Amazon’s launching (in preview) a privacy-preserving service that lets AWS customers deploy “lookalike” AI models trained for one-off company-company collaborations. Called Clean Rooms ML ...

“Voice tone analysis uses machine learning (ML) to extract sentiment from a speech ... principal developer advocate at AWS, wrote in a blog post. “Voice tone analysis for live calls are ...

To activate ML-KEM post-quantum TLS when using AWS services such as KMS, ACM, or Secrets Manager, users need to update their client SDKs and enable the feature explicitly.

The AWS Clean Rooms ML is available in preview. This new capability allows users to generate predictive insights using ML models while keeping the consumer data protected. The Clean Rooms ML uses a ...

Kevin DeJong, a software development engineer – Infrastructure as Code at AWS, writes: Stack refactoring in AWS CloudFormation represents a significant advancement in infrastructure management.

Amazon AWS recently launched ML-powered coding companion CodeWhisperer, which provides code recommendations based on developers' comments in natural language and their code in the integrated ...

“Over 100,000 customers across industries – including adidas, New York Stock Exchange, Pfizer, Ryanair, and Toyota – are using AWS AI and ML services ... layer of the stack – from the ...

In an interview with Computer Weekly, Olivier Klein, chief technologist for Asia-Pacific and Japan at AWS, delves into the technology stack the company has built to ease GenAI adoption while ...

At its re:Invent conference, AWS today announced Amazon DataZone, a new data management service that can help enterprises catalog, discover, share and -- most importantly -- govern their data.

The results found most respondents are currently using Microsoft’s Azure Stack, AWS’ Outposts and VMware’s vSphere with vCenter for their private cloud workloads. VMware vSphere is the ...

INFACore is a development and data science framework powered by the Intelligent Data Management Cloud that simplifies the process of composing data pipelines and building and deploying AWS ML models.