Amazon RDS for MySQL now supports community MySQL Innovation Release 9.4 in the Amazon RDS Database Preview Environment, allowing you to evaluate the latest Innovation Release on Amazon RDS for MySQL. You can deploy MySQL 9.4 in the Amazon RDS Database Preview Environment which provides the benefits of a fully managed database, making it simpler to set up, operate, and monitor databases.

MySQL 9.4 is the latest Innovation Release from the MySQL community. MySQL Innovation releases include bug fixes, security patches, as well as new features. MySQL Innovation releases are supported by the community until the next innovation minor, whereas MySQL Long Term Support (LTS) Releases, such as MySQL 8.0 and MySQL 8.4, are supported by the community for up to eight years. Please refer to the MySQL 9.4 release notes and Amazon RDS MySQL release notes for more details.

Amazon RDS Database Preview Environment supports both Single-AZ and Multi-AZ deployments on the latest generation of instance classes. Amazon RDS Database Preview Environment database instances are retained for a maximum of 60 days and are automatically deleted after the retention period. Amazon RDS database snapshots created in the Preview Environment can only be used to create or restore database instances within the Preview Environment.

Amazon RDS Database Preview Environment database instances are priced the same as production RDS instances created in the US East (Ohio) Region. For further information, see Working with the Database Preview Environment. To get started with the Preview Environment from the RDS console, navigate here.

​Amazon RDS for MySQL now supports community MySQL Innovation Release 9.4 in the Amazon RDS Database Preview Environment, allowing you to evaluate the latest Innovation Release on Amazon RDS for MySQL. You can deploy MySQL 9.4 in the Amazon RDS Database Preview Environment which provides the benefits of a fully managed database, making it simpler to set up, operate, and monitor databases. MySQL 9.4 is the latest Innovation Release from the MySQL community. MySQL Innovation releases include bug fixes, security patches, as well as new features. MySQL Innovation releases are supported by the community until the next innovation minor, whereas MySQL Long Term Support (LTS) Releases, such as MySQL 8.0 and MySQL 8.4, are supported by the community for up to eight years. Please refer to the MySQL 9.4 release notes and Amazon RDS MySQL release notes for more details. Amazon RDS Database Preview Environment supports both Single-AZ and Multi-AZ deployments on the latest generation of instance classes. Amazon RDS Database Preview Environment database instances are retained for a maximum of 60 days and are automatically deleted after the retention period. Amazon RDS database snapshots created in the Preview Environment can only be used to create or restore database instances within the Preview Environment. Amazon RDS Database Preview Environment database instances are priced the same as production RDS instances created in the US East (Ohio) Region. For further information, see Working with the Database Preview Environment. To get started with the Preview Environment from the RDS console, navigate here.  

AWS Organizations now offers full IAM policy language support for service control policies (SCPs), enabling you to write SCPs with the same flexibility as IAM managed policies. With this launch, SCPs now support use of conditions, individual resource ARNs, and the NotAction element with Allow statements. Additionally, you can now use wildcards at the beginning or middle of Action element strings and the NotResource element.

With these policy language enhancements, you can now create more concise and precise policies to implement sophisticated permissions guardrails across your organization. For example, you can restrict access to specific resources with condition statements. The enhanced functionality maintains backward compatibility with existing SCPs, so no changes to current policies are required.

This feature is now available in all AWS commercial and AWS GovCloud (US) Regions.

To learn more about the enhanced SCP capabilities, see service control policies in the AWS Organizations User Guide and AWS blog.

​AWS Organizations now offers full IAM policy language support for service control policies (SCPs), enabling you to write SCPs with the same flexibility as IAM managed policies. With this launch, SCPs now support use of conditions, individual resource ARNs, and the NotAction element with Allow statements. Additionally, you can now use wildcards at the beginning or middle of Action element strings and the NotResource element. With these policy language enhancements, you can now create more concise and precise policies to implement sophisticated permissions guardrails across your organization. For example, you can restrict access to specific resources with condition statements. The enhanced functionality maintains backward compatibility with existing SCPs, so no changes to current policies are required. This feature is now available in all AWS commercial and AWS GovCloud (US) Regions. To learn more about the enhanced SCP capabilities, see service control policies in the AWS Organizations User Guide and AWS blog.  

Amazon OpenSearch Ingestion now supports cross-account ingestion for push-based sources such as HTTP and OpenTelemetry (OTel). With this launch, customers can easily share OpenSearch Ingestion pipelines across AWS accounts without relying on additional configurations like VPC peering or AWS Transit Gateway.

