Huh? I restricted it to 2023-now, and got 146 results. 80 for 2024 only.

146 in how many? 80 in how many?

80/557

146/1109

that's above 12% on both.

now correct it for number of sold phones each (estimated by looking at the 70 most popular models) and we'll get why they said 1/4.

For an app as popular as Transit this is a purely academic exercise—25% of the most popular models is way too low to be worth building their detection around, even if they could assume that all of their customers use the most popular models (which they obviously can't).

25% of popular models doesn't mean 25% of phones currently in circulation. If the iPhone has a barometer (which it does), that's already a huge share of phones out there.

The conversation was about Android.

But the point stands, it’s about the distribution of phones not how many models support it.

I'm in favor of Transit trying to reach more than 25% of the most popular phone models even if doing so would get them 75% of the population.

It may be too low, but I'd imagine the app could also look for other Transit users nearby and as long as one of them has the appropriate sensor, this might be sufficient. Probably still not something you want to rely on since it would be pretty annoying to have a feature not work when you're alone on a train.

> the app could also look for other Transit users nearby

That seems unlikely in an environment with no cellular / wifi signal. Theoretically possible, but expensive for battery and probably disallowed by the OS.

Does the current version of their app run on 25% of the most popular models? This update runs a classifier on your phone. I imagine that would be no less restrictive than the barometer requirement.

Most classifiers are nowhere near as heavy as the LLMs that are trending right now. The article doesn't specify, but I would be surprised if the resource requirements are especially onerous.