Wayve, the UK embedded autonomous driving company, has bought Quality Match, a German startup with expertise in data quality assurance for computer vision datasets and AI. The acquisition reflects Wayve’s …

The post Wayve buys Quality Match appeared first on Electronics Weekly .

Novocomms of Birmingham, UK, has £1.5m of Innovate UK funding to develop 28GHz in-antenna switches. “The components we are developing are based on addressable low-loss semiconductors which can be used …

The post £1.5m grant for Novocomms switchable antenna appeared first on Electronics Weekly .

Lodestar Space has received £30,000 funding through the UK Space Agency’s Space Ecosystem Commercialisation Programme (SECP). This is to accelerate development of its pioneering on-orbit sensing system. The award was …

The post SECP grant for Lodestar’s on-orbit sensing system appeared first on Electronics Weekly .

Today, AWS Marketplace announces the general availability of variable payments, a new billing option that allows professional services sellers to bill customers as work is delivered. This capability allows sellers to set contract caps and create payment requests throughout project delivery, rather than requiring upfront payment or fixed installment schedules.

Professional services engagements often involve complexity and uncertainty, making it challenging to accurately scope and price deliverables before work begins. Variable payments supports a flexible engagement approach, while providing transparency and control for buyers. AWS Marketplace Sellers can create private offers for professional services and utilize variable payments to bill up to a predetermined contract maximum. This allows sellers to bill in AWS Marketplace based on outcomes, as milestones are completed, or as time and materials are consumed. Throughout the engagement, sellers create payment requests that describe deliverables and specify milestones or time and materials. Customers receive email notifications and can review and approve each request manually, or enable auto-approval for streamlined processing.

To learn more, visit the variable payments documentation , or access the AWS Marketplace Management Portal to create a professional services private offer with variable payment.

AWS announces preview of AWS Interconnect – multicloud, providing simple, resilient, high-speed private connections to other cloud service providers (CSPs), starting in preview with Google Cloud as the first launch partner and then with Microsoft Azure later in 2026.

Customers have been adopting multicloud strategies while migrating more applications to the cloud. They do so for many reasons including interoperability requirements, the freedom to choose technology that best suits their needs, and the ability to build and deploy applications on any environment with greater ease and speed. Previously, when interconnecting workloads across multiple cloud providers, customers had to go the route of a ‘do-it-yourself’ multicloud approach, leading to complexities of managing global multi-layered networks at scale. AWS Interconnect – multicloud is the first purpose-built product of its kind and a new way of how clouds connect and talk to each other. It enables customers to quickly establish private, secure, high-speed network connections with dedicated bandwidth and built-in resiliency between their Amazon VPCs and other cloud environments. Interconnect – multicloud makes it easy to connect AWS networking services such as AWS Transit Gateway, AWS Cloud WAN, and Amazon VPC to other Cloud Service Providers (CSPs) quickly, instead of weeks or months.

Interconnect – multicloud is available in preview in five AWS Regions. You can enable this capability using the AWS Management Console. CSPs can also easily adopt via a published open API package on GitHub . For more information, see the AWS Interconnect – multicloud documentation pages .

Today, AWS announces the AWS AI League 2026 Championship, expanding its flagship AI tournament with new challenges and doubling the prize pool to $50,000 for builders to compete and innovate. AI League transforms how builders use AWS AI services through gamified competition centered on solving real world business challenges.

The program provides participants with a quick orientation, then focuses on tournaments with two challenge tracks: the Model Customization challenge using Amazon SageMaker AI to fine-tune foundation models for specific domains, and the Agentic AI challenge using Amazon Bedrock AgentCore to build intelligent agents that can reason, plan, and execute complex tasks. Enterprises can apply to host internal tournaments and receive AWS credits, creating environments where teams collaborate and compete while building AI solutions relevant to their specific business needs. Individual developers can participate at AWS Summits, testing their abilities against peers while working directly with AWS AI services.

For more information about the AWS AI League and how to participate, please visit the AWS AI League page .

AWS Identity and Access Management (IAM) announces IAM Policy Autopilot, an open source Model Context Protocol (MCP) server and command-line tool that helps your AI coding assistants quickly create baseline IAM policies that you can refine as your application evolves, so you can build faster. IAM Policy Autopilot analyzes your application code locally to create identity-based policies to control access for application roles, reducing the time you spend on writing IAM policies and troubleshooting access issues.

