Apple has the best edge inference silicon in the world (neural engine), but they have effectively zero presence in a training datacenter. They simply do not have the TPU pods or the H100 clusters to train a frontier model like Gemini 2.5 or 3.0 from scratch without burning 10 years of cash flow.
To me, this deal is about the bill of materials for intelligence. Apple admitted that the cost of training SOTA models is a capex heavy-lift they don't want to own. Seems like they are pivoting to becoming the premium "last mile" delivery network for someone else's intelligence. Am I missing the elephant in the room?
It's a smart move. Let Google burn the gigawatts training the trillion parameter model. Apple will just optimize the quantization and run the distilled version on the private cloud compute nodes. I'm oversimplifying but this effectively turns the iPhone into a dumb terminal for Google's brain, wrapped in Apple's privacy theater.
Setting aside the obligatory HN dig at the end, LLMs are now commodities and the least important component of the intelligence system Apple is building. The hidden-in-plain-sight thing Apple is doing is exposing all app data as context and all app capabilities as skills. (See App Intents, Core Spotlight, Siri Shortcuts, etc.)
Anyone with an understanding of Apple's rabid aversion to being bound by a single supplier understands that they've tested this integration with all foundation models, that they can swap Google out for another vendor at any time, and that they have a long-term plan to eliminate this dependency as well.
> Apple admitted that the cost of training SOTA models is a capex heavy-lift they don't want to own.
I'd be interested in a citation for this (Apple introduced two multilingual, multimodal foundation language models in 2025), but in any case anything you hear from Apple publicly is what they want you to think for the next few quarters, vs. an indicator of what their actual 5-, 10-, and 20-year plans are.
Google and Apple together will posttrain Gemini to Apple's specification. Google has the know-how as well as infra and will happily do this (for free ish) to continue the mutually beneficial relationship - as well as lock out competitors that asked for more money (Anthropic)
Once this goes live, provided Siri improves meaningfully, it is quite an expensive experiment to then switch to a different provider.
For any single user, the switching costs to a different LLM are next to nothing. But at Apple's scale they need to be extremely careful and confident that the switch is an actual improvement
I was in the map search, so I just said "Costco" and it said "I can't help with that right now, please try again later" or something of the sort. I tried a couple more times until I changed up to saying "Navigate me to Costco" where it finally did the search in the textbox and found it for me.
Obviously this isn't the same thing as Gemini but the experience with Android Auto becomes more and more garbage as time passes and I'm concerned that now we're going to have 2 google product voice assistants.
Also, tbh, Gemini was great a month ago but since then it's become total garbage. Maybe it passes benchmarks or whatever but interacting with it is awful. It takes more time to interact with than to just do stuff yourself at this point.
I tried Google Maps AI last night and, wow. The experience was about as garbage as you can imagine.
Seems like they are waiting for the "slope of enlightenment" on the gartner hype curve to flatten out. Given you can just lease or buy a SOTA model from leading vendors there's no advantage to training your own right now. My guess is that the LLM/AI landscape will look entirely different by 2030 and any 5 year plan won't be in the same zip code, let alone playing field. Leasing an LLM from Google with a support contract seems like a pretty smart short term play as things continue to evolve over the next 2-3 years.
[1] https://emp.lbl.gov/news/new-study-refocuses-learning-curve
[2] https://ourworldindata.org/grapher/solar-pv-prices-vs-cumula...
LLMs are now commodities and the least important component of the intelligence system Apple is building
Apple won't switch Google out as a provider for the same reason Google is your default search provider. They don't give a shit about how many advertisements you're shown. You are actually detached from 2026 software trends if you think Apple is going to give users significant backend choices. They're perfectly fine selling your attention to the highest bidder.
Guess who's the bestie of Twitter's owner? Any clues? Could that be a vindictive old man with unlimited power and no checks and balances to temper his tantrums?
Of course they both WANT Twitter the fuck out of the store, but there are very very powerful people addicted to the app and what they can do with it.
