Waymo's investment in data mining, training cycle, and automation of the feedback loop is key to building a robust and generalizable autonomous driving system.
- Investment in frameworks and infrastructure for closing the loop on data mining training cycle
- Investment in feedback loop as a first-class object in the development life cycle
- Automation and low human engineering cost in the ML infrastructure
- Discovery of interesting long-tail examples through data mining and hard data example mining strategy
- Challenges in optimizing for both long-tail and average case distributions
- Unification and simplification of technology development and team organization to build a robust and generalizable core stack