New – Process PDFs, Word Documents, and Images with Amazon Comprehend for IDP

Today we are announcing a new Amazon Comprehend feature for intelligent document processing (IDP). This feature allows you to classify and extract entities from PDF documents, Microsoft Word files, and images directly from Amazon Comprehend without you needing to extract the text first. Many customers need to process documents that have a semi-structured format, like Read more about New – Process PDFs, Word Documents, and Images with Amazon Comprehend for IDP[…]

New for Amazon SageMaker – Perform Shadow Tests to Compare Inference Performance Between ML Model Variants

As you move your machine learning (ML) workloads into production, you need to continuously monitor your deployed models and iterate when you observe a deviation in your model performance. When you build a new model, you typically start validating the model offline using historical inference request data. But this data sometimes fails to account for Read more about New for Amazon SageMaker – Perform Shadow Tests to Compare Inference Performance Between ML Model Variants[…]

Next Generation SageMaker Notebooks – Now with Built-in Data Preparation, Real-Time Collaboration, and Notebook Automation

In 2019, we introduced Amazon SageMaker Studio, the first fully integrated development environment (IDE) for data science and machine learning (ML). SageMaker Studio gives you access to fully managed Jupyter Notebooks that integrate with purpose-built tools to perform all ML steps, from preparing data to training and debugging models, tracking experiments, deploying and monitoring models, Read more about Next Generation SageMaker Notebooks – Now with Built-in Data Preparation, Real-Time Collaboration, and Notebook Automation[…]

New – Share ML Models and Notebooks More Easily Within Your Organization with Amazon SageMaker JumpStart

Amazon SageMaker JumpStart is a machine learning (ML) hub that can help you accelerate your ML journey. SageMaker JumpStart gives you access to built-in algorithms with pre-trained models from popular model hubs, pre-trained foundation models to help you perform tasks such as article summarization and image generation, and end-to-end solutions to solve common use cases. Read more about New – Share ML Models and Notebooks More Easily Within Your Organization with Amazon SageMaker JumpStart[…]

AWS Machine Learning University New Educator Enablement Program to Build Diverse Talent for ML/AI Jobs

AWS Machine Learning University is now providing a free educator enablement program. This program provides faculty at community colleges, minority-serving institutions (MSIs), and historically Black colleges and universities (HBCUs) with the skills and resources to teach data analytics, artificial intelligence (AI), and machine learning (ML) concepts to build a diverse pipeline for in-demand jobs of Read more about AWS Machine Learning University New Educator Enablement Program to Build Diverse Talent for ML/AI Jobs[…]

AWS Week in Review – October 31, 2022

No tricks, just treats in this weekly roundup of news and announcements. Let’s switch our AWS Management Console into dark mode and dive right into it. Last Week’s Launches Here are some launches that got my attention during the previous week: AWS Local Zones in Hamburg and Warsaw now generally available – AWS Local Zones help Read more about AWS Week in Review – October 31, 2022[…]

Amazon EC2 Trn1 Instances for High-Performance Model Training are Now Available

Deep learning (DL) models have been increasing in size and complexity over the last few years, pushing the time to train from days to weeks. Training large language models the size of GPT-3 can take months, leading to an exponential growth in training cost. To reduce model training times and enable machine learning (ML) practitioners Read more about Amazon EC2 Trn1 Instances for High-Performance Model Training are Now Available[…]

New Hands-On Course for Business Analysts – Practical Decision Making using No-Code ML on AWS

Artificial intelligence (AI) is all around us. AI sends certain emails to our spam folders. It powers autocorrect, which helps us fix typos when we text. And now we can use it to solve business problems. In business, data-driven insights have become increasingly valuable. These insights are often discovered with the help of machine learning Read more about New Hands-On Course for Business Analysts – Practical Decision Making using No-Code ML on AWS[…]

AWS Week In Review – July 25, 2022

A few weeks ago, we hosted the first EMEA AWS Heroes Summit in Milan, Italy. This past week, I had the privilege to join the Americas AWS Heroes Summit in Seattle, Washington, USA. Meeting with our community experts is always inspiring and a great opportunity to learn from each other. During the Summit, AWS Heroes Read more about AWS Week In Review – July 25, 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[…]