In my experience apple's ML on iphones is seamless. Tap and hold on your dog in a picture and it'll cut out the background, your photos are all sorted automatically including by person (and I think by pet).
OCR is seamless - you just select text in images as if it was real text.
I totally understand these aren't comparable to LLMs - rumor has it apple is working on an llm - if their execution is anything like their current ML execution it'll be glorious.
(Siri objectively sucks although I'm not sure it's fair to compare siri to an LLM as AFAIK siri does not do text prediction but is instead a traditional "manually crafted workflow" type of thing that just uses S2T to navigate)
Does android even have native OCR? Last I checked everything required an OCR app of varying quality (including windows/linux).
On ios/macos you can literally just click on a picture and select the text in it as if it wasn't a picture. I know for sure on iOS you don't even open an app to do it, just any picture you can select it.
Last I checked the Opensource OCR tools were decent but behind the closed source stuff as well.
Not sure about other Android OEMs but OCR has been built in to Samsung Gallery (equivalent to Photos app on iPhones) for a while. Works the same way - long press on text in an image to select it as text. Haven't had any issues with it.
I'm not saying they will on the high-end, but maybe on the low end. Apple's strategy is to embed local AI in all their devices. Local AI will never be as capable as AI running in massive GPU datacenters, but if it can get to a point that it's "good enough" for most average users, that may be enough for Apple to undercut the low end of the market.
> Local AI will never be as capable as AI running in massive GPU datacenters
I'm not sure this is true, even in the short term. For some things yes, that's definitely true. But for other things that are real-time or near real-time where network latency would be unacceptable, we're already there. For example, Google's Pixel 8 launch includes real-time audio processing/enhancing which is made possible by their new Tensor chip.
I'm no fan of Apple, but I think they're on the right path with local AI. It may even be possible that the tendency of other device makers to put AI in the cloud might give Apple a much better user experience, unless Google can start thinking local-first which kind of goes against their grain.
> But for other things that are real-time or near real-time where network latency would be unacceptable, we're already there.
Agreed. Something else I wonder is if local AI in mobile devices might be better able to learn from its real-time interactions with the physical world than datacenter-based AI.
It's walking around in the world with a human with all its various sensors recording in real-time (unless disabled) - mic, camera, GPS/location, LiDAR, barometer, gyro, accelerometer, proximity, ambient light, etc. Then the human uses it to interact with the world too in various ways.
All that data can of course be quickly sent to a datacenter too, and integrated into the core system there, so maybe not. But I'm curious about this difference and wonder what advantages local AI might eventually confer.
This is a fascinating thought! It could send all the data to the cloud, but all those sensors going all the time would be a lot of constant data to send, and would use a lot of mobile data which would be unacceptable to many people (including probably the mobile networks). If it's running locally though, the data could we quickly analyzed and probably deleted, avoiding long term storage issues. There's got to be a lot of interesting things you could do with that kind of data
