This is a smart move. Apple seems so far behind in generative AI it's making Google look innovative.
Apple is a best-in-class second mover.
With the clusterfuck that has been generative AI (from OpenAI’s corporate drama to Google renaming and reörganizing their products every fifteen minutes) this seems prescient, with the only savvy player so far being Microsoft.
Possibly. On the consumer side, they’re in their own niches. What will get interesting is how Apple lets developers hook into the on-device AI, or one that’s running on its own metal.
Adobe seems to be the only one with an empowered product team that's consistently finding sensible and profitable uses for machine learning.
Edit: And on my iPhone, the offline photo categorization and image OCR
A careful plan for a product would be less hamfisted and include more flexibility to deal with the backlash.
Apple's biggest successes have come from being the first mover in a brand new space.
Apple II, Macintosh, iPod, iPhone, iPad, Airpods, Watch were all category defining rather than "me too" products.
In fact Apple is terrible at throwing its hat into an already crowded space, and doubly so when it comes to software.
iPod was released in 2001. Portable MP3 players were released in the late 90s.
I would say that only one of the examples you gave was unambiguously the first mover in a brand new space. I will give you "category defining", though.
For example, the iPod had tons of competitors already in the field when it launched.
Airpods were not even close to the first wireless earbuds.
One of the Apple Watch's major competitors (fitbit) launched 8 years prior. The first smartwatch that could sync with a computer came out in the 80s.
The iPad came like a decade after Microsoft's first major tablet push. ATT and Sony/Magicap and Apple all released "smart tablets" in the early 90s.
The iPhone was not the first capacitive touch screen smartphone, and certainly not the first smartphone - over a decade late to that game.
The Macintosh was (sort of) a sequel to Apple's own Lisa, which itself was also not a first mover. The Mac was incredibly innovative and successful, but was preceded by the LISA, PERQ, Alto, various Lisp Machines.
> In fact Apple is terrible at throwing its hat into an already crowded space, and doubly so when it comes to software.
Couldn't be farther from the truth.
Apple Watch was a success because it used iPhone as a moat. iPad was built upon iPhone's foundation.
Apple is - by and large - "an iPhone company".
I was already using smart phones, handhelds, tablets, etc, for years before the iPhone. Apple entered an existing category.
The iPhone wasn't even the first capacitive touchscreen phone.
https://en.wikipedia.org/wiki/LG_Prada
Back in 2007 it was not seen as a completely new category or truly original. It was a variation within an existing category. At the time we did not think it was revolutionary, but of course it became the new standard.
Before they became an "iPhone company" they were an "iPod company", and that was also an existing category when it launched.
Wow, you really got their asses. Who could forget Microsoft's first major tablet push.
you think when the iPhone came out the space was not crowded? You think they defined the category? Jobs himself have put up a number of smartphones in his 2007 presentation. Yes, the iPhone was far, very far better but it was definitely not a first.
Same thing with the iPod vs Diamond Rio MP3 layers.
As for the Watch, gosh, I do not even know where to start. Pebble Kickstarter two years before that? Two generations of the Samsung Galaxy Gear came out well before the Apple Watch.
They didn't take whatever was out there in the market and copy it/make it incrementally better. They started from scratch and built something drastically different and better than the rest. Same for iPod (yes there were plenty of cheap MP3 players out there, but none of them were comparable), Airpods and all the rest.
It wasn't that far ahead when it first launched. Very basic functionality. But a few versions later it was the end of Nokia and Blackberry.
https://www.mobilegazette.com/2007-review-07x12x12.htm
"No handset polarised opinions during 2007 more than the Apple iPhone. Although it has many good points, the list of bad points is equally impressive. The iPhone lacks 3G, the camera is only two megapixels and lacks autofocus and flash, you cannot send MMS messages, third party applications are not allowed, the battery is not replaceable and it is absurdly expensive."
Literally EVERY single example you listed were markets that already existed before Apple entered them (except maybe the Mac but that was so long ago who cares). MP3 players existed before the iPod. Smartphones existed before the iPhone. Wireless earbuds existed before Airpods. Tablets existed before the iPad. Smartwatches existed before the Apple Watch. VR goggles existed before Vision. Smartrings existed before the Apple Ring (just wait, its coming).
Their skill isn't in being a first mover. Their skill is being a second, or even last, mover into a space that has untapped potential, and unlocking that potential (for both their benefit and competitors).
That's not savvy that's desperate.
