Drago Anguelov: Waymo and Autonomous Vehicles

Drago Anguelov: Waymo and Autonomous Vehicles

Author: Daniel Bashir April 20, 2023 Duration: 1:05:23

In episode 69 of The Gradient Podcast, Daniel Bashir speaks to Drago Anguelov.

Drago is currently a Distinguished Scientist and Head of Research at Waymo, where he joined in 2018. Earlier, he spent eight years at Google working on 3D vision and pose estimation for StreetView, then leading a research team that developed computer vision systems for annotating Google Photos. He has been involved in developing popular neural network methods such as the Inception architecture and the SSD detector. Before joining Waymo, he also led the 3D perception team at Zoox.

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Outline:

* (00:00) Intro

* (02:04) Drago’s background in AI and self-driving, work with Daphne Koller + Sebastian Thrun, computer vision / pose estimation

* (14:20) One- and two-stage object detectors

* (15:15) Early experiences and thoughts on self-driving and its prospects

* (21:00) An introduction to the “self-driving stack”: mapping & localization, perception, behavior modeling & planning, simulation

* (29:25) From Stuart Russell’s comments on early Waymo’s “old-fashioned” approach

* (37:34) Scaling 3D Detection: challenges and architectural innovations

* (43:20) Behavior modeling: making decisions and modeling interactions in multi-agent environments

* (52:42) Distributional RL (+ imitation learning) in self-driving?

* (54:10) The Waymo Open Dataset

* (1:01:48) Looking forward in self-driving

* (1:04:36) Outro

Links:

* Drago’s LinkedIn and Twitter

* Research

* SSD: Single-Shot Multibox Detector

* SCAPE: Shape completion and animation of people

* Behavior Models for Autonomous Driving

* Wayformer

* Symphony: Learning Realistic and Diverse Agents for Autonomous Driving Simulation

* Imitation Is Not Enough

* Scaling 3D Detection to the Long Tail



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Hosted by Daniel Bashir, The Gradient: Perspectives on AI moves beyond surface-level headlines to explore the intricate machinery and human ideas shaping artificial intelligence. Each episode is built on a foundation of deep research, leading to conversations that are both technically substantive and broadly accessible. You'll hear from researchers, engineers, and philosophers who are actively building and critiquing our technological future, discussing not just how AI systems work, but the larger implications of their integration into society. This isn't about speculative hype; it's a grounded examination of real progress, persistent challenges, and ethical considerations from those on the front lines. The discussions peel back layers on topics like model architecture, policy, and the fundamental science behind the algorithms becoming part of our daily lives. For anyone curious about the substance behind the buzz-whether you have a technical background or are simply keen to understand a defining technology of our age-this podcast offers a crucial and thoughtful resource. Tune in for a consistently detailed and nuanced take that treats artificial intelligence with the complexity it deserves.
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