Category: Artificial Intelligence

Analyzing large-scale genomic variant data just got easier with the latest release of Amazon EMR and its integration with AWS HealthOmics. HealthOmics Analytics provides tabular access to genetic variant data sets and annotations, empowering researchers and data scientists to uncover valuable insights through Amazon Athena queries and now Amazon EMR jobs. While Amazon Athena excels […]

Introduction This blog post describes a feature in AWS HealthLake which allows direct integration with Amazon EventBridge. Additionally, this blog post will show how AWS HealthLake’s event-driven capabilities can be leveraged to track events at the FHIR resource levels, allowing you to address complex notifications and subscription scenarios with native AWS services. AWS HealthLake, a […]

In the high-stakes arena of manufacturing, where product quality can make or break market reputation, using visual intelligence effectively remains the linchpin of excellence. Visual intelligence, in this context, refers to the application of artificial intelligence (AI) precision to enhance visual quality inspection (VQI), seamlessly integrating visual data with operational metrics like overall equipment effectiveness […]

Generative artificial intelligence (AI) is rapidly becoming a cornerstone technology, driving significant advancements in manufacturing through the creation of synthetic data and images, optimized designs, process simulations, insights from operational data, and more. Recent research from Capgemini indicates that a substantial majority of manufacturers are not just curious about generative AI; 55% are actively exploring […]

In this blog, you’ll discover how to harness the power of serverless computing to streamline genomics analysis workflows, enabling faster insights. By leveraging AWS Step Functions, AWS Lambda, and AWS HealthOmics, you can parallelize and modularize resource-intensive genomics pipelines. This approach enhances efficiency, scalability, and cost optimization, empowering businesses and researchers to accelerate time-to-insight. The […]

Introduction Advancements in next-generation sequencing (NGS) technology have created new opportunities for omics data analysis, unlocking valuable insights for precision medicine, clinical diagnostics, and drug discovery. To keep pace with this high-throughput technology and handle the fluctuations in data volume, healthcare and life sciences (HCLS) customers seek a secure, reliable, and scalable environment for data […]

In the oil and gas industry, rig reports are essential for monitoring the performance and operations of drilling rigs. These reports contain a vast amount of unstructured data, including comments from rig personnel regarding rig activities such as drilling progress, equipment maintenance, process interruptions, and safety observations (Figure 1). In blog #1, we discussed a […]

As early adopters of artificial intelligence (AI), healthcare and life science organizations are among the most enthusiastic and advanced users of generative AI. The transformative technology has undergone a remarkable evolution in the past year, propelling innovations once considered science fiction into reality – with the potential to transform these industries and significantly improve patient outcomes […]

Marketers and advertisers need a unified view of consumer data to drive highly relevant marketing and advertising experiences across web, mobile, contact center, and social media channels. For example, if a consumer is shopping for a pair of sneakers on a brand’s website, the marketer would like to surface the most relevant products to save […]

Mobile World Congress (MWC) Barcelona was another successful year where AWS for Telecom was on hand to deliver insightful sessions and interactive demos providing attendees with an opportunity to engage with AWS experts. A curated selection of more than 20 customer focused partner integrated demos were showcased across four areas of expertise: generative AI, SaaS, […]