Category: Amazon Machine Learning

In this post, we will explore the use of generative artificial intelligence (AI) chatbots as a natural language alternative to the service catalog approach. We will present an Amazon Web Services (AWS) architecture pattern to deploy an AI chatbot that can understand user requests in natural language and provide interactive responses to user requests, directing them to the specific systems or services they are looking for. Chatbots simplify the content navigation and discovery process while improving the customer experience.

In this post, we explore the complexities of data privacy and controls on Amazon Web Services (AWS), examine how creating a landing zone within which to contain such data is important, and highlight the differences between creating a landing zone from scratch compared with using the AWS Landing Zone Accelerator (LZA) for Healthcare. To aid explanation, we use a simple healthcare workload as an example. We also explain how LZA for Healthcare codifies HIPAA controls and AWS Security Best Practices to accelerate the creation of an environment to run protective health information workloads in 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.

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.

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.

From check-in through departure to the airfield and then back through the baggage halls, technology can transform the experience of airport passengers, partners, and staff. The UK’s Manchester Airports Group (MAG), which runs Manchester, London Stansted, and East Midlands airports, invests in this transformation. Read this post to learn how MAG has created a technology and data strategy in collaboration with Amazon Web Services (AWS) to integrate the elements of its complex ecosystems and deliver efficiencies.

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.

City Colleges of Chicago (CCC)—the largest community college system in Illinois and one of the largest in the nation—participates in two no-cost Amazon Web Services (AWS) initiatives to advance and develop undergraduate technical programs. The AWS Machine Learning University Educator Enablement Program (MLU EEP) and the Skills to Jobs Tech Alliance connect early career talent to in-demand technical jobs globally, including in Illinois. Read this post to learn more.

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.