There are many issues with Tesla's autopilot that are completely unrelated to the amount of data they have, and they will not be fixed with more data, and having more data will not make it easier to fix it. At this point, I would argue that the discussion about who owns more millions of miles of data is completely irrelevant.
Tesla has built out amazing infrastructure to capture extensive amounts of "hard" examples from their fleet, turn them around into labeled data for training very efficiently and then utilizing simulations to further broaden the distribution of such quirky long-tail events in their training-set. In the absence of AGI, this is a very effective "brute-force" approach and they have a huge upper hand over every other player in this space.
I say all of this even though I am very skeptical that anyone will achieve L5 self-driving with where the state of things are today. But Karpathy and team are very pragmatic and making lots of good decisions coupled with excellent engineering and infrastructure development.
Good thread on ground Tesla would need to make up to catch AV leaders here. https://twitter.com/Christiano92/status/1428671634131628033
Simulation is important for sure, and Tesla even talked about that as much. But you can only simulate the scenario's that you've thought of, it can't replace real world data, which again Tesla has several orders of magnitude more of than Waymo.
As for the comments about Dojo I think they're unfounded. Tesla has already proven that they can create their own custom chip and have shipped it to hundreds of thousands of cars. I don't see any reason to think they can't get the system running in the next year or so. But even if they can't do that in time they still have NVIDIA to fall back on. Elon even said in the talk that maybe it might not work out, and if that's the case they can always buy a solution.
this raises the question of: what happens when those environments change?
It absolutely is implausible.