Amazon OpenSearch Service now supports latest generation x86 based high performance Storage Optimized i7i instances. Powered by 5th generation Intel Xeon Scalable processors, I7i instances deliver up to 23% better compute performance and more than 10% better price performance over previous generation I4i instances.
I7i instances have 3rd generation AWS Nitro SSDs with up to 50% better real-time storage performance, up to 50% lower storage I/O latency, and up to 60% lower storage I/O latency variability compared to I4i 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.
Amazon OpenSearch Service supports i7i instances in following AWS Regions US East (N. Virginia, Ohio), US West (N. California, Oregon), Canada (Central), Canada West (Calgary), Europe (Frankfurt, Ireland, London, Milan, Spain, Stockholm, Zurich ), Africa (Cape Town), Asia Pacific (Hong Kong, Hyderabad, Jakarta, Malaysia, Melbourne, Mumbai, Osaka, Seoul, Singapore, Sydney, Tokyo), Middle East (UAE), South America (São Paulo) & AWS GovCloud (US-West).
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 latest generation x86 based high performance Storage Optimized i7i instances. Powered by 5th generation Intel Xeon Scalable processors, I7i instances deliver up to 23% better compute performance and more than 10% better price performance over previous generation I4i instances. I7i instances have 3rd generation AWS Nitro SSDs with up to 50% better real-time storage performance, up to 50% lower storage I/O latency, and up to 60% lower storage I/O latency variability compared to I4i 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. Amazon OpenSearch Service supports i7i instances in following AWS Regions US East (N. Virginia, Ohio), US West (N. California, Oregon), Canada (Central), Canada West (Calgary), Europe (Frankfurt, Ireland, London, Milan, Spain, Stockholm, Zurich ), Africa (Cape Town), Asia Pacific (Hong Kong, Hyderabad, Jakarta, Malaysia, Melbourne, Mumbai, Osaka, Seoul, Singapore, Sydney, Tokyo), Middle East (UAE), South America (São Paulo) & AWS GovCloud (US-West). 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 expands support for the latest generation Graviton4-based Amazon EC2 instance families. These new instance types are compute optimized (c8g), general purpose (m8g), and memory optimized (r8g, r8gd) instances.
AWS Graviton4 processors provide up to 30% better performance than AWS Graviton3 processors with c8g, m8g and r8g & r8gd offering the best price performance for compute-intensive, general purpose, and memory-intensive workloads respectively. To learn more about Graviton4 improvements, please see the blog on r8g instances and the blog on c8g & m8g instances.
Amazon OpenSearch Service Graviton4 instances are supported for all OpenSearch versions, and Elasticsearch (open source) versions 7.9 and 7.10.
Apart from the regions already supported, one or more than one Graviton4 instance types are now also available in following region: Asia Pacific (Hong Kong), Asia Pacific (Hyderabad), Asia Pacific (Jakarta), Asia Pacific (Melbourne), Asia Pacific (Osaka), Asia Pacific (Thailand), Europe (Milan), Europe (Paris), Europe (Zurich), Middle East (UAE), AWS GovCloud (US-West) and AWS GovCloud (US-East).
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 expands support for the latest generation Graviton4-based Amazon EC2 instance families. These new instance types are compute optimized (c8g), general purpose (m8g), and memory optimized (r8g, r8gd) instances. AWS Graviton4 processors provide up to 30% better performance than AWS Graviton3 processors with c8g, m8g and r8g & r8gd offering the best price performance for compute-intensive, general purpose, and memory-intensive workloads respectively. To learn more about Graviton4 improvements, please see the blog on r8g instances and the blog on c8g & m8g instances. Amazon OpenSearch Service Graviton4 instances are supported for all OpenSearch versions, and Elasticsearch (open source) versions 7.9 and 7.10. Apart from the regions already supported, one or more than one Graviton4 instance types are now also available in following region: Asia Pacific (Hong Kong), Asia Pacific (Hyderabad), Asia Pacific (Jakarta), Asia Pacific (Melbourne), Asia Pacific (Osaka), Asia Pacific (Thailand), Europe (Milan), Europe (Paris), Europe (Zurich), Middle East (UAE), AWS GovCloud (US-West) and AWS GovCloud (US-East). For region specific availability & pricing, visit our pricing page. To learn more about Amazon OpenSearch Service and its capabilities, visit our product page.
