Heck, they've been doing machine learning since at least 2004, when they added Latent Semantic Analysis for junk mail filtering to the Mail app. And does anybody remember iTunes Genius (collaborative filtering on your playlists in the cloud)?

I think Apple has traditionally done a really good job of keeping the technology used under wraps, for better or worse.

The Apple Newton had handwriting recognition in the early 90's.

It was technology acquired from a Russian company called ParaGraph.(http://articles.chicagotribune.com/1993-07-26/business/93072...)

Did Genius use AI? I thought it was more of a collaborative filtering feature where it used other people's playlists to build relationships between songs.

Congrats, you just described all of modern AI!

Do Bayes/Kalman filters count as (super simplistic) A.I. somehow?

Yes.

The only reason why machine learning was not called AI, is because funding for research into AI dried up in the AI winter.

Recently Google decided to revive the AI term, and here we are.

It always bugs me when people throw AI buzzword around when they are talking about machine learning.

Nah, it doesn't count. Unless you are a buzzword person.

AI is data science but not all data science is AI.

They aren't. Marketing makes them AI though, but they aren't.

Just the same way folks think they have 'big data'.

AI effect maybe?

"As soon as AI successfully solves a problem, the problem is no longer a part of AI."

https://en.wikipedia.org/wiki/AI_effect

This attitude I encountered already on HN: "By discounting artificial intelligence people can continue to feel unique and special."

I found this a nice way to communicate the difference between AI, ML and Data Science [0].

TL;DR

AI produces actions

ML produces predictions

Data Science produces insights

[0] http://varianceexplained.org/r/ds-ml-ai/

Well, I would say there is not much difference... but AI, sounds much more PR

Isn’t an action just the highest probability of a set of actions per given time though?

There's a chapter on Bayesian stuff (maybe more, the book is at home) in "AI a Modern Approach" so I'd say the answer is yes. I remember it vividly because they use a dentist/toothache example :P

I know "it's in AIAMA" is hardly a formal definition but it's good enough for me.

Most everything described as “AI” these days involves training data of some kind.

Collaborative filtering is machine learning, so if you consider AI machine learning, definitely yes.

There is nothing intelligent about machine learning. It’s cool but far from intelligent. AI buzzword to describe machin learning is equivalent to people calling computers cpus. Let’s me know really quickly just how clueless they are.

If you consider machine learning a type of AI.

Pretty much no one on the market are doing AI that couldn’t be called machine learning. It’s all about the buzzwords and remarketing...

IMO a calculator is AI; prove me wrong.

If a calculator is AI then a wrench may as well be AI. There is huge disagreement over what ~really~ is Artificial Intelligence so the argument is pointless without a chosen definition.

Is that really true? Long ago weak AI was distinguished from strong AI.

Artificial yes, intelligence I dont think so.

The "O" part can ("in my Opinion") cannot be proved or disproved.

If it's indeed so in your opinion, it is so (in your opinion).

Uh, opinions can still be proven wrong. Contrary to public postmodern belief, opinions are falsifiable.

Uh, missed the point.

An opinion can be proved wrong.

The statement "in my opinion, X is Y" cannot.

Wow, so your comment was even more useless. Or was it a joke that I didn't get? The challenge was "prove me wrong" (with the opinion that I just uttered), not "disprove that this is my opinion".

>Wow, so your comment was even more useless.

It was technically correct, which is the best kind of correct.

https://www.cheerupemokid.com/comic/rescue

> Heck, they've been doing machine learning since at least 2004, when they added Latent Semantic Analysis for junk mail filtering to the Mail app.

LSA is a knowledge (text) representation technique not machine learning.

Fair point, I mentioned it because I was thinking they combined the LSA with some form of classifier that got trained as you marked messages as spam (or told it when it misclassified), I'm not sure what Apple's full implementation was though.

Yup - it seems like they used Adaptive Latent Semantic Analysis as a dimensionality reduction technique to represent knowledge[ 0]. LSA helped them use the filtering technique on the device itself as it was not heavy.

[0] https://www.youtube.com/watch?v=7N8b3NZSJoY&t=1m21s

AI is used all over the place in iOS. In a number of cases it is actually worse than not having it.

For example if you force touch the Maps icon it uses a ML model to determine what favourite location to show.

Unfortunately it takes a few seconds when really just asking the user for a favourite location would've been better.

allegedly "machine learning" was the reason behind the unicode nonsense text replacement on iOS six months ago.

Apple’s computer vision search functionality in Photos works much better than Google’s solution for me

Apple has actually really really fallen behind. Their speech reco is shit. Their maps are super shit. Siri search is so bad and gets in way all the time that I turn it off right away on my iOS devices. Their photo management and image search is literally circa 2000. The spell check and completion is circa 2007 (ie no significant improvement since first enabled). They can’t get right even about when to auto-turn caps. Large number of badly spelled and misunderstood messages in the world can now be attributed to utter incompetence of Apple in AI arena.

To me it wasn’t a surprise that Apple finally got out of self driving car project. They simply don’t have cultural aspects to undertake such a massive AI heavy project including hiring and motivating the necessary talent. This is prime example of how money can’t help if you don’t have right culture. They focused on design so much that ML and AI were relavent only to the extent it helped design. Thing is that such pragmatic view doesn’t work in highly exploratory and rapidly advancing field where 90% of the things have no apparent business use but you do need those in the hope of cross-pollination with other 10%.

Apple is not an AI company and is not setup to be an AI company. There will be massive cultural shift that would be needed to turn this around.

Apple Maps has improved significantly over the past few years. I now have no issues using it for every situation, except for some place where they don’t have transit info. Still need google maps for that.