Which is why privacy theatre was an excellent way to put it
So I'm glad Apple is not trying to get too much into a bidding war. As for how well orgs are run, Meta has its issues as well (cf the fiasco with its eponymous product), while Google steadily seems to erode its core products.
My money is still on Apple and Google to be the winners from LLMs.
I can see them eventually training their own models (especially smaller and more targeted / niche ones) but at their scale they can probably negotiate a pretty damn good deal renting Google TPUs and expertise.
Its also a race to the bottom type scenario. Apple would have never been able to keep up with server release schedules.
Was an interesting but ultimately odd moment of history for servers.
The Allen Institute (a non-profit) just released the Molmo 2 and Olmo 3 models. They trained these from scratch using public datasets, and they are performance-competitive with Gemini in several benchmarks [0] [1].
AMD was also able to successfully train an older version of OLMo on their hardware using the published code, data, and recipe [2].
If a non-profit and a chip vendor (training for marketing purposes) can do this, it clearly doesn't require "burning 10 years of cash flow" or a Google-scale TPU farm.
[0]: https://allenai.org/blog/molmo2
I was under the impression that all these GPUs and such were needed to run the AI, not only ingest the data.
Because almost every example of previous cases of things like this eventually leveled out.
https://machinelearning.apple.com/research/apple-intelligenc...
I'm curious if this officially turns the foundation model providers into the new "dumb pipes" of the tech stack?
It is their strength to take commodity products and scale it well.
So what does it take? How many actual commitments to privacy does Apple have to make before the HN crowd stops crowing about "theater"?
It sounds like the value of these very time-consuming, resource-intensive, and large scale operations is entirely self-contained in the weights produced at the end, right?
Given that we have a lot of other players enabling this in other ways, like Open Sourcing weights (West vs East AI race), and even leaks, this play by Apple sounds really smart and the only opportunity window they are giving away here is "first to market" right?
Is it safe to assume that eventually the weights will be out in the open for everyone?
A lot of the hype in LLM economics is driven by speculation that eventually training these LLMs is going to lead to AGI and the first to get there will reap huge benefits.
So if you believe that, being "first to market" is a pretty big deal.
But in the real world there's no reason to believe LLMs lead to AGI, and given the fairly lock-step nature of the competition, there's also not really a reason to believe that even if LLMs did somehow lead to AGI that the same result wouldn't be achieved by everyone currently building "State of the Art" models at roughly the same time (like within days/months of each other).
So... yeah, what Apple is doing is actually pretty smart, and I'm not particularly an Apple fan.
Yes, and the knowledge gained along the way. For example, the new TPUv4 that Google uses requires rack and DC aware technologies (like optical switching fabric) for them to even work at all. The weights are important, and there is open weights, but only Google and the like are getting the experience and SOTA tech needed to operate cheaply at scale.
This sort of thing didn't work out great for Mozilla. Apple, thankfully, has other business bringing in the revenue, but it's still a bit wild to put a core bit of the product in the hands of the only other major competitor in the smartphone OS space!
Down the road Apple has an advantage here in a super large training data set that includes messages, mail, photos, calendar, health, app usage, location, purchases, voice, biometrics, and you behaviour over YEARS.
Let's check back in 5 years and see if Apple is still using Gemini or if Apple distills, trains and specializes until they have completed building a model-agnostic intelligence substrate.
The moat is talent, culture, and compute. Apple doesn't have any of these 3 for SOTA AI.
Source: I worked there
Culture is overrated. Money talks.
They did things far more complicated from an engineering perspective. I am far more impressed by what they accomplished along TSMC with Apple Silicon than by what AI labs do.
Google invented the transformer architecture, the backbone of modern LLMs.
It goes back much further than that - up until 2016, Apple wouldn't let its ML researchers add author names to published research papers. You can't attract world-class talent in research with a culture built around paranoid secrecy.
They also were deceptive about iCloud encryption where they claimed that nobody but you can read your iCloud data. But then it came out after all their fanfare that if you do iCloud backups Apple CAN read your data. But they aren’t in a hurry to retract the lie they promoted.