IAM Policy Autopilot integrates with AI coding assistants like Kiro, Claude Code, and Cursor, and supports Python, TypeScript, and Go applications. It stays up to date with the latest AWS services and features so that builders and coding assistants have access to the latest AWS IAM permissions knowledge.

IAM Policy Autopilot is available at no additional cost and can be used from your own machine. To start using IAM Policy Autopilot, visit the GitHub repository and follow the setup instructions for MCP server. You can also learn more about IAM Policy Autopilot by visiting AWS News Blog . 

Today, AWS announces the general availability of multimodal retrieval in Bedrock Knowledge Bases. Amazon Bedrock Knowledge Bases offers managed, end-to-end Retrieval Augmented Generation (RAG) workflows to create accurate, low latency, and custom Generative AI applications by incorporating contextual information from your company’s data sources. Supporting multimodal retrieval in Knowledge Bases enables developers to build AI-powered search and question-answering applications that work across text, images, audio, and video files. For example, a user could ask their assistant “show me Q1 projections for Amazon Bedrock” and Bedrock Knowledge Bases will retrieve relevant text from documents, graphs, video snippets, and audio related to revenue projections for Bedrock, allowing the assistant to generate richer and more complete answers for the end user. Previously, customers could only search through text documents and images. Now they can unlock insights from all their enterprise data formats through one unified, fully managed workflow.

Organizations struggle to extract insights from their growing multimedia data—videos, audio recordings, images, and documents— because building AI applications that can search across these different modalities is complex. As a result, valuable information trapped in terabytes of meeting recordings, training videos, and visual documentation remains inaccessible, preventing organizations from making data-driven decisions quickly and accurately. With multimodal retrieval for Knowledge Bases, developers can ingest multimodal content with full control of the parsing, chunking, embedding (e.g. Amazon Nova multimodal), and vector storage options. From there, they can then send a text query or an image as input and get relevant text, image, audio, and video segments back in order to generate a response in their generative AI applications using their choice of LLM.

For more information about creating multimodal Knowledge Bases in Bedrock, please refer to the documentation. Region availability is dependent on the features selected for multimodal support, please refer to the documentation for details.

Today, AWS announces the AWS MCP Server, a managed remote Model Context Protocol (MCP) server that helps AI agents and AI-native IDEs perform real-world, multi-step tasks across one or more AWS services. The AWS MCP Server consolidates capabilities from the existing AWS API MCP and AWS Knowledge servers into a unified interface, providing access to AWS documentation, generating and executing calls to over 15,000 AWS APIs including those for newly released services, and following pre-built workflows called Agent standard operating procedures (SOPs) that guide AI agents through common tasks on AWS.

With the AWS MCP Server, you can ask AI assistants to perform tasks like hosting static websites on S3, provisioning EC2 instances, troubleshooting Lambda issues, and configuring CloudWatch alarms using Agent SOPs to provide step-by-step guidance. The server handles authentication and authorization through AWS Identity and Access Management (IAM) and provides audit logging through AWS CloudTrail, giving you full control over resources and permissions while enabling AI agents to execute tasks across multiple AWS services helping you complete real-world tasks faster.

The AWS MCP Server is available at no additional cost in the US East (N. Virginia) Region. You pay only for AWS resources you create and applicable data transfer costs. To learn more, see the AWS MCP Server documentation .

AWS launches AWS Interconnect – last mile, a fully managed connectivity offering that allows customers to connect their branch offices, data centers, and remote locations to AWS with just a few clicks, eliminating the friction of discovering partners and the complexity of network setup. As a milestone collaboration between AWS and Lumen, AWS Interconnect – last mile combines AWS cloud innovation with Lumen’s extensive network footprint to redefine how businesses connect to the cloud.

Customers can now instantly establish private, high-speed connections to AWS by simply entering their location, selecting bandwidth, and choosing their AWS Region. The launch simplifies the connectivity experience by automating complex network configuration including BGP peering, VLAN configuration, and ASN assignment. Customers can dynamically scale bandwidth from 1 Gbps to 100 Gbps through the AWS console and benefit from zero down-time maintenance. The service is architected for high availability and backed by SLAs. MACsec encryption is enabled by default for enhanced security between AWS Direct Connect and partner devices.

AWS Interconnect – last mile is available as a gated preview through Lumen, our launch partner, for customers in US starting today. Request access here .