Amazon Connect now supports larger, multi-line text fields on case templates allowing agents to capture detailed free-form notes and structured data directly within cases. These fields expand vertically to accommodate multiple paragraphs, making it easier to document root cause analysis, transaction details, investigation findings, or customer-facing updates.
Amazon Connect Cases is available in the following AWS regions: US East (N. Virginia), US West (Oregon), Canada (Central), Europe (Frankfurt), Europe (London), Asia Pacific (Seoul), Asia Pacific (Singapore), Asia Pacific (Sydney), Asia Pacific (Tokyo), and Africa (Cape Town) AWS regions. To learn more and get started, visit the Amazon Connect Cases webpage and documentation.
Amazon Connect now supports larger, multi-line text fields on case templates allowing agents to capture detailed free-form notes and structured data directly within cases. These fields expand vertically to accommodate multiple paragraphs, making it easier to document root cause analysis, transaction details, investigation findings, or customer-facing updates. Amazon Connect Cases is available in the following AWS regions: US East (N. Virginia), US West (Oregon), Canada (Central), Europe (Frankfurt), Europe (London), Asia Pacific (Seoul), Asia Pacific (Singapore), Asia Pacific (Sydney), Asia Pacific (Tokyo), and Africa (Cape Town) AWS regions. To learn more and get started, visit the Amazon Connect Cases webpage and documentation.
Amazon Bedrock now extends reinforcement fine-tuning (RFT) support to popular open-weight models, including OpenAI GPT-OSS and Qwen models, and introduces OpenAI-compatible fine-tuning APIs. These capabilities make it easier for developers to improve open-weight model accuracy without requiring deep machine learning expertise or large volumes of labeled data. Reinforcement fine-tuning in Amazon Bedrock automates the end-to-end customization workflow, allowing models to learn from feedback on multiple possible responses using a small set of prompts, rather than traditional large training datasets. Reinforcement fine-tuning enables customers to use smaller, faster, and more cost-effective model variants while maintaining high quality.
Organizations often struggle to adapt foundation models to their unique business requirements, forcing tradeoffs between generic models with limited performance and complex, expensive customization pipelines that require specialized infrastructure and expertise. Amazon Bedrock removes this complexity by providing a fully managed, secure reinforcement fine-tuning experience. Customers define reward functions using verifiable rule-based graders or AI-based judges, including built-in templates for both objective tasks such as code generation and math reasoning, and subjective tasks such as instruction following or conversational quality. During training, customers can use AWS Lambda functions for custom grading logic, and access intermediate model checkpoints to evaluate, debug, and select the best-performing model, improving iteration speed and training efficiency. All proprietary data remains within AWS’s secure, governed environment throughout the customization process.
Models supported at this launch are: qwen.qwen3-32b and openai.gpt-oss-20b. After fine-tuning completes, customers can immediately use the resulting fine tuned model for on-demand inference through Amazon Bedrock’s OpenAI-compatible APIs – Responses API and Chat Completions API, without any additional deployment steps. To learn more, see the Amazon Bedrock documentation.
