AWS Graviton4-based R8g database instances are now generally available for Amazon Aurora with PostgreSQL compatibility in the AWS Canada (Central), AWS Asia Pacific (Singapore) and AWS Asia Pacific (Seoul) regions. R8g instances offer larger instance sizes, up to 48xlarge and features an 8:1 ratio of memory to vCPU, and the latest DDR5 memory. Graviton4-based instances provide up to a 40% performance improvement and up to 29% price/performance improvement for on-demand pricing over Graviton3-based instances of equivalent sizes on Amazon Aurora PostgreSQL databases, depending on database engine, version, and workload.
AWS Graviton4 processors are the latest generation of custom-designed AWS Graviton processors built on the AWS Nitro System. R8g DB instances are available with new 24xlarge and 48xlarge sizes. With these new sizes, R8g DB instances offer up to 192 vCPU, up to 50Gbps enhanced networking bandwidth, and up to 40Gbps of bandwidth to the Amazon Elastic Block Store (Amazon EBS).
Amazon Aurora is designed for unparalleled high performance and availability at global scale with full PostgreSQL compatibility. It provides built-in security, continuous backups, serverless compute, up to 15 read replicas, automated multi-Region replication, and integrations with other AWS services. To get started with Amazon Aurora, take a look at our getting started page.
AWS Graviton4-based R8g database instances are now generally available for Amazon Aurora with PostgreSQL compatibility in the AWS Canada (Central), AWS Asia Pacific (Singapore) and AWS Asia Pacific (Seoul) regions. R8g instances offer larger instance sizes, up to 48xlarge and features an 8:1 ratio of memory to vCPU, and the latest DDR5 memory. Graviton4-based instances provide up to a 40% performance improvement and up to 29% price/performance improvement for on-demand pricing over Graviton3-based instances of equivalent sizes on Amazon Aurora PostgreSQL databases, depending on database engine, version, and workload. AWS Graviton4 processors are the latest generation of custom-designed AWS Graviton processors built on the AWS Nitro System. R8g DB instances are available with new 24xlarge and 48xlarge sizes. With these new sizes, R8g DB instances offer up to 192 vCPU, up to 50Gbps enhanced networking bandwidth, and up to 40Gbps of bandwidth to the Amazon Elastic Block Store (Amazon EBS). You can launch Graviton4 R8g database instances in the Amazon RDS Management Console or using the AWS CLI. Upgrading a database instance to Graviton4 requires a simple instance type modification. For more details, refer to the Aurora documentation. Amazon Aurora is designed for unparalleled high performance and availability at global scale with full PostgreSQL compatibility. It provides built-in security, continuous backups, serverless compute, up to 15 read replicas, automated multi-Region replication, and integrations with other AWS services. To get started with Amazon Aurora, take a look at our getting started page.
Amazon Connect now supports agent schedule adherence notifications, making it easier for you to proactively identify when agents aren’t adhering to their scheduled activities. You can define rules to automatically send email or text notifications (via EventBridge) to supervisors when agents exceed adherence thresholds. For example, if agent adherence drops below 85% in a trailing 15-minute window, supervisors can receive an email alert. These automated notifications eliminate the need for continuous dashboard monitoring and enable proactive intervention before service levels decline, improving both supervisor productivity and customer satisfaction.
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 supports agent schedule adherence notifications, making it easier for you to proactively identify when agents aren’t adhering to their scheduled activities. You can define rules to automatically send email or text notifications (via EventBridge) to supervisors when agents exceed adherence thresholds. For example, if agent adherence drops below 85% in a trailing 15-minute window, supervisors can receive an email alert. These automated notifications eliminate the need for continuous dashboard monitoring and enable proactive intervention before service levels decline, improving both supervisor productivity and customer satisfaction. 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 supports copy and bulk edit of agent scheduling configuration, making it easier to set up and maintain agent schedules. You can create new scheduling configurations by copying existing ones — for example, copy a weekday shift profile to create a weekend variant, or, copy scheduling configuration (time-zone, weekly working hours, days off, etc.) from an existing agent to multiple new hires. When bulk editing, you can select specific fields to update, such as update time-zone and start date for new hires without changing their weekly working hours. These updates reduce time spent by managers on configuration management, thus improving productivity and operational efficiency.
