Category: Amazon SageMaker Neo

Starting Monday, October 5, 2020, the NVIDIA GPU Technology Conference (GTC) is offering online sessions for you to learn AWS best practices to accomplish your machine learning (ML), virtual workstations, high performance computing (HPC), and internet of things (IoT) goals faster and more easily. Amazon Elastic Compute Cloud (Amazon EC2) instances powered by NVIDIA GPUs […]

When running deep learning models in production, balancing infrastructure cost versus model latency is always an important consideration. At re:Invent 2018, AWS introduced Amazon SageMaker Neo and Amazon Elastic Inference, two services that can make models more efficient for deep learning. In most deep learning applications, making predictions using a trained model—a process called inference—can […]

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 […]

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 […]

 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 […]