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This piece is interesting because Apple was saying this all along but no one really believed them because it sounded like excuse making. But here JG is basicall

This piece is interesting because Apple was saying this all along but no one really believed them because it sounded like excuse making. But here JG is basically saying the same thing: >Yes, I understand this perception of bigger models in data centers somehow are more accurate, but it's actually wrong. It's actually technically wrong. It's better to run the model close to the data, rather than moving the data around. And whether that's location data—like what are you doing— [or] exercise data—what's the accelerometer doing in your phone—it's just better to be close to the source of the data, and so it's also privacy preserving. A few years ago was when this narrative was at its peak and I believe it was mostly because Google (and to a lesser extent Facebook) were talking about machine learning and AI in basically every public communication. What came of it? Were all the people who claimed Apple's privacy stance would leave them in the dust proven right? For one, being "good at machine learning" is like saying you're good at database technology. It's a building block, not a product. Maybe Google and Facebook are doing cutting edge research in the field, but so was Xerox PARC.

jeffbee 6y ago
It still sounds like excuse-making because Apple are behind in their own chosen terms: their competitor launched on-device machine translation a long time ago. The only remaining part of Apple’s AI privacy story is insinuation.
skybrian 6y ago
It's not my area, but I read Google's AI blog and they seem to be doing machine learning research that ends up in its phones, such as various camera improvements and offline Google Translate. It seems like it's the sort of thing you do when you can, but often it comes as a second phase after getting it to work in the data center. I didn't see anything in this article that was obviously unique to Apple.
- jolux 6y ago
  I think a lot of people have underrated the benefits Apple reaps in this area from being so far ahead in chip design and controlling their hardware. As regards to successfully productizing ML I’ve recently become convinced that Apple has been more successful at it than Google so far. Translation was already well within Google’s wheelhouse and they had been doing it for years, and their work with cameras is going to inevitably be hindered by the fact that they can’t depend on certain specs the way Apple can. I suspect the Pixel exists at least partially to prove that they understand those benefits.
  - aspenmayer 6y ago
    Pixel is Google being aware of their handicap in this in-house hardware prototyping and research area, and ironically and obviously and predictably for Google, they apply ML to it too. Apple can come at this same problem from the hardware and software sides all at once, with their own internal dev cycles aligning with the yearly iOS/iPadOS software drops, and iPhone/iPad hardware drops timed to a month or two of each other, year after year. Sure, it’s buggy as hell, but it still works better than Android. One would hope so, since you can’t do proper sideloading, as Android natively supports. Apple’s security argument is a childlike excuse for not doing one’s homework, not a reasonable justification for Apple unreasonably and intentionally feature-gating iOS and iPadOS devices. I’m an owner and I’m root. I fully control devices I own because that is a Natural Right of exclusive ownership of hardware devices under American First Sale Doctrine, which has also been recognized by the Library of Congress as Constitutionally-protected usage to preserve inalienable rights to nondiscrimination in computing devices. So Apple can take a hike. We’re getting what we need, and we’re getting bugs fixed. Jailbreaking has surfaced more 0days than jailbreak devs squirrel away for the next rainy day after iOS updates. We need native full root support, full stop. These research phones have landmines everywhere in the license agreements to get one, and I’m not re-buying an iPhone I already own to get half-assed fakeroot, especially when I’m already running as root on all the iPhones I ever bought. It’s not hard to avoid updates and save blobs, but should we really have to intentionally run old, known-insecure builds just to have r/w and root? Is this a mainframe? This is a joke. https://developer.apple.com/programs/security-research-device/ https://developer.apple.com/programs/security-research-devic... What is Apple even arguing against? It’s not reality, that ought to be clear. They’re arguing for increased and continued profits for Apple, at the cost of our rights being trampled and violated, and were supposed to accept that they had our best interests at heart via increased security? Tell me another joke. Benjamin Franklin and me’ll be here all life. The lack of free sideloading without a $99/year dev ticket is a joke. The scraps we get with 7 days between resigning apps is a joke. Devs are forced to abuse TestFlight to distribute apps which would otherwise be listed on App Store, if not for developers’ fears of App Store rejection, and potentially