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Cinco años que sacudieron el mundo de los negocios

septiembre 19, 2025

Cinco años que sacudieron el mundo de los negocios

Un extracto de la nueva antología de WorkLab

Composición abstracta en capas recortadas de papel que representa una cabeza con una apertura circular, en una gama de azules.

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.

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Announcing AWS Neuron SDK 2.26.0

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:

 

​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  

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Amazon Kinesis Data Streams expands Internet Protocol version 6 support to the AWS GovCloud (US) Regions

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.  

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Stability AI Image Services now available in Amazon Bedrock

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.   

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OpenAI open weight models expand to new regions on AWS Bedrock

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.   

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Qwen3 models are now available fully managed in Amazon Bedrock

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.  

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DeepSeek-V3.1 model now available fully managed in Amazon Bedrock

DeepSeek-V3.1 is now available as a fully managed foundation model in Amazon Bedrock. This advanced open weight model allows you to switch between thinking mode for detailed step-by-step analysis and non-thinking mode for quicker responses. With comprehensive multilingual support, it delivers enhanced accuracy and reduced hallucinations compared to previous DeepSeek models, while maintaining visibility into its decision-making process.

You can use DeepSeek-V3.1’s enterprise-grade capabilities across critical business functions, from state-of-the-art software development to complex mathematical reasoning and data analysis. The model excels at sophisticated problem-solving tasks, demonstrating strong performance in coding benchmarks and technical challenges. Its enhanced tool-calling capabilities and seamless workflow integration make it ideal for building AI agents and automating enterprise processes, while its transparent reasoning approach helps teams understand and trust its outputs.

DeepSeek-V3.1 is now available in the US West (Oregon), Asia Pacific (Tokyo), Asia Pacific (Mumbai), Europe (London), and Europe (Stockholm) AWS Regions. To learn more, read the blog, product page, Amazon Bedrock pricing, and documentation. To get started with DeepSeek in Amazon Bedrock, visit the Amazon Bedrock console.

 

​DeepSeek-V3.1 is now available as a fully managed foundation model in Amazon Bedrock. This advanced open weight model allows you to switch between thinking mode for detailed step-by-step analysis and non-thinking mode for quicker responses. With comprehensive multilingual support, it delivers enhanced accuracy and reduced hallucinations compared to previous DeepSeek models, while maintaining visibility into its decision-making process. You can use DeepSeek-V3.1’s enterprise-grade capabilities across critical business functions, from state-of-the-art software development to complex mathematical reasoning and data analysis. The model excels at sophisticated problem-solving tasks, demonstrating strong performance in coding benchmarks and technical challenges. Its enhanced tool-calling capabilities and seamless workflow integration make it ideal for building AI agents and automating enterprise processes, while its transparent reasoning approach helps teams understand and trust its outputs. DeepSeek-V3.1 is now available in the US West (Oregon), Asia Pacific (Tokyo), Asia Pacific (Mumbai), Europe (London), and Europe (Stockholm) AWS Regions. To learn more, read the blog, product page, Amazon Bedrock pricing, and documentation. To get started with DeepSeek in Amazon Bedrock, visit the Amazon Bedrock console.  

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Microsoft 365 Copilot: Habilitación de equipos de agentes humanos

septiembre 18, 2025

Microsoft 365 Copilot: Habilitación de equipos de agentes humanos

Una mujer y un hombre sostienen unas laptops. al lado, un texto dice "Microsoft 365 Copilot"

Por: Nicole Herskowitz, vicepresidenta corporativa, Microsoft 365 y Copilot.

El trabajo es, de manera fundamental, un deporte de equipo, pero hasta ahora la IA ha sido en gran medida un asistente personal. Hoy, presentamos nuevos agentes centrados en la colaboración para los usuarios de Microsoft 365 Copilot, lo que brinda a cada equipo, proyecto, reunión y comunidad un compañero de equipo de IA, que agrega IA sensible al contexto para respaldar las necesidades únicas de cada escenario de colaboración.

Estos nuevos agentes colaborativos están diseñados para mejorar el trabajo en Microsoft Teams, SharePoint y Viva Engage, para ayudar a los grupos a coordinarse, comunicarse y ejecutar con mayor claridad y eficacia. Al aprovechar la inteligencia de trabajo de Microsoft Graph, estos agentes ofrecen soporte contextual al tiempo que mantienen los controles de seguridad, identidad, cumplimiento y administración de nivel empresarial, lo que ayuda a que las interacciones sigan productivas y protegidas. Lean a continuación para explorar cómo estos agentes se convierten en participantes activos en cada etapa del trabajo en equipo.

