The lead architect wasn’t very interested in simulation for accelerating learning: all their training data came from the cars.
(take all mention of timelines and claims of capability with a grain of salt, maybe add some months/years and divide capability by 2 or 3)
“Tesla has been able to do real-world video generation with accurate physics for about a year.
It wasn’t super interesting, because all the training data came from the cars, so it just looks like video from a Tesla, albeit with a dynamically generated (not remembered) world.”
Another 2024 moment of clarity:
”Two sources of data scale infinitely: synthetic data, which has an “is it true?” problem and real-world video, which does not.”
Now in 2025 a different view:
This is a positive for Tesla AI driving, it shows signs of learning a better way.
Tesla has been learning since its founding. The difference with many or most legacy automakers is that Tesla recognizes where change is necessary and they change.
They have probably trained on thousands and thousands of hours of road experience and tapes of various situations. Simulation is probably most useful for fine tuning software responses to various situations.
Most driving is eventless which means most of the data is repetitious. By contrast data about accidents is sparse and that is where simulation is most useful, the so called, “edge cases.”