realmariotorres

Great topic for an AMA. Waymo is famous for using deep neural nets at the perception of your cars. Do you also use any kind of machine learning techniques on the behaviour level as well? If so, how do you guarantee the car will never do anything bad?

Hi Nathaniel, I believe predicting the behavior of other road users is very challenging. Can you say anything about which kind of techniques do you use at waymo to make sure your predictions are correct? How do you make sure that waymo will not cause accidents if some of those predictions are wrong?

Simulating the world is a great way to train ML. How do you cope with wrong models (behavior models, light reflection models, etc.)?

Thanks for answering. When you mention that you work with "a framework that can leverage strengths of ML but combined with engineered solutions" are you thinking about ML with proofs of behavior or more like a Doer-Checker architecture?

Are the DNN and ML models transferable to different cities, countries? When can one expect to see Waymo cars driving in Tokyo, or Rome for instance?