Starting today, Amazon EC2 Capacity Manager supports tag-based dimensions, enabling you to use tags from your EC2 resources to group and filter capacity metrics. EC2 Capacity Manager helps you monitor and optimize capacity usage across On-Demand Instances, Spot Instances, and Capacity Reservations. This launch also introduces Account Name as a new built-in dimension.
You can activate up to five custom tag keys — such as environment, team, or cost-center — and use them alongside built-in dimensions like Region, Instance Type, and Availability Zone to group and filter capacity metrics by tag values in the console and APIs, and include tag data as additional columns in newly created S3 data exports. Capacity Manager also includes four Capacity Manager-provided tags by default: EC2 Auto Scaling group name, EKS cluster name, EKS Kubernetes node pool, and Karpenter node pool. The new Account Name dimension makes it easier to identify accounts when analyzing cross-account capacity data across your organization.
This feature is available in all AWS Regions where EC2 Capacity Manager is available. To get started, navigate to the Settings tab in Capacity Manager and choose Manage tag keys, or use the AWS CLI. To learn more, see Managing monitored tag keys in the Amazon EC2 User Guide. For more information about Amazon EC2 Capacity Manager, visit the EC2 Capacity Manager documentation.
Starting today, Amazon EC2 Capacity Manager supports tag-based dimensions, enabling you to use tags from your EC2 resources to group and filter capacity metrics. EC2 Capacity Manager helps you monitor and optimize capacity usage across On-Demand Instances, Spot Instances, and Capacity Reservations. This launch also introduces Account Name as a new built-in dimension.
You can activate up to five custom tag keys — such as environment, team, or cost-center — and use them alongside built-in dimensions like Region, Instance Type, and Availability Zone to group and filter capacity metrics by tag values in the console and APIs, and include tag data as additional columns in newly created S3 data exports. Capacity Manager also includes four Capacity Manager-provided tags by default: EC2 Auto Scaling group name, EKS cluster name, EKS Kubernetes node pool, and Karpenter node pool. The new Account Name dimension makes it easier to identify accounts when analyzing cross-account capacity data across your organization.
This feature is available in all AWS Regions where EC2 Capacity Manager is available. To get started, navigate to the Settings tab in Capacity Manager and choose Manage tag keys, or use the AWS CLI. To learn more, see Managing monitored tag keys in the Amazon EC2 User Guide. For more information about Amazon EC2 Capacity Manager, visit the EC2 Capacity Manager documentation.
Amazon Interactive Video Service (Amazon IVS) Real-Time Streaming now supports redundant ingest, helping protect your live streams against source encoder failures and first-mile network issues. With redundant ingest, you can stream from two encoders simultaneously to a single stage with automated failover, ensuring uninterrupted delivery to your viewers.
Redundant ingest is ideal for live events, 24/7 live streams, or any scenario where uninterrupted delivery is essential. This capability helps you maintain viewer engagement during unexpected disruptions and enables continuous 24/7 streaming.
Amazon IVS is a managed live streaming solution designed to make low-latency or real-time video available to viewers around the world. Visit the AWS region table for a full list of AWS Regions where the Amazon IVS console and APIs for control and creation of video streams are available.
Amazon Interactive Video Service (Amazon IVS) Real-Time Streaming now supports redundant ingest, helping protect your live streams against source encoder failures and first-mile network issues. With redundant ingest, you can stream from two encoders simultaneously to a single stage with automated failover, ensuring uninterrupted delivery to your viewers.
Redundant ingest is ideal for live events, 24/7 live streams, or any scenario where uninterrupted delivery is essential. This capability helps you maintain viewer engagement during unexpected disruptions and enables continuous 24/7 streaming.
Amazon IVS is a managed live streaming solution designed to make low-latency or real-time video available to viewers around the world. Visit the AWS region table for a full list of AWS Regions where the Amazon IVS console and APIs for control and creation of video streams are available.
To learn more, please visit the Amazon IVS Real-Time Streaming RTMP ingest documentation page.
Amazon WorkSpaces Advisor is a new AI-powered tool that helps administrators quickly troubleshoot and resolve issues with Amazon WorkSpaces Personal. Using generative AI capabilities, it analyzes WorkSpace configurations, identifies problems, and provides actionable recommendations to restore service and optimize performance.
