As AI models increase in sophistication, there’s increasingly large model data needed to serve them. Loading the models and weights along with necessary frameworks to serve them for inference can add seconds or even minutes of scaling delay, impacting both costs and the end-user’s experience.  For example, inference servers such as Triton, Text Generation Inference […]

Managing applications across multiple Kubernetes clusters is complex, especially when those clusters span different environments or even cloud providers. One powerful and secure solution combines Google Kubernetes Engine (GKE) fleets and, Argo CD, a declarative, GitOps continuous delivery tool for Kubernetes. The solution is further enhanced with Connect Gateway and Workload Identity. This blog post […]

Rapidly evolving generative AI models place unprecedented demands on the performance and efficiency of hardware accelerators. Last month, we launched our sixth-generation Tensor Processing Unit (TPU), Trillium, to address the demands of next-generation models. Trillium is purpose-built for performance at scale, from the chip to the system to our Google data center deployments, to power […]

As generative AI evolves, we’re beginning to see the transformative potential it is having across industries and our lives. And as large language models (LLMs) increase in size — current models are reaching hundreds of billions of parameters, and the most advanced ones are approaching 2 trillion — the need for computational power will only […]

Every November, we start sharing forward-looking insights on threats and other cybersecurity topics to help organizations and defenders prepare for the year ahead. The Cybersecurity Forecast 2025 report, available today, plays a big role in helping us accomplish this mission. This year’s report draws on insights directly from Google Cloud’s security leaders, as well as […]