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 supports copy and bulk edit of agent scheduling configuration, making it easier to set up and maintain agent schedules. You can create new scheduling configurations by copying existing ones — for example, copy a weekday shift profile to create a weekend variant, or, copy scheduling configuration (time-zone, weekly working hours, days off, etc.) from an existing agent to multiple new hires. When bulk editing, you can select specific fields to update, such as update time-zone and start date for new hires without changing their weekly working hours. These updates reduce time spent by managers on configuration management, thus improving productivity and operational efficiency. 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 EBS io2 Block Express volumes are now available in Amazon Web Services China (Beijing) Region, operated by Sinnet and Amazon Web Services China (Ningxia) Region, operated by NWCD.
io2 Block Express leverage the latest generation of EBS storage server architecture designed to deliver consistent sub-millisecond latency and 99.999% durability. With a single io2 Block Express volume, you can achieve 256,000 IOPS, 4GiB/s throughput, and 64TiB storage capacity. You can also attach an io2 Block Express volume to multiple instances in the same Availability Zone, supporting shared storage fencing through NVMe reservations for improved application availability and scalability. With the lowest p99.9 I/O latency among major cloud providers, io2 Block Express is the ideal choice for the most I/O-intensive, mission-critical deployments such as SAP HANA, Oracle, SQL Server, and IBM DB2.
Customers using io1 volumes can upgrade to io2 Block Express without any downtime using the ModifyVolume API to achieve 100x durability, consistent sub-millisecond latency, and significantly higher performance at the same or lower cost than io1. With io2 Block Express, you can drive up to 4x IOPS and 4x throughput at the same storage price as io1, and up to 50% cheaper IOPS cost for volumes over 32,000 IOPS.
io2 Block Express is now available in all the Amazon Web Services regions. You can create and manage io2 Block Express volumes using the Amazon Web Services Management Console, Amazon Command Line Interface (CLI), or Amazon SDKs. For more information on io2 Block Express, see our tech documentation.
Amazon EBS io2 Block Express volumes are now available in Amazon Web Services China (Beijing) Region, operated by Sinnet and Amazon Web Services China (Ningxia) Region, operated by NWCD. io2 Block Express leverage the latest generation of EBS storage server architecture designed to deliver consistent sub-millisecond latency and 99.999% durability. With a single io2 Block Express volume, you can achieve 256,000 IOPS, 4GiB/s throughput, and 64TiB storage capacity. You can also attach an io2 Block Express volume to multiple instances in the same Availability Zone, supporting shared storage fencing through NVMe reservations for improved application availability and scalability. With the lowest p99.9 I/O latency among major cloud providers, io2 Block Express is the ideal choice for the most I/O-intensive, mission-critical deployments such as SAP HANA, Oracle, SQL Server, and IBM DB2. Customers using io1 volumes can upgrade to io2 Block Express without any downtime using the ModifyVolume API to achieve 100x durability, consistent sub-millisecond latency, and significantly higher performance at the same or lower cost than io1. With io2 Block Express, you can drive up to 4x IOPS and 4x throughput at the same storage price as io1, and up to 50% cheaper IOPS cost for volumes over 32,000 IOPS. io2 Block Express is now available in all the Amazon Web Services regions. You can create and manage io2 Block Express volumes using the Amazon Web Services Management Console, Amazon Command Line Interface (CLI), or Amazon SDKs. For more information on io2 Block Express, see our tech documentation.
Amazon Neptune Analytics is now available in the AWS Canada (Central) and Australia (Sydney) Regions. You can now create and manage Neptune Analytics graphs in the AWS Canada (Central) and Australia (Sydney) Regions and run advanced graph analytics and vector similarity search.
