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Of course, otherwise would mean investing in huge data centers for running LLM models, or worse, buying hardware from NVIDIA.
Optimization is the key. Privacy is just an added bonus.
No. Seriously, you underestimate how much these companies can make by transferring data to their server.
You probably underestimate the amount of effort Apple puts into not doing this, to maintain user privacy, and for a good while their services have suffered for it.
As an example I’d highlight the year in review feature between Apple Music and Spotify. “Replay” is significantly worse than “Wrapped” and I believe the difference is data handling is the key differentiator. However, there are some advances in balancing privacy 2ith utility, as highlighted in this post from Apple ML research: https://machinelearning.apple.com/research/scenes-differential-privacy
I’m going to disagree on the quality difference between Wrapped and Replay. I found Replay to actually be more useful when it came to actual data, Spotify doesn’t tell you as much as Apple about your listening patterns over the year and they also don’t even tell you what the whole year was, just January to October. Apple will also provide you with a large CSV file of every song you’ve listened to since 2018 if you go to their privacy page and request it. It takes a week or two, but they clearly have the data on file.
If you want a better Wrapped or Replay experience, try Last.fm. I get a ton of metrics from my listening and it has helped me find so much new music in the process.
Imagine all the stuff that Grammarly gets to see