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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

#21

I like how Apple can't win here. If they publish, they aren't doing anything new and they haven't innovated since Steve died, and they should really just give up because there's obviously no point to anything they do and hasn't been since 1997. If they don't publish, they're evil secretive bastards who don't contribute to the ML community and probably drown puppies or something because who knows what goes on behind c…

> if people

Your mistake here is thinking "people" are one coherent group when in fact what you're describing here is (probably) two different ends of a polarised discussion! You're probably in a more moderate central position (generally satisfied iphone owner). It may or may not be a good thing that apple is so controversial that they provoke such vigorous discussion (my personal take is that it is), but that not everybody is satisfied with "good enough" isn't a reason to silence discussion. Particularly when as a brand they're pitched as high end rather than just good enough.

Re: How AI and Machine Learning Work at Apple

#22

I like how Apple can't win here. If they publish, they aren't doing anything new and they haven't innovated since Steve died, and they should really just give up because there's obviously no point to anything they do and hasn't been since 1997. If they don't publish, they're evil secretive bastards who don't contribute to the ML community and probably drown puppies or something because who knows what goes on behind c…

People aren't just one person, they have diverging opinions. You can't expect everyone to settle on one narrative. Plus, you know, trolls.

It basically happens to every company, nothing to be sad about.

Re: How AI and Machine Learning Work at Apple

#23

Earlier quoted context omitted.

How much of Apple's investment in OS X was in Darwin, and how much was in proprietary technology? Apple built a proprietary product using open source technology, and are now building proprietary products using open ML research. But it seems they're doing so for their own profit, not to benefit the open source and research communities.

That's what the top level comment said, you are only adding noise.

I added a question.

My impression is that Apple invested vastly more in the closed parts of OS X than the open parts.

Re: How AI and Machine Learning Work at Apple

#24
post #8

I have a big problem with articles like this. Apple's PR is notorious for cracking the whip, which means that the "inside story", if they give it to you, comes with a warning to the journalist to behave and be nice. Levy's piece is generous with flattery and cautious with criticism. He quotes Kaplan and Etzioni high and briefly in the piece, and spends the rest of it refuting them. Apple will give him another inside…

Good comment - a few thoughts:

AlphaGo is impressive no doubt but has DeepMind done anything really key to Google's bottom line yet? A lot of the really sweet stuff they do doesn't have immediate commercial utility that I can see. Apple might be waiting to strike once Google has found the killer app (remember they're never really first at anything and focus holistically on the product).

Apple is benefiting from other companies releasing their research. If everyone but Apple releases the community is nearly as good, and Apple gets the pick of external and internal research while not needing to give up any of their own ideas. I know they send people to conferences and it can be a bit weird talking to someone who won't tell you anything about what they do.

Regarding researchers, I don't know of any top trend setters who've joined but they do have some very good applied ML people through direct- or aqui-hires.

Tl;dr: Apple doing what they usually do and keeping their powder dry/free loading off other's work until they can execute the product.

Re: How AI and Machine Learning Work at Apple

#26
post #24
post #8

I have a big problem with articles like this. Apple's PR is notorious for cracking the whip, which means that the "inside story", if they give it to you, comes with a warning to the journalist to behave and be nice. Levy's piece is generous with flattery and cautious with criticism. He quotes Kaplan and Etzioni high and briefly in the piece, and spends the rest of it refuting them. Apple will give him another inside…

Good comment - a few thoughts: AlphaGo is impressive no doubt but has DeepMind done anything really key to Google's bottom line yet? A lot of the really sweet stuff they do doesn't have immediate commercial utility that I can see. Apple might be waiting to strike once Google has found the killer app (remember they're never really first at anything and focus holistically on the product). Apple is benefiting from other…

DeepMind reduced Google data center cooling bill by 40% in an experiment. If this effect is real, it probably more than justified the $500m tag Google paid to acquire DeepMind. Google might not have come up with a killer app, but perhaps the real killer app is not in the consumer space.

https://deepmind.com/blog

https://news.ycombinator.com/item?id=12126298

Re: How AI and Machine Learning Work at Apple

#27

I like how Apple can't win here. If they publish, they aren't doing anything new and they haven't innovated since Steve died, and they should really just give up because there's obviously no point to anything they do and hasn't been since 1997. If they don't publish, they're evil secretive bastards who don't contribute to the ML community and probably drown puppies or something because who knows what goes on behind c…

If they were serious, they'd provide objective evidence for their claims. Papers, source code, numbers. Not "we have the biggest, baddest GPU farm" and refuse to say any more as policy. Under this veil of secrecy and doubletalk, all they have is marketing: Trust the brand rather than objective reality.

Many other companies are mature enough to show their cards but Apple keeps declaring victory. Apple writes its own narrative instead of participating.

There are mature ways for this to shake out and they don't include your strawman dichotomy.

Re: How AI and Machine Learning Work at Apple

#28
post #2

None of this really answers the overlying question that Jerry Kaplan and Oren Etzioni raised. The question raised by most in the field isn't whether Apple use AI/ML internally, the real question is why they avoid the research community so strongly. For me, the greatest thing about the ML/AI community is how open it is and how strong a sense of camaraderie there is between people across the entire field, regardless of…

>the real question is why they avoid the research community so strongly.

Along the same vein, does Apple even employ any 'brand-name' researchers? From what I've seen, all they do is take research invented somewhere else and just apply it. I think Alex Acero is the biggest recognizable researcher that Apple employs.

So to answer your question, they don't publish and don't attend conferences because they simply don't have many researchers on board.

Re: How AI and Machine Learning Work at Apple

#29
post #6
post #2

None of this really answers the overlying question that Jerry Kaplan and Oren Etzioni raised. The question raised by most in the field isn't whether Apple use AI/ML internally, the real question is why they avoid the research community so strongly. For me, the greatest thing about the ML/AI community is how open it is and how strong a sense of camaraderie there is between people across the entire field, regardless of…

What makes you think this is self-congratulation? This is a response to Marco Arment, Ben Thompson, and other pundits (largely spurred by the PR efforts of Google and to a lesser extent Facebook and Microsoft) who claim that Apple is "behind" in this field or that it somehow poses an existential threat to Apple. This is Apple saying "uh no". They'd be perfectly fine with not talking about it as they've done until now…

This article lacks any real evidence they're ahead though, which is essentially equivalent to "behind" if (a) the majority of the advances are democratized by your competitors and (b) you lack the ability to attract top tier talent. If AI/ML is an existential threat to Apple, then this article doesn't provide any comfort beyond being a PR puff piece.

The talent war for AI/ML is truly insane. Given that the top researchers and engineers can get similar benefits at other entities, whilst also continuing to publish code and research out in the open, Apple aren't that attractive.

They may try compensating for this via acquisitions but that still leaves a fundamental issue when it comes to long term retention.

As I mentioned before, this is a fairly universal trait. Many come from academia or have open source affiliations / rely on open source tools for their skill set, so the idea of putting their ideas out there to be used, ...

Re: How AI and Machine Learning Work at Apple

#30
Off topic a bit, but this article makes me wonder where does one start with Deep/Machine Learning/AI? I've seen a few posts the past few days talking about the topic (Deep Learning with Python, etc.), but what are the core requirements regarding math, statistics, programming, etc? Where should a web developer start?
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