[solutron]

Waymo has to learn the exact space it's going to drive in ahead of time, and then have high resolution lidar maps generated to assist. It's currently limited to use in grid-like pre-mapped areas like Phoenix AZ. Tesla is building a general learning solution such that you can take the vehicle anywhere, and not have the requirement that the area be pre-mapped or 'learned' by Tesla beforehand. Tesla has orders of magnitude more data and mileage driven than Waymo could possibly ever imagine having. Waymo is not going to scale. CEO departures like this are a big red flag. Pin this comment. Google will shutter Waymo in less than five years.

[formerly_proven]

The problem is, Tesla does not posses magic.

We know (from introspection) how trained skills work. Everyone knows the feeling when that bunch of neurons which you trained to semi-autonomously do something for you (e.g. switch gears, write letters, type words, observing traffic, staying in an imaginary lane etc.) raises their hand so that Daddy AGI (our conscious) can come have a look at that weird situation it doesn't know how to handle.

Tesla can't do that, either, and literally no one on this planet has the faintest idea how to do anything like it.

[Laremere]

I think you're highlighting the difference in approach instead of pointing out a fatal flaw in Waymo's strategy.

Tesla is focusing on data because they believe they can machine learn through the problem.

Waymo has a lot of data, but is also focusing on better sensors, augmenting them with maps, and ML perception feeding into more traditional programing doing the actual control and decision making.

It's kind of like Tesla and Waymo are both learning basket ball. Tesla believes that if it just plays a lot of games of basket ball, that is the best strategy. Waymo think that playing some games is good, but it should also do things like practice free throws and weight train.

Also, a few misconceptions:

1. Waymo currently only has public service in Arizona, AFAIK. However they are testing in San Fran, Seattle area, and Michigan. Easiest first doesn't mean later is impossible.

2. pre-mapping is NOT a blocker of automated service. Consider how much effort goes into making each section of road. Driving a car by a few times is a trivial cost in comparison. This is further shown by the fact that Google has been doing street view for well over a decade. Also I'd like to see Tesla demonstrate they can drive with the road covered in snow and still know where they are without a map.

3. CEO departures can be a red flag. They can also be a completely benign changeover, or even green flag that the board identified others would perform better in the CEO position. The leaving announcements are always fluff about spending time with family, so it's really hard to tell what's going on from the outside. If this is followed by more leadership leaving Waymo, then I'd be concerned.

[Geee]

Yeah. Andrej Karpathy said in a recent interview that at this point it's almost completely a data problem, instead of a machine learning research problem. Most of their work is in figuring out the best way to collect and annotate lots of good data. Waymo has a few hundred cars and Tesla has millions, and in this problem space, scale wins over more precise sensors.

Here's the interview: https://open.spotify.com/episode/0IuwH7eTZ3TQBfU8XsMaRr?si=6...

[bobsil1]

Yep, Waymo approach is brittle