AWS Week in Review – July 4, 2022

This post is part of our Week in Review series. Check back each week for a quick roundup of interesting news and announcements from AWS! Summer has arrived in Finland, and these last few days have been hotter than in the Canary Islands! Today in the US it is Independence Day. I hope that if Read more about AWS Week in Review – July 4, 2022[…]

New – Amazon SageMaker Ground Truth Now Supports Synthetic Data Generation

Today, I am happy to announce that you can now use Amazon SageMaker Ground Truth to generate labeled synthetic image data. Building machine learning (ML) models is an iterative process that, at a high level, starts with data collection and preparation, followed by model training and model deployment. And especially the first step, collecting large, Read more about New – Amazon SageMaker Ground Truth Now Supports Synthetic Data Generation[…]

AWS Week in Review – June 13, 2022

This post is part of our Week in Review series. Check back each week for a quick roundup of interesting news and announcements from AWS! Last Week’s Launches I made a short trip to Austin, Texas last week in order to visit and learn from some customers. As is always the case, the days when Read more about AWS Week in Review – June 13, 2022[…]

Amazon SageMaker Serverless Inference – Machine Learning Inference without Worrying about Servers

In December 2021, we introduced Amazon SageMaker Serverless Inference (in preview) as a new option in Amazon SageMaker to deploy machine learning (ML) models for inference without having to configure or manage the underlying infrastructure. Today, I’m happy to announce that Amazon SageMaker Serverless Inference is now generally available (GA). Different ML inference use cases Read more about Amazon SageMaker Serverless Inference – Machine Learning Inference without Worrying about Servers[…]

Announcing Fully Managed RStudio on Amazon SageMaker for Data Scientists

Two years ago, we introduced Amazon SageMaker Studio, the industry’s first fully integrated development environment (IDE) for machine learning (ML). Amazon SageMaker Studio provides a single, web-based visual interface where you can perform all ML development steps, improving data science team productivity by up to 10 times Many data scientists love the R project, an Read more about Announcing Fully Managed RStudio on Amazon SageMaker for Data Scientists[…]

Scaling Ad Verification with Machine Learning and AWS Inferentia

Amazon Advertising helps companies build their brand and connect with shoppers, through ads shown both within and beyond Amazon’s store, including websites, apps, and streaming TV content in more than 15 countries. Businesses or brands of all sizes including registered sellers, vendors, book vendors, Kindle Direct Publishing (KDP) authors, app developers, and agencies on Amazon Read more about Scaling Ad Verification with Machine Learning and AWS Inferentia[…]

Amazon SageMaker Named as the Outright Leader in Enterprise MLOps Platforms

Over the last few years, Machine Learning (ML) has proven its worth in helping organizations increase efficiency and foster innovation. As ML matures, the focus naturally shifts from experimentation to production. ML processes need to be streamlined, standardized, and automated to build, train, deploy, and manage models in a consistent and reliable way. Perennial IT Read more about Amazon SageMaker Named as the Outright Leader in Enterprise MLOps Platforms[…]

Amazon Redshift ML Is Now Generally Available – Use SQL to Create Machine Learning Models and Make Predictions from Your Data

With Amazon Redshift, you can use SQL to query and combine exabytes of structured and semi-structured data across your data warehouse, operational databases, and data lake. Now that AQUA (Advanced Query Accelerator) is generally available, you can improve the performance of your queries by up to 10 times with no additional costs and no code Read more about Amazon Redshift ML Is Now Generally Available – Use SQL to Create Machine Learning Models and Make Predictions from Your Data[…]

Decrease Your Machine Learning Costs with Instance Price Reductions and Savings Plans for Amazon SageMaker

Launched at AWS re:Invent 2017, Amazon SageMaker is a fully-managed service that has already helped tens of thousands of customers quickly build and deploy their machine learning (ML) workflows on AWS. To help them get the most ML bang for their buck, we’ve added a string of cost-optimization services and capabilities, such as Managed Spot Read more about Decrease Your Machine Learning Costs with Instance Price Reductions and Savings Plans for Amazon SageMaker[…]

Amazon SageMaker JumpStart Simplifies Access to Pre-built Models and Machine Learning Solutions

Today, I’m extremely happy to announce the availability of Amazon SageMaker JumpStart, a capability of Amazon SageMaker that accelerates your machine learning workflows with one-click access to popular model collections (also known as “model zoos”), and to end-to-end solutions that solve common use cases. In recent years, machine learning (ML) has proven to be a Read more about Amazon SageMaker JumpStart Simplifies Access to Pre-built Models and Machine Learning Solutions[…]