Also if someone in another country messages you, if that country’s laws require that Apple provide the name, email, phone number, and content of the local users, guess what. Since they messaged you, now not only their name and information, but also your name and private information and message content is shared with that country’s government as well. By Apple. Do they tell you? No. Even if your own country respects privacy. Does Apple have a help article explaining this? No.
It's something a smart niece or nephew could handle in terms of managing risk, but the implications could mean getting locked out of your device which you might've been using as the doorway to everything, and Apple cannot help you.
I don't mean to sound like an Apple fanboy, but is this true just for SMS or iMessage as well? It's my understanding that for SMS, Apple is at the mercy of governments and service providers, while iMessage gives them some wiggle room.
Ancedotal, but when my messages were subpoenaed, it was only the SMS messages. US citizen fwiw
Mullvad requires nothing but an envelope with cash in it and a hash code and stores nothing. Apple owns you.
Works great for me with NextDNS.
Orion browser - while also based on WebKit - is also awesome and has great built in Adblock and supposedly privacy respecting ideals.
And it works until it's made illegal in your country and removed from the app store. You have no guarantees that anything that works today will work tomorrow with Apple.
Apple is setting us up to be under a dictator's thumb one conversion at a time.
If you want to use the App Store on these devices, you do need to have an email address.
[0] https://en.wikipedia.org/wiki/Apple%E2%80%93FBI_encryption_d...
Then you learn that every modern CPU has a built-in backdoor, a dedicated processor core, running a closed-source operating system, with direct access to the entire system RAM, and network access. [a][b][c][d].
You can not trust any modern hardware.
https://en.wikipedia.org/wiki/Intel_Management_Engine
https://en.wikipedia.org/wiki/AMD_Platform_Security_Processo...
https://en.wikipedia.org/wiki/ARM_architecture_family#Securi...
* Certain types of Android
Why did they change their wording from:
Nobody can read your data, not even Apple
to:
Apple cannot read your data.
You know why.
It also lets Apple stand by while the dust settles on who will out innovate in the AI war - they could easily enter the game on a big way much later on.
I can see a future where LLM research stalls and stagnates, at which point the ROI on building/maintaining their own commodity LLM might become tolerable. Apple has had Siri as a product/feature and they've proven for the better part of a decade that voice assistants are not something they're willing to build a proficiency in. My wife still has an apple iPhone for at least a decade now, and I've heard her use Siri perhaps twice in that time.
Probably not missing the elephant. They certainly have the money to invest and they do like vertical integration but putting massive investment in bubble that can pop or flatline at any point seems pointless if they can just pay to use current best and in future they can just switch to something cheaper or buy some of the smaller AI companies that survive the purge.
Given how much AI capable their hardware is they might just move most of it locally too
They have always been a premium "last mile" delivery network for someone else's intelligence, except that "intelligence" was always IP until now. They have always polished existing (i.e., not theirs) ideas and made them bulletproof and accessible to the masses. Seems like they intend to just do more of the same for AI "intelligence". And good for them, as it is their specialty and it works.
Google really could care less about Android being good. It is a client for Google search and Google services - just like the iPhone is a client for Google search and apps.
apple to some users "are you leaving for android because of their ai assistant? don’t leave we are bringing it to iphone"
Can you cite this claim? The Qualcomm Hexagon NPU seems to be superior in the benchmarks I've seen.
> without burning 10 years of cash flow.
Don't they have the highest market cap of any company in existence?
Wasn't Apple sitting on a pile of cash and having no good ideas what to spend it on?
Edit: especially given that Apple doesn’t do b2b so all the spend would be just to make consumer products
They still generate about ~$100 billion in free cash per year, that is plowed into the buybacks.
They could spend more cash than every other industry competitor. It's ludicrous to say that they would have to burn 10 years of cash flow on trivial (relative) investment in model development and training. That statement reflects a poor understanding of Apple's cash flow.
