Here are the key discussion topics from the AWS re:Invent 2020 Infrastructure Keynote from Peter DeSantis – Senior VP of Global Infrastructure and Customer Support, with a focus on efforts to improve resiliency, availability, and sustainability for its customers: AWS Nitro System: Enables faster innovation and enhanced security. Nitro version hypervisor chips is the most […]
Continue reading..AWS re:Invent Recap: Infrastructure KeynoteWhat happened? Amazon SageMaker Edge Manager was announced during the re:Invent Machine Learning Keynote. This new feature gives developers model management tools for to optimize, secure, monitor, and maintain machine learning models on fleets of edge devices such as smart cameras, robots, personal computers, and mobile devices. Why is it important? Device Compatibility: It enables […]
Continue reading..AWS re:Invent Recap: Amazon SageMaker Edge ManagerWhat happened? Amazon SageMaker Debugger, a tool that monitors machine learning training performance to help developers train models faster, was announced during the re:Invent 2020 Machine Learning keynote. This tracks the system resource utilization and creates alerts for problems during training. With these new capabilities, automatic recommendations for resource allocation for training jobs, resulting in […]
Continue reading..AWS re:Invent Recap: Amazon SageMaker DebuggerWhat happened? AWS released Amazon SageMaker Clarify, a new tool for mitigating bias in machine learning model that helps customers more accurately and rapidly detect bias to build better solutions. This provides critical data and insights that increase transparency to help support analysis and explanation of model behavior to stakeholders and customers. Why is it […]
Continue reading..AWS re:Invent Recap: Amazon SageMaker ClarifyHere are the key announcements from the re:Invent 2020 Machine Learning Keynote: Faster Distributed Training on Amazon SageMaker is the quickest and most efficient approach for training large deep learning models and datasets. Through model parallelism and data parallelism, SageMaker distributed training automatically splits deep learning models and datasets for training in significantly less time […]
Continue reading..AWS re:Invent Recap: Machine Learning KeynoteWhat Happened: The newest AWS custom-designed chip, AWS Trainium, was announced during Andy Jassy’s 2020 re:Invent keynote, with the projected best price performance for training Machine Learning (ML) models in the cloud. Meant for deep learning training workloads for applications, it includes capabilities of image classification, semantic search, translation, voice recognition, NLP (Natural Language Processing), […]
Continue reading..AWS 2020 re:Invent Recap: AWS TrainiumWhat happened? The new service, Amazon SageMaker Pipelines, has been launched to provide continuous integration and delivery pipelines that automate steps of ML (Machine Learning) workflows. It’s the first CI/CD service for ML to build, store, and track automated workflows and also create an audit trail for training data and modeling configurations. Why is it […]
Continue reading..AWS re:Invent Recap: Amazon SageMaker PipelinesWhat Happened: With machine learning workloads growing rapidly and faster machines needed for training models in the cloud, Andy Jassy announced Habana Gaudi-based Amazon EC2 Instances will be available in the first half of 2021. Powered by new Habana Gaudi pre-processors from Intel, users can expect a 40% better price/performance over the current GPU based […]
Continue reading..AWS re:Invent Recap: Habana Gaudi Based EC2 System