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How AI and Machine Learning Work at Apple

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Re: How AI and Machine Learning Work at Apple

#121

Post by sangnoir »

dummyacc111 wrote: post #120
sangnoir wrote: post #68

Earlier quoted context omitted.

> It explicitly talks about how they've accomplished a lot of this without violating their users' privacy. My question are: A. who is violating user's privacy, B. How is Apple any different[1] from them, besides proclaiming they aren't violating privacy? 1. Some data is collected from the device and sent to a server for processing. Until Apple does something truly radical (like 100% encrypted information that is proc…

> Until Apple does something truly radical (like 100% encrypted information that is processing on-device) This is exactly what Apple does, which should answer question B.

> This is exactly what Apple does

That is not true, even the puff-piece article admits as much if you read it carefully. This can be proven trivially: is Siri processed locally?

Re: How AI and Machine Learning Work at Apple

#123

Post by koko775 »

posterboy wrote: post #5
soperj wrote: post #4

Earlier quoted context omitted.

That's what they did with osx.

OSX is much more than the kernel. Darwin is open source, even. What are you talking about?

The truth of that statement is dwindling rapidly with time, however. XPC is closed-source, and with launchd being subsumed into it as it has become more important to macOS's system, Darwin hasn't had a working init system for years.

It's been effectively TiVo'ed, or turned into shared-source-ish instead of open enough to run it as a real OS.

Re: How AI and Machine Learning Work at Apple

#124

Post by leereeves »

Chronic9q wrote: post #103
leereeves wrote: post #88

Earlier quoted context omitted.

In the article, Apple spun that as an advantage. > “Our practices tend to reinforce a natural selection bias — those who are interested in working as a team to deliver a great product versus those whose primary motivation is publishing,” says Federighi. And I think they may be right. Researchers often aren't the best product creators.

> Researchers often aren't the best product creators. You NEED researchers to build a robust autonomous vehicle or speech recognition system. Hell, you know how many electrical and materials scientists they have working on the iPhone? Physical products actually requires science and research. Designing a responsive landing page does not.

You need people who understand the science but whose primary focus is developing the product, not developing new theory.

Edison and Ford vs Einstein and Faraday.

Re: How AI and Machine Learning Work at Apple

#125

Post by leereeves »

coldtea wrote: post #89
leereeves wrote: post #19

Earlier quoted context omitted.

Apple's core "product" is the user experience. Darwin is open source, Carbon and Cocoa are not. I think that philosophy will continue as they use ML tools. They might share the ML equivalent of plumbing like Webkit/LLVM/Swift, but probably not improvements to the user experience like Siri's brain.

> Apple's core "product" is the user experience. Darwin is open source, Carbon and Cocoa are not. So? Why should they open source and commoditize their core product? Besides, I don't know any company that did it and got much out of it, except for some gratitude from OSS fans.

I'm not saying they should, I'm saying they wouldn't (and probably shouldn't).

Re: How AI and Machine Learning Work at Apple

#126

Post by Twisell »

throwaway287391 wrote: post #48
mathattack wrote: post #13

Earlier quoted context omitted.

Some companies engage academia, many others do not. I find it very surprising how willing companies like Microsoft and Google are to let their best and brightest invest in publishing. I get the long term benefit, but in most companies secrecy is the default.

To me it's much more surprising that Apple and other companies refuse to allow publishing. Anyone in AI who wants to continue to be recognized in and remain friends with others in the field and advance their career should absolutely refuse to go anywhere like Apple, unless they plan to stay at that one company their entire life. It's amazing how frustrating it is trying to talk to Apple employees at conferences -- at…

A friend of mine work in medical drugs research. Secrecy is definitely the norm in this field and they even prefer to keep formula in a safe than publish a patent, because they think patent system is not protective enough to get they R&D money back.

Now that all come down to the same old paradox. The current patent system encourage patent troll and discourage real innovators to publish because they are too easily copied.

One alternative is open source, but when huge R&D costs are involved it's maybe not the best idea. I think Apple is currently doing a great mix, they work on some project with OpenSource (WebKit, Swift) were community feedback is important... and they keep innovative R&D technics under secrecy to monetize them.

Re: How AI and Machine Learning Work at Apple

#127

Post by sangnoir »

leereeves wrote: post #88
sangnoir wrote: post #71

Earlier quoted context omitted.

> The field might lose out (but there are always free riders) but does Apple? Yes - those in the field who prefer to publish will not be willing to join Apple. How much of an opportunity cost this is to Apple remains an open question.

In the article, Apple spun that as an advantage. > “Our practices tend to reinforce a natural selection bias — those who are interested in working as a team to deliver a great product versus those whose primary motivation is publishing,” says Federighi. And I think they may be right. Researchers often aren't the best product creators.

> “Our practices tend to reinforce a natural selection bias — those who are interested in working as a team to deliver a great product versus those whose primary motivation is publishing,”

This is a blatantly false dichotomy: there's nothing about publishing that precludes anyone from "working as a team to deliver a great product"

> Researchers often aren't the best product creators.

Tell that to Andrew Ng!

Re: How AI and Machine Learning Work at Apple

#128

Post by castell »

Is there a way to op-out of this on iOS and macOS? That's really scary.

ML and AI on OS-level should run decentral on the device itself, and don't leak data at all. The spirit of the 1990s was that way, and we older desktop software works fine that way (even on Pentium 1 hardware), so it would run like a piece of cake on a modern smartphone.

The "differential privacy" technology may sound good, but without an independent audit who knows how good it works.

Re: How AI and Machine Learning Work at Apple

#129

Post by jomamaxx »

wavefunction wrote: post #105
jomamaxx wrote: post #73

Earlier quoted context omitted.

"real question is why they avoid the research community so strongly." I think it's within their DNA. They are a very secretive company for a lot of historical reasons. Company culture is what companies are ... they are the social rules built into the organization that are very difficult to change once established. Apple is within their moral right to do what they are doing. There are different approaches taken by oth…

>>They are a very secretive company for a lot of historical reasons. It's true, they saw what happened to Xerox PARC's ground-breaking UI work...

Every companies copy other companies innovations.

Smartphones would not exist unless BlackBerry created the market for them.

But they are secretive not for that reason - they are secretive because they want to announce and present things on their own terms. They don't want leakage pre-product.

Re: How AI and Machine Learning Work at Apple

#130

Post by leereeves »

sangnoir wrote: post #127
leereeves wrote: post #88

Earlier quoted context omitted.

In the article, Apple spun that as an advantage. > “Our practices tend to reinforce a natural selection bias — those who are interested in working as a team to deliver a great product versus those whose primary motivation is publishing,” says Federighi. And I think they may be right. Researchers often aren't the best product creators.

> “Our practices tend to reinforce a natural selection bias — those who are interested in working as a team to deliver a great product versus those whose primary motivation is publishing,” This is a blatantly false dichotomy: there's nothing about publishing that precludes anyone from "working as a team to deliver a great product" > Researchers often aren't the best product creators. Tell that to Andrew Ng!

Andrew Ng is a great example.

He's made enormous contributions to human knowledge, but doesn't seem to be interested in the hard work of bringing a product to market.

He even left Coursera to return to theory.

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