Category: Artificial Intelligence

Inference is an important stage of machine learning pipelines that deliver insights to end users from trained neural network models. These models are deployed to perform predictive tasks like image classification, object detection, and semantic segmentation. However, constraints can make implementing inference at scale on edge devices such as IoT controllers and gateways challenging. Learn how to train and convert a neural network model for image classification to an edge-optimized binary for Intel FPGA hardware.

Machine learning is a core component of tomorrow’s technology solutions. That’s why we are working with customers and APN Partners to drive this transformation journey. AWS has developed several partner programs to accelerate the process and enable you to create value for customers. This post explores APN Navigate, a comprehensive enablement program for APN Partners, and the AWS Machine Learning Competency, which validates and promotes a partner’s expertise in ML.

As mobile devices and 5G networks pave the way for diversified content consumption across the globe, the new global media trend poses new challenges to traditional broadcasting companies. MegazoneCloud’s customer, a global broadcaster based in South Korea, turned to the cloud for help transforming its media production system and providing leading-edge services to its audience. The customer adopted state-of-the-art, cloud-based media technology, and undertook an industry-leading digital transformation.

Companies attempting to deploy personalized customer experiences face many challenges. To do personalization well, you must understand the behavior of specific user segments and their affinities for specific products. However, you can’t uncover affinities and propensities without product analytics. Learn how to combine Amazon Personalize’s machine learning algorithms with Amplitude’s product intelligence platform to track user behavior in real-time.

Manually extracting data from multiple sources is repetitive, error-prone, and can create a bottleneck in the business process. Idexcel built a solution based on Amazon Textract that improves the accuracy of the data extraction process, reduces processing time, and boosts productivity to increase operational efficiencies. Learn how this approach can solidify your competitive edge, help you respond faster to market opportunities, and increase operational efficiency.

The oil and gas industry is highly complex and churns out copious amounts of data from sensors and machines at every stage in their business value chain. This post analyzes the role of machine learning for document extraction in the oil and gas industry for better business operations. Learn about Quantiphi’s document processing solution built on AWS, and how it helped a Canadian oil and gas organization address document management challenges through AI and ML techniques.

The aviation industry has long been in the vanguard of digital disruption. An interactive navigation and operations solution developed by the Accenture AWS Business Group (AABG) can improve the airport experience of travelers, whether they are waiting for a flight or looking for a check-in area, food court, lounge, transportation, or customer service counter. Accenture’s smart airport assistant, called 5G-Connected Airport, uses facial recognition to help travelers pass quickly through security once they have registered.

As COVID-19 began to sweep the globe, organizations of all shapes, sizes, and missions sought every available tool in the fight to save lives and limit the scope and spread of the pandemic. One of the key tools at their disposal was data. G-Med, the world’s largest online medical community, teamed up with AWS Competency Partner Sisense to make a plethora of COVID-19 treatment protocols easily analyzed and searchable using AWS machine learning technologies.

The healthcare industry is experiencing a global shortage of doctors, nurses, and other healthcare professionals. Telemedicine, which provides primary healthcare services to patients through remote connectivity, is one approach for addressing this challenge. SourceFuse developed an easy-to-use and secure telemedicine application called SF Medic that can be adopted by hospitals, clinics, and even single-physician practices.

Fragmented supply-chain management systems can impair an enterprise’s ability to make informed, timely decisions. Accenture’s Intelligent Revenue and Supply Chain (IRAS) platform integrates insights generated by machine learning models into an enterprise’s technical and business ecosystems. This post explains how Accenture’s IRAS solution is architected, how it can coexist with other ML forecasting models or statistical packages, and how you can consume its insights in an integrated way.