this post was submitted on 05 Jan 2025
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Privacy
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At that scale and because they do pay for servers I bet they did the math and are constantly optimizing the process as they own the entire stack. They might have somebody who worked on the M4 architecture give them hint on how to do so. Just speculating here but arguably they are in a good position to make this quite efficient, even though in fine if it's actually worth the ecological costs is arguable.
Did they? Because it seems like everyone else is in a hype bubble and doesn't give a shit about how much this costs or how much money it makes.
Looks like they did "Brakerski-Fan-Vercauteren (BFV) HE scheme, which supports homomorphic operations that are well suited for computation (such as dot products or cosine similarity) on embedding vectors that are common to ML workflows" namely they use a scheme that is both secure and efficient specifically for the kind of compute they do here. https://machinelearning.apple.com/research/homomorphic-encryption
At least it's not going to be the overhyped LLM doing the analysis, it seems, considering the input is a photo data.
Here indeed I don't think so but other vision models, e.g. https://github.com/vikhyat/moondream are relying on LLM to generate the resulting description.
My gosh, what is with people's reliance on single thing
Well to be fair, and even though I did spend a bit of time to write about the broader AI hype BS cycle https://fabien.benetou.fr/Analysis/AgainstPoorArtificialIntelligencePractices LLMs are in itself not "bad". It's an interesting idea to rely on our ability to produce and use languages to describe a lot of useful things around us. So using statistics on it to try to match is actually pretty smart. Now... there are so many things that went badly for the last few years I won't even start (cf link) but the concept per se, makes sense to rely on it sometimes.
Their chips are pretty good at not drawing much power. But then you also get to the balance of power cost, computing power and physical space.
Google and Microsoft are already building their own power generation systems for even faster AI slop. That would make power a lot cheaper, and super efficient chips might not be the best answer.
I don't know which way Apple will go, except further up their own behind. But either way, these are some really cool approaches to implementing this technology, and I hope they keep it up!
Yep, reading their blog post to read a bit better. I don't like that it's enabled by default, especially despite iCloud off (which should be a signal to say the user does NOT want data leaving their device) but considering what others are doing, this seems like the best trade off.