This capability makes it simpler for organizations with multiple accounts to centralize observability and analytics workflows. For example, a central logging team can create ingestion pipelines and grant access to development teams across different accounts, enabling them to ingest logs, metrics, and traces directly into OpenSearch domains or OpenSearch Serverless collections. This reduces operational overhead and lowers the cost of sharing ingestion pipelines across accounts.

Cross-account ingestion for Amazon OpenSearch Ingestion is available today in all AWS regions where OpenSearch Ingestion is offered. Customers can get started by creating resource policies in the AWS Management Console or using the AWS CLI, and then enabling pipeline endpoints from their VPCs to ingest data seamlessly.

To learn more about this feature, see the Amazon OpenSearch Service Developer Guide and the launch blog.

​Amazon OpenSearch Ingestion now supports cross-account ingestion for push-based sources such as HTTP and OpenTelemetry (OTel). With this launch, customers can easily share OpenSearch Ingestion pipelines across AWS accounts without relying on additional configurations like VPC peering or AWS Transit Gateway.
This capability makes it simpler for organizations with multiple accounts to centralize observability and analytics workflows. For example, a central logging team can create ingestion pipelines and grant access to development teams across different accounts, enabling them to ingest logs, metrics, and traces directly into OpenSearch domains or OpenSearch Serverless collections. This reduces operational overhead and lowers the cost of sharing ingestion pipelines across accounts.
Cross-account ingestion for Amazon OpenSearch Ingestion is available today in all AWS regions where OpenSearch Ingestion is offered. Customers can get started by creating resource policies in the AWS Management Console or using the AWS CLI, and then enabling pipeline endpoints from their VPCs to ingest data seamlessly.
To learn more about this feature, see the Amazon OpenSearch Service Developer Guide and the launch blog.  

Amazon Redshift announces the general availability of Multidimensional Data Layouts (MDDL) that dynamically sort data based on actual query filters, accelerating query performance. Unlike traditional sorting methods that sort data based on fixed columns, MDDL sorts data based on query filters (for example, Sales in US), achieving up to 10x better end-to-end performance compared to using only optimal single-column sort keys for query workloads with repetitive query filters.

For each table with an AUTO sort key, which is the default for tables without an explicit sort key, Redshift analyzes the table’s query history and automatically selects either a single-column sort key or MDDL for your table, depending on potential performance improvements for your workload. Redshift with MDDL automatically constructs a multidimensional virtual sort key that co-locates rows typically accessed by the same queries. This virtual column, equivalent to a new sort key for the table, is subsequently used during query execution to skip data blocks and even skip scanning entire predicate columns. Redshift with MDDL provides a more expressive generalization of existing compound and interleaved sort keys that significantly improves the performance of table scans, especially when your query workload contains repetitive query filters. For pre-existing tables with manually defined sort keys, you can take advantage of MDDL by altering the sortkey of the table to AUTO.

MDDL is available in all AWS commercial regions where Redshift is available. To get started, read the documentation, blog, and Amazon Science publication to learn more about benchmarks on query performance improvements. 

​Amazon Redshift announces the general availability of Multidimensional Data Layouts (MDDL) that dynamically sort data based on actual query filters, accelerating query performance. Unlike traditional sorting methods that sort data based on fixed columns, MDDL sorts data based on query filters (for example, Sales in US), achieving up to 10x better end-to-end performance compared to using only optimal single-column sort keys for query workloads with repetitive query filters. For each table with an AUTO sort key, which is the default for tables without an explicit sort key, Redshift analyzes the table’s query history and automatically selects either a single-column sort key or MDDL for your table, depending on potential performance improvements for your workload. Redshift with MDDL automatically constructs a multidimensional virtual sort key that co-locates rows typically accessed by the same queries. This virtual column, equivalent to a new sort key for the table, is subsequently used during query execution to skip data blocks and even skip scanning entire predicate columns. Redshift with MDDL provides a more expressive generalization of existing compound and interleaved sort keys that significantly improves the performance of table scans, especially when your query workload contains repetitive query filters. For pre-existing tables with manually defined sort keys, you can take advantage of MDDL by altering the sortkey of the table to AUTO. MDDL is available in all AWS commercial regions where Redshift is available. To get started, read the documentation, blog, and Amazon Science publication to learn more about benchmarks on query performance improvements.   

