Artificial Intelligence Now

Chapter 12. How to Build a Robot That “Sees” with $100 and TensorFlow

Lukas Biewald

Object recognition is one of the most exciting areas in machine learning right now. Computers have been able to recognize objects like faces or cats reliably for quite a while, but recognizing arbitrary objects within a larger image has been the holy grail of artificial intelligence. Maybe the real surprise is that human brains recognize objects so well. We effortlessly convert photons bouncing off objects at slightly different frequencies into a spectacularly rich set of information about the world around us. Machine learning still struggles with these simple tasks, but in the past few years, it’s gotten much better.

Deep learning and a large public training data set called ImageNet have made an impressive amount of progress toward object recognition. TensorFlow is a well-known framework that makes it very easy to implement deep learning algorithms on a variety of architectures. TensorFlow is especially good at taking advantage of GPUs, which in turn are also very good at running deep learning algorithms.

Building My Robot

I wanted to build a robot that could recognize objects. Years of experience building computer programs and doing test-driven development have turned me into a menace working on physical projects. In the real world, testing your buggy device can burn down your house, or at least fry your motor and force you to wait a couple of days for replacement parts to arrive.

The new third-generation ...