Apple can arrive last to a product market. They can take six years of iterative releases to refine their vision on a product market. They will still dominate that market. Cue the "they can't keep getting away with this" meme, because this happens with EVERY PRODUCT THEY RELEASE and these people still keep thinking this time will be different.
The whole "Siri sucks" thing is also hilarious, because you have to ask: So? So what? Apple, Google, and Amazon invested billions upon billions into these systems (Amazon especially). Then LLMs came around and are absolutely eating their same lunch ten times faster. Apple, again, looks like a genius (intentionally, or far more likely, not). They didn't over-invest. They're not laying off a thousand people from the Alexa division [1], or removing a ton of Google Assistant features [2], or releasing hardware no one is buying. They built exactly enough of a voice assistant to be competitive throughout the 2010s, and now its time for the next generation of all these things anyway.
[1] https://apnews.com/article/amazon-alexa-job-cuts-generative-...
[2] https://www.theverge.com/2024/1/11/24034262/google-assistant...
EDIT: what I really mean is what makes people think this is a commercially viable thing to spend time and money on? Like, say one of these companies hits some magic jackpot and discovers "AGI".. then what? Is that worth money, somehow?
EDIT: actually, I overcommitted a little bit with "really good Wikipedia search". I can rely on Wikipedia search to not invent stuff from whole cloth and try to pass it off as results.
The idea here is that it won't stop at 25%. Even if you were to accept this premise, maybe you're just thinking about chat gpt 3.5 or 4. But it really doesn't take a lot more imagination to think about what version 7 or 30 might do.
The same goes for the image/video generation models. Smaller production studios might forgo several artist hires and just generate the stuff they need. Large ones will have an enormous pool of unemployed creatives and won't have to pay them much at all.
Auto-completing function bodies with stack overflow content is cool! I'm not trying to say this technology isn't doing anything. It's clearly doing something "cool". But that doesn't necessarily actually make anyone more productive. That seems like an extraordinary claim (at least based on my own small experience working with it), so I'd expect to see some extraordinary evidence.
I've seen new colleagues use co-pilot at work and it definitely increases the amount of stuff they can now figure out for themselves within a given time.
Better keyboard text prediction and power management. A competent Siri.
How does "generative AI" help ?
This, but it is really exciting because for the first time, you can just tell your computer what to do. Not just a given set of tasks, but e.g. "go to my gym and book a slot with my personal trainer"; "contact Shauna and set up a meeting to talk about X, then book me tickets to get there".
Think about how much monkey-work we all do with our smartphones. We might look back in 10 years and laugh at the idea that we had to press buttons all the time.
But iOS users don't really know what they're missing from GBoard, so.
Most of the time I just wish I could plug my full sized keyboard into the phone, that would fix it completely most of the time (except, obviously, when I'm not near my desk).
An ideal compromise would be physical buttons on the device for when it's necessary and the ability to easily use my workstation's external keyboard (dock + switch maybe?) the rest of the time.
EDIT: Now that I think of it.. let me plug in a mouse too and give me a real OS (maybe in a container like you get on a Chromebook) and i can just replace my workstation with the docked phone. But then I would buy only half as many computers and wouldn't need all that GPU compute to train a bunch of statistical models so I guess that doesn't work for the computer companies.
I'm sad there isn't more built around Android's AVF. I thought for sure, by now, we were going to have "Linux on Android" ala Crostini.
Simple example: Adding something to a reminder list, but the name of your lists don't exactly match the list you said to add to.
Prompt: "Add milk to my shopping list"
Siri: "I didn't find a shopping list, do you want to create one?"
ChatGPT (when asked to pick from my actual lists), properly identifies the "groceries" list as the intended list.
I wouldn't dream of trying to use a Siri, it sounds absolutely maddening. All I expect is that when I press a key on the keyboard the character I commanded with my key press shows up on the screen before I can blink, and does so exactly once.
Sounds infuriating to me. (To be clear, I don't have any always-(maybe)-on mics in my life, I doubt Hey Google or Bard or whatever is much better.)
I use Siri to add stuff to my grocery list and set timers. That's it. It's useful when I'm in the kitchen to just say what needs to go on this list instead of remembering to write it down later.
The day when Siri or Google or whatever can make the corrections I mentioned in my higher post will improve it vastly.