• Categoría: Noticias de Microsoft

septiembre 19, 2025

Cinco años que sacudieron el mundo de los negocios

Un extracto de la nueva antología de WorkLab

Por Colette Stallbaumer, cofundadora de WorkLab y directora general de Copilot.

Para comprender el mundo laboral actual impulsado por la IA, comiencen por observar los cinco años que nos llevaron aquí. En abril de 2020, cuando el mundo pasó al trabajo remoto casi de la noche a la mañana, lanzamos WorkLab para ayudar a los líderes a comprender los cambios radicales que redefinen los negocios. Desde entonces, nos hemos asociado con líderes de opinión, investigadores y ejecutivos de todas las industrias para arrojar luz sobre los patrones que remodelan el trabajo, desde el trabajo híbrido hasta las empresas fronterizas en el borde irregular de la reinvención de la IA.

Nadie puede predecir el futuro, solo podemos aprender sobre la marcha y compartir lo que aprendemos en el camino. Ahora, reunimos esas lecciones en una nueva antología de nuestros datos e historias más convincentes: WorkLab: Cinco años que sacudieron el mundo de los negocios y provocaron un futuro donde la IA es primero.

Estamos encantados de compartir que WorkLab llegará a los estantes el 21 de octubre. Asegúrense de reservar su copia hoy a través de Amazon, Bookshop.org, Barnes & Noble o su librería local favorita.

Lean a continuación para ver un extracto de WorkLab: Cinco años que sacudieron el mundo de los negocios y provocaron un futuro donde la IA es primero, por la cofundadora de Worklab, Colette Stallbaumer.

Los tempestuosos años 20, la década que comenzó en 2020, en la oscuridad de una pandemia global y luego la curiosa luz de una transición de IA, han desafiado nuestro antiguo ideal de trabajo. El cambio es la única constante: las normas cambiantes que alguna vez tardaron décadas en desarrollarse ahora se materializan en meses o semanas. A medida que miramos hacia los próximos cinco años, es casi imposible imaginar cuánto más cambiará el trabajo.

Cuando pienso en ese futuro, pienso en mis dos adolescentes: brillantes, independientes y a punto de ingresar al mundo laboral. En este momento de cambio constante, veo un mundo de posibilidades para ellos. Ellos, y sus compañeros, nos han demostrado que hay formas casi infinitas de aprender y adquirir experiencia. Son artistas, músicos, influencers y emprendedores autodidactas. Espero que el trabajo sea muy diferente para ellos y que tengan múltiples carreras a lo largo de sus vidas.

Entonces, si el cambio es la constante, ¿qué permanece igual? ¿Cómo nos preparamos para un futuro del trabajo en constante evolución? Mientras reflexiono sobre lo que hemos aprendido en los últimos cinco años, este es mi mejor consejo para los próximos cinco:

Aprender es el trabajo. Satya Nadella escribió en su libro de 2017, Hit Refresh, que una mentalidad de crecimiento es lo más importante que puede aportar al trabajo. Eso nunca ha sido más cierto. El futuro pertenece a aquellos con un hambre y un deseo de aprender que arde brillante. Ve tras él. En un mundo en rápida evolución, la resiliencia y la adaptabilidad son habilidades muy valoradas: perfecciónenlas. El panorama cambia con rapidez, pero su mayor ventaja competitiva, como ser humano o como empresa, es el conocimiento para poner la IA a trabajar para ustedes. Mantengan la curiosidad y levanten la mano para el trabajo desordenado e inexplorado. Ahí es donde se encuentran las mayores oportunidades para aprender y las mayores recompensas. 

Mantenerse humanos. Me preguntan todo el tiempo, mientras miramos hacia la próxima década, ¿importarán los humanos en el trabajo? Mi respuesta es un rotundo sí. El mayor error sobre el trabajo en la era de la IA es que las habilidades humanas no importarán, cuando en realidad es un llamado a amplificar lo que nos hace humanos únicos. Inteligencia emocional; la capacidad de pensar de manera crítica y ejercer el juicio; la chispa creativa que se enciende cuando las personas colaboran (ahora con IA en el viaje); la habilidad para conectar los puntos y leer una habitación: esas cualidades nunca han sido más importantes. Lo entiendo, la colaboración entre humanos e IA es aterradora y nueva. Pero el trabajo está listo para un reinicio, y ya he comenzado a ver cómo en verdad, poner a la IA y a los agentes a trabajar para nosotros, crea espacio para el enfoque, la innovación y la creatividad, las cosas que hacen que el trabajo sea más gratificante. Tienen talentos humanos únicos que la IA no puede replicar, apóyense en ellos.  