Amazon Bedrock now extends reinforcement fine-tuning (RFT) support to popular open-weight models, including OpenAI GPT-OSS and Qwen models, and introduces OpenAI-compatible fine-tuning APIs. These capabilities make it easier for developers to improve open-weight model accuracy without requiring deep machine learning expertise or large volumes of labeled data. Reinforcement fine-tuning in Amazon Bedrock automates the end-to-end customization workflow, allowing models to learn from feedback on multiple possible responses using a small set of prompts, rather than traditional large training datasets. Reinforcement fine-tuning enables customers to use smaller, faster, and more cost-effective model variants while maintaining high quality. Organizations often struggle to adapt foundation models to their unique business requirements, forcing tradeoffs between generic models with limited performance and complex, expensive customization pipelines that require specialized infrastructure and expertise. Amazon Bedrock removes this complexity by providing a fully managed, secure reinforcement fine-tuning experience. Customers define reward functions using verifiable rule-based graders or AI-based judges, including built-in templates for both objective tasks such as code generation and math reasoning, and subjective tasks such as instruction following or conversational quality. During training, customers can use AWS Lambda functions for custom grading logic, and access intermediate model checkpoints to evaluate, debug, and select the best-performing model, improving iteration speed and training efficiency. All proprietary data remains within AWS’s secure, governed environment throughout the customization process. Models supported at this launch are: qwen.qwen3-32b and openai.gpt-oss-20b. After fine-tuning completes, customers can immediately use the resulting fine tuned model for on-demand inference through Amazon Bedrock’s OpenAI-compatible APIs – Responses API and Chat Completions API, without any additional deployment steps. To learn more, see the Amazon Bedrock documentation.
Amazon Managed Streaming for Apache Kafka (Amazon MSK) now supports dual-stack connectivity (IPv4 and IPv6) for existing MSK Provisioned and MSK Serverless clusters. This capability enables customers to connect to Amazon MSK using both IPv4 and IPv6 protocols, in addition to the existing IPv4-only option. It helps customers modernize applications for IPv6 environments while maintaining IPv4 compatibility, making it easier to meet compliance requirements and prepare for future network architectures.
Amazon MSK is a fully managed service for Apache Kafka that makes it easier for customers to build and run applications that use Apache Kafka as a data store. Previously, MSK Provisioned and Serverless clusters exclusively utilized IPv4 addressing for all connectivity options. With this new capability, customers can now enable dual-stack connectivity (IPv4 and IPv6) on existing MSK clusters using Amazon MSK Console, AWS CLI, SDK, or CloudFormation by modifying the Network Type parameter for a cluster from IPv4 to dual-stack. Upon successful update, MSK provisions IPv6-enabled network interfaces while maintaining existing IPv4 connectivity, ensuring uninterrupted service. To retrieve new IPv6 bootstrap broker strings for MSK Provisioned clusters, customers can use the GetBootstrapBrokers API to obtain the necessary connection information. All MSK Provisioned and Serverless clusters will retain IPv4-only connectivity unless explicitly updated.
Dual-stack connectivity for existing MSK Provisioned and Serverless clusters is now available in all AWS Regions where Amazon MSK is available, at no additional cost. To learn more about Amazon MSK dual-stack support, refer to the Amazon MSK developer guide.
Amazon Managed Streaming for Apache Kafka (Amazon MSK) now supports dual-stack connectivity (IPv4 and IPv6) for existing MSK Provisioned and MSK Serverless clusters. This capability enables customers to connect to Amazon MSK using both IPv4 and IPv6 protocols, in addition to the existing IPv4-only option. It helps customers modernize applications for IPv6 environments while maintaining IPv4 compatibility, making it easier to meet compliance requirements and prepare for future network architectures. Amazon MSK is a fully managed service for Apache Kafka that makes it easier for customers to build and run applications that use Apache Kafka as a data store. Previously, MSK Provisioned and Serverless clusters exclusively utilized IPv4 addressing for all connectivity options. With this new capability, customers can now enable dual-stack connectivity (IPv4 and IPv6) on existing MSK clusters using Amazon MSK Console, AWS CLI, SDK, or CloudFormation by modifying the Network Type parameter for a cluster from IPv4 to dual-stack. Upon successful update, MSK provisions IPv6-enabled network interfaces while maintaining existing IPv4 connectivity, ensuring uninterrupted service. To retrieve new IPv6 bootstrap broker strings for MSK Provisioned clusters, customers can use the GetBootstrapBrokers API to obtain the necessary connection information. All MSK Provisioned and Serverless clusters will retain IPv4-only connectivity unless explicitly updated. Dual-stack connectivity for existing MSK Provisioned and Serverless clusters is now available in all AWS Regions where Amazon MSK is available, at no additional cost. To learn more about Amazon MSK dual-stack support, refer to the Amazon MSK developer guide.
