Tag: technical how-to

In this post, we provide technical guidance to help satellite operators build, deploy, and analyze satcom waveforms on Amazon Web Services (AWS). Details are provided about the orchestration of multiple waveforms, including an example of one Amazon Field-Programmable Gate Array (FPGA) Image being swapped in for another. We analyze the FPGA utilization and metrics in Amazon CloudWatch and Amazon QuickSight, and validate network performance against system latency requirements. Finally, we recommend actions you can take to build an agile satcom strategy.

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.

A multi-account strategy is important for Amazon Web Services (AWS) public sector customers because it is the foundation of cloud governance and compliance. Public sector customers using a shared account model can improve security and operational efficiency by adopting a multi-account strategy. In this post, we explore methods for existing AWS public sector customers to prepare for and migrate to a multi-account environment.

Organizations deploying the Landing Zone Accelerator (LZA) on AWS solution, provided by Amazon Web Services (AWS), often face challenges in managing and versioning their configuration files. In this post, we explore how to use GitHub as a configuration file repository for the Landing Zone Accelerator on AWS solution, allowing better version control, collaboration, and automation in your LZA deployments.

Governors for Schools is a charity operating across England and Wales to find and place volunteers on school and academy governing boards. Amazon Web Services (AWS) has worked with Governors for Schools by providing financial support, in addition to more than 100 AWS employees applying to take on school governance roles, providing much needed technical expertise in education. But in this post, we explain how Governors for Schools used Amazon Bedrock to process unstructured documents and generate meaningful insights into UK schools.

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.

Public sector organizations worldwide face a common challenge: processing an ever-growing volume of document-heavy applications across various services. From naturalization procedures to asylum applications and university admissions, many crucial processes still rely on manual or partially manual methods, leading to significant backlogs, extended processing times, and increased costs. This post explores how Amazon Bedrock can be used to address these challenges, focusing on streamlining naturalization applications.

Generative artificial intelligence (AI) has captured the imagination of organizations across industries, promising to revolutionize workflows and drive innovation. As public sector entities explore this transformative technology, a critical challenge emerges: identifying and prioritizing high-value use cases that align with specific business objectives and delivering measurable outcomes. In this post, we present an Amazon Web Services (AWS) framework to help public sector organizations navigate generative AI adoption and unlock its true potential.

The Amazon Web Services (AWS) Modular Data Center (MDC) is a service that enables rapid deployment of AWS managed data centers for running location- or latency-sensitive applications in locations with limited infrastructure. It reduces deployment time in remote areas and supports up to five racks of AWS Outposts or AWS Snow Family devices. In this post, we guide you through the end-to-end process of deploying the MDC at your site.

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.