Category: Amazon Machine Learning

Artificial intelligence (AI) and machine learning (ML) are maturing rapidly. According to Gartner, 75% of enterprises will shift from piloting to operationalizing AI by 2024. That’s why we are expanding the AWS Machine Learning Competency to help customers identify and engage qualified AWS Partners that have deep technical expertise and proven customer success in the areas of Applied AI and Machine Learning Operations (MLOps).

To help safeguard workplaces from the pandemic, TensorIoT developed SafetyVisor, a suite of machine learning tools that can operate independently or in tandem with existing business infrastructure to monitor safety gear usage (like masks) and social distancing. SafetyVisor’s computer vision models are designed to work with your existing cameras, and the entire solution is built utilizing a flexible architecture to facilitate easy deployment and use.

DXC Technology created a serverless artificial intelligence-powered solution called CoDetect to help detect manifestations of COVID-19 (and other medical conditions) in CT scans. Learn about the AWS services DXC chose for this solution, and explore two functional use cases that demonstrate the benefits of DXC’s CoDetect design and implementation approach. CoDetect is a web-based app that allows end users to submit CT scan studies for an AI model analysis.

Many organizations have started applying machine learning and artificial intelligence expertise to scale customer communications and accelerate research during the COVID-19 pandemic. Onica has been actively involved in these efforts, leveraging AWS technologies to help decision makers navigate this pandemic. In this post, dive into the technical details of two COVID-19-related solutions Onica has produced and learn about their results and impact.

Scaling doctors’ expertise through artificial intelligence (AI) and machine learning (ML) provides an affordable and accurate solution, giving millions of infants equal access to eye screening. Learn how Pr3vent, a medical AI company founded by ophthalmologists, teamed up with AWS Machine Learning Competency Partner Provectus to develop an advanced disease screening solution powered by deep learning that detects pathology and signs of possible abnormalities in the retinas of newborns.

Organizations often need business analysts and citizen data scientists to work with data scientists to create machine learning (ML) models, but they struggle to provide a common ground for collaboration. Newly enriched Dataiku Data Science Studio (DSS) and Amazon SageMaker capabilities answer this need, empowering a broader set of users by leveraging the managed infrastructure of Amazon SageMaker and combining it with Dataiku’s visual interface to develop models at scale.

Edge computing is a new paradigm in which the resources of a small data center are placed at the edge of the internet, in close proximity to mobile devices, sensors, and end users. Learn about the Physical Distancing Video Analytics Solution (VAS) on campus private 4G/5G networks that was developed utilizing AWS edge services in partnership with Carnegie Mellon University’s Open Edge Computing Initiative, Megh Computing’s Video Analytics Solution, and Federated Wireless Private Network Connectivity as a Service.

Medical coding helps providers maintain patient records and obtain reimbursement for services. Unfortunately, the process is complicated, time-consuming, and prone to error. Learn how ClearScale developed a solution that increases the efficiency and accuracy of the coding process. Powered by AWS Machine Learning, the application translates recorded medical appointment notes, and uses the information to generate more accurate medical codes.

For businesses like GoCheck Kids, machine learning infrastructure is vital. The company has developed a next-generation, ML-driven pediatric vision screening platform that enables healthcare practitioners to screen for vision risks in children in a fast and easy way by utilizing GoCheck Kids’ smartphone app. Learn how GoCheck Kids teamed up with Provectus to build a secure, auditable, and reproducible ML infrastructure on AWS to ensure its solution is powered by highly accurate image classification model.

The growth of AI in a wide range of applications demands more purpose-built processors to provide scalable levels of performance, flexibility, and efficiency. The LG AIoT board helps customers accelerate their computer vision and machine learning journey using AWS. Learn how to build a simple AI-enabled application with AWS IoT Greengrass that takes advantage of the hardware AI acceleration on the LG AIoT board. AWS IoT Greengrass extends AWS on your device and offers the cloud programming model and tools at the edge.