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1. Unlocking video insights at scale with Amazon Bedrock multimodal models

   In this post, we explore how the multimodal foundation models (FMs) of Amazon Bedrock enable scalable video understanding through three distinct architectural approaches. Each approach is designed for different use cases and cost-performance trade-offs.

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

   In this series of posts, you will learn how streaming architectures help address these challenges using Pipecat voice agents on Amazon Bedrock AgentCore Runtime. In Part 1, you will learn how to deploy Pipecat voice agents on AgentCore Runtime using different network transport approaches including WebSockets, WebRTC and telephony integration, with practical deployment guidance and code samples.

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

   In this post, we walk through the end-to-end workflow of using RFT on Amazon Bedrock with OpenAI-compatible APIs: from setting up authentication, to deploying a Lambda-based reward function, to kicking off a training job and running on-demand inference on your fine-tuned model.

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

   In this post, we walk through how to search for available p-family GPU capacity, create a training plan reservation for inference, and deploy a SageMaker AI inference endpoint on that reserved capacity. We follow a data scientist's journey as they reserve capacity for model evaluation and manage the endpoint throughout the reservation lifecycle.

5. Accelerating custom entity recognition with Claude tool use in Amazon Bedrock

   This post introduces Claude Tool use in Amazon Bedrock which uses the power of large language models (LLMs) to perform dynamic, adaptable entity recognition without extensive setup or training.

6. How Reco transforms security alerts using Amazon Bedrock

   In this blog post, we show you how Reco implemented Amazon Bedrock to help transform security alerts and achieve significant improvements in incident response times.

7. Integrating Amazon Bedrock AgentCore with Slack

   In this post, we demonstrate how to build a Slack integration using AWS Cloud Development Kit (AWS CDK). You will learn how to deploy the infrastructure with three specialized AWS Lambda functions, configure event subscriptions properly to handle Slack's security requirements, and implement conversation management patterns that work for many agent use cases.

8. Overcoming LLM hallucinations in regulated industries: Artificial Genius’s deterministic models on Amazon Nova

   In this post, we’re excited to showcase how AWS ISV Partner Artificial Genius is using Amazon SageMaker AI and Amazon Nova to deliver a solution that is probabilistic on input but deterministic on output, helping to enable safe, enterprise-grade adoption.

9. Run NVIDIA Nemotron 3 Super on Amazon Bedrock

   This post explores the technical characteristics of the Nemotron 3 Super model and discusses potential application use cases. It also provides technical guidance to get started using this model for your generative AI applications within the Amazon Bedrock environment.

10. Use RAG for video generation using Amazon Bedrock and Amazon Nova Reel

    In this post, we explore our approach to video generation through VRAG, transforming natural language text prompts and images into grounded, high-quality videos. Through this fully automated solution, you can generate realistic, AI-powered video sequences from structured text and image inputs, streamlining the video creation process.