Have we seen any evidence of that so far? Can Tesla do anything that Waymo can't? I think it is not so obvious that a given number of vehicles driven around randomly by laymen and having only limited uplink capacity will provide more useful data than a smaller fleet driven in a targeted way by trained drivers and with unlimited uplink capacity.
The fact that they use ADAS maps to control certain features shows that they don't just work anywhere.
I think the advantage is in how Tesla uses it. Tesla is working to build their own neural nets from scratch. To do this, they need to feed the computer with a lot of data in order to train it. The fleet provides that large amount of data. Karpathy has given us some specific examples. When Tesla wanted to train the vision NN to recognize cars cutting in, they got lots of short video clips of cars merging and fed those clips into the machine until the NN reached a high accuracy of being able to predict if a car is going to cut in. Tesla can get clips of anything they need to teach the NN from traffic lights to debris on the road etc... So no, I don't think it gives Tesla some secret ability that Waymo can't do, but it does help Tesla build their NN's much faster.
The other advantage is that the large fleet can provide feedback to Tesla to help them tweak their software. Tesla can run the software in shadow mode on a lot of cars in various environments and see how it performs. Furthermore, when Tesla does release "City NOA" with driver supervision to the general public, Tesla collects driver intervention data and can further tweak the software to handle edge cases. We saw this with how Tesla released NOA with and then without confirmation.
Waymo is different. Presumably, Waymo already has their own vision neural nets so they don't need to build them. Waymo uses a combination of HD maps, lidar data, cameras and radars to do their self-driving. Waymo's smaller fleet with trained safety drivers operating in a small geofenced area, does have the advantage of being able to perfect the FSD software to work extremely well in that geofenced area. Which is why we see Waymo cars operating at far better FSD in their areas that what Tesla has. When you test your cars over and over again in a small area, you can really focus on making them great in that area.
My question about Waymo's approach is that I am not sure it translates super well to other areas. Just because you get your cars to self-drive super well in say Phoenix, does not mean that they can automatically self-drive super well in San Francisco. So Waymo has to test their cars extensively in each new area.
I do think that once Tesla gets to "feature complete FSD" that the large fleet will be able to provide feedback that Tesla can use to perfect their software. For example, maybe Tesla cars handle intersections really well in one city but not so well in another city. Tesla will get that disengagement data and tweak the software to work in that city. So Tesla will essentially be able to test their FSD in every area that has Tesla cars simultaneously.
Think of it this way: Waymo's testing will expand out. Waymo started in one city and then expands to 2 more, then expands to 3 more, etc... Tesla's testing is more like a rising sea level. It's starts low everywhere and rises slowly everywhere.