Category: Amazon Q Business

In recent years, public sector organizations have found success running their scientific data processing workloads on Amazon Web Services. As the number of workloads increase with the massive data volume and complex scientific simulations, organizations are looking for ways to optimize cost while maintaining research momentum. Amazon EC2 Spot Instances presents a compelling option to run unused Amazon Elastic Compute Cloud (Amazon EC2) capacity with an up to 90 percent discount compared to On-Demand prices. However, the intermittent nature of Spot Instances often requires careful consideration, especially when handling time-sensitive mission-critical workloads. In this post, we discuss how organizations can effectively identify opportunities to use Spot Instances and Amazon Q Business to develop an enhanced Spot Instance analysis. 

The AWS Open Data Sponsorship Program makes high-value, cloud-optimized datasets publicly available on Amazon Web Services (AWS). AWS works with data providers to democratize access to data by making it available to the public for analysis on AWS; develop new cloud-based techniques, formats, and tools that lower the cost of working with data; and encourage the development of communities that benefit from access to shared datasets. The full list of publicly available datasets are on the Registry of Open Data on AWS and are now also discoverable on AWS Data Exchange. This quarter, AWS released 53 new or updated datasets and you can learn more about them in this post.

PubMed Central (PMC) is a leading resource for biomedical literature, offering a vast repository of full-text biomedical and life sciences journal articles. While PMC offers immense potential to accelerate scientific progress, inform evidence-based practice, and drive innovation in the biomedical and life sciences fields, the sheer volume of data presents a significant challenge. This is where Amazon Q Business comes in. It’s a powerful service designed to streamline the process of analyzing vast amounts of scientific literature and provide valuable insights efficiently. Read this post to learn more.

Healthcare organizations face a significant challenge in making sense of the vast amounts of unstructured medical data trapped in patient records, lab results, and clinical guidelines. Approximately 97 percent of the 50 petabytes (PB) of healthcare data generated annually goes unused. This untapped resource could hold the key to improving patient care and saving valuable clinician time. Read this post learn how we built an innovative solution on Amazon Web Services (AWS) generative artificial intelligence (AI) capabilities that lets clinicians unlock this data treasure trove.

Amazon Web Services (AWS) offers a variety of options for building chat-based assistants with generative artificial intelligence (AI) capabilities. The goal of this post is to present in simple words some of these options and what to keep in mind to decide which to use and how to get started.