Fragments 2017

Today we stand on the cusp of witnessing AI take over several aspects of our life. Google struck a chord when it announced at I/O that it was marking a shift from Mobile-first to AI-first. TensorFlow Lite allows for in device machine learning, without having to hit a remote server over the Internet each time. In this crisp talk, I will be speaking about the convergence of mobile and AI, and how TensorFlow Lite can be leveraged for the same.

Outline

Draft Outline:

1. The convergence of Mobile and AI
   • Touch upon AI - past, present and future.
   • Why mix up Mobile and AI
2. A little Background
   • A high-level overview of what neural networks are; what deep learning is.
   • How traditional machine learning with mobile works (Remote servers, hit an API)
3. What is TensorFlow
   • What, why, how.
4. What is TensorFlow Lite
   • How does it work behind the scenes.
   • Deep learning is compute intensive. How does Tensorflow Lite target mobile phones?
   • Packaging model within the app; the different ways of packaging app and model.
5. Getting Started with TensorFlow Lite
   • Requirements
   • Configuration
6. Applications and Scope of TensorFlow Lite
   • Look at some current applications
   • What Tensorflow Lite can help you achieve

Speaker bio

I am Supriya Srivatsa; I recently graduated from Amrita Vishwa Vidyapeetham and currently work at Xome as a software engineer - mobile. I love exploring and tinkering with new technology and have been deeply immersed in android app development lately. I have a keen interest in machine learning and also love participating in hackathons, breathing life into ideas to create a tangible product.

Links

• https://www.linkedin.com/in/supriya-srivatsa