AWS Public Sector Blog
Category: Amazon SageMaker
Fine-tuning an LLM using QLoRA in AWS GovCloud (US)
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 adapting LLMs to specific domains with parameter efficient fine-tuning techniques made accessible through Amazon SageMaker integrations with Hugging Face.
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 Amazon SageMaker to perform data analytics in AWS GovCloud (US) Regions
Amazon SageMaker is a fully managed machine learning (ML) service that provides various capabilities, including Jupyter Notebook instances. While RStudio, a popular integrated development environment (IDE) for R, is available as a managed service in Amazon Web Services (AWS) commercial Regions, it’s currently not offered in AWS GovCloud (US) Regions. Read this post, however, to learn how you can use SageMaker notebook instances with the R kernel to perform data analytics tasks in AWS GovCloud (US) Regions.
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.
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.
Health Electrification and Telecommunications Alliance works with AWS to electrify health facilities in sub-Saharan Africa
The Health Electrification and Telecommunications Alliance (HETA) is Power Africa’s initiative for health facility electrification and digital connectivity in sub-Saharan Africa. Power Africa is part of the United States Agency for International Development (USAID) and harnesses the collective resources of public and private sectors to expand electricity in sub-Saharan Africa. This post describes how AWS and HETA bring together governments, donors, technology providers, and health organizations to develop sustainable business models that can electrify and digitally connect healthcare infrastructure.
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.
The transformative power of generative artificial intelligence for the public sector
Applications and user experiences are poised to be reinvented with generative artificial intelligence (AI), and the public sector is no exception. Governments, education institutions, nonprofits, and health systems must constantly adapt and innovate to meet the changing needs of their constituents, students, beneficiaries, and patients. If used responsibly, this powerful technology can open doors to endless possibilities to increase creativity, productivity, and progress.
UC Davis Health Cloud Innovation Center, powered by AWS, uses generative AI to fight health misinformation
The University of Pittsburgh, the University of Illinois Urbana-Champaign (UIUC), the University of California Davis Health Cloud Innovation Center (UCDH CIC)—powered by Amazon Web Services (AWS)—and the AWS Digital Innovation (DI) team have built a prototype that uses machine learning (ML) and generative artificial intelligence (AI) to transform the public health communications landscape by giving officials the tools they need to fight medical misinformation, disinformation, and malinformation.
New AWS survey reveals the link between AI fluency and the next education revolution
Access Partnership recently conducted a study commissioned by Amazon Web Services (AWS) on AI skills across various industries globally—including education. The study found that employers and employees in the education sector anticipate that AI utilization will improve productivity by more than one-third. Read this post to learn more about this finding, and others, and what it means for the education sector.