Google Cloud just dropped a new resource packed with 101 architectural blueprints designed to help developers and business leaders move from inspiration to implementation. Each blueprint outlines a real-world generative AI use case—like document automation, sales forecasting, fraud prevention, patient outcome improvement—paired with a complete tech stack built on Google Cloud services. The use cases span industries from retail to healthcare, finance, manufacturing, media, and more. Whether you're looking to unify online and in-store retail, power AI-driven product search, automate content generation, or streamline clinical workflows, this guide gives you a ready-made foundation to start building. https://cloud.google.com/blog/products/ai-machine-learning/real-world-gen-ai-use-cases-with-technical-blueprints?utm_source=chatgpt.com

Google recently published a hands-on guide to creating a low‑latency, bi‑directional, real‑time voice agent using its Gemini model and the Agent Development Kit (ADK). Here’s the core breakdown: - Start with a basic conversational agent — one with persona and trained knowledge, but no external tool access. - Make it more capable by integrating tools like Google Search and the Maps MCP Toolset, giving your agent real‑world data and dynamic capabilities. - Use RunConfig with bi-directional streaming (BIDI) to configure seamless voice input/output and allow interruptions — for natural, conversational feel. - Manage concurrency with Python's asyncio and TaskGroup, enabling your system to listen, think, and speak simultaneously. - Encode audio responses in Base64 for smooth transmission, and stream text transcripts in real-time to support rich interaction. Everything you need is in the blog—code samples, configuration tips, and architectural insights to help you get started faster and smoother. https://cloud.google.com/blog/products/ai-machine-learning/build-a-real-time-voice-agent-with-gemini-adk?utm_source=chatgpt.com