Cloud Computing

Google Cloud is partnering with leading AI and cybersecurity startups to accelerate their growth and innovation, through the ISV Startup Springboard program, announced today at the Google Cloud Startup Summit.  Over the last year, more than 100 startups have already benefited from this program, innovating on our generative AI platform, collaborating on co-sales opportunities, and […]

Google Cloud constantly innovates and invests significantly in our capabilities to stop cyberattacks such as distributed denial-of-service attacks from taking down websites, apps, and services. It’s an essential part of protecting our customers.  Our Project Shield offering, which uses Google’s Cloud networking and our Global Front End infrastructure to help defend against attacks, including stopping

Controlling runaway spend and minimizing unexpected costs is a priority for every business. Imagine a scenario where faulty development or rogue code results in a usage spike over the weekend, unbeknownst to you. If not caught in time, this kind of usage can result in cost spikes that can exhaust your budgets and put a

In today’s hyper-competitive market, businesses can’t afford to wait weeks or months for critical enterprise data. The ability to gain fast, actionable insights into core business processes like order-to-cash is no longer a luxury, it’s a necessity. Why the urgency? Because visibility empowers enterprises to: Spot sales trends as they emerge: Identify top-performing products, pinpoint

As AI adoption speeds up, one thing is becoming clear: the developer platforms that got you this far won’t get you to the next stage. While yesterday’s platforms were awesome, let’s face it, they weren’t built for today’s AI-infused application development and deployment. And organizations are quickly realizing they need to update their platform strategies

Have you ever wished you could get a foundation model to respond in a particular style, exhibit domain-specific expertise, or excel at a specific task? While foundation models like Gemini demonstrate remarkable capabilities out-of-the-box, there can be a gap between their general knowledge and the nuanced understanding required for specific applications.  Supervised Fine-Tuning (SFT) emerges

Introduction Retrieval Augmented Generation (RAG) is revolutionizing how we build Large Language Model (LLM)-powered applications, but unlike tabular machine learning where XGBoost reigns supreme, there’s no single “go-to” solution for RAG. Developers need efficient ways to experiment with different retrieval techniques and evaluate their performance. This post provides a practical guide to rapidly prototyping and