Practicar el coraje creativo. El cambio y la incertidumbre de los últimos cinco años han sido muchos, y sería fácil tener una visión del futuro con el vaso medio vacío. Pero aquí está la cosa: nunca ha habido un mejor momento para iniciar un negocio, administrar su trabajo como si fuera su propia startup o dar vuelo a la idea de mil millones de dólares que burbujea en la noche. La IA reduce la barrera de entrada para dominar cualquier habilidad que quieran aprender o crear la vida que desean para ti. Un solo individuo puede construir una empresa; los equipos pueden producir semanas de trabajo en un solo día; y como sociedad, al final podemos lograr un progreso real en grandes problemas como el cambio climático y la búsqueda de curas para enfermedades raras, todo gracias a la IA. Esta no es solo la era de la IA, es la era del ingenio humano. Ahora no es el momento de quedarse al margen, es momento de actuar.  

Líderes, les insto a que aprovechen este momento para ayudar a las personas a ver las posibilidades. Construyan equipos, organizaciones y mentalidades que prosperen en movimiento. Reúnan a la gente en torno a la IA para fortalecer a tu equipo. Cuando todos usan IA, las recompensas y el impacto aumentan.

El futuro del trabajo se escribe ahora mismo, y ustedes tienen un bolígrafo. Saludemos la era que se avecina con optimismo y propósito.

Etiquetas:

• IA
• Vida y Trabajo

The post Cinco años que sacudieron el mundo de los negocios appeared first on Source LATAM.

​The post Cinco años que sacudieron el mundo de los negocios appeared first on Source LATAM.  

Today, AWS announces the general availability of Neuron SDK 2.26.0, delivering improvements for deep learning workloads on AWS Inferentia and Trainium-based instances. This release introduces support for PyTorch 2.8 and JAX 0.6.2, along with enhanced inference capabilities on Trainium2 (Trn2) instances. These updates enable developers to leverage the latest frameworks while benefiting from improved model deployment flexibility and performance optimizations.

With Neuron SDK 2.26.0, customers can now deploy FLUX.1-dev image generation model, along with Llama 4 Scout and Maverick variants (beta) on Trn2 instances. The release introduces expert parallelism support (beta) for efficient distribution of Mixture-of-Experts (MoE) models across multiple NeuronCores, and adds new capabilities through new Neuron Kernel Interface (NKI) APIs. The updated Neuron Profiler provides improved capabilities, including system profile grouping for distributed workloads.

The new SDK version is available in all AWS Regions supporting Inferentia and Trainium instances, offering enhanced performance and monitoring capabilities for machine learning workloads.

To learn more and for a full list of new features and enhancements, see:

• AWS Neuron 2.26.0 release notes
• Trn2 Instances
• Trn1 Instances
• Inf2 Instances

​Today, AWS announces the general availability of Neuron SDK 2.26.0, delivering improvements for deep learning workloads on AWS Inferentia and Trainium-based instances. This release introduces support for PyTorch 2.8 and JAX 0.6.2, along with enhanced inference capabilities on Trainium2 (Trn2) instances. These updates enable developers to leverage the latest frameworks while benefiting from improved model deployment flexibility and performance optimizations. With Neuron SDK 2.26.0, customers can now deploy FLUX.1-dev image generation model, along with Llama 4 Scout and Maverick variants (beta) on Trn2 instances. The release introduces expert parallelism support (beta) for efficient distribution of Mixture-of-Experts (MoE) models across multiple NeuronCores, and adds new capabilities through new Neuron Kernel Interface (NKI) APIs. The updated Neuron Profiler provides improved capabilities, including system profile grouping for distributed workloads. The new SDK version is available in all AWS Regions supporting Inferentia and Trainium instances, offering enhanced performance and monitoring capabilities for machine learning workloads. To learn more and for a full list of new features and enhancements, see:

AWS Neuron 2.26.0 release notes
Trn2 Instances
Trn1 Instances
Inf2 Instances  

Amazon Kinesis Data Streams now allows customers to make API requests over Internet Protocol version 6 (IPv6) in the AWS GovCloud (US) Regions. Customers have the option of using either IPv6 or IPv4 when sending requests over dual-stack public or VPC endpoints. The new endpoints have also been validated under the Federal Information Processing Standard (FIPS) 140-3 program.