WorkSpaces Advisor streamlines administrative workflows by reducing the time needed to investigate and fix common issues. Administrators can leverage AI-driven insights to proactively maintain their virtual desktop infrastructure, improve end-user experience, and minimize downtime across their WorkSpaces.
Amazon WorkSpaces Advisor is now available in all AWS commercial regions where Amazon WorkSpaces is offered. Visit the Amazon WorkSpaces console to access WorkSpaces Advisor and begin troubleshooting your environment. Learn more in the feature blog and user guide.
Amazon WorkSpaces Advisor is a new AI-powered tool that helps administrators quickly troubleshoot and resolve issues with Amazon WorkSpaces Personal. Using generative AI capabilities, it analyzes WorkSpace configurations, identifies problems, and provides actionable recommendations to restore service and optimize performance.
WorkSpaces Advisor streamlines administrative workflows by reducing the time needed to investigate and fix common issues. Administrators can leverage AI-driven insights to proactively maintain their virtual desktop infrastructure, improve end-user experience, and minimize downtime across their WorkSpaces.
Amazon WorkSpaces Advisor is now available in all AWS commercial regions where Amazon WorkSpaces is offered. Visit the Amazon WorkSpaces console to access WorkSpaces Advisor and begin troubleshooting your environment. Learn more in the feature blog and user guide.
Amazon SageMaker HyperPod task governance now supports gang scheduling, which ensures all pods required for a distributed training job are ready before training begins. Administrators can configure gang scheduling to prevent wasted compute from partial job runs and avoid deadlocks from jobs waiting for resources.
Data scientists running distributed AI/ML training jobs on Amazon SageMaker HyperPod clusters using the EKS orchestrator require multiple pods to work together across nodes with pod-to-pod communication. When some pods start but others do not, jobs can hold onto resources without making progress, block other workloads, and increase costs. Gang scheduling resolves this by monitoring all pods in a workload and pulling the workload back if not all pods are ready within a set time. Pulled-back workloads are automatically requeued to prevent stalling. Administrators can adjust settings on the HyperPod Console, such as how long to wait for pods to be ready, how to handle node failures, whether to admit workloads one at a time to avoid deadlocks on busy clusters, and how retries are scheduled.
This capability is currently available for Amazon SageMaker HyperPod clusters using the EKS orchestrator across the following AWS Regions: US East (N. Virginia), US East (Ohio), US West (N. California), US West (Oregon), Asia Pacific (Mumbai), Asia Pacific (Singapore), Asia Pacific (Sydney), and Asia Pacific (Tokyo), Asia Pacific (Jakarta), Europe (Frankfurt), Europe (Ireland), Europe (London), Europe (Stockholm), Europe (Spain), and South America (São Paulo).
Amazon SageMaker HyperPod task governance now supports gang scheduling, which ensures all pods required for a distributed training job are ready before training begins. Administrators can configure gang scheduling to prevent wasted compute from partial job runs and avoid deadlocks from jobs waiting for resources. Data scientists running distributed AI/ML training jobs on Amazon SageMaker HyperPod clusters using the EKS orchestrator require multiple pods to work together across nodes with pod-to-pod communication. When some pods start but others do not, jobs can hold onto resources without making progress, block other workloads, and increase costs. Gang scheduling resolves this by monitoring all pods in a workload and pulling the workload back if not all pods are ready within a set time. Pulled-back workloads are automatically requeued to prevent stalling. Administrators can adjust settings on the HyperPod Console, such as how long to wait for pods to be ready, how to handle node failures, whether to admit workloads one at a time to avoid deadlocks on busy clusters, and how retries are scheduled. This capability is currently available for Amazon SageMaker HyperPod clusters using the EKS orchestrator across the following AWS Regions: US East (N. Virginia), US East (Ohio), US West (N. California), US West (Oregon), Asia Pacific (Mumbai), Asia Pacific (Singapore), Asia Pacific (Sydney), and Asia Pacific (Tokyo), Asia Pacific (Jakarta), Europe (Frankfurt), Europe (Ireland), Europe (London), Europe (Stockholm), Europe (Spain), and South America (São Paulo). To learn more, visit SageMaker HyperPod webpage, and HyperPod task governance documentation.
