IonQ is to buy Oxford Ionics, the quantum chip  developer, for $1.08 billion. The price is made up of around $1.07 billion in shares and $10 million in cash. The …

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Qualcomm has bought Alphawave for $2.4 billion in cash. The price is nearly double Alphawave’s market cap before Qualcomm was known to be interested in buying the company. Softbank and …

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Amazon SageMaker now offers an upgrade experience that enables customers to transition from SageMaker Studio to SageMaker Unified Studio while preserving their existing resources and maintaining consistent access controls. This new capability allows customers to import their SageMaker AI domains, user profiles, and spaces into SageMaker Unified Studio without redeploying infrastructure. The upgrade tool ensures that identity, authentication, and authorization experiences remain consistent, with users retaining access to only the resources they were previously permitted to use.

With this upgrade experience, customers can continue to access their resources from both SageMaker Studio and SageMaker Unified Studio during the transition period, allowing teams to gradually adapt to the new experience. The tool preserves access to existing JupyterLab and CodeEditor spaces, as well as other SageMaker AI resources like training jobs, ML pipelines, models, inference endpoints etc, previously created from SageMaker Studio. Administrators maintain control over the upgrade process and can disable access to SageMaker Studio once users are comfortable with the SageMaker Unified Studio experience. The upgrade tool is available as an open-source solution that provides a guided, step-by-step process to ensure a smooth transition to SageMaker Unified Studio.

The upgrade experience is available in all AWS Commercial Regions where the next generation of Amazon SageMaker is available. See the supported regions list for more details. To learn more about upgrading from SageMaker Studio to SageMaker Unified Studio, visit the GitHub repository , and to learn more about the next generation of Amazon SageMaker, visit the product detail page .
 

Customers can now create file systems using Amazon Elastic File System (Amazon EFS) in the AWS Asia Pacific (Taipei) Region.

Amazon EFS is designed to provide serverless, fully elastic file storage that lets you share file data without provisioning or managing storage capacity and performance. It is built to scale on demand to petabytes without disrupting applications, growing and shrinking automatically as you add and remove files. Because Amazon EFS has a simple web services interface, you can create and configure file systems quickly and easily. The service is designed to manage file storage infrastructure for you, meaning that you can avoid the complexity of deploying, patching, and maintaining complex file system configurations.

For more information, visit the Amazon EFS product page, and see the AWS Region Table for complete regional availability information.
 

Amazon Connect now allows you to track durations of holds initiated by individual agents in multiparty calling scenarios through the new Agent Initiated Hold Duration field on the contact record. This new field allows contact center managers to gain insights into hold patterns at the individual agent level during customer interactions. This also provides other benefits including better agent performance management, allowing managers to identify areas for improvement in call handling. Additionally, it helps in optimizing your customers’ experience by providing insights into hold patterns and durations across different agents and scenarios. This level of granularity in data can lead to more informed decision-making in workforce management and training initiatives.

To learn more refer to our public documentation . This new feature is available in all AWS regions where Amazon Connect is available. To learn more about Amazon Connect, the AWS cloud-based contact center, please visit the Amazon Connect website .
 

Amazon OpenSearch Ingestion now allows you ingest data from Atlassian Jira and Confluence and seamlessly index it in Amazon OpenSearch managed clusters and serverless collections. With this integration, you can now create a unified searchable knowledge base of all your data in Atlassian Jira and Confluence to power your RAG applications.

This integration allows data ingestion with flexible filtering options for projects and types in Jira and spaces and pages in Confluence ensuring that only the information you need is imported. Updates to your data in Jira and Confluence is continuously monitored and automatically synchronized with indices in Amazon OpenSearch Service. To ensure secure and reliable connectivity, multiple authentication methods, including basic API key authentication and OAuth2 authentication, with the added security of managing credentials using a secret stored in AWS Secrets Manager are supported.

This feature is available in all the 16 AWS commercial regions where Amazon OpenSearch Ingestion is currently available: US East (Ohio), US East (N. Virginia), US West (Oregon), US West (N. California), Europe (Ireland), Europe (London), Europe (Frankfurt), Europe (Spain), Asia Pacific (Tokyo), Asia Pacific (Sydney), Asia Pacific (Singapore), Asia Pacific (Mumbai), Asia Pacific (Seoul), Canada (Central), South America (Sao Paulo), and Europe (Stockholm).

To get started, you can start ingesting data from Atlassian Jira and Confluence using the AWS Management Console, AWS SDK, or CLI. To learn more about this feature, see the Amazon OpenSearch Service Developer Guide .

AWS Key Management Service (KMS) is announcing support for on-demand rotation of symmetric encryption KMS keys with imported key material. This new capability enables you to rotate the cryptographic key material of Bring Your Own Keys (BYOK) keys without changing the key identifier (key ARN). Rotating keys helps you meet compliance requirements and security best practices that mandate periodic key rotation.

Organizations can now better align key rotation with their internal security policies when using imported keys within AWS KMS. This new on-demand rotation capability supports both immediate rotation as well as scheduled rotation. Similar to flexible rotation for standard KMS keys, this new rotation capability offers seamless transition to new key material within an existing KMS key ARN and key alias, with zero downtime and complete backwards compatibility with existing data protected under this key.

On-demand key rotation is available in all AWS Regions, including the AWS GovCloud (US) Regions and in the China Regions. To learn more, see the AWS Security Blog for how to use on demand rotation with imported keys , and the rotate on-demand topic in the AWS KMS developer guide.
 

Today, we are announcing the availability of AWS Backup in the Asia Pacific (Taipei) Region. AWS Backup is a fully-managed, policy-driven service that allows you to centrally automate data protection across multiple AWS services spanning compute, storage, and databases. Using AWS Backup, you can centrally create and manage backups of your application data, protect your data from inadvertent or malicious actions with immutable recovery points and vaults, and restore your data in the event of a data loss incident.

You can get started with AWS Backup using the AWS Backup console , SDKs, or CLI by creating a data protection policy and then assigning AWS resources to it using tags or Resource IDs. For more information on the features available in the Asia Pacific (Taipei) Region, visit the AWS Backup product page and documentation . To learn about the Regional availability of AWS Backup, see the AWS Regional Services List .

Today, Amazon SageMaker AI announces the general availability of Amazon EC2 P6-B200 instances in Training Jobs, powered by NVIDIA B200 GPUs. Amazon EC2 P6-B200 instances offer up to 2x performance compared to P5en instances for AI training.

P6-B200 instances feature 8 Blackwell GPUs with 1440 GB of high-bandwidth GPU memory and a 60% increase in GPU memory bandwidth compared to P5en, 5th Generation Intel Xeon processors (Emerald Rapids), and up to 3.2 terabits per second of Elastic Fabric Adapter (EFAv4) networking. P6-B200 instances are powered by the AWS Nitro System, so you can reliably and securely scale AI workloads within Amazon EC2 UltraClusters to tens of thousands of GPUs.

The instances are available through SageMaker HyperPod Flexible Training Plans in US West (Oregon) AWS Region. For on-demand reservation of B200 instances, please reach out to your account manager.

Amazon SageMaker Model Training lets you easily train machine learning models at scale using fully managed infrastructure optimized for performance and cost. To get started with Training Jobs, visit SageMaker Model Training .

16 years ago, Steve Cutler, Intel’s technical marketing manager, cane up with these ten predictions for the technology industry: Prediction One – new classes of portable devices with ten times …

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