Tag: Artificial Intelligence

State and local governments (SLGs) are constantly looking for ways to improve the lives and well-being of their constituents. They strive for increased efficiencies in delivering existing government services or potential new services such as those related to assistance with food, health, education, affordable housing, weatherization, and more. Enterprise resource planning (ERP) solutions, along with ancillary business systems that support performance-based budgeting, play a key role in providing data insights. The balancing act between tight budgets and enablement of government services is enabled by fiscal health, sound policies, and data insights. ERP systems deployed on the cloud can help with the capabilities and technology tools that governments need to derive efficiencies with existing services and deploy new services.

The maturing of artificial intelligence (AI) has brought ready-made services that organizations can use, not only to automate data entry work but also to apply intelligence into the business process. Using modern AI capabilities on AWS, organizations can transform approaches to document management. This allows public sector organizations to save time (enabling faster throughput especially during higher volume paperwork times), so they can help get constituents their services faster, and focus on the most valuable work of the high-touch or high-need cases. Document automation helps reduce human entry error and provide backup services in case of natural disaster.

Nonprofits have found themselves thrust into a digital-first landscape, with an increasing demand for virtual or remote services for beneficiaries, donors, volunteers, and staff. During the COVID-19 pandemic, nonprofit organizations put forth tremendous effort to fill gaps unmet by the government and private sectors for our communities. Nonprofits have shown agility in their pivot to online events, remote service delivery, sharing of data and research, and more. To help nonprofits access the best-in-class tools provided by AWS, today we are launching the 2021 AWS Imagine Grant program. Guidelines and instructions on how to apply for this year’s cycle are available today.

Nonprofits can leverage the cloud to reduce the burden associated with their fundraising activities. With machine learning (ML), nonprofits can identify individuals who are more likely to engage and donate to their cause to support their mission. Read more to learn exactly how you can put these solutions into action and leverage ML to help your nonprofit with fundraising efforts. In this post, discover how to use Amazon Personalize to build a ML model that supports a wide-range of personalization experiences—without prior machine learning experience.

Alzheimer’s, a progressive brain disease that gradually deteriorates memories and thinking skills, is one of the leading causes of death in the United States, according to nonprofit UsAgainstAlzheimer’s (UsA2). To help address the immense need for brain health information and insights, UsA2 recently launched BrainGuide working with AWS and Biogen. BrainGuide is a first-of-its-kind platform that empowers people with knowledge and resources to take the best next steps in managing their own or a loved one’s brain health.

The Urban Analytics Lab at the National University of Singapore (NUS) spearheads research in geospatial data analysis and 3D city modelling. The lab’s work underpins the development of smart cities and provides scientists, architects, urban planners, and real estate developers with data insights. These insights help parties make informed decisions about projects ranging from energy modelling to urban farming. To meet rising global demand for its data analytics and planning tools, Urban Analytics Lab turned to Amazon Web Services (AWS).

To help protect investments on ML, government organizations can securely store ML source code. Storing Amazon SageMaker Studio code in an AWS CodeCommit repository enables you to keep them as standalone documents to reuse in the future. SageMaker Studio provides a single, web-based visual interface where you can perform all ML development steps required to prepare data and build, train, and deploy models. Read on to learn the steps to configure a git-based repository on CodeCommit to manage ML code developed with SageMaker.

In 2020, education transformed like never before. Educational institutions needed to be able to provide students, teachers, and staff with immediate access to education and AWS helped customers and partners modernize their systems and applications and reach learners remotely, quickly, and at scale. In 2021, innovation continues in the world of teaching, learning, and research—as well as the use of technology to automate processes and drive better student outcomes.

Research exploring how humans work with machines to solve problems in fields ranging from space to sustainability has established the potential to create far-reaching change in children’s education. The test-bed project is part of a wider program set up by Oxford University with support from AWS. Researchers have been as surprised by how quickly they have reached results as they are pleased with the outcomes. One of the test-beds, the Oxford X-Reality Hub Ed Tech project, set out to investigate how virtual reality (VR) could transform the classroom experience and close the gap between disadvantaged groups of pupils who statistically do less well than their peers.

As populations continue to grow, government departments around the world are exploring new ways to scale their delivery of client services. The Public Services Health & Safety Association (PSHSA), a transfer payment agency of the Ontario government’s Ministry of Labour Training and Skills Development, turned to an artificial intelligence (AI)-powered chatbot to better serve customers by addressing their occupational health and safety training and consulting questions.