Going with Anthropic or OpenAI, despite on the surface having that clean Apple smell and feel, carries a lot of risk Apple's part. Both companies are far underwater, liable to take risks, and liable to drown if they even fall a bit behind.
Definitely. At at this point, Apple just needs to get anything out the door. It was nearly two years ago they sold a phone with features that still haven't shipped and the promise that Apple Intelligence would come in two months.
Anthropic doesn't have a single data centre, they rent from AWS/Microsoft/Google.
https://daringfireball.net/linked/2026/01/12/apple-google-fo...
Beyond Siri, Apple Foundation Models are available as API; will Google's technologies thus also be available as API? Will Apple reduce its own investment in building out the Foundation models?
"Apple Intelligence will continue to run on Apple devices and Private Cloud Compute, while maintaining Apple's industry-leading privacy standards."
"These models will help power future Apple Intelligence features, including a more personalized Siri coming this year."
1. The first issue is that there is significant momentum in calling Siri bad, so even if Apple released a higher quality version it will still be labelled bad. It can enhance the user's life and make their device easier to use, but the overall press will be cherrypicked examples where it did something silly.
2. Basing Siri on Google's Gemini can help to alleviate some of that bad press, since a non-zero share of that doomer commentary comes from brand-loyalists and astroturfing.
3. The final issue is that on-device Siri will never perform like server-based ChatGPT. So in a way it's already going to disappoint some users who don't realise that running something on mobile device hardware is going to have compromises which aren't present on a server farm. To help illustrate that point: We even have the likes of John Gruber making stony-faced comparisons between Apple's on-device image generator toy (one that produces about an image per second) versus OpenAI's server farm-based image generator which makes a single image in about 1-2 minutes. So if a long-running tech blogger can't find charity in those technical limitations, I don't expect users to.
> The final issue is that on-device Siri will never perform like server-based ChatGPT. So in a way it's already going to disappoint some users who don't realise that running something on mobile device hardware is going to have compromises which aren't present on a server farm.
For many years, siri requests were sent to an external server. It still sucked.
Their point is that if Apple totally scraps the current, bad, product called "Siri" and replaces it with an entirely different, much better product that is also named "Siri" but shares nothing but the name, people's perceptions of the current bad Siri will taint their impressions of the new one.
These models tend to have a "mind of their own", and I can totally, absolutely, see a current SOTA LLM convincing itself it needs to call 911 because you asked it how to disinfect a cut.
Yes, Apple is acknowledging that Google's Gemini will be powering Siri and that is a big deal, but are they going to be acknowledging it in the product or is this just an acknowledgment to investors?
Apple doesn't hide where many of their components come from, but that doesn't mean that those brands are credited in the product. There's no "fab by TSMC" or "camera sensors by Sony" or "display by Samsung" on an iPhone box.
It's possible that Apple will credit Gemini within the UI, but that isn't contained in the article or video. If Apple uses a Gemini-based model anonymously, it would be easy to switch away from it in the future - just as Apple had used both Samsung and TSMC fabs, or how Apple has used both Samsung and Japan Display. Heck, we know that Apple has bought cloud services from AWS and Google, but we don't have "iCloud by AWS and GCP."
Yes, this is a more public announcement than Apple's display and camera part suppliers, but those aren't really hidden. Apple's dealings with Qualcomm have been extremely public. Apple's use of TSMC is extremely public. To me, this is Apple saying "hey CNBC/investors, we've settled on using Gemini to get next-gen Siri happening so you all can feel safe that we aren't rudderless on next-gen Siri."
If they do refer to it as "Gemini" then this is a huge win for Google, and huge loss for OpenAI, since it really seems that the "ChatGPT" brand is the only real "moat" that OpenAI have, although recently there has been about a 20% shift in traffic from ChatGPT to Gemini, so the moat already seems to be running dry.
