[1] DeepMind, the AI research laboratory funded by Google's parent company, Alphabet, today published the results of a collaboration with mathematicians to apply AI toward discovering
new insights in areas of mathematics. DeepMind claims that its AI technology helped to uncover a new formula for a previously unsolved conjecture, as well as a connection between different areas of mathematics elucidated by studying the structure of knots.
"At DeepMind, we believe that AI techniques are already sufficient to have a foundational impact in accelerating scientific progress across many different disciplines," Alex Davies, DeepMind machine learning specialist, said in a statement. "Pure maths is one example of such a discipline, and we hope that [our work] can inspire other researchers to consider the potential for AI as a useful tool in the field."
What ostensibly sets DeepMind's work apart is its detection of the existence of patterns in mathematics with supervised learning — and giving insight into these patterns with attribution techniques from AI.
[2] Yesterday at its
re:Invent 2021 conference, Amazon announced the Amazon Web Services (AWS)
IoT TwinMaker, a service designed to make it easier for developers to create digital twins of real-time systems like buildings, factories, industrial equipment, and product lines. The company also debuted AWS
IoT FleetWise, an offering that makes it ostensibly easier and more cost-effective for automakers to collect, transform, and transfer vehicle data in the cloud in near-real-time.
With IoT TwinMaker, Amazon says that customers can
leverage prebuilt connectors to data sources like equipment, sensors, video feeds, and business applications to automatically build knowledge graphs and 3D visualizations. IoT TwinMaker supplies dashboards to help visualize operational states and updates in real time, mapping out the relationships between data sources.
IoT FleetWise enables AWS customers to collect and standardize data across fleets of upwards of millions of vehicles. IoT FleetWise can apply intelligent filtering to extract only what's needed from connected vehicles to reduce the volume of data being transferred. Moreover, it features tools that allow automakers to perform remote diagnostics, analyze fleet health, prevent safety issues, and improve autonomous driving systems.
>> Read more.
[3] Microsoft is rolling out a fully managed
load testing service for Azure, helping quality assurance testers and developers optimize their app's performance and scalability.
Load testing fits into the broader
software performance testing and quality assurance sectors, which might include everything from cross-platform web testing to continuous profiling for cutting cloud bills — it's all about ensuring that an application is robust and optimized for every potential scenario, minimizing outages and downtime for software in production environments.
But as its name suggests,
Azure Load Testing is designed with Azure customers in mind. This includes integrated Azure resource management and billing, and integrations with related products such as Azure Monitor, Microsoft's monitoring tool for applications, infrastructure, and networks.
"Azure Load Testing is designed from the ground up with a specific focus on Azure customers and delivering
Azure-optimized capabilities," Mandy Whaley, Microsoft's partner director of product for Azure dev tools, told VentureBeat.
>> Read more.
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