Amazon Elastic Kubernetes Service (Amazon EKS) managed node groups now support Auto Scaling warm pools, enabling you to maintain pre-initialized EC2 instances ready for rapid scale-out. This reduces node provisioning latency for applications with burst traffic patterns, time-sensitive workloads, or long instance boot times due to complex initialization scripts and software dependencies.
With warm pools enabled, your EKS managed node group maintains a pool of instances that have already completed OS initialization, user data execution, and software configuration. When demand increases and the Auto Scaling group scales out, instances transition from the warm pool to active service without repeating the full cold-start sequence. You can configure instances in the warm pool as Stopped (lower cost, longer transition) or Running (higher cost, faster transition). You can also enable reuse on scale-in, which returns instances to the warm pool during scale-down instead of terminating them. Warm pools work with Cluster Autoscaler without requiring any additional configuration.
You can enable warm pools through the EKS API, AWS CLI, AWS Management Console, or AWS CloudFormation by adding a warmPoolConfig to your CreateNodegroup or UpdateNodegroupConfig requests. Existing managed node groups that do not enable warm pools are unaffected.
This feature is available in all AWS Regions where Amazon EKS is available, except for the China (Beijing) Region, operated by Sinnet and the China (Ningxia) Region, operated by NWCD. To get started, see the Amazon EKS managed node groups documentation.
Amazon Elastic Kubernetes Service (Amazon EKS) managed node groups now support Auto Scaling warm pools, enabling you to maintain pre-initialized EC2 instances ready for rapid scale-out. This reduces node provisioning latency for applications with burst traffic patterns, time-sensitive workloads, or long instance boot times due to complex initialization scripts and software dependencies. With warm pools enabled, your EKS managed node group maintains a pool of instances that have already completed OS initialization, user data execution, and software configuration. When demand increases and the Auto Scaling group scales out, instances transition from the warm pool to active service without repeating the full cold-start sequence. You can configure instances in the warm pool as Stopped (lower cost, longer transition) or Running (higher cost, faster transition). You can also enable reuse on scale-in, which returns instances to the warm pool during scale-down instead of terminating them. Warm pools work with Cluster Autoscaler without requiring any additional configuration. You can enable warm pools through the EKS API, AWS CLI, AWS Management Console, or AWS CloudFormation by adding a warmPoolConfig to your CreateNodegroup or UpdateNodegroupConfig requests. Existing managed node groups that do not enable warm pools are unaffected. This feature is available in all AWS Regions where Amazon EKS is available, except for the China (Beijing) Region, operated by Sinnet and the China (Ningxia) Region, operated by NWCD. To get started, see the Amazon EKS managed node groups documentation.
Amazon Bedrock AgentCore Browser now supports OS-level interaction capabilities, enabling automation of browser workflows that require direct operating system control beyond Chrome DevTools Protocol (CDP) capabilities. This enhancement addresses automation scenarios where CDP alone is insufficient, such as mouse operations, print dialogs, native system alerts, and keyboard shortcuts. The feature serves AI agent developers, test automation engineers, and organizations building LLM-powered web interaction tools.
The new capabilities provide automation through mouse operations (click, move, drag, scroll), keyboard operations (type, press, shortcuts like ctrl+a and ctrl+p), and full desktop screenshots, all at OS-level coordinates extending beyond the browser viewport. Key use cases include automated testing with system dialog handling, document management workflows, complex UI interactions with right-click menus, and vision-based AI agents that require complete browser environment visibility.
This feature is available by default on all browser instances in all 14 AWS Regions where Amazon Bedrock AgentCore Browser is available: US East (N. Virginia), US East (Ohio), US West (Oregon), Europe (Frankfurt), Europe (Ireland), Europe (London), Europe (Paris), Europe (Stockholm), Asia Pacific (Mumbai), Asia Pacific (Singapore), Asia Pacific (Sydney), Asia Pacific (Tokyo), Asia Pacific (Seoul), and Canada (Central).
