Artificial Intelligence
Category: Advanced (300)
Human-in-the-loop constructs for agentic workflows in healthcare and life sciences
In healthcare and life sciences, AI agents help organizations process clinical data, submit regulatory filings, automate medical coding, and accelerate drug development and commercialization. However, the sensitive nature of healthcare data and regulatory requirements like Good Practice (GxP) compliance require human oversight at key decision points. This is where human-in-the-loop (HITL) constructs become essential. In this post, you will learn four practical approaches to implementing human-in-the-loop constructs using AWS services.
Building intelligent audio search with Amazon Nova Embeddings: A deep dive into semantic audio understanding
This post walks you through understanding audio embeddings, implementing Amazon Nova Multimodal Embeddings, and building a practical search system for your audio content. You’ll learn how embeddings represent audio as vectors, explore the technical capabilities of Amazon Nova, and see hands-on code examples for indexing and querying your audio libraries. By the end, you’ll have the knowledge to deploy production-ready audio search capabilities.
Manage AI costs with Amazon Bedrock Projects
With Amazon Bedrock Projects, you can attribute inference costs to specific workloads and analyze them in AWS Cost Explorer and AWS Data Exports. In this post, you will learn how to set up Projects end-to-end, from designing a tagging strategy to analyzing costs.
Building real-time conversational podcasts with Amazon Nova 2 Sonic
This post walks through building an automated podcast generator that creates engaging conversations between two AI hosts on any topic, demonstrating the streaming capabilities of Nova Sonic, stage-aware content filtering, and real-time audio generation.
Accelerate agentic tool calling with serverless model customization in Amazon SageMaker AI
In this post, we walk through how we fine-tuned Qwen 2.5 7B Instruct for tool calling using RLVR. We cover dataset preparation across three distinct agent behaviors, reward function design with tiered scoring, training configuration and results interpretation, evaluation on held-out data with unseen tools, and deployment.
Building Intelligent Search with Amazon Bedrock and Amazon OpenSearch for hybrid RAG solutions
In this post, we show how to implement a generative AI agentic assistant that uses both semantic and text-based search using Amazon Bedrock, Amazon Bedrock AgentCore, Strands Agents and Amazon OpenSearch.
From isolated alerts to contextual intelligence: Agentic maritime anomaly analysis with generative AI
This blog post demonstrates how Windward helps enhance and accelerate alert investigation processes by combining geospatial intelligence with generative AI, enabling analysts to focus on decision-making rather than data collection.
Simulate realistic users to evaluate multi-turn AI agents in Strands Evals
In this post, we explore how ActorSimulator in Strands Evaluations SDK addresses the challenge with structured user simulation that integrates into your evaluation pipeline.
Scaling seismic foundation models on AWS: Distributed training with Amazon SageMaker HyperPod and expanding context windows
This post describes how TGS achieved near-linear scaling for distributed training and expanded context windows for their Vision Transformer-based SFM using Amazon SageMaker HyperPod. This joint solution cut training time from 6 months to just 5 days while enabling analysis of seismic volumes larger than previously possible.
Control which domains your AI agents can access
In this post, we show you how to configure AWS Network Firewall to restrict AgentCore resources to an allowlist of approved internet domains. This post focuses on domain-level filtering using SNI inspection — the first layer of a defense-in-depth approach.









