Tag: Machine Learning

As more and more healthcare companies use their data to remain competitive, protecting patient data is as critical than ever. With increasing adoption of AI/ML models in healthcare, making sure that these technologies comply with privacy regulations such as HIPAA and GDPR has become a top priority. Amazon Bedrock is a fully managed service that provides unified access to a diverse selection of high-performance foundation models from industry-leading AI companies. In this post, we walk you through the importance of healthcare data privacy and how to use Amazon Bedrock Guardrails to safeguard sensitive information in AI-driven healthcare solutions.

Academic research IT departments around the world face the same challenge: how to balance their existing on-premises infrastructure with the opportunities of cloud computing. At the Supercomputing 2024 (SC24) conference, Amazon Web Services hosted a panel featuring two research IT leaders: Circe Tsui, associate director of solutions architecture at Emory University in the Office of Information Technology, and Dr. Robert Shen, director of the RMIT AWS Supercomputing Hub (RACE) at the Royal Melbourne Institute of Technology (RMIT). During the panel, Tsui and Shen shared how their institutions use AWS to augment and enhance their research operations with more scalability, security, and collaboration alongside their on-premises infrastructure. Read this post to learn more.

Higher education institutions are under increasing pressure to demonstrate the effectiveness of their programs and provide students with a clear path to degree completion. Data analytics can help these institutions proactively identify and support at-risk students, allowing them to develop personalized intervention strategies to improve student retention and graduation rates. In this post, we’ll explore how Amazon Redshift ML, a powerful machine learning (ML) capability within the Amazon Redshift data warehouse, can enable higher education leaders to quickly predict student outcomes and communicate insights to key stakeholders.

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.

This post explores the architectural design and security concepts employed by Radboud University Medical Center Nijmegen (Radboudumc) to build a secure artificial intelligence (AI) runtime environment on Amazon Web Services (AWS). Business leaders dealing with sensitive or regulated data will find this post invaluable because it demonstrates a proven approach to using the power of AI while maintaining strict data privacy and security standards.

Across NATO’s 32 member states, today’s rapidly evolving threat landscape requires continuous modernization of advanced technology solutions, underscoring the strategic importance of the alliance’s digital transformation. This modernization effort demands speed, scale, security, and global innovation capabilities to stay ahead. Collaborating with technology leaders like Amazon Web Services (AWS) can accelerate innovation and NATO’s ability to deliver mission-ready solutions to counter known and emerging threats.

In the age of generative artificial intelligence (AI), data isn’t just king—it’s the entire kingdom. Our previous blog post, Anduril unleashes the power of RAG with enterprise search chatbot Alfred on AWS, highlighted how Anduril Industries revolutionized enterprise search with Alfred, their innovative chat-based assistant powered by Retrieval-Augmented Generation (RAG) architecture. In this post, we examine the technical intricacies that make this system possible.

Global leaders are convening in Germany this week at the annual Munich Security Conference (MSC) to discuss key foreign policy and security challenges. Amid these discussions, one thing is clear: global leadership increasingly hinges on technological progress. In particular, the rapid progress of artificial intelligence (AI) presents an extraordinary opportunity for transformative innovation. For the U.S. government, this moment marks a crucial inflection point: embrace bold modernization of digital infrastructure and AI investment or risk being outpaced by global competitors.

Government agencies handle vast volumes of bureaucratic documents daily, ranging from tax forms to medical records. This document-heavy workflow, often reliant on manual processing, can result in delays, errors, and increased operational inefficiencies, causing frustration among both employees and stakeholders. This post explores how intelligent document processing (IDP) solutions from Amazon Web Services (AWS) can modernize bureaucratic workflows, improve efficiency, and enhance service delivery within government agencies.

In this post, we explore how generative artificial intelligence (AI), powered by services such as Amazon Bedrock and Amazon SageMaker, can be harnessed to meet the unique challenges of AWS GovCloud (US). We highlight use cases that demonstrate the potential of generative AI to enhance efficiency, automate workflows, and extract insights—all within a secure, compliant framework.