TestFlight revokes. There’s gotta be a better way, but jailbreaking is the best we’ve got, for now. To that point, the Jailbreak Bot on Telegram is a public service, as is saurik himself and the entire reddit community r/jailbreak. https://t.me/rJailbreakBot https://t.me/rJailbreakBot https://old.reddit.com/r/jailbreak https://old.reddit.com/r/jailbreak All that being said, Apple really is in a league of its own, with the market capitalization to back it up; Apple has features found in other companies while simultaneously being unlike every other company on Earth. [Current] https://developers.google.com/ml-kit/vision/object-detection/android https://developers.google.com/ml-kit/vision/object-detection... [2018] https://www.fastcompany.com/90247454/the-pixel-3-puts-googles-extraordinary-ai-in-your-pocket https://www.fastcompany.com/90247454/the-pixel-3-puts-google...
- DerSaidin 6y ago
  https://ai.googleblog.com/2020/05/federated-analytics-collaborative-data.html https://ai.googleblog.com/2020/05/federated-analytics-collab... https://federated.withgoogle.com/ https://federated.withgoogle.com/
tw04 6y ago
Well, google’s predictive keyboard and speech to text leave Apple in the dust. As does their voice assistant. So... yes?
- gbear605 6y ago
  I’m not an Apple fankid but the predictive keyboard and speech to text work wonderfully on my iPhone and I use Siri everyday with no problems. Google’s is probably better, but the different is not a meaningful one from what I can tell.
  - somethingwitty1 6y ago
    As someone that bought the first Android phone and now has an iPhone...it is extremely noticeable how much better Android is on these fronts. But depending on the person that gap may not be important. For me, it is night and day. I felt Google had a long way to go on these fronts, so I was stunned at just how bad Apple was :(.
    - nknealk 6y ago
      As someone who switched to iOS from android I’ll second this. Also googles keyboard swipe is WAY better than the iOS implementation
      - canofbars 6y ago
        Just switched from android to iOS and the major issue is it tries to correct things that are not real words. Somehow the android one was able to detect better when something is a typo of a common word or just something it doesn't know.
    - on_and_off 6y ago
      that's pretty much what I hear for anybody that has switched to iOS after a while on Android : they start by complaining about iOS's keyboard
  - 6y ago
moandcompany 6y ago
When it comes to machine learning, the subtlety here is that there are at least two sides or facets to machine learning: (1) training and (2) inference. It's fair to say that there are multiple areas for AI leadership. It is generally believed that: Model Creation (1) Those with the access to the best (which is not necessarily the most, but often believed to be) data have a strong starting point for training models; because of this Google, Facebook, and Microsoft have often been attributed to have this advantage due to the nature of their businesses. Model Application (2) Inference/prediction at the edge, e.g. on-device, is believed to be the best point for applying those models; this can be for a variety of reasons, including latency and other costs associated with sending model input data from edge sensors/devices. Some applications are entirely impractical or likely impossible to achieve without conducting inference on-device. Privacy-preservation is also a property of this approach. Depending on how you want to view this, this property could be a core design principle or a side-effect. Apple's hardware ecosystem approach and marketshare (i.e. iPhones) provide a strong starting point for making the technology ubiquitous for consumer experiences.
- llampx 6y ago
  Re: Prediction at the edge, I would think that it's better if there aren't going to be any updates to the model. Or if internet access is limited. Correct me if I'm wrong, but most of the ML inference actually takes place on the cloud nowadays, not on-device.
  - the_gipsy 6y ago
    IIRC, for example phone keyboards use federated learning, where the model is further trained locally. You don't want to send every word the user types, for privacy reasons and others. Some kind of "diff" of the local model can then be sent to the cloud at some time to add up to the base model. There is still an attack vector, you can infer a bit from the "diff", but you probably can't tell exactly what the user wrote.
  - tialaramex 6y ago
    Here's a nice example that like a lot of the best things is always passively present. My Pixel 2 knows what music it hears. There's a pop song playing, I kinda like it. I could pay attention to the lyrics and try to Google them or ask somebody that might know what it is... no need, I just look at my phone, "Break My Heart by Dua Lipa" it says on the lock screen. The phone will remember it heard this, so if I get home this evening and check what was that... oh, "Break My Heart by Dua Lipa". Google builds a model and sends it to phones that opted in to enable this service. It's not large, and I actually don't know how often it's updated - every day? Every week? Every month? No clue. But the actual matching happens on the device, where it's most useful and least privacy invading.

