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• Categoría: Noticias de Microsoft

septiembre 4, 2025

Una forma más inteligente de hablar con su televisor: Microsoft Copilot se lanza en televisores y monitores Samsung

Por: Equipo de Copilot.

La IA impulsada por voz se encuentra con un compañero visual para el entretenimiento, la ayuda diaria y todo lo demás.

Anunciamos el lanzamiento de Copilot en televisores y monitores Samsung seleccionados, para transformar la pantalla más grande de su hogar en su compañero más personal y útil, y es de uso gratuito.  

Copilot hace que su televisor sea más fácil y divertido de usar con su interfaz impulsada por voz, su personaje amigable en pantalla y sus sencillas tarjetas visuales. Ahora pueden encontrar con rapidez lo que buscan y descubrir nuevos favoritos directo desde su sala de estar.   

Debido a que vive en la pantalla más grande del hogar, Copilot es una experiencia social, algo que pueden usar junto con familiares y amigos para iniciar conversaciones, ayudar a los grupos a decidir qué ver y convertir el televisor en un espacio compartido para la curiosidad y la conexión.

«Copilot en televisores y monitores Samsung saca la IA de su bolsillo y la lleva al corazón de su hogar», dijo David Washington, gerente general de socios de Microsoft AI. «Está ahí cuando ustedes y su familia quieren descubrir algo para ver juntos, obtener respuestas a sus preguntas, planificar su fin de semana o tan solo pasar el rato».

Basado en la asociación

Microsoft y Samsung tienen una larga historia de reunir lo mejor de la tecnología, desde Windows y Office en dispositivos Galaxy hasta Xbox Cloud Gaming en televisores Samsung. Esta colaboración aporta ese mismo espíritu de innovación a Copilot, para hacer que su televisor sea más inteligente, más personal y más divertido.

Para resúmenes, madrigueras de conejo y todo lo demás

Copilot brilla cuando se trata de encontrar su próxima cosa favorita para ver, pero también está ahí para las pequeñas preguntas, los grandes planes y los momentos cotidianos intermedios.

• Resúmenes personalizados y sin spoilers: «Quiero volver a The Crown, lo dejé en la temporada 3, episodio 4. ¿Qué pasó hasta entonces?»
• Recomendaciones ultraespecíficas: «Como The Queen’s Gambit, pero sobre cocinar en lugar de ajedrez, y menos de dos horas».  
• Selecciones para grupos: «A Hannah le gustan las comedias románticas, a David le gusta la ciencia ficción, a Mark le gustan los thrillers. ¿Qué es algo que nos gustará a todos?» Perfecto para cuando todos están reunidos en la sala de estar y quieren decidir juntos.  
• Inmersiones profundas posteriores a la visualización: «¿Quién fue el actor de voz de ese personaje?» o «¿Qué más ha hecho el director?»
• Ayuda diaria: «¿Habrá el sábado en Seattle buenas condiciones para hacer senderismo?» o «Anímame después de una ruptura».  

Una experiencia más visual, más personal

La apariencia de Copilot  es una presencia amigable y animada en su televisor que reacciona y sincroniza los labios mientras hablan, con expresiones que coinciden con el tono de la conversación. Es un recordatorio visible de que su compañero los escucha, piensa y responde solo para ustedes. 

Y cuando Copilot responde, no solo se los dice, sino que se los muestra. Los resultados de películas, clima e imágenes aparecen como tarjetas ricas y visibles diseñadas para la pantalla grande, con calificaciones, fotos y detalles clave. 

Cómo funciona

1. Activar Copilot: Copilot se implementará en automático en televisores Samsung seleccionados. Los usuarios pueden ver Copilot (en la pestaña Aplicaciones) en el Samsung Tizen OS home Samsung Daily+. Presionen el botón del micrófono en su control remoto Samsung y hablen con naturalidad. 
2. (Opcional) Inicien sesión para un toque personal: usen un código QR rápido para conectar su cuenta de Microsoft y desbloquear la personalización, la memoria y las preferencias de Copilot por ustedes.  
3. Pidan lo que quieren: Ya sea un título, una pregunta o un consejo, Copilot los entiende.
4. Vean y escuchen su respuesta: vean cómo Copilot responde con una combinación de imágenes y voz.

