AWS Public Sector Blog
Category: Amazon Simple Storage Service (S3)
Univ. of Pittsburgh Athletics use AWS to unlock data insights for every step of the fan journey
The University of Pittsburgh Athletics Department wanted to know more about its fans, so it looked for an innovative solution and turned to Amazon Web Services (AWS). By focusing on fan behavior and seeking out trends in ticket sales, the department hoped to answer questions surrounding team loyalty and how they could stay competitive. This post provides an overview of the powerful solution Pitt Athletics built to engage with and sell to its fanbase.
Building NHM London’s Planetary Knowledge Base with Amazon Neptune and the Registry of Open Data on AWS
The Natural History Museum in London is a world-class visitor attraction and a leading science research center. NHM and Amazon Web Services (AWS) have worked together to transform and accelerate scientific research by bringing together a broad range of UK biodiversity and environmental data types in one place for the first time. In this post, the first in a two-part series, we provide an overview of the NHM-AWS project and the potential research benefits.
Use modular architecture for flexible and extensible RAG-based generative AI solutions
In this post, we cover an Amazon Web Services (AWS) Cloud infrastructure with a modular architecture that enables you to explore and take advantage of the benefits from different Retrieval-Augmented Generation (RAG)-based generative AI resources in a flexible way. This solution provides several benefits, along with faster time-to-market and shorter development cycles.
Use Landing Zone Accelerator on AWS customizations to deploy Cloud Intelligence Dashboards
In this post, you will learn how to deploy Amazon Web Services (AWS) Cloud Intelligence Dashboards (CID) using the Landing Zone Accelerator on AWS (LZA) solution. In doing so, you will learn how to customize your LZA deployment using the customizations-config.yaml file. By utilizing the LZA and CID together, you can streamline the deployment process, ensure compliance with best practices, and gain valuable insights into your cloud environment, ultimately leading to improved operational efficiency, enhanced security, and better-informed decision-making.
ICF helps FDA accelerate the drug labeling review process with AWS machine learning
Within the Food and Drug Administration’s Center for Drug Evaluation and Research, the Division of Medication Error Prevention and Analysis (DMEPA) plays a critical role. DMEPA reviews premarket and postmarket drug labeling to minimize the risk of medication errors. In partnership with DMEPA, Amazon Web Services (AWS) Partner ICF is developing a machine learning (ML) prototype known as the Computerized Labeling Assessment Tool (CLAT). The prototype employs innovative applications of optical character recognition (OCR) technology and the novel use of computer vision techniques that will alleviate bottlenecks in and enhance the efficiency of the drug labeling review process.
AWS Partner Kokomo24/7 transforms Los Angeles Unified School District’s health data system in one year
Kokomo24/7 is a health and safety software education technology (EdTech) platform committed to creating safer schools and communities. Kokomo used Amazon Web Services (AWS) database and analytics tools to create a health-tracking platform that allowed the Los Angeles Unified School District (LAUSD), the second-largest school district in the US, to cut its costs by 50 percent while improving flexibility and response times.
Germany’s International University of Applied Sciences automates creation of educational videos using generative AI, serverless on AWS
The International University of Applied Sciences (IU) maintains 90 percent of its course content online. Through its online programs, IU aims to give people worldwide access to highly individualized education, enabling them to further enrich their lives. The large majority of IU’s infrastructure runs on Amazon Web Services (AWS). Read this post to learn why IU worked directly with AWS experts through the Experience-Based Acceleration (EBA) program to expand their automated video generation pipelines to be more scalable, modular, and robust.
Unlocking data governance for multiple accounts with Amazon DataZone
This post discusses how Amazon Web Services (AWS) can help you successfully set up an Amazon DataZone domain, aggregate data from multiple sources into a single centralized environment, and perform analytics on that data. Additionally, this post provides a sample architecture as well as a walkthrough on how to set up that architecture. Ultimately, this post serves as a valuable resource if you’re seeking to optimize your data management processes and derive actionable insights to drive business growth.
Deploy LLMs in AWS GovCloud (US) Regions using Hugging Face Inference Containers
Government agencies are increasingly using large language models (LLMs) powered by generative artificial intelligence (AI) to extract valuable insights from their data in the Amazon Web Services (AWS) GovCloud (US) Regions. In this guide, we walk you through the process of hosting LLMs on Amazon Elastic Compute Cloud (Amazon EC2) instances, using the Hugging Face Text Generation Inference (TGI) Container (TGI) for serving custom LLMs.
ASTERRA helps build a more sustainable Earth by identifying and mitigating ‘lost water’ using AWS
ASTERRA, an Israel-based geospatial and Earth observation company, uses Amazon Web Services (AWS) to help water utilities and a number of industries identify and mitigate pipeline leaks. ASTERRA uses AWS to derive intelligence and insights from beneath the surface of their largest installations and to bypass the need to break ground and dig for leaks. Read this post to learn how AWS has helped ASTERRA overcome traditional on-premises infrastructure limitations and to accelerate the development of solutions for anticipating and mitigating failures, saving water, energy, and avoiding carbon dioxide (CO2) emissions as a result.