Amazon Bedrock AgentCore Browser now supports OS-level interaction capabilities, enabling automation of browser workflows that require direct operating system control beyond Chrome DevTools Protocol (CDP) capabilities. This enhancement addresses automation scenarios where CDP alone is insufficient, such as mouse operations, print dialogs, native system alerts, and keyboard shortcuts. The feature serves AI agent developers, test automation engineers, and organizations building LLM-powered web interaction tools. The new capabilities provide automation through mouse operations (click, move, drag, scroll), keyboard operations (type, press, shortcuts like ctrl+a and ctrl+p), and full desktop screenshots, all at OS-level coordinates extending beyond the browser viewport. Key use cases include automated testing with system dialog handling, document management workflows, complex UI interactions with right-click menus, and vision-based AI agents that require complete browser environment visibility. This feature is available by default on all browser instances in all 14 AWS Regions where Amazon Bedrock AgentCore Browser is available: US East (N. Virginia), US East (Ohio), US West (Oregon), Europe (Frankfurt), Europe (Ireland), Europe (London), Europe (Paris), Europe (Stockholm), Asia Pacific (Mumbai), Asia Pacific (Singapore), Asia Pacific (Sydney), Asia Pacific (Tokyo), Asia Pacific (Seoul), and Canada (Central). To learn more, visit the AgentCore Browser documentation.
Amazon OpenSearch Service now supports i8ge instances, which is the latest generation of storage optimized instances offering the best performance for storage-intensive workloads.
Powered by AWS Graviton4 processors, I8ge instances deliver up to 60% better compute performance compared to previous generation Graviton2-based storage optimized Im4gn instances. I8ge instances use the latest third generation AWS Nitro SSDs, local NVMe storage that deliver up to 55% better real-time storage performance per TB while offering up to 60% lower storage I/O latency and up to 75% lower storage I/O latency variability compared to previous generation Im4gn instances. Built on the AWS Nitro System, these instances offload CPU virtualization, storage, and networking functions to dedicated hardware and software enhancing the performance and security for your workloads.
I8ge instances are available of sizes up to 18xlarge and 45 TB instance storage. At 112.5 Gbps, these instances have the highest networking bandwidth among storage optimized instances available in Amazon OpenSearch Service.
I8ge instances support all OpenSearch versions & Elasticsearch (open source) versions 7.9 and 7.10.
Amazon OpenSearch Service supports i8ge instances in following AWS Regions : US East (N. Virginia), US East (Ohio), US West (Oregon), Europe (Frankfurt), Europe (Ireland), Europe (Stockholm), Asia Pacific (Malaysia), Asia Pacific (Mumbai), Asia Pacific (Singapore) and Asia Pacific (Sydney).
For region specific availability & pricing, visit our pricing page. To learn more about Amazon OpenSearch Service and its capabilities, visit our product page.
Amazon OpenSearch Service now supports i8ge instances, which is the latest generation of storage optimized instances offering the best performance for storage-intensive workloads. Powered by AWS Graviton4 processors, I8ge instances deliver up to 60% better compute performance compared to previous generation Graviton2-based storage optimized Im4gn instances. I8ge instances use the latest third generation AWS Nitro SSDs, local NVMe storage that deliver up to 55% better real-time storage performance per TB while offering up to 60% lower storage I/O latency and up to 75% lower storage I/O latency variability compared to previous generation Im4gn instances. Built on the AWS Nitro System, these instances offload CPU virtualization, storage, and networking functions to dedicated hardware and software enhancing the performance and security for your workloads. I8ge instances are available of sizes up to 18xlarge and 45 TB instance storage. At 112.5 Gbps, these instances have the highest networking bandwidth among storage optimized instances available in Amazon OpenSearch Service. I8ge instances support all OpenSearch versions & Elasticsearch (open source) versions 7.9 and 7.10. Amazon OpenSearch Service supports i8ge instances in following AWS Regions : US East (N. Virginia), US East (Ohio), US West (Oregon), Europe (Frankfurt), Europe (Ireland), Europe (Stockholm), Asia Pacific (Malaysia), Asia Pacific (Mumbai), Asia Pacific (Singapore) and Asia Pacific (Sydney). For region specific availability & pricing, visit our pricing page. To learn more about Amazon OpenSearch Service and its capabilities, visit our product page.
