Cloud Computing

Building Generative AI applications has become accessible to everyone, but moving those applications from a prototype to a production-ready system requires one critical step: Evaluation. How do you know if your LLM is safe? How do you ensure your RAG system isn’t hallucinating? How do you test an agent that generates SQL queries on the

To build a production-ready agentic system, where intelligent agents can freely collaborate and act, we need standards and shared protocols for how agents talk to tools and how they talk to each other. In the Agent Production Patterns module in the Production-Ready AI with Google Cloud Learning Path, we focus on interoperability, exploring the standard

We can all agree that the quality of AI-driven answers relies on the consistency of the underlying data. But AI models, while powerful, lack business context out of the box. As more organizations ask questions of their data using natural language, it is increasingly important to unify business measures and dimensions, ensure consistency company-wide. If

Welcome to the first Cloud CISO Perspectives for December 2025. Today, Francis deSouza, COO and president, Security Products, Google Cloud, shares our Cybersecurity Forecast report for the coming year, with additional insights from our Office of the CISO colleagues. As with all Cloud CISO Perspectives, the contents of this newsletter are posted to the Google

Give your AI apps and agents a natural, almost human-like interface, all through a single WebSocket connection.  Today, we announced the general availability of Gemini Live API on Vertex AI, which is powered by the latest Gemini 2.5 Flash Native Audio model. This is more than just a model upgrade; it represents a fundamental move