Disponibilidad
Copilot se lanza en la línea 2025 de televisores y monitores Samsung ^[1] y ya está disponible, con más años de modelo y características a seguir. La experiencia está disponible sin costo alguno. 

^[1] Copilot está disponible en los modelos de TV 2025, incluidos Micro RGB, Neo QLED, OLED, The Frame Pro, The Frame, así como en los monitores inteligentes M7, M8 y M9. Copilot está disponible en mercados seleccionados. La disponibilidad se ampliará a regiones y modelos adicionales con el tiempo y la experiencia puede variar según el mercado. 

Etiquetas:

• IA
• Tecnología
• Vida y Trabajo

The post Una forma más inteligente de hablar con su televisor: Microsoft Copilot se lanza en televisores y monitores Samsung appeared first on Source LATAM.

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Today, AWS announced the opening of a new AWS Direct Connect location within East African Data Centres NBO1 near Nairobi, Kenya. You can now establish private, direct network access to all public AWS Regions (except those in China), AWS GovCloud Regions, and AWS Local Zones from this location. This site is the first AWS Direct Connect location in Kenya. This Direct Connect location offers dedicated 10 Gbps and 100 Gbps connections with MACsec encryption available.

The Direct Connect service enables you to establish a private, physical network connection between AWS and your data center, office, or colocation environment. These private connections can provide a more consistent network experience than those made over the public internet. 

For more information on the over 145 Direct Connect locations worldwide, visit the locations section of the Direct Connect product detail pages. Or, visit our getting started page to learn more about how to purchase and deploy Direct Connect.

​Today, AWS announced the opening of a new AWS Direct Connect location within East African Data Centres NBO1 near Nairobi, Kenya. You can now establish private, direct network access to all public AWS Regions (except those in China), AWS GovCloud Regions, and AWS Local Zones from this location. This site is the first AWS Direct Connect location in Kenya. This Direct Connect location offers dedicated 10 Gbps and 100 Gbps connections with MACsec encryption available. The Direct Connect service enables you to establish a private, physical network connection between AWS and your data center, office, or colocation environment. These private connections can provide a more consistent network experience than those made over the public internet.  For more information on the over 145 Direct Connect locations worldwide, visit the locations section of the Direct Connect product detail pages. Or, visit our getting started page to learn more about how to purchase and deploy Direct Connect.  

Amazon SageMaker Catalog now supports governed classification through Restricted Classification Terms, allowing catalog administrators to control which users and projects can apply sensitive glossary terms to their assets. This new capability is designed to help organizations enforce metadata standards and ensure classification consistency across teams and domains.

With this launch, glossary terms can be marked as «restricted», and only authorized users or groups—defined through explicit policies—can use them to classify data assets. For example, a centralized data governance team may define terms like “Seller-MCF” or “PII” that reflect data handling policies. These terms can now be governed so only specific project members (e.g., trusted admin groups) can apply them, which helps support proper control over how sensitive classifications are assigned.

This feature is now available in all AWS regions where Amazon SageMaker Unified Studio is supported.

To get started and learn more about this feature, see SageMaker Unified Studio user guide.

​Amazon SageMaker Catalog now supports governed classification through Restricted Classification Terms, allowing catalog administrators to control which users and projects can apply sensitive glossary terms to their assets. This new capability is designed to help organizations enforce metadata standards and ensure classification consistency across teams and domains. With this launch, glossary terms can be marked as «restricted», and only authorized users or groups—defined through explicit policies—can use them to classify data assets. For example, a centralized data governance team may define terms like “Seller-MCF” or “PII” that reflect data handling policies. These terms can now be governed so only specific project members (e.g., trusted admin groups) can apply them, which helps support proper control over how sensitive classifications are assigned. This feature is now available in all AWS regions where Amazon SageMaker Unified Studio is supported. To get started and learn more about this feature, see SageMaker Unified Studio user guide.  

