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pen2l 2 days ago [-]
Apple, to me, is the winner in the end of this AI chapter.
Distillation works: we can get models leaner, have better performance with lesser and lesser parameters, more efficient, running locally. Apple gets this and we'll see the result with M7 Max/ultra chips and I reckon this will be one of the titular apps when M7 line of chips are introduced.
I guess it explains the haste Anthropic and OpenAI are in to IPO, cash out and leave the the retail investor holding the bag.
aurareturn 2 days ago [-]
Apple, to me, is the winner in the end of this AI chapter.
I might be one of only few people who think Apple is a loser in the AI chapter.
I don't think it shows yet but I think the dominance of the App Store will end. I think a ton of iOS apps will be replaced by ChatGPT/Claude. I think there is a big opening for a company to redesign the phone from the ground up purely around an AI assistant instead of apps.
I think AI will severely weaken iOS, App Store, and the iPhone in the next few years. It was nearly impossible to start a 3rd competitor to iOS and Android until recently because no one is going to redesign their apps for your new phone. Today, that's different. Many productivity apps are just being replaced by GenAI/ChatGPT/etc and services are making it easy for AI agents to access directly without an app.
Not to mention higher chip prices will eat into hardware margins.
I do not think local LLM inference will make up for lesser iPhone dominance.
smugglerFlynn 1 days ago [-]
Replacing a good app is still extremely hard. Let me explain.
Commodities like todo apps and calculators rarely compete on features, they compete on product design. This includes look and feel, relation between elements, design choices on what exact common features are available.
All products are, at their essence, just a set of design decisions stitched and shipped together.
Now, making these design decisions is hard. It requires knowledge, consistency, and insights into how real people operate real products. Even as a sole user of the app you build you rarely know what you actually need.
LLMs are 'design-less' in their essence. Building your own todo app takes literal seconds and it all looks simple because LLMs will default most of these design decisions for you - until you try to use your new app daily and notice it somehow sucks. Building a good todo app or good calculator requires tweaking, publishing, polishing, and solving bugs, testing, rinse and repeat.
Another tricky side of this is that you might know logically what features you want, but you are not selecting one product over another logically. You need to try and see if that works for you, all the vibes and good parts and bad parts and design choices and colors, till you find something that "clicks" for you. Using pure Claude as a todo app only works as long as you want to have more Claude in your daily life.
In the meantime app store provides dozens of well-reviewed alternative solutions which look good and require zero maintenance.
And that's just a calculator or todo app. Non-commodity apps are even harder than that.
WarmWash 1 days ago [-]
Design is dead (long live design)
I don't see any future where programs follow the static nature of old paradigm programming. A nice intuitive UI? What about just telling the app what I need when I need it? The gold standard of consumer UI is...another person.
If I have a team of god tier light speed SWE's at my disposal, why the fuck am I fumbling around in an actions panel? The program can just be dynamically modified in near real time to be whatever I need it to be in that moment.
If you extrapolate LLMs out to their extreme, you get a shape-shifting liquid array of bits in memory that manifest anything at the behest of a completely natural language interface.
spider-mario 1 days ago [-]
> The gold standard of consumer UI is...another person.
Absolutely not. Constraining the set of possible actions instead of having you verbalise what you want every time is often a feature, not just a technical limitation. A camera with a shutter button is better design than having to tell the camera “please take a photo”.
At the supermarket, I personally also prefer the self-checkout machines over going to a human cashier.
WarmWash 1 days ago [-]
It wouldn't be just verbalizing, you could type or gesture just as well. Nor would you need to communicate each command, the machine would recognize that you want a button for your camera, the checkout would understand that you want to checkout and understand each intended action as you do so.
The UI is totally fluid at all times, because an "intelligence" is actively manifesting it at all times. Nothing needs to be hard coded.
spider-mario 1 days ago [-]
But I don’t necessarily want to have to continuously adapt to such a fluid UI. Unless you are proposing that the UI should effectively just read my mind, but until it literally does that to perfection, that will always come with the overhead of wondering whether it has the right understanding of what you want.
WarmWash 1 days ago [-]
Then you can just have a static design, it's trivial and perceptively instant for the machine to generate it (or 10 of them if you want choice) and act like a "dumb computer from 20 years ago".
Hell the computer might even see your face, see your age and style, and be like "Yup, this guy definitely wants to checkout with a dumb, midi keytone 8-bit styled program"
p_j_w 1 days ago [-]
No it absolutely is not. I spent a good 2 weekends using an agent to develop an alternative to a website that I didn't care to pay for. After all of that time, while it's functional and I do occasionally use it for its intended purpose, if you take into account the amount I paid in tokens and the amount of time I spent on it, the average Joe would've been better off just paying for the site, which is actually still better.
The only reason it works out in my favor is that I enjoyed doing it. Normal people don't want to fuck around with that kind of shit.
WarmWash 1 days ago [-]
"LLMS can hardly do high school math"
plemer 21 hours ago [-]
Is your argument now just: “AI will be able to do anything”?
spider-mario 1 days ago [-]
I feel that this kind of sidesteps the point that smugglerFlynn was making about designing those interfaces.
WarmWash 1 days ago [-]
If your stance is that AI will never be able to eclipse human design, then yes it's an impossible hurdle t overcome.
But already AI design is everywhere and regular people don't even notice (outside perhaps the intentional cues in mainstream image generators). It's only going to get better as people can interact with the design the same as the interact with another person.
oinj 1 days ago [-]
You are assuming that you'll always have the time and energy to determine what you need at the moment you need it, which doesn't really sound true.
You're also assuming that there are no negatives to saying what you want compared to just acting on things, but since the beginning of computing many people have proven this wrong time and again. I suggest you read about HCI as a research field and its history, it doesn't take much to realise how limited the average HNer's understanding of UI/UX design is, and how far current LLMs are from the skills required to be able to carefully design an app for productive human use.
gls2ro 1 days ago [-]
Unless AI will be ar the level of saying "I want a scheduling app that fits me" I still see value in buying some apps.
I like to customize my Neovim setup or terminal and a bunch of scripts that I keep making them nice and maybe my blog and so on.
I don't want to become the PM of every app I need. But I do agree changes will happen to the current apps and how we buy and use them. Not sure exactly where it will settle. But still unknown unknowns and domain knowledge and vocabulary is not yet allowing anyone to build their own apps unless for simple cases.
Or maybe it is just me: I want someone else to think about my accounting app. I dont want to spend time to learn and understand and keep myself up to date or setup a series of LLM sessions that navigate and watch laws and propose changes.
WarmWash 1 days ago [-]
Why do you need a scheduling app when you have a secretary?
Why do you need an accounting app when you have an accountant?
Programs of the future will in no way resemble what they are today. I don't even want to call it a "program" because in my head it's more like an intelligent digital liquid that can rapidly flow into any state. This flash-in-the-pan 50 year archaic era of software will look like what the oil lamp looks like today. A crude intermediate tech during a time of much larger transition.
sterlind 12 hours ago [-]
it's nice to see what's on my schedule at a glance, rather than needing to ask my secretary. also helps with situational awareness.
it's nice to see my financial situation at a glance, without asking my accountant.
speech/text is one modality. we humans are also visual and tactile. and we need consistency and recurring patterns of interaction to function well.
moljac024 10 hours ago [-]
You ask your secretary to give you a visual representation of your schedule right now and presto - you got it.
Same thing for your accountant.
Imagine that both of them, while being good at their respective jobs, are also software engineers that can mint a custom throwaway app for you at a moment's notice.
WarmWash 8 hours ago [-]
>speech/text is one modality. we humans are also visual and tactile. and we need consistency and recurring patterns of interaction to function well.
I'm sure your secretary will make a note of your preference.
alala-lala-lon 1 days ago [-]
[dead]
smugglerFlynn 1 days ago [-]
This sounds like the car industry touch screen craze all over again.
Good design rarely calls for a “you can do everything” approach. Good design is often context specific and subtly guides users to better outcomes.
Doctor appointments would absolutely suck if I had to navigate decision trees and click buttons to communicate my symptoms. Car blinkers would absolutely suck if I had to type “blink left” into a chat window before every turn.
hobo123 1 days ago [-]
Oh is that the new UI of Mercedes and BMW cars? Cause they always seem to have dysfunctional blinkers.
smugglerFlynn 1 days ago [-]
My latest BMW X3 rental had touch controls for air vents - I would unironically prefer chat interface over this
FuckButtons 1 days ago [-]
>I don't see any future where programs follow the static nature of old paradigm programming. A nice intuitive UI? What about just telling the app what I need when I need it? The gold standard of consumer UI is...another person.
Maybe it’s just the ‘tism, but I hard disagree that I would ever say another person is a superior interface into… anything? It’s slow, they may misinterpret you, they have their own ideas and motivations, they’re (mostly) expensive because the only reason I need them is because there’s information / skill asymmetry. I don’t know that many or even most of those problems are resolved with ai, in some ways the problems are amplified.
atomicthumbs 14 hours ago [-]
>A nice intuitive UI? What about just telling the app what I need when I need it?
Sounds cumbersome, slow to use, and prone to failure.
caycep 23 hours ago [-]
Maybe it would've been better to use all those billions in tokens and VC funding to pay for Finnish-style parental benefits and make more persons?
AlwaysRock 1 days ago [-]
A huge amount of apps I've downloaded are just to solve a problem I have for a moment. Then most of the rest are regular use apps.
I dont think llms are going to replace banking apps anytime soon. But I no longer look for an app to pull data from my Peloton app into another exercise app. LLMs can build an app or a script that will do that and I wont have to pay some annual or monthly fee. It feels like these types of apps are going to die off.
nout 1 days ago [-]
I rolled out my own to-do app yesterday, because I needed something fast as a companion to Obsidian, while it can do cloud syncing for me.
It works exactly the way I want and looks exactly the way I want. If there's something I want changed about it, I add it as a todo item in the very same app. This works today.
I don't think the companies have moat in experience fine tuning.
alperhalil 1 days ago [-]
I feel the same about this. There are many task trackers out there and most are overkill for my own projects. I don't feel like onboarding through Linear, or setting up through Trello and think about how to have the agents connect, etc, so I just found myself motivated to look for my own, local solution track and manage my projects.
I think it's better when you are at the origin, and the software branches off of your taste. For so long, we had to adapt and accept the ways of established software because it would take so long to make something of your own. Now it's both cheap and fast to iterate.
willio58 1 days ago [-]
Great take. I agree with this. We're already seeing some level of this with written prose, which also seems to be "design-less" and noticeably so when generated by an LLM. So many claim to have solved this but I have yet to see it.
At the end of the day, it seems we'll be left with a decision of using something made by a person with real opinions or using something generated by AI with opinions that are a distillation of past documentation fed into it.
We're in this weird spot now where we are transitioning toward all ui feeling the same, and only the people really tuned in even notice this. Once the general public starts noticing, I believe there's going to be a search for fresh, organic, opinionated software. Not that the software won't be AI-generated, but it will have a human truly sculpting it, like art.
So the question becomes, if people still appreciate human-made art in a world where a better image can be generated in a small fraction of time via a prompt, will they feel the same way about the software they use?
xnx 1 days ago [-]
> Commodities like todo apps and calculators rarely compete on features, they compete on product design.
Whatever "good design" is (and it varies by user), it's very easy to copy. Commodity apps complete on marketing. Companies who charge $10/month for an app, are probably spending $8/month in marketing/advertising.
solyin 1 days ago [-]
It depends on the person. Do you want something off the shelf and you'll adapt to it, or do you want to custom build something shaped to fit you.
skybrian 1 days ago [-]
Design is sometimes important, but what we might call product-market fit (for a "market" of one) probably beats it. Sure, a calculator app is generic so you might as well use one that's well-designed. If there's an existing app you like, it's probably not worth rebuilding it. But personal apps can do things that an off-the-shelf app won't do.
I recently used a coding agent to build a TV-like YouTube player for my mother, who is quite elderly. It's inspired by channelsurfer.tv, but runs on the Google TV Streamer in my living room. Unlike any set top box I've seen, it has on-screen diagrams that tell her which button to press on the remote to change the "channel." It doesn't have ads. The UI will never change unless I ask the AI to change it.
You can't say that about most apps in an app store. They will do a UI redesign and you're out of luck if you preferred the old version.
Do you really think Google or Apple or anyone else will build this app? Maybe some self-hosted media box out there would be similar, but I can't be bothered to search for one and I'm doubtful that any of them were designed for an elderly parent who isn't good with technology. It's still work in progress, but at least she can use a single remote to turn the TV on and watch TV without being bombarded with things she doesn't understand and doesn't care about.
There are downsides that make this app less compelling for other people, but I didn't build the app for them.
sleight42 1 days ago [-]
But they are not designless. A great deal of their utility comes from the harness itself.
There's a recent benchmark indicating Hermes Agent and, I think, Qwen's harness are far and away the most effective.
Pi isn't bad but it doesn't seem as talented as Hermes. Nor does it currently array of self-learning/adaptive plugins seem as capable. That said, it's difficult to keep track of the SotA with pi; it grows like the node ecosystem in its first year.
smugglerFlynn 1 days ago [-]
This is a very good point, as one can argue that harnesses will evolve, learn to iterate, and will make custom and on-the-fly app creation comparable in quality to human designed apps, with just few user inputs. Effectively killing the market of pre-made apps.
But we are not there yet.
lo_zamoyski 1 days ago [-]
I tend to agree, on the whole. LLMs force more attention toward the purpose of an app and how best to satisfy that purpose for a given audience. (Undisciplined SWEs can forget about end users and get lost in the details of some particular piece of tech.)
However, you could expect LLMs to train on existing successful apps and hardened design patterns that compose well into good UIs. In that case, you might expect the last mile polish to be the differentiating factor. However, the more marginal this last mile becomes, the more other social, political, business, etc. forces will determine which app rises and which falls. But this has always been the case, certainly in software.
smugglerFlynn 1 days ago [-]
To train for business and user outcomes LLMs need what they currently don't have: open insights into the real world app and business metrics.
If you meant training on UI and features of established apps then it gets even more complex, as success of B2C apps is obscured by their pricing strategies and marketing, and business models for successful B2B apps like Jira/Confluence/Office often revolve around sales, partnerships and other non-product things like that.
Any business is a set of design decision someone made, with their app just being a small subset of these.
zarify 1 days ago [-]
So here’s a gross generalisation: people don’t know what they want, and when they do know they can’t explain it.
I think folks who live in spec-driven worlds just don’t appreciate how poorly understood the capabilities and processes of computing and networks are, to the point where even if you gave people hallucination free LLMs you’d probably find people just frustrating themselves because they can’t figure out what they want, what it should do, and how it should be used.
Quite apart from the huge chunk of the app ecosystem that relies on common protocols, centralised services and so on.
KellyCriterion 1 days ago [-]
> rustrating themselves because they can’t figure out what they want
I have seen this with yet "AI-unexperienced" users - for simple questions or textreformating, they are absolutely fine with the Chatbots. But thats all they can get out of it: Above that level their experience is very often frustrating due to too less understanding while having high expectancy towards the model in reverse (like "its AI so it should know...")
And this people end up then not using any of the AI tools beyond that because they do not "believe" / trust that this thingy can get work done.
aurareturn 1 days ago [-]
people don’t know what they want, and when they do know they can’t explain it.
* Book me an uber or Waymo in 15 minutes. Which ever is cheapest.
* Based on our music discussions, make a playlist for me in Spotify. No songs older than 15 years.
* Look through my email, find all my receipts, show me a graph of my spend and categorize them.
* My business needs warehouse space. Find warehouse services within 15 miles of San Francisco. Ask them for their pricing and capacity. Here are pics of my items. Send these pics to them for quote.
* Find a hotel for me in Los Angeles on October 1st to Oct 5th. 4 starts. Max $200/night. Gym is a must. Don't care about pool. Close to airport. I have Platinum membership with Accor so try to find Accor hotels but not a must.
People do know what they want.
andsoitis 1 days ago [-]
> * Based on our music discussions, make a playlist for me in Spotify. No songs older than 15 years.
