Verizon, the telecommunications company, and Skylo, a non-terrestrial network (NTN) service provider, have announced a partnership to launch a commercial direct-to-device messaging service via satellite. This will enable Verizon customers – …

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After 25 years of operation IBM is to close its R&D units in China. The units, called the  China Development Lab (CDL) and China Systems Lab (CSL), were set up …

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Sakana AI, a one year-old Tokyo startup founded by ex-Google researchers, has raised $137 million in a funding round led by Nvidia. Other investors are Khosla Ventures, New Enterprise Associates …

The post SakanaAI raises $137m led by Nvidia appeared first on Electronics Weekly .

A China state-controlled news site – the Global Times – has threatened ASML with long-term exclusion from the Chinese market if it complies with US restrictions on selling spares and …

The post China threatens ASML appeared first on Electronics Weekly .

Keysight has introduced a series of 14bit general purpose oscilloscopes with up to 1GHz bandwidth. The HD3 Series is “built from the ground up with a custom asic deep memory …

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Today, Amazon Simple Email Service (SES) launched enhancements to its onboarding experience to help customers easily discover and activate key SES features. The SES console now features an adaptive setup page that brings recommendations for optimal setup to the forefront. Additionally, the update introduces the option to enable the Virtual Deliverability Manager (VDM) within the initial onboarding wizard, offering maximum guidance from the beginning of the setup process.

Previously, the SES onboarding process focused primarily on the initial steps of authenticating domains and attaining production access. With an on-demand advisor check, this workflow guides customers to begin sending authenticated email that meets mailbox provider requirements with DKIM-alignment, SPF-alignment, and a DMARC policy. Now, the enhanced onboarding experience empowers customers to optimize their email deliverability from the start. Customers can easily configure email monitoring, provision dedicated IP addresses, and adjust sending limits to meet their projected volume – all through the adaptive setup page that detects their current configuration and provides tailored recommendations. With these enhancements, SES customers can be confident they are setting up their email infrastructure for long-term success from the beginning of their SES journey.

SES offers a guided onboarding experience in all AWS regions where SES is available.

For more information, please visit the documentation for getting started with SES .
 

Stable Image Ultra, Stable Diffusion 3 Large (SD3 Large), and Stable Image Core models from Stability AI are now generally available in Amazon Bedrock. These models will empower customers in various industries, including media, marketing, retail, and game development, to generate high-quality visuals with unprecedented speed and precision.

All three of these models are capable of generating stunningly photo-realistic images with exceptional detail, color accuracy, and lifelike lighting. Each model caters to diverse use cases:

• Stable Image Ultra – produces the highest quality, photo-realistic outputs, making it perfect for professional print media and large-format applications. This model excels at rendering exceptional detail and realism.
• Stable Diffusion 3 Large – strikes an ideal balance between generation speed and output quality, making it ideal for creating high-volume, high-quality digital assets like websites, newsletters, and marketing materials.
• Stable Image Core – optimized for fast and affordable image generation, making it great for rapidly iterating on concepts during the ideation phase.

These models enable customers to streamline creative processes, swiftly adapt to market trends, drive innovation through visual brainstorming, and gain a competitive advantage by boosting productivity, reducing costs, and improving visual communication across business functions.

Stability AI’s Stable Image Ultra, SD3 Large, and Stable Image Core models are now available in Amazon Bedrock in the US West (Oregon) AWS region. To learn more read the AWS News Blog or visit the Stability AI in Amazon Bedrock product page , and documentation . To get started with SD3 in Amazon Bedrock, visit the Amazon Bedrock console .

We are excited to announce the launch of enhanced management options for Amazon Timestream for InfluxDB, allowing you to scale your instance sizes up or down as needed and update your deployment configuration between Single-AZ and Multi-AZ, giving you greater flexibility and control over your time-series data processing and analysis.

Timestream for InfluxDB is extensively used in applications that require high-performance time-series data processing and analysis. You can quickly respond to changes in data ingestion rates, query volumes, or other workload fluctuations by scaling your instances sizes up and down, ensuring that your Timestream for InfluxDB instances always have the necessary resources to handle your workload and cost effectively. You can also change your availability configuration by moving between Single-AZ and Multi-AZ configurations depending on your needs and budget. This means you can focus on building and deploying your applications, rather than worrying about instance sizing and management.

Amazon Timestream for InfluxDB is available in the following AWS Regions: US East (Ohio), US East (N. Virginia), US West (Oregon), Asia Pacific (Tokyo), Asia Pacific (Sydney), Asia Pacific (Singapore), Asia Pacific (Mumbai), Europe (Ireland), Europe (Frankfurt), and Europe (Stockholm).

You can create a Amazon Timestream Instance from the Amazon Timestream console , AWS Command line Interface (CLI), or SDK, and AWS CloudFormation. To learn more about compute scaling for Amazon Timestream for InfluxDB, visit the product page, documentation , and pricing page .
 

Starting today, memory-optimized Amazon Compute Cloud (Amazon EC2) X2idn instances are available in Middle East (Bahrain) region. These instances, powered by 3rd generation Intel Xeon Scalable Processors and built with AWS Nitro System, are designed for memory-intensive workloads. They deliver improvements in performance, price performance, and cost per GiB of memory compared to previous generation X1 instances. These instances are SAP-certified for running Business Suite on HANA, SAP S/4HANA, Data Mart Solutions on HANA, Business Warehouse on HANA, SAP BW/4HANA, and SAP NetWeaver workloads on any database.

With this launch, X2idn are available in the following AWS Regions : US East (Ohio, N. Virginia), US West (Oregon, N. California), Africa (Cape Town), Asia Pacific (Hyderabad, Jakarta, Malaysia, Mumbai, Osaka, Seoul, Singapore, Sydney, Tokyo), China (Beijing, Nginxia), Middle East (Bahrain, Dubai), Europe (Frankfurt, Ireland, London, Milan, Paris, Stockholm, Spain, Zurich), Canada (Central), South America (São Paulo), and the AWS GovCloud (US-East, US-West) Regions. X2idn is available for purchase with Savings Plans, Reserved Instances, Convertible Reserved, On-Demand, and Spot instances, or as Dedicated instances or Dedicated hosts. To learn more, visit the EC2 X2i Instances Page, or connect with your AWS Support contacts.

You can now run petabyte-scale data analytics and machine learning on Amazon EMR Serverless directly from Amazon SageMaker Studio notebooks. EMR Serverless automatically provisions and scales the required resources, allowing you to focus on your data and models without having to configure, optimize, tune, or manage clusters. EMR Serverless automatically installs and configures open source frameworks and provides a performance-optimized runtime that is compatible with and faster than standard open source.

With this release, you can now visually create and browse EMR Serverless applications directly from SageMaker Studio and connect to them in a few simple clicks. Once connected to an EMR Serverless application, you can use Spark SQL, Scala, Python to interactively query, explore and visualize data, and run Apache Spark jobs to process data directly from Studio Notebooks. Jobs run fast because they use EMR’s performance-optimized versions of Spark. For e.g. Spark on EMR 7.1 is 4.5x faster than it’s open source equivalent . EMR Serverless offers fine-grained automatic scaling, which provisions and quickly scales the compute and memory resources to match the requirements of your application and you pay for only what you use.

These features are supported on SageMaker Distribution 1.10 and above, and are generally available in all AWS Regions where SageMaker Studio is available. To learn more, read the blog Use LangChain with PySpark for Processing documents at massive scale with Amazon SageMaker Studio and EMR Serverless , or the SageMaker Studio documentation here .