Category: Federal

Generative artificial intelligence (AI) innovation and inspiration dominated today’s AWS Summit Washington, DC keynote. But there was no shortage of newsworthy moments and key takeaways that extended beyond generative AI. Dave Levy, vice president of Worldwide Public Sector at Amazon Web Services (AWS), delivered the keynote and was joined onstage by three guest speakers who helped him set the tone for the annual two-day event that brings the public sector cloud community together in the nation’s capital.

The Amazon Web Services (AWS) commitment to safe, transparent, and responsible artificial intelligence (AI)—including generative AI—is reflected in our endorsement of the White House Voluntary AI Commitments, our participation in the UK AI Safety Summit, and our dedication to providing customers with features that address specific challenges in this space. In this post, we explore how AWS can help agencies address the governance requirements outlined in the Office of Management and Budget (OMB) memo M-2410 as public sector entities look to build internal capacity for AI.

Governments encourage public sector organizations, businesses, and citizens to embrace digital technologies and practices through a range of incentives. These incentives standardize processes and motivate behaviors that achieve the objectives of these initiatives in a way that can be sustained over time. This post, written by an Amazon Web Services (AWS) government transformation advisor, highlights 10 ways that governments use incentives to accelerate successful digital transformation. 

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.

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.

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.

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.

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.

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.

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.