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Favorite 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
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Shared by AWS Machine Learning December 9, 2020
Favorite Core ML is a machine learning (ML) model format created and supported by Apple that compiles, deploys, and runs on Apple devices. Developers who train their models in popular frameworks such as TensorFlow and PyTorch convert models to Core ML format to deploy them on Apple devices. AWS has
Read More Shared by AWS Machine Learning December 9, 2020
Favorite Amazon SageMaker Neo now uses the NVIDIA TensorRT acceleration library to increase the speedup of machine learning (ML) models on NVIDIA Jetson devices at the edge and AWS g4dn and p3 instances in the AWS Cloud. Neo compiles models from TensorFlow, TFLite, MXNet, PyTorch, ONNX, and DarkNet to make
Read More Shared by AWS Machine Learning December 9, 2020
Favorite Amazon SageMaker Neo was launched at AWS re:Invent 2018. It made notable performance improvement on models with statically known input and output data shapes, typically image classification models. These models are usually composed of a stack of blocks that contain compute-intensive operators, such as convolution and matrix multiplication. Neo
Read More Shared by AWS Machine Learning December 9, 2020
Favorite Amazon SageMaker Neo enables developers to train machine learning (ML) models once and optimize them to run on any Amazon SageMaker endpoints in the cloud and supported devices at the edge. Since Neo was first announced at re:Invent 2018, we have been continuously working with the Neo-AI open-source communities
Read More Shared by AWS Machine Learning December 9, 2020
Favorite We’re excited to announce the Amazon Forecast Weather Index, which can increase your forecasting accuracy by automatically including local weather information in your demand forecasts with one click and at no extra cost. Weather conditions influence consumer demand patterns, product merchandizing decisions, staffing requirements, and energy consumption needs. However,
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Favorite The difference between Knowledge Sharing and Knowledge Management lies in three words – systematic, routine, strategic. Quite often we find clients who don’t like the term “knowledge management” and prefer something like “knowledge sharing” instead. Often this comes from the assumption that “knowledge management” means “the management of knowledge”,
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Shared by Nick Milton December 9, 2020
Favorite This post is co-written by John Duprey and Filippo Pompili from Thomson Reuters. Thomson Reuters (TR) is one of the world’s most trusted providers of answers, helping professionals make confident decisions and run better businesses. Teams of experts from TR bring together information, innovation, and confident insights to unravel
Read More Shared by AWS Machine Learning December 8, 2020
Favorite Internal company search seldom works as well as Google, because so few people optimise the findability of their content. Image from Wikimedia commons People often cite Google as the gold-standard in search, but partly Google works so well because of the prevalence of search-engine optimisation in the World Wide
Read More Shared by Nick Milton December 8, 2020
Favorite A year ago, Google’s Quantum AI team achieved a beyond-classical computation by using a quantum computer to outperform the world’s fastest classical computer. With this, we entered a new era of quantum computing. We still have a long journey ahead of us to find practical applications, and we know
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Shared by Google AI Technology December 7, 2020