I thought the fact they have 1,000 data labelers was interesting.
I'm unsure about their dojo efforts. Seems cool, seems better than Nvidia but not 10x better (hard to tell it's not apples to apples). For example their dojo cluster us supposed to have over an exaflop vs a A100 superpod at 700pb (seems like I/O is over 2x better which I understand conceptually why it matters but not real world implications). By the time this gets production ready (next year) seems possible Nvidia will have a replacement that is about as good or better.
Network architecture was not using video before, it was using 2-3 frames, which seemed obviously not going to work so seems better now.
The updated network architecture plus the fact they need to train with a supercomputer to me means they will almost certainly need a new inference chip. They didn't announce a v3 of their FSD computer, but that is probably the physical component blocking FSD rollout.
My take on timeline for actual compete everywhere self driving (robotaxi) seems to be: -dojo isn't even in production until next year, so no earlier than that. -FSD chip v3 probably not going to be design finalized until they use some dojo models in it. That plus chip shortages means it's unlikely to happen at scale until 2023.
So I think this presentation was to make it clear the large about of progress they are making (very impressive), but IMO this was also a subtle way of making 2023 the new target FSD date.
The alternative is they don't think they need dojo to get FSD, and if that is the case why bother building a fully integrated chip manufacturing process?