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 you are celebrating, you’re having a great time. This week I’m very excited about some developer experience and artificial intelligence launches. Last Week’s Launches Here are some launches that got my attention during the previous week: AWS SAM Accelerate is now generally available – SAM Accelerate is a new capability of the AWS Serverless Application Model CLI, which makes it easier for serverless developers to…

AWS Week in Review – June 27, 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! It’s the beginning of a new week, and I’d like to start with a recap of the most significant AWS news from the previous 7 days. Last week was special because I had the privilege to be at the very first EMEA AWS Heroes Summit in Milan, Italy. It was a great opportunity of mutual learning as this community of experts shared their thoughts with AWS developer advocates, product managers, and technologists on topics such as containers, serverless, and machine learning. Last Week’s Launches Here are the launches that got my attention last week: Amazon…

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, diverse, and accurately labeled datasets for your model training, is often challenging and time-consuming. Let’s take computer vision (CV) applications as an example. CV applications have come to play a key role in the industrial landscape. They help improve manufacturing quality or automate warehouses. Yet, collecting the data to train these CV models often takes a long time or can be impossible. As a data…

Now in Preview – Amazon CodeWhisperer- ML-Powered Coding Companion

As I was getting ready to write this post I spent some time thinking about some of the coding tools that I have used over the course of my career. This includes the line-oriented editor that was an intrinsic part of the BASIC interpreter that I used in junior high school, the IBM keypunch that I used when I started college, various flavors of Emacs, and Visual Studio. The earliest editors were quite utilitarian, and grew in sophistication as CPU power become more plentiful. At first this increasing sophistication took the form of lexical assistance, such as dynamic completion of partially-entered variable and function names. Later editors were able to parse source code, and to offer assistance based on syntax…

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