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Tesla AI Day 2022

Tesla AI Day 2022 on HackerTube: recommended by 2 Hacker News commenters across 2 separate months, 2022–2026.

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Tesla's full AI Day 2022 presentation, covering the Tesla Bot hardware and software, Full Self-Driving planning and perception, the occupancy network, data labeling, simulation and Dojo training infrastructure.

Why Hacker News recommends it

HN uses it as primary-source evidence on how Tesla's vision-based driving stack and training pipeline work.

people recommended it
2
separate months
2
strong recommendations
1
discussed on HN
2022–2026
“Learning about their engineering in that regard really changed my perception of the likelihood that they could solve the problem. Give it a watch”
— timschmidt, Oct 2024, in “The Retreat to Muskworld”

What HN commenters said

8 Hacker News comments link this video. Each one links back to its thread.

timschmidtOct 2024Strongly recommends

> If the data from supervised driving can he used for unsupervised driving So you're unaware of the AI day presentations about their driving training pipeline. Learning about their engineering in that regard really changed my perception of the likelihood that they could solve the problem. Give it a watch: ▶ this video > failure to keep up with competitors like Waymo Looks like each of them lead in different ways to me. Waymo leads within certain specific city limits, Tesla leads on the open road. These seem to be direct consequences of their engineering decisions. Question is which will converge on working everywhere all the time.

in “The Retreat to Muskworld” · View on HN

aeternumOct 2022Recommends

It is pretty cool: ▶ this video They transitioned from 2D to 3D a couple years ago, major transition but it does seem like a critical step. We live in a 3d rather than 2d world.

in “Why Tesla removed radar and ultrasonic sensors [video]” · View on HN

schiffernFeb 2026Cites it

>I've never really thought of Waymo as a robot in the same way as e.g. a Boston Dynamics humanoid, but of course it is a robot of sorts. So for the record, with this realization you're 3+ years behind Tesla. ▶ this video

in “The Waymo World Model: A New Frontier for Autonomous Driving Simulation” · View on HN

cptcobaltApr 2023Cites it

Exactly. There's no better facsimilie for the sheer variety of public roads than, well, public roads. Tesla even has rigorous simulation in place for hostile situations that should never occur on public roads: A good general overview from two minute papers: [link] Tesla's AI Day 2022 video, timestamped around labeling and simulation ▶ this video

in “Tesla Again Paints a Misleading Story with Their Crash Data” · View on HN

zaptremOct 2022Cites it

No, and they should be criticized for that. However, this is the transparency that makes up for it: ▶ this video

in “Starlink now over 1M user terminals manufactured” · View on HN

simondotauOct 2022Cites it

As stated by Tesla just a few days ago, the occupancy network is not currently shown in the customer-facing visualisation. (Some unrecognised objects are represented by generic placeholders. This is derived from, but not the output of, the occupancy network.) This video links to the relevant citation, and if you continue watching for around ten seconds you can see examples of the occupancy network visualised: ▶ this video

in “Tesla Vision Update: Replacing Ultrasonic Sensors with Tesla Vision” · View on HN

Show 2 more comments
113245Oct 2022Cites it

The Tesla AI day videos [1] go into some detail about this. They use multiple networks that are dedicated to specific tasks. [1] [link] (2021), ▶ this video (2022)

in “Why Tesla removed radar and ultrasonic sensors [video]” · View on HN

whiddershinsOct 2022Cites it

The replies to your comment don't seem to understand you at all. in the video link here ▶ this video he clearly states 16x dynamic range as a result of direct photon processing.

in “Why Tesla removed radar and ultrasonic sensors [video]” · View on HN

Topics & tags

Self-driving & autonomous vehiclesRoboticsMachine learning & deep learningteslafull self-drivingoccupancy networksdojohumanoid robotscomputer vision