Data: How Google's Self-Driving Cars Work

The Trick That Makes Google's Self-Driving Cars Work - The Atlantic
"Google has created a virtual track out of Mountain View. 

The key to Google's success has been that these cars aren't forced to process an entire scene from scratch. Instead, their teams travel and map each road that the car will travel...

They're probably best thought of as ultra-precise digitizations of the physical world, all the way down to tiny details like the position and height of every single curb. A normal digital map would show a road intersection; these maps would have a precision measured in inches...

Google has mapped 2,000 miles of road. The US road network has 4 million miles of road. "It is work," Urmson added, shrugging, "but it is not intimidating work." 

www.datascienceassn.org/sites/default/files/Unreasonable Effectiveness of Data.pdf @ IEEE
The Unreasonable Effectiveness of Data
Alon Halevy, Peter Norvig, and Fernando Pereira, Google

• For many tasks, words and word combinations provide all the representational machinery we need to learn from text.
• Because of a huge shared cognitive and cultural context, linguistic expression can be highly ambiguous and still often be understood correctly.
• The same meaning can be expressed in many different ways, and the same expression can express many different meanings. 
• Choose a representation that can use unsupervised learning on unlabeled data, which is so much more plentiful than labeled data.