3 ms·

How does Snapchat use it?

kkielhofner 3y ago
https://qz.com/1005879/snapchat-quietly-revealed-how-it-can-put-ai-on-your-phone https://qz.com/1005879/snapchat-quietly-revealed-how-it-can-...
- smoldesu 3y ago
  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?
  - kkielhofner 3y ago
    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 https://github.com/snap-research/EfficientFormer
    - lern_too_spel 3y ago
      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.
      - kkielhofner 3y ago
        The link was provided to refute "Snap uses CPU". The repo is from 2022 but do you really think Snap publishes breaking code and papers on new, novel, and highly competitive functionality? The snap-research GH org wasn't even created until 2020. Do you really think they weren't doing anything before that because it's not on Github? 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.
        lern_too_spel 3y ago
        It's bizarre how you keep refusing to acknowledge you were wrong. You made specific claims that were specifically refuted and now you're "yeah, butting" wildly to try to somehow win an argument you started by trying to find something else that Apple might be better at. As far as I'm concerned, the war has always (since the mid-80s) been Apple versus everybody else. Nobody else makes clearly wrong claims like the comment at the start of this thread. What yanks my chain is that Apple is against user control, and we as developers should be above falling for their marketing that they're first or best when they very clearly aren't.
    - smoldesu 3y ago
      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 the first link. It's why I asked for clarification.
      - kkielhofner 3y ago
        Is it really so hard to believe that the technical details of Snap's implementation just may not have been made publicly available at the time they deployed it? It's not as though they're known for running a breaking engineering blog like some smaller companies... Speaking of which: 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-recognition/ 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 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.
        deleted 3y ago
        [deleted]

https://qz.com/1005879/snapchat-quietly-revealed-how-it-can-put-ai-on-your-phone https://qz.com/1005879/snapchat-quietly-revealed-how-it-can-...

smoldesu 3y ago
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?
- kkielhofner 3y ago
  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 https://github.com/snap-research/EfficientFormer
  - lern_too_spel 3y ago
    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.
    - kkielhofner 3y ago
      The link was provided to refute "Snap uses CPU". The repo is from 2022 but do you really think Snap publishes breaking code and papers on new, novel, and highly competitive functionality? The snap-research GH org wasn't even created until 2020. Do you really think they weren't doing anything before that because it's not on Github? 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.
      - lern_too_spel 3y ago
        It's bizarre how you keep refusing to acknowledge you were wrong. You made specific claims that were specifically refuted and now you're "yeah, butting" wildly to try to somehow win an argument you started by trying to find something else that Apple might be better at. As far as I'm concerned, the war has always (since the mid-80s) been Apple versus everybody else. Nobody else makes clearly wrong claims like the comment at the start of this thread. What yanks my chain is that Apple is against user control, and we as developers should be above falling for their marketing that they're first or best when they very clearly aren't.
  - smoldesu 3y ago
    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 the first link. It's why I asked for clarification.
    - kkielhofner 3y ago
      Is it really so hard to believe that the technical details of Snap's implementation just may not have been made publicly available at the time they deployed it? It's not as though they're known for running a breaking engineering blog like some smaller companies... Speaking of which: 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-recognition/ 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 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.
      - deleted 3y ago
        [deleted]