Amazon MQ now supports OAuth 2.0 authentication and authorization for RabbitMQ brokers with public identity providers in both single instance and highly available Multi-AZ cluster deployments. This feature enables RabbitMQ brokers to authenticate clients and users using JWT-encoded OAuth 2.0 access tokens, providing enhanced security and flexibility in access management.

You can configure OAuth 2.0 on your RabbitMQ broker on Amazon MQ using the AWS Console, AWS CloudFormation, AWS Command Line Interface (CLI), or the AWS Cloud Development Kit (CDK). This feature is available in all AWS regions where Amazon MQ is available. To get started, create a new RabbitMQ broker with OAuth 2.0 authentication or update your existing broker’s configuration to enable OAuth2.0 support. This feature maintains compatibility with standard RabbitMQ OAuth 2.0 implementations, ensuring seamless migration for existing OAuth 2.0 enabled brokers. For detailed configuration options and steps, refer to the Amazon MQ documentation page. 

​Amazon MQ now supports OAuth 2.0 authentication and authorization for RabbitMQ brokers with public identity providers in both single instance and highly available Multi-AZ cluster deployments. This feature enables RabbitMQ brokers to authenticate clients and users using JWT-encoded OAuth 2.0 access tokens, providing enhanced security and flexibility in access management. You can configure OAuth 2.0 on your RabbitMQ broker on Amazon MQ using the AWS Console, AWS CloudFormation, AWS Command Line Interface (CLI), or the AWS Cloud Development Kit (CDK). This feature is available in all AWS regions where Amazon MQ is available. To get started, create a new RabbitMQ broker with OAuth 2.0 authentication or update your existing broker’s configuration to enable OAuth2.0 support. This feature maintains compatibility with standard RabbitMQ OAuth 2.0 implementations, ensuring seamless migration for existing OAuth 2.0 enabled brokers. For detailed configuration options and steps, refer to the Amazon MQ documentation page.   

Anthropic’s Claude Sonnet 4 is now available with Global cross-Region inference in Amazon Bedrock, so you can now use the Global Claude Sonnet 4 inference profile to route your inference requests to any supported commercial AWS Region for processing, optimizing available resources and enabling higher model throughput.

Amazon Bedrock is a comprehensive, secure, and flexible service for building generative AI applications and agents. When using on-demand and batch inference in Amazon Bedrock, your requests may be restricted by service quotas or during peak usage times. Cross-region inference enables you to seamlessly manage unplanned traffic bursts by utilizing compute across different AWS Regions. With cross-region inference, you can distribute traffic across multiple AWS Regions, enabling higher throughput. Previously, you were able to choose cross-region inference profiles tied to a specific geography such as the US, EU, or APAC, which automatically selected the optimal commercial AWS Region within that geography to process your inference requests. For your generative AI use cases that do not require you to choose inference profiles tied to a specific geography, you can now use the Global cross-region inference profile to further increase your model throughput.

To learn more about global cross-Region inference in Amazon Bedrock, you can visit our documentation on increasing throughput with cross-Region inference, see supported Regions and models for inference profiles, and follow the steps mentioned in the Use an inference profile in model invocation page to get started.

​Anthropic’s Claude Sonnet 4 is now available with Global cross-Region inference in Amazon Bedrock, so you can now use the Global Claude Sonnet 4 inference profile to route your inference requests to any supported commercial AWS Region for processing, optimizing available resources and enabling higher model throughput. Amazon Bedrock is a comprehensive, secure, and flexible service for building generative AI applications and agents. When using on-demand and batch inference in Amazon Bedrock, your requests may be restricted by service quotas or during peak usage times. Cross-region inference enables you to seamlessly manage unplanned traffic bursts by utilizing compute across different AWS Regions. With cross-region inference, you can distribute traffic across multiple AWS Regions, enabling higher throughput. Previously, you were able to choose cross-region inference profiles tied to a specific geography such as the US, EU, or APAC, which automatically selected the optimal commercial AWS Region within that geography to process your inference requests. For your generative AI use cases that do not require you to choose inference profiles tied to a specific geography, you can now use the Global cross-region inference profile to further increase your model throughput. To learn more about global cross-Region inference in Amazon Bedrock, you can visit our documentation on increasing throughput with cross-Region inference, see supported Regions and models for inference profiles, and follow the steps mentioned in the Use an inference profile in model invocation page to get started.  

