Solving some of the world’s most difficult problems with AWS and AI for Good
This year, Amazon Web Services (AWS) is a gold sponsor of AI for Good, the action-oriented technology-education platform hosted by the United Nations (UN). The organization is delivering a webinar series to provide best practices around how to adopt artificial intelligence (AI) and machine learning (ML) technologies.
With less than 10 years remaining to achieve the 17 United Nations’ Sustainable Development Goals (SDGs) by 2030, organizations all over the world are using AWS services to deliver various AI and ML-enabled solutions—from delivering disaster-relief services at the edge to reconnecting telecommunications after a hurricane. We are also helping organizations adopt AI and ML technologies more readily in the areas of computer vision, automatic speech recognition, and natural language process to solve ongoing global challenges.
Over the next few weeks, AWS is sharing technology use cases that highlight the potential of AI and ML with the AI for Good community:
How AI and ML are helping to solve the world’s most difficult problems
Advancements in AI and ML are making applications smarter and helping mission-oriented organizations increase impact. But taking concepts to deployment is often harder in practice than in theory. With AWS AI and ML services, all organizations can put ML technology into the hands of every developer—regardless of technical depth or experience—to build new, innovative solutions that improve lives and protect our planet. For example, Wadhwani Institute for Artificial Intelligence is working with AWS to build and train ML models for social good in areas such as public health, agriculture, financial inclusion, infrastructure, and education.
Improving disaster response at the edge and in pandemics
Nothing is more timely than overcoming the current COVID-19 pandemic, which is pushing organizations to think more about disaster response. Whether it is a natural disaster or an outbreak, organizations must be ready for whatever is to come in order to stay connected, maintain continued access to workloads and datasets in limited or disconnected environments, and provide critical services when and where they’re needed most. For example, AWS is working with the University of Washington Medicine and University of North Carolina Health to deliver and scale relief services in the midst of the COVID-19 pandemic, and used ML services to build chatbots that provide information on COVID-19 testing, offer 24/7 medical consulting, route patient requests to the relevant teams, and scale these services across increased call volumes during the pandemic.
To learn more, register for these upcoming AI for Good webinars:
- November 5: How AI and ML are solving the world’s most difficult problems — Bill Richmond, AI/ML Evangelist, Worldwide Public Sector, AWS (16:00 CET and 10:00 ET)
- November 12: Improving disaster response at the edge in pandemics — Grace Kitzmiller, Disaster Response Principal, AWS (16:00 CET and 10:00 ET)
Discover more by reading “Lessons in disaster response” from our AWS Disaster Response team and dive into more of the technology stories highlighting the big ideas, discoveries, and turning points in solving some of the world’s largest challenges on the Fix This podcast.