TensorFlow Lite: Solution for running ML on-device

Pete Warden (Google), Nupur Garg (Google), Matthew DuPuy (Arm)

11:50am–12:30pm Thursday, October 31, 2019

Location: Great American Ballroom J/K

Core technologies

Average rating:

(4.00, 2 ratings)

Who is this presentation for?

Mobile app developers and hardware and software makers

Level

New to TensorFlow

Description

Pete Warden, Nupur Garg, and Matthew Dupuy take you through TensorFlow Lite, TensorFlow’s lightweight cross-platform solution for mobile and embedded devices. It enables on-device machine learning inference with low latency, high performance, and a small binary size. It’s the standard solution at Google and the primary inference framework for all on-device use cases.

Prerequisite knowledge

Familiarity with ML

What you'll learn

Learn how TensorFlow Lite tools work and how to convert and optimize models for mobile and embedded devices

Pete Warden

Google

Pete Warden is the technical lead of the mobile and embedded TensorFlow Group on Google’s Brain team.

Nupur Garg

Google

Nupur Garg is a software engineer on the TensorFlow Lite team at Google Brain. She holds an MS in computer science from Cal Poly in San Luis Obispo.

Matthew DuPuy

Arm

Matthew Du Puy has been a software engineer at Arm for 8 years and is currently working on AI at the edge and IoT technology. Previously he worked on Android, open-source math libraries and the Linux Kernel. He is also the second American to have climbed Annapurna, K2, and Everest.