AWS Partner Network (APN) Blog

Category: Artificial Intelligence

Bursting Your On-Premises Data Lake Analytics and AI Workloads on AWS

Developing and maintaining an on-premises data lake is a complex undertaking. To maximize the value of data and use it as the basis for critical decisions, the data platform must be flexible and cost-effective. Learn how to build a hybrid data lake with Alluxio to leverage analytics and AI on AWS alongside a multi-petabyte on-premises data lake. Alluxio’s solution is called “zero-copy” hybrid cloud, indicating a cloud migration approach without first copying data to Amazon S3.

Read More
Onica-AWS-Partners-2

How Onica Leverages AWS AI, ML, and IoT Services to Combat the Pandemic

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.

Read More

How Pr3vent Uses Machine Learning on AWS to Combat Preventable Vision Loss in Infants

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.

Read More
Capgemini-AWS-Partners

How Capgemini Simplifies Pandemic Management with AWS Machine Learning Services

In a global pandemic, it can be hard for medical practitioners and patients to get connected and treated. Continually being on top of patients’ progress is also a challenge, along with scarcity of doctors who themselves are affected by the pandemic. Learn about a reference architecture from Capgemini that uses AWS machine learning services to enable doctors and patients to interact with the least amount of physical contact, while also improving efficiency in treatment management, tracking, and auditing.

Read More

How to Build and Deploy Amazon SageMaker Models in Dataiku Collaboratively

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.

Read More
Solutions-Architecture-1

Intelligent Video Analytics and Effective Remote Learning on Campus Private 4G/5G Networks

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.

Read More

How to Export a Model from Domino for Deployment in Amazon SageMaker

Data science is driving significant value for many organizations, including fueling new revenue streams, improving longstanding processes, and optimizing customer experience. Domino Data Lab empowers code-first data science teams to overcome these challenges of building and deploying data science at scale. Learn how to build and export a model from the Domino platform for deployment in Amazon SageMaker. Deploying models within Domino provides insight into the full model lineage.

Read More
ClearScale-AWS-Partners

How AWS Machine Learning Services Increase Medical Coding Accuracy and Efficiency

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.

Read More

Automated Cloud Network Threat Detection and Response with Blue Hexagon and AWS

VPC traffic mirroring and VPC ingress routing are powerful AWS networking primitives to monitor network traffic in your VPC at the packet-level. With Blue Hexagon’s next-gen Network Detection and Response (NG-NDR) security tool for AWS, which is powered by real-time deep learning, you can detect threats in network headers and payloads in less than a second. The additional AWS Security Hub integration enables you to trigger a rich action space of remediation and response.

Read More

How Provectus and GoCheck Kids Built ML Infrastructure for Improved Usability During Vision Screening

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.

Read More