How does Tesla manage to label ALL THAT DATA? And why does it even matter?? AI Day Part 6

Описание: On August 19th, during Tesla AI day, Andrej Karpathy, director of artificial intelligence and autopilot vision, dove into a topic that is distinctly not sexy, but absolutely necessary for modern machine learning: collecting and especially labeling data for training.
After covering how Tesla Vision converts 2D images into 3D vector space, and discussing how the cars can plan ahead not just for them, but for all other agents in the scene (you can watch my previous videos, linked above, for much more on this), Dr. Karpathy broached the topic of how Tesla deals with the mountains of data it’s 2 million car strong fleet produces now.
And while I thought I’d be bored by this section of the talk, I was, frankly, blown away by how brilliant Tesla’s data labeling strategy is, and also how much time, person power, and money Tesla has and is putting into labelling the best, most targeted data possible. Along with the incredible neural network architecture, this data labeling is what is enabling Tesla to achieve what seemed impossible just a short time ago: full autonomous driving using only cameras!

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