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Sacha Arnoud, Director of Engineering, Waymo - MIT Self-Driving Cars

Name: Sacha Arnoud, Director of Engineering, Waymo - MIT Self-Driving Cars
Description: Sacha Arnoud, Waymo's Director of Engineering, gives a lecture in MIT's 2018 deep learning for self-driving cars course on the rise of machine learning in autonomous vehicles. It covers how Waymo uses deep learning and how it handles tricky driving situations.

Lex Fridman

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3 HN users recommended this lecture2 months2018–2023 score 2.5

Years with an HN recommendation, 2007–2026

Pointed to during self-driving news threads as an insider view of Waymo's progress, deep learning's role and its limits.

Sacha Arnoud, Waymo's Director of Engineering, gives a lecture in MIT's 2018 deep learning for self-driving cars course on the rise of machine learning in autonomous vehicles. It covers how Waymo uses deep learning and how it handles tricky driving situations.

“Check the lecture, its fantastic imo.” (HN, 2018)

1 strong recommendations · 2 recommendations · 1 citations · Lectures · intermediate · partly dated

Self-driving & autonomous vehicles Machine learning & deep learning University lectures & courses Lectures AI, Machine Learning & Data

4 Hacker News comments

From the HN archive; up to 20 kept per video, favoring different commenters. Recommendations first.

@RosanaAnaDana Mar 2018 Strongly recommends

on HN thread LiDAR scans are finding hidden Roman roads and cutting crime

I believe this talk will specifically and completely answer your questions: [this video] Short answer: Self driving vehicles do use deep learning, but they avoid some types not because it is unreliable, but it is processing power intense. Traffic lights, road signs, pedestrians etc.. That's a whole ball of wax to unravel. Check the lecture, its fantastic imo.

Explains how self-driving cars use deep learning and its limits.

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@lacerta Mar 2018 Recommends

on HN thread Self-driving Uber car kills Arizona woman crossing street

It is both an over and underhyped field depending on the area you are looking at. HUGE difference between consumer self driving car [Everywhere, at all times] and the Machines as a Service [Geo, time, weather-fenced operations][1]. Waymo appears to be at the head of the pack; Sacha Arnoud, Director of Engineering for Waymo gave a talk a few weeks ago at MIT[2] and gives a good idea. We are about 5 years out until these start rolling out as MaaS (machines as a service). Probably 10+ years for level 4 highway operations for consumer models according to Frazzoli. [1]Emilio Frazzoli, CTO of nuTonomy [link] [2] [this video]

Gives a good idea of Waymo's progress and timelines.

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@Zarel Aug 2018 Recommends

on HN thread Uber’s Vision of Self-Driving Cars Begins to Blur

The second article I linked to also mentioned work on unmapped roads: [link] Waymo has solved problem after problem you think they haven't solved yet, for some reason. They've intentionally gone after unpredictable situations and dealt with them. Look at any video where they explain how it works, and you'll notice how many situations they can manage: [this video] And even if Waymo only works on well-mapped cities? That's still far from "can only work if they repurpose existing transportation infrastructure to only belong to self-driving cars" which is the comment I was replying to.

Shows how many tricky driving situations Waymo can manage.

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Citations, criticism and jokes

@verdverm Jan 2023 Cites it

on HN thread GPT is all you need for the back end

Google/Waymo demo'd the AI driving in a snow storm and the method they used to see through the flakes and maintain object detection. Having trouble finding the video I'm thinking of. Here are some videos related to self-driving in snow and progress on weird edge cases. - [link] (snow, like the google demo) - [this video] | [this video] (snow, but not the one I was thinking of)

Related self-driving video on snow and edge cases.

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