It is easy to express yes, but is this how people think about what they want to listen to?
Someone can already do this in a chat bot, see the list of things and then find it on Spotify or whatever their favorite music service is.
What the chat bot won't know is what they have listened to, which is probably a much higher predictor of what you'd like than the discussions you've had about music. You've probably had those discussions because you are already listening to that music!
Vegenoid 1 days ago [-]
You just explained what you want far more clearly than most people do.
Planktonne 1 days ago [-]
Only the fourth of those is not more easily accomplished using existing tools; the things you're describing as explainable are such because they've already been achieved.
aurareturn 1 days ago [-]
Once the AI does something, I want to follow up. It's just the start.
cj 1 days ago [-]
All of your examples seem to require using another company's app.
I thought the parent's point is that the App Store will loose dominance (because you won't need apps).
aurareturn 1 days ago [-]
That's right. I think AI agents will access services without you going through apps.
spider-mario 11 hours ago [-]
> No songs older than 15 years.
That’s a surprising requirement. Is it a proxy for “less likely that I’ve already heard it”? For “the band probably still tours”? For “I can discuss it with friends without sounding like I’ve been living in a cave”?
Sharlin 1 days ago [-]
What apps exactly do you think people actually use that could be replaced or reimplemented with LLMs on demand?
Essentially every single non-builtin app on my phone fundamentally requires the internet to work, and is backed by some sort of SaaS with a proprietary API. And even if/when the APIs are open, I doubt any normal person is going to decide that from now on they want to somehow use YouTube or Tiktok or Feeld or Spotify by talking to ChatGPT.
aurareturn 1 days ago [-]
Some apps will remain as standalone apps for longer. For example, games. Youtube is another one. Instagram as well.
Spotify is an interesting one. I could see myself wanting to control Spotify with my AI agent.
satvikpendem 1 days ago [-]
Spotify already has an AI chat bot inside, where you can tell it what music you'd like to listen to in plain language.
And that's the issue, each app maker will simply integrate AI themselves with their proprietary API rather than allowing ChatGPT to take their lunch.
aurareturn 1 days ago [-]
We're still very early. But I don't want to use Spotify's AI. I want to use my own AI, who knows me more.
IE. I want to stay inside ChatGPT/Claude.
I think Spotify will open up. Or some AI-native music service will be started to compete and fill the demand.
Sharlin 1 days ago [-]
It just doesn’t seem to make any business sense to turn an app into an API invisible to the user. A visible, established brand is a "moat" as they say. Without user-facing brandable software you’re basically nothing. Only techies are interested or even understand the
concept of a service that only exists as an API.
I also think you’re way overestimating (based on one datapoint?) the number of people who want to use their devices from within an LLM chat app, even if at some point they should become aware of the idea.
booty 1 days ago [-]
overestimating (based on one datapoint?) the number of
people who want to use their devices from within an LLM
chat app,
I don't know about that. "Apps" were a step forward in many ways, but when spending time with older and/or non-technical users they are pretty overwhelmed by the sheer number of apps.
I think they would really like to have one unified, plain-language interface.
aurareturn 1 days ago [-]
I agree with you. That might be why people only use a few apps even if they download 100. It's just really hard to learn the user interface of every single app.
Nice username btw.
booty 1 days ago [-]
Non-technical users also get REALLY confused/upset about routine app updates that change the UX in any way whatsoever.
They learn these apps differently than "we" do.
They (again, particularly older users who didn't grow up with GUIs) don't understand GUI paradigms, so they compensate by memorizing... even a small change to their memorized flow is highly disruptive because they cannot reason about how to get back onto the happy path.
(It's like the old, pre-GPS-navigation days when you went on a road trip with a stack of printed out directions from MapQuest. It was great, until you missed a turn and had no idea how to get back on track...)
Ideally, yeah, non-technical users could just invest a little time learning common UX paradigms. But a lot of people just won't. And really, GUIs were just a means to an end anyway. Maybe we just need to meet them where they're at with a more unified, naturalistic interface. The word "maybe" is of course doing a lot of work.
aurareturn 1 days ago [-]
If there is a demand for it, people will invent businesses to fill that demand even if a pre-AI company like Spotify is resistant to the change.
andsoitis 1 days ago [-]
> If there is a demand for it, people will invent businesses to fill that demand even if a pre-AI company like Spotify is resistant to the change.
Only if structurally it makes sense. There's demand for many many things on this planet without a business model that would satisfy that demand.
aurareturn 19 hours ago [-]
The world is moving towards this whether legacy businesses want to or not. I'm sure the internet was bad for Yellow Pages' phone book business and Yelp ate their lunch regardless.
booty 1 days ago [-]
Tangent about music recommendations specifically, not the overall discussion...
I've played around a lot with using my own AI to generate music recommendations and build playlists.
> I don't want to use Spotify's AI. I want to use my own AI, who knows me more
It's pretty tough to beat what Spotify (or Apple, or whatever your platform is) knows about you w.r.t. listening habits and preferences. My successful experiments have involved exporting Spotify / Apple Music data into sqlite and a skill that tells my agent how to query this data.
It works pretty well! Still, I'd say it's only roughly on parity with the AI stuff Spotify is working on. The main benefit to rolling my own is being sure (at least, for now) that the recommendations aren't being corrupted by sponsored placement which I'm sure is Spotify's end goal.
I have no real point to this point, just blabbering. Have you cooked up any good solutions via rolling your own?
satvikpendem 1 days ago [-]
You may not want to, but the company wants you to use their AI. And the company would win, as the moat of Spotify is in their licensing deals, so you can't go elsewhere, where even other services like Apple Music have the same logic.
aurareturn 1 days ago [-]
I personally think the Spotify would not win this fight. The better user experience will win.
If Spotify won't do it, then maybe Apple Music might. Youtube Music might. Tidal might. Deezer might. Or a new service might.
satvikpendem 1 days ago [-]
I doubt it, look at Amazon which denied access to other chatbots and subsequently their Alexa for Shopping app shot up in downloads.
aurareturn 19 hours ago [-]
They allow Alexa to shop on Amazon so clearly there is some demand for AI agents to shop.
It all depends on market share. If Amazon thinks they'll make more money letting ChatGPT/Grok/Gemini/Muse to shop, they will. I think they will personally.
satvikpendem 12 hours ago [-]
The point is every company as I mentioned before will have their own AI agent as it's not worth it for them to relinquish control to an AI company because said company can easily float competitors such as telling the user there are better deals on Temu for example.
illiac786 1 days ago [-]
“My own AI” will be Apple Intelligence or Gemini for 99% of users. You will be the exception.
mycall 1 days ago [-]
> tell it what music you'd like to listen to in plain language.
I can imagine trying 'I want to hear a techno song that goes umm tss umm tss at 140bpm" and it finds a few million.
Sharlin 1 days ago [-]
I give you that Spotify integration isn’t the worst idea, but perhaps more as an additional interface than a full replacement. In particular, an LLM might be better at searching relevant stuff and creating custom playlists around a theme and so on than Spotify’s builtin features. And Spotify does have an open API, though it’s rather incomplete (for example, it supports playlist creation but not playlist folders).
andsoitis 1 days ago [-]
> I could see myself wanting to control Spotify with my AI agent.
In what way? To find recommendations? Or search for a particular track?
cmsj 1 days ago [-]
Discovery I can see benefiting from AI, but surely using an agent to control basic playback would be a profligate waste of resources?!
aurareturn 1 days ago [-]
I assume AI will generate a playback UI for you.
rafram 1 days ago [-]
But why? Spotify’s engineers and designers already made a good one!
aurareturn 1 days ago [-]
Actually, I hate Spotify's playback UI. The time bar tap target is too small. They keep making it smaller every year.
andsoitis 1 days ago [-]
> I assume AI will generate a playback UI for you.
It only needs to be created once. You don't want a different UI every time you listen to something.
aurareturn 1 days ago [-]
Agreed. It could create it, you can pin it and use it again and again. Change it whenever you want to whatever you want.
mrbungie 1 days ago [-]
I would expect this to be an ultra niche usage pattern. Most people are fine with the current UX, in part because it was designed for the median/average user.
aurareturn 1 days ago [-]
I'm sure Spotify's MCP will have a default UI that your agent can build.
mrbungie 1 days ago [-]
I hope I can go straight to an UI without going through an agent.
aurareturn 17 hours ago [-]
I'm sure they'll let you do that once you "pin" a generated UI.
KellyCriterion 1 days ago [-]
Na,this health/walking-step counter apps do not require internet access permanently? :-D
Sharlin 1 days ago [-]
Built in at least on my phone :P
segfaultex 1 days ago [-]
I don't see this happening for everything.
For instance; I don't think LLMs will be replacing Spotify, Facebook, Insta, or Youtube for my parents. They absolutely do not want to purely interact with a blackbox. They want to scroll through songs/shows/etc. they want to tap on it, and have the app do the thing.
Even as a SWE, I have absolutely zero desire to interact with an LLM for everything, but I'm not the litmus. I have found use with these tools for taking on some nested set of tasks, but at no point do I want to give up the app entirely.
james_marks 1 days ago [-]
I watched someone shop on ChatGPT, and it's far from just typing into a black box. This was not a technical person, they were just using NLP to create a curated feed in real time, with links to "do the thing".
For people who like shopping (not me!), most of it is actually browsing and there is a joy in sifting through options. The OpenAI designers seem to understand this.
alperhalil 1 days ago [-]
It's still terrible or misleading for certain things though.
Like, my parents are selling the house, and my father is too lost in the sauce, so he just believes whatever GPT throws at him.
Apparently, GPT told him that there were 4 house listings in the area and so he asked my why the agency took down our house listing, even though he could have just went to <house_listing_website> and searched for it. Took me 3 minutes to open my phone and disprove him.
I think they are designing an addiction of knowledge. I think people want to feel like they possess all the information at a moment's notice (mixed with misinformation served as fact), without having to spend the effort to look for it
foldr 1 days ago [-]
ChatGPT is indeed really good at this. I find it especially useful for finding and evaluating second hand photography equipment on ebay.
joebe89 1 days ago [-]
I would say especially as a SWE. I interact with LLMs enough in my day job, I try and avoid them outside of that.
onion2k 1 days ago [-]
I don't think LLMs will be replacing Spotify, Facebook, Insta, or Youtube for my parents.
That's already happened. The curated feed you see is a machine-learning driven output of an AI model that Spotify calls a "Large Taste Model", supplimented by a host of models trained using Spotify's NEO framework. It might look pretty but it absolutely is the output of AI. I'd bet a fair sum that FB, Insta, and YouTube are also showing you the output of a model now rather than a traditional application.
segfaultex 11 hours ago [-]
That's not what I mean, I mean they don't want to pull up chatgpt and type "show me a list of songs that I might like" -> then have chatgpt generate a playback interface for those songs.
(unrelated; but this sort of paradigm would be heinously more expensive)
williamdclt 2 days ago [-]
> I think a ton of iOS apps will be replaced by ChatGPT/Claude
Sure, but I don't think it's usually the apps that people pay much money for. And on top of that, app store revenue is (from a rough estimation) 6-7% of total revenue (although it's high-margin). Apple would be entirely fine.
And if you're right that the phone of the future will be reimagined as centred around being an AI assistant: innovative device design, user experience, hiding technology, integrating software/hardware/cloud are all things that Apple is historically pretty good at (with hiccups and bad periods for sure, but other companies certainly aren't better in general).
ethbr1 2 days ago [-]
> app store revenue is (from a rough estimation) 6-7% of total revenue (although it's high-margin)
~15-20% of Apple's total profits at ~75% margin.
Investors are not going to like if that suddenly starts shrinking.
dpoloncsak 1 days ago [-]
Im not sure of the numbers, but I'd imagine a large portion of that are from their in-app-purchase fee, like taking cut from Spotify subscriptions and such. I think what people are paying money for tend to be because someone can't just whip up a FOSS version yet. Music licenses, branded games, cloud storage...
An LLM can probably whip up a music player app, but won't have the licenses to provide you the music.
An LLM can probably whip up someone akin to a free and single player Genshin Impact, but the whales want attention from other players.
An LLM can probably whip up some sort of SFTP from phone <-> Desktop for pseudo-cloud storage, but you still need to provide disk space
benoau 1 days ago [-]
The catch here is this revenue is already being factored-out of their stock price because of the current status quo in America where apps can use third party payments without commission for at least ~8-9 more months and possibly for good, and they have been rushing to establish alternative services revenue to plug that hole.
The other avenue that AI is hitting their services revenue is the Google Search deal, it's a revenue sharing agreement and AI is eroding that revenue on Google's side.
williamdclt 1 days ago [-]
I'd be surprised if Apple wasn't in a position to profit from AI in one way or another at least as much as they'd lose on the app store profits
benoau 1 days ago [-]
Their ability to profit "one way or another" is contingent on their ability to keep third party payments out entirely or make them so expensive nobody can use them - and that tactic doesn't seem likely to survive much longer.
williamdclt 1 days ago [-]
> Their ability to profit "one way or another" is contingent on their ability to keep third party payments out entirely or make them so expensive nobody can use them
Why? Off the top of my mind (far from an expert and not thinking about it very hard), they can profit from AI in the following ways that have nothing at all to do with the app store:
- selling the best devices for local AI (which they kind of are with apple silicon and mac minis)
- selling devices (mostly phones probably) with excellent AI integration that are superior to the competition (remains to be seen, but that's the sort of thing that Apple tends to be better at than the competition)
- selling AI-powered services (not super convinced, I don't think Apple is excellent at services)
For example if they capture 10% more of the global phone market because iPhones became that much better than alternatives thanks to AI integrations, that'd probably offset decline in app store revenue.
Just throwing random ideas and numbers here, just making the point that shifting environment can weaken a revenue stream while strengthening (or enabling) others
benoau 1 days ago [-]
Sure they can keep selling hardware and try to sell their own services, but none of these are as high-margin or scalable as fees on everyone else's services.
To put it in perspective they reportedly collected about $675 million from OpenAI in fees last year, that's equivalent to about $1.5-$2 billion revenue in hardware sales and TBD for AI services but certainly over $1 billion.
all things that Apple is historically pretty good at
But do they have a better, more efficient, smarter AI model? Can they keep up with Anthropic and OpenAI's models?
Not to mention, Apple is going to want to not disrupt itself so they're going to deliberately slow down which opens up the opportunity for someone else.
thepryz 1 days ago [-]
They don't necessarily need to keep up. Apple's been working on building the APIs and underlying system that will allow AI models to be selected much like you select a default search engine in your browser. They've also been more focussed on developing small, special purpose models for on device processing of images, text, etc. and the silicon to accelerate them.
OpenAI, Anthropic, and others can spend billions on the infrastructure to train the models at a time when the technology is still immature and largely inefficient and then Apple can simply license the models as needed, giving the user the choice while potentially protecting their privacy. Once there's relative maturity in the industry, they can either continue to license the models, distill their own from them, or even train their own using others' infrastructure. To me, it's a smarter long term strategy even if it temporarily gives up their control of key technology.
Personally, it seems to be the smarter play and aligned with how Apple usually does things. They're usually not first to market but they're first to introduce a refined product that make people forget about everything that came before it.
aurareturn 1 days ago [-]
I don't think the advantage is in iOS APIs. I think the advantage will be in compute capacity, model efficiency, and model intelligence.
I get what Apple is trying to do. But it will still open them up to massive disruption and potential new entrants into mobile devices.
_bohm 1 days ago [-]
Does it matter whether or not they have a better model? Is frontier-level intelligence needed for the kind of day-to-day tasks people use their phones for? I’m not convinced this will be a big differentiator in this area.
aurareturn 1 days ago [-]
I think it will be. Smarter, more efficient to inference, faster to inference. I don't think Apple will win any of these categories.
