Google Cloud ML Deployment Options: Cloud vs Edge

Exploring AI Agents on Google Cloud’s Vertex AI? Here’s a practical guide to kickstart your journey! It walks you through the basics to deploying production-ready agents. 🔹 Just getting started with AI Agents? Start with Section 1 — it breaks down the core concepts and design principles. 🔹 Ready to roll up your sleeves? Head to Section 2 — create your first agent using the Agent Development Kit (ADK). 🔹 Have an agent up and running? Don’t skip Section 3 — learn safety, scalability, and stability best practices for enterprise-ready agents. Want to go deeper? Comment or DM me and I’ll share “Building Agents 102” — a guide on advanced topics like agent evaluation and practical ways to use Google agent products for solving complex, real-world problems. #GoogleCloud #VertexAI #GenAI #AIagents #ADK #AgenticAI

🚀 Google Cloud: Leading the AI Revolution in 2025 Google Cloud is transforming how enterprises harness AI with its latest innovations. Powered by the Gemini AI suite, Google Cloud now offers agentic AI platforms that automate complex workflows in data engineering, data science, and analytics. The new Gemini Data Agents APIs enable seamless integration of AI into existing apps, while enhanced visual search and conversational analytics redefine accessibility. With distributed multimodal AI models and deep integration across Google Workspace, the platform boosts productivity and innovation at scale. How is Google Cloud powering your AI transformation journey? #BooleanSystems #GoogleCloud #GeminiAI #AgenticAI #DataCloud #AIInnovation #TechTrends2025 www.booleansystems.com

I was asked how I keep AI margins predictable when models run on OpenAI or Anthropic APIs. You don’t — unless you architect for control. Most realize this when inference bills start scaling burn, not revenue. My design rule: Control your core models. Scale with cloud APIs. Local inference → profit protection. Cloud APIs → market expansion. Hybrid routing → sustainable advantage. #AIArchitecture #AIEconomics #GenAI #LLM #MLOps #AITech #AIInfrastructure #DataEngineering #AIStartup

Google launches Gemini Enterprise, competing with Anthropic and OpenAI in workplace AI tools. #Ai #Cloud #Innovation Just follow our page for the latest updates!

Ready to build your AI agents? Get started now with Google Cloud's Startup technical guide: AI agents. This 64-page guide offers an easy, step-by-step process to help you move from idea to production-ready AI, bringing you up to speed on essential concepts. Build reliable agents, and navigate AgentOps for production deployment. Start building now! https://goo.gle/3KjHdiW (I'll be going through this guide myself too - great to see coverage of up-to-date topics like ADK as well as hands-on guidance like prompts in there!)

Seamlessly install and configure Sidian 👉 Download Sidian Beta : https://sidian.dev Ready to revolutionize your coding process? This video is your step-by-step guide to setting up Sidian, the intelligent AI code editor designed to make you a more efficient developer. Sidian supports leading AI providers, including OpenAI, Anthropic, Google, xAI, DeepSeek, Groq, Mistral AI, OpenRouter, Inc, Microsoft Azure,Google Cloud, Ollama, LM Studio, Z.ai, Qwen,LiteLLM (YC W23) and Moonshot AI. It also integrates seamlessly with local models so you can run inference on your own hardware when privacy or latency matters.

Wednesday Watch: Claude Sonnet 4.5 is here ⚡ Big move for teams exploring AI agents and hands-on coding at scale. Why it matters (for adoption): • Built for real-world agents & computer use — Anthropic is positioning 4.5 as its best model yet for long-running, practical work. • Stays productive longer — early customer runs report ~30 hours of autonomous coding, a notable jump from prior gens. • Zero-friction access — now available on AWS Bedrock and Google Vertex AI, so you can pilot on your existing cloud. • Safer defaults — emphasis on reduced misaligned behaviors and stronger alignment out of the box. If you’ve been on the fence with agents, Q4 is your window: start small, tie to business value, and keep humans-in-the-loop. #WednesdayThinking

Are public cloud solutions the key to AI success, or are enterprises missing a crucial piece of the puzzle? Despite the scalability and cost efficiency of platforms like AWS, Microsoft, and Google, a staggering 80% of AI and machine learning workloads still face deployment challenges. The disconnect often lies in the ineffective integration of these tools with existing data ecosystems. To truly unlock AI's potential, businesses must prioritize connecting internal and external data sets, focusing on targeted use cases that bring tangible value. Investing in AI without a clear data strategy can lead to costly failures. #AI #MachineLearning #CloudInfrastructure #DataIntegration #PublicCloud

AI in Practice Session This week I rolled up my sleeves to explore how to run and test AI models locally no cloud, no complex infrastructure, just my own machine. Using Ollama + Postman, I built a small playground where I could chat directly with local models like Llama 2 and see how everything works under the hood. Why this matters: Running AI locally helps you understand the real mechanics behind Large Language Models without API limits, latency, or privacy concerns. Here’s what I tried: 1 Installed Ollama to run models locally 2 Started Llama 2 with a simple terminal command 3 Exposed the model via HTTP using ollama server 4 Sent chat requests through Postman like calling your own mini-API! Substack Link: https://lnkd.in/db_Xj8Pv This setup is perfect for offline testing, prototyping, and learning how AI can integrate with everyday applications. The goal of these “AI in Practice” sessions is to turn AI theory into something you can actually touch, build, and play with. Next up: connecting it to a simple web app and exploring Chat-as-a-Service powered by local AI models. #AI #LLM #Ollama #Postman #PracticalAI #MachineLearning #LocalModels #AIDevelopment #Innovation #HandsOnAI

AI and ML are no longer future tech they’re driving business transformation today. From smarter healthcare to fraud detection in finance, the possibilities are endless. But the real question is: how do you harness AI without getting lost in complexity? That’s where AI/ML Services in Google Cloud Platform (GCP) come in. With tools like Vertex AI, BigQuery ML, AutoML, and pre-trained APIs, Google Cloud makes it easier than ever to build, scale, and deploy intelligent applications. 👉 Dive into our latest blog to explore the full potential of AI/ML Services in Google Cloud Platform (GCP), key benefits, and real-world use cases. 🔗 https://lnkd.in/dXFXwHgB #ArtificialIntelligence #MachineLearning #AI #ML #DeepLearning #GoogleCloud #GCP #CloudComputing #VertexAI #BigQuery #Innovation #FutureOfWork #TechTrends #CloudAI