Neptune Analytics is a memory-optimized graph database engine for analytics. With Neptune Analytics, you can get insights and find trends by processing large amounts of graph data in seconds. To analyze graph data quickly and easily, Neptune Analytics stores large graph datasets in memory. It supports a library of optimized graph analytic algorithms, low-latency graph queries, and vector search capabilities within graph traversals. Neptune Analytics is an ideal choice for investigatory, exploratory, or data-science workloads that require fast iteration for data, analytical and algorithmic processing, or vector search on graph data. It complements Amazon Neptune Database, a popular managed graph database. To perform intensive analysis, you can load the data from a Neptune Database graph or snapshot into Neptune Analytics. You can also load graph data that’s stored in Amazon S3.
Amazon Neptune Analytics is now available in the AWS Canada (Central) and Australia (Sydney) Regions. You can now create and manage Neptune Analytics graphs in the AWS Canada (Central) and Australia (Sydney) Regions and run advanced graph analytics and vector similarity search. Neptune Analytics is a memory-optimized graph database engine for analytics. With Neptune Analytics, you can get insights and find trends by processing large amounts of graph data in seconds. To analyze graph data quickly and easily, Neptune Analytics stores large graph datasets in memory. It supports a library of optimized graph analytic algorithms, low-latency graph queries, and vector search capabilities within graph traversals. Neptune Analytics is an ideal choice for investigatory, exploratory, or data-science workloads that require fast iteration for data, analytical and algorithmic processing, or vector search on graph data. It complements Amazon Neptune Database, a popular managed graph database. To perform intensive analysis, you can load the data from a Neptune Database graph or snapshot into Neptune Analytics. You can also load graph data that’s stored in Amazon S3. To get started, you can create a new Neptune Analytics graphs using the AWS Management Console, or AWS CLI. For more information on pricing and region availability, refer to the Neptune pricing page and AWS Region Table.
IA en el trabajo: La búsqueda de la verdad sobre la IA para los negocios
Los titulares sobre el futuro del trabajo no están alineados con lo que en realidad necesitan los líderes.
Por Jared Spataro, CMO de IA en el trabajo de Microsoft
Si han leído los titulares recientes, podrían pensar que la IA está a punto de quitarles el trabajo o fracasará de manera espectacular intentándolo. La verdad, como siempre, tiene más matices.
Con frecuencia, el problema es una brecha entre la nueva investigación de IA y cómo la interpretan los medios de comunicación: a veces la investigación es sólida, pero los titulares se equivocan. Otras veces, el estudio en sí está tan lejos de las condiciones del mundo real que nos dice muy poco sobre cómo la IA remodela el trabajo, sin embargo, los titulares tratan los hallazgos como presagios de fatalidad.
Es evidente que existe una desalineación fundamental entre los titulares, y gran parte de la investigación actual, y lo que los líderes y empleados buscan en este momento. Lo que falta para ambos es el cómo. Para los líderes, cómo remodelar una organización para que la IA sea lo primero en ella y, para los empleados, cómo trabajar de manera efectiva en una de estas organizaciones evolucionadas. Necesitan un libro de jugadas para convertir la promesa de la IA en una ventaja competitiva duradera.
El problema con los titulares de IA
El contexto se pierde en la traducción: en julio, mis colegas de Microsoft Research publicaron un estudio que mapeó 200 mil conversaciones de Copilot a actividades laborales. Es una investigación importante, diseñada para mostrar dónde se superponen las habilidades de la IA con las tareas diarias que realizamos en varios roles laborales. ¿Pero los titulares? Los medios de comunicación lo redujeron a «¡Historiadores en riesgo!» y «¿Es segura su carrera?»
Eso no es lo que dijo el estudio. La superposición de tareas no es un reemplazo de tareas. La capacidad de investigar y redactar textos no convierte a la IA en historiadora. Lo que hace a un historiador es la interpretación, el juicio y el contexto, todas habilidades que son muy humanas.
El desafío es separar la señal del ruido cuando se encuentran titulares e investigaciones de IA. Mi equipo usa un filtro simple que llamamos la verificación de la realidad de las 3C, donde hacemos una pausa para considerar el contexto, las comparaciones y las consecuencias.
Aplíquenlo en este caso y la imagen se aclara con rapidez:
Contexto: El estudio fue sobre mapeo de tareas, no sobre pronósticos de trabajo.
