Cloud Computing

The recent explosion of machine learning (ML) applications has created unprecedented demand for power delivery in the data center infrastructure that underpins those applications. Unlike server clusters in the traditional data center, where tens of thousands of workloads coexist with uncorrelated power profiles, large-scale batch-synchronized ML training workloads exhibit substantially different power usage patterns. Under […]

AWS Software Development Kits (SDKs) and Command Line Interfaces (CLIs) are bundled with a default configuration that is carefully designed to optimize availability and reliability. Two such settings are the AWS Security Token Service (STS) endpoint and the default retry strategy. To improve the default posture for AWS customers, we will update these two defaults on

At Google Cloud, we strive to make it easy to deploy AI models onto our infrastructure. In this blog we explore how the Cross-Cloud Network solution supports your AI workloads. Managed and Unmanaged AI options Google Cloud provides both managed (Vertex AI) and do-it-yourself (DIY) approaches for running AI workloads.  Vertex AI: A fully managed

2025 is off to a racing start. From announcing strides in the new Gemini 2.0 model family to retailers accelerating with Cloud AI, we spent January investing in our partner ecosystem, open-source, and ways to make AI more useful. We’ve heard from people everywhere, from developers to CMOs, about the pressure to adapt the latest

We are excited to announce the availability of datasets on Google Cloud Marketplace through BigQuery Analytics Hub, opening up new avenues for organizations to power innovative analytics use cases and procure data for enterprise business needs. As a centralized procurement platform, Google Cloud Marketplace offers access to a wide array of enterprise applications, foundational AI