Taking a completely different type of example, image editing. Let's say you ask your computer to remove a blemish in a photo. A professional could remove it, maybe better even, without AI. They know the tools to use, the keys to press, and effect change. Regular people don't give a crap about that, they want to circle the item (or otherwise identify it) and click "remove." When the computer removes the selected item they're happy, and generative AI is working on THAT type of solution.
It's not here yet, so yes you're right that Siri IS maddening to use.
This feels dangerously close to a lack of empathy for the user. I understand that's not your intention, in fact the opposite. But in order to accept the notion that users actually want an intelligent employee instead of a tool I have to believe that everyone truly wants to be a manager instead of an individual contributor. I don't believe it.
Take a simpler case, hammering in a nail. What I want from my hammer is for it to disappear and become an extension of my arm. I just want to hammer in the nail. I don't want to negotiate with the hammer about how it's going to strike the nail, all I want is to hit the nail. There's no amount of "clever" the hammer can be which will help. Cleverness can only hurt my user experience.
In your example, what recourse does the user have if the AI didn't do the job the way they wanted? Removing something from an image implies (probably? or maybe not?) that the void is "backfilled" somehow. What if they're not happy with the backfill job? Do they have to argue with the tool about it? Will the tool take their feedback well or will it become a fight?
I think, generally, giving users tools that scale like hammers is the way to go. A hammer in the hands of a skilled carpenter, blacksmith, or cobbler with 30yr experience is no different than the same hammer in the hands of a 2yo child learning to drive their first nail. But that hammer's utility will scale with that child's skill for their entire lifetime. There's no "beginner" vs "advanced" distinction. What makes us (as computer hammer builders) believe that we can distinguish between "beginner" or "advanced" computer hammers? Or "regular" vs "special" users?
EDIT: or maybe we're not building hammers, instead we're building dishwashers. Dishwasher users aren't supposed to be skilled beyond loading and unloading the dishwasher, and hitting the start button. Do "regular users" really want an appliance, or do they want a tool?
EDIT: another way to phrase it -- are computers "bicycles for the mind" or are they just a bus?
It doesn't even seem to matter anymore. The tail is fully wagging the dog. Wall Street doesn't really care what companies are doing with AI, how they are using it, or whether their use of AI is going to actually drive earnings. They just care that they are using it. If a company says "We're doing AI blah blah blah" that's enough: investors are happy and stock price goes up.
On the other hand there’s what the washing machine, mechanized farm equipment, etc. did. A slow shift in how many people are required to do a job. There were no absolute jobs lost, just a shift in the economy.
Chances are it’ll be somewhere in between.
Generative AI is significant enough to Apple's use cases that there would seem to be a very strong business case to bring it in house.
They are laughably behind the curve. Android should see widespread deployment of Gemini baked into the next generation of phones, and this could have a significant impact on Apple.
Their reputation is of being the best. The most polished. The most accessible.
It’s never been to be on the bleeding edge. Apple’s brand is that of the perfectionists. Even in their hackiest 80s lore, the elements that rise to myth are those about resourcefulness and design.
Quite the opposite.
The iPod was panned by tech commentators; famously, "No wireless. Less space than a nomad. Lame."
The iPhone saw similar reactions; https://www.fastcompany.com/40436054/10-of-the-most-interest.... "There is nothing revolutionary or disruptive about any of the technologies."; "The real elephant in the room is the fact that I just spent $600 on my iPhone and it can’t do some crucial functions that even $50 handsets can."; "That virtual keyboard will be about as useful for tapping out emails and text messages as a rotary phone."
I can't imagine how apoplectic Gates was over the iPad's success after a decade of trying to make a Windows tablet sell.
Apple's advantage is always been superior hardware and processing. My guess is that they try to do some on device LLM. It's currently possible to run Mistral 7B on your phone (MLCChat app), which is quite decent for a small model but is pretty terrible compared to the largest / best models.
The fact of the matter is it remains to be seen how smart either model will be.
I just asked mistral 7b to provide 5 sentences that end with Apple. It couldn't do it. I then provided 5 examples generated from ChatGPT 4 and asked it to generate 5 more. It still couldn't do it. 10 ChatGPT examples- still couldn't do it.
You seem to be saying the models can generalize on the entire context size, that I should keep provided examples up to the token limit because this will make the model smarter. Is there evidence of that?
It can do some extrapolation on tasks it's already been proven to do, but that's not every task.
I mean looking at Google and the various daily AI dramas they get, it seems like everyone else has rushed to market and is dealing with the negative fallout of that.