Tag: Internet

AWS Clean Rooms now supports two enhancements to its machine learning capabilities that help you train models more efficiently and at scale to generate predictive insights in a Clean Rooms collaboration. Incremental training enables you to build upon existing model artifacts to create new models, and distributed training allows you to train models across multiple compute instances simultaneously. These capabilities help data scientists and ML practitioners accelerate data collaboration and analysis while maintaining the privacy of the training datasets. With AWS Clean Rooms ML custom modeling, you and your partners can train and run inference on a custom ML model using collective datasets at scale without having to share sensitive intellectual property. With incremental training, you can leverage previously trained models to create new variants using expanded datasets, significantly reducing training time and compute resources. Additionally, distributed training lets you pr

Today, AWS re:Post Private announces the launch of channels, designed to enhance collaborative knowledge sharing within companies. Channels allow companies to create secure, dedicated private spaces within their re:Post Private environment, tailored to specific teams, projects, or topics. With channels, companies invite relevant users to collaboratively solve problems and build a team-specific knowledge base. Teams can collaborate on specific topics without exposing content to the entire community in their company. Companies can manage access to channels using Identity and Access Management (IAM) Identity Center groups with centralized access management. Channels on re:Post Private are ideal for scenarios where companies need to create dedicated, topic-specific spaces for various business functions, such as legal departments or confidential projects. This feature is also valuable for companies supporting multiple agencies or clients, allowing them to establish separate, sec

AWS HealthImaging announces support for storing DICOM P10 files to HealthImaging via the DICOMweb STOW-RS protocol. Now it’s easier than ever to import your medical imaging data to HealthImaging. This launch offers a synchronous data import action that is ideal for latency sensitive workflows, such as storing new medical imaging studies, annotations, and reports. With HealthImaging STOW-RS, you can import up to 1 GB of DICOM data per action. With this launch, AWS HealthImaging offers DICOMweb APIs for data import, search, and retrievals, which simplifies integrating HealthImaging with existing DICOMweb enabled applications. AWS HealthImaging is generally available in the following AWS Regions: US East (N. Virginia), US West (Oregon), Asia Pacific (Sydney), and Europe (Ireland). AWS HealthImaging is a HIPAA-eligible service that empowers healthcare providers, life sciences researchers, and their software partners to store, analyze, and share medical image

Amazon SageMaker Catalog, part of the next generation of Amazon SageMaker, now supports AI recommendations for descriptions—including table summaries, use cases, and column-level descriptions—for custom structured assets registered programmatically. This applies to a wide range of assets, for example, Iceberg tables in Amazon S3, or datasets from third-party and internal applications. Building on existing automated metadata capabilities for harvested assets from native services like AWS Glue and Amazon Redshift, this enhancement enables users to generate business-friendly descriptions for custom assets using large language models (LLMs) via Amazon Bedrock. With just a few clicks, users can trigger AI-generated suggestions, review and refine descriptions, and publish enriched asset metadata directly to the catalog. This helps reduce manual documentation effort, improves metadata consistency, and accelerates asset discoverability across organizations. Le

Today, AWS announces the opening of a new AWS Data Transfer Terminal location within Equinix MU1 in Munich, Germany. This marks AWS's first Data Transfer Terminal outside the United States and its debut in Europe. Data Transfer Terminal is a secure, physical location where you can bring your storage devices and upload data to AWS including Amazon Simple Storage Service (Amazon S3), Amazon Elastic File System (Amazon EFS), and others using a high throughput network connection. Data Transfer Terminals are ideal for customers who need to transfer large amounts of data to the AWS quickly and securely. Common use cases span various industries and applications, including training data for Advanced Driver Assistance Systems (ADAS) in the automotive industry, video production data for processing in the media and entertainment industry, migrating legacy data in the financial services industry, and uploading equipment sensor data in the industrial and agricultural sectors. Once uploa

Amazon Web Services (AWS) has introduced Amazon ECS Optimized Windows AMIs compatible with Windows Server 2025, offering two distinct platforms: 2025-Core and 2025-Full. These AMIs are specifically engineered to support Windows container deployments on Amazon ECS. Each AMI comes ready-to-use with essential components and optimizations tailored for running containerized workloads, streamlining the container deployment process. Windows Server 2025 provides enhanced performance optimization and improved resource utilization compared to previous versions, allowing for more efficient container operations. It features advanced security capabilities, including better isolation between containers to prevent container escape attacks and stronger kernel boundaries between containers and host. Windows Server 2025 also introduces enhanced networking capabilities like network namespace isolation and better integration with the Host Netwroking Service (HNS) that enable faster container c

Amazon Q in Connect, a generative AI-powered assistant for customer service, now supports 6 additional languages for offering proactive recommendations for customer service agents to resolve issues quickly and accurately. Amazon Q in Connect detects customer intent during voice and chat interactions in Spanish, French, Portuguese, Mandarin, Japanese, and Korean, in addition to English. Amazon Q in Connect can also support end-customer self-service interactions across Interactive Voice Response (IVR) and digital channels in 26 languages. For the full list of supported languages, please see the Languages supported by Amazon Connect features. For region availability, please see the availability of Amazon Connect features by Region. To lear

Amazon SageMaker Catalog, part of the next generation of Amazon SageMaker, now supports AI recommendations for descriptions—including table summaries, use cases, and column-level descriptions—for custom structured assets registered programmatically. This applies to a wide range of assets, for example, Iceberg tables in Amazon S3, or datasets from third-party and internal applications. Building on existing automated metadata capabilities for harvested assets from native services like AWS Glue and Amazon Redshift, this enhancement enables users to generate business-friendly descriptions for custom assets using large language models (LLMs) via Amazon Bedrock. With just a few clicks, users can trigger AI-generated suggestions, review and refine descriptions, and publish enriched asset metadata directly to the catalog. This helps reduce manual documentation effort, improves metadata consistency, and accelerates asset discoverability across organizations. Le

Amazon RDS Custom for Oracle now supports Multi-AZ deployments, providing high availability for business critical workloads. Amazon RDS Custom for Oracle is a managed service for running Oracle databases on AWS, with ability to customize the database environment and underlying operating system. With Multi-AZ deployments, RDS Custom for Oracle synchronously replicates data between two Availability Zones, and performs an automatic failover in case the primary database instance becomes unavailable so that customers benefit from higher availability. To set up an RDS Custom for Oracle database instance with Multi-AZ deployment, customers can specify their configuration when they create their database instance. RDS Custom automatically provisions primary and standby database instances in the different availability zones, and synchronously replicates data to the standby instance. If the primary database instance becomes unavailable, RDS Custom automatically fails over to the stand

Amazon Connect Contact Lens is now available in AWS GovCloud (US-West). Amazon Connect Contact Lens helps you to monitor, measure, and continuously improve contact quality and agent performance for a better overall customer experience. With Contact Lens conversational analytics, you can transcribe customer calls, analyze customer sentiment, discover top contact drivers, help redact sensitive data, and more, all natively within Amazon Connect. With Contact Lens performance evaluations, you can define custom evaluation criteria, evaluate up to 100% of agents’ contacts using insights from conversational analytics, and get aggregated insights to improve agent performance. With this launch, Contact Lens is available in all AWS regions where Amazon Connect operates. To learn more, please visit our