Today, Amazon Transcribe announces the general availability of generative AI-powered call summarization available through the Amazon Transcribe Call Analytics API. Generative call summarization delivers a concise summary of contact center interactions, capturing key components such as why the customer called, how the issue was addressed, and what follow-up actions were identified. Contact center agents spend precious time after each call manually summarizing the notes. Supervisors also spend significant time listening to call recordings or reading entire transcripts while investigating caller issues. With generative call summarization, Amazon Transcribe Call Analytics can now automatically condense the entire call recording into a concise summary. For example, this is a sample summary of a 10-minute call: “Customer reported a missing order 10 days after the expected delivery date. The agent offered a free replacement and $10 credit. The agent will follow-up with the customer in 2 days to confirm the receipt of the replacement order”. After completing a customer interaction, agents can directly proceed to help the next customer since they don’t have to summarize a conversation, resulting in reduced customer wait times and improved agent productivity. Further, supervisors can review the summary when investigating a customer issue to get a gist of the conversation, without having to listen to the entire call recording or read the transcript. The generative call summarization capability is currently supported in English language and is available in the following AWS regions: US East (N. Virginia) and US West (Oregon). You will incur additional charges as described in pricing. To learn more, see the blog post and documentation.

We are excited to announce public availability of an enhanced dataset discovery workflow for AWS Mainframe Modernization File Transfer with BMC. This new capability makes it easier for users to discover and select mainframe data sets for conversion and transfer to AWS. Users can now browse the mainframe data set catalog directly from the AWS Mainframe Modernization service console, select data sets from one or multiple mainframe volumes for transfer, view extended data set metadata, and choose data set codepage conversions. The enhanced workflow provides an intuitive and unified mechanism for mainframe data access and transfer. AWS Mainframe Modernization File Transfer allows customers to seamlessly discover, copy and convert mainframe data sets for a variety of use cases such as mainframe application modernization and migration, and mainframe data driven augmentation using AWS. Using advanced compression, conversion of source mainframe encodings, and automation, mainframe data sets can be transferred to Amazon S3 storage. Once the mainframe data is on AWS, it can be harnessed for application modernization, analytics, Machine Learning, and Artificial Intelligence enabling agility, cost savings, and innovations. AWS Mainframe Modernization File Transfer is available through the AWS Mainframe Modernization service console. To learn more, visit AWS Mainframe Modernization service product and documentation pages.

We are excited to announce AWS HealthOmics now supports the ability to share HealthOmics workflows across AWS accounts. AWS HealthOmics is a fully managed service that empowers healthcare and life science organizations to store, query, analyze omics data, and generate insights to improve health and drive scientific discoveries. With this release, customers can now develop analyses within a single AWS account and share them with other AWS accounts in the same organization or across organizations. With this feature, customers can now share analyses that are defined as HealthOmics private workflows with both internal and external collaborators. Users can then start runs without having to configure any of the underlying workflow script or having to know the specific bioinformatics languages they’re written in. By running from the same workflow, bioinformaticians can enable reproducible science and validate experiments more easily. Cross-account workflow sharing is supported in the following AWS HealthOmics regions: US East (N. Virginia), US West (Oregon), Europe (Frankfurt, Ireland, London), Asia Pacific (Singapore), and Israel (Tel Aviv). To get started, see the AWS documentation.

Amazon DynamoDB now supports an AWS Fault Injection Service action to pause replication for global tables. FIS is a fully managed service for running controlled fault injection experiments to improve an application’s performance, observability, and resilience. Global tables replicate your Amazon DynamoDB tables automatically across your choice of AWS Regions to achieve fast, local read and write performance. Customers can use the new FIS action to observe how their application responds to a pause in regional replication, and tune their monitoring and recovery process to improve resiliency and application availability. Global tables are designed to meet the needs of high availability applications, providing you 99.999% availability, increased application resiliency, and improved business continuity. This new FIS action reproduces the real-world behavior when replication to a global table replica is interrupted and resumed.  This lets customers test and build confidence that their application responds as intended when resources in a Region are not accessible. Customers can create an experiment template in FIS to integrate the experiment with continuous integration and release testing and to combine with other FIS actions. For example, DynamoDB Pause Replication is combined with other actions in the Cross-Region: Connectivity scenario to isolate a Region. DynamoDB Pause Replication is now available in all AWS commercial Regions where FIS is available. To learn more, visit the DynamoDB FIS actions documentation.