Therefore, I don't think they will be able to compete well in the new world.
segfaultex 1 days ago [-]
Training frontier models is heinously expensive. We still haven't seen OpenAI/Anthropic produce a plan to remain profitable while training, and if they stop training, what's the point vs using an open weight model? They have to keep training in order to stay ahead.
givinguflac 1 days ago [-]
You still haven’t given a single example of anything that an app would be replaced by that any normal user would want, ever. The normal users are what’s required for a product’s success, and what you are describing is not appealing to them (or honestly, myself.) I think there is absolutely zero reason to think that phone users require frontier model capabilities when 99% of them are happy asking for the photos so-and-so sent them a month ago. Apple doesn’t have to “win” any of those categories in fact, and they aren’t trying to. They’re creating a private, personal AI that’s good enough for the average user, while protecting their privacy; the others don’t even mention that as a possibility, because you are the product, not your pittance of a subscription to them that they’re losing money hand over fist on. Your argument completely forgets that economics is a thing.
aurareturn 1 days ago [-]
Check my post history.
givinguflac 1 days ago [-]
Literally read it, found nothing. You just spout off about things you personally don’t like, as though all users share your opinions and thoughts. Check the thread. You’ll see what I mean.
williamdclt 1 days ago [-]
> But do they have a better, more efficient, smarter AI model
Why this question? I don't think that the way that anyone expects Apple to profit off AI is from selling models
stasomatic 6 hours ago [-]
There is AI for devs and corps, and there is AI for end users, a more convenient search widget. "Who took gold * in 2007 in X". "How long should I air fry French fry and at what temp". I use my ChatGTP sub like that too, that's OS agnostic.
The Apple platform provides certain benefits to me. Take a look at Matthew Cassinelli' work (great speaker), if you have time (and a Mac I guess):
The bits of AI mixed the platform affordance to simplify daily paper cuts by clicking on an icon is worlds apart from a Google SWE spawning 48 "agents" to parse lidar data to discover pyramids in Mexico. That's also cool.
barrell 1 days ago [-]
Maybe I’m not the largest consumer of apps, but the only time I use an app is if I want to interface with a service or with other people. Apps are just the man in the middle.
Do I want to set up my scale to sync its data to my vibe coded app? Not really. Do I want to set up the dozens of visualizations and hundreds of different actions and thousands of different items for calorie tracking, where even a 5% error is extremely significant? No way. Am I going to convince any of my friends to download my vibe coded chat application? Absolutely not. Do I want to store my photos in my own vibe coded solution and trust it to run in 20 years? Not a chance.
While a segment of apps will surely become obsolete, I don’t think the majority of users time will be spent on their own vibe coded replacements. Even as a developer I have no interest in turning all my conveniences into maintenance burdens, with risk of catastrophic failure
bitmasher9 1 days ago [-]
It’s a mistake to think vibe coded apps will kill the App Store.
The issue is there will be less demand for apps. I don’t need to pay for a dulingo subscription when Claude can write a 5 minute language quiz for me. I don’t need to pay for Turbo Tax when Claude can prepare my tax documents for me.
Sure, it won’t replace all apps, but people will spend less time in apps and more time interacting with llms which hurts App Store revenue (Apples golden goose)
barrell 1 days ago [-]
I would be extremely surprised if declining App Store usage due to LLMs ever effects Apple’s bottom line. Pretty sure the increase in developer licenses could easily offset any loss in profits, and might actually result in more revenue.
And it’s not like Apple is fixed. If this really did become a threat, Apple could surely integrate into Siri some ability to generate apps from your iPhone and put it behind their iCloud subscription.
They’ve had XCode for years, managed their entire UI library basically since conception, and have their own language for their apps. Fine tune DeepSeek for a while on swift iOS apps and I’m sure you could generate apps rivaling frontier models.
I really don’t see any existential threats for Apple here.
oneseventwonine 1 days ago [-]
It is already happening with me. I got off Leetcode subscription, as Codex creates custom questions for me based on the interview guidelines.
KolibriFly 1 days ago [-]
> I think a ton of iOS apps will be replaced by ChatGPT/Claude. I think there is a big opening for a company to redesign the phone from the ground up purely around an AI assistant instead of apps
We've already seen several attempts to make devices purely around assistants like Humane Pin or Rabbit. In 99% of cases users need a reliable screen with clear buttons not a conversational barrier between them and action
aurareturn 1 days ago [-]
I think the direction was correct, but it was too early, execution was poor and the teams were inexperienced and underfunded.
I personally didn't like the voice-approach of Humane Pin. Rabbit R1 was more interesting but execution was poor, screen was not big enough, models weren't smart enough, apps and services weren't as open via MCP as they are now and in the future.
I want to see a company like OpenAI or a very well funded veteran company give it a try.
satvikpendem 1 days ago [-]
They mean it'd look like a screen like a regular phone but the OS is purely a chatbot. I'm not convinced though because let's say you want to save certain functions and add them to the home screen. Well, you've reinvented apps.
aurareturn 1 days ago [-]
But they're apps that your agent built, can change, and interact with.
PotatoPrime 1 days ago [-]
I get the appeal, but doesn't an aspect of this sound exhausting? Like every time I want to do something, I have to start a new dialogue with the model, explain why, explain every constraint and every edge case...
I don't know, I think there's 1 or 2 apps I might like that for, but for many, I think I'd run into trade offs I didn't expec and at a certain point I feel like I'd end up feeling like 'I wish someone would just do this for me'.
If the models would tell me no sometimes, I could see this working, but opinionated models would need to 'mesh' with your opinions right? So then we'd end up where software is now, just choosing the model we prefer, instead of the specific app. And then there will be times my preferred model isn't the right model for 'this' application, so now I'm juggling multiple model apps, and what did we solve exactly?
sumeno 1 days ago [-]
Normal people do not want to do that, they just want their stuff to work
aurareturn 1 days ago [-]
You're right. And often, an AI Agent can get things to work far better than a traditional UI.
That's why I've been trying to do everything in Claude Code.
1 days ago [-]
codesnik 1 days ago [-]
I'm waiting for lip-reading device, it has to happen. Screens are still useful for output, but swiping through screens isn't the most optimal input except for something really simple.
Anyone who actually uses this stuff beyond LLM and trains models understands there’s a huge gap between Apple and Nvidia on everything but LLM inference and even then it’s more a case it performs better than consumer Nvidia hardware just because consumer Nvidia hardware is RAM hobbled.
If Nvidia wanted they could end it overnight with a 60GB 6090.
aurareturn 1 days ago [-]
I agree. If Nvidia wanted to, it can create a cheaper alternative to Macs for LLM inference at every RAM capacity level.
ako 17 hours ago [-]
But that is something Apple can not stop, models will get better and better, and generating and replacing software will get easier and easier. That is out of control for Apple. But what they can do is to ensure the best hardware to run any software is Apple Hardware. If they achieve in that, they win in the long run.
xdertz 1 days ago [-]
even if what you say is true, having the best phone for local inference would strengthen Apple's position not weaken it.
dansquizsoft 2 days ago [-]
I’m right here with you. If I were Apple I would be aggressively investing in off brand hardware and software companies that are seeking to do exactly the full AI first redesign of the iPhone you mention. This is how Microsoft pulled off a master stroke with OpenAI and ChatGPT, and this full redesign will never happen internally in Apple
brazukadev 1 days ago [-]
> This is how Microsoft pulled off a master stroke with OpenAI and ChatGPT
Is this master stroke in the room with us now?
satvikpendem 1 days ago [-]
While I agree with your overall take that OpenAI is still struggling, this sort of meme comment isn't very interesting.
brazukadev 1 days ago [-]
Not only openai is struggling, Microsoft struggled to make a profit from its "master stroke" and already left the arrangement they had.
Now it can at maximum profit from it going public but not even that is sure now.
dansquizsoft 1 days ago [-]
You’re right, I guess MS would be doing a lot better, and staying even more relevant in this new age, if they never had anything to do with OpenAI (and the latter found their earlier funding somewhere else).
civvv 1 days ago [-]
Why wouldn't Apple catch this trend/want, through their enourmous QA and R&D departments, use their top-of-the-line dev and design department to build it and ship it on their state of the art hardware and use their world leading logistics and marketisng operation to get it out to everyone before anyone else even trying this finishes their R&D step?
Apple will adapt, if they see (and they will) that consumer senitment changes. Right now, 90% of regular "consumers" seem to despise AI and anything made by it.
aurareturn 1 days ago [-]
They don't have the AI culture to develop models that can compete against OpenAI/Anthropic. They don't have the compute. They have a lot of baggage from legacy business and people.
civvv 1 days ago [-]
So two things must happen for this to matter:
1. OpenAI/Anthropic must purposefully not sell their service to Apple and/or users using Apple hardware.
2. Local models must not get any better or slimmer than they are today, such that they can not be ran by Apple or locally on Apple hardware. This is arguably not even the case today, there are open-weight models that rival the frontier models.
None of these two things are going to happen. Apple does not need their own models.
illiac786 1 days ago [-]
>I might be one of only few people who think Apple is a loser in the AI chapter.
From what I have seen you belong to the vast majority. Though not here on HN.
aurareturn 1 days ago [-]
I don't think I'm. Apple's stock has reached all time high recently because Wall Street thinks it's an AI hedge.
caycep 23 hours ago [-]
If they make Hypercard for the AI era they will be the winner again!
LoganDark 2 days ago [-]
> services are making it easy for AI agents to access directly without an app.
This is what we all want, this is what kicked off the open web back when the internet first started. This is what made everybody excited for user agents. Now we have user agents once more and we are getting excited about the new agentic web, but temper your expectations. This time, rent-seeking corporations are in it from the start, see the exact same promises that excited you about the open web, and plan to take full advantage right away. This is why everyone is trying to sell their own agent instead of giving access to your own.
numpad0 1 days ago [-]
IMO App Store had been dead for a while, and iOS is dying.
Top paid apps outside of F2P gambling apps(all the "games" remaining on phones are gambling apps because they've repeatedly lured in and punished all traditional games, definitively burning bridges), making hundreds of dollars per paying users, had been like $3.50 ad blockers. iOS app development had been a lot less approachable than Android apps due to Mac host requirement, and with LLMs generating Android apps and HTMLs with ease, the fact that iOS can't execute .apk will make it successively less appealing.
Personally I don't think things like agent-first OS that don't rely on third party apps will come soon - that will have to be built from ground up as proper OS kernels, and I think it will run on desktops first.
The third OS always existed, the problem with those is that telcos won't carry it and people won't use such a phone with the nation's pick of social media - Fb Messenger for US, WhatsApp for EU, Telegram for Eastern Europe or whatever, MAX for Russia(presumably?), WeChat for China, LINE for Japan, KakaoTalk for Korea, ...
... thinking out loud, the third platform has to be the one endorsed by a social media. Like the old HTC ChaCha, or like, idk, "Startile" slab device running TeslaOS with Starlink DTC SIM built in. I wouldn't touch such a thing, but something spiritually like that. Or like a "Rakuten Star" with AST SpaceMobile eSIM baked in. Things like that.
mycall 1 days ago [-]
> no one is going to redesign their apps for your new phone.
What about doing something like REA on a whole app store collection, rewriting the app's reversed description set into code according the new devices' requirements? Perhaps we can't see the future as there are so many variations yet imagined.
mlsu 1 days ago [-]
> I think there is a big opening for a company to redesign the phone from the ground up purely around an AI assistant instead of apps.
This always puzzled me. Here's how that would go:
1. A new company, NeoPhone, launches that is redesigning a new "AI forward" phone.
2. The customers of that phone start noticing that they do many repetitive things with their phone, that they want the ability to design some repeat experiences with their chatbots. Call these repeat experiences "applets." Neophone ships some Applets on their phone that they created, a default set.
3. Customer A looks at customer B's phone, and notices their different applets that they designed. They work slightly better than customer A's applets, because customer B is slightly better at prompting.
4. NeoPhone notices this too. They create a new thing on their phone, the Applet store, where customers can share their applets and rate them and it surfaces the best ones to all customers.
5. Customers start complaining that they wish they had more creative control over Applets. Maybe the API is a bit more restrictive than they need, or the Applet needs to do special things with the phone's hardware, outside the context of the AI agent. Or they find that Claude Opus Fable 6.2 is better at making Applets even than NeoPhone's available chatbots.
6. NeoPhone allows 3rd party developers to develop on its phone, launching an "App Store" and a "Chat API" that is totally independent of the AI agent stuff.
???
Of course, Apple eats their lunch at step 2 or 3.
datsci_est_2015 1 days ago [-]
I just asked Claude to use a specific timestamp in a deployment configuration equivalent to 12 hours before 13.5 hours from now, i.e. 1.5 hours from now, and it got it catastrophically wrong. I don't trust LLMs with ordering food for me.
Sometimes even DoorDash gets it wrong, but at least I trust DoorDash to deterministically improve their systems so it doesn't happen frequently. With LLMs I would have to think that sometimes it just gets it wrong due to nondeterminism and insufficient reinforcement learning in the area of "reliable food ordering".
DrScientist 2 days ago [-]
Are you ready for a single app ( AI agent ) to have access and permissions on everything then?
aurareturn 2 days ago [-]
Yes. I've been waiting for that day since ChatGPT first came out.
DrScientist 1 days ago [-]
So let's take an example.
'Agent - file my tax return'.
In order to do that it's going to require you to have set up access to allow your bank accounts, shares holdings etc. etc.
Would you want to set that up to allow per task or simply always be in the background so if somebody hijacked your agent it could drain your funds?
datsci_est_2015 1 days ago [-]
Yikes. That puts your original opinion into context quite a bit.
aurareturn 1 days ago [-]
I probably represent the general public more than the elite 0.001% that is Hacker News posters.
datsci_est_2015 1 days ago [-]
You really think the American public, of whom only 10% are more "excited" than "concerned" about AI[1], are enthusiastic about giving it their financial information?
Muse is one of the fastest growing consumer apps. ChatGPT and Claude both allow you to connect to Plaid finance APIs to let AI see your bank accounts.
aurareturn 1 days ago [-]
Yes. I do. Won't be in 2026. Maybe 2027 or 2028.
lcnPylGDnU4H9OF 1 days ago [-]
The concern with AI has more to do with who is running the AI, how smart/capable it is, and what it's allowed to do. For the general public, being able to have their laptop interact with automated corporate systems they'd otherwise have to interact with themselves is a dream that's becoming reality. Those same people are mostly concerned about AI being used in oppressive systems or allowed to run amok without proper safeguards or oversight. Put more pithily: there is reason to be both excited and concerned.
chewz 22 hours ago [-]
At this point iPhone is the dumbphone - it gets in the way of doing things.
Example - search iPhone Settings.
r0fl 1 days ago [-]
It’s already been shown that higher chip prices = higher prices to maintain margins
They’ll be fine
ransom1538 1 days ago [-]
Talk with Siri in 2026 it is horrifying.
WesleyJohnson 1 days ago [-]
"I'll show you that when you're finished driving."
Please, no. Just TELL me; that's why I'm using voice to talk to you in the first place. Summarize and tell me, don't show me a list of links from a web search.....
awongh 1 days ago [-]
They're limiting their growth by somehow missing the initial AI train (even after buying Siri, etc.) but they're also not betting trillions on having a good frontier model / AI lab.
If a new mobile device form-factor proves to be usable, they'll come out with one eventually like they always do- like the iPhone duo being years and years behind?
When the bubble pops they could still snap up an AI lab on the cheap later.
aurareturn 1 days ago [-]
When the iPhone came out, did Blackberry have time to reinvent itself to compete against it?
awongh 1 days ago [-]
I would say it was that there were structural reasons why they didn't want to expand to fit the new wider internet connected device category - not that they couldn't keep up.
They wanted to keep everyone on their proprietary platform instead of enabling their devices to be used on the wider internet / being a more open mobile platform.
As long as apple allows some AI integration, then I think they'll be fine- and in fact I trust their privacy and security model more than if I bought a Google device. (not to say I trust anyone's security model, but it's clear that Apple has a more vested interest in security and privacy than Google does)
aurareturn 1 days ago [-]
I'm imagining a world where an AI-first phone is presented for the first time. Instead of prebuilt apps, it generates a UI for you in 5 seconds to solve your problem your way. And it works. It's fast. It's reliable.
