AWS Architecture Blog

Category: Artificial Intelligence

Media Analysis Architecture

Analyze media content using AWS AI services

Organizations managing large audio and video archives face significant challenges in extracting value from their media content. Consider a radio network with thousands of broadcast hours across multiple stations and the challenges they face to efficiently verify ad placements, identify interview segments, and analyze programming patterns. In this post, we demonstrate how you can automatically transform unstructured media files into searchable, analyzable content.

Edge-to-cloud architecture for real-time driver monitoring using AWS IoT, Kinesis, and ML services

Optimizing fleet operations using Amazon SageMaker AI and Amazon Bedrock

In this post, we’ll explore how to maximize the value of dashcam footage through best practices for implementing and managing Computer Vision systems in commercial fleet operations. We’ll demonstrate how to build and deploy edge-based machine learning models that provide real-time alerts for distracted driving behaviors, while effectively collecting, processing, and analyzing footage to train these AI models.

Revolutionizing agricultural knowledge management using a multi-modal LLM: A reference architecture

In this blog post, we introduce a reference architecture that offers an intelligent document digitization solution that converts handwritten notes, scanned documents, and images into editable, searchable, and accessible formats. Powered by Anthropic’s Claude 3 on Amazon Bedrock, the solution uses the sophisticated vision capabilities of LLMs to process a wide range of visual formats, preserving the original formatting while extracting text, tables, and images.

Project implementation process with architecture review checkpoints

Build and operate an effective architecture review board

In this post, we identify the components of an efficient architecture review process, define what an ARB is, and describe how to build and operate an effective enterprise ARB.

Training a call center fraud detection model for IVR calls with Amazon SageMaker Canvas

This blog post will show you how to use the power of ML to build a fraud-detection model using Amazon SageMaker Canvas, a no-code/low-code ML service that business analysts and domain experts can use to build, train, and deploy ML models without requiring extensive ML expertise.

Top 10

Top Architecture Blog Posts of 2024

Well, it’s been another historic year! We’ve watched in awe as the use of real-world generative AI has changed the tech landscape, and while we at the Architecture Blog happily participated, we also made every effort to stay true to our channel’s original scope, and your readership this last year has proven that decision was […]