AWS Partner Network (APN) Blog
Category: Artificial Intelligence
How to Deploy AI Inference on the Edge with the LG AIoT Board and AWS IoT Greengrass
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.
Interactive Scientific Visualization on AWS with NVIDIA IndeX SDK
Scientific visualization is critical to understand complex phenomena modeled using high performance computing simulations. However, it has been challenging to do this effectively due to the inability to visualize, explore, and analyze large volumes of data and lack of collaborative workflow solutions. NVIDIA IndeX on AWS addresses each of these problems by providing a scientific visualization solution for massive datasets, thus opening the doors for discovery.
Amazon Fraud Detector Can Accelerate How AI is Embedded in Your Business
Online fraud is estimated to be costing businesses billions of dollars a year. As Fraudsters evolve new behaviors to get around preventive measures, businesses need a strategy that enables them to be responsive to new problems as they emerge. Learn how Inawisdom uses Amazon Fraud Detector to accelerate how AI can be embedded in a company’s strategy. What makes machine learning more flexible is its focus on identifying general patterns by looking at lots of examples.
Using Fewer Resources to Run Deep Learning Inference on Intel FPGA Edge Devices
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.
How to Leverage APN Navigate to Prepare for the AWS Machine Learning Competency
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.
How a Global Broadcaster Deployed Real-Time Automated News Clipping with AWS Media Services
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.
Measuring the Effectiveness of Personalization with Amplitude and Amazon Personalize
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.
Improving Data Extraction Processes Using Amazon Textract and Idexcel
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.
Cognitive Document Processing and Data Extraction for the Oil and Gas Industry
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.
Transforming the Traveling Experience with Accenture 5G Smart Airport Assistant and Amazon AR/VR
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.