Amazon QuickSight dashboards can now be embedded in applications. As an application developer, you can now create rich, interactive dashboards in QuickSight and embed them into your application portals and websites, without having to investigate charting libraries, add specialized analytics know-how to their teams, or set up, manage and optimize servers to scale to your growing userbase. 

Today, we are announcing the preview availability of ML Insights for Amazon QuickSight. ML Insights allows customers to discover hidden trends and outliers, identify key business drivers, forecast future results, and summarize their data in easy-to-understand, natural language narratives, without spending countless hours on manual analysis and investigation. With ML-powered anomaly detection, customers can continuously analyze their data across billions of data points to uncover hidden insights that are often buried in aggregates, not visible in plain sight, and are not scalable with manual analysis. With ML-powered forecasting, non-technical business users can now predict their key business metrics with point and click simplicity. Finally, we’re announcing auto-narratives, a new feature that automatically delivers insights in plain language, embedded contextually in the dashboard, allowing customers to create a shared understanding of data across the organization, without interpreting complex visualizations. You don’t need any ML, excel modeling, or domain expertise to use these features. Read our blog post to learn more about these features.

The nearly mile-long white and colored illumination spans bridges, climbs landmark skyscrapers, and marks Signify’s largest-ever connected architectural lighting project.

Samsung has added full-spectrum white LEDs to its horticultural-lighting-targeted portfolio along with new blue, red, and far-red LEDs, and announced horticultural modules, while Luminus Devices touts CMH replacement and Seoul Semiconductor wins award for SunLike.

AWS RoboMaker is a service that makes it easy to develop, simulate, and deploy intelligent robotics applications at scale. RoboMaker extends the most widely used open-source robotics software framework, Robot Operating System (ROS), with connectivity to cloud services. This includes AWS machine learning services, monitoring services, and analytics services that enable a robot to stream data, navigate, communicate, comprehend, and learn. RoboMaker provides a robotics development environment for application development, a robotics simulation service to accelerate application testing, and a robotics fleet management service for remote application deployment, update, and management.

S3 Intelligent-Tiering is a new Amazon S3 storage class designed for customers who want to optimize storage costs automatically when data access patterns change, without performance impact or operational overhead. S3 Intelligent-Tiering is the first cloud object storage class that delivers automatic cost savings by moving data between two access tiers — frequent access and infrequent access — when access patterns change, and is ideal for data with unknown or changing access patterns.

Today we are announcing 2x improvement in peak performance of Provisioned IOPS SSD (io1) Volumes from 32,000 IOPS to 64,000 IOPS and from 500 MB/s to 1,000 MB/s of throughput per volume when attached to Nitro system EC2 instances.

AWS DataSync is an online data transfer service that makes it easy for you to automate movement of data between on-premises storage and Amazon S3 or Amazon Elastic File System (Amazon EFS). DataSync uses a purpose-built protocol to accelerate and secure data transfer over the Internet or AWS Direct Connect, at speeds up to 10 times faster than open-source tools.

S3 Batch Operations is a new feature that makes it simple for customers to manage billions of objects stored in Amazon S3, with a single API request or a few clicks in the S3 Management Console. Now, all AWS customers can make changes to object properties and metadata, and perform other storage management tasks – such as copying objects between buckets, replacing tag sets, modifying access controls, and restoring archived objects from Amazon S3 Glacier – for any number of S3 objects in minutes instead of months.