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I would like to agree with you. However, your vision hinges on this massive invisible infrastructure which is the cloud. Your phone didn't recognize the object

I would like to agree with you. However, your vision hinges on this massive invisible infrastructure which is the cloud. Your phone didn't recognize the object, you relied on a cloud service to do that for you. When you use such services for free, you'll end up with all kinds of legal compromises that don't necessarily benefit you as an individual in the long run. Your personal convenience is subservient to other goals that don't necessarily align with public interests at large. You could argue that the infrastructure will keep miniaturizing and one day you might not need those services. But that's not how things are currently evolving. Moreover, it will always take massive amounts of data to re-create the same models that are able to recognize patterns that are relevant to your specific context when you have a query. At the end of the day, it's about what trade offs you are willing to accept. Cloud services based on machine learning do give you a good amount of convenience, but then you have to be willing to accept the hidden costs as well.

codetrotter 7y ago
> Your phone didn't recognize the object, you relied on a cloud service to do that for you. In iOS 13 (which I am running), it is indeed my phone that does this. https://www.apple.com/ios/photos/pdf/Photos_Tech_Brief_Sept_2019.pdf https://www.apple.com/ios/photos/pdf/Photos_Tech_Brief_Sept_... (page 4) says: > Photos is enabled by powerful machine learning to deliver unique features like Memories, Search Suggestions, and For You. Photos analyzes every photo in a user’s photo library using on-device machine learning that delivers a personalized experience for each user. And this analysis is designed from the ground up with privacy in mind, with all of the processing done on device—and the results of this analysis are not shared with anyone, not even Apple. > Photos uses on-device processing to analyze each photo and video in a number of ways, including: > • Scene classification > Identifies objects, like an airplane or a bike, and scenes, like a cityscape or a zoo, that visually appear in a photo, using a multilabel network with over a thousand classes. > [...] The training itself as you point out, happens not on the local device but on the servers that Apple own. So that part you are right about, but that is to be expected. Otherwise, manual tagging by each individual user (as well as significantly more processing power) would be required after all in order to train the models in the first place.
- tialaramex 7y ago
  Yes, phones are now powerful enough that if the resulting ML core can be crushed down small enough you can just send that to the phone. My Pixel is set to passively identify every song it hears and display it on the lock screen. No Clown network service nonsense involved, Google built it for other reasons and went "Oh, this would fit on a phone. Cool, might as well".

codetrotter 7y ago

> Your phone didn't recognize the object, you relied on a cloud service to do that for you. In iOS 13 (which I am running), it is indeed my phone that does this. https://www.apple.com/ios/photos/pdf/Photos_Tech_Brief_Sept_2019.pdf https://www.apple.com/ios/photos/pdf/Photos_Tech_Brief_Sept_... (page 4) says: > Photos is enabled by powerful machine learning to deliver unique features like Memories, Search Suggestions, and For You. Photos analyzes every photo in a user’s photo library using on-device machine learning that delivers a personalized experience for each user. And this analysis is designed from the ground up with privacy in mind, with all of the processing done on device—and the results of this analysis are not shared with anyone, not even Apple. > Photos uses on-device processing to analyze each photo and video in a number of ways, including: > • Scene classification > Identifies objects, like an airplane or a bike, and scenes, like a cityscape or a zoo, that visually appear in a photo, using a multilabel network with over a thousand classes. > [...] The training itself as you point out, happens not on the local device but on the servers that Apple own. So that part you are right about, but that is to be expected. Otherwise, manual tagging by each individual user (as well as significantly more processing power) would be required after all in order to train the models in the first place.

tialaramex 7y ago
Yes, phones are now powerful enough that if the resulting ML core can be crushed down small enough you can just send that to the phone. My Pixel is set to passively identify every song it hears and display it on the lock screen. No Clown network service nonsense involved, Google built it for other reasons and went "Oh, this would fit on a phone. Cool, might as well".