Tag: Amazon S3

In 2023, the students from Redback Racing at the University of New South Wales (UNSW) wove together their many disciplines of engineering prowess to create their latest cars: RB23 and RB21-D. After developing and going live with their real-time telemetry system on Amazon Web Services (AWS), the team has placed as the highest-ranking Australian squad in the electric vehicle (EV) division of the Australasia Formula SAE competition, placing second overall. Read this post to learn more.

How can technology leaders rapidly deliver responsible artificial intelligence-based innovation while aligning with the broad spectrum of strict regulatory requirements? The answer is simple: Amazon Web Services (AWS) GovCloud (US) provides the technology that underpins a solid foundation for securely and compliantly building and deploying AI capabilities. Read this post to learn more.

Federal agencies typically collect, manage, use, and distribute a wide array of documents. Storing and distributing federal agency documents is often a complicated process; documents can range from structured formats to free-flowing documentation with personal identifiable information (PII) that needs careful redaction. And because federal agencies cover a wide breadth of domains, it is challenging to develop a one-size-fits-all approach for document processing. In this post, we explore an example of how a federal agency can use Amazon Web Services (AWS) to design and deploy a solution that addresses this document processing challenge.

The 2024 version of the United Nations (UN) annual report “The State of Food Security and Nutrition in the World” found that about 29.6 percent of the global population, or about 2.4 billion people, were moderately or severely food insecure in 2022, meaning they did not have adequate access to food. Food security can be caused by a number of factors, including poverty, inflationary factors, violent conflict, and the effects of climate change. In this post, we demonstrate how generative artificial intelligence (AI) can help organizations better understand the food security crisis.

Rideshare demand prediction is a well-explored topic in academia and industry, with abundant online resources offering diverse modeling frameworks tailored to different geographic contexts. A challenge with rideshare demand prediction, however, is that the trip data required to calibrate or train models can be exceptionally large. In this post, we explore the challenges of big data analytics and showcase how ArcGIS GeoAnalytics Engine, a spatial analytics library for the Apache Spark environment, can be used on Amazon EMR to effectively address these problems.

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.

Acentra Health helps Medicare beneficiaries file quality of care complaints and appeals regarding early hospital discharge or early termination of skilled services. Processing these cases requires meticulous data entry from patient records and forms related to prior authorization notices, patient care, and case management, which often consist of complex medical history. To better support its clients, Acentra Health implemented an intelligent document processing (IDP) solution using Amazon Web Services (AWS). Read this post to learn how their IDP solution reduced document processing times and lowered costs.

Efficiently addressing internal customer support tickets can profoundly impact an organization’s productivity and employee well-being, apart from their ability to focus on the mission at hand. To meet these demands, many nonprofits, such as Thorn, are turning to innovative technology solutions. In this post, we explore how Thorn used Amazon Web Services (AWS) in conjunction with generative artificial intelligence (AI) to revolutionize their internal customer support for organization-wide IT, security, and engineering.

Amazon Web Services (AWS) Wickr is an end-to-end encrypted messaging and collaboration service with features designed to keep internal and external communications secure, private, and compliant. In this post, we present an architecture that uses the Wickr messaging solution for protected communication with a generative AI backend system, which uses an existing open source project: the AWS GenAI Chatbot. Read this post to learn more.

Generative artificial intelligence (AI) can transform the experience of state and local government constituents. With Amazon Lex, you can design and build sophisticated voice and text conversational interfaces, deploy omnichannel experiences with pre-built integrations to contact center solutions, and pay only for speech and text requests with no upfront costs or minimum fees. This post provides a technical walkthrough for building a generative AI chat-based solution.