AWS Public Sector Blog

Tag: Machine Learning

Personalizing studying with machine learning: Course Hero’s approach

Different students learn in different ways. While many traditional classrooms continue to rely on a one-size-fits-all approach, Course Hero delivers personalized learning to every student through its innovative, machine learning (ML)-powered online platform. Operating under the slogan “Master your Classes,” Course Hero was founded with the vision of a world where every student graduates confident and prepared. The platform provides students access to study materials, including study guides, class notes, and practice problems. The service also includes on-demand access to subject matter expert tutors, available to help students 24/7.

How technology can help the intelligence community stay a step ahead

Leaders at all levels of government are continuing to think big about how they can leverage technology to modernize citizen services and better deliver on mission. Cloud is playing a foundational role in enabling this innovation. Teresa Carlson, Vice President of Worldwide Public Sector at Amazon Web Services (AWS), led a fireside chat with Andrew Hallman, Deputy Director of Digital Innovation at the CIA, at FedTalks 2019. In the conversation, Andrew covered the need for agile adoption of the latest technologies within the CIA to compete more effectively in an increasingly complex threat landscape, the intersection of innovation and security, and CIA’s commitment to strengthening its digital acumen.

Environmental Problem Solvers: University of California Santa Barbara Builds Machine Learning Tool to Measure Chemical Impact

Currently, there are 150 million chemicals registered and managed by the American Chemical Society. Every day, 15,000 to 20,000 new chemicals are registered. These chemicals are present in everything from our household cleaning products to the food we eat. But how do these chemicals affect us? And how do they affect the environment? A research group at the Bren School of Environmental Science & Management at UC Santa Barbara, with funding from the Environmental Protection Agency (EPA), works to answer those questions for the masses with the Chemical Life Cycle Collaborative (CLiCC) tool.

How Ride Data Helps Drive a Car Share Business

The British Columbia Automobile Association (BCAA) started the mobility revolution in B.C. over 100 years ago when a small group of British Columbians, passionate about cars and mobility, joined together to form an auto club. A century later, BCAA continues to help new generations get to where they need to go, and Evo is one way BCAA meets their changing mobility needs. Evo Car Share is Vancouver’s free-floating car sharing service offering a full fleet of 1,500 four-door, hybrid vehicles.

City of Louisville Builds Open Source Traffic Tools using Data, Collaboration, and the Cloud

Cities spend hundreds of thousands of dollars every year to do point-in-time traffic studies. Those studies assist cities in planning traffic signal timings and detours during street-closures. The City of Louisville, Kentucky, was paying every year for traffic studies and analysis and was getting static reports back. Instead, Louisville decided to use real-time congestion data freely available to governments through the Waze CCP (Connected Citizens Program). Combined with other information like built environment data and collision reports, Louisville could bring this together in the cloud for advanced analytics.

Changing the World, One Artificial Intelligence (AI) Application at a Time

There is no one-size-fits-all profile of the ideal artificial intelligence (AI) and machine learning (ML) customer, user, or developer. AWS is making AI and ML technologies more accessible with managed services that let anyone embed intelligence into their applications. It is why some of the most exciting uses for AI and ML are coming from unexpected places – public sector organizations with a mission to make the world a better place. Learn from some of the many public sector customers re-defining what it means to use AI to solve big challenges.

Using Data in Education: Four Steps to Success

Educators are increasingly adopting data analytics to understand and address gaps in education. This includes educators in higher education seeking to personalize student-learning experiences and improve learning outcomes, as well as policymakers looking to understand and scale effective teaching methods, increase efficiency and teaching capacity, among other concerns. AWS’s “Four Steps to Success” offers a high-level guide for leaders seeking to adopt new tools to make better use of the data they are collecting.

Helping to End Future Famines with Machine Learning

The United Nations, World Bank, and International Committee of the Red Cross (ICRC) with support from Amazon Web Services and other technology companies, recently launched the Famine Action Mechanism (FAM). The FAM is the first global mechanism dedicated to preventing future famines. In the past, responses to these devastating events have often come too late, once many lives have already been lost.

Estimating Hurricane Wind Speeds with Machine Learning

Better estimates of hurricane wind speeds can lead to better decisions around evacuations and general hurricane response planning, saving both lives and property. Hurricane windspeed estimates are currently made using the manual Dvorak technique. The National Hurricane Center releases them every three to six hours. Artificial intelligence (AI) experts with the IMPACT team at NASA’s Marshall Space Flight Center and Development Seed created the Deep Learning-Based Hurricane Intensity Estimator to automate this process.

Highlights from the 2018 IMAGINE: A Better World, A Global Education Conference

Timed with the 2018 back-to-school season, nearly 600 students, educators, university presidents, college administrators, superintendents, and business leaders from 14 different countries met in Seattle, Washington, to discuss how the cloud can address challenges and opportunities facing education. The conference revolved around three core themes: innovation and transformation, the role of machine learning in education, and building the workforce of tomorrow.