Today, we are excited to announce the AWS DeepRacer League’s 2020 season is nearing the final lap with the Championship at AWS re:Invent 2020. From November 10 through December 15, there are three ways to join in the racing fun: learn how to develop a competitive reinforcement learning model through our sessions, enter and compete in the racing action for a chance to win prizes, and watch to cheer on other developers as they race for the cup. More than 100 racers have already qualified for the Championship Cup, but there is still time to compete. Log in today to qualify for a chance to win the Championship Cup by entering the Wildcard round, offering the top 5 racers spots in the Knockout Rounds.

The EKS Construct Library is an AWS CDK module that helps customers provision Amazon EKS clusters using infrastructure-as-code best practices. Up until now, it has been in an experimental state, incorporating lots of customer feedback and undergoing multiple API and behavioral changes. Starting from version 1.65.0 (https://github.com/aws/aws-cdk/releases/tag/v1.65.0), the library is graduating to Developer Preview. This means that we are not planning any breaking changes going forward and are preparing the library for GA.

AWS Step Functions is now integrated with Amazon EKS, making it easier to build resilient applications that orchestrate jobs running on Kubernetes with AWS services such as AWS Lambda, Amazon SNS, and Amazon SQS with minimal code. You can now build workflows including steps that launch tasks in Amazon EKS and wait for its completion without writing code to manage the state of the Kubernetes job.  

AWS Shield Advanced now allows you to bundle resources into protection groups, giving you a self-service way to customize the scope of detection and mitigation for your application by treating multiple resources as a single unit. Resource grouping improves the accuracy of detection, reduces false positives, eases automatic protection of newly created resources, and accelerates the time to mitigate attacks against multiple resources. For example, if an application consists of four CloudFront distributions, you can add them to one protection group to receive detection and protection for the collection of resources as a whole. Reporting can be consumed at the protection group level, in addition to the resource level, giving a more holistic view of overall application health.

Starting today, Amazon Augmented AI (Amazon A2I) is a HIPAA eligible service. Amazon Augmented AI makes it easy to build the workflows required for human review of ML predictions. HIPPA eligibility applies to AWS Regions where the service is available and means you can use Amazon A2I to help you add human review of Protected Health Information (PHI) to power your healthcare workflows through your private workforce.

Today we are excited to announce that Amazon SageMaker Studio now supports multi-GPU instances of ml.g4dn.12xlarge, ml.p3.8xlarge, and ml.p3.16xlarge. Multi-GPU instances accelerate machine learning model training significantly, allowing users to train more advanced machine learning models that are too large to fit into a single GPU. They also provide the flexibility to process larger batches of data such as 4k images for image classification and object detection.

Amazon QuickSight now supports Waterfall charts. Waterfall charts show how any metric is affected positively or negatively by a series of contributing factors. Dashboard authors can create a waterfall chart by choosing this new visual type from the visuals menu. See here for more details.  

Amazon VPC Container Networking Interface (CNI) Plugin version 1.7 is now the default for newly created Amazon EKS clusters.

AWS RoboMaker WorldForge now supports tag-on-create for 3D simulation worlds, world generation jobs, and world export jobs. RoboMaker WorldForge is a capability that makes it faster, easier, and less expensive to create a multitude of 3D simulation worlds for testing and training robots. By tagging worlds at the time of creation, you can eliminate the need to run custom tagging scripts after world creation, which can save time and make it easier to manage simulation worlds.  

Amazon Lex is a service for building conversational interfaces into any application using voice and text. Today, we are launching support for French, Spanish, Italian and Canadian French. With these new languages, you can build and expand your conversational experiences to better understand and engage your customer base. Amazon Lex can be applied to a diverse set of use cases such as virtual agents, conversational IVR systems, self-service chatbots, or application bots.