At Electronica 2024 we caught up with Sebastian Fernandez Alvarez, Sales Manager Mexico at WINSOURCE, as part of our promotional coverage for the event. He discusses WINSOURCE’s global procurement strategy …

The post Electronica: Video Interview – WINSOURCE on global sourcing supporting local production flexibility appeared first on Electronics Weekly .

Toshiba is aiming at 400V automotive systems with a 400V photo-relay that can handle 900V and ~30mA. Recommended maximum operating voltage is 720V. Called TLX9150M, it measures around 10 x …

The post 900V 100mA photo-relay for 400V automotive batteries appeared first on Electronics Weekly .

Watch the video below, providing an overview of the recent Siemens EDA Automotive Semiconductor Tech Day. It examines why semiconductor development is the most important factor for the automotive industry, …

The post Siemens Tech Day: Video Overview of Automotive Semiconductor Tech Day appeared first on Electronics Weekly .

Today, AWS announces the preview of Amazon Q Developer transformation capabilities for VMware, the first generative AI–powered assistant that can simplify and accelerate the migration and modernization of VMware workloads to Amazon Elastic Compute Cloud (EC2). These new capabilities help you streamline complex VMware transformation tasks, reducing the time and effort required to move VMware workloads to the cloud. Using advanced AI techniques to automate critical steps in the migration process, Amazon Q Developer helps accelerate your cloud journey, reduce costs, and drive innovation.

Amazon Q Developer transformation agents simplify and automate VMware transformation tasks including on-premises application data discovery, wave planning, network translation and deployment, and orchestration of the overall migration process. Two of the most challenging aspects of VMware transformations— wave planning and network translation— are now automated using VMware domain-expert agents and large language models (LLMs). These AI-powered tools convert VMware networking configurations and firewall rules into native AWS network constructs, significantly reducing complexity and potential errors. Importantly, Amazon Q Developer maintains a balance between automation and human oversight, proactively promoting user input at key decision points to ensure accuracy and control throughout the migration and modernization process.

The preview of Amazon Q Developer transformation capabilities for VMware is available in US East (N. Virginia) AWS region. To learn more about Amazon Q Developer and how it can accelerate your migration to AWS, visit Amazon Q Developer .

Independent software vendors (ISVs) like Asana, Miro, PagerDuty, Zoom, and more are integrating the Amazon Q index into their applications to enrich their generative AI experiences with enterprise knowledge and user context spanning multiple applications. End customers remain in control of which applications can access their data, and the index retains user-level permissions.

The Amazon Q index is a canonical source of content and data that unites data from across over 40 supported connectors. Amazon Q Business customers create an index based on their enterprise data so that generated responses, insights, and actions are most relevant to employees. Software providers register their application with Amazon Q Business, and then their customers permit them to access their indexed data. Once connected, the software vendor uses the additional data to enrich their native generative AI features to deliver more personalized responses back to the customer. This new feature inherits the same security, privacy, and guardrails as Amazon Q Business, accelerating an ISV’s generative AI roadmap so they can focus their efforts on innovative, differentiated features for their end users. 

ISVs can use the Amazon Q index in all AWS Regions where Amazon Q Business is available. 

Learn more about the Amazon Q index for software providers . 

Today, AWS announces the general availability of Amazon Elastic Compute Cloud (Amazon EC2) P5en instances, powered by the latest NVIDIA H200 Tensor Core GPUs. These instances deliver the highest performance in Amazon EC2 for deep learning and high performance computing (HPC) applications.

You can use Amazon EC2 P5en instances for training and deploying increasingly complex large language models (LLMs) and diffusion models powering the most demanding generative AI applications. You can also use P5en instances to deploy demanding HPC applications at scale in pharmaceutical discovery, seismic analysis, weather forecasting, and financial modeling.

P5en instances feature up to 8 H200 GPUs which have 1.7x GPU memory size and 1.5x GPU memory bandwidth than H100 GPUs featured in P5 instances. P5en instances pair the H200 GPUs with high performance custom 4^th Generation Intel Xeon Scalable processors, enabling Gen5 PCIe between CPU and GPU which provides up to 4x the bandwidth between CPU and GPU and boosts AI training and inference performance. P5en, with up to 3200 Gbps of third generation of EFA using Nitro v5, shows up to 35% improvement in latency compared to P5 that uses the previous generation of EFA and Nitro. This helps improve collective communications performance for distributed training workloads such as deep learning, generative AI, real-time data processing, and high-performance computing (HPC) applications. To address customer needs for large scale at low latency, P5en instances are deployed in Amazon EC2 UltraClusters, and provide market-leading scale-out capabilities for distributed training and tightly coupled HPC workloads.

P5en instances are now available in the US East (Ohio), US West (Oregon), and Asia Pacific (Tokyo) AWS Regions and US East (Atlanta) Local Zone us-east-1-atl-2a in the p5en.48xlarge size.

To learn more about P5en instances, see Amazon EC2 P5en Instances .