Amazon Location Service has released a Places plugin for MapLibre GL JS Geocoder, simplifying the integration of Amazon Location Places Service with MapLibre. Along with the authentication libraries, this plugin provides a frictionless experience to use Amazon Location Places with MapLibre GL JS.  This plugin integrates Amazon Location Places APIs into Search Control that can be added to a map in MapLibre, enabling developers to expedite their application development. Web developers can use the integration library (Amazon Location for MapLibre GL Geocoder) to seamlessly call Places APIs (SearchPlaceIndexForText, SearchPlaceIndexForPosition, GetPlace, SearchPlaceIndexForSuggestions) and easily integrate location-based features into their applications with minimal additional code and without introducing new dependencies. To learn more, visit to the Amazon Location Service Developer Guide. Amazon Location Service is a fully managed service that helps developers easily and securely add maps, points of interest, geocoding, routing, tracking, and geofencing to their applications without compromising on data quality, user privacy, or cost. Amazon Location Service is available in the following AWS Regions: US East (Ohio), US East (N. Virginia), US West (Oregon), Asia Pacific (Mumbai), Asia Pacific (Singapore), Asia Pacific (Sydney), Asia Pacific (Tokyo), Canada (Central), Europe (Frankfurt), Europe (Ireland), Europe (London), Europe (Stockholm), South America (São Paulo), and AWS GovCloud (US-West).

We are excited to announce AWS HealthOmics private workflows now support file systems that dynamically scale with your workflow. AWS HealthOmics is a fully managed service that empowers healthcare and life science organizations to store, query, analyze omics data to generate insights to improve health and drive scientific discoveries. With this release, customers can now choose between static and dynamic run storage options. Dynamic run storage automatically scales storage up and down based on file system utilization during a private workflow run and ensures your workflow always has sufficient storage provisioned. This enables faster workflow startup times and is ideal for both small workflows that need to run quickly and iterative development cycles during new workflow prototyping. Dynamic run storage is supported in the following AWS HealthOmics regions: US East (N. Virginia), US West (Oregon), Europe (Frankfurt, Ireland, London), Asia Pacific (Singapore) and Israel (Tel Aviv). To get started using dynamic run storage, see the Running Workflows section in the AWS HealthOmics documentation.

Today, AWS announces the general availability of RubyGems support in CodeArtifact. Gems, which are used to distribute Ruby libraries, can now be stored in CodeArtifact. Popular tools including the RubyGems and Bundler CLIs can be used to publish and download gems from CodeArtifact repositories. Developers can configure CodeArtifact to fetch gems from RubyGems.org, the Ruby community’s gem hosting service. When a RubyGems package manager is connected to a CodeArtifact repository, CodeArtifact will automatically fetch gems requested by the client from RubyGems.org and store them in the CodeArtifact repository. By storing both private first-party gems and public, third-party gems in CodeArtifact, developers can access their critical application dependencies from a single source. CodeArtifact support for RubyGems is available in all 13 CodeArtifact regions. To learn more, see AWS CodeArtifact.

AWS Launch Wizard now allows you to automate deployment of SAP Web Dispatcher. This launch expands on existing Launch Wizard capabilities that allow you to automate deployment of SAP HANA, SAP NetWeaver based applications on HANA and ASE databases, SAP BW/4HANA, SAP S/4HANA, and SAP S/4HANA foundations using APIs or a console-based approach. SAP Web Dispatcher helps you achieve optimal utilization of resources including load balancing, session management, and URL filtering for your SAP applications. This launch supports deployment of SAP Web Dispatcher alongside SAP HANA and SAP NetWeaver deployments in single-node, distributed, and high availability(HA) architecture patterns to meet application and performance requirements. Additionally, you can optionally setup Load Balancer to load balance access requests to Web Dispatcher(s) for HA deployments. Visit the AWS Launch Wizard workload availability for details of which Launch Wizard supported workloads are available in each of the regions. To learn more about AWS Launch Wizard, visit the Launch Wizard Page, or learn how to deploy SAP Web Dispatcher on AWS with AWS Launch Wizard in this blog.

63 years ago, in Electronics Weekly’s issue of April 26th 1961, this ad appeared from EEV.

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Semiconductor research lab Imec has demonstrated wafer-bonding with 400nm pitch copper conductors across the boundary, proposing the technology for logic-on-logic and memory-on-logic wafer stacking within ICs, and for adding back-side …

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