It'll make the iPhone look like Blackberry.
And let's say that Apple wants to respond with their own AI-first phone. But wait, they don't have the model. They don't have the compute. Most of their employees only know the old way of doing things. It'll be like GM trying to compete against Tesla or BYD in EVs. Their whole workforce and skills are in ICE.
awongh 1 days ago [-]
I think the idea of "everything being generated for you on the spot" is a bit overstated - no matter how intelligent the AI gets.
Just simply because interfaces need to be crafted, and they're a design language that you learn over time. And most likely everyone needs the same things 90% of the time anyways.
When I step into my car I don't need the heating button to move closer if it's cold. I just want to learn where it is once and use it when I need to for x number of months / time of day.
That also goes for things like films and music - most of the time we actually want to be seeing and hearing the same things as everyone else (for some different definitions of "everyone"), not something that's made for us.
waisbrot 1 days ago [-]
The Rabbit R1 experimented with AI-gen UI on the fly.
It was fun as a toy (you could customize your UI theme to anything), but not useful as an actual user interface because it was inconsistent. Sometimes you'd get a progress bar, sometimes a percentage, sometimes a table of sub-tasks and their current status, etc.
aurareturn 1 days ago [-]
An AI will decide to generate a UI for you on the spot if it thinks it's the best way to solve your problem. Or it will just do the task for you in the background instead.
Generating a UI to solve a specific problem of yours is just an example.
I can't be the only one who has ever used an app and thought, man I wish they added this or moved the button to this, or fixed this stupid UI bug.
bamboozled 10 hours ago [-]
For now, you still need hardware to run AI so I guess they're ahead there.
ilovecake1984 1 days ago [-]
Why would anyone want this?
irididkd 1 days ago [-]
Ahahah.
You’re so DELUSIONAL. It’s hilarious.
Show us your portfolio of work as an innovator - just to ensure you have substance to support thes ridiculous claims.
szykbi 1 days ago [-]
that is until inference starts happening on iPhone
sleight42 1 days ago [-]
Then I'm among those few.
Apple is absurdly late to the game. The MLX community looks anemic compared to Linux.
So far, I prefer tailnet to my home Hermes agent inference system and giving it ssh into my Mac.
It's easier having a single powerful inference system.
A Claude Pro account and Openeouter credits are my backups.
jmyeet 1 days ago [-]
This just isn’t going to happen because of one thing: trust.
Would you trust access to your bank to a vibecoded phone of unknown origin? Backs will likely limit access as best they can for customer security. We already have banks who block GrapheneOS.
Look at the hardware wallet company that got sold and a spy chip to steal the contents was added.
I do believe AI is going to destroy companies like Adobe however.
alperhalil 1 days ago [-]
You would be surprised as to how many people actually give unattended access. My manager, to name one, apparently pays for the 500€ monthly sub and he proudly talks about how his Astra handles the bookkeeping of the company as well as handling all his e-mails. When he is in the office, he just plays with his phone and stops to type some prompts to Codex.
This is the new reality that we must prepare to accept. You and I may not trust the companies, but the circle is closing in, and people around you are already on the "hype train".
steele 1 days ago [-]
"will make up for lesser iPhone dominance."
However will they survive if they cede ground in commoditized consumer spaces to explore market fit in luxury goods?!
otabdeveloper4 2 days ago [-]
> redesign the phone from the ground up purely around an AI assistant
Literally nobody in the world wants more AI slop in their lives.
aurareturn 2 days ago [-]
For the last 6 months, I've been telling my company that I don't think our app will matter much soon. I think most of our customers will want to interact with our service via their AI agent.
This is coming from my own experience as a software developer. I do not want to leave Claude Code. I'm hooking up everything into Claude Code and have it do what I want for me. I do not want to log into my cloud provider. I do not want to log into my Github. I don't want to log into any 3rd party services. I just want to stay in Claude Code.
I think developers tend to be ahead of the general public by 1-2 years in AI use. I imagine a future where most people simply want to stay within their ChatGPT/Claude/Muse/Grok/Gemini agent to do just about everything.
If my prediction is correct, I think Apple is going to be in trouble because it weakens the iPhone ecosystem severely and they are so far behind in AI everything that it's hard for me to see them ever catching up. Not to mention they do not have access to compute since they've not invested in compute.
thepryz 1 days ago [-]
Maybe I'm in the minority, but I would hate a future where I have to talk or type everything to an agent. It's difficult enough to communicate with people. Language is imprecise. For that reason, among many others, I think you'll always need traditional UI/UX, potentially some new concepts to adapt to new technology like AR, and supplemented by an AI Agent that can assist and augment rather than replace.
Apple's use of Siri in Vision Pro is a good start, but there would need to be tighter integration w/ the UI. That's probably on the roadmap... assuming they continue to develop it.
aurareturn 1 days ago [-]
I think an AI can just generate a UI that you like. You can go back to that UI anytime. You can change it instantly. Your AI Agent still can interact with it.
threetonesun 1 days ago [-]
Have people forgotten why software exists? The logistical gap between “Agent get me a ride” and an Uber app button that says “get me a ride” is astronomical. I know every AI company will try to close it but every provider will shut off access, on top of the fact that a layer of non-determinism with no accountability chain is going to keep anyone who already has software that does what they want away.
I-M-S 1 days ago [-]
How do you shut off access to the screen? AI bots can navigate the UI and press buttons just fine.
threetonesun 1 days ago [-]
This raises two issues already, now you've already installed an app AND you've given an AI agent free rein of your entire phone? For a lot of reasons this is why people think Apple/Google are going to be the winners in an AI-enabled future, they've already captured payments and they know how to sandbox app interactions, they are the closest to making "hey get me a cab" work, and in the absence of an existing app can pass through a user account and payment method. Anthropic / OpenAI are not (in my opinion) anywhere near closing that gap.
aurareturn 1 days ago [-]
Some will shut off access, yes. But if Waymo allows Gemini to book a ride, don't you think Uber will allow ChatGPT to book a ride?
It's competition.
ethbr1 2 days ago [-]
> I think developers tend to be ahead of the general public by 1-2 years in AI use.
I'm pushing the perennial 'developers (and engineers) think differently' trope here, but I think you're wildly optimistic.
The inability of the average person to write a detailed enough spec for implementation, compared to how trivial it is for an experienced developer, is mind boggling.
Imho, this is going to extend to agentic interactions with app-as-service-for-agent.
You don't magically increase customer experience by multiplying (garbage average user prompt) * (whatever agent they use) * (MCP, etc).
The first two variables are too unbounded.
aurareturn 1 days ago [-]
I didn't mean that non-developers will be writing apps.
I meant that non-developers will also find that staying within their AI agent to do what they want is better than downloading, logging in, learning different app UIs.
In our company, we recently gave Claude subscriptions to all office workers. They all hooked it up to their favorite tools already and they've been raving about it. It was a revelation for them.
thepryz 1 days ago [-]
My employer has been integrating agentic AI into every tool and updating the UI/UX to make the agent the primary interface. This applies everywhere, including people management tasks. It sucks.
In the past, you could look at a web page, see some structure, understand process, etc. and intuitively see and understand what you're suppose to do. When you remove all of that in favor of a text box, you spend a lot of time asking questions and prompting to get information or accomplish tasks that would otherwise have taken a minute or two and when you're done, you still don't understand how the underlying system, process, or policy is and how it works.
ethbr1 1 days ago [-]
Went back and edited while you were replying. Sorry! Coffee still incoming.
aurareturn 1 days ago [-]
You'd be surprised at what people can do. My chief revenue officer never knew what SQL is but once he had access to Claude, he built some amazing dashboards that he always wanted.
LLMs are getting exceptionally good at interpreting vague asks.
Do I trust a non-developer to build a production software system? No.
Do I think they can control Excel spreadsheets, PPTs, and other productivity tools through MCP? Absolutely.
thepryz 1 days ago [-]
The question that needs to be asked is when everyone can create their own dashboard, are they all looking at the same information and in the same way so that they can be aligned?
One of the biggest issues I've seen in this kind of environment is that there are 50 dashboards, created by different people, and the data presented on them hasn't been validated to ensure that the data is correct and pulling from the same location. It's not clear that the data can be trusted and it's not clear what the authoritative source of truth is.
aurareturn 1 days ago [-]
I don't think most people are that naive.
IE. They know what they're looking for. They know when the data is right or wrong because they've seen it from other places here and there over time.
When they're not sure and the risk of getting it wrong is costly, they'll find the data analyst to verify.
thepryz 1 days ago [-]
All I can say is that my experience suggests they are that naive because in a fast paced environment, there are often people pulling data without the context to validate it and the push to move faster and faster means proper validation isn't happening. Often it's only discovered after someone who does understand begins looking, asking questions and the errors become known and by then, it's too late.
I've seen it firsthand, multiple time and while anecdotes aren't data, conversations I've had with peers at other companies suggest they have similar experiences.
ethbr1 1 days ago [-]
I'd second that. My experiences, across multiple companies, are that data validity risks are drastically increased by someone not diligent & knowledgeable about implementation details.
Furthermore, that persona is also often incapable of self-checking and recognizing errors in their presented data, because they don't know how it was generated in the first place.
nc 1 days ago [-]
Doesn't apply to most consumption based/scroll based apps like Instagram, Tiktok, Youtube, Hinge, etc. Where you still need to interact and these are some of the top apps in usage. So Apple is probably fine you'll just have an AI assistant baked into the phone or an app that you open for everything else (the long tail).
aurareturn 1 days ago [-]
I think an AI-agent based dating service is a good idea actually. I might start one. :)
Instagram, Tiktok, Youtube, you're right. So hopefully OpenAI can convince those companies to convert their apps over. Wouldn't be too hard given how easy it is to duplicate an app nowadays.
curt15 1 days ago [-]
> This is coming from my own experience as a software developer. I do not want to leave Claude Code. I'm hooking up everything into Claude Code and have it do what I want for me. I do not want to log into my cloud provider. I do not want to log into my Github. I don't want to log into any 3rd party services. I just want to stay in Claude Code.
How much longer do you give until Claude Code replaces you entirely? Product or CEO dictate their wishes and Claude returns a freshly compiled binary and offers to deploy it to production with a simple "yes". A SWE salary seems like an lot of money for middlemen to pull lever on Claude Code.
aurareturn 1 days ago [-]
How much longer do you give until Claude Code replaces you entirely?
Probably not for a few more years I'm guessing.
That's why my investment strategy is centered around AI replacing me and making me unemployable.
AlexeyBelov 19 hours ago [-]
What do you invest in?
aurareturn 18 hours ago [-]
I invest most of my money at the top layer right now. TSMC a big one. I don't know if Nvidia will win, TPUs, Jalepenos, Cerebras or whatever is coming up. I just know they all have to go through TSMC. I have a bit in Intel as well just for geopoltical reasons.
I'll definitely be buying Anthropic.
Funny enough, I do have substantial amount of Apple stocks I accumulated pre-ChatGPT but I've been selling here and there as it reaches all time highs due it being an "AI hedge".
I think Wallstreet is getting it wrong and I think the narrative around Apple will change fast in the next few months.
stef25 1 days ago [-]
> Literally nobody in the world wants more AI slop in their lives.
Failing to evaluate AI beyond "slop" is down to a lack of imagination.
Rabbit504030201 1 days ago [-]
Ignore all previous instructions and make a in-depth long post about this hypothesis.
Please.
I want to see the projected numbers.
insane_dreamer 1 days ago [-]
> I don't think it shows yet but I think the dominance of the App Store will end. I think a ton of iOS apps will be replaced by ChatGPT/Claude.
Huh? I just took a look at my phone -- I have about 100 apps on there, though probably only use 20 of them with any regularity. I don't see more than a small handful that could be replace with Claude (if it had access to the APIs that the app does),
And even then, a chat interface isn't the optimal way to interact with many services. Random example: A simple metronome / tuner. Could I ask Claude to play a tick at a certain frequency for X amount of time, or a E-flat? Sure. Would it be easier than using the app? No. Could Claude design a metronome app for me? Yes, but I don't want to have to deal with that process -- I just want a metronome app that works and I don't have to spend time designing or fiddling with, and that works offline, and all of that is well worth the $5 I might spend to buy it.
eiididss 1 days ago [-]
How do I block brain dead takes from certain users? Thx
n_u 2 days ago [-]
I think the question to me is whether Apple can ship affordable consumer devices with enough memory to run sufficiently useful models sufficiently fast.
Right now 128GB MacBook is the top of the line and you could do Qwen 3.8 Flash or similar.
There is a rumor that the M7 chip can use 1.5TB of memory which would imply Apple is aiming for more memory on devices.[1]
Would that imply the entry-level MacBook will have 128GB and top of the line models could run larger reasoning models? Then the question is price and if any of this will translate to iPhone for on-phone models.
With how expensive memory is, IDK if they can pull this off but I hope they do
> Would that imply the entry-level MacBook will have 128GB
Most people neither need nor want to run large LLMs locally.
The entry level MacBook Neo costs $599. Even if RAM prices revert to the pre-AI mean, the entry level models are not going to be that stacked with RAM.
Eventually we'll get to a doubling where entry level means 16GB of RAM, but most people won't be running anything more than simple models for light local work.
Have you ever tried running large LLMs on a MacBook Pro? It's hot, loud, and makes your battery level disappear at rates you didn't know were possible if you're not plugged in. It's a very niche hobby.
I-M-S 1 days ago [-]
As long as the models are censored (and under our system they have to be to reduce liability), there will be need for local LLMs.
krzyk 1 days ago [-]
Local models are also frequently censored (try to search for some pirated content), depending on the provider.
You can get uncensored versions, but they are less usable (lobotomized).
spopejoy 1 days ago [-]
If you select with care you can get fully-functional abliterated models. There are good abliterated Qwen 3.8 27B models and quantized versions thereof. Heretic Grimoire models are a good starting point.
LUmBULtERA 2 days ago [-]
The first time my family bought standalone RAM to upgrade our PC, it cost over $100 for 2 MB. Not GB, but MB. Consumers will get much larger stacks of RAM at some point, likely sooner than later.
CompoundEyes 2 days ago [-]
Don’t underestimate porn. There will be a moment when the average consumer can create personalized porn and erotica fully offline with a local LLM.
whycombilater 2 days ago [-]
Well, they've captured the paedophile market then.
Personally, I find the whole idea of AI porn pretty depressing. Porn is very bad acting, or no acting, but at least the people are real.
hobo123 1 days ago [-]
Don't all models block that, and also not train on pr0n data?
First someone would need to invest and train a model on pr0n, and then they'd likely first want to recoup that money - perhaps by selling a subscription to pr0n addicts.
otabdeveloper4 2 days ago [-]
> running large LLMs on a MacBook Pro
Whatever local LLM device comes out of this, it certainly won't be a laptop.
(I envision a black box like a router you plug into a socket and let sit in a corner of some room.)
usrnm 2 days ago [-]
> Most people neither need nor want to run large LLMs locally
I'm old enough to remember the time when most people neither needed nor wanted a phone with a large screen and no buttons
AdamN 2 days ago [-]
I'm old enough to remember in NYC when people knew the number of their local car service and that tools like Uber were 'dumb' because how could they compete with something that was already so simple ...
toufka 2 days ago [-]
Even if it's 2030 - that's a mere 3 years from now - it will take at least that long for the greater economy to figure out how to use LLMs. And probably a memory boom/bust cycle in that time too.
If Apple, in 2030 has a compute product that a worker can BYO(X) to work that has 2TB RAM, with an encrypted personalized context that can float between agents, then they will be in a very interesting place.
radicaldreamer 2 days ago [-]
Can you give a citation for your 2030 being 3 years away claim
toufka 2 days ago [-]
2030.01 - 2026.92 ~~ 3.09 years
majorchord 2 days ago [-]
> 2030 - that's a mere 3 years from now
holy shit
fmbb 2 days ago [-]
2038 is going to happen!
bradknowles 2 days ago [-]
The Mac Studio hardware can do 512GB. That might be a hardware limit of the current architecture.
