Category: Amazon Simple Storage Service (S3)

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.

Singapore General Hospital (SGH), SingHealth Office of Academic Informatics (OAI), and Amazon Web Services (AWS) collaborated to develop a cost-effective, scalable cloud infrastructure that enables researchers to perform their own analyses on a centrally secured and compliant cloud platform. AWS HealthOmics offers a suite of services that help bioinformaticians, researchers, and scientists to store, query, analyze, and generate insights from genomic and other biological data. Read this post to learn more about the three primary components of HealthOmics used in the solution.

The process of transcribing video or audio files has traditionally been manual and time-consuming. Beyond the need for accurate and cost-effective transcriptions, attorneys have determined a need for timestamping capabilities, speaker identification, search and replace capabilities, the highlighting of specific words, editing capabilities, and most importantly, shortened turnaround times.To address the need for quicker and more accurate transcription of audiovisual files, the Contra Costa County (CCC) District Attorney’s (DA) Office reached out to Amazon Web Services (AWS) and partnered with AWS Partner ScaleCapacity to develop a solution that would automate the manual transcription process. Read this post to learn more.

In this post, we explore how healthcare and life sciences organizations can embrace the data mesh and data as a product (DaaP) principles to unlock the full potential of their health data, drive faster and more efficient drug development, and ultimately, bring life-saving treatments to patients more quickly. We also showcase the Amazon Web Services (AWS) services that support the journey towards effective data management and alignment with data mesh principles.

When government agencies choose Amazon Web Service (AWS) to store data, they choose to take advantage of inheriting the strictest security controls and standards. In addition, AWS services offer a unique opportunity to enhance networking and security approaches, ensuring safe and resilient data transfer mechanisms. This blog post provides guidance towards data sharing among government agencies, offering prescriptive approaches and best practices for implementing secure data exchange solutions using AWS services.

Pathologists have been looking at morphological patterns in patients’ tissue sections highlighted by hematoxylin and eosin (H&E) staining for more than a century. However, as the pathology transformation from glass slides to digital imaging gains momentum, it opens the door to artificial intelligence (AI) tools to complement expert assessment with quantitative measurements to enable data-driven medicine. Yet, challenges remain with handling digital imaging files such as storage and pre-processing prior to application of AI tools. Genomics England have utilised Amazon Web Services (AWS) and tools such as Amazon SageMaker to demonstrate how to prepare digital pathology images for research and the development of machine learning models.

The Natural History Museum (NHM) in London is a world-class visitor attraction and a leading science research center. NHM and Amazon Web Services (AWS) have partnered up to transform and accelerate scientific research by bringing together a broad range of biodiversity and environmental data types in one place for the first time. In an earlier post, we discussed NHM’s overall vision for using open data in combination with large-scale compute, data systems, and machine learning (ML) to create the Planetary Knowledge Base (PKB), a knowledge graph of global biodiversity. In this post, we focus on the underlying services and architecture that comprise the PKB.

The­ Digital Transformation Hub (DxHub) at California Polytechnic State University (Cal Poly) in San Luis Obispo – powered by Amazon Web Services (AWS) and part of the AWS Cloud Innovation Centers (CIC) program – collaborated with the City of San Diego and the San Diego Cyber Center of Excellence (CCOE) to create ‘My eCISO,’ a generative artificial intelligence (AI)-based application that propels public and private organizations on a path to cyber resiliency. This post explores the technology behind My eCISO and its implications for organizations looking to protect against attacks.