But it's a whole lot easier to switch from Gemini to Claude or Gemini to a hypothetical good proprietary LLM if it's white label instead of "iOS with Gemini"
Depends on where you are. In my experience here in Sweden Google Maps is still better, Apple maps sent us for a loop in Stockholm (literally {{{(>_<)}}} )
Google wanted to shove ads in it. Apple refused and to switch.
Their hand was forced by that refusal.
Apple announced last year they are putting their own ads in Maps so if that was the real problem the corporate leadership has done a complete 180 on user experience.
Apple is a very VERY different company than they were back then.
Back then they didn’t have all sorts of services that they advertised to you constantly. They didn’t have search ads in the App Store. They weren’t trying to squeeze every penny out of every customer all the time no matter how annoying.
Maybe I'm weird but mobile assistants have never been useful for me. I tried Siri a couple of times and it didn't work. I haven't tried it since because even if it worked perfectly I'm not sure I'd have any use for it.
I see it more like the Vision Pro. Doesn't matter how good the product ends up being, I just don't think it's something most people are going to have a use for.
As far as I'm concerned no one has proved the utility of these mobile assistants yet.
Apple explicitly acknowledged that they were using OpenAI’s GPT models before this, and now they’re quite easily switching to Google’s Gemini
Surely research money is not the problem. Can't be lack of competence either, I think.
Apple is competent at timing when to step into a market and I would guess they are waiting for AI to evolve beyond being considered untrustworthy slop.
First, they touted features that no one actually built and then fired their AI figurehead “leader” who had no coherent execution plan—also, there appears to have been territorial squabbling going on, about who would build what.
How on earth did Apple Senior Management allow this to unravel? Too much focus on Services, yet ignoring their absolute failures with Siri and the bullshit that was Apple Intelligence, when AI spending is in the trillions?
Google AI can make mistakes
So, yes, practically speaking, the Apple to Google payment offsets a tiny fraction of the Google to Apple payment, but real money will change hands for each and very likely separately.
Sounds like Apple Foundation Models aren't exactly foundational.
The idiomatic "British" way of doing this ...
Alternatively, for an Imperial-style approach, ...
As a professional software engineer you really should ...
(Because I just have a short blurb about my educational background, career, and geography in there, which with every other model I've tried works great to ensure British spelling, UK information, metric units, and cut the cruft because I know how to mkdir etc.)
It's given me a good laugh a few times, but just about getting old now.
Siri: Would you like to answer?
Me: Yes
Siri: ...
Me: No + more words
Siri: Ok (shuts off)
Even "Play the album XY" leads to Siri only playing the single song. It's hilariously bad.
Me: "Hey Siri, play <well known hit song from a studio album that sold 100m copies"
Siri: "OK, here's <correct song but a live version nobody ever listens to, or some equally obscure remix>"
Being these things are at their core probability machines, ... How? Why?
Might sound crazy but remember they did exactly this for web search. And Maps as well for many years.
This way they go from having to build and maintain Siri (which has negative brand value at this point) and pay Google's huge inference bills to actually charging Google for the privilege.
Because Apple Silicon is so good for LLM inferencing, I hope they also do a deal for small on-device Gemma models.
At the moment, I’m using https://picxstudio.com to generate 4K-quality images with the Nano Banana Pro model, but my goal is to build my own app that delivers the same level of quality and control.
The non-hardware AI industry is currently in an R&D race to establish and maintain marketshare, but with Apple's existing iPhone, iPad and Mac ecosystem they already have a market share they control so they can wait until the AI market stabilizes before investing heavily in their own solutions.
For now, Apple can partner with solid AI providers to provide AI services and benefits to their customers in the short term and then later on they can acquire established AI companies to jumpstart their own AI platform once AI technology reaches more long term consistency and standardization.
The better the basic NLP tasks like named entity recognition, PoS tagging, Dependency Parsing, Semantic Role Labelling, Event Extraction, Constituency parsing, Classification/Categorization, Question Answering, etc, are implemented by the model layer, the farther you can go on implementing meaningful use-cases in your agent.
Apple can now concentrate on making Siri a really useful and powerful agent.
