Mobile, AI and TensorFlow Lite
Submitted by Supriya Srivatsa (@sup95) on Sunday, 2 July 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.
- The convergence of Mobile and AI
- Touch upon AI - past, present and future.
- Why mix up Mobile and AI
- 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)
- What is TensorFlow
- What, why, how.
- 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.
- Getting Started with TensorFlow Lite
- Applications and Scope of TensorFlow Lite
- Look at some current applications
- What Tensorflow Lite can help you achieve
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.