Mobile AI revolution is increasingly moving on-device, driven by demands for privacy, low latency, and offline capability. In this session, I’ll demonstrate how to leverage cutting-edge on-device AI tools including Gemini Nano, Google Edge AI SDK, and MediaPipe LLM Inference APIs to build intelligent Android apps entirely on-device.

Key Takeaways:

* On-Device AI Landscape - Understand the shift from cloud to on-device AI, the privacy benefits, and real-world use cases for features like smart reply, summarisation, image analysis, and more.

* Getting Started with Gemini Nano - Walk through integrating Google’s Gemini Nano generative model into a modern Android app, highlighting both ML Kit Gen-AI APIs and the experimental AI Edge SDK for custom scenarios.

* Beyond Gemini - MediaPipe, LiteRT, and Custom Models: Explore the MediaPipe ecosystem for LLM (large language model) inference on-device, and how to bring your own models using LiteRT/TensorFlow Lite for specialised tasks.

* Production Considerations - Address model size, device compatibility, privacy, and performance optimisation lessons learned from deploying AI features at scale in consumer and enterprise Android apps.

Session to be presented on Droidcon Uganda 2025 on 10th November.