Maybe someday they'll build their own, the way they eventually replaced Google Maps with Apple Maps. But I think they recognize that that will be years away.
With OpenAI, will it even be around 3 years from now, without going bankrupt? What will its ownership structure look like? Plus, as you say, the MS aspect.
So why not Google? It's very common for large corporations to compete in some areas and cooperate in others.
I didn't see you 41 day old reply to me until it was too late to comment on it. So here's a sarcastic "thanks for ignoring what I wrote" and telling me that exactly what I was complaining about is the solution to the problem I was complaining about.
https://news.ycombinator.com/item?id=46114935
1) I told you my household can't use Target or Amazon for unscented products, without costly remediation measures, BECAUSE EVEN SCENT-FREE ITEMS COME SMELLING FROM PERFUME CROSS-CONTAMINATION THANKS TO CLEANING, STORAGE, AND TRANSPORTATION CONDITIONS. SOMETIMES REALLY BADLY.
FFS. If you are going to respond, first read.
I also mentioned something other than "government intervention to dictate how products are made" as a solution to this issue, namely adequate segregation between perfumed and non-perfumed products.
And I care less about my wallet than I do about my time and actual ability to acquire products that are either truly scent free, or like yesteryear, don't have everlasting fragrance fixatives.
For people in my position, which make up a small percentage of the population (that still numbers in the millions), the free market has failed. We are a specialized niche that trades tips on how to make things tolerable.
SORRY TO EVERYONE ELSE FOR GOING OFF TOPIC.
For who? Regular people are quite famously not clamouring for more AI features in software. A Siri that is not so stupendously dumb would be nice, but I doubt it would even be a consideration for the vast majority of people choosing a phone.
I don't expect the current US government to do anything about it though.
I admit I don't see the issue here. Companies are free to select their service providers, and free to dominate a market (as long as they don't abuse such dominant position).
It also lends credence to the DOJ's allegation that Apple is insulated from competition - the result of failing to produce their own winning AI service is an exclusive deal to use Google while all competing services are disadvantaged, which is probably not the outcome a healthy and competitive playing field would produce.
This feels a little squishy... At what size of each company does this stop being an antitrust issue? It always just feels like a vibe check, people cite market cap or marketshare numbers but there's no hard criteria (at least that I've seen) that actually defines it (legally, not just someones opinion).
The result of that is that it's sort of just up to whoever happens to be in charge of the governing body overseeing the case, and that's just a bad system for anyone (or any company) to be subjected to. It's bad when actual monopolistic abuse is happening and the governing body decides to let it slide, and it's bad when the governing body has a vendetta or directive to just hinder certain companies/industries regardless of actual monopolistic abuse.
No they were already being sued for antitrust violations, it just mirrors what they are accused of doing to exploit their platform.
https://storage.courtlistener.com/recap/gov.uscourts.njd.544...
It's the line of thinking that I'm trying to dig into more, not the specifics of this case. Now it feels like you're saying "this is anti-trust because someone accused them of anti-trust before".
If that case was prosecuted and Apple was found guilty, I suppose you can point to it as precedent. But again, does it only serve as precedent when it's a deal between Apple and Google? Is it only a precedent when there's a case between two "large" companies?
Again this is all really squishy, if companies aren't allowed to outsource development of another feature once they pass some sense of "large", when does it apply? What about the $1T pharmaceutical company that wants to use AI modeling? They're a large technically component company, if Eli Lily partnered with Gemini would you be sitting here saying that they also are abusing a monopolistic position that prevents competition in the AI model space?
No it's antitrust because they have a failed product, but purely by virtue of shutting out competitors from their platform they have been able to turn three years of flailing around into a win-by-outsourcing. What would Siri's position be like today if they hadn't blocked default voice assistants? Would they be able to recover from their plight to dominate the market just by adopting Google's technology? How would that measure against OpenAI, Anthropic or just using Google directly? This is why it's an antitrust issue.
"it's antitrust because they have a failed product" is objectively hilarious
> What would Siri's position be like today if they hadn't blocked default voice assistants?