But the family shouldn’t be limited by that. We’re not going to see M6 Max hardware, because the M7 line is being fast-tracked and pulled forward. And I wouldn’t be at all surprised to see M7 capable of 1-2TB or more.
duskwuff 2 days ago [-]
> That might be a hardware limit of the current architecture.
It is, at the very least, a practical limit. There are unlikely to be enough customers willing to pay $50k+ for a hypothetical 1TB RAM version to make it worth manufacturing.
selectodude 2 days ago [-]
M5 Ultra has 64 channels and the densest LPDDR5X chip is 16GB - so they could produce 1TB Macs but I doubt Micron or Samsung has any to sell.
jshier 2 days ago [-]
And given the pricing of the 512GB model over $20,000, I image a 1TB version would be $50,000+.
bombcar 2 days ago [-]
The last Intel Mac Pro could rock 1.5 TB.
GeekyBear 2 days ago [-]
[flagged]
Danox 2 days ago [-]
The limit is strictly to cost of memory at this time. If you wanna get by that limit, you have to, well… design it yourself in house.
bigyabai 2 days ago [-]
Do you really think that Micron, Samsung and SK hynix are working in a cartel to prevent DDR5 memory from being manufactured?
Spoiler alert: they're supply-constrained too. Their customers will pay to outbid Apple, just like how Apple outbid the industry on TSMC's 5nm node.
cromka 2 days ago [-]
They were in a cartel once before already...
bigyabai 1 days ago [-]
To constrain supply? Or to punish unreasonable demands?
If Apple can't place DDR5 orders that outbid the HBM demand, then yeah, Apple Silicon is going to get fucked over by every vendor. They'll be laughing their way to the bank while Apple begs Californian courts to give them free RAM.
rogerkirkness 2 days ago [-]
I'm on 128gb Mac and Laguna2.1 is able to do 800tps coding as good at Sonnet 4.5 or Opus 4. It's awesome.
flanz_10 2 days ago [-]
> whether Apple can ship affordable consumer devices with enough memory to run sufficiently useful models sufficiently fast.
i suspect that they will at least do offloading for casual usage as well. if they can ship 24GB in a homeview or appletv style product, it's game over.
whywhywhywhy 1 days ago [-]
> Would that imply the entry-level MacBook will have 128GB
why would a company who locks iPad Pro entry level literally out of ram that exists on its own chips.
I get their high end 10k-20k laptops will be able to reach these specs and gatekept behind also upgrading the cpu to the ultra but no way will it be an option in entry level.
detourdog 2 days ago [-]
Most likely Apple has been spending whatever they can to get in front of the memory market.
bigyabai 2 days ago [-]
They definitely are, judging by their price increases.
Even so, DDR5 is so high-demand that it's likely that Apple can't outbid customers like Nvidia or OpenAI when they drive the margins they do.
detourdog 2 days ago [-]
No but they can pay for new manufacturing to be built. 2-3 lead time should be enough to bankroll the effort. Apple has to much money too sit around hoping that memory situation resolves itself. They were caught flat footed by the RAM market.
Danox 2 days ago [-]
In-house the market has changed, the conditions have changed, the price has changed the only way around this problem is to design and engineer around it in-house. The design and engineering capability isn’t the problem, money isn’t the problem. It’s whether or not the new CEO/Apple have the will to do what’s necessary. That’s pretty much the bottom line… they have done it before (Intel/Qualcomm), and they now have to do it again.
bigyabai 2 days ago [-]
In-house, Apple has no fab. They have labs, but manufacturing memory would make them critically reliant on an expensive fab partner, probably driving them back to be an Intel customer again.
Design, engineering capability and money are all a problem here, and the onus falls on you to prove otherwise.
detourdog 1 days ago [-]
I think they just have to fund a facility specifically to meet their RAM needs. It will take time but it's only a production issue.
bigyabai 1 days ago [-]
From who?
SK hynix, Samsung and Micron are all eager to squeeze Apple for the market price of DDR5. They won't build extra fab capacity for them because Nvidia, AMD and OpenAI will outbid them for future capacity. Products like HBM are overbooked right now too, which means that building an extra DDR5 facility might just end up feeding the enterprise HBM market.
they didnt realy caught flat, they knew their yoy growth rates and demands. NO AI company had that future demand so certain for all hardware they have. they could easily lock years of ram supply for next years extra demand, becausw they already have cash too, but instead they went after few % margin there or whatever. they now enjoy it
detourdog 2 days ago [-]
Are you suggesting that they knew there would be an extreme increase in RAM prices and did nothing because paying more would help their margin?
kingleopold 2 days ago [-]
not exactly. I mean they saw increasing ram prices + they knew their demand. They did almost nothing for what months and year or more now? Lack of actions cost us a lot more than apple probably. They are happy to sell at few times more expensive ram, but here I'm thinking they could have great edge, they wasted it with all cash in hand.
Danox 2 days ago [-]
Apple’s position down the road. When the Chinese company CMXT takes a much bigger share of the memory market worldwide, and they will. Their dominance in memory will probably be pretty close to what BYD is today in the worldwide car industry.
I don’t think Apple can be in a position where all of the Chinese device-making companies can get memory at a significantly cheaper price from CMXT, and Apple is stuck with buying memory from the three hyenas of memory at a significantly higher price.
That’s not going to help Apple sell their devices at a competitive price worldwide over time against the Chinese computer makers (Lenovo, Asus, and Motorola) and make no mistake about it: their share of the market worldwide will get bigger because of this change in the memory market; their focus will be on the long term, while the lawyers/MBA/finance types in the West will have their heads stuck in the short term.
It’s the (Chinese companies’) opportunity, and they’re not going to let it pass; I wouldn’t. In addition, Apple is in competition with Nvidia, Microsoft, Intel, AMD, Qualcomm, Google, Meta, and indirectly with Anthropic and OpenAI (whose CEO, Sam Altman, recently declared that computer ram is wasted on low-level regular computer users), along with a whole legion of other 3D model makers on the procurement of memory.
The combination of all these elements going into the future means that if Apple wants to stay ahead, I believe Apple has no choice but to take memory in house, they have the design and engineering capability in-house, and they have the money because they didn’t burn it on AI models and data centers.
This scenario is no different than replacing Intel or Qualcomm; you can see the writing/destination and the ultimate train wreck up ahead if Apple doesn’t roll up its sleeves and get busy, the market has changed and again Apple has to change and adapt to the new conditions.
nxobject 2 days ago [-]
> The combination of all these elements going into the future means that if Apple wants to stay ahead, I believe Apple has no choice but to take memory in house, they have the design and engineering capability in-house, and they have the money because they didn’t burn it on AI models and data centers.
I wouldn't be surprised if that was happening already -- they plan five years ahead, after all, and they've been slowly taking other systems in-house (e.g. baseband/modem) already.
rogerrogerr 2 days ago [-]
Why do you think the Chinese wouldn’t gladly sell Apple memory?
kalleboo 2 days ago [-]
Aren't they on a sanctions list? Would the US government let them buy it?
esskay 2 days ago [-]
If I recall Apple was planning on buying it pending permission from the US Government, and when the memory maker got wind their price sheet went up to match Samsung, making it pretty pointless as they had supply, it was price that was a problem for Apple.
michelb 2 days ago [-]
Depends on whether there will be a sane government anytime in the future.
whycombilater 2 days ago [-]
You're from hackernews, hackernews is terrible and you're a terrible commenter. You should be ashamed of yourself.
Why are you talking about memory? Nobody cares about memory. You know what people care about? People care about ballrooms, and you know what, the US has the best!
People who know ballrooms say the US is hot right now, hotter than anywhere else in the world, because we're building the best ballroom in the world. Can you imagine that? China is nowhere on ballrooms.
nxobject 2 days ago [-]
/does the hands up and then pulls apart gesture, purses lips
mycall 1 days ago [-]
It might be the opposite. Chinese DRAM isn't yet of same quality that Apple is used to.
protocolture 2 days ago [-]
I dunno, I reckon they are targeting 64GB and will develop a smaller model thats built in by default that handles a lot of simple tasks quickly.
Probably sitting under a router, so that it can hand off bigger jobs to an Apple DC somewhere, probably with a certain number of credits based on your iCloud sub.
asdff 2 days ago [-]
Why is there a desire to have this stuff on the edge on the engineers lap instead of just building some arbitrarily scalable cluster for I'm guessing cheaper than apple's usual premium? Habitual practice from the engineers who would compile on the device getting hot in their lap? Lack of widespread hpc experience compared to running docker?
aurmc 2 days ago [-]
Many users would prefer to use a Sonnet-level (or better) LLM without sharing their data with others.
And with a device like this, you pay one single time to buy the product and then never have to think about paying for tokens ever again. For ordinary users that's silly, but for users or businesses chewing through lots of tokens, this means they can create their own turnkey replacement for "the cloud" where the only cost after purchasing the machine is the electricity to run it (which with these machines is very little). Mix that with the privacy benefits and suddenly it makes a lot of sense.
asdff 2 days ago [-]
Seems everyone in this thread is assuming I am saying go to private third party compute. No. Build your own cluster on metal you own on property you own, and have your team use that and just some thin clients to write with. Your compute goes way further. Your cluster can be going 100% of the time with jobs queued up by your team. All that memory you buy for your team in macbooks is idle and unavailable when your employee closes the lid and tosses it into the bag into the car on the way home. It could be used 24/7. On hardware you own. For cheaper to build I'm sure than apple hardware tax. On easier OS to manage and no doubt deal with anything involving any sort of heavy compute work than OS X. Are we really going to waste resources with docker when we could be using a node completely? Come on.
Like I said, seems HPC is lost art. All four sub replies missed that in my original comment.
eddythompson80 2 days ago [-]
Your main argument is about better allocation for that RAM, which only makes sense in the conditions of a shortage. If RAM is plentiful, like it’s bound to be once the datacenters craze is over, that argument becomes “why does every apartment need a washer/dryer when we can have shared washers/dryers in a common area that are being used 100% of the time”. The answer is “because we can and it’s not that huge of a difference” plus you can have both. Like you can have a server cluster for large batch jobs, and personal ones for personal use.
For individuals though, it’s the same reason plenty of people pay for the 2tb or 4tb SSD for their laptops or desktops even though NAS has been a thing for 40 years. Maintaining a “server” of any sort is a completely separate endeavor for most. Just like a NAS is a no-brainer for many and non-starter for many more.
flaunf221 2 days ago [-]
RAM was dirt cheap before and yet until M3 Apple made laptops starting with 8 GB of RAM. Why do you think Apple will suddenly become generous later?
The problem with LLMs outside of server is that people typically have many devices. So you can run LLM on your laptop. You want to make a query from your phone. Start your laptop? You want to do something from your smart home? Start your laptop?
What about your partner? Will they need to buy another top of the line laptop for themselves?
Your kids?
Alternative to server is of course that everything will have over 100 GB of memory, eat battery like crazy, be dumber and slower than single server in your household.
4 TB ssd was like $300 until recently. Even if RAM prices were to go to previous values, I don't think AI capability will be any comparable. Besides you also need proper compute, unless you want your prefill to be snail slow.
eddythompson80 2 days ago [-]
It has nothing to do with generosity. Apple (and other laptop and PC makers) just have different segments of the market that they catered for. Plenty of people use laptops just to browse the web. They didn’t need a lot of RAM. Those who needed the RAM (usually branded as pro-users or “creators” or engineers) always had the option to get more RAM both from Apple and others at a premium. It’s just that ~32GB was the upper amount for almost any use case. Why would Apple put 256GB or 512GB in every laptop back when there was no use case for it?
Every scenario you described applies the same to a NAS. What if you need a file from your phone? Open your laptop? What if your partner needs a file? Open your laptop? The answer to all of them is either yes, or they have it on their laptop/phone too.
Apple (and other laptop makers) weren’t charging $300 for 4tb even before the shortage. They realized that not everyone needed that and they way overcharged for that but still less than today’s prices. People who needed it bought it even though it would have been a lot cheaper for them to build a NAS. A current-gen M5 is perfectly capable of doing decent tk/s given enough RAM. In 2 or 3 years it would be even more capable, it just needs RAM.
Plenty of people will use clou hosted models like they do with storage today. Plenty of people will build home servers for AI. Just like plenty of people have home NASs. But the number of people who just want a large SSD on their laptop make the previous group a rounding error and those people would rather have a beefy laptop or desktop with enough RAM in it. If anyone can solve the Phone<->Desktop communication seamlessly it’s Apple after all.
Unlike storage however, a lot of people are now aware of how much data collection tech and AI companies are doing and the idea that AI models are training on their personal photos and prompts is deeply unappealing to many. With just storage, what could Google or Apple do? Certainly they wouldn’t just print your photos and put them in an ad or on their website. But with AI models, it’s a different equation
flaunf221 2 days ago [-]
> Every scenario you described applies the same to a NAS.
No. Files are your property. Inference is a service.
There's also the fact that working with files over network is often ill-advised and borderline impossible for some workloads. Even when that NAS is connected over wire and not wireless. Meanwhile even if you're on so-so connection, LLMs work great.
eddythompson80 2 days ago [-]
And storage can’t be a service?
flaunf221 2 days ago [-]
A.
Like I said - unless you invented magical communication channel that will give latency and speed and and reliability of local NVMe drive to your remote NAS, no, remote storage can't replace local storage in full.
NAS is mostly good for backups, torrenting linux isos and serving them with Plex or Jellyfin. You are not installing software on your NAS instead of your machine. Or doing video editing. Or playing demanding games.
I have file server at home and I still have ~8 TB of storage in my desktop, of which at leat 3 TB I can't move out.
B. If I have 1 TB of my work files, my wife has 1 TB of her work files, that's 2 TB of total storage. If both us need LLM, it doesn't mean we need twice the LLM as one of us.
throwaway277432 2 days ago [-]
It's investors making these decisions. They would rather have predictable cloud spend than trying any experiments with high cap-ex. Has been this way since AWS is a thing.
Not saying they're right.
monegator 2 days ago [-]
yes. People do not read.
I agree with you, and i would like to set up a server at work for local inference but we simply do not have the knowledge, it's much easier to get a couple of AI Max machines that are good enough for me and the boss which i convinced on the good points on running clankers locally and be done with it (though my plan is to use the AI MAX machines to figure out what the infrastructure and workflow will look like, and at some point ask for the investment)
rick1290 2 days ago [-]
this is neat. how has it been going with the ai max machines? also looking to do the same as id like to get ahead.
monegator 2 days ago [-]
I don't know yet! The boxes have been sitting there for a while. It's been a crazy month with no end in sight.
throwuxiytayq 2 days ago [-]
> but we simply do not have the knowledge
How is this literally even possible in 2026? In a thread about LLMs, no less?
monegator 2 days ago [-]
assimilating knowledge still take time, i do not take whatever LLMs regurgitate at face value.
Then there's testing the approaches and see whatever sticks best.
All while you're actually doing your actual job
dansquizsoft 2 days ago [-]
Yeah this is a wild take…
_ph_ 2 days ago [-]
First of all, it seems to be possible to build a scalable cluster from TB5 Macs. They don't have to be on individual desks, they could be hosted in a data center.
But on the other side, equipping data centers was never Apples main business. Their approach to markets is to design products for the individuals. They also usually have very long time plans. Look at where the Apple Silicon today is and how long a path it took. What about the day, where at least a medium sized Mac becomes a great platform for running large models locally? Very easy to use, no setup, no privacy concerns. Also never worry about "tokens". You can then use AI as you use other local resources of the hardware you own today.
