Forget AI, all potential suckers have been roped in for that one, the current opportunity to rope a dope is quantum, Ed confides to his diary. The good thing about …

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As you head off to the European holiday spots spare a thought for your hotelier’s forebodings with 41% of European hoteliers believing that climate change will have a high or …

The post The Worry Of Europe’s Hoteliers appeared first on Electronics Weekly .

Europe’s smartphone shipments returned to growth in Q1 2024, increasing by 10% YoY, according to Counterpoint Research’s Market Monitor Service. This marked the region’s first YoY increase in shipments since …

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The UK’s Defence Science and Technology Laboratory (DSTL) has announced it has been developing a Radio Frequency Directed Energy Weapon (RFDEW), which it describes as a cutting-edge drone killer radio …

The post Radio Frequency Directed Energy Weapon targets swarms of drones appeared first on Electronics Weekly .

Volvo Trucks is developing trucks with combustion engines that run on hydrogen. On-road tests with trucks using hydrogen in combustion engines will begin in 2026, and the commercial launch is …

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Weebit Nano and Efabless have got together to enable fast and easy prototyping of  ICs using Weebit’s technology. Under the agreement, Efabless chipIgnite customers have access to Weebit’s ReRAM IP, …

The post Weebit Nano and Efabless hook up for prototyping appeared first on Electronics Weekly .

Starting today, Amazon Elastic Compute Cloud (Amazon EC2) M7i-flex, M7i, and C7i instances powered by custom 4th Generation Intel Xeon Scalable processors (code-named Sapphire Rapids) are available in the AWS GovCloud (US-East) Region. These custom processors, available only on AWS, offer up to 15% better performance over comparable x86-based Intel processors utilized by other cloud providers.

M7i-flex instances are the easiest way for you to get price-performance benefits for a majority of general-purpose workloads, and deliver up to 19% better price-performance compared to M6i. M7i-flex instances offer the most common sizes, from large to 8xlarge, and are a great first choice for applications that don’t fully utilize all compute resources such as web and application servers, virtual-desktops, batch-processing, and microservices.

M7i and C7i deliver up to 15% better price-performance compared to prior generation M6i and C6i instances. They offer larger instance sizes up to 48xlarge, can attach up to 128 EBS volumes and two bare metal sizes (metal-24xl, metal-48xl). These bare-metal sizes support built-in Intel accelerators: Data Streaming Accelerator, In-Memory Analytics Accelerator, and QuickAssist Technology that are used to facilitate efficient offload and acceleration of data operations and optimize performance for workloads.

In addition, all three instance types support the new Intel Advanced Matrix Extensions (AMX) that accelerate matrix multiplication operations for applications such as CPU-based ML.

We are excited to announce the launch of the Amazon Kinesis Data Streams Connector for Spark Structured Streaming on Amazon EMR. The new connector makes it easy for you to build real-time streaming applications and pipelines that consume Amazon Kinesis Data Streams using Apache Spark Structured Streaming. Starting Amazon EMR 7.1, the connector comes pre-packaged on Amazon EMR on EKS, EMR on EC2 and EMR Serverless. Now, you do not need to build or download any packages and can focus on building your business logic using the familiar and optimized Spark Data Source APIs when consuming data from your Kinesis data streams.

Amazon Kinesis Data Streams is a serverless streaming data service that makes it easy to capture, process, and store streaming data at massive scale. Amazon EMR is the cloud big data solution for petabyte-scale data processing, interactive analytics, and machine learning using Apache Spark and other open-source frameworks. The new Amazon Kinesis Data Streams Connector for Apache Spark is faster, more scalable, and fault-tolerant than alternative open-source options. The connector also supports Enhanced Fan-out consumption with dedicated read throughput. To learn more and see a code example, go to Build Spark Structured Streaming applications with the open source connector for Amazon Kinesis Data Streams .
 

The Mistral Small foundation model from Mistral AI is now generally available in Amazon Bedrock . You can now access four high-performing models from Mistral AI in Amazon Bedrock including Mistral Small, Mistral Large, Mistral 7B, and Mixtral 8x7B, further expanding model choice. Mistral Small is a highly efficient large language model optimized for high-volume, low-latency language-based tasks. It provides outstanding performance at a cost-effective price point. Key features of Mistral Small include retrieval-augmented generation (RAG) specialization, coding proficiency, and multilingual capabilities.

Mistral Small is perfectly suited for straightforward tasks that can be performed in bulk, such as classification, customer support, or text generation. The model specializes in RAG ensuring important information is retained even in long context windows, which can extend up to 32K tokens. Mistral Small excels in code generation, review, and commenting, supporting all major coding languages. Mistral Small also has multilingual capabilities delivering top-tier performance in English, French, German, Spanish, and Italian; it also supports dozens of other languages. The model also comes with built-in efficient guardrails for safety.

Mistral AI’s Mistral Small foundation model is now available in Amazon Bedrock in the US East (N. Virginia) AWS region. To learn more, read the AWS News launch blog , Mistral AI in Amazon Bedrock product page , and documentation . To get started with Mistral Small in Amazon Bedrock, visit the Amazon Bedrock console .
 

Amazon RDS for PostgreSQL 17 Beta 1 is now available in the Amazon RDS Database Preview Environment , allowing you to evaluate the pre-release of PostgreSQL 17 on Amazon RDS for PostgreSQL. You can deploy PostgreSQL 17 Beta 1 in the Amazon RDS Database Preview Environment that has the benefits of a fully managed database.

PostgreSQL 17 includes updates to vacuuming that reduces memory usage, improves time to finish vacuuming, and shows progress of vacuuming indexes. With PostgreSQL 17, you no longer need to drop logical replication slots when performing a major version upgrade. PostgreSQL 17 continues to build on the SQL/JSON standard, adding support for `JSON_TABLE` features that can convert JSON to a standard PostgreSQL table. The `MERGE`command now supports the `RETURNING` clause, letting you further work with modified rows. PostgreSQL 17 also includes general improvements to query performance and adds more flexibility to partition management with the ability to SPLIT/MERGE partitions. Please refer to the PostgreSQL community announcement for more details.

Amazon RDS Database Preview Environment database instances are retained for a maximum period of 60 days and are automatically deleted after the retention period. Amazon RDS database snapshots that are created in the preview environment can only be used to create or restore database instances within the preview environment. You can use the PostgreSQL dump and load functionality to import or export your databases from the preview environment.

Amazon RDS Database Preview Environment database instances are priced as per the pricing in the US East (Ohio) Region.