My idea for manually setting a 16bit number using two potentiometers worked technically, but was not the brilliant method I had vaingloriously imagined 🙁 In summary, a keypad would be quicker to use, but this is simple to implement Not in summary, read on…. Note: scroll down if you want to look at the test …

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Well, hello, little Trilobot. What are you? A mid-level Raspberry Pi-based robot kit from Pimoroni, is the answer, designed with educational use in mind.

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Infineon is launching a new generation of 1,700V EconoDual IGBT modules at PCIM next week, using its IGBT7 die series. “With this new chip technology, the EconoDual 3 provides a current of 900A, and enables an improved power range for inverters,” according to the company. “Compared to modules with the previous IGBT4 chipset, FF900R17ME7_B11 with the …

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GCHQ’s National Cyber Security Centre is hosting a conference on cyber security in South Wales next week – 10-11 May – with an exhibition running alongside. Held in-person at ICC Wales in Newport, CyberUK 2022 has the overarching theme of ‘cyber security for the whole of society’, and according to NCSC will interest cyber security leaders …

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Intelligent metasufaces – structures that dynamically manipulate electromagnetic radiation using arrays of phase modifiers under the supervision of artificial intelligence – will be key to 6G communications and even computation, according to researchers from Peking, Southeast and Xidian Universities, who have published a survey of the state-of-the-art. “This field has refreshed human insights into many fundamental …

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Customers use Amazon Rekognition Face APIs to analyze faces within images and videos at scale without requiring any machine learning expertise. This enables use cases, such as identity verification, photo search, and media analysis. Amazon Rekognition has launched Face APIs version 6 to deliver higher accuracy for the face detection, comparison, and search features. Additionally, face detection latency has been reduced by 70%.

Starting today, the general-purpose Amazon EC2 M6a instances are now available in US East (Ohio) and Europe (Frankfurt). Additionally, compute-optimized Amazon EC2 C6a instances are now available in US East (Ohio), Asia Pacific (Mumbai), and Europe (Frankfurt). M6a and C6a instances are powered by 3rd generation AMD EPYC (code named Milan) processors with an all-core turbo frequency of 3.6 GHz. M6a instances deliver up to 35% better price performance compared to M5a instances, while C6a instances deliver up to 15% better price performance compared to C5a instances. Both M6a and C6a instances offer 10% lower cost than comparable x86-based EC2 instances. M6a and C6a instances are built on the AWS Nitro System, a combination of dedicated hardware and lightweight hypervisor, which delivers practically all of the compute and memory resources of the host hardware to your instances. M6a instances are SAP-Certified and a good fit for workloads such as web and application servers, back-end servers supporting enterprise applications, web servers, micro-services, multi-player gaming servers, caching fleets, as well as for application development environments. C6a instances are well suited for compute-intensive applications like batch processing, distributed analytics, high performance computing (HPC), ad serving, highly-scalable multiplayer gaming, and video encoding.

Amazon Kinesis Data Firehose is now available in the Asia Pacific (Jakarta) AWS Region.

Starting today, Amazon Chime SDK messaging is generally available in the Europe (Frankfurt) Region.

Amazon SageMaker Data Wrangler reduces the time it takes to aggregate and prepare data for machine learning (ML) from weeks to minutes in Amazon SageMaker Studio, the first fully integrated development environment (IDE) for ML. With SageMaker Data Wrangler, you can simplify the process of data preparation and feature engineering, and complete each step of the data preparation workflow, including data selection, cleansing, exploration, and visualization, from a single visual interface. SageMaker Data Wrangler runs on ml.m5.4xlarge by default. SageMaker Data Wrangler includes built-in data transforms and analyses written in PySpark so you can process large data sets (up to hundreds of gigabytes (GB) of data) efficiently on the default instance.