Cloud Computing

Crafting the perfect prompt for generative AI models can be an art in itself. The difference between a useful and a generic AI response can sometimes be a well-crafted prompt. But, getting there often requires time-consuming tweaking, iteration, and a learning curve. That’s why we’re thrilled to announce new updates to the AI-powered prompt writing […]

Welcome to the first Cloud CISO Perspectives for November 2024. Today I’m joined by Andy Wen, Google Cloud’s senior director of product management for Google Workspace, to discuss a new Google survey into the high security costs of legacy tech. As with all Cloud CISO Perspectives, the contents of this newsletter are posted to the

Overview On 2024-11-13, the AWS Command Line Interface (AWS CLI) v2 PKG installer and source distribution bundle will no longer support macOS 10.15 (Catalina), following the macOS support policy for the AWS CLI v2. This means that macOS 10.15’s compatibility with newer AWS CLI v2 versions will not be guaranteed. Migrating to macOS 11 or

Matthijs Gielen, Jay Christiansen Background New solutions, old problems. Artificial intelligence (AI) and large language models (LLMs) are here to signal a new day in the cybersecurity world, but what does that mean for us—the attackers and defenders—and our battle to improve security through all the noise? Data is everywhere. For most organizations, the access

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

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

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