AWS Machine Learning Blog
Category: Case Study
Fast-track SOP processing using Amazon Bedrock
When a regulatory body like the US Food and Drug Administration (FDA) introduces changes to regulations, organizations are required to evaluate the changes against their internal SOPs. When necessary, they must update their SOPs to align with the regulation changes and maintain compliance. In this post, we show different approaches using Amazon Bedrock to identify relationships between regulation changes and SOPs.
GuardianGamer scales family-safe cloud gaming with AWS
In this post, we share how GuardianGamer uses AWS services including Amazon Nova and Amazon Bedrock to deliver a scalable and efficient supervision platform. The team uses Amazon Nova for intelligent narrative generation to provide parents with meaningful insights into their children’s gaming activities and social interactions, while maintaining a non-intrusive approach to monitoring.
How Clearwater Analytics is revolutionizing investment management with generative AI and Amazon SageMaker JumpStart
In this post, we explore Clearwater Analytics’ foray into generative AI, how they’ve architected their solution with Amazon SageMaker, and dive deep into how Clearwater Analytics is using LLMs to take advantage of more than 18 years of experience within the investment management domain while optimizing model cost and performance.
How Amazon Music uses SageMaker with NVIDIA to optimize ML training and inference performance and cost
In the dynamic world of streaming on Amazon Music, every search for a song, podcast, or playlist holds a story, a mood, or a flood of emotions waiting to be unveiled. These searches serve as a gateway to new discoveries, cherished experiences, and lasting memories. The search bar is not just about finding a song; […]
MDaudit uses AI to improve revenue outcomes for healthcare customers
MDaudit provides a cloud-based billing compliance and revenue integrity software as a service (SaaS) platform to more than 70,000 healthcare providers and 1,500 healthcare facilities, ensuring healthcare customers maintain regulatory compliance and retain revenue. Working with the top 60+ US healthcare networks, MDaudit needs to be able to scale its artificial intelligence (AI) capabilities to […]
How United Airlines built a cost-efficient Optical Character Recognition active learning pipeline
In this post, we discuss how United Airlines, in collaboration with the Amazon Machine Learning Solutions Lab, build an active learning framework on AWS to automate the processing of passenger documents. “In order to deliver the best flying experience for our passengers and make our internal business process as efficient as possible, we have developed […]
How xarvio Digital Farming Solutions accelerates its development with Amazon SageMaker geospatial capabilities
This is a guest post co-written by Julian Blau, Data Scientist at xarvio Digital Farming Solutions; BASF Digital Farming GmbH, and Antonio Rodriguez, AI/ML Specialist Solutions Architect at AWS xarvio Digital Farming Solutions is a brand from BASF Digital Farming GmbH, which is part of BASF Agricultural Solutions division. xarvio Digital Farming Solutions offers precision […]
How Yara is using MLOps features of Amazon SageMaker to scale energy optimization across their ammonia plants
Learn how Yara is using Amazon SageMaker features, including the model registry, Amazon SageMaker Model Monitor, and Amazon SageMaker Pipelines to streamline the machine learning (ML) lifecycle by automating and standardizing MLOps practices. We provide an overview of the setup, showcasing the process of building, training, deploying, and monitoring ML models for plants around the globe.
LiDAR 3D point cloud labeling with Velodyne LiDAR sensor in Amazon SageMaker Ground Truth
LiDAR is a key enabling technology in growing autonomous markets, such as robotics, industrial, infrastructure, and automotive. LiDAR delivers precise 3D data about its environment in real time to provide “vision” for autonomous solutions. For autonomous vehicles (AVs), nearly every carmaker uses LiDAR to augment camera and radar systems for a comprehensive perception stack capable […]
How Cepsa used Amazon SageMaker and AWS Step Functions to industrialize their ML projects and operate their models at scale
This blog post is co-authored by Guillermo Ribeiro, Sr. Data Scientist at Cepsa. Machine learning (ML) has rapidly evolved from being a fashionable trend emerging from academic environments and innovation departments to becoming a key means to deliver value across businesses in every industry. This transition from experiments in laboratories to solving real-world problems in […]