Starting today, the compute-optimized Amazon EC2 C8a instances are available in the Europe (Frankfurt) and Europe (Ireland) regions. C8a instances are powered by 5th Gen AMD EPYC processors (formerly code named Turin) with a maximum frequency of 4.5 GHz, delivering up to 30% higher performance and up to 19% better price-performance compared to C7a instances.
C8a instances deliver 33% more memory bandwidth compared to C7a instances, making these instances ideal for latency sensitive workloads. Compared to Amazon EC2 C7a instances, they are up to 57% faster for GroovyJVM allowing better response times for Java-based applications. C8a instances offer 12 sizes including 2 bare metal sizes. This range of instance sizes allows customers to precisely match their workload requirements.
C8a instances are built on AWS Nitro System and are ideal for high performance, compute-intensive workloads such as batch processing, distributed analytics, high performance computing (HPC), ad serving, highly-scalable multiplayer gaming, and video encoding.
To get started, sign in to the AWS Management Console. Customers can purchase these instances via Savings Plans, On-Demand instances, and Spot instances. For more information visit the Amazon EC2 C8a instance page.
Starting today, the compute-optimized Amazon EC2 C8a instances are available in the Europe (Frankfurt) and Europe (Ireland) regions. C8a instances are powered by 5th Gen AMD EPYC processors (formerly code named Turin) with a maximum frequency of 4.5 GHz, delivering up to 30% higher performance and up to 19% better price-performance compared to C7a instances. C8a instances deliver 33% more memory bandwidth compared to C7a instances, making these instances ideal for latency sensitive workloads. Compared to Amazon EC2 C7a instances, they are up to 57% faster for GroovyJVM allowing better response times for Java-based applications. C8a instances offer 12 sizes including 2 bare metal sizes. This range of instance sizes allows customers to precisely match their workload requirements. C8a instances are built on AWS Nitro System and are ideal for high performance, compute-intensive workloads such as batch processing, distributed analytics, high performance computing (HPC), ad serving, highly-scalable multiplayer gaming, and video encoding. To get started, sign in to the AWS Management Console. Customers can purchase these instances via Savings Plans, On-Demand instances, and Spot instances. For more information visit the Amazon EC2 C8a instance page.
Amazon Connect now includes agent time-off requests in draft schedules, making it easier for you to view why an agent was not scheduled on a particular day or part of the day. For example, when generating schedules for next month, you can see that an agent who typically works Monday to Friday wasn’t scheduled for the first week because they’re on leave without needing to check the published schedules or troubleshooting configuration as to why agent was not scheduled. This launch helps schedulers quickly identify coverage gaps and adjust schedules before publishing them to agents.
This feature is available in all AWS Regions where Amazon Connect agent scheduling is available. To learn more about Amazon Connect agent scheduling, click here.
Amazon Connect now includes agent time-off requests in draft schedules, making it easier for you to view why an agent was not scheduled on a particular day or part of the day. For example, when generating schedules for next month, you can see that an agent who typically works Monday to Friday wasn’t scheduled for the first week because they’re on leave without needing to check the published schedules or troubleshooting configuration as to why agent was not scheduled. This launch helps schedulers quickly identify coverage gaps and adjust schedules before publishing them to agents. This feature is available in all AWS Regions where Amazon Connect agent scheduling is available. To learn more about Amazon Connect agent scheduling, click here.
Starting today, Amazon Bedrock supports Claude Sonnet 4.6, which offers frontier performance across coding, agents, and professional work at scale. According to Anthropic, Claude Sonnet 4.6 is their best computer use model yet, allowing organizations to deploy browser-based automation across business tools with near-human reliability. Claude Sonnet 4.6 approaches Opus 4.6 intelligence at a lower cost. It enables faster, high-quality task completion, making it ideal for high-volume coding and knowledge work use cases.