jeffbee 6y ago

It still sounds like excuse-making because Apple are behind in their own chosen terms: their competitor launched on-device machine translation a long time ago. The only remaining part of Apple’s AI privacy story is insinuation.

skybrian 6y ago

It's not my area, but I read Google's AI blog and they seem to be doing machine learning research that ends up in its phones, such as various camera improvements and offline Google Translate. It seems like it's the sort of thing you do when you can, but often it comes as a second phase after getting it to work in the data center. I didn't see anything in this article that was obviously unique to Apple.

jolux 6y ago
I think a lot of people have underrated the benefits Apple reaps in this area from being so far ahead in chip design and controlling their hardware. As regards to successfully productizing ML I’ve recently become convinced that Apple has been more successful at it than Google so far. Translation was already well within Google’s wheelhouse and they had been doing it for years, and their work with cameras is going to inevitably be hindered by the fact that they can’t depend on certain specs the way Apple can. I suspect the Pixel exists at least partially to prove that they understand those benefits.
- aspenmayer 6y ago
  Pixel is Google being aware of their handicap in this in-house hardware prototyping and research area, and ironically and obviously and predictably for Google, they apply ML to it too. Apple can come at this same problem from the hardware and software sides all at once, with their own internal dev cycles aligning with the yearly iOS/iPadOS software drops, and iPhone/iPad hardware drops timed to a month or two of each other, year after year. Sure, it’s buggy as hell, but it still works better than Android. One would hope so, since you can’t do proper sideloading, as Android natively supports. Apple’s security argument is a childlike excuse for not doing one’s homework, not a reasonable justification for Apple unreasonably and intentionally feature-gating iOS and iPadOS devices. I’m an owner and I’m root. I fully control devices I own because that is a Natural Right of exclusive ownership of hardware devices under American First Sale Doctrine, which has also been recognized by the Library of Congress as Constitutionally-protected usage to preserve inalienable rights to nondiscrimination in computing devices. So Apple can take a hike. We’re getting what we need, and we’re getting bugs fixed. Jailbreaking has surfaced more 0days than jailbreak devs squirrel away for the next rainy day after iOS updates. We need native full root support, full stop. These research phones have landmines everywhere in the license agreements to get one, and I’m not re-buying an iPhone I already own to get half-assed fakeroot, especially when I’m already running as root on all the iPhones I ever bought. It’s not hard to avoid updates and save blobs, but should we really have to intentionally run old, known-insecure builds just to have r/w and root? Is this a mainframe? This is a joke. https://developer.apple.com/programs/security-research-device/ https://developer.apple.com/programs/security-research-devic... What is Apple even arguing against? It’s not reality, that ought to be clear. They’re arguing for increased and continued profits for Apple, at the cost of our rights being trampled and violated, and were supposed to accept that they had our best interests at heart via increased security? Tell me another joke. Benjamin Franklin and me’ll be here all life. The lack of free sideloading without a $99/year dev ticket is a joke. The scraps we get with 7 days between resigning apps is a joke. Devs are forced to abuse TestFlight to distribute apps which would otherwise be listed on App Store, if not for developers’ fears of App Store rejection, and potentially TestFlight revokes. There’s gotta be a better way, but jailbreaking is the best we’ve got, for now. To that point, the Jailbreak Bot on Telegram is a public service, as is saurik himself and the entire reddit community r/jailbreak. https://t.me/rJailbreakBot https://t.me/rJailbreakBot https://old.reddit.com/r/jailbreak https://old.reddit.com/r/jailbreak All that being said, Apple really is in a league of its own, with the market capitalization to back it up; Apple has features found in other companies while simultaneously being unlike every other company on Earth. [Current] https://developers.google.com/ml-kit/vision/object-detection/android https://developers.google.com/ml-kit/vision/object-detection... [2018] https://www.fastcompany.com/90247454/the-pixel-3-puts-googles-extraordinary-ai-in-your-pocket https://www.fastcompany.com/90247454/the-pixel-3-puts-google...
DerSaidin 6y ago
https://ai.googleblog.com/2020/05/federated-analytics-collaborative-data.html https://ai.googleblog.com/2020/05/federated-analytics-collab... https://federated.withgoogle.com/ https://federated.withgoogle.com/

