AWS News Blog
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AWS Week in Review – December 12, 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! The world is asynchronous, is what Werner Vogels, Amazon CTO, reminded us during his keynote last week at AWS re:Invent. At the beginning of the keynote, he showed us how […]
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 […]
New — Create Point-to-Point Integrations Between Event Producers and Consumers with Amazon EventBridge Pipes
It is increasingly common to use multiple cloud services as building blocks to assemble a modern event-driven application. Using purpose-built services to accomplish a particular task ensures developers get the best capabilities for their use case. However, communication between services can be difficult if they use different technologies to communicate, meaning that you need to […]
Step Functions Distributed Map – A Serverless Solution for Large-Scale Parallel Data Processing
I am excited to announce the availability of a distributed map for AWS Step Functions. This flow extends support for orchestrating large-scale parallel workloads such as the on-demand processing of semi-structured data. Step Function’s map state executes the same processing steps for multiple entries in a dataset. The existing map state is limited to 40 […]
AWS Marketplace Vendor Insights – Simplify Third-Party Software Risk Assessments
Update 8 February 2023: I edited this blog post to remove the “preview” messaging for AWS Artifact third-party reports. —- AWS Marketplace Vendor Insights is a new capability of AWS Marketplace. It simplifies third-party software risk assessments when procuring solutions from the AWS Marketplace. It helps you to ensure that the third-party software continuously meets […]
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 […]
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, […]
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. […]