Cloud Computing

The transformative power of AI and intelligent agents is driving profound changes, where software can understand natural language questions and commands — and even autonomously act on our behalf. At the heart of this revolution is the “AI-ready” enterprise database, an active, intelligent engine that understands the semantics of structured and unstructured data, and uses […]

As an object storage service, Google Cloud Storage is popular for its simplicity and scale, a big part of which is due to the stateless REST protocols that you can use to read and write data. But with the rise of AI and as more customers look to run data-intensive workloads, two major obstacles to

For decades, businesses have wrestled with unlocking the true potential of their data for real-time operations. Bigtable, Google Cloud’s pioneering NoSQL database, has been the engine behind massive-scale, low-latency applications that operate at a global scale. It was purpose-built for the challenges faced in real-time applications, and remains a key piece of Google infrastructure, including

Today at Google Cloud Next ‘25, we’re announcing a major step in making Looker the most powerful platform for data analysis and exploration,by enhancing it with powerful AI capabilities and a new reporting experience, all built on our trusted semantic model — the foundation for accurate, reliable insights in the AI era. Starting today, all

Data is the fuel for AI, and organizations are racing to leverage enterprise data to build AI agents, intelligent search, and AI-powered analytics for productivity, deeper insights, and a competitive edge. To power their data clouds, tens of thousands of organizations already choose BigQuery and its integrated AI capabilities. This decade requires  AI-native, multimodal, and

The high-performance storage stack in AI Hypercomputer incorporates learnings from geographic regions, zones, and GPU/TPU architectures, to create an agile, economical, integrated storage architecture. Recently, we’ve made several innovations to improve accelerator utilization with high-performance storage, helping you to optimize costs, resources, and accelerate your AI workloads: Rapid Storage: A new Cloud Storage zonal bucket

Supporting customers where they want to be is a core value at Google Cloud, and a big part of the reason that we have partnered with Oracle — so that you can innovate faster with the best of Google and the best of Oracle.  This week at Google Cloud Next, we announced significant expansions to

Data is the critical foundation for AI, yet a vast amount of data’s potential remains untapped. Why? Data quality remains a top barrier. To use enterprise data to drive analytics-driven decisions and build differentiated AI, businesses need to be able to find, understand, and trust their data assets. This requires effective data governance encompassing discovery,

At Google Cloud Next, we introduced H4D VMs, our latest machine type for high performance computing (HPC). Building upon existing HPC offerings, H4D VMs are designed to address the evolving needs of demanding workloads in industries such as manufacturing, weather forecasting, EDA, and healthcare and life sciences. H4D VMs are powered by the 5th Generation

When it comes to AI, inference is where today’s generative AI models can solve real-world business problems. Google Kubernetes Engine (GKE) is seeing increasing adoption of gen AI inference. For example, customers like HubX run inference of image-based models to serve over 250k images/day to power gen AI experiences, and Snap runs AI inference on