AWS Clean Rooms ML custom modeling enables you and your partners to train and run inference on a custom ML models using collective datasets at scale without having to share your sensitive data or intellectual property. With today’s launch, collaborators can configure a new privacy control that sends redacted error log summaries to specified collaboration members. Error log summaries include the exception type, error message, and line in the code where the error occurred. When associating the model to the collaboration, collaborators can decide and agree which members will receive error log summaries and whether those summaries will contain detectable Personally Identifiable Information (PII), numbers, or custom strings redacted.

AWS Clean Rooms ML helps you and your partners apply privacy-enhancing controls to safeguard your proprietary data and ML models while generating predictive insights—all without sharing or copying one another’s raw data or models. For more information about the AWS Regions where AWS Clean Rooms ML is available, see the AWS Regions table. To learn more, visit AWS Clean Rooms ML.

​AWS Clean Rooms ML custom modeling enables you and your partners to train and run inference on a custom ML models using collective datasets at scale without having to share your sensitive data or intellectual property. With today’s launch, collaborators can configure a new privacy control that sends redacted error log summaries to specified collaboration members. Error log summaries include the exception type, error message, and line in the code where the error occurred. When associating the model to the collaboration, collaborators can decide and agree which members will receive error log summaries and whether those summaries will contain detectable Personally Identifiable Information (PII), numbers, or custom strings redacted.
AWS Clean Rooms ML helps you and your partners apply privacy-enhancing controls to safeguard your proprietary data and ML models while generating predictive insights—all without sharing or copying one another’s raw data or models. For more information about the AWS Regions where AWS Clean Rooms ML is available, see the AWS Regions table. To learn more, visit AWS Clean Rooms ML.  

AWS Config now supports 5 additional AWS resource types. This expansion provides greater coverage over your AWS environment, enabling you to more effectively discover, assess, audit, and remediate an even broader range of resources.

With this launch, if you have enabled recording for all resource types, then AWS Config will automatically track these new additions. The newly supported resource types are also available in Config rules and Config aggregators.

You can now use AWS Config to monitor the following newly supported resource types in all AWS Regions where the supported resources are available.

Resource Types:

AWS::CodeArtifact::Domain

AWS::Config::ConformancePack

AWS::Glue::Database

AWS::NetworkManager::TransitGatewayPeering

AWS::RolesAnywhere::TrustAnchor

​AWS Config now supports 5 additional AWS resource types. This expansion provides greater coverage over your AWS environment, enabling you to more effectively discover, assess, audit, and remediate an even broader range of resources. With this launch, if you have enabled recording for all resource types, then AWS Config will automatically track these new additions. The newly supported resource types are also available in Config rules and Config aggregators. You can now use AWS Config to monitor the following newly supported resource types in all AWS Regions where the supported resources are available.
Resource Types:
AWS::CodeArtifact::Domain
AWS::Config::ConformancePack
AWS::Glue::Database
AWS::NetworkManager::TransitGatewayPeering
AWS::RolesAnywhere::TrustAnchor  

Amazon CloudWatch now allows you to monitor multiple individual metrics via a single alarm. By dynamically including metrics to monitor via a query, this new capability eliminates the need to manually manage separate alarms for dynamic resource fleets.

As customers rely more on autonomous teams and autoscaled resources, they face a choice between maintenance-free aggregated monitoring and the operational cost of maintaining per-resource alarming. Alarms that evaluate multiple metrics provide granular monitoring with individual actions through an alarm that automatically adjusts in real time as resources get created or deleted. This reduces operational efforts, allowing customers to focus on the value of their observability while ensuring no resources go unmonitored.