Claude Sonnet 4.6 serves as a direct upgrade to Sonnet 4.5 across use cases that require consistent conversational quality and efficient multi-step orchestration. For search and chat applications, it delivers reliable performance across single and multi-turn exchanges at a price point that makes high-volume deployment practical, maintaining quality standards while optimizing for scale. Developers can leverage Claude Sonnet 4.6’s for agentic workflows, seamlessly filling both lead agent and subagent roles in multi-model pipelines with precise workflow management and context compaction capabilities. Enterprise teams can use Claude Sonnet 4.6 to power domain-specific applications with professional precision, including spreadsheet and financial model creation that accelerates analysis workflows, compliance review processes that require meticulous attention to detail, and data summarization tasks where iteration speed and accuracy are paramount. Claude Sonnet 4.6 requires only minor prompting adjustments from Sonnet 4.5, ensuring smooth migration for existing implementations.
Claude Sonnet 4.6 is now available in Amazon Bedrock. For the full list of available regions, refer to the documentation. To learn more and get started with Claude Sonnet 4.6 in Amazon Bedrock, read the About Amazon blog and visit the Amazon Bedrock console.
Starting today, Amazon Bedrock supports Claude Sonnet 4.6, which offers frontier performance across coding, agents, and professional work at scale. According to Anthropic, Claude Sonnet 4.6 is their best computer use model yet, allowing organizations to deploy browser-based automation across business tools with near-human reliability. Claude Sonnet 4.6 approaches Opus 4.6 intelligence at a lower cost. It enables faster, high-quality task completion, making it ideal for high-volume coding and knowledge work use cases.
Claude Sonnet 4.6 serves as a direct upgrade to Sonnet 4.5 across use cases that require consistent conversational quality and efficient multi-step orchestration. For search and chat applications, it delivers reliable performance across single and multi-turn exchanges at a price point that makes high-volume deployment practical, maintaining quality standards while optimizing for scale. Developers can leverage Claude Sonnet 4.6’s for agentic workflows, seamlessly filling both lead agent and subagent roles in multi-model pipelines with precise workflow management and context compaction capabilities. Enterprise teams can use Claude Sonnet 4.6 to power domain-specific applications with professional precision, including spreadsheet and financial model creation that accelerates analysis workflows, compliance review processes that require meticulous attention to detail, and data summarization tasks where iteration speed and accuracy are paramount. Claude Sonnet 4.6 requires only minor prompting adjustments from Sonnet 4.5, ensuring smooth migration for existing implementations.
Claude Sonnet 4.6 is now available in Amazon Bedrock. For the full list of available regions, refer to the documentation. To learn more and get started with Claude Sonnet 4.6 in Amazon Bedrock, read the About Amazon blog and visit the Amazon Bedrock console.
Más allá de Davos 2026: 5 prácticas para alinear la transformación de la IA y la sostenibilidad
Por: Melanie Nakagawa, directora de sostenibilidad.
Las conversaciones en la reunión del Foro Económico Mundial en Davos, Suiza, siempre giran en torno a los temas urgentes que abarcan los negocios, la política, el clima y la sociedad. La reunión de este año no fue diferente. La IA ha estado en el centro de estas conversaciones en los últimos años, aunque este año noté un cambio en el tono. Los líderes empiezan a ver la IA no como una tecnología independiente, sino como un catalizador, uno que moldeará su impacto ambiental, su resiliencia operativa y su éxito a largo plazo. La IA ya no es una promesa abstracta; es una palanca práctica que redefine cómo funcionan, escalan y crean valor las organizaciones, para gestionar al mismo tiempo la confianza y la responsabilidad.