Probably pretty much the same. What would Gemini's position be like today if they hadn't blocked out default voice assistants? You only get Gemini when you use Gemini, just like you only got Siri when you use Siri (up until this deal takes effect). Also Siri has used ChatGPT already, so I'm not even convinced this is a valid criticism. They already didn't block OpenAI from being part of Siri.
> Would they be able to recover from their plight to dominate the market just by adopting Google's technology?
This is relevant how?
> How would that measure against OpenAI, Anthropic or just using Google directly?
How would what measure against other ai models? How would their ability to recover from a lack of investing in a better "homemade" AI model differ if they used OpenAI instead of Gemini? How does that have anything to do with antitrust? That's a business case study type of question. Also, shouldn't they be allowed to recover from their own lack of developing a model by using the best tool available to them?
Why only in Japan? Because Japan forced them to: https://9to5mac.com/2025/12/17/apple-announces-sweeping-app-...
The problem isn't that they used another company's model. It's that they are using a model made by the only company competing with them in the market of mobile OS.
Sorry if I'm missing the point but if Apple had picked OpenAI, couldn't you have made the same comment? "nobody else can be the default voice assistant or power Siri, so where does this leave eg Gemini/Claude?".
However I don't see the link, how they are "using their duopoly", and why "they" would be using it but only one of them benefits from it. Being a duopoly, or even a monopoly, is not against anti-trust law by itself.
In September, a judge ruled against a worst-case scenario outcome that could have forced Google to divest its Chrome browser business.
The decision also allowed Google to continue to make deals such as the one with Apple."
How much is Google paying Apple now
If these anti-competitive agreements^1 were public,^2 headlines could be something like,
(A) "Apple agrees to use Google's Gemini for AI-powered Siri for $[payment amount]"
Instead, headlines are something like,
(B) "Apple picks Google's Gemini to run Ai-powered Siri"
1. In other words, they are exclusive and have anticompetitive effects
2. Neither CNBC nor I are suggesting that there is any requirement for the parties to make these agreements public. I am presenting a hypothetical relating to headlilnes, (A) versus (B), as indicated by the words "If" and "could"
I understand other things like image recognition, wikipedia information, etc require external data sets, and transferring over local data to that end can be a privacy breach. But the local stuff should be easy, at least in one or two languages.
In the original announcement of the Siri revamped a couple of years ago, they specifically talked about having the on-device model handle everything it can, and only using the cloud models for the harder or more open ended questions.
The biggest thing Apple has to do is get a generic pipeline up and running, that can support both cloud and non-cloud models down the road, and integrate with a bunch of local tools for agent-style workloads (e.g. "restart", "audio volume", "take screenshot" as tools that agents via different cloud/local models can call on-device).
But you may be right, maybe on-device won't be smart enough to decide it isn't smart enough. Though it does seem like the local LLMs have gotten awfully good.
I'm really curious how Apple is bridging the gap between consumer silicon and the datacenter scale stack they must have to run a customized Gemini model for millions of users.
RDMA over Thunderbolt is cool for small lab clusters but they must be using something else in the datacenter, right?
It would take US antitrust approval, but under Trump, that's for sale.
But why on earth would they do that? It's both cheaper and safer to buy Google's model, with whom they already have a longstanding relationship. Examples include the search engine deal, and using Google Cloud infrastructure for iCloud and other services. Their new "private cloud compute" already runs on GCP too, perfect! Buying Gemini just makes sense, for now. Wait a few years until the technology becomes more mature/stable and then replace it with their own for a reasonable price.
I can't wait for gemini to lecture me why I should throw away my android
To be clear, I'd much rather have my personal cloud data private than have good AI integration on my devices. But strictly from an AI-centric perspective, Apple painted themselves into a corner.
If it would suddenly get better, like they teased (Some would say, lied about the capabilities) with Apple Intelligence that would fit pretty well. That they delegate that to Gemini now is a defeat.
