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THE VIDEO SHELF · tesla self-driving

Tesla Autonomy Day

Tesla's roughly four-hour Autonomy Day investor event covers its in-house self-driving chip, vision-only approach, fleet data engine and robotaxi plans, with talks by Andrej Karpathy and others.

Why HN readers recommended it

Cited both as a primary source on Tesla's technical autonomy approach and, later, for Musk's unmet robotaxi predictions.

This is a summary from the source dataset, not an endorsement by Hacker News or the video creator.

Video & recommendation details

Creator / channel
Tesla
Topic
tesla self-driving
Format
talk
Level
intermediate
HN recommenders in dataset
3
HN mentions in dataset
20
Recommendation years in dataset
2019–2024

These counts and years describe the included Hacker News records; they are not YouTube views or the video’s publication date.

From the original HN conversations

Excerpts from the recorded comments. Follow each source for the full comment and surrounding discussion.

  • After the recent "Tesla Autonomy Day" video [VIDEO] (almost 4h long, but worth a watch), I do rather feel like the incumbent services are about to be in a spot of bother. I think there's a bubble in this sector, and it's going to pop.

    furriephillips on Hacker News · 2019-05
    In The investor who turned down Uber at a $5m valuation
  • Watch the presentation from 6 months ago, where they explain the decision to build their own hardware for inferring : [VIDEO] It's not surprising that they also build the hardware for training. Correct me if I'm wrong, but Google use the same TPUs for training …

    antpls on Hacker News · 2019-11
    In Andrej Karpathy talks about how Tesla's NNs are structured and trained [video]
  • I heard from a tesla engineer that they do use lidar to train their models, but that they don’t see the value in deploying it to the fleet. It’s worth watching the tesla event from about a year ago if you haven’t seen it for …

    fossuser on Hacker News · 2020-08
    In Electric car startup Lucid is challenging Tesla’s anti-Lidar stance

Summaries, classifications and recommendation records are from the HackerTube source dataset. Read about this library and its limitations.