Oracle Database@AWS is now generally available in five additional AWS Regions: EU-West-1 (Dublin), EU-West-2 (London), AP-South-1 (Mumbai), AP-South-2 (Hyderabad), and AP-Northeast-2 (Seoul). Oracle Database@AWS enables customers to access Oracle Cloud Infrastructure (OCI) managed Oracle Exadata systems within AWS data centers. With this launch, customers in Europe and Asia Pacific with in-region data residency requirements can migrate on-premises Oracle Exadata and Oracle Real Application Clusters (RAC) applications to AWS. Dublin, Mumbai, and Hyderabad are available with two Availability Zones (AZs), while London and Seoul are available with one Availability Zone. Additionally, CA-Central-1 (Canada Central) and AP-Southeast-2 (Sydney) now support two Availability Zones, providing enhanced high availability for production workloads.
With this expansion, Oracle Database@AWS services are now available in twelve Regions: US-East-1 (N. Virginia), US-West-2 (Oregon), US-East-2 (Ohio), CA-Central-1 (Canada Central), EU-Central-1 (Frankfurt), EU-West-1 (Dublin), EU-West-2 (London), AP-Northeast-1 (Tokyo), AP-Southeast-2 (Sydney), AP-South-1 (Mumbai), AP-South-2 (Hyderabad), and AP-Northeast-2 (Seoul). To use Oracle Database@AWS services, request a private offer from Oracle through the AWS Marketplace, and use AWS Management Console to setup and use your databases.
Oracle Database@AWS is now generally available in five additional AWS Regions: EU-West-1 (Dublin), EU-West-2 (London), AP-South-1 (Mumbai), AP-South-2 (Hyderabad), and AP-Northeast-2 (Seoul). Oracle Database@AWS enables customers to access Oracle Cloud Infrastructure (OCI) managed Oracle Exadata systems within AWS data centers. With this launch, customers in Europe and Asia Pacific with in-region data residency requirements can migrate on-premises Oracle Exadata and Oracle Real Application Clusters (RAC) applications to AWS. Dublin, Mumbai, and Hyderabad are available with two Availability Zones (AZs), while London and Seoul are available with one Availability Zone. Additionally, CA-Central-1 (Canada Central) and AP-Southeast-2 (Sydney) now support two Availability Zones, providing enhanced high availability for production workloads. With this expansion, Oracle Database@AWS services are now available in twelve Regions: US-East-1 (N. Virginia), US-West-2 (Oregon), US-East-2 (Ohio), CA-Central-1 (Canada Central), EU-Central-1 (Frankfurt), EU-West-1 (Dublin), EU-West-2 (London), AP-Northeast-1 (Tokyo), AP-Southeast-2 (Sydney), AP-South-1 (Mumbai), AP-South-2 (Hyderabad), and AP-Northeast-2 (Seoul). To use Oracle Database@AWS services, request a private offer from Oracle through the AWS Marketplace, and use AWS Management Console to setup and use your databases. To learn more, visit Oracle Database@AWS overview and documentation.
Microsoft y Publicis Groupe amplían su colaboración para impulsar el futuro del marketing agéntico
Juntas, las empresas construyen una solución de marketing impulsada por IA que desbloqueará la creatividad, acelerará la innovación y empoderará a los clientes para liderar el futuro del marketing
REDMOND, Washington y PARÍS —Diez años después de co-crear Marcel, una innovadora plataforma de IA, Microsoft y Publicis Groupe anuncian la ampliación de su alianza estratégica para construir una solución de marketing full-stack que unifica sistemas heredados, agentes de IA y datos basados en identidad para acelerar los resultados de marketing en la era de la IA agéntica.
En un momento en que las empresas avanzan más rápido que nunca para adaptarse, ya que el comportamiento de los clientes cambia y cada vez más necesitan conectar sus inversiones de manera directa con los ingresos y los resultados, la IA cambia de manera fundamental la ecuación. A través de la colaboración, Microsoft y Publicis aprovecharán la experiencia mutua para integrar la IA agéntica en todo el flujo de trabajo, de modo que los responsables de marketing puedan centrarse en lo que mejor saben hacer: estrategia, creatividad y la búsqueda de ideas originales.