Their image classification happens on-device, in comparison Google Photos does that server side so they already have ML infra.
Apple definitely has software expertise, maybe it's not as specialized into AI as it is about optimizing video or music editors, but to suggest they'd be at the same starting point as an agriculture endeavor feels dishonest.
Why does a MacBook seem better than PC laptops? Because Apple makes so few designs. When you make so few things, you can spend more time refining the design. When you're churning out a dozen designs a year, can you optimize the fan as well for each one? You hit a certain point where you say "eh, good enough." Apple's aluminum unibody MacBook Pro was largely the same design 2008-2021. They certainly iterated on it, but it wasn't "look at my flashy new case" every year. PC laptop makers come out with new designs with new materials so frequently.
With iPhones, Apple often keeps a design for 3 years. It looks like Samsung has churned out over 25 phone models over the past year while Apple has 5 (iPhone, iPhone Plus, iPhone Pro, iPhone Pro Max, iPhone 16e).
It's easy to look so good at things when you do fewer things. I think this is one of Apple's great strengths - knowing where to concentrate its effort.
Hell, they can’t even make a TV this year that’s less shit than last years version of it and all that requires is do literally nothing.
https://support.apple.com/guide/iphone/use-chatgpt-with-appl...
So I'm guessing in a future update it will be Gemini instead. I hope it's going to be more of an option to choose between the 2.
Was this just a massive oversight at Apple? Were there not AI researchers at Apple sounding the alarm that they were way off with their technology and its capabilities? Wouldn't there be talk within the industry that this form of AI assistant would soon be looked at as useless?
Am I missing something?
Siri was never an “AI agent”, with intent based systems, you give the system phrases to match on (intents) and to fulfill an intent, all of the “slots” have to be fulfilled. For instance “I want to go from $source to $destination” and then the system calls an API.
There is no AI understanding - it’s a “1000 monkeys implementation”, you just start giving the system a bunch of variations and templates you want to match on in every single language you care about and match the intents to an API. That’s how Google and Alexa also worked pre LLM. They just had more monkeys dedicated to creating matching sentences.
Post LLM, you tell the LLM what the underlying system is capable of, the parameters the API requires to fulfill an action and the LLM can figure out the users intentions and ask follow up questions until it had enough info to call the API. You can specify the prompt in English and it works in all of the languages that the LLM has been trained on.
Yes I’ve done both approaches
Apple weighs using Anthropic or OpenAI to power Siri
> Apple and Google have entered into a multi-year collaboration under which the next generation of Apple Foundation Models will be based on Google's Gemini models and cloud technology. These models will help power future Apple Intelligence features, including a more personalized Siri coming this year.
... https://blog.google/company-news/inside-google/company-annou...
By the way, have any of you ever tried to delete and disabled Siri’s iCloud backup? You can’t do it.
On iPhone, Settings → iCloud → Storage → Siri → Disable and Delete
Edit: Tried it. It works for me. Takes a minute though.
- setting a timer
- dictating a title to search on Apple TV
A feature set that has remained unchanged since Siri’s launch…
Siri needs faster and more flexible handling of Spotify, Google Maps and third-party messaging apps, not a slop generator.
That's the Internet Explorer of chatbots.
This work is to turn it it into something else, more like a chatbot, presumably
In iOS 18.1 (on iPhone 15+) Siri is part intent-based, part on-device "Apple Intelligence" small LLM, and in iOS 18.2 it also supports off-device ChatGPT.
This year Siri 2.0 is expected to ditch the legacy intent-based system and instead use just the small on-device Apple Intelligence LLM plus (opt-in) off-device Gemini (running in some private cloud).
Also, I have never turned on Apple "Intelligence".
> The U.S. government said Apple Chief Executive Officer Tim Cook and Google CEO Sundar Pichai met in 2018 to discuss the deal. After that, an unidentified senior Apple employee wrote to a Google counterpart that “our vision is that we work as if we are one company.”
https://www.bloomberg.com/news/articles/2020-10-20/apple-goo...