#tesla #selfdriving #karpathy

Tesla is pushing the state-of-the-art in full self-driving, and interestingly, they explicitly switch from having multiple different sensors to a vision-only system. We discuss the highlights of Andrej Karpathy's talk about Tesla's FSD system, how to label petabytes of data, how to sample edge-cases, how to train a neural network that has to work in real-time, and why moving to having only cameras is superior to multi-sensor approaches.

OUTLINE:

0:00 - Intro & Overview

1:55 - Current Auto-Breaking system

3:20 - Full Self-Driving from vision only

4:55 - Auto-Labelling for collecting data

8:45 - How to get diverse data from edge-cases

12:15 - Neural network architecture

16:05 - Tesla's in-house supercomputer

17:00 - Owning the whole pipeline

18:20 - Example results from vision only

23:10 - Conclusion & Comments

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