So how can you claim that apple has taken the lead if you're not familiar with the biggest direct competitor?

I think the question was rhetorical. At this time, Apple is the only FAANG(M) with affinity for building features with on-device algorithms.

Google Photos is the wrong product to ask this question, IMHO. One of its key highlight is sharing albums with others and preserving them for the future, so why waste a consumer device's energy on unnecessary tasks if the image is going to end in a Google datacenter anyway?

Google Lens, which isn't about sharing, does run many functions on device: for example, it does ondevice offline translation: https://9to5google.com/2021/01/25/google-lens-translate-offl...

The general direction at Google (https://ai.googleblog.com/2021/11/improved-on-device-ml-on-p...) is to move as much as possible on device for privacy and latency reasons.

There are published and opensource (Apache license, according to the github LICENSE file) models for Tensorflow Lite which runs on Pixel Edge TPUs (and most embedded devices):

https://tfhub.dev/s?q=edgetpu https://github.com/tensorflow/models/tree/master/official/pr...

why would you make your claim about that apple is ahead if you don't know the answer to this question?

> does Google Photos perform all the analysis on device?

Does Apple? If I upload photos from my computer it does analysis in the cloud, doesn't it?

No. Apple has published several papers about how it works. It all happens on device.

How does that work when you upload via the browser from a Windows or Linux PC? Do they get stored in iCloud without being processed?

Presumably one of:

- the image is never analyzed

- the image is sync'd to device and then analyzed