TDK has created a spin-memristor for analogue neural networks, and built a network that can separate three types of sound in real-time. It has been collaborating on memristors with French …

The post Robust analogue AI separates music, speech and noise appeared first on Electronics Weekly .

Raytheon has been awarded a three-year, two-phase contract from DARPA to develop ultra-wide bandgap semiconductors based on diamond and aluminum nitride. Both of these also have high thermal conductivity – …

The post Diamond and AlN semiconductors for RF devices appeared first on Electronics Weekly .

Vishay has introduced a pair of 1008 (2.5 x 2 x 1.2mm) power inductor types. “The commercial IHLL-1008AB-1Z and Automotive Grade IHLP-1008ABEZ-5A achieve the same performance as the next-smallest IHLP …

The post Inductors carry amps through 1008 bodies appeared first on Electronics Weekly .

Amazon Data Firehose (Firehose) can now deliver data streams into Apache Iceberg tables in Amazon S3.

Firehose enables customers to acquire, transform, and deliver data streams into Amazon S3, Amazon Redshift, OpenSearch, Splunk, Snowflake, and other destinations for analytics. With this new feature, Firehose integrates with Apache Iceberg, so customers can deliver data streams directly into Apache Iceberg tables in their Amazon S3 data lake. Firehose can acquire data streams from Kinesis Data Streams, Amazon MSK, or Direct PUT API, and is also integrated to acquire streams from AWS Services such as AWS WAF web ACL logs, Amazon CloudWatch Logs, Amazon VPC Flow Logs, AWS IOT, Amazon SNS, AWS API Gateway Access logs and many others listed here . Customers can stream data from any of these sources directly into Apache Iceberg tables in Amazon S3, and avoid multi-step processes. Firehose is serverless, so customers can simply setup a stream by configuring the source and destination properties, and pay based on bytes processed.

The new feature also allows customers to route records in a data stream to different Apache Iceberg tables based on the content of the incoming record. To route records to different tables, customers can configure routing rules using JSON expressions. Additionally, customers can specify if the incoming record should apply a row-level update or delete operation in the destination Apache Iceberg table, and automate processing for data correction and right to forget scenarios.

To get started, visit Amazon Data Firehose documentation , pricing , and console .

Amazon Managed Streaming for Apache Kafka (Amazon MSK) APIs now come with AWS PrivateLink support, allowing you to invoke Amazon MSK APIs from within your Amazon Virtual Private Cloud (VPC) without traversing the public internet.

By default, all communication between your Apache Kafka clients and your Amazon MSK provisioned clusters is private, and your data never traverses the internet. With this launch, clients can also invoke MSK APIs via a private endpoint. This allows client applications with strict security requirements to perform MSK specific actions, such as fetching bootstrap connection strings or describing cluster details, without needing to communicate over a public connection .

AWS PrivateLink support for Amazon MSK is available in all AWS Regions where Amazon MSK is available. To get started, follow the directions provided in the AWS PrivateLink documentation . To learn more about Amazon MSK, visit the Amazon MSK documentation .
 

Amazon Connect now supports the ability to initiate outbound SMS contacts, enabling you to help increase customer satisfaction by engaging your customers on their preferred communication channel. You can now deliver proactive SMS experiences for scenarios such as post-contact surveys, appointment reminders, and service updates, allowing customers to respond at their convenience. Additionally you can offer customers the option to switch to SMS while waiting in a call queue, eliminating their hold time.

To get started, add the new Send message block to a contact flow or use the new StartOutboundChatContact API to initiate outbound SMS contacts. This feature is available in US East (N. Virginia), US West (Oregon), Asia Pacific (Tokyo), Asia Pacific (Seoul), Asia Pacific (Singapore), Asia Pacific (Sydney), Canada (Central), Europe (Frankfurt), and Europe (London). To learn more and get started, please refer to the documentation for the Send message flow block and StartOutboundChatContact API.
 

Starting today, AWS Incident Detection and Response supports incident engagement in Japanese language. AWS Incident Detection and Response offers AWS Enterprise Support customers proactive engagement and incident management for critical workloads. With AWS Incident Detection and Response, AWS Incident Management Engineers (IMEs) are available 24/7 to detect incidents and engage with you within five minutes of an alarm from your workloads, providing guidance for mitigation and recovery.

