Thomas Ezan

Android Developer Relations @Google

Talk Title

How to use hardware acceleration for Machine Learning inference on Android


Salle Blin




15:15 > 20 min


on Twitter

The rising processing power of Android devices unlocks on-device machine learning capabilities unthinkable a few years ago.

To enable machine learning real-time experiences (augmented reality filters, live speech transcription, etc…) you need to accelerate ML processes. TensorFlow Lite on Android can leverage specialized hardware available on the device (GPU, DSP, NPU, etc…).

In this session we will explain how to use Acceleration delegates and new TensorFlow Lite Android APIs to enable ML hardware acceleration.

#tflite #ML #AI #gpu #performance

Speaker Bio

Thomas Ezan is an Android Engineer. He is currently working in the Android Developer Relations Team at Google. Before joining Google he spent 6 years in Lyft’s Growth team and worked at Pocket and Eventbrite. He is currently based in Seattle, WA.