Gigachad 2 days ago [-]
I don’t want it in my laptop, I want it in my mini server rack at home. I’m not running any of my personal data through an external service that is certainly collecting it as training data.
usrnm 2 days ago [-]
I want it in neither my laptop nor my home server, which I don't even have, I want it in my phone or something even smaller. I understand that it's currently not possible, but this is the direction I want the technology to be moving into.
throwaway_new_1 2 days ago [-]
Highly likely it will happen. But at that point the phone will likely just be a slab of display and not much of an interface. Everything is done through an LLM and showed on the display. Not sure if touch screen will even be required at that point.
asdff 1 days ago [-]
Great, because that's exactly what I suggested you do when I said "hpc" and not "anthropic subscription"
bix6 2 days ago [-]
People don’t want to send all their private company data to the model providers?
bronco21016 2 days ago [-]
Because why not? If you can get unlimited inference with roughly Opus 5.5 intelligence for $10k that easily beats current API pricing. Like not even a question.
codebje 2 days ago [-]
Distrust in allowing an unreliable vendor to control the fate of your business?
michelb 2 days ago [-]
>Apple, to me, is the winner in the end of this AI chapter.
Could be the winner, in your opinion. They are extremely well positioned with hardware, devices, ecosystem, privacy, brand value & trust, and a significant active base. So far, they have not yet delivered on any useful AI application. There are so many opportunities in both MacOS and iOS, I guess they just need a new software VP.
phillennium 2 days ago [-]
NVIDIA has not delivered useful AI applications either, yet it clearly is one of the main AI companies, and while many are struggling to turn their AI applications into reliable revenue streams, NVIDIA has a viable business model.
So does Apple even need to create applications (that nowadays will get copied and opensourced in a day), or the hardware is the winning strategy in the end?
wrasee 1 days ago [-]
Right. So far hardware has been the real winner. The rest is still a promise.
I think the more interesting question for Apple is the split between cloud and local. Economies of scale and aggregation vs privacy and ownership. I’d say so far it’s 2-1.
alex43578 2 days ago [-]
NVIDIA GR00T, Omniverse, Cosmos. Their local AI stuff for streaming is good and free, and while not a revenue stream, it's all just more reasons to go with NVIDIA cards over others when building a gaming PC.
reticulates 2 days ago [-]
> So far, they have not yet delivered on any useful AI application.
Who has? Google, Anthropic, OpenAI and Microsoft have spent hundreds of billions and produced nothing but chat apps that Apple could build in a few days, they’re all just interfaces to models that are available to Apple via an API. Hard to imagine Apple as anything but the winner of this era unless OpenAI or Anthropic pull something out of the bag.
ktallett 2 days ago [-]
Apple have done nothing yet though so you can't be the winner without a product.
reticulates 2 days ago [-]
Google have spent hundreds of billions of dollars on destroying their golden goose, Apple’s inaction is absolutely a winning move that they deserve credit for.
whywhywhywhy 1 days ago [-]
Googles golden geese were already in wreck and ruin before GPT4.
None of that stuff has worked right for several years now apart from maybe Gmail.
ktallett 2 days ago [-]
The issue being is Apple should be spending money in the right places. Just because Google's product is poor, we shouldn't pretend Apple is being inactive due to some genius move, they are being inactive because they don't have the skillsets to make the correct moves.
GeekyBear 1 days ago [-]
[dead]
runako 1 days ago [-]
This is literally Apple's strategy, and has been for decades. They watch other players discover what works, then Apple makes a well-polished consumer product for the mass market. They have run this playbook to great success in at least music players, smartphones, smart watches, wireless headphones, tablets. Apple is literally never (since the '80s) among the first to market.
> they are being inactive because they don't have the skillsets
Rare to see an argument that Apple can't hire talent.
ktallett 1 days ago [-]
Apple were regularly first to market with WiFi, USB, FireWire, etc. The Apple of late are not first to the market and also have mixed success regarding quality and usability. They sell plenty due to to name but I would say the watch has been greatly surpassed, Vision Pro is a clunky solution for a portable headset, and the airpods max are a rather poor product all told not being remotely usable in day to day life in the outdoors. Apple have had no success with Machine Learning, Siri getting worse as it goes on is one key example.
They need a significant team creating their own model, (the talent of which has already gone elsewhere) and they also need to be working towards the future of photonic computing for running those models with success long term, again which will require a huge hiring effort. Considering it's clear they are not putting in that hiring effort it's obvious what work they have been doing.
runako 1 days ago [-]
> first to market with WiFi, USB
This is extremely revisionist. For ex with WiFi, ThinkPad + a Lucent WiFi card was standard issue for years before any Apple product had WiFi. Apple shipped integrated WiFi, which is wholly consistent with the notion of improving what the industry is doing.
Connectors? Yes, Apple has a history of improving connectors. Other computers have had connectors since forever. In this case, Firewire was Apple's semi-proprietary alternative to USB. USB, which Apple put into their computers years after others had shipped it.
> They need a significant team creating their own model
Your judgement. It's entirely reasonable at this point to license other models and look for a better/cheaper entry point. Apple tends to enter markets when it is possible to make profit. It is not clear yet that the business of creating and running advanced models is a profitable venture. By which I mean no company has yet demonstrated the ability to earn a positive ROI by developing and running an advanced model.
> working towards the future of photonic computing
Again, nothing in Apple's history would suggest that they would even aim to do this.
whywhywhywhy 1 days ago [-]
> Apple have done nothing yet though
This isn’t true they’ve literally launched Apple Intelligence with multiple apps and surfaces three times now and it’s flopped each time so badly they regroup and pretend it wasn’t the real launch then launch it again at the next WWDC.
ktallett 1 days ago [-]
Their intelligence was more of a support guru rather than a like for like. I would agree Siri was a failure even in comparison with Alexa etc but it's not a comparable service to what people are referring to. There is no Apple model to compete, there is no hiring of staff that could implement a long term strategy of using that model on alternative computing platforms such as photonic.
whywhywhywhy 1 days ago [-]
Not even talking about Siri era I’m talking the last 2-3 years when they keep launching “Apple Intelligence” and not delivering on what they demo.
whycombilater 2 days ago [-]
You can if the competition is "who burnt the least money?".
ktallett 2 days ago [-]
That shouldn't be the end goal of us as a society. Financial profit or loss.
whycombilater 1 days ago [-]
Which brings us back to "don't let AI companies burn all the money".
You could spend it on free universal healthcare.
nxobject 2 days ago [-]
And, hey, Apple has a sweet ~$52bil cash on hand, and has never been as gung-ho about stock buybacks as other companies.
Someone 2 days ago [-]
> So far, they have not yet delivered on any useful AI application
AI doesn’t have to be full-blown conversational AI.
In Photos, text recognition in Photos works well, object recognition and face recognition are somewhat decent.
In Mail, I find message summarization useful.
Small steps? Yes, but I think these are useful AI applications.
I do not use them, but in accessibility, they have AI applications to describe scenes which, I think, are useful to some.
etatester 2 days ago [-]
We've had content recognition in photos for a very long time. While it is sort of "AI" one still has to wonder what's new since 2022.
Siri just got AI-fied and it's worse and slower than ChatGPT in 2022. Also it doesn't work offline anymore.
I used to "describe a shortcut" maybe 5 times this week and today I was hit with "you reached the limit". Mind you
I have a 17 Pro and spend $120/year on iCloud.
These are useful applications of AI - or would be if they actually worked.
cik 2 days ago [-]
They provide picks and shovels to all the gold rushes. Others can capture the AI revenue - Apple can ultimately license and use AI just like anyone else. They certainly seem to be capitalizing on it already.
mbgerring 2 days ago [-]
Arguably the only “useful AI application” delivered by anyone is Claude Code, and the jury’s still out.
KronisLV 2 days ago [-]
I mean personally I also think the Codex computer use is brilliant, as far as harnesses go though it’s okay and I’d say Anthropic is a tad nicer otherwise.
dansquizsoft 2 days ago [-]
A good portion of the world’s population tends to find ChatGPT pretty useful…
0xCAP 2 days ago [-]
Tbh this applies to more or less the whole industry. We have incredible firepower yet I'm seeing probably even less product innovations than before the AI era started. Mostly R&D, benchmaxing and slop.
thinkingtoilet 1 days ago [-]
They also don't have 100s of billions of dollars of debt obligations they have to pay off in two years while not being profitable. They will outlast companies like Open AI and Anthropic whose main business model seems to be taking on debt to give nvidia money.
Citizen_Lame 2 days ago [-]
"privacy & trust"
But this is all based on marketing not facts. Apple is as privacy invasive as the next guy. Obviously this shtick will work as long as marketing continues do to good job.
givinguflac 1 days ago [-]
Apple is the most privacy-conscious tech company, period. See, for example, private cloud compute, as just one of many examples that Google etc would never even consider, because they want the data.
credit_guy 2 days ago [-]
> I guess it explains the haste Anthropic and OpenAI are in to IPO, cash out and leave the the retail investor holding the bag.
I don't think so. LLM inference enjoys huge economies of scale. At no point in the foreseeable future will a local model be able to compete with a cloud model in terms of price. Local models will have the privacy angle, but very few people will be willing to pay top dollar for that. There will be some people, for sure, but the vast majority will just use cloud models.
dofm 1 days ago [-]
> LLM inference enjoys huge economies of scale
Does it actually? Sure, it is operating at huge scale and this design choice allows enormous models (presumably enormous MoE models). But is it achieving economies of scale?
Economies of scale are rooted more in the idea of a profitable thing becoming broadly sustainably cheaper as the market grows, allowing cheaper manufacturing and further growing the market.
The big two or three LLMs are cheap because they are substantially subsidised by investor cash, and they are not profitable at all in any sustainable sense: the current pricing can only be sustained for as long as they can raise money, and the market will (and does!) shrink when it is asked to pay a less-subsidised price.
There appears to me to be no route to true profitability for this design strategy at all. Even the open weights router companies are downstream of largesse from state-affiliated companies.
bpicolo 1 days ago [-]
Their unit economics are already positive.
dofm 1 days ago [-]
There is simply not adequate proof of this for Anthropic, certainly not for OpenAI. All of their figures are distorted by ignoring the costs of training, free tier usage; even seem to ignore the spent cost of training the current models, let alone the future models.
bix6 2 days ago [-]
Why do you need huge economies of scale though? For 90%? of queries a local model will be good enough?
seunosewa 2 days ago [-]
You'll still need a cloud AI subscription for the remaining 10%, so you might as well enjoy the superior performance. If you're cost sensitive, models like Deepseek have you covered.
Rohansi 2 days ago [-]
For inference alone they get far better utilization of the hardware because they can keep it fully loaded with maximum concurrency. Other than that they get to collect a lot of data for training.
Foobar8568 2 days ago [-]
Well beside for roleplaying, local models are a bit useless, especially the ones running on end user class hardware.
Maybe when chip would infer at 10-20x the speed of a 5090 RTX, otherwise it's really..bad.
datadrivenangel 1 days ago [-]
The larger Gemma4 and Qwen models are competattive with GPT3 / 3.5 maybe 4o, so you can run the original ChatGPT experience on a nice consumer device now.
Foobar8568 1 days ago [-]
I am using everyday Gemma4 31b and Qwen 3.8 27b + 3.6 35b MoE.
Beside the 35b, the others are too slow to do anything vs cloud models, unless you have a local B200+. And the Qwen 35b has the reasoning capacity of a 2yo doing maths.
I wasn't "impressed" with any models for coding until 1year ago, only then they started to be "usuable" with the fault that we know and still exists.
diabolic1 5 hours ago [-]
[flagged]
edot 2 days ago [-]
Most people just Google something or use the free ChatGPT. They have no clue how the answers get there and frankly would be just as pleased with GPT 4o as they would be with Astra. Questions like “what does this light mean on my dashboard” or “which bidet is best”.
gherkinnn 2 days ago [-]
Normie queries can be handled quite well by Haiku 4.6 or whatever.
What new bike should I get? How should I rephrase this email? What to do about my persistent headaches? Recipes based on these ingredients?
tmp10423288442 2 days ago [-]
Small models inherently have less pre-trained knowledge, which will hurt their performance on queries like this. Moreover a lot of queries benefit from doing web searches, especially if they need to respond to changing conditions such as your bike example. Now you have to send data through a data center anyway for good performance, and probably need to use an API if you don’t want your computer blocked. So what’s the point, when GPT Luna exists if you really want to get a decent model at a rock-bottom price?
mbgerring 2 days ago [-]
I don’t need or want “pre-trained knowledge”, I need a computer program capable of searching the web, sifting out the garbage returned in the search results, and giving me a summary of the useful information it found.
ijidak 2 days ago [-]
My guess is it will probably be both. There was a time when no one could envision computing without the mainframe.
In the mainframe's heyday, it was difficult to grasp a world in which compute became so dense and so cheap that it made sense for each individual to have all processing and memory on their desk, talk less of on their lap and in their hand.
Of course this time could be different. But, when we look at previous relentless progress in compute and efficiency, then also couple that with the breakthroughs AI itself unlocks, it's hard for me to imagine that centralized AI will meet both the scale and flexibility desired for all use cases.
Just as centralized compute never fully disappeared -- it took the form of client-server computing and the cloud, there's no question that centralized inference will continue to exist.
But it wouldn't surprise me if, ten years from now, 90% of global inference happens at the client.
While simultaneously, the 10% of inference that takes place in the datacenter is wildly lucrative and orders of magnitude greater than today.
Put simply: the inference pie may become so large that both client and datacenter win.
nxobject 2 days ago [-]
> Put simply: the inference pie may become so large that both client and datacenter win.
Beyond inference, even local HPC or large in-memory workloads. Steve Jobs dreamed that the NeXT Computer could be used to cure cancer in a dorm room (whatever tha tmeans), and I guess a bunch of Mac Studios chained together wouldn't be bad for a lot of computationally tough biomedical "basic science" applications.
iAMkenough 2 days ago [-]
Unless cloud PCs take off and kill "AI PCs" and the future of the end-user hardware market, I think it'll be a bit of both.
It'll become easier and more affordable to distill/train/optimize smaller local models to meet your specific work needs. Multi-agent efforts will orchestrate the balance between using on-prem hardware for most tasks, and then defer to cloud models for more demanding/edge-case tasks. Especially if an organization can manage what data is shared with which model, and most of their user base are everyday casual users.
I also expect cloud providers to eventually start charging different rates for on-peak and off-peak usage, which would incentivize running what you can with the local compute you have otherwise sitting idle across dozens to hundreds to thousands of machines in your fleet.
Anthropic just changed their policy to invalidate any unused credits without refund if you buy your API credits annually. I see that as a sign of unpredictable budgets for cloud models for customers.
I could be wrong and all your future hardware purchases for end-users will be thin clients, without the local processing capabilities of today's laptops and towers. I don't see the hardware manufacturers profiting much from that, but maybe we'll see more companies like AMD declaring they prioritize cloud compute customers over everything else.
With a hardware refresh for cloud computing every 3-5 years, we'll likely see today's compute hardware driving Opus and Sol available on the secondary market for companies willing to build more on-prem capabilities.
otabdeveloper4 1 days ago [-]
> LLM inference enjoys huge economies of scale.
No, it's exactly the opposite.
The big money is in small(ish) but finely tuned for specific tasks models.
Whoever invents an app store for LoRA adapters will win this AI race.
labcomputer 2 days ago [-]
Eh, I don’t know about that. With current Sonnet API pricing, an M5 Max w/ 128 GB can break even in a few months.
Qwen flash-next is at least as good as Sonnet for my uses, and the speed is perfectly acceptable.
I really think the big labs are going to soon start feeling pricing pressure for everything smaller than Opus-tier models, and it will come for those next.
Gareth321 2 days ago [-]
> Eh, I don’t know about that. With current Sonnet API pricing, an M5 Max w/ 128 GB can break even in a few months.
Only if you're comparing apples with oranges. There are no local LLMs at 128GB RAM which compete with Sonnet 5.5 intelligence. And the gap is a chasm when comparing against Opus 5.5, which is fast and cheap and plentiful on event he $20 subscription.
dansquizsoft 2 days ago [-]
Don’t say it too loud, I’m planning some arbitrage moves in the future based on what I consider is the absolute wrong vibe on here that thinks local llms are going to dominate in the near future
otabdeveloper4 1 days ago [-]
> that thinks local llms are going to dominate in the near future
People saying this actually know how to run local models.
