On-device intelligence: Optimized performance and quality using Android ML Kit APIs

From the creator

In this session, we'll explore different GenAI use cases using ML Kit APIs to understand when on-device GenAI is ideal for an app and also understand how to evaluate existing GenAI use cases to see if on-device models can satisfy their quality bar. Resources: Android ML Kit overview → https://goo.gle/4kd3hM1 Android AICore Developer preview → https://goo.gle/4izxio1 Android AI Edge gallery → https://goo.gle/4smvtOK Android ML Kit samples → https://goo.gle/4sDJS9z Jetpacker samples → https://goo.gle/4iBaynK Speakers: David Chou Chapters: 0:00 - Introduction to on-device AI 4:32 - Optimizing Gemini nano performance and benchmarks 8:27 - Overview of new Gemini API capabilities 10:00 - End-to-end scam detection walkthrough 13:40 - Triaging inputs using prompt API and function calling 16:17 - Retrieving order data with embeddings and appsearch 18:58 - Comparing order details and defining audit verdicts 23:00 - Recap and closing remarks Watch the intelligent apps sessions from Android Dev Summit 2026 → https://goo.gle/ADS26-Intelligent-Apps Watch all the sessions from Android Dev Summit 2026 → https://goo.gle/ADS26-All-Sessions Subscribe to Android Developers → https://goo.gle/AndroidDevs #AndroidDevSummit2026 Event: Android Dev Summit 2026 Products Mentioned: ML Kit, ML Kit GenAI, Android Performance

Published 2026-10-29 · Watch on YouTube ↗
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