Because snow conditions are inherently more dangerous and more likely to yield data for the cases we really care about, i.e. accidents and near accidents. Getting commute data in California is likely to just give you a ton of boring repeat data going to and from googleplex and a few locations. As far as I understand, the technology is already good enough to handle that sort of 80% reliability stuff. It's the last 20% - the hard stuff - that needs to be hammered on from now on.

> snow conditions are ... likely to yield data for the cases we really care about

That’s not intuitive to me. I don’t see why snow conditions would teach us about likely accidents in Pali Alto.

Someone had a good example in this thread, for example, you're more likely going to run into issues with clogged sensors in detroit than you are in palo alto. Another thing that happens way more in snow is automatic torque rebalancing in 4WD systems. Rainy days aren't nearly as common in Palo Alto as snowy days are in Detroit but both share the property of poorer visibility and an increase in pedestrian distraction levels. Etc, etc.

A lot of technology only exists because their original problem set was extreme in nature (e.g. things out of NASA or military research). I think a lot of "easier" problems in autonomous driving could benefit from a breakthrough solution that got discovered in the course of solving a harder problem.