With the launch of VPC Resources for Amazon VPC Lattice, you can now access all of your application dependencies through a VPC Lattice service network. You’re able to connect to your application dependencies hosted in different VPCs, accounts, and on-premises using additional protocols, including TLS, HTTP, HTTPS, and now TCP. This new feature expands upon the existing HTTP-based services support, enabling you to share a wider range of resources across your organization.

With VPC Resource support, you can add your TCP resources, such as Amazon RDS databases, custom DNS, or IP endpoints, to a VPC Lattice service network. Now, you can share and connect to all your application dependencies, such as HTTP APIs and TCP databases, across thousands of VPCs, simplifying network management and providing centralized visibility with built-in access controls.

VPC Resources are generally available with VPC Lattice in Africa (Cape Town), Asia Pacific (Mumbai), Asia Pacific (Singapore), Asia Pacific (Sydney), Europe (Frankfurt), Europe (Ireland), Europe (Paris), Europe (Stockholm), Middle East (Bahrain), South America (Sao Paulo), US East (N. Virginia), US East (Ohio), US West (Oregon).

To get started, read the VPC Resources launch blog , architecture blog , and VPC Lattice User Guide . Learn more about VPC Lattice, visit Amazon VPC Lattice Getting Started .
 

Latency-optimized inference for foundation models in Amazon Bedrock now available in public preview, delivering faster response times and improved responsiveness for AI applications. Currently, these new inference options support Anthropic’s Claude 3.5 Haiku model and Meta’s Llama 3.1 405B and 70B models offering reduced latency compared to standard models without compromising accuracy. As verified by Anthropic, with latency-optimized inference in Amazon Bedrock, Claude 3.5 Haiku runs faster on AWS than anywhere else. Additionally, with latency-optimized inference in Bedrock, Llama 3.1  405B and 70B runs faster on AWS than any other major cloud provider.

As more customers move their generative AI applications to production, optimizing the end-user experience becomes crucial, particularly for latency-sensitive applications such as real-time customer service chatbots and interactive coding assistants. Using purpose-built AI chips like AWS Trainium2 and advanced software optimizations in Amazon Bedrock, customers can access more options to optimize their inference for a particular use case. Accessing these capabilities requires no additional setup or model fine-tuning, allowing for immediate enhancement of existing applications with faster response times.

Latency-optimized inference is available for Anthropic’s Claude 3.5 Haiku and Meta’s Llama 3.1 405B and 70B in the US East (Ohio) Region via cross-region inference . To get started, visit the Amazon Bedrock console . For more information about Amazon Bedrock and its capabilities, visit the Amazon Bedrock product page , pricing page , and documentation .

GROW with SAP on AWS is now available for subscription from AWS Marketplace. As a complete offering of solutions, best practices, adoption acceleration services, community and learning, GROW with SAP helps any size organization adopt cloud enterprise resource planning (ERP) with speed, predictability, and continuous innovation. GROW with SAP on AWS can be implemented in months instead of years with traditional on-premises ERP implementations.

By implementing GROW with SAP on AWS, you can simplify everyday work, grow your business, and secure your success. At the core of GROW with SAP is SAP S/4HANA Cloud, a full-featured SaaS ERP suite built on the learnings of SAP’s 50+ years of industry best practices. GROW with SAP allows your organization to gain end- to- end process visibility and control with integrated systems across HR, procurement, sales, finance, supply chain, and manufacturing. It also includes SAP Business AI-powered processes leveraging AWS to provide data-driven insights and recommendations. Customers can also innovate with generative AI using their SAP data through Amazon Bedrock models in the SAP generative AI hub. GROW with SAP on AWS takes advantage of AWS Graviton processors, which offer up to 60% less energy than comparable cloud instances for the same performance.

GROW with SAP on AWS is initially available in the US-East Region.

To subscribe to GROW with SAP on AWS, visit the AWS Marketplace listing . Or, to learn more, visit the GROW with SAP on AWS detail page .

Starting today, Amazon Q Developer can also perform code reviews, automatically providing comments on your code in the IDE, flagging suspicious code patterns, providing patches where available, and even assessing deployment risk so you can get feedback on your code quickly.

Q Developer is a generative AI-powered assistant for designing, building, testing, deploying, and maintaining software. Its agents for software development have a deep understanding of your entire code repos, so they can accelerate many tasks beyond coding. By automating the first round of code reviews and improving review consistency, Q Developer empowers code authors to fix issues faster, streamlining the process for both authors and reviewers. With this new capability, Q Developer can help you get immediate feedback for your code reviews and code fixes where available, so you can increase the speed of iteration and improve the quality of your code.

This capability is available in the integrated development environment (IDE) through a new chat command: /review. You can start automating code reviews via the Visual Studio Code and IntelliJ IDEA Integrated Development Environments (IDEs) with both an Amazon Q Developer Free Tier or Pro Tier subscription. For more details on pricing, see Amazon Q Developer pricing . 

This capability is available in all AWS Regions where Amazon Q Developer is available . To get started with generating documentation, visit Amazon Q Developer or read the news blog .