Today, we’re excited to announce the preview of our new G4 VMs based on NVIDIA RTX PRO 6000 Blackwell Server edition — the first cloud provider to do so. This follows the introduction earlier this year of A4 and A4X VMs powered by NVIDIA Blackwell GPUs, designed for large-scale AI training and serving. At the […]
New G4 VMs with NVIDIA RTX PRO 6000 Blackwell power AI, graphics, gaming and beyond Read More »
At Google Cloud, we’re committed to providing the most streamlined, powerful, and cost-effective production- and enterprise-ready serverless Spark experience. To that end, we’re thrilled to announce a significant evolution for Apache Spark on Google Cloud, with Google Cloud Serverless for Apache Spark. Serverless Spark is now also generally available directly within the BigQuery experience. This
Google Cloud Serverless for Apache Spark: high-performance, unified with BigQuery Read More »
This year, we’ve spent dozens of hours synthesizing hundreds of conversations with CXOs across leading organizations, trying to uncover their biggest thorns when it comes to building Multi-Agent Systems (MAS). These conversations have revealed a clear pattern: MAS is helping enterprises re-think clunky legacy processes, but many CXOs are focused on automating those legacy processes
Lessons from the field: What decision-makers want to know about multi-agentic systems Read More »
Datadog and Google Cloud have long provided customers with powerful capabilities that enable performant, scalable, and differentiated applications in the cloud; in the past two years alone, Datadog’s revenue on Google Cloud Marketplace has more than doubled. As these customers bring Google Cloud’s AI capabilities into their technology stacks, they require observability tools that allow
Ryan and Ben welcome Tulsee Doshi and Logan Kilpatrick from Google’s DeepMind to discuss the advanced capabilities of the new Gemini 2.5, the importance of feedback loops for model improvement and reducing hallucinations, the necessity of great data for advancements, and enhancing developer experience through tool integration.
Better vibes and vibe coding with Gemini 2.5 Read More »
In the dynamic world of beauty retail, staying ahead requires more than just the hottest trends — it demands agility, data-driven insights, and seamless customer experiences. Ulta Beauty, a leader in the beauty and wellness industry, understands this. Building on the success of modernizing its e-commerce platform with Google Kubernetes Engine (GKE), Ulta Beauty partnered
Ulta Beauty redefines beauty retail with BigQuery Read More »
Today, we’re introducing Pub/Sub Single Message Transforms (SMTs) to make it easy to perform simple data transformations right within Pub/Sub itself. This comes at a time when businesses are increasingly reliant on streaming data to derive real-time insights, understand evolving customer trends, and ultimately make critical decisions that impact their bottom line and strategic direction.
Simplify your streaming pipelines with new Pub/Sub Single Message Transforms Read More »
Today, we’re excited to announce the general availability of the memory-optimized machine series: Compute Engine M4, our most performant memory-optimized VM with under 6TB of memory. The M4 family is designed for workloads like SAP HANA, SQL Server, and in-memory analytics that benefit from higher memory-to-core ratio. The M4 is based on Intel’s latest 5th
Unlock 66% better price-performance with new M4 VMs for memory-intensive workloads Read More »
The pace of innovation in open-source AI is breathtaking, with models like Meta’s Llama4 and DeepSeek AI’s DeepSeek. However, deploying and optimizing large, powerful models can be complex and resource-intensive. Developers and machine learning (ML) engineers need reproducible, verified recipes that articulate the steps for trying out the models on available accelerators. Today, we’re excited
Accelerate your gen AI: Deploy Llama4 & DeepSeek on AI Hypercomputer with new recipes Read More »
Looking to fine-tune multimodal AI models for your specific domain but facing infrastructure and implementation challenges? This guide demonstrates how to overcome the multimodal implementation gap using Google Cloud and Axolotl, with a complete hands-on example fine-tuning Gemma 3 on the SIIM-ISIC Melanoma dataset. Learn how to scale from concept to production while addressing the
Building a Production Multimodal Fine-Tuning Pipeline Read More »