En Microsoft, vemos con claridad este cambio en nuestras conversaciones con clientes de todo el mundo. Los líderes avanzan con rapidez para escalar la IA, para mantener al mismo tiempo la responsabilidad de los compromisos de sostenibilidad ante clientes, inversores, reguladores y empleados. Demasiadas veces, estos objetivos se presentan como compensaciones. En la práctica, refuerzan. Cuando la transformación de la IA se aborda con intención y disciplina, puede impulsar un mejor rendimiento empresarial mientras avanza en los resultados de sostenibilidad.
Por qué la transformación de la IA y la sostenibilidad van juntas
El impacto más significativo de la IA no proviene de pilotos aislados, sino de la transformación —cuando la inteligencia está integrada en la estrategia, el modelo operativo y la cultura. Esa es la premisa de la visión de transformación de la IA de Microsoft en Frontera, donde las organizaciones enriquecen la experiencia de los empleados, reinventan la implicación del cliente, reingeniean procesos empresariales centrales y doblan la curva de la innovación.
Lo que a menudo se pasa por alto es que estos mismos cambios generan beneficios en sostenibilidad. Los procesos más eficientes requieren menos energía y menos recursos, mejores datos reducen el desperdicio y la sobreproducción, y las arquitecturas modernas de nube e IA —cuando se diseñan de manera intencionada— pueden reducir la huella digital mientras aumentan la velocidad y la resiliencia.
Cinco prácticas para la transformación sostenible de la IA
Adoptar una estrategia moderna en la nube. Mover las cargas de trabajo a entornos de nube eficientes y a gran escala suele ser el paso más importante que pueden dar las organizaciones para reducir el consumo energético y mejorar el rendimiento. Las plataformas modernas en la nube permiten a las organizaciones escalar la IA de forma inteligente, al optimizar el cálculo, el almacenamiento y la refrigeración de formas difíciles de lograr en las instalaciones.
Evaluar los objetivos de sostenibilidad y confianza de su proveedor de nube. La huella ambiental de una organización se extiende cada vez más, más allá de sus propios muros. La transparencia, los compromisos de energía renovable y las operaciones responsables de los centros de datos importan porque las prácticas de tus socios se convierten en parte de su ecuación de sostenibilidad.
Gestionar los datos de manera responsable para una IA eficiente y precisa. Canales de datos eficientes, una gobernanza sólida y una gestión reflexiva del ciclo de vida hacen mucho más que reducir el riesgo. También reducen el cálculo y almacenamiento innecesarios, lo que ayuda a que los sistemas de IA sean más precisos, escalables y sostenibles.
Optimizar las cargas de trabajo en la nube. A medida que la IA pasa de pilotos a producción, los resultados de sostenibilidad dependen cada vez más de cómo se diseñan y ejecutan las cargas de trabajo en la nube. Ajustar el cálculo, reducir los recursos inactivos y agilizar el movimiento de datos disminuye el consumo energético mientras mejora el rendimiento y el control de costes.
Adaptar el modelo a la misión. Con bases de nube eficientes, los líderes pueden centrarse en seleccionar los modelos de IA adecuados para los trabajos adecuados. Alinear la elección del modelo con los objetivos empresariales, los requisitos de rendimiento y las metas de sostenibilidad permite a las organizaciones escalar la IA de forma responsable, al maximizar el impacto sin necesidad de complejos o recursos innecesarios.
En conjunto, estas prácticas ayudan a los líderes a ir más allá de la aspiración hacia la ejecución—para ofrecer lo que la guía describe como un doble retorno: un mejor rendimiento empresarial junto con un impacto medioambiental reducido.
Lo que muestra la investigación
La IA puede ofrecer mejores resultados—más rápido y de manera más sostenible
En un experimento sencillo destacado en la Guía Estratégica: Alinear la Transformación de la IA con los Objetivos de Sostenibilidad, Microsoft se propuso entender cómo la IA podría realizar de manera eficiente una tarea común de trabajo de conocimiento.
Se pidió a cinco profesionales que resumieran un informe técnico de 3.000 palabras en 200 palabras. Completar la tarea llevó una mediana de 41 minutos y consumió alrededor de 13,7 vatios-hora de energía del portátil.
