“Autonomy” by Lawrence Burns

I just finished listening to Autonomy by Lawrence Burns, a former VP of R&D at General Motors and a (former?) strategy consultant for Waymo. The focus of the book is the history of self-driving car R&D and the potential future impact on society. I’m disappointed that there isn’t more in the book about the actual technology.

Topics that are emphasized and repeatedly discussed in the book:

  • HD maps
  • lidar

Topics that are not discussed in the book:

  • neural networks
  • computer vision
  • machine learning, deep learning, reinforcement learning, imitation learning

This book was published in 2018.

At one point, the author seems to misdescribe Mobileye’s computer vision technology as comparing objects on the road to a large library of images. This sounds like a garbled description of a neural network.* Later, there is a brief mention of HW1 Autopilot — using Mobileye’s EyeQ chip — being taught to recognize vehicles, but it isn’t explained beyond that.

*Edit: The Mobileye chip could conceivably have used an outdated technology called a support-vector machine (SVM), sometimes referred to as a “shallow neural network”, instead of a deep neural network, so Burns’ description might be accurate. But, still, if this book were all you had to go on, you would not be aware of the existence of deep neural networks.

The basic concept of a deep neural network or deep learning is not explained in the book. It only goes as far as to describe the “software” or “code” or “programming” of the vehicles, giving the impression that everything in a self-driving car is just conventional, hand-coded software. That hand-coded software is also only discussed in hazy, general terms.

The way I see it, autonomous cars would not be possible without deep neural networks (at a minimum for perception), yet from reading the book you wouldn’t even know they exist. You would think autonomous cars are just a matter of HD maps, lidar, and hand coding.

If you want to learn about the internal politics at Waymo, or hear stories from the DARPA Grand Challenge, then you might like this book. If you want to learn about the technology, I would recommend Lex Fridman’s free MIT course instead.

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