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https://qz.com/1005879/snapchat-quietly-revealed-how-it-can-...
The linked paper makes no reference to CoreML or Apple in general. It seems to be CPU-accelerated on all platforms, iPhone included. Do you have another source that goes into Apple's implementation?
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It already does and I hate it. If a person you’re speaking with misspells a word, it’ll happy suggest^w forcibly autocorrect a similar word to that misspelling if it was recent enough.
I think tpowell was asking about the all-new autocorrect system. Do you have information on how that works, or were you just talking about the old system that is being deleted on Monday?
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> Apple put neural in their silicon a full four years before Google did: You're confusing when Google started designing its own mobile SOC with when Android devices (including Google's) first started using neural network accelerators, which happened months earlier on Android than on iPhones. https://www.qualcomm.com/news/onq/2017/01/tensorflow-machine... As for GP's claim, Android has indeed had what the iPhone is no…
> You're confusing when Google started designing its own mobile SOC with when Android devices (including Google's) first started using neural network accelerators, which happened months earlier on Android than on iPhones. Apple (famously) doesn't announce until new functionality/devices are actually available. When they announce real people in the real world get it within a week if not less. A press release from Qual…
This press release was for a new Tensorflow release for devices that had been shipping for many months before that. It was in people's hands long before Apple even announced anything similar.
> If not that's on the Gboard team at Google for not supporting neural on iOS and Apple hardware that came far, far sooner.
Once again, Apple's hardware came later than Qualcomm's hardware. Pixel phones come with a lot of features that could be implemented on iOS, but why should Google go through the work of porting it only to promote a competitor's inferior platform? For example, Google Maps with navigation shipped years earlier on Android. Grammar check with a transformer model is now on all Android devices in Gboard (for more than a year and a half) and still no iOS devices.
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Because at work I’m typing the same bland things all the time in documents and communications. I appreciate stuff like the predictive word stuff in Google Docs. It’s helpful because business language is expected to be normalized and boring. On the other side of that token, the average language abilities of the average American office worker are pretty low so I’m assuming they view this as an enhanced AutoCorrect and…
> Because at work I’m typing the same bland things all the time in documents and communications. This problem can be solved without text prediction by building a personal knowledge base with hyperlinking[0] and backlinking[1] for discovery, and transclusion[2] for automating writing the same bland things. How I org in 2023 by Nick Anderson[3] goes over a great workflow for this. The advantage of this is that all of t…
Anyway, I like and use the feature daily at work. So do lots and lots of other people.
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The linked paper makes no reference to CoreML or Apple in general. It seems to be CPU-accelerated on all platforms, iPhone included. Do you have another source that goes into Apple's implementation?
I'm pretty fatigued on constantly providing references and sources in this thread but an example of what they've made availably publicly (second result Googling "snap coreml"): https://github.com/snap-research/EfficientFormer
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The linked paper makes no reference to CoreML or Apple in general. It seems to be CPU-accelerated on all platforms, iPhone included. Do you have another source that goes into Apple's implementation?
I'm pretty fatigued on constantly providing references and sources in this thread but an example of what they've made availably publicly (second result Googling "snap coreml"): https://github.com/snap-research/EfficientFormer
It's extremely unclear how any of these sources corroborate your claim, particularly the first link. It's why I asked for clarification.
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I regularly use 4 languages on my iPhone and my autocorrect is completely broken. I can’t be bothered switching between keyboards, so the English keyboard has just completely lost the plot…
Yup same, that's why I am sticking with Android as well. I want multi-language auto-correct for my preferred languages _on the English QWERTY keyboard_.
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I'm pretty fatigued on constantly providing references and sources in this thread but an example of what they've made availably publicly (second result Googling "snap coreml"): https://github.com/snap-research/EfficientFormer
It's important to ask, because your sources are not referring to the same thing. The first is a reference to training techniques that have nothing to do with CoreML or Apple hardware. The second thing you've linked is a transformer model from 2022 that was ported to CoreML (alongside Pytorch, ONNX and 10+ other execution providers). It's extremely unclear how any of these sources corroborate your claim, particularly…
In my top comment I said "Snapchat, as one example". Feel free to search around to find others that were more transparent on implementation details, such as this random weight loss app from 2017:
https://loseitblog.com/2017/11/10/on-device-image-recognitio...
They actually include the following sentence: "While we are still awaiting the official launch of Tensorflow Lite, Apple released CoreML with iOS 11."
And another:
https://dl.acm.org/doi/abs/10.1145/3132787.3132815
If you're genuinely curious there are plenty of references of apps using CoreML in 2017 (again, Google) but at this point I'm pretty confident you're just (lazily) trying to win an argument.
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I'm pretty fatigued on constantly providing references and sources in this thread but an example of what they've made availably publicly (second result Googling "snap coreml"): https://github.com/snap-research/EfficientFormer
Your linked source says Snapchat has been using CoreML for neural network acceleration since 2022, which is not "since the early days" as you had originally claimed.
This thread has been exhausting, I suspect due to the religious war that is Apple/Google. As I've said time and time again - if you're genuinely curious Google is your friend here and it takes seconds to find any number of apps, projects, etc using CoreML in 2017.
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> You're confusing when Google started designing its own mobile SOC with when Android devices (including Google's) first started using neural network accelerators, which happened months earlier on Android than on iPhones. Apple (famously) doesn't announce until new functionality/devices are actually available. When they announce real people in the real world get it within a week if not less. A press release from Qual…
> A press release from Qualcomm that came a few months before Apple actually got it in people's hands This press release was for a new Tensorflow release for devices that had been shipping for many months before that. It was in people's hands long before Apple even announced anything similar. > If not that's on the Gboard team at Google for not supporting neural on iOS and Apple hardware that came far, far sooner. On…
What's interesting about this "debate" is my original links very, very, very clearly show the reality: Google being excited about launching the Pixel 6 (in 2021) with Tensor silicon - a first for them.
All anyone on this thread has done since is refuse to acknowledge how obvious and clear that is while deflecting and throwing things at the wall.