[runako]

> the vast amount of training data they are collecting

They keep pushing this point. And they do appear to be collecting an absolute firehose of data from the millions of vehicles they have on the road. By comparison, Waymo collects a lot less data from many fewer vehicles.

Which leads to some tough questions about Tesla's tech. If they have (conservatively) 10x the training data that Waymo has, why can't their product perform as well as Waymo? Do they need 100x? 1,000x? 10,000x?

Assuming they were at parity with Waymo today, this would suggest that their AI is only at best 10% as effective as Waymo's, and possibly more like 1% or 0.1% or whatever. But since they can't achieve parity, it's not even possible to bound it.

It's entirely possible that their current stack cannot solve the problem of autonomous driving any more than the expert systems of the 60s could do speech translation.

I haven't heard a compelling argument as to why a system that is at best 10% as effective would ever be expected to be the leader.

[npinsker]

Data isn’t as useful here as in other domains, since when you change the car’s behavior even a tiny bit, a lot of the timeseries is invalidated. It’s not evergreen, and it can be quite subjective what it means to “pass” a scenario that one previously failed.

Also, Tesla collects data from its fleet, but that data’s fidelity is likely quite limited compared to other companies, because of bandwidth if nothing else. Waymo can easily store every lidar point cloud of every frame of driving.