Kinesis Data Streams allows users to capture, process, and store data streams in real time at any scale. IPv6 increases the number of available addresses by several orders of magnitude, so customers will no longer need to manage overlapping address spaces. Many devices and networks today already use IPv6, and now they can easily write to and read from data streams. FIPS-compliant endpoints help companies contracting with the US federal governments meet the FIPS security requirement to encrypt sensitive data in supported Regions.

Support for IPv6 with Kinesis Data Streams is now available in all Regions where Kinesis Data Streams is available, including AWS GovCloud (US) and China Regions. See here for a full listing of our Regions. To learn more about Kinesis Data Streams, please refer to our Developer Guide.

​Amazon Kinesis Data Streams now allows customers to make API requests over Internet Protocol version 6 (IPv6) in the AWS GovCloud (US) Regions. Customers have the option of using either IPv6 or IPv4 when sending requests over dual-stack public or VPC endpoints. The new endpoints have also been validated under the Federal Information Processing Standard (FIPS) 140-3 program. Kinesis Data Streams allows users to capture, process, and store data streams in real time at any scale. IPv6 increases the number of available addresses by several orders of magnitude, so customers will no longer need to manage overlapping address spaces. Many devices and networks today already use IPv6, and now they can easily write to and read from data streams. FIPS-compliant endpoints help companies contracting with the US federal governments meet the FIPS security requirement to encrypt sensitive data in supported Regions. Support for IPv6 with Kinesis Data Streams is now available in all Regions where Kinesis Data Streams is available, including AWS GovCloud (US) and China Regions. See here for a full listing of our Regions. To learn more about Kinesis Data Streams, please refer to our Developer Guide.  

Amazon Bedrock announces the availability of Stability AI Image Services, a comprehensive suite of 9 specialized image editing tools designed to accelerate professional creative workflows. Stability AI Image Services enable granular control over image editing with a range of tools designed to work with your creative process, allowing you to take a single concept from ideation to finished product with precision and flexibility.

Stability AI Image Services offers two categories of image editing capabilities: Edit tools: Remove Background, Erase Object, Search and Replace, Search and Recolor, and Inpaint let you make targeted modifications to specific parts of your images. Control tools: Structure, Sketch, Style Guide, and Style Transfer give you powerful ways to generate variations based on existing images or sketches.

Stability AI Image Services is now available in Amazon Bedrock through the API and is supported in US West (Oregon), US East (N. Virginia), and US East (Ohio). For more information on supported regions, visit the Amazon Bedrock Model Support by Regions guide. For more details about Stability AI Image Services and its capabilities, visit the Stability AI product page and Stability AI documentation page. 

​Amazon Bedrock announces the availability of Stability AI Image Services, a comprehensive suite of 9 specialized image editing tools designed to accelerate professional creative workflows. Stability AI Image Services enable granular control over image editing with a range of tools designed to work with your creative process, allowing you to take a single concept from ideation to finished product with precision and flexibility. Stability AI Image Services offers two categories of image editing capabilities: Edit tools: Remove Background, Erase Object, Search and Replace, Search and Recolor, and Inpaint let you make targeted modifications to specific parts of your images. Control tools: Structure, Sketch, Style Guide, and Style Transfer give you powerful ways to generate variations based on existing images or sketches. Stability AI Image Services is now available in Amazon Bedrock through the API and is supported in US West (Oregon), US East (N. Virginia), and US East (Ohio). For more information on supported regions, visit the Amazon Bedrock Model Support by Regions guide. For more details about Stability AI Image Services and its capabilities, visit the Stability AI product page and Stability AI documentation page.   

Today, AWS announces the expansion of OpenAI open weight models on AWS Bedrock to eight new regions. This expansion brings these powerful AI models closer to customers in various parts of the world, enabling lower latency and improved performance for a wide range of AI-powered applications.

With this expansion, the OpenAI open weight models are now available in the following AWS Regions: US East (N. Virginia), Asia Pacific (Tokyo), Europe (Stockholm), Asia Pacific (Mumbai), Europe (Ireland), South America (São Paulo), Europe (London), and Europe (Milan), in addition to the previously supported region of US West (Oregon). This broader availability allows more customers to leverage these state-of-the-art AI models while keeping their data within their preferred geographic locations, helping to address data residency requirements and reduce network latency.

