Tag: AWS IAM

Today, generative artificial intelligence (AI) is at the core of many of the decisions and technologies businesses across the globe are implementing. The linchpin to ensuring that generative AI is effective depends on the foundation models (FMs) storing the data. To make sure that those FMs are pulling the correct data, Amazon Web Services (AWS) has developed a solution through Amazon Bedrock to generate SQL to answer user questions about the data. The solution was developed to support the Federal Institute of São Paulo (IFSP) and has optimized their decision-making.

In this post, we explore how AWS services, open source software, and bespoke source code can help address resource sharing enhancements requested by public sector customers using AWS Outposts. This solution aims to provide greater flexibility, control, and cost management for organizations leveraging Outposts in multi-account environments, specifically focusing on key AWS resources, including Amazon Elastic Compute Cloud (Amazon EC2), Amazon Elastic Block Store (Amazon EBS), and Amazon Simple Storage Service (Amazon S3) on Outposts.

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.

In this post, we showcase a Retrieval-Augmented Generation (RAG) application that can search and query across multiple Indian languages using the Cohere Embed – Multilingual model and Anthropic Claude 3 on Amazon Bedrock. This post focuses on Indian languages, but you can use the approach with other languages that are supported by the large language model.

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.

The Generative AI Sandbox on AWS, powered by Amazon Bedrock Studio, provides a secure, governed, and isolated environment for organizations to explore the power of large language models (LLMs) and other generative artificial intelligence capabilities. Bedrock Studio users can test different LLMs side by side to understand which ones best suit their specific use cases: from drafting policy documents to analyzing public feedback, or creating educational content.

On October 24, 2024, the White House released a National Security Memorandum (NSM) on Artificial Intelligence (AI), which focuses on ensuring US leadership in developing advanced AI technologies. Amazon Web Services (AWS) is uniquely positioned to address the critical needs of the defense and national security customers in advancing their AI capabilities. Our comprehensive suite of AI and high performance computing (HPC) capabilities offers flexible and robust solutions to meet the NSM’s goals and empower national security missions.

As federal agencies strive to enhance digital services and create a seamless customer experience, integrating robust identity and access management (IAM) solutions has become paramount. Amazon Cognito, a robust user identity management service offered by Amazon Web Services (AWS), provides a secure and scalable solution for managing user authentication and authorization. When combined with Login.gov, a trusted identity platform developed by the U.S. General Services Administration (GSA), federal agencies can unlock a powerful combination that streamlines user access while maintaining the highest levels of security and compliance.

Malcolm is a powerful, open source network traffic analysis tool suite created by the Cybersecurity and Infrastructure Security Agency (CISA) to aid public and private sector customers in improving their network security monitoring and incident response. Malcolm is most commonly used for incident response, network monitoring, threat hunting, training, and research, but can be adapted for other use cases. In this post, we introduce you to the key components of Malcolm on Amazon Elastic Kubernetes Service (Amazon EKS).

As government organizations transition to Amazon Web Services (AWS), they often seek to maintain operational continuity by using their existing on-premises firewall solutions. Gateway Load Balancer (GWLB) enables seamless integration of these firewall appliances into the AWS architecture, ensuring consistent security policies and minimizing disruptions. This post explores best practices for implementing GWLB to facilitate centralized traffic inspection for both east-west and north-south traffic flows.