Tesla AI Day 2022
Tesla2 HN recommenders · recommended in 2 months, 2022-2026
2.3M views · 4 years ago · talk · dated
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.
HN uses it as primary-source evidence on how Tesla's vision-based driving stack and training pipeline work.
3:03:20Tesla AI Day 2021
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3:52:20Tesla Autonomy Day
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30:09Andrej Karpathy - AI for Full-Self Driving at Tesla
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1:06Tesla Bot Update
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37:47Andrej Karpathy (Tesla): CVPR 2021 (see description for better quality version)
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0:31Autonomous Car Learns To Powerslide Into Parking Spot
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1:13:22Sacha Arnoud, Director of Engineering, Waymo - MIT Self-Driving Cars
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![[CVPR'21 WAD] Keynote - Andrej Karpathy, Tesla](https://i.ytimg.com/vi/g6bOwQdCJrc/hq2.jpg)
31:32[CVPR'21 WAD] Keynote - Andrej Karpathy, Tesla
WAD at CVPR
51K views • 5 years ago
1:18Tesla Bot Update | Sort & Stretch
Tesla
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14:28How Google's Self-Driving Car Works
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1:57Full Self-Driving
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35:31Autonomous Car - what goes into sensing for autonomous driving?
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1:56Google Self-Driving Car on City Streets
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1:06Atlas | Partners in Parkour
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13:31[FSD Beta 8.2] Oakland - Close Calls, Pedestrians, Bicycles!
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44:17No Priors Ep. 80 | With Andrej Karpathy from OpenAI and Tesla
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2:48Waymo's fully autonomous driving technology is here
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10:24Elon Musk on Cameras vs LiDAR for Self Driving and Autonomous Cars
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1:44Optimus - Gen 2 | Tesla
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9:16FSDBeta 8.2 - 2021.4.11.1 - 4K Drone View of Unprotected Left Turns with Forward Facing Traffic
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8 comments from Hacker News
>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
> 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.
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
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.
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.
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)
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
No, and they should be criticized for that. However, this is the transparency that makes up for it: ▶ this video