Category: Artificial Intelligence

Artificial intelligence (AI) and machine learning (ML) are critical tools being used in healthcare research, autonomous applications, predictive maintenance, and also a key tool used to advance sustainability solutions. However, to use AI and ML to solve sustainability problems, innovators need specific datasets that are prepared for analysis and training of the models. To help create and accelerate sustainability solutions, the Amazon Sustainability Data Initiative (ASDI) today announced easier identification of sustainability datasets with integration in AWS Data Exchange and the launch of a sustainability hackathon.

To mitigate synthetic fraud, government agencies should consider complementing their rules-based improper payment detection systems with machine learning (ML) techniques. By using ML on a large number of disparate but related data sources, including social media, agencies can formulate a more comprehensive risk score for each individual or transaction to help investigators identify improper payments efficiently. In this blog post, we provide a foundational reference architecture for an ML-powered improper payment detection solution using AWS ML services.

Can you see sounds? Using open data, you can. To celebrate this year’s World Oceans Day, an artist and sustainability application architect at Amazon Web Services (AWS), created an artwork titled Can You See the Sound of the Ocean. To create the art, she drew inspiration from the Pacific Ocean Sound Recordings from the Monterey Bay Aquarium Research Institute (MBARI), available through the Amazon Sustainability Data Initiative (ASDI). Learn more about the dataset and the art work.

Nursing shortages are not a new phenomenon, but the pandemic has exacerbated the problem. The situation has forced hospitals to think creatively about their staffing models and has also brought clinical teams, operators, and IT departments together in an effort to seek new ways to use technology. One healthcare system is using robotics powered by cloud technology, including artificial intelligence (AI) and machine learning (ML), to help nurses spend more time with patients.

On April 1, the US National Archives and Records Administration (NARA) released the 1950 Census data to the general public. Census data is released 72 years after a census is conducted, and it has been 10 years since the last census data for the 1940 Census was publicly released. With the support of cloud technologies, this release marks a number of important firsts. AWS is honored to support the release of the 1950 Census and help make this data available to the public.

As AI and ML becomes more ubiquitous and simple to use, EdTech companies and startups around the world are unlocking the benefits of these technologies, particularly when it comes to personalizing learning content for a learner or educator’s specific needs. Learn how EdTech startups and AWS EdStart Members are using AI and ML to help revolutionize the education industry. 

A research team led by Dr. Beatriz Martinez Lopez at UC Davis supports pig farmers with a data analytics platform that aggregates and analyzes animal health data to diagnose animal viruses and diseases. But this platform was primarily designed for analysts and data scientists. To truly transform animal disease management, Martinez-Lopez wants to put this data analytics tool into the hands of farmers around the world. So the research team is using the scalable, cost-effective tools of the AWS Cloud, along with a research grant letter of support from AWS, to make this optimized platform a reality.

Skillshare is the largest global online learning community for creativity. They offer thousands of inspiring classes for creative and curious people on topics including illustration, design, photography, video, freelancing, and more. Skillshare wanted their members to easily discover relevant content with a seamless discovery process of personalized recommendations. Skillshare decided to test Amazon Personalize from AWS to make these data-fueled recommendations for members with machine learning. This blog post describes their Amazon Personalize solution architecture, their AWS Step Functions process, and the results of their experiment.

The extensive higher education landscape in India poses many challenges, like the rising complexity of administrative and academic activities, increase in student enrollment from a tech-savvy generation, data security issues, and more. The education technology (EdTech) company CollPoll is a full-stack web- and mobile-based campus automation, digital learning, and analytics platform designed to address these challenges with artificial intelligence powered by Amazon Web Services (AWS). CollPoll uses the cloud to provide end-to-end automation of key academic and administrative processes to bring digital transformation solutions to educational institutions in India and around the world.

Electronic notifications of patient events are a vital mechanism for care providers to improve care coordination and promote appropriate follow-up care in a timely manner. This post shows how a combination of Amazon Web Services (AWS) technologies, like AWS Lambda, Amazon Comprehend Medical, and AWS Fargate, can effectively manage and deliver actionable data to help healthcare customers deliver electronic notifications in a secure and efficient way.