A través de un solo prompt, Microsoft Copilot completó la misma tarea en menos de un minuto, usando solo 0,29 vatios-hora de energía del centro de datos. Eso es cerca de 55 veces más rápido y 47 veces más eficiente a nivel energético. Los revisores independientes también calificaron el resumen generado por IA por mayor claridad, precisión, completitud y calidad general.
La conclusión es clara: cuando la IA se aplica de forma reflexiva, puede reducir el tiempo, el consumo energético y la fricción, al tiempo que ofrece mejores resultados.
Cómo se ve esto en la práctica
En distintos sectores, las organizaciones ya han comenzado a demostrar cómo la transformación de la IA y la sostenibilidad se refuerzan de manera mutua.
ABB, líder mundial en electrificación y automatización, utiliza la IA para ayudar a que industrias intensivas en energía y activos funcionen de manera más eficiente mientras cumple objetivos de sostenibilidad cada vez más ambiciosos. La plataforma Genix Industrial AI ayuda a los clientes de ABB a lograr un aumento de eficiencia del 25% en los centros de datos hasta un ahorro energético del 18% en la producción de cemento.
En el sector de la construcción, Giatec aborda uno de los materiales con mayor consumo de carbono del mundo: el hormigón. Construido sobre Microsoft Azure, Azure IoT Hub, y Azure OpenAI in Foundry Models, la plataforma inteligente de Giatec optimiza los diseños de mezclas, redujo 2,5 millones de toneladas de emisiones de carbono, y aumentó los márgenes de beneficio para los productores de hormigón hasta en un 100%.
Space Intelligence utiliza IA para convertir grandes cantidades de datos satelitales en conocimientos fiables y accionables para los esfuerzos globales de clima y conservación. La empresa pasó a Microsoft Foundry y al ecosistema Planetary Computer para reducir el tiempo necesario para cartografiar los bosques del mundo en un 75%, para completar la cobertura de más de 50 países en solo un año, algo que habría llevado seis años, lo que retrasa la capacidad de controlar y verificar el impacto climático en el mundo real.
Convertirse en una organización de Frontera, de manera responsable
Estos ejemplos apuntan a una tendencia más amplia: las organizaciones líderes en IA también redefinen cómo es la innovación responsable. Las organizaciones de Frontera no tratan la sostenibilidad como una iniciativa o un ejercicio de informes separado. Lo diseñan en su transformación desde el principio.
Resolver desafíos sistémicos como el cambio climático requiere colaboración, entre cadenas de valor, ecosistemas y sectores. También requiere líderes dispuestos a plantear mejores preguntas sobre cómo se despliega, mide y gobierna la tecnología.
Esta perspectiva se demuestra con el reciente anuncio de Microsoft sobre una infraestructura de IA centrada en la comunidad. A medida que escalamos la IA, tenemos la responsabilidad de considerar no solo lo que estos sistemas pueden hacer, sino también cómo y dónde se construyen. Eso significa invertir en infraestructuras que apoyen a las comunidades locales, prioricen las energías renovables, gestionen el agua de forma responsable y estén diseñadas con la transparencia y la colaboración a largo plazo en mente. Construir IA de manera responsable no solo consiste en reducir riesgos, sino en ganarse la confianza y asegurar que los beneficios de la innovación se compartan de manera amplia, desde el centro de datos hacia el interior.
Usada con reflexión, la IA puede ayudarnos a tomar decisiones más inteligentes, operar de manera más eficiente y desbloquear formas nuevas de crear valor, manteniéndonos dentro de los límites planetarios. Si se usa de forma descuidada, corre el riesgo de acelerar los mismos desafíos que intentamos resolver.
Por eso la claridad importa. Los marcos importan. Y la orientación práctica importa.
