Episode description

Drago Anguelov is a Distinguished Scientist and Head of Research at Waymo, an autonomous driving technology company and subsidiary of Alphabet Inc.

We begin by discussing Drago's work on the original Inception architecture, winner of the 2014 ImageNet challenge and introduction of the inception module. Then, we explore milestones and current trends in autonomous driving, from Waymo's release of the Open Dataset to the trade-offs between modular and end-to-end systems.

Drago also shares his thoughts on finding rare examples, and the challenges of creating scalable and robust systems.

Show notes (transcript and links): http://wandb.me/gd-drago-anguelov

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⏳ Timestamps:

0:00 Intro

0:45 The story behind the Inception architecture

13:51 Trends and milestones in autonomous vehicles

23:52 The challenges of scalability and simulation

30:19 Why LiDar and mapping are useful

35:31 Waymo Via and autonomous trucking

37:31 Robustness and unsupervised domain adaptation

40:44 Why Waymo released the Waymo Open Dataset

49:02 The domain gap between simulation and the real world

56:40 Finding rare examples

1:04:34 The challenges of production requirements

1:08:36 Outro

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Connect with Drago & Waymo

📍 Drago on LinkedIn: https://www.linkedin.com/in/dragomiranguelov/

📍 Waymo on Twitter: https://twitter.com/waymo/

📍 Careers at Waymo: https://waymo.com/careers/

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Links:

📍 Inception v1: https://arxiv.org/abs/1409.4842

📍 "SPG: Unsupervised Domain Adaptation for 3D Object Detection via Semantic Point Generation", Qiangeng Xu et al. (2021), https://arxiv.org/abs/2108.06709

📍 "GradTail: Learning Long-Tailed Data Using Gradient-based Sample Weighting", Zhao Chen et al. (2022), https://arxiv.org/abs/2201.05938

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💬 Host: Lukas Biewald

📹 Producers: Cayla Sharp, Angelica Pan, Lavanya Shukla

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