What if your next app could run AI completely offline? Discover the transformative potential of on-device AI, eliminating ongoing costs and cloud dependency while protecting user data. We explore the shift from cloud-based AI to powerful on-device intelligence. Using the latest Gemma models, you'll learn when and why to choose on-device AI, understand its cost and privacy benefits, and get step-by-step guidance on implementation in Flutter apps. Watch real-world demos and anticipate future advancements in this rapidly evolving space. Ready to try it yourself? Links and resources are in the description below. Subscribe and stay tuned for our next episode on building an MCP server. 00:00 Introduction: The Future of Offline AI 00:16 The Privacy Concerns with Cloud AI 01:17 Exploring On-Device AI Solutions 01:23 Building On-Device AI Apps 02:19 Understanding On-Device AI 03:08 Real-World Applications of On-Device AI 04:38 Integrating Gemma 3N into Your Apps 09:01 Setting Up On-Device AI Models 12:07 Performance Considerations 13:33 When to Choose On-Device AI 14:21 Conclusion and Next Steps RESOURCES: - FlutterFlow Gemma 3n Library: - Library Usage Instructions: - flutter_gemma package: #nocode #lowcode #aicopilot #appdevelopment #visualdevelopment #letsbuild #aitools #makers #buildinpublic #vibecoding #NoCodeNoLimits #flutterflow #gemma #gemma3 #ondeviceai