Monitoring multiple metrics with a single alarm is now available in all commercial AWS regions, the AWS GovCloud (US) Regions, and the China Regions.

To start alarming on multiple metrics, create an alarm on a Metrics Insights (SQL) metrics query using GROUP BY and ORDER BY conditions. The alarm automatically updates the query results with each evaluation, and matches corresponding metrics as resources change. You can configure alarms through the CloudWatch console, AWS CLI, CloudFormation, or CDK. Metrics Insights query alarms’ pricing applies, see CloudWatch pricing for details. To learn more about monitoring multiple metrics with query alarms and improving your monitoring efficiency, visit the CloudWatch alarms documentation.

​Amazon CloudWatch now allows you to monitor multiple individual metrics via a single alarm. By dynamically including metrics to monitor via a query, this new capability eliminates the need to manually manage separate alarms for dynamic resource fleets. As customers rely more on autonomous teams and autoscaled resources, they face a choice between maintenance-free aggregated monitoring and the operational cost of maintaining per-resource alarming. Alarms that evaluate multiple metrics provide granular monitoring with individual actions through an alarm that automatically adjusts in real time as resources get created or deleted. This reduces operational efforts, allowing customers to focus on the value of their observability while ensuring no resources go unmonitored. Monitoring multiple metrics with a single alarm is now available in all commercial AWS regions, the AWS GovCloud (US) Regions, and the China Regions. To start alarming on multiple metrics, create an alarm on a Metrics Insights (SQL) metrics query using GROUP BY and ORDER BY conditions. The alarm automatically updates the query results with each evaluation, and matches corresponding metrics as resources change. You can configure alarms through the CloudWatch console, AWS CLI, CloudFormation, or CDK. Metrics Insights query alarms’ pricing applies, see CloudWatch pricing for details. To learn more about monitoring multiple metrics with query alarms and improving your monitoring efficiency, visit the CloudWatch alarms documentation.  

Amazon CloudWatch now allows you to query metrics data up to two weeks in the past using the Metrics Insights query source. CloudWatch Metrics Insights offers fast, flexible, SQL-based queries. This new capability allows you to display, aggregate, or slice and dice metrics data older than 3 hours, for enhanced visualization and investigation.

Customers creating dashboards and alarms to monitor dynamic groups of metrics over their resources and applications could visualize up to 3 hours of data when using Metrics Insights SQL queries. This enhancement helps customers identify trends and investigate impact for a longer period of time, even days after an event. This extended query time range helps improve the operational health of teams and ensures impacts are never missed.

Querying metrics data up to two weeks old with Metrics Insights is now available in commercial AWS regions.

The ability to query metrics data up to 2 weeks old is automatically available at no additional cost. Standard pricing applies for alarms, dashboards or API usage on Metrics Insights, see CloudWatch pricing for details. To learn more about metrics queries with Metrics Insights, visit the CloudWatch documentation.

​Amazon CloudWatch now allows you to query metrics data up to two weeks in the past using the Metrics Insights query source. CloudWatch Metrics Insights offers fast, flexible, SQL-based queries. This new capability allows you to display, aggregate, or slice and dice metrics data older than 3 hours, for enhanced visualization and investigation. Customers creating dashboards and alarms to monitor dynamic groups of metrics over their resources and applications could visualize up to 3 hours of data when using Metrics Insights SQL queries. This enhancement helps customers identify trends and investigate impact for a longer period of time, even days after an event. This extended query time range helps improve the operational health of teams and ensures impacts are never missed. Querying metrics data up to two weeks old with Metrics Insights is now available in commercial AWS regions. The ability to query metrics data up to 2 weeks old is automatically available at no additional cost. Standard pricing applies for alarms, dashboards or API usage on Metrics Insights, see CloudWatch pricing for details. To learn more about metrics queries with Metrics Insights, visit the CloudWatch documentation.