Habilitación de equipos humano-agente

Los nuevos agentes diseñados con propósito, proporcionan IA siempre activa integrada donde ocurre la colaboración. Cada agente se basa en el contexto del grupo y está equipado con habilidades adaptadas a las formas únicas en que los grupos colaboran en canales, reuniones y comunidades en Teams, y bibliotecas y sitios en SharePoint. Digamos, por ejemplo, que un equipo trabaja en el lanzamiento de un producto para “Project Pluto».

El equipo consolida todas sus conversaciones y planes en un canal dedicado al «Project Pluto» en Teams, que ahora está equipado con un «Agente del Project Pluto». Los usuarios del canal pueden dirigir a este agente para resumir hilos, destilar decisiones, redactar planes y publicaciones, programar puntos de control y coordinarse con el agente de Project Manager para crear tareas para mantener el trabajo en movimiento.

Cuando llega el momento de una reunión de planeación en Teams para discutir el «Project Pluto», el agente facilitador de las reuniones interviene para preparar las agendas. Durante la reunión, toma notas de manera proactiva, mantiene la discusión en el buen camino, captura las decisiones y las convierte en acciones propias con seguimientos, rastreadas por completo a través de la integración con el agente del gerente de proyectos, e incluso completa algunas tareas por su cuenta. Los participantes de la reunión pueden guiar de manera colectiva al agente para que haga cosas como reorganizar la agenda o establecer un temporizador de reunión. 

Y para amplificar el lanzamiento del producto en la «Comunidad de ventas» en Viva Engage, el «Agente de la comunidad de ventas» maneja los anuncios, responde preguntas comunes con fuentes citadas y ayuda a los administradores de la comunidad a mantener las discusiones activas y precisas en tiempo real.

Detrás de escena, el Agente de conocimiento en SharePoint mantiene en forma el espacio de trabajo del «Project Pluto». Organiza y enriquece archivos, aplica las etiquetas correctas, realiza un seguimiento de las actualizaciones y une contenido relacionado del canal de Teams, las reuniones y la comunidad de ventas. Por lo tanto, cuando alguien le hace una pregunta a Microsoft 365 Copilot, ya sea «¿Cuál es nuestro posicionamiento aprobado?» o «¿Qué especificación es definitiva?»—extrae la fuente autorizada con citas.

Juntos, estos agentes mantienen cada etapa del lanzamiento del «Project Pluto», desde la planificación hasta la ejecución y la comunicación, con un funcionamiento sin problemas, con la IA que trabaja junto al equipo. Teams también admite un ecosistema abierto de agentes creados por socios y, con Model Context Protocol (MCP), esos agentes pueden colaborar sin problemas con agentes nativos de Teams, para compartir contexto e invocar las herramientas de los demás dentro del mismo flujo de trabajo. Estamos entusiasmados de trabajar con socios para desarrollar soluciones para que la colaboración multiplataforma con Teams sea sencilla.

Reimaginar el trabajo en equipo con IA: Primeros pasos

Microsoft 365 Copilot va más allá de la productividad personal para permitir que los equipos trabajen juntos con IA, para crear estrategias, reducir la falta de comunicación y acelerar el progreso. Estos nuevos agentes de colaboración ya están disponibles para todos los usuarios de Microsoft 365 Copilot en versión preliminar pública, y Facilitador para reuniones de Teams ya está disponible con carácter general. Dado que estas experiencias se basan en los mismos estándares de seguridad, cumplimiento y privacidad que sustentan Microsoft 365, las organizaciones pueden adoptarlas con confianza.

Para comenzar, pidan ayuda a cualquiera de estos agentes dondequiera que trabajen. Aquí hay algunas formas de colaborar con IA:

  • Utilicen Facilitador para su próxima reunión de equipo para generar una agenda, capturar decisiones, asignar seguimientos en automático y probar la presión de los puntos principales planteados durante la reunión.
  • Pidan al agente de uno de sus canales de Teams que redacte un informe de estado de la semana pasada, basado en las conversaciones del canal y en las reuniones en las que participaron.
  • Habiliten un agente en su comunidad de Viva Engage más ocupada y comparen las respuestas proporcionadas por el agente de su comunidad con su respuesta.
  • Pidan al Knowledge Agent que etiquete y organice todos los archivos relevantes para un proyecto en el que trabajen, luego creen un resumen del proyecto que pueda compartir con las partes interesadas.

