In 2021, nearly one in six Australians—around four million individuals—experience some level of hearing loss, from mild to profound. This statistic is part of a broader global trend reported by the World Health Organization (WHO), which estimates that 466 million people worldwide live with hearing impairment, including 34 million children. Furthermore, approximately 1.1 billion young individuals are at risk of hearing loss due to exposure to loud noises in recreational environments and through personal audio devices. Amazon Web Services (AWS) provides solutions designed to assist organizations in creating comprehensive, accessible tools that enhance daily activities such as social interactions, medical consultations, live media, and public announcements. For additional insights into how technology can aid accessibility, check out this blog post.
State and local governments continually seek to enhance the lives of their constituents by improving the efficiency of existing services and exploring new offerings related to food assistance, healthcare, education, affordable housing, and more. Enterprise resource planning (ERP) solutions, along with other business systems that facilitate performance-based budgeting, are pivotal in providing the necessary data insights. The delicate balance between constrained budgets and effective government service delivery is supported by strong fiscal health, well-defined policies, and analytical insights. Cloud-based ERP systems empower governments with the technological capabilities required to optimize current services and roll out new initiatives.
The advancement of artificial intelligence (AI) has introduced ready-to-use services that organizations can utilize to not only automate data entry tasks but also enhance business processes. By leveraging modern AI capabilities available on AWS, public sector organizations can revolutionize their document management strategies. This transformation allows for increased efficiency, particularly during peak paperwork periods, enabling faster service delivery to constituents while allowing staff to concentrate on more critical, high-need cases. Automation of documents minimizes human error and ensures backup systems are in place in the event of natural disasters.
Nonprofits can harness cloud technology to alleviate the challenges associated with fundraising. Through machine learning (ML), these organizations can identify potential donors who are more likely to engage with and contribute to their missions. Find out how you can implement these solutions effectively to boost fundraising efforts at your nonprofit. Discover how to utilize Amazon Personalize to create an ML model that supports a diverse range of personalization experiences—no prior ML expertise needed. For more information from an authority on this topic, visit this link.
BrainGuide, developed in partnership with AWS and Biogen, is a pioneering platform aimed at providing individuals with essential knowledge and resources for managing brain health. This initiative addresses the critical need for informative resources about Alzheimer’s disease, a leading cause of mortality in the United States, as identified by the nonprofit organization UsAgainstAlzheimer’s (UsA2).
The Urban Analytics Lab at the National University of Singapore (NUS) leads research in geospatial data analysis and 3D city modeling, essential for the development of smart cities. Their work offers valuable insights to scientists, architects, urban planners, and real estate developers, guiding informed decision-making across various projects, including energy modeling and urban agriculture. To meet the growing global demand for its data analytics and planning tools, the Urban Analytics Lab has partnered with Amazon Web Services (AWS).
To safeguard investments in machine learning, government entities can securely manage ML source code. By storing Amazon SageMaker Studio code in an AWS CodeCommit repository, organizations can maintain these codes as standalone documents for future use. SageMaker Studio provides a unified, web-based visual interface for completing all necessary ML development steps, from data preparation to model deployment. Learn how to set up a git-based repository on CodeCommit to effectively manage ML code created with SageMaker.
Education is undergoing a profound transformation, driven by advancements in artificial intelligence and innovative customer solutions.
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