Category: Amazon Comprehend

Like many healthcare providers, University Hospitals Coventry and Warwickshire (UHCW) NHS Trust, which manages two major hospitals and serves a population of more than one million, has operated with legacy technology that relies heavily on phone calls and manual processes for contacting patients. Recognizing an opportunity to modernize, the Trust linked up with IBM Consulting for an innovative pilot project to digitize patient engagement channels using Amazon Web Services (AWS). Read this post to learn more.

As a teacher with the KIPP charter school network in Houston, Texas, Dave Wakefield knew there had to be a better way for educators to gain insightful feedback on their instruction. Traditionally, educators who wanted feedback on their teaching either had to have someone visit their classroom or film themselves and then send that video to a mentor or peer for review. In 2013, Wakefield founded education technology (EdTech) company Sibme as a way to use technology, powered by Amazon Web Services (AWS), to help educators access quicker and more reliable feedback.

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 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.

As the daily volumes of document submissions increases for government organizations, intelligent document processing (IDP) solution architectures must absorb spikes in requests without creating delays or other impact for the users. In cases where the processing volume exceeds the limits of the resources available in an AWS Region, organizations can distribute the workloads across multiple regions to increase the document processing throughput. This post presents high-level architecture guidance built around Amazon Comprehend to create a distributed document processing workload that can overcome the challenges of unpredictable request patterns.

This fall, artist Suchi Reddy and Amazon Web Services (AWS), in collaboration with the Smithsonian FUTURES Exhibition, debuted me+you in Washington, DC, which embodies the collective answers to the question, “What do you want your future to look like?” me+you is an interactive work of art powered by artificial intelligence (AI) and machine learning (ML) and is the centerpiece of the Smithsonian FUTURES exhibition.

Since 2003, the US federal government has made approximately $1.7 trillion in improper payments, with an estimated $206 billion made in FY 2020 alone. Improper payments are now anticipated to increase proportionally to new levels of federal spending. How can agencies fight improper payments at this scale? And what tools can agencies use to address fraud, erroneous data submission and other causes of this problem? Agencies can use AWS to solve the multi-sided issues of payment integrity.

Earlier this year, the Australian Bureau of Statistics (ABS) ran the Australian Census, the agency’s most significant workload, on Amazon Web Services (AWS). The Census is the most comprehensive snapshot of the country, and includes around 10 million households and over 25 million people. With the COVID-19 pandemic causing lockdowns across the country, ABS needed a digital option for the Census that was accessible and reliable for millions of people. They turned to the cloud.

Public sector organizations want to innovate the way they engage their communities to make information easier to access, improve user experience, expand their reach by supporting multiple communication channels, and improve efficiency and scalability through intelligent automation. Conversational artificial intelligence (AI) and chatbots can be used to transform the customer experience, enhance engagement, improve services, and help scale more simply.

During the COVID-19 pandemic, educational institutions that operated on in-person model shifted many of their traditionally in-person operations and activities—including grading, assessments and testing, and admissions—to a virtual format, where many had never been before. Educational technology (EdTech) companies around the world used the cloud to help quickly create and scale to meet the needs of these academic institutions while maintaining a consistent and smooth student experience.