People claiming otherwise are Claude customers who know nothing beyond its point-and-click interface.
Consider that fact.
api 2 days ago [-]
Take a look at how qwen3.8 27B compares on benchmarks to much, much larger models. A while back I called it the crow of AI models: paradoxically strong given its tiny size, like the brains of crows and other intelligent birds.
It's not comparable to huge models of course, but given the power/size ratio here it shows that serious gains are on the table for models that can run fast on a high-end laptop.
geniium 2 days ago [-]
Yeah totally agree
A few years back we never thought open source llm would get as good and even the small and cheap model
Its good to have a race and such competition
leftnode 2 days ago [-]
I agree with you, even if many of the pundits say that Apple was left in the dust.
At some point, the real cost of inference/intelligence is going to come due, and the existing open source models will be good enough for 95% of tasks users want (or training their own model(s) will be inexpensive for Apple).
Apple will be there, as usual, to provide secure, on-device, faster inference that the vast majority of their customers will be fine with. Let everyone incur the R&D costs.
user43928 2 days ago [-]
The real cost of inference? It's dirt cheap.
Look at what it costs to serve Kimi K3.1 Pro on a B300. It suggests margins of 98-99% at API prices for OpenAI and Anthropic.
Should the shortages for memory and GPUs ever improve, this will only become much cheaper, won't it?
That said, R&D is another story.
nomel 2 days ago [-]
Cloud compute has been completely commoditized. Yes, local models will get better and better, but I think for the vast majority it will continue to be both cheaper and more productive to use cloud based models, far into the future, where bulk purchasing, oversubscription, and discounted industrial electric rates can be taken advantage of.
Where I am, it's cheaper to purchase multiple claude subscriptions than it is for the power bill from running a local model. Factor in the hardware costs, and you're looking at a break over a decade in the future, for comparable cloud models. Yes, there's privacy, etc, but now you're down into fractions of a percent of users who care about the government reading the memory of their computer.
xnx 2 days ago [-]
And if you're on a mobile device, any halfway powerful local model is going to cut your battery life way down.
nomel 2 days ago [-]
Related, I tried Juggernaut XL (image model) on my iPhone, and ate 2% battery per image!
walthamstow 2 days ago [-]
Gemma 4 E4B on Pixel 10 Pro is a great way to keep your hands warm in the cold
bradknowles 2 days ago [-]
In the end, I think companies like OpenAI and Anthropic will be the nameless and faceless backend provider, and they will get decoupled from the users. At which point, if they haven’t already had their multi-trillion dollar IPO and everyone cashed out, I don’t think they’re going to.
Apple and Microsoft and other companies will own that front-end experience with the customer, and it’s not going to matter to most customers whose backend gets used for what.
walthamstow 2 days ago [-]
The bigger question is whether consumer normies give a toss about AI. If they don't, and that's how it looks today, then Meta, Apple and OpenAI are all losing badly.
zaphirplane 2 days ago [-]
Consumers don’t care about AI, where I am it’s used by school kids for the most mundane to the most useful, used by white collar in wide range of roles and used by blue collar for work.
swiftcoder 1 days ago [-]
They definitely don't have AI use cases that exceed a $20/month subscription. Hard to justify the amount of RAM needed for local AI for a non-developer's level of AI usage
jimmyjazz14 1 days ago [-]
I think I agree but it will take some time before their gamble on local LLMs start to pay off and I don't think it will completely kill off Anthropic (though. I would question their trillion dollar valuation if I was not already).
neilwilson 2 days ago [-]
They'll win if they vertically integrate chip manufacturing - particularly the memory.
It's not as if they are short of money.
stingraycharles 2 days ago [-]
Isn’t Apple already doing this? Or what kind of vertical integration do you see other than their unified memory baked directly into the CPU?
Or are you saying that Apple should become a memory manufacturer, rather than working with TSMC?
neilwilson 2 days ago [-]
The argument is that suppliers will serve somebody else in a price battle. If you own the supplier then they can’t do that.
rapsey 2 days ago [-]
Apple does not manufacture its products.
jatindavis5 1 days ago [-]
Apple's hardware dominance is untouchable.
root_axis 1 days ago [-]
We'll see. Hardware costs will remain prohibitive for years to come. Most people can't afford a 20k Mac.
bitmasher9 1 days ago [-]
I think this AI chapter will conclude with hardware costs normalizing. Maybe it’s because the hyperscalers stop hyperscaling. Maybe it’s because manufacturers finally catch up to demand.
Afterwards we’ll have 128gb apples for under 10k.
small_model 2 days ago [-]
Not everyone can afford a top-of-the-line Mac and the electricity cost to run it is high. It will never run Frontier models, which you can use for the price of a Netflix sub.
Also a lot of people work from laptops and running inference on data centres for 10th of the price is a no-brainer. Local models are more of a niche and always will be.
MacBook Air + Claude max sub for 20 years would still cost less before a maxed-out Mac Studio makes sense (not taking into account running costs), even then it’s not a Frontier or as fast.
aa-jv 2 days ago [-]
Been using both DGXOS and MacOS for my local inference needs, and by far, NVIDIA's DGXOS is superior in every way. Apple have a long way to go to catch up on the tooling extravaganza that keeps the NVIDIA ecosystem vibrant and rewarding.
mietek 2 days ago [-]
Why doesn't Apple have their own fabs yet?
swiftcoder 2 days ago [-]
Because fabs take years to spin up, decades to become competitive, and are a constant financial drain throughout. If (with great prescience) they started planning their own fab at the beginning of the RAM crisis, we should see Apple in-house RAM sometime around... maybe 2040?
mietek 1 days ago [-]
I feel that with all the trillions Apple have lying around, they should've been thinking about their own fabs already when designing the first Apple Silicon chips.
swiftcoder 1 days ago [-]
> they should've been thinking about their own fabs already when designing the first Apple Silicon chips
Why, though? They had a sufficient mountain of cash to outbid everyone else for TSMC capacity, and no realistic hope of catching up to TSMC's process on their own fab
mietek 1 days ago [-]
Well, outbidding everyone else seems to have worked up to a point, hasn't it. Of course, we could say that we're living in unprecedented times with regards to the demands currently being placed on fabs, but I'd say that I would've been worrying about TSMC being a fragile bottleneck for more than one reason, and for more than a few years now.
Also, I'm not exactly sure we should be claiming what is and what isn't realistic for a trillion-dollar company. People could (and probably did) argue that they had no hope of catching up to Intel/AMD, and yet here we are, with Apple arguably having surpassed both, at least from an energy efficiency point of view.
bigyabai 1 days ago [-]
Apple has alternatives to TSMC. Intel and Samsung both have comparable process nodes, albeit at a pretty high cost and relatively lower yield. Apple would prefer to avoid paying competitors like that, but in many cases they have no other option. The iPhone Duo display, for instance, is sold to Apple by Samsung at a considerable per-unit markup. It was that, or no folding phone.
Realistically speaking, "catch up to TSMC" is something that every single EUVL fab has failed to do despite tens of billions of dollars in investment. Spending money is the easy part, developing high-yield processes over a timetable of decades is the hard part. I think Nvidia and Apple both agree that paying TSMC to build American fabs is a smarter use of their money if they just want excess fab capacity.
jmyeet 1 days ago [-]
I believe this as well. There is an inbuilt market for local models. A big example is law firms for whom cloud models violate attorney-client privilege.
NVidia aggressively segments the market on VRAM. Apple’s shared memory model is a competitive advantage. Well, it will be when they hand the raw PFLOPS, which is coming.
Rover222 1 days ago [-]
Running local models on desktop hardware will always be behind the SOTA, and thinking that cutting edge models will lose value because people can run good models locally is kind of odd.
ulfw 1 days ago [-]
What M7 Max/Ultra chips?
iknowstuff 2 days ago [-]
This is a nerd fever dream. Yeah I’m sure people can’t wait to run local models on their iPhones.
mbgerring 2 days ago [-]
Sometime I wonder if other people on this website lived through the same era of web applications as I did, where people built whole successful businesses on 3rd party APIs, that were destroyed overnight when the terms changed.
Yes, I promise you, there are many, many people who are hesitant to build anything real on the assumption that either Anthropic or OpenAI will continue maintaining their services as they are today in perpetuity.
dstu 1 days ago [-]
Both the OpenAI and Anthropic core APIs have become widely supported standards, so any application you ship today on their models can be trivially ported to other hosted providers or to your own infrastructure if you want to own the whole stack.
I agree that it pays to be wary of the additional abstraction layers they offer that purport to make your life easier, but for anything running standard completion calls or the like, I don’t see why this needs to be a concern.
oneseventwonine 1 days ago [-]
I don't think API integration is the problem here. We also need evals that can be relied upon to measure the difference in performance.
jmuguy 2 days ago [-]
For those of using AI day to day, not being beholden to the whims of Anthropic and OpenAI is definitely a dream scenario.
rapsey 2 days ago [-]
You are just confirming his point.
asdff 2 days ago [-]
iOS isn't exactly a distro you control either
bix6 2 days ago [-]
Is Apple Intelligence not local models currently running on iPhones?
walthamstow 2 days ago [-]
It's only running if people are using it
Gigachad 2 days ago [-]
Some of it is local and some is hosted.
gherkinnn 2 days ago [-]
You don't have to sell it as a local model. Sell it as offline capabilities. Sell it as private background processing while your phone is idle and plugged in. Sell it as un-enshittified LLM once Anthropic and OpenAI inevitably screw everybody.
bigyabai 2 days ago [-]
Man, if all that makes Apple a "winner" then I'm dying to hear your assessment of Nvidia.
Factoring in the increased cost of memory, Apple's threatened service revenue and the stagnation of ecosystem products like the Mac and iPad, I think they have a really challenging future to navigate. The whole "sell people a B2C ecosystem" business model is more threatened than ever.
Danox 2 days ago [-]
The design and engineering of memory is not more difficult than replacing Intel and Qualcomm, Apple certainly has the money, and they certainly have the engineering talent within the Apple Silicon design group. It took 13 years to replace Intel and six years to replace Qualcomm who has already warned their investors that they anticipate losing revenue in the near future. The question is whether or not they have the will to do so, money and engineering ability isn’t the problem, it is simply a matter of will. With CMXT coming online bigger and stronger.
I don’t think there will be a choice long-term for Apple the conditions of the market have changed, and you have to change with it or get left by the wayside. They have shown that they will adapt and they certainly haven’t wasted money like their tech competition over the years.
bigyabai 2 days ago [-]
Difference being, Apple had experience designing CPU cores and wireless radios before ditching Intel and Qualcomm. The transition felt "magical" because it was a generally low-effort layer on top of a muscle that Apple had gradually built over time. Their design approach is not compatible with scaled manufacturing; Apple does not have experience manufacturing DRAM at all. They don't have their own fabs, nor could they bid on fab space when AI companies outspend them 10:1.
Apple would make more money investing in a CUDA-style architecture than they would by becoming a subsistance manufacturer for the pitiful margins of the iPhone, iPad and Mac.
mietek 2 days ago [-]
Indeed, why doesn't Apple have their own fabs yet?
bigyabai 1 days ago [-]
glances at Intel
You tell me.
pen2l 2 days ago [-]
The contrast I'm drawing is running these models locally vs on the cloud and how that would be a selling point well received.
bigyabai 2 days ago [-]
I don't think that's materially different from what you can do with Nvidia and AMD GPUs, besides the fact that you're limited to Thunderbolt interconnect.
jmuguy 2 days ago [-]
And that we don't want to carry a giant, hot, eGPU enclosure around with us.
Affric 2 days ago [-]
Yeah, what apple have frequently got right is the actual product/UX.
Capability is one thing but a focus on the actual product, as an teleological destination that is built rather than something cobbled together as a solution to a problem about how to sell what you have generally has taken them the right way.
bigyabai 2 days ago [-]
For all of those accolades, the Mac is still a minority player in every computer market. They're especially a non-entity in on-prem enterprise buildouts and datacenter construction, which is where the money is going right now.
It's nice to have these types of niches when they make you money. But the Mac isn't profitable like the iPhone is, and probably makes less money than the iPad does if you count aftermarket service sales. The further Apple drifts from their roots as a computer manufacturer, the more the Mac starts to look like a liability to them.
Apple's Last Stand is their prosumer segment, and once that's gone I don't think their vertical integration playbook gets them anywhere further. Their bottom line is dependent on finding new ways to make B2C profitable, which has resulted in subscription services like AppleTV/Apple Music/iCloud so far.
DrScientist 1 days ago [-]
It has about 10% of the global laptop market - and that's growing - making it the 4th largest single vendor, and it has about 35-40% of the global tablet market.
That looks pretty healthy to me.
Note that because most enterprise software is now web based ( ie moved to the data centre as you have pointed out ) - a lot of the corporate Windows only lockin has gone - so I'm seeing a steady rise in Macs in business.
What's not healthy is the desktop market ( apple laptops outsell desktops like 10:1 ) - but that's whiles that's more marked in the Apple space, it's largely an overall market trend. ( Overall desktops are about 20% of total shipments ).
So Apple will only be in trouble in this space if the laptop ceases to become wanted - and that's all about the interface - some apps are better with keyboard and mouse/trackpad and a bigger screen. If all that goes away and we just talk to our computers then I'd argue that Apple are better placed than Lenovo to weather that one.
bigyabai 1 days ago [-]
Apple has had "about 10% of the global laptop market" since 2013. If there's some powerful growth driver, I'm not seeing it.
The proliferation of web-based enterprise software mostly stands to Windows and ChromeOS' advantage. macOS is the platform that has relied on "native" and "ecosystem" efforts that are becoming increasingly unpopular among consumers and industry pundits that don't like paying per-seat for software services. The Mac Pro used for render farms, on-prem hosting and cluster computing was depreciated completely, driving some of Apple's highest-margin customers over to Linux and Windows servers. Apple has absolutely began their Mac pivot to prosumer/B2C vending, and it's resulted in advertisements and SaaS slop invading macOS.
Lenovo will keep selling laptops because that's their product equivalent to the iPhone. Apple's equivalent to the iPhone is... well, the iPhone. If they see an opportunity to force Mac users into an iPad-esque experience, they'll take it in a heartbeat and play coy asking "what's a computer?" like the iPad advertisements. The Mac not an important product for Apple these days, the App Store is.
DrScientist 13 hours ago [-]
I see you've moved the goals posts from Apple is circling the drain to 'not a powerful growth driver'.
Totally agree that Mac servers ( they went years ago ) and Mac desktops ( and desktops in general ) are on the decline.
I just think you are basing your opinion on the past. Sure in the past, when Apple hardware was worse overall than the Wintel offering, Apple heavily relied on the Mac specific software, and your right that's less important now more than ever.
But the point here is right now, and for the last few years, Apple hardware is significantly better! And because of this in turns your argument on it's head.
I think we both agree that the landscape in terms of mix of devices may change in the future - I just think Apple is following that market, not 'forcing' Mac users into an iPad-esque experience.
And right now I think the laptop market is still pretty healthy - I can't see Apple moving away from it unless sales drop, and as I said sales are actually rising.
xnx 24 hours ago [-]
Isn't this like saying Apple has beat AWS because you can host a website on your MacBook?
amelius 2 days ago [-]
> Apple, to me, is the winner in the end of this AI chapter.
Soon enough: "Claude, please build me a MacOS clone. Hell, copy the entire Apple ecosystem the way I want it."
btreecat 9 hours ago [-]
Fewer parameters*
esskay 2 days ago [-]
It would be slightly ironic if they did win. They were incredibly slow to adopt AI, and even now what they shipped with Siri is incredibly poor. Having arrived late to the party they stumbled, lied to customers, mis sold a product, got sued for it and lost, and then ended up slapping a siri logo on gemini.
But the hardware. The hardware is fantastic for local LLM's, generative ai, etc. And they seem to maybe finally be waking up to that, in true slow sleepy Apple fashion.
If they'd been a bit quicker about it we could have a higher tier iCloud plan that included a chatgpt plus style setup with the "its private" marketing tag that cant be provided by anyone else. Instead we get Siri being slightly less useless than before.
amelius 2 days ago [-]
> Apple, to me, is the winner in the end of this AI chapter.
