophisticated analysis of […]

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March 26, 2026Machine learning

Run Generative AI inference with Amazon Bedrock in Asia Pacific (New Zealand)

Kia ora! Customers in New Zealand have been asking for access to […]

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March 26, 2026Machine learning

Introducing Amazon Polly Bidirectional Streaming: Real-time speech synthesis for conversational AI

Building natural conversational experiences requires speech synthesis that keeps pace with real-time […]

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March 26, 2026Machine learning

Accelerating LLM fine-tuning with unstructured data using SageMaker Unified Studio and S3

Last year, AWS announced an integration between Amazon SageMaker Unified Studio and […]

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March 26, 2026Machine learning

Building age-responsive, context-aware AI with Amazon Bedrock Guardrails

As you deploy generative AI applications to diverse user groups, you might […]

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March 25, 2026Machine learning

Deploy voice agents with Pipecat and Amazon Bedrock AgentCore Runtime – Part 1

This post is a collaboration between AWS and Pipecat. Deploying intelligent voice […]

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March 25, 2026Machine learning

Unlocking video insights at scale with Amazon Bedrock multimodal models

Video content is now everywhere, from security surveillance and media production to […]

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March 25, 2026Machine learning

Reinforcement fine-tuning on Amazon Bedrock with OpenAI-Compatible APIs: a technical walkthrough

In December 2025, we announced the availability of Reinforcement fine-tuning (RFT) on […]

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March 24, 2026Machine learning

Deploy SageMaker AI inference endpoints with set GPU capacity using training plans

Deploying large language models (LLMs) for inference requires reliable GPU capacity, especially […]

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