Comparaciones: Midió la superposición, no el reemplazo.
Consecuencias: Copilot puede ayudar a investigar y redactar el texto, pero no puede proporcionar la interpretación y el juicio que definen el papel del historiador.
A través de las 3C, los titulares dejan de sonar como predicciones y comienzan a parecerse a lo que en realidad son: señales tempranas.
No se tienen en cuenta las limitaciones de la investigación: en otros casos, los titulares no reconocen las limitaciones de un estudio. Tomemos un estudio reciente de una organización llamada METR: los investigadores realizaron una prueba aleatoria con desarrolladores de código abierto experimentados y descubrieron que la IA los ralentizó en un 19%. Gran titular, pero veamos las 3C. Contexto: Los investigadores presentaron a los desarrolladores experimentados una nueva herramienta de IA. Comparaciones: midieron la productividad del primer uso frente a herramientas desconocidas, no la adopción del flujo de trabajo a largo plazo. Consecuencias: Los desarrolladores fueron más lentos, pero sobre todo porque se adaptaban a nuevas herramientas y dedicaban más tiempo a revisar el trabajo de la IA. Nada de eso significa que la IA no pueda acelerar la productividad una vez que esté integrada por completo. El punto perdido: la transformación lleva tiempo.
La causa y el efecto no son lo que parecen: luego está el informe «GenAI Divide» del Proyecto NANDA del MIT. Los titulares gritaban sobre una «tasa de fracaso del 95%». Ese es un titular llamativo, pero las 3C cuentan una historia diferente. El contexto era una instantánea breve y autoinformada que medía la adopción, no la capacidad. Las comparaciones carecían de una línea de base real, por lo que el número del 95% es direccional en el mejor de los casos, no una verdad para todo el mercado. Y la consecuencia es clara: esta no es evidencia de grado de decisión. Lo que en realidad muestra es que el cuello de botella no es la tecnología, es la adopción y el rediseño del flujo de trabajo.
Apuntar a los puntos de referencia incorrectos
Otro problema es que demasiados estudios de IA se apoyan en puntos de referencia sintéticos, rompecabezas aislados que son fáciles de escalar pero que se parecen poco al trabajo real, y cuando esos resultados de laboratorio se traducen directo en los titulares, la imagen se distorsiona de manera importante. Es por eso que la investigación a la que vale la pena prestar atención no se trata de tasas de fracaso sensacionalistas o acertijos de laboratorio, sino de cómo la IA en realidad cambia la manera en que trabajamos.
Es por eso que me encantan los estudios como The Cybernetic Teammate. En un experimento de campo con Procter & Gamble, Karim Lakhani y su equipo de la Escuela de Negocios de Harvard descubrieron que las personas que usaban IA se desempeñaban a la par con equipos enteros que trabajaban sin ella. Lo que en realidad me emociona es que la IA ayudó a romper los silos. Los profesionales de investigación y desarrollo, que por lo general se inclinan hacia soluciones técnicas, y los profesionales comerciales, que se inclinan hacia ideas comerciales, produjeron soluciones más equilibradas cuando tenían IA en la mezcla. Y no solo eso, sino que las personas informaron sentirse más positivas y comprometidas mientras hacían el trabajo. Estos hallazgos son notables: la IA no solo ayuda con las tareas, sino que cambia la manera en que las personas colaboran. Lakhani a menudo compara la IA con un nuevo medicamento: no lo aprueba después de una sola prueba. Se realizan ensayos, en diferentes condiciones, con diferentes poblaciones, hasta que en verdad se comprenden sus efectos. La IA merece la misma disciplina. Necesita una experimentación estructurada para revelar dónde se acelera, dónde falla y cómo remodela no solo los flujos de trabajo, sino organizaciones enteras.
En resumen
El futuro de la IA en el trabajo no se decidirá por titulares o puntos de referencia. Será moldeado por líderes y empleados que traten a la IA como un compañero de equipo capaz, uno que amplíe el juicio, fortalezca la colaboración y democratice la experiencia. La oportunidad no está en generar exageración, sino en reimaginar cómo se hace el trabajo.