«Hace diez años, con Microsoft, co-creamos Marcel, la primera plataforma de IA del marketing», dijo Arthur Sadoun, CEO de Publicis Groupe. «Ahora volvemos a colaborar para moldear la industria, esta vez mientras nuestros clientes se enfrentan a la dinámica de la era agéntica. Juntos, combinamos la tecnología inigualable y las capacidades de IA de Microsoft con la experiencia en transformación de Publicis Sapient, además de los datos de identidad líderes en la industria de Epsilon, para ofrecer soluciones agénticas que en verdad cambian las reglas del juego para los clientes. Ambas empresas creen que el futuro de la IA requiere agentes al servicio de las personas y la humanidad, y con esta colaboración creamos una oportunidad única para que nuestros clientes lideren contra esta ambición.»
En un mercado saturado de soluciones puntuales de IA fragmentadas, la mayoría de las empresas necesitan, pero rara vez logran, una transformación conectada. Para atender las necesidades actuales de los profesionales del marketing, las empresas ofrecerán:
Bases modernas en la nube para la IA: El framework Slingshot de Publicis Sapient aprovechará la nube de Microsoft, para permitir a las organizaciones migrar sistemas heredados a Microsoft Azure para crear bases modernas y nativas de la nube para la adopción de la IA.
Despliegue de agentes de IA: Las soluciones de IA sapiente integrarán Microsoft Copilot Studio, Microsoft Agent 365 y Microsoft IQ, para permitir a los clientes integrar la IA directo en los procesos empresariales principales. La plataforma Bodhi de Sapient permitirá entonces a las organizaciones desplegar y escalar agentes de IA seguros y de nivel empresarial en operaciones, comercio, marketing y compromiso con el cliente, al conectar datos, flujos de trabajo y toma de decisiones para generar un impacto tangible en el negocio.
Modelo de datos basado en identidad: A diferencia de la IA basada en datos públicos o modelos aislados, esta colaboración está anclada en Epsilon, la capa de inteligencia intelectual de Publicis. Epsilon conecta a clientes y prospectos para generar resultados medibles a través de fusionar identidad, medios, marketing e inteligencia del cliente. Los agentes de IA construidos sobre Microsoft Fabric e impulsados por Epsilon podrán razonar, decidir y actuar sobre datos confiables, reales y propietarios, para lograr un impacto que vaya más allá del rendimiento del modelo hacia un valor empresarial sostenido. Por ejemplo, un agente de IA puede identificar de forma autónoma segmentos de clientes de alto valor, generar y personalizar contenido, desplegar campañas en diferentes canales y optimizar de manera continua el gasto en tiempo real — dentro de los límites establecidos por los líderes de marketing.
«Esta colaboración refleja nuestra convicción de que la IA debe hacer más para servir a la humanidad a través de fomentar la creatividad y la innovación», dijo Judson Althoff, CEO del negocio comercial de Microsoft. «Al unir las capacidades de nube e IA de Microsoft con las soluciones Publicis Groupe basadas en Azure, damos a los creativos y creadores la libertad de dedicar menos tiempo a la ejecución repetitiva y más tiempo a dar forma a ideas, construir marcas y fomentar un crecimiento significativo para nuestros clientes.»
Como parte de esta colaboración, Publicis pone Microsoft 365 Copilot en manos de los más de 114.000 empleados de todo el mundo. También han seleccionado a Microsoft Azure como proveedor de nube preferido. Al trabajar con Microsoft, que ofrece la plataforma de nube e IA más escalable y segura del sector, Publicis fortalece su capacidad para ofrecer personalización a gran escala y ampliar el papel de Marcel, para pasar de ser pionero en IA en marketing a impulsar la próxima generación de IA a nivel empresarial.
Además, Publicis se convertirá en la agencia de medios global de referencia de Microsoft. A través de una coinnovación enfocada, construida con Microsoft Azure, las empresas conectarán mejor audiencias, señales y datos de rendimiento para maximizar los resultados empresariales.