tw04 6y ago

Well, google’s predictive keyboard and speech to text leave Apple in the dust. As does their voice assistant. So... yes?

gbear605 6y ago
I’m not an Apple fankid but the predictive keyboard and speech to text work wonderfully on my iPhone and I use Siri everyday with no problems. Google’s is probably better, but the different is not a meaningful one from what I can tell.
- somethingwitty1 6y ago
  As someone that bought the first Android phone and now has an iPhone...it is extremely noticeable how much better Android is on these fronts. But depending on the person that gap may not be important. For me, it is night and day. I felt Google had a long way to go on these fronts, so I was stunned at just how bad Apple was :(.
  - nknealk 6y ago
    As someone who switched to iOS from android I’ll second this. Also googles keyboard swipe is WAY better than the iOS implementation
    - canofbars 6y ago
      Just switched from android to iOS and the major issue is it tries to correct things that are not real words. Somehow the android one was able to detect better when something is a typo of a common word or just something it doesn't know.
  - on_and_off 6y ago
    that's pretty much what I hear for anybody that has switched to iOS after a while on Android : they start by complaining about iOS's keyboard
- 6y ago

moandcompany 6y ago

When it comes to machine learning, the subtlety here is that there are at least two sides or facets to machine learning: (1) training and (2) inference. It's fair to say that there are multiple areas for AI leadership. It is generally believed that: Model Creation (1) Those with the access to the best (which is not necessarily the most, but often believed to be) data have a strong starting point for training models; because of this Google, Facebook, and Microsoft have often been attributed to have this advantage due to the nature of their businesses. Model Application (2) Inference/prediction at the edge, e.g. on-device, is believed to be the best point for applying those models; this can be for a variety of reasons, including latency and other costs associated with sending model input data from edge sensors/devices. Some applications are entirely impractical or likely impossible to achieve without conducting inference on-device. Privacy-preservation is also a property of this approach. Depending on how you want to view this, this property could be a core design principle or a side-effect. Apple's hardware ecosystem approach and marketshare (i.e. iPhones) provide a strong starting point for making the technology ubiquitous for consumer experiences.

llampx 6y ago
Re: Prediction at the edge, I would think that it's better if there aren't going to be any updates to the model. Or if internet access is limited. Correct me if I'm wrong, but most of the ML inference actually takes place on the cloud nowadays, not on-device.
- the_gipsy 6y ago
  IIRC, for example phone keyboards use federated learning, where the model is further trained locally. You don't want to send every word the user types, for privacy reasons and others. Some kind of "diff" of the local model can then be sent to the cloud at some time to add up to the base model. There is still an attack vector, you can infer a bit from the "diff", but you probably can't tell exactly what the user wrote.
- tialaramex 6y ago
  Here's a nice example that like a lot of the best things is always passively present. My Pixel 2 knows what music it hears. There's a pop song playing, I kinda like it. I could pay attention to the lyrics and try to Google them or ask somebody that might know what it is... no need, I just look at my phone, "Break My Heart by Dua Lipa" it says on the lock screen. The phone will remember it heard this, so if I get home this evening and check what was that... oh, "Break My Heart by Dua Lipa". Google builds a model and sends it to phones that opted in to enable this service. It's not large, and I actually don't know how often it's updated - every day? Every week? Every month? No clue. But the actual matching happens on the device, where it's most useful and least privacy invading.