To learn more about OpenAI open weight models on AWS Bedrock and how to get started, visit the Amazon Bedrock console or check out our documentation. For more information about the initial release of these models on AWS Bedrock, refer to our previous blog post. 

​Today, AWS announces the expansion of OpenAI open weight models on AWS Bedrock to eight new regions. This expansion brings these powerful AI models closer to customers in various parts of the world, enabling lower latency and improved performance for a wide range of AI-powered applications. With this expansion, the OpenAI open weight models are now available in the following AWS Regions: US East (N. Virginia), Asia Pacific (Tokyo), Europe (Stockholm), Asia Pacific (Mumbai), Europe (Ireland), South America (São Paulo), Europe (London), and Europe (Milan), in addition to the previously supported region of US West (Oregon). This broader availability allows more customers to leverage these state-of-the-art AI models while keeping their data within their preferred geographic locations, helping to address data residency requirements and reduce network latency. To learn more about OpenAI open weight models on AWS Bedrock and how to get started, visit the Amazon Bedrock console or check out our documentation. For more information about the initial release of these models on AWS Bedrock, refer to our previous blog post.   

Amazon Bedrock continues to expand model choice by adding four Qwen3 open weight foundation models, now available as fully managed, serverless offerings. The lineup includes: Qwen3-Coder-480B-A35B-Instruct, Qwen3-Coder-30B-A3B-Instruct, Qwen3-235B-A22B-Instruct-2507, and Qwen3-32B for efficient dense computation. These models feature both dense and Mixture-of-Experts (MoE) architectures, providing flexible options for various development needs.

These open weight models enable you to build powerful AI applications with advanced agentic capabilities, without managing any infrastructure. The two Qwen3-Coder models excel at agentic coding and complex software engineering tasks, offering state-of-the-art performance for function calling and tool use. The 235B model delivers efficient general reasoning and instruction following across diverse tasks, while the 32B dense model provides a more traditional architecture suitable for a wide range of computational tasks.

Qwen3 models (32B, Coder-30B) are available today in the US East (N. Virginia), US West (Oregon), Asia Pacific (Mumbai, Tokyo), Europe (Ireland, London, Milan, Stockholm), and South America (São Paulo) AWS Regions. Qwen 235B is available today in theUS West (Oregon), Asia Pacific (Mumbai, Tokyo), and Europe (London, Milan, Stockholm) AWS Regions. Qwen Coder-480B is available today in the US West (Oregon), Asia Pacific (Mumbai, Tokyo), and Europe (London, Stockholm) AWS Regions. Check the full Region list for future updates. To learn more, read the blog, product page, Amazon Bedrock pricing, and documentation. To get started with Qwen in Amazon Bedrock, visit the Amazon Bedrock console.

​Amazon Bedrock continues to expand model choice by adding four Qwen3 open weight foundation models, now available as fully managed, serverless offerings. The lineup includes: Qwen3-Coder-480B-A35B-Instruct, Qwen3-Coder-30B-A3B-Instruct, Qwen3-235B-A22B-Instruct-2507, and Qwen3-32B for efficient dense computation. These models feature both dense and Mixture-of-Experts (MoE) architectures, providing flexible options for various development needs. These open weight models enable you to build powerful AI applications with advanced agentic capabilities, without managing any infrastructure. The two Qwen3-Coder models excel at agentic coding and complex software engineering tasks, offering state-of-the-art performance for function calling and tool use. The 235B model delivers efficient general reasoning and instruction following across diverse tasks, while the 32B dense model provides a more traditional architecture suitable for a wide range of computational tasks. Qwen3 models (32B, Coder-30B) are available today in the US East (N. Virginia), US West (Oregon), Asia Pacific (Mumbai, Tokyo), Europe (Ireland, London, Milan, Stockholm), and South America (São Paulo) AWS Regions. Qwen 235B is available today in theUS West (Oregon), Asia Pacific (Mumbai, Tokyo), and Europe (London, Milan, Stockholm) AWS Regions. Qwen Coder-480B is available today in the US West (Oregon), Asia Pacific (Mumbai, Tokyo), and Europe (London, Stockholm) AWS Regions. Check the full Region list for future updates. To learn more, read the blog, product page, Amazon Bedrock pricing, and documentation. To get started with Qwen in Amazon Bedrock, visit the Amazon Bedrock console.