Desbloquear la colaboración de IA con Microsoft

Obtengan más información sobre Microsoft 365 Copilot y exploren los recursos siguientes para obtener más información sobre las funcionalidades de IA colaborativa descritas arriba:

The post Microsoft 365 Copilot: Habilitación de equipos de agentes humanos appeared first on Source LATAM.

 

​The post Microsoft 365 Copilot: Habilitación de equipos de agentes humanos appeared first on Source LATAM.  

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Second-generation AWS Outposts racks now supported in the AWS Canada (Central) and US West (N. California) Regions

Second-generation AWS Outposts racks are now supported in the AWS Canada (Central) and US West (N. California) Regions. Outposts racks extend AWS infrastructure, AWS services, APIs, and tools to virtually any on-premises data center or colocation space for a truly consistent hybrid experience.

Organizations from startups to enterprises and the public sector in and outside of Canada and the US can now order their Outposts racks connected to these two new supported Regions, optimizing for their latency and data residency needs. Outposts allows customers to run workloads that need low-latency access to on-premises systems locally while connecting back to their home Region for application management. Customers can also use Outposts and AWS services to manage and process data that needs to remain on-premises to meet data residency requirements. This regional expansion provides additional flexibility in the AWS Regions that customers’ Outposts can connect to.

To learn more about second-generation Outposts racks, read this blog post and user guide. For the most updated list of countries and territories and the AWS Regions where second-generation Outposts racks are supported, check out the Outposts racks FAQs page.

 

​Second-generation AWS Outposts racks are now supported in the AWS Canada (Central) and US West (N. California) Regions. Outposts racks extend AWS infrastructure, AWS services, APIs, and tools to virtually any on-premises data center or colocation space for a truly consistent hybrid experience.
Organizations from startups to enterprises and the public sector in and outside of Canada and the US can now order their Outposts racks connected to these two new supported Regions, optimizing for their latency and data residency needs. Outposts allows customers to run workloads that need low-latency access to on-premises systems locally while connecting back to their home Region for application management. Customers can also use Outposts and AWS services to manage and process data that needs to remain on-premises to meet data residency requirements. This regional expansion provides additional flexibility in the AWS Regions that customers’ Outposts can connect to.
To learn more about second-generation Outposts racks, read this blog post and user guide. For the most updated list of countries and territories and the AWS Regions where second-generation Outposts racks are supported, check out the Outposts racks FAQs page.  

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Amazon Lex provides enhanced confirmation and currency built-in slots to 10 additional languages

Amazon Lex now provides support for confirmation and currency slot types in 10 additional languages: Portuguese, Catalan, French, Italian, German, Spanish, Mandarin, Cantonese, Japanese, and Korean. Built-in slots help you build more natural and efficient conversations by understanding synonyms of what you user says and resolving those inputs to a standard format. The confirmation slot helps understand various expressions of user acknowledgement and converts them into ‘Yes’, ‘No’, “Don’t know’‘, or ‘Maybe’. The currency slot helps identify currency and represents the input in a structured way. For example, when a user says “nope” or “absolutely not”, the confirmation slot resolves to ‘No’ or when the user says “1 dollar’, the currency slot resolves it to ”USD 1.00“. These built-in slots help you build more natural and efficient conversational experiences.

This feature is available in all commercial AWS Regions where Amazon Lex operates. To learn more about these features, visit Amazon Lex documentation or to learn how Amazon Connect and Amazon Lex deliver cloud-based conversational AI experiences for contact centers, please visit the Amazon Connect website.

 

​Amazon Lex now provides support for confirmation and currency slot types in 10 additional languages: Portuguese, Catalan, French, Italian, German, Spanish, Mandarin, Cantonese, Japanese, and Korean. Built-in slots help you build more natural and efficient conversations by understanding synonyms of what you user says and resolving those inputs to a standard format. The confirmation slot helps understand various expressions of user acknowledgement and converts them into ‘Yes’, ‘No’, “Don’t know’‘, or ‘Maybe’. The currency slot helps identify currency and represents the input in a structured way. For example, when a user says “nope” or “absolutely not”, the confirmation slot resolves to ‘No’ or when the user says “1 dollar’, the currency slot resolves it to ”USD 1.00“. These built-in slots help you build more natural and efficient conversational experiences. This feature is available in all commercial AWS Regions where Amazon Lex operates. To learn more about these features, visit Amazon Lex documentation or to learn how Amazon Connect and Amazon Lex deliver cloud-based conversational AI experiences for contact centers, please visit the Amazon Connect website.