Today, Amazon Personalize is excited to announce recommenders which are optimized to deliver personalized experiences for common use cases in Media & Entertainment and Retail. It is now faster and easier to deliver high performing personalized user experiences in your applications without any ML expertise required. Recommenders reduce the time needed to build and deliver personalized experiences and fully manage the lifecycle of the experience to help ensure you recommend what is most relevant to your users.

Amazon CodeGuru is a developer tool powered by machine learning that provides intelligent recommendations to detect security vulnerabilities, improve code quality and identify an application’s most expensive lines of code.

Today, we are excited to announce the First Annual AWS BugBust re:Invent challenge. Java and Python developers of all skill levels, can compete to fix as many software bugs as possible to earn points and climb the global leaderboard. There will be an array of prizes, from hoodies and fly swatters to Amazon Echo Dots, available to participants who meet certain milestones in the challenge. There’s also the coveted title of “Ultimate AWS BugBuster” accompanied by a cash prize of $1500 for whomever earns the most points by squashing bugs during the event.

Amazon Personalize now offers intelligent user segmentation which allows you to run more effective prospecting campaigns through your marketing channels. Traditionally, user segmentation has relied on demographic information and manually curated business rules to make assumptions about users’ intentions and assign them to pre-defined audience segments. Amazon Personalize uses machine learning techniques to learn about your items, users, and how your users interact with your items. Amazon Personalize segments users based on their preferences for different products, categories, brands, and more. This can help you drive higher engagement with marketing campaigns, increase retention through targeted messaging, and improve the return on investment for your marketing spend.

Calling all Gadget Masters! Once again we are looking for the brightest and most talented young electronics engineers in the UK, as part of EW BrightSparks in 2022.

This story continues at Last chance to enter for EW BrightSparks of 2022!

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There’s a hydrogen project near Glasgow, IBM’s view of quantum advantage, DARPA contracts fro military antennas, booming smartphone production and Samsung building a $17 billion foundry fab in Texas…

This story continues at Most Read articles – Quantum advantage, RF sensing, Samsung fab

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Advantech has based a series of small AI inferencing computers around the Nvidia Jetson family. The AIR-020 series is 139 x 110 x 44.5mm, and the company sees them being used in automated guided vehicles (AGV), autonomous mobile robots (AMR), medical imaging, traffic monitoring, defect inspection and people counting. AIR-020X – Nvidia Jetson Xavier NX SoM embedded, up to …

This story continues at Small Nvidia Jetson industrial PCs for AI

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The University of Cambridge has developed a squishy jelly with 80% water content that is unfazed by being run over with a car. “At 80% water content, you’d think it would burst apart like a water balloon, but it doesn’t: it stays intact and withstands huge compressive forces,” said Professor Oren Scherman who led the …

This story continues at Super-squidgy gel is super-tough for soft robotics

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Amazon QuickSight now supports dataset versioning, which allows dataset owners to understand historical changes within a dataset, preview a specific version, or revert back to a previous version if needed. Dataset versions can be viewed and tracked via the UI, allowing dataset owners to view versions and switch to a specific version via UI. Dataset Versions gives dataset authors the confidence to experiment with their content, knowing that their older versions are available and that they easily can revert back to it when required.

EMR Studio is an integrated development environment (IDE) that makes it easy for data scientists and data engineers to develop, visualize, and debug big data and analytics applications written in R, Python, Scala, and PySpark. Today, we are excited to announce two new capabilities in EMR Studio. First, you can now more easily execute python scripts directly from the EMR Studio Notebooks. Second, you can execute other dependent Jupyter notebooks directly from a notebook in EMR Studio. Earlier, both of these capabilities required manually copying these files from EMR Studio to the EMR Cluster.