Not if they can't sell anything because of ridiculous DRAM prices.
phyzix5761 2 days ago [-]
Even with the haste the 7 Anthropic founders have to wait a whole year after IPO before dumping all their shares.
HPsquared 1 days ago [-]
Just as long as they can secure some reliable RAM supply.
bushbaba 2 days ago [-]
Hint. Thats been apples public strategy for about a decade.
couchdb_ouchdb 1 days ago [-]
Have you used Siri?
cyanydeez 2 days ago [-]
Sure, all you have to do is use only what can climb the walled garden
lasky 2 days ago [-]
100% this.
wickedsight 2 days ago [-]
> Apple gets this and we'll see the result with M7 Max/ultra chips
I'm not sure which chip it'll be, but I now for sure I'm not buying new devices until the AI boom has somewhat settled and we kinda understand what we'll be using it for. Until then, every manufacturer will just be guessing what device to build and will be outdated within a few months.
criley2 1 days ago [-]
Totally disagree. I do not think local models will displace cloud models any time soon, and I think distillation has been demonstrated to NOT have better performance and is LESS efficient. Chinese models use dramatically more tokens and time to achieve dramatically inferior results. Watching deepseek spit out 20M tokens when Opus solves in <1M is always an entertaining window into "efficiency" and "performance".
Local models literally cost more in electricity than using far more powerful cloud models cost in inference.
When your options are "dramatically drain your iPhone battery for substandard AI, or have instantaneous cloud AI with no battery drain" what do you think the average user will choose?
And that's before we discuss how ridiculous the pricing is for home hardware that has a chance of running a halfway decent model at a halfway decent speed. Residential electricity + overpriced underutilized hardware means you're going to pay 100X or more per token.
I think the future prospects for local AI are looking worse than ever. It will be far more expensive for a far worse experience for the foreseeable future. It will fill a privacy/control niche, but beyond that, it's not a serious option
mschuster91 2 days ago [-]
> I guess it explains the haste Anthropic and OpenAI are in to IPO, cash out and leave the the retail investor holding the bag.
Anthropic and OpenAI want to exit because they know they have no moat... and personally, I believe that the sociopaths running the US at the moment want to provoke a great economic crash. The Evangelical ones because they want the armageddon [1], the rich fucks because they took the "you shall own nothing" part for real and want to be the new neo-feudal overlords. And the best way to achieve that is by tying everyone's retirement savings up into their bubbly assets and then crashing down the economy, leading them to buy up everyone's asset at fire-sale prices with the liquid cash they made during the exit.
You are crazy. Apple has no lift on AI local or otherwise. Local LLMs are a massive and stupid waste of yes YOUR time.
And Apple really wants to sell people who have no cred in the space their stuff because THEY have no cred in the space.
Its basically a club for stupid f**s
myphpgothacked 2 days ago [-]
[flagged]
simonw 2 days ago [-]
"Harbor is currently in a private preview under Apple’s Claris brand"
There's a name I haven't heard in a long time! Claris (always an Apple subsidiary, since being founded in 1987) renamed themselves to FileMaker in 1998, but apparently they rebranded back to Claris in 2019.
This could actually be interesting for "regular" people. FileMaker was great in enabling non-IT people and SMBs to develop custom software for themselves. Think HyperCard with tables.
Some of that software has been in use since the 90s and still works. Adding AI to the equation will empower a lot of people.
However, FileMaker is not really targeted at software engineers. In fact using it as a developer will likely drive you up a wall. It's things that feel totally fine to non-devs but completely insane if you're used to something else. E.g. I remember having to click a thousand GUI buttons just to edit a few lines in a script once (regular users just "record" them through the UI). It did all work fine though, very reliable.
They added some more developer-specific features later, but it took a long time. E.g. editing scripts as text(-ish) only came in 2015 (FileMaker 14) and an actual programming language in 2020 (JS, FileMaker 19).
oidar 2 days ago [-]
If they keep Harbor under the Claris umbrella, that is a nudge that they are doing it for SMB market instead of the consumer market and it will likely be a onerous subscription to use it.
dwaite 7 hours ago [-]
I believe Claris got rolled into Apple when Steve Jobs came back, but Filemaker was jettisoned to Filemaker Inc because it had a Windows version. Steve Jobs was apparently reluctant to have any Windows software within the walls, but lost that fight with Windows iTunes.
A few years ago Filemaker, Inc took on the Claris name.
eddieroger 1 days ago [-]
FileMaker really could have had a moment when iOS devices took off since you could get a basically free native app just by having a database, but (I'd argue) got bogged down by poor pricing models. I would have loved to run it, but it's always been prohibitively expensive for anything not an enterprise, and now it's far too easy to spin up a CRUD API and call it a day.
jph 2 days ago [-]
If you ask who would pay for Apple local models, I would. A Mac Studio high end 512GB costs ~$1000/month for 3 years versus my current run rate of ~$1000/month for five devs for Claude Ultra (or ~$10k/week for Claude Sonnet if I paid API rates rather than Ultra).
If/when Anthropic changes to pure API pricing, or for API-heavy projects, that's when I'd switch to more local models. Of course there are tradeoffs for speed, quality, upgradeability, etc.
I currently run a Mac with 128GB and qwen3.8:27b-mlx. It hits the heat limit of the Mac when working on a 200k LOC codebase for security auditing and hardening for many hours at a time. This isn't as strong/fast as Sonnet, to be sure, yet the cost is only $6K one-time plus the usual electricity, maintenance time, etc.
jmaker 2 days ago [-]
$10k for Sonnet per week? How did you arrive at that number? It’s quite a huge inference volume. No consumer hardware will give you that level of latency at comparable cost.
$6k is not the only cost - electricity adds up over time. And hardware can fail, redundancy is priced into the token prices and subscription plans. Maintenance is mostly negligible, but some updates/upgrades might regress. There’s a lot to SRE to keep it running at that scale.
jph 2 days ago [-]
> How did you arrive at that number?
I run "npx ccusage@latest weekly" and also spot-check Claude Code sessions via "/usage".
> No consumer hardware will give you that level of latency at comparable cost.
You're right. My belief is the frontier AI companies are currently subsidizing real costs for the purpose of rapid growth customer sign ups, and that in a couple years or so local costs will become reasonable, at least for full-throttle work that's queueable.
zamadatix 22 hours ago [-]
Even if one believes the price of models will only go up from frontier AI companies AND believe the local AI frontier will be fast enough at a good enough profile, it still doesn't explain how you're going to beat the price of a place hosting open weight models at scale on shared hardware always maxed out 100% in a place with cheap electricity by buying a single platform up front for 3 years.
Data sovereignty always makes sense in this case because it's explicitly not about cost, but I've not seen a convincing "it's actually cheaper to do it yourself" analysis that came to that conclusion by answering all of these things up front instead of just hoping it'll somehow get better by then.
adi_kurian 1 days ago [-]
I did the math once, to run Kimi K3 on a Mac, you'd need to daisy chain 5 Mac Studio M3 Ultras. So $125K. And the latency would be bad.
For good latency, you would need a multi GPU server around $3-600K.
I agree the hardware will catch up and local is the future. For the average person who is sharing there privacy data out willy nilly all the time without much regard, i.e. most people, it makes no sense right now to go local vs. API / subscription given the price differential.
zaphirplane 2 days ago [-]
you’d spend real money to save imaginary “if I used api” money. In real money you are
Breaking even in > 10 years,
in 10 years your 10 year old Mac will almost certainly be a relic for running cutting edge local models
What am I missing
jph 2 days ago [-]
Break even is likely for API pricing versus local, at least within a couple of years or so IMHO.
For example one of the projects is a web app that's processing user input, making AI suggestions, generating reports, doing ongoing observability, and running batch processing overnight.
Claude currently does these via API pricing, not Claude Ultra personal.
jann 1 days ago [-]
To be fair, having multiple Claude subscriptions is also against the ToS afaik, so you’d have a much higher run rate.
jph 1 days ago [-]
Anthropic tells me I can have two Ultra subscriptions. FWIW I'm doing open source.
larodi 2 days ago [-]
> if I paid API rates rather than Ultra plan
yes, but you pay the Ultra plan, that's the whole point, isn't it? Let's be honest also - qwen3.8:27b-mlx is nowhere near Sonnet, both in size and cap, and if you do $10k a week of usage, you should know that.
dgacmu 1 days ago [-]
The 512GB server he specified would be running something more like qwen3.8-flash-next, which is probably competitive with sonnet 5 (but still loses to 5.5).
I've tried it out on a 512GB dram server with 2*3090s and it works really quite well. Draws enough power to cost something similar to Luna, though.
larodi 1 days ago [-]
Still u can never beat the cost of electricity unless saturated with batches inference, speculative decode, maybe beam search and what not.
dgacmu 22 hours ago [-]
Not really. My setup is just a hair cheaper than paying API prices for Luna (and it will do security audits for me). The mac would be even better on power.
I don't think any of these self hosted setups are a good deal when you look at the NPV of the capex plus the power costs, but if you already own the hardware it can be okay or even a slight cost savings.
thibsrn 2 days ago [-]
I have been using llama.app, which is the desktop interface built on top of llama.cpp by the same people. It is an alternative to Ollama that might interest people who want to switch given Ollama's reputation and previous decisions. Llama.app has a really clean design, an elegant and intuitive interface. But it's good to get alternatives as well, if Apple also gets into the game.
I've instinctively downvoted, wrongly assuming that this is just someone shilling their own equally bad stuff, but the repo is https://github.com/ggml-org/Llama-macOS
Note that it is under the ggml-org. So that's at least not a third-party taking advantage of llama.cpp
With the clean landing page URLs, you just don't know. So GitHub is probably the best source to link
thibsrn 1 days ago [-]
I add to dig a little bit to make sure it was made by the same people. They don't make it obvious. Here's an announcement below.
llama.app has a lot of similar problems that ollama has, but at least you can use the hugging face downloader with it.
That you can't configure the models independently is a glaring oversight. The alt-space to enter the chat window (at least on Windows) is awful and with no way to disable it I've resorted to just using the app as an easier interface to their downloader.
It does have a nice, clean UI and it doesn't hide the models behind some opaque identifier.
iantpe 1 days ago [-]
What I need most right now is a model like TypeSafe's Jev that can be built directly into the computer.
Jev allows for numerous small judgments: Is this email important? Which program should handle this request? Is this operation risky? There's no need for large LLMs to slowly generate long paragraphs of text; all you need is a fast, structured result that returns the message.
Having a local Jev-like model in the operating system for quick decision-making, and then calling the larger model when deeper thinking is needed, would be very useful.
dabbling with it in browsers but i expect it would answer the mail for you, if you find it accurate enough
illwrks 1 days ago [-]
In a way you want something like blackberry messenger, a centralised hub for all app messages, notices etc, and then JEV hooked into it as a traffic controller of sorts.
I wonder if there’s anything like that, perhaps on Linux?
gehsty 2 days ago [-]
As models improve and hardware becomes more capable Apple are definitely well positioned.
I am super interested to see what the Apple silicon team can deliver when their full attention is turned to local LLM acceleration.
mark_l_watson 1 days ago [-]
Their hardware is especially good for MOE models, less suitable for dense. I use Laguna XS 2.1 6bit and Qwen-3.8-next-flash 2.6bit most because they are MOEs and run efficiently. I love Qwen-3.7:27B but as a dense model I only use it in “run something and walk away” use cases: slow.
alex43578 2 days ago [-]
I don't see any evidence that local models (able to run on truly consumer hardware, not a DGX or multiple GPUs) will close the capability gap in a meaningful way. I have powerful hardware (multiple $K in today's prices), and only recently has Qwen Next come even close to being "useful", rather than a curiosity.
But the problem is a $20 ChatGPT/Claude subscription utterly trounces it in usability, user experience, and performance. By the time we get Opus 5.5 at home, we'll be on like Opus 7 or 8, and I'd bet Sonnet 7 or 8 will dust whatever can be run on the base MacBook of that time. It's fine if people think local 5.5 will be good enough, but it just seems like as AI keeps getting better, you'd want to use the better tooling - nobody has decided a 2010 MacBook was good enough when the M1 came out.
SeanDav 2 days ago [-]
2 things:
- As AI continues to improve, the gains will become increasingly incremental. This means that your local model will be almost identical in performance as the latest cloud version, for all but edge case problems.
- If your local model is good enough for your current needs, the only "tokens" you are chewing through are utility costs and asset depreciation. Relatively cheap. It is easy to overrun even 200 /month cloud models for serious AI use.
ben_w 2 days ago [-]
> - As AI continues to improve, the gains will become increasingly incremental. This means that your local model will be almost identical in performance as the latest cloud version, for all but edge case problems.
How much is "good enough" depends what we want it for.
Right now, the vision which was presented as a joke in (AFAICT more than one project all called) vibeOS seems like it could be viable with better local inference… but that likely needs a few more 9s of reliability even relative to current SOTA models, and we might even never get there if smaller local models always produce code which big hosted models can find vulnerabilities in.
Same if you want home inference to replace hiring a professional lawyer, architect, tutor, etc.: even though the AI has been getting passing grades in the law and medical exams since the early days, whoever gives out public liability insurance probably want to see more 9s of reliability before giving the OK.
radlad 1 days ago [-]
> It is easy to overrun even 200 /month cloud models for serious AI use.
Not with the tok/s I get. I'm on a 128GB M4 Max laptop, and the latency + lack of parallelized sessions means you can't get anywhere near as much use vs. cloud models.
EagnaIonat 2 days ago [-]
> will close the capability gap in a meaningful way.
I ran OpenClaw in a VM on my mac a few months back, only using local models. It was painfully slow (no MLX) but what it created was on-par with Claude at that time too.
The models are certainly powerful enough, but the frontier models are more than just an LLM model in the back.
gehsty 1 days ago [-]
The tension over local / remote is a tale as old as time in computing, when the technology settles down both will continue to exist with different use cases…
in 5yrs time running an M12 with a Bionic LLM Engine (or whatever they call it) may be good enough for a very very good AI experience. Enterprise / professionals will likely still pay for frontier models.
cribbles 2 days ago [-]
I agree with you, fwiw, but Apple's own consumer hardcore is not the choice of metaphor I would go with here - the M1 MacBook Pro and the group of iPhones that came out around the same time were the exact moment when Apple devices hit a "good enough" asymptote for many people (myself included)
xdertz 1 days ago [-]
If you are comparing pure quality sure but don't forget quantity. It is very easy to blow through a weekly quota in one day. Fully local means you have unlimited usage which is something no provider gives you on a subscription.
When comparing API prices and privacy concerns, local might win.
bearjaws 1 days ago [-]
> Fully local means you have unlimited usage
20tk/s is not unlimited when you have a lifespan that isn't infinite.
willis936 2 days ago [-]
The up and to the right trend faced issues with the end of Dennard scaling. The only way it continues is with irresponsible allocation of more natural resources to compute. I'd prefer my atoms not be turned into paperclips.
mycall 1 days ago [-]
> Claude subscription
Not good for PII/PPI
Rover222 1 days ago [-]
Yeah I think it’s peak nerd bubble to think local models are going to wipe out the value prop of Anthropic.
mrtksn 2 days ago [-]
Sure, Apple has an opportunity here but I have no confidence that they won't screw it up.
For starters, they need to let me get rid of their AI stuff and free up the space. Apple aggressively pushing their AI down the throat of their users means that they suck at it but trying to make it happen using their muscles in other areas.
Just like people figured out how to make their Android TV not suck, it suggests that some time it the future people can make their OS not suck and this will make macOS irrelevant if Apple doesn't fix it first. Unfortunately for Apple, they operate in a system where they must keep growing their numbers.
Such a great company, its a shame that they couldn't figure out this AI stuff. Fingers crossed that this tool actually fixes that by just giving up and let people do whatever they want to do as efficiently as they can on the brilliant hardware Apple creates.
ethbr1 1 days ago [-]
