AWS Machine Learning Blog

Tag: Amazon SageMaker Neo

Demystifying machine learning at the edge through real use cases

Edge is a term that refers to a location, far from the cloud or a big data center, where you have a computer device (edge device) capable of running (edge) applications. Edge computing is the act of running workloads on these edge devices. Machine learning at the edge (ML@Edge) is a concept that brings the […]

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Amazon SageMaker Neo Helps Detect Objects and Classify Images on Edge Devices

Nomura Research Institute (NRI) is a leading global provider of system solutions and consulting services in Japan and an APN Premium Consulting Partner. NRI is increasingly getting requests to help customers optimize inventory and production plans, reduce costs, and create better customer experiences. To address these demands, NRI is turning to new sources of data, specifically […]

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Amazon SageMaker Neo Enables Pioneer’s Machine Learning in Cars

Pioneer Corp is a Japanese multinational corporation specializing in digital entertainment products. Pioneer wanted to help their customers check road and traffic conditions through in-car navigation systems. They developed a real-time, image-sharing service to help drivers navigate. The solution analyzes photos, diverts traffic, and sends alerts based on the observed conditions.  Because the pictures are of […]

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AWS launches open source Neo-AI project to accelerate ML deployments on edge devices

 At re:Invent 2018, we announced Amazon SageMaker Neo, a new machine learning feature that you can use to train a machine learning model once and then run it anywhere in the cloud and at the edge. Today, we are releasing the code as the open source Neo-AI project under the Apache Software License. This release […]

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