AWS Public Sector Blog

Category: Federal

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Generative AI for public agencies: 5 best practices for secure implementation

Generative artificial intelligence (AI) is revolutionizing public agencies by streamlining services and providing valuable insights from large datasets. However, adding generative AI to your agency is not a simple process. SMX, an Amazon Web Services (AWS) Premier Tier Services Partner, helped one nonprofit agency build a robust architecture in the AWS Cloud that provided them the foundation for building and implementing generative AI tools. In this guest post, experts from SMX explain five best practices they used to help this agency prepare for generative AI.

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Improving customer experience for the public sector using AWS services

Citizens are increasingly expecting government to provide modern digital experiences for conducting online transactions. Market research tells us 63 percent of consumers see personalization as the standard level of service. This post offers various architectural patterns for improving customer experience for the public sector for a wide range of use cases. The aim of the post is to help public sector organizations create customer experience solutions on the Amazon Web Services (AWS) Cloud using AWS artificial intelligence (AI) services and AWS purpose-built data analytics services.

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Fine-tuning an LLM using QLoRA in AWS GovCloud (US)

Government agencies are increasingly using large language models (LLMs) powered by generative artificial intelligence (AI) to extract valuable insights from their data in the Amazon Web Services (AWS) GovCloud (US) Regions. In this guide, we walk you through the process of adapting LLMs to specific domains with parameter efficient fine-tuning techniques made accessible through Amazon SageMaker integrations with Hugging Face.

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Reimagining customer experience with AI-powered conversational service discovery

In this post, we will explore the use of generative artificial intelligence (AI) chatbots as a natural language alternative to the service catalog approach. We will present an Amazon Web Services (AWS) architecture pattern to deploy an AI chatbot that can understand user requests in natural language and provide interactive responses to user requests, directing them to the specific systems or services they are looking for. Chatbots simplify the content navigation and discovery process while improving the customer experience.

Breaking barriers and leveraging generative AI to advance the US Federal Government: Insights from AWS executive Yvette Cesario

The US Federal Government has endless opportunity to lead the way as well as adopt best practices for how the latest technologies, including generative artificial intelligence (AI), can be leveraged to fulfill its various missions. Yvette Cesario, director of national security sales at Amazon Web Services (AWS) Worldwide Public Sector (WWPS), was the guest on the seventh episode of the AWS Behind the Cloud vodcast and shared her insights about how generative AI has endless opportunities for the US Federal Government to leverage to transform its operations and missions.

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ICF helps FDA accelerate the drug labeling review process with AWS machine learning

Within the Food and Drug Administration’s Center for Drug Evaluation and Research, the Division of Medication Error Prevention and Analysis (DMEPA) plays a critical role. DMEPA reviews premarket and postmarket drug labeling to minimize the risk of medication errors. In partnership with DMEPA, Amazon Web Services (AWS) Partner ICF is developing a machine learning (ML) prototype known as the Computerized Labeling Assessment Tool (CLAT). The prototype employs innovative applications of optical character recognition (OCR) technology and the novel use of computer vision techniques that will alleviate bottlenecks in and enhance the efficiency of the drug labeling review process.

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Automate cybersecurity analysis with MBSE workflows enabled by AWS

Digital engineering fundamentally relies on integrating data across model structures by using a digital thread – an underlying framework for integrating data from across traditionally siloed functions that create a consolidated view of the system’s data throughout its lifecycle. The cloud is integral to digital engineering by supporting collaboration across geographically dispersed organizations, automating workflows for data connectivity and trade space analysis in a reliable, scalable, and cost-effective manner. This post describes how Amazon Web Services (AWS) Partner General Dynamics Information Technology (GDIT) has used digital engineering in combination with secure and scalable AWS services, to deliver secure IT systems to a large defense program.

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Resiliency imperatives for CIOs with sensitive and highly-available cloud environments in AWS GovCloud (US)

Amazon Web Services (AWS) customers, technology leaders, and government agency CIOs continually balance risk and reward to accomplish many things by using AWS GovCloud (US). They work to transform citizen experiences, save taxpayers money, support sustainable growth, expand market presence, modernize legacy systems, increase security, drive efficiencies, strengthen brand equity, and reduce environmental impact.

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Improving government contact center agent experience with Amazon Connect

Peraton, an Amazon Web Services (AWS) Premier Partner, has worked with multiple government agencies to improve both customer and agent experiences using Amazon Connect. This post explores how Amazon Connect, the cloud contact center solution from AWS, delivers relevant information to agents through a unified experience to help government organizations and agencies of all sizes improve interaction with customers and employees.

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Deploy LLMs in AWS GovCloud (US) Regions using Hugging Face Inference Containers

Government agencies are increasingly using large language models (LLMs) powered by generative artificial intelligence (AI) to extract valuable insights from their data in the Amazon Web Services (AWS) GovCloud (US) Regions. In this guide, we walk you through the process of hosting LLMs on Amazon Elastic Compute Cloud (Amazon EC2) instances, using the Hugging Face Text Generation Inference (TGI) Container (TGI) for serving custom LLMs.