AWS Machine Learning Blog
Category: Amazon SageMaker Neo
Speeding up TensorFlow, MXNet, and PyTorch inference with Amazon SageMaker Neo
Various machine learning (ML) optimizations are possible at every stage of the flow during or after training. Model compiling is one optimization that creates a more efficient implementation of a trained model. In 2018, we launched Amazon SageMaker Neo to compile machine learning models for many frameworks and many platforms. We created the ML compiler […]
Join AWS and NVIDIA at GTC, October 5–9
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 […]
Increasing performance and reducing the cost of MXNet inference using Amazon SageMaker Neo and Amazon Elastic Inference
Note: Amazon Elastic Inference is no longer available. Please see Amazon SageMaker for similar capabilities. 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 […]
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 […]
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 […]
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 […]