At his final results call Tim Cook turned in some pretty good numbers in a tough consumer electronics market. Apple had fiscal Q3 (calendar Q2) revenues up 16.4% y-o-y at […]

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Element14 has launched a home and healthcare design challenge inviting engineers, makers and technology enthusiasts to design and build a prototype smart home or healthcare system designed to support a […]

The post Element14 poses home and healthcare design challenge appeared first on Electronics Weekly .

Amazon reported Q2 sales up 20% y-o-y to $200.6bn. Operating  profit was up 43% y-o-y to $27.5bn. Net profit was $62.6bn up from $18.2bn in Q2 2025. AWS sales were […]

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The first company to get regulatory approval for a genuinely driverless robotaxi is Amazon’s Zoox (pictured). Zoox has been licensed to deploy 2,500 vehicles annually for two years The US […]

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Today, AWS announces the general availability of node lifecycle actions in AWS Parallel Computing Service (PCS). With node lifecycle actions, you can run custom scripts automatically at defined points in a compute node’s lifecycle. You can use them to prepare your nodes for work. For example, you can mount shared storage, join a directory service, install software, or set up monitoring.

You define node lifecycle actions in your PCS compute node group configuration when you create or update the group, and you can reuse the same script across multiple compute node groups and clusters. For each script, you set its location as an Amazon S3 or HTTPS URI, the arguments to pass, which lifecycle stage it runs in, whether it re-runs on reboot, and its error-handling behavior. AWS PCS writes the output to a dedicated log file, giving you visibility into what ran.

AWS PCS is a managed service that simplifies running and scaling high performance computing (HPC) workloads on AWS using Slurm. You can build complete, elastic environments that integrate compute, storage, networking, and visualization tools, and the service manages cluster updates and provides built-in observability.

Node lifecycle actions are available in all AWS Regions that support AWS PCS. To learn more, see the AWS PCS User Guide .

Duplicate patient records are one of the costliest problems in healthcare data management, scattering a patient’s information, leading to redundant tests, missed diagnoses, billing errors, manual reconciliation, and broken analytics that count one patient as many.

AWS HealthLake now supports resource matching, which automatically identifies and links duplicate records in a datastore. Healthcare organizations can build accurate longitudinal patient records and trustworthy population health datasets without specialized master data management tooling.
Resource matching works across seven Fast Healthcare Interoperability Resources (FHIR) resource types: Patient, Practitioner, Organization, Location, Device, RelatedPerson, and PractitionerRole. It matches high-confidence healthcare identifiers such as Social Security, medical record, and national provider numbers, applying each identifier’s real-world scope and filtering out placeholder values to avoid false matches.

Once enabled, every record that is created or updated is automatically evaluated and matches are connected through FHIR Linkage resources. Resource matching requires no configuration, matching rules, or third-party tools. Original records are never modified or deleted, preserving full provenance. Linkages are automatically re-evaluated as source records change and removed when records no longer match.

AWS HealthLake resource matching is available in gated preview in the US East (N. Virginia), US East (Ohio), US West (Oregon), Asia Pacific (Mumbai), Europe (London), Europe (Ireland), Asia Pacific SouthEast (Sydney), and Canada (Central) Regions. To turn it on for your datastore during the preview period, request to be added to the allowlist here .

To learn more, see Matching duplicate FHIR resources documentation in the AWS HealthLake developer guide.

You can now run OpenSearch version 3.7 on Amazon OpenSearch Service. OpenSearch 3.7 introduces improvements in vector search performance, search relevance, and Query Insights.

With this launch, 1-bit scalar quantization on the Faiss and Lucene engines compresses vectors, reducing the storage and memory required by vector workloads while maintaining search accuracy. You can now retrieve vectors faster using doc values instead of document source, with no reindexing required. Search Relevance Workbench adds new evaluation metrics, CSV judgment uploads, and expanded hybrid search optimization, helping you measure and improve search quality.

This launch also introduces new Query Insights capabilities, including automated query recommendations, a finished-queries cache for observing recently completed queries, and the option to export top query data to Amazon S3, helping you identify expensive queries and analyze trends over time.

For information on upgrading to OpenSearch 3.7, please see the documentation . OpenSearch 3.7 is now available in all AWS Regions where Amazon OpenSearch Service is available.

xAI’s Grok 4.3 model is now available on Amazon Bedrock in AWS GovCloud (US-West). With this launch, xAI joins Amazon Bedrock as a model provider in AWS GovCloud (US-West), giving you even more choice as you build generative AI applications across reasoning, agentic, and enterprise workflows.

Grok 4.3 is a reasoning-first model that offers configurable reasoning effort (none, low, medium, high). It also offers strong tool use and instruction-following capabilities for building reliable agents, and token efficiency to help keep high-volume inference cost-effective. Grok 4.3 is especially well suited to enterprise workloads such as customer support, web development, case law research, and financial document Q&A, while delivering consistent, high-quality results across conversational Al, search, chat, and multi-turn workflows. Grok 4.3 runs on Mantle, a new inference engine in Amazon Bedrock designed for price performance, with support for tool calling, structured output, and response streaming.

See region availability of Grok 4.3 for list of supported regions. To get started, visit the Grok 4.3 model detail page in our documentation.

AWS Directory Service now allows you to upgrade your AWS Managed Microsoft AD directory from Standard Edition to Enterprise Edition directly through the AWS Management Console, AWS CLI, and API without migrating to a new directory or re-joining your existing workloads.

Standard Edition is designed for organizations with up to 5,000 users and objects, while Enterprise Edition supports up to 500,000 objects and provides greater scalability for larger deployments. Customers who have outgrown Standard Edition limits can now upgrade in place, preserving existing trust relationships, application integrations, and group policies. The upgrade requires no changes to your DNS configuration or connected AWS workloads.

This new capability is available in all AWS Regions where AWS Directory Service is available. To get started, navigate to the AWS Directory Service console, select your Standard Edition directory, and choose Upgrade Edition from the directory actions menu. See the administrator guide for step-by-step instructions. For pricing details, go to the AWS Directory Service pricing page .

Amazon MSK Express brokers now delivers data to Amazon S3 general purpose buckets, providing a fully managed capability to deliver Apache Kafka data in Amazon S3 for downstream processing in the easiest and most reliable way. This capability automatically scales to deliver high-throughput Kafka data to S3 with end-to-end reliability for mission-critical workloads, while reducing ingestion and delivery costs by up to 60% compared to self-managed alternatives.

Customers deliver Apache Kafka data to Amazon S3 for use cases such as log archival, compliance retention, Kafka replay, and training AI/ML models, and typically build these pipelines with self-managed connectors that grow costly and operationally complex as workloads scale, forcing teams to build or source S3 connector plugins, secure approvals to deploy them, and continually scale capacity, and apply security updates across connector fleet. With this capability, MSK Express automatically handles scaling, retries, and backpressure so customers no longer manage connector fleets or coordinate across teams. MSK Express  supports throughput of up to 10 GB/s for data delivery to Amazon S3, and manages routine operations such as capacity scaling and version upgrades without introducing delivery gaps. Additionally, customers add this delivery capability without provisioning additional broker egress throughput, which eliminates the incremental infrastructure costs that scaling connector-based pipelines typically incurs, so customers scale delivery to actual workload demand rather than provisioning for peak, achieving reliable, high-throughput delivery to Amazon S3 while removing operational overhead and lowering costs.

Amazon MSK data delivery to Amazon S3 is available today in every AWS Region where Amazon MSK Express brokers are offered. For pricing information, visit the pricing page . To learn more, visit the Amazon MSK Developer Guide and Amazon MSK AI skills .