Para obtener más información sobre la IA y el futuro del trabajo, suscríbanse a este boletín.
Today, we are excited to announce that Amazon SageMaker notebook instance supports Amazon Linux 2023. You can now choose Amazon Linux 2023 for your new Amazon SageMaker notebook instance to take advantage of the latest innovations, enhanced security features.
Amazon SageMaker notebook instances are fully managed Jupyter Notebooks with pre-configured development environments for data science and machine learning. Data scientists and developers can use SageMaker Notebooks to interactively explore, visualize and prepare data, and build and deploy machine learning models on SageMaker.
Amazon Linux 2023 (AL2023) is a general-purpose rpm-based Linux distribution and successor to Amazon Linux 2 (AL2). Amazon Linux 2023 simplifies operating system management through its secure, stable, and high-performance runtime environment. This Linux distribution follows a predictable two-year major release cycle with five years of long-term support. The first two years provide standard support with quarterly security patches, bug fixes, and new features, followed by three years of maintenance. Enhanced security features include SELinux support and FIPS 140-3 validation for cryptographic modules.
With this you now have the options to launch a notebook instance with AL2023 or AL2. For more details about this launch and instructions on how to get started with AL2023 notebook instances, please refer to the Amazon Linux 2023 documentation.
Today, we are excited to announce that Amazon SageMaker notebook instance supports Amazon Linux 2023. You can now choose Amazon Linux 2023 for your new Amazon SageMaker notebook instance to take advantage of the latest innovations, enhanced security features. Amazon SageMaker notebook instances are fully managed Jupyter Notebooks with pre-configured development environments for data science and machine learning. Data scientists and developers can use SageMaker Notebooks to interactively explore, visualize and prepare data, and build and deploy machine learning models on SageMaker. Amazon Linux 2023 (AL2023) is a general-purpose rpm-based Linux distribution and successor to Amazon Linux 2 (AL2). Amazon Linux 2023 simplifies operating system management through its secure, stable, and high-performance runtime environment. This Linux distribution follows a predictable two-year major release cycle with five years of long-term support. The first two years provide standard support with quarterly security patches, bug fixes, and new features, followed by three years of maintenance. Enhanced security features include SELinux support and FIPS 140-3 validation for cryptographic modules. With this you now have the options to launch a notebook instance with AL2023 or AL2. For more details about this launch and instructions on how to get started with AL2023 notebook instances, please refer to the Amazon Linux 2023 documentation.
Amazon DynamoDB now offers customers the option to use Internet Protocol version 6 (IPv6) addresses in their Amazon Virtual Private Cloud (VPC) when connecting to DynamoDB tables, streams, and DynamoDB Accelerator (DAX), including with AWS PrivateLink Gateway and Interface endpoints. Customers moving to IPv6 can simplify their network stack and meet compliance requirements by using a network that supports both IPv4 and IPv6.
The continued growth of the internet is exhausting available Internet Protocol version 4 (IPv4) addresses. IPv6 increases the number of available addresses by several orders of magnitude and customers no longer need to manage overlapping address spaces in their VPCs. Customers can standardize their applications on the new version of Internet Protocol by moving to IPv6 with a few clicks in the AWS Management Console.
Support for IPv6 in Amazon DynamoDB is now available in all commercial AWS Regions in the United States and the AWS GovCloud (US) Regions. It will deploy to the remaining global AWS Regions where Amazon DynamoDB is available over the next few weeks.
Amazon DynamoDB now offers customers the option to use Internet Protocol version 6 (IPv6) addresses in their Amazon Virtual Private Cloud (VPC) when connecting to DynamoDB tables, streams, and DynamoDB Accelerator (DAX), including with AWS PrivateLink Gateway and Interface endpoints. Customers moving to IPv6 can simplify their network stack and meet compliance requirements by using a network that supports both IPv4 and IPv6.
The continued growth of the internet is exhausting available Internet Protocol version 4 (IPv4) addresses. IPv6 increases the number of available addresses by several orders of magnitude and customers no longer need to manage overlapping address spaces in their VPCs. Customers can standardize their applications on the new version of Internet Protocol by moving to IPv6 with a few clicks in the AWS Management Console.
