The only reason I haven't switched, is when using uv as my environment manager, starting/connecting to the python kernel in notebooks within vscode takes forever.
My biggest issue is using uv envs in vscode under WSL. Starting up interactive sessions takes forever. Its just too slow, can't figure out what the deal is.
I've been at two small companies that had layoffs, and who was cut/retained was 100% based on what was best for the company (except some visa holders were retained). Which is what it should be.
That is not what the study found. The study found people are able to guess the given names of adults from four choices at slightly better than chance, ~30%. With 117 (or 116?) people guessing and 16 images.
I agree it seems like flimsy justification. But it is also likely harder to assess and communicate. Temperature they get a point prediction for the high and you can easily calculate the mean absolute error.
For precipitation you will be getting percent chance often with an interval, 10% chance of 0.1-0.25 inches with higher likely in thunderstorms. Also precipitation patterns tend to be much more irregular within small spatial extents. You can asses things like calibration and perhaps take a mean value for there intervals to get point errors. But all of this will make it harder to communicate actual performance.
But temperature error matters a lot less. 82° instead of 87° is "high" error but the practical difference for me is essentially zero. If it's raining when my phone said it wouldn't rain, I have to change my plans.
I had a friend who did forecasting for a utility and getting the forecast wrong by 5 degree would have been very expensive at the time. I don't remember if it was worse in the summer (AC) or winter. And I wish I could remember if they were buying just electricity or also natural gas
In the same vein as you, I don't care much if it is raining at my office closer to the mountains but I care about it at home. The distance is ~10 miles and I regularly can see a difference.
I like the ping pong of one day an article being posted where everyone asks, "when/why did everything become so complicated", and then the next day something like this is posted.
