Category: Amazon SageMaker

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.

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.

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.

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.

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.

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.

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.

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.

The Amazon Web Services (AWS) Open Data Sponsorship Program makes high-value, cloud-optimized datasets publicly available on AWS. Through this program, customers are making more than 100 petabytes (PB) of high-value, cloud-optimized data available for public use. Read this blog post to learn about the 34 new or updated datasets that were released in the first quarter.

Amazon Web Services (AWS) employs project management principles to deliver public sector cloud outcomes. These principles drive successful service launches, new solutions, and workload migrations. Read this blog post to learn about the project management tools, references, and AWS Management Console tips that give public sector customers better project visibility, automate task management, and help accelerate project outcomes.