Support for IPv6 in Amazon DynamoDB is now available in all commercial AWS Regions in the United States and the AWS GovCloud (US) Regions. It will deploy to the remaining global AWS Regions where Amazon DynamoDB is available over the next few weeks.
To connect to DynamoDB using IPv6 addresses and check regional availability, please see the DynamoDB developer guide and the DynamoDB Accelerator user guide.
Today, AWS announced the expansion of 10 Gbps and 100 Gbps dedicated connections with MACsec encryption capabilities at the existing AWS Direct Connect location in the Netrality KC1 data center near Kansas City, MO. You can now establish private, direct network access to all public AWS Regions (except those in China), AWS GovCloud Regions, and AWS Local Zones from this location.
The Direct Connect service enables you to establish a private, physical network connection between AWS and your data center, office, or colocation environment. These private connections can provide a more consistent network experience than those made over the public internet.
For more information on the over 146 Direct Connect locations worldwide, visit the locations section of the Direct Connect product detail pages. Or, visit our getting started page to learn more about how to purchase and deploy Direct Connect.
Today, AWS announced the expansion of 10 Gbps and 100 Gbps dedicated connections with MACsec encryption capabilities at the existing AWS Direct Connect location in the Netrality KC1 data center near Kansas City, MO. You can now establish private, direct network access to all public AWS Regions (except those in China), AWS GovCloud Regions, and AWS Local Zones from this location. The Direct Connect service enables you to establish a private, physical network connection between AWS and your data center, office, or colocation environment. These private connections can provide a more consistent network experience than those made over the public internet. For more information on the over 146 Direct Connect locations worldwide, visit the locations section of the Direct Connect product detail pages. Or, visit our getting started page to learn more about how to purchase and deploy Direct Connect.
Amazon Web Services (AWS) announces the availability of high performance Storage Optimized Amazon EC2 I7i instances in the AWS Europe (Spain) region. Powered by 5th generation Intel Xeon Scalable processors with an all-core turbo frequency of 3.2 GHz, these new instances deliver up to 23% better compute performance and more than 10% better price performance over previous generation I4i instances. Powered by 3rd generation AWS Nitro SSDs, I7i instances offer up to 45TB of NVMe storage 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.
I7i instances offer the best compute and storage performance for x86-based storage optimized instances in Amazon EC2, ideal for I/O intensive and latency-sensitive workloads that demand very high random IOPS performance with real-time latency to access the small to medium size datasets (multi-TBs). Additionally, torn write prevention feature support up to 16KB block sizes, enabling customers to eliminate database performance bottlenecks.
I7i instances are available in eleven sizes – nine virtual sizes up to 48xlarge and two bare metal sizes – delivering up to 100Gbps of network bandwidth and 60Gbps of Amazon Elastic Block Store (EBS) bandwidth. To learn more, visit the I7i instances page.
Amazon Web Services (AWS) announces the availability of high performance Storage Optimized Amazon EC2 I7i instances in the AWS Europe (Spain) region. Powered by 5th generation Intel Xeon Scalable processors with an all-core turbo frequency of 3.2 GHz, these new instances deliver up to 23% better compute performance and more than 10% better price performance over previous generation I4i instances. Powered by 3rd generation AWS Nitro SSDs, I7i instances offer up to 45TB of NVMe storage 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. I7i instances offer the best compute and storage performance for x86-based storage optimized instances in Amazon EC2, ideal for I/O intensive and latency-sensitive workloads that demand very high random IOPS performance with real-time latency to access the small to medium size datasets (multi-TBs). Additionally, torn write prevention feature support up to 16KB block sizes, enabling customers to eliminate database performance bottlenecks. I7i instances are available in eleven sizes – nine virtual sizes up to 48xlarge and two bare metal sizes – delivering up to 100Gbps of network bandwidth and 60Gbps of Amazon Elastic Block Store (EBS) bandwidth. To learn more, visit the I7i instances page.