Acerca de Publicis Groupe – El poder de uno
Publicis Groupe [Euronext Paris FR0000130577, CAC 40] es un líder mundial en comunicación. El Groupe está posicionado en cada etapa de la cadena de valor, desde la consultoría hasta la ejecución, que combina la transformación del marketing y la transformación digital del negocio. Publicis Groupe es un socio privilegiado en la transformación de sus clientes para mejorar la personalización a gran escala. El Groupe se apoya en diez especializaciones concentradas en cuatro actividades principales: Comunicación, Medios, Datos y Tecnología. A través de una organización unificada y fluida, sus clientes tienen acceso facilitado a toda su experiencia en cada mercado. Presente en más de 100 países, Publicis Groupe emplea a unos 103.000 profesionales.
Acerca de Microsoft
Microsoft (Nasdaq «MSFT» @microsoft) crea plataformas y herramientas impulsadas por IA para ofrecer soluciones innovadoras que respondan a las necesidades cambiantes de nuestros clientes. La empresa tecnológica está comprometida a hacer que la IA esté disponible de forma amplia y responsable, con la misión de empoderar a cada persona y organización del planeta para lograr más.
Para más información, solo prensa: Microsoft Media Relations, We. Communications para Microsoft, (425) 638-7777, rapidresponse@wecommunications.com
Nota para los editores: Para más información, noticias y perspectivas de Microsoft, por favor visite Microsoft Source LATAM en https://news.microsoft.com/source/latam. Los enlaces web, números de teléfono y títulos eran correctos en el momento de la publicación, pero pueden haber cambiado. Para asistencia adicional, periodistas y analistas pueden contactar con el Equipo de Respuesta Rápida de Microsoft u otros contactos apropiados listados en https://news.microsoft.com/microsoft-public-relations-contacts.
Amazon Braket, the quantum computing service from AWS, now offers access to Rigetti’s Cepheus-1-108Q device, the first 100+ qubit superconducting quantum processing unit (QPU) available on Amazon Braket. Cepheus-1-108Q uses Rigetti’s modular multi-chip architecture, consisting of a 3×4 array of twelve 9-qubit chiplets with tunable couplers and intermodule couplers between chiplets.
Cepheus-1-108Q introduces CZ (controlled phase) gates, replacing the iSWAP gates used on previous Rigetti QPUs. CZ gates provide higher resilience to phase errors common in superconducting systems, and Rigetti’s adiabatic CZ implementation further reduces leakage errors. These improvements enable customers to run deeper circuits for use cases such as chemical simulation, combinatorial optimization, and machine learning. Customers can build and run quantum programs using the Braket SDK or other frameworks such as Qiskit, CUDA-Q, and Pennylane. Pulse-level control is also available for researchers who need low-level hardware access to study noise, develop gates, or devise error mitigation schemes.
Amazon Braket, the quantum computing service from AWS, now offers access to Rigetti’s Cepheus-1-108Q device, the first 100+ qubit superconducting quantum processing unit (QPU) available on Amazon Braket. Cepheus-1-108Q uses Rigetti’s modular multi-chip architecture, consisting of a 3×4 array of twelve 9-qubit chiplets with tunable couplers and intermodule couplers between chiplets.
Cepheus-1-108Q introduces CZ (controlled phase) gates, replacing the iSWAP gates used on previous Rigetti QPUs. CZ gates provide higher resilience to phase errors common in superconducting systems, and Rigetti’s adiabatic CZ implementation further reduces leakage errors. These improvements enable customers to run deeper circuits for use cases such as chemical simulation, combinatorial optimization, and machine learning. Customers can build and run quantum programs using the Braket SDK or other frameworks such as Qiskit, CUDA-Q, and Pennylane. Pulse-level control is also available for researchers who need low-level hardware access to study noise, develop gates, or devise error mitigation schemes.
Cepheus-1-108Q is available in the US West (N. California) Region. Get started by viewing the device on the Amazon Braket Management Console, reading our Amazon Braket documentation, or applying for AWS credits to support experiments on Amazon Braket through the AWS Cloud Credits for Research program.