This feature allows AWS Enterprise Support customers to interact with Japanese-speaking Incident Management Engineers (IMEs) who will provide proactive engagement and incident management for critical incidents. To use this service in Japanese, customers must select Japanese as their preferred language during workload onboarding.

For more details, including information on supported regions and additional specifics about the AWS Incident Detection and Response service, please visit the product page .
 

AWS announces general availability of AWS Organizations support in AWS Chatbot. AWS customers can now centrally govern access to their accounts from Slack and Microsoft Teams with AWS Organizations.

This launch introduces chatbot management policy type in AWS Organizations to control access to your organization’s accounts from chat channels. Using Service Control Policies (SCPs), customers can also globally enforce permission limits on CLI commands originating from chat channels.

With this launch, customers can use chatbot policies and multi-account management services in AWS Organizations to determine which permissions models, chat applications, and chat workspaces can be used to access their accounts. For example, you can restrict access to production accounts from chat channels in designated workspaces/teams. Customers can also use SCPs to specify guardrails on the CLI command tasks executed from chat channels. For example, you can specify deny all rds: delete-db-cluster CLI actions originating from chat channels.

AWS Organizations support in AWS Chatbot is available at no additional cost in all AWS Regions where AWS Chatbot is offered. Visit the Securing your AWS organization in AWS Chatbot documentation and blog to learn more.

Amazon EMR Serverless is a serverless option in Amazon EMR that makes it simple for data engineers and data scientists to run open-source big data analytics frameworks without configuring, managing, and scaling clusters or servers. Today, we are excited to announce job run admission control on Amazon EMR Serverless with support for job run concurrency and queuing controls.

Job run concurrency and queuing enables you to configure the maximum number of concurrent job runs for an application and automatically queues all other submitted job runs. This prevents job run failures caused when API limits are exceeded due to a spike in job run submissions or when resources are exhausted either due to an account or application’s maximum concurrent vCPUs limit or an underlying subnet’s IP address limit being exceeded. Job run queuing also simplifies job run management by eliminating the need to build complex queuing management systems to retry failed jobs due to limit errors (e.g., maximum concurrent vCPUs, subnet IP address limits etc.). With this feature, jobs are automatically queued and processed as concurrency slots become available, ensuring efficient resource utilization and preventing job failures.

Amazon EMR Serverless job run concurrency and queuing is available in all AWS Regions where AWS EMR Serverless is available, including the AWS GovCloud (US) Regions and excluding China regions. To learn more, visit Job concurrency and queuing in the EMR Serverless documentation.
 

Amazon announces DCV version 2024.0. In this latest release, NICE DCV has been renamed to Amazon DCV. The new DCV version introduces several enhancements, including support for Ubuntu 24.04 and enabling the QUIC UDP protocol by default. Amazon DCV is a high-performance remote display protocol designed to help customers securely access remote desktop or application sessions, including 3D graphics applications hosted on servers with high-performance GPUs.

Amazon DCV version 2024.0 introduces the following updates, features, and improvements:

• Renames to Amazon DCV. NICE DCV is now renamed as Amazon DCV. Additionally, Amazon has consolidated the WorkSpaces Streaming Protocol (WSP), used in Amazon WorkSpaces, with Amazon DCV. The renaming does not affect customer workloads, and there is no change to folder paths and internal tooling names.
• Supports Ubuntu 24.04, the latest LTS version of Ubuntu with the latest security patches and updates, providing improved stability and reliability. Additionally, the DCV client on Ubuntu 24.04 now natively supports Wayland, providing better performance through more efficient graphical rendering.
• Enables the QUIC UDP protocol by default, allowing end users to receive an optimized streaming experience.
• Adds the ability to blank the Linux host screen when a remote user is connected to the Linux server in a console session, preventing users physically present near the server from seeing the screen and interacting with the remote session using the input devices connected to the host.

For more information, please see the Amazon DCV 2024.0 release notes or visit the Amazon DCV webpage to get started with DCV.