Category: Amazon Rekognition

In 2019, Pennsylvania State University (Penn State) began looking for a better way to meet the needs of its digital-native student population—specifically, a seamless way to connect students with on-campus resources. Seeking to create a personalized mobile app experience, Penn State partnered with Modo Labs, an educational technology company (EdTech) offering a no-code app-building platform powered by Amazon Web Services (AWS). The result of this collaboration was Penn State Go, an all-in-one platform that quickly connects students to vital resources and services.

How can technology leaders rapidly deliver responsible artificial intelligence-based innovation while aligning with the broad spectrum of strict regulatory requirements? The answer is simple: Amazon Web Services (AWS) GovCloud (US) provides the technology that underpins a solid foundation for securely and compliantly building and deploying AI capabilities. Read this post to learn more.

Machine learning (ML) and artificial intelligence (AI) are transformative technologies, enabling organizations of all sizes to further their mission in ways not previously possible. But, it is critical to think responsibly about these technologies so that all users are treated fairly, data is appropriately protected, and individuals can make informed choices about consent. In this post, we discuss responsible AI and how you should think about your workloads. This approach will help ensure your AI systems are fair, transparent, and secure.

As a teacher with the KIPP charter school network in Houston, Texas, Dave Wakefield knew there had to be a better way for educators to gain insightful feedback on their instruction. Traditionally, educators who wanted feedback on their teaching either had to have someone visit their classroom or film themselves and then send that video to a mentor or peer for review. In 2013, Wakefield founded education technology (EdTech) company Sibme as a way to use technology, powered by Amazon Web Services (AWS), to help educators access quicker and more reliable feedback.

The vision of Singapore’s National Library Board goes beyond making information accessible; the NLB is focused on bringing the richness of the nation’s cultural heritage right to the palm of your hand. As part of its LAB25 (Libraries and Archives Blueprint 2025) Singapore Storytellers initiative, the NLB seeks to nurture a stronger appreciation and understanding of the Singapore experience. To support this, Amazon Web Services (AWS) collaborated with Singapore-based NCS, a leading technology services firm, to create an interactive augmented reality (AR) web application prototype on the AWS Cloud.

Amazon Rekognition, a code-free automated machine learning (AutoML) service from Amazon Web Services (AWS), showed impeccable diagnostic performance in categorizing various retinal diseases using optical coherence tomography (OCT) scans. This blog post details the steps to use Amazon Rekognition Custom Labels to train a model that categorizes retinal diseases and the process of training and fine-tuning convolutional neural networks (CNNs), the standard deep learning methodology.

Since wildfires can double in size and intensity every three to five minutes, early detection and reduced response times are essential. Cloud technologies, including artificial intelligence (AI) and machine learning (ML), can help with this. Learn a high-level architecture to create a solution with AWS that uses AI to identify and classify wildfire smoke imagery and then rapidly alert and inform first responders about the location and condition of a fire incident.

Citizens want to report issues to their local governments in a fast and simple manner and not have to worry about identifying the right government agency or phone number—for instance, if a fire hydrant is broken, or a road sign has fallen over. In this blog post, learn how to set up a solution with AWS deep learning services that creates a fluid experience for reporting and addressing these issues.

NHS Digital launched NHS login, a serverless identity platform to facilitate access to a range of health and care apps for residents in England, with AWS, amongst other suppliers. Using the AWS Cloud, NHS Digital achieves scale, high availability, and security for citizens accessing these services, and helps users access NHS services quicker and more simply. NHS login is one of a number of services NHS Digital are hosting on the cloud as part of the UK government’s ‘Cloud First’ policy.

Since 2003, the US federal government has made approximately $1.7 trillion in improper payments, with an estimated $206 billion made in FY 2020 alone. Improper payments are now anticipated to increase proportionally to new levels of federal spending. How can agencies fight improper payments at this scale? And what tools can agencies use to address fraud, erroneous data submission and other causes of this problem? Agencies can use AWS to solve the multi-sided issues of payment integrity.