Category: HAQM Machine Learning

For this post, we implement a RAG architecture with HAQM Bedrock Knowledge Bases using a custom connector and topics built with HAQM Managed Streaming for Apache Kafka (HAQM MSK) for a user who may be interested to understand stock price trends.

In this post, we explore how QyrusAI and HAQM Bedrock are revolutionizing shift-left testing, enabling teams to deliver better software faster. HAQM Bedrock is a fully managed service that allows businesses to build and scale generative AI applications using foundation models (FMs) from leading AI providers. It enables seamless integration with AWS services, offering customization, security, and scalability without managing infrastructure.

HAQM Bedrock Data Automation (BDA) is a new managed feature powered by FMs in HAQM Bedrock. BDA extracts structured outputs from unstructured content—including documents, images, video, and audio—while alleviating the need for complex custom workflows. In this post, we demonstrate how BDA automatically extracts rich video insights such as chapter segments and audio segments, detects text in scenes, and classifies Interactive Advertising Bureau (IAB) taxonomies, and then uses these insights to build a nonlinear ads solution to enhance contextual advertising effectiveness.

In this post, we demonstrate how to orchestrate multiple HAQM Bedrock agents to create a sophisticated HAQM EKS troubleshooting system. By enabling collaboration between specialized agents—deriving insights from K8sGPT and performing actions through the ArgoCD framework—you can build a comprehensive automation that identifies, analyzes, and resolves cluster issues with minimal human intervention.

In this post, we present a solution using generative AI and large language models (LLMs) to alleviate the time-consuming and labor-intensive tasks required to build a computer vision application, enabling you to immediately start taking pictures of your asset labels and extract the necessary information to update the inventory using AWS services

The collaboration between Clario and AWS demonstrated the potential of AWS AI and machine learning (AI/ML) services and generative AI models, such as Anthropic’s Claude, to streamline document generation processes in the life sciences industry and, specifically, for complicated clinical trial processes.

This post demonstrates how to integrate open-source multi-agent framework, LangGraph, with HAQM Bedrock. It explains how to use LangGraph and HAQM Bedrock to build powerful, interactive multi-agent applications that use graph-based orchestration.

This post demonstrates how enterprises can implement a scalable agentic text-to-SQL solution using HAQM Bedrock Agents, with advanced error-handling tools and automated schema discovery to enhance database query efficiency.

This post describes how the AWS Customer Channel Technology – Localization Team worked with TransPerfect to integrate HAQM Bedrock into the GlobalLink translation management system, a cloud-based solution designed to help organizations manage their multilingual content and translation workflows. Organizations use TransPerfect’s solution to rapidly create and deploy content at scale in multiple languages using AI.

In this post, we explore the challenges of large-scale frontier model training, focusing on hardware failures and the benefits of HAQM SageMaker HyperPod – a solution that minimizes disruptions, enhances efficiency, and reduces training costs.