Tesla AI

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Tesla AI

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FSD is trained on billions of real-world miles, including power outages 📸 Edge Case

Tap button, press brake And just like that, FSD Supervised takes you wherever you want

These models will learn from a huge set of extremely diverse data from the Tesla fleet

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Eclipse as seen by one of our test vehicles in Spain

Teslas now drive themselves from their birthplace at the factory to their designated loading dock lanes without human intervention One step closer to large-scale unsupervised FSD

Real-world AI is about solving for the edge case, not the average case

Giga Texas production now uses FSD Unsupervised to deliver cars from end of line to the outbound logistics lot. Over 50,000 driverless miles have been accrued between California and Texas factories so far

Tesla is building the foundation models for autonomous robots

Every FSD release is rigorously tested, including rare and adversarial scenarios on closed courses — Here's 16 examples: 1. Reverse Cut-in (Occluded)

Starting with the ~1.2 mile route at the Fremont factory

Cybercab is individualized point-to-point autonomous transport

FSD (Supervised) testing in Melbourne, Australia And yes, that’s a hook turn

New Teslas drive themselves off the line at Giga Berlin Autonomously navigating the factory premises, they stop by the on-site Supercharger, then park in the outbound lot

These imagined futures can be action-conditioned to produce different outcomes. For example, the videos below are generated entirely by the neural network by simply using different prompts

15. High Speed Stationary Child

Our multi-modal neural networks are already in customer vehicles—these networks take in arbitrary modalities such as camera videos, maps, navigation, IMU (Inertial Measurement Unit), GPS etc.

All of this is enabled by fleet scale auto-labelling. By using video data from multiple trips in the same location, we can reconstruct the entire scene

16. High Speed Crossing Child