Lo que los líderes pueden hacer a continuación
Si son responsables de definir la estrategia de IA, la agenda de sostenibilidad o ambas de su organización, los animo a que exploren la Guía Estratégica: Alinear la transformación de la IA con los objetivos de sostenibilidad. Está diseñada para ayudarlos a superar la complejidad, identificar por dónde empezar y avanzar con estrategias claras y accionables.
En Microsoft, estamos comprometidos a ayudar a nuestros clientes a convertirse en organizaciones Frontera que lideran con innovación, responsabilidad e impacto.
Los retos a los que nos enfrentamos son complejos. Pero con la estrategia adecuada, la tecnología adecuada y un compromiso compartido con el progreso, la IA puede ayudarnos a construir un futuro más sostenible y próspero—para todos.
AWS Glue 5.1 is now available in eighteen additional AWS Regions: Africa (Cape Town), Asia Pacific (Hyderabad, Jakarta, Melbourne, Osaka, Seoul, Taipei), Canada (Calgary, Central), Europe (London, Milan, Paris, Zurich), Israel (Tel Aviv), Mexico (Central), Middle East (Bahrain, UAE), and US West (N. California).
AWS Glue is a serverless, scalable data integration service that simplifies discovering, preparing, moving, and integrating data from multiple sources. AWS Glue 5.1 upgrades core engines to Apache Spark 3.5.6, Python 3.11, and Scala 2.12.18, bringing performance and security enhancements. It also updates support for open table format libraries, including Apache Hudi 1.0.2, Apache Iceberg 1.10.0, and Delta Lake 3.3.2. Additionally, AWS Glue 5.1 introduces support for Apache Iceberg format version 3.0, adding default column values, deletion vectors for merge-on-read tables, multi-argument transforms, and row lineage tracking. This release also extends AWS Lake Formation fine-grained access control to write operations (both DML and DDL) for Spark DataFrames and Spark SQL. Previously, this capability was limited to read operations only. AWS Glue 5.1 also adds full-table access control in Apache Spark for Apache Hudi and Delta Lake tables, providing more comprehensive security options for your data.
With this expansion, AWS Glue 5.1 is now available in thirty-three AWS Regions.
You can get started with AWS Glue 5.1 using AWS Glue APIs, AWS Command Line Interface (CLI), AWS Software Development Kit (SDK), AWS Glue Studio, or Amazon SageMaker Unified Studio. To learn more, visit the AWS Glue product page and our documentation.
AWS Glue 5.1 is now available in eighteen additional AWS Regions: Africa (Cape Town), Asia Pacific (Hyderabad, Jakarta, Melbourne, Osaka, Seoul, Taipei), Canada (Calgary, Central), Europe (London, Milan, Paris, Zurich), Israel (Tel Aviv), Mexico (Central), Middle East (Bahrain, UAE), and US West (N. California).
AWS Glue is a serverless, scalable data integration service that simplifies discovering, preparing, moving, and integrating data from multiple sources. AWS Glue 5.1 upgrades core engines to Apache Spark 3.5.6, Python 3.11, and Scala 2.12.18, bringing performance and security enhancements. It also updates support for open table format libraries, including Apache Hudi 1.0.2, Apache Iceberg 1.10.0, and Delta Lake 3.3.2. Additionally, AWS Glue 5.1 introduces support for Apache Iceberg format version 3.0, adding default column values, deletion vectors for merge-on-read tables, multi-argument transforms, and row lineage tracking. This release also extends AWS Lake Formation fine-grained access control to write operations (both DML and DDL) for Spark DataFrames and Spark SQL. Previously, this capability was limited to read operations only. AWS Glue 5.1 also adds full-table access control in Apache Spark for Apache Hudi and Delta Lake tables, providing more comprehensive security options for your data. With this expansion, AWS Glue 5.1 is now available in thirty-three AWS Regions.
You can get started with AWS Glue 5.1 using AWS Glue APIs, AWS Command Line Interface (CLI), AWS Software Development Kit (SDK), AWS Glue Studio, or Amazon SageMaker Unified Studio. To learn more, visit the AWS Glue product page and our documentation.
