Waymo, DeepMind to work together to improve self-driving cars

Waymo’s self driving cars will soon employ neural networks to perform tasks such as detecting objects and even predicting how others will behave.

Reuters reporter Alexandria Sage steps out of a Waymo self-driving vehicle during a demonstration in Chandler, Arizona, November 29, 2018. REUTERS/Caitlin O’Hara (REUTERS)

Alphabet-owned Waymo has partnered with UK-based computer programmes company DeepMind on a 'Population-Based Training' method for pedestrian detection that has the best neural networks like life forms do in natural selection, thus, saving time and effort.

According to the company, Waymo's self-driving vehicles employ neural networks to perform many driving tasks, from detecting objects and predicting how others will behave, to planning a car's next moves.

"Now, Waymo, in a research collaboration with DeepMind, has taken inspiration from Darwin's insights into evolution to make this training more effective and efficient," Yu-hsin Chen, Senior Software Engineer at Waymo recently wrote in a blog post.

"To make this process more efficient, researchers at DeepMind devised a way to automatically determine good hyperparameter schedules based on evolutionary competition (called 'Population-Based Training' or PBT), which combines the advantages of hand-tuning and random search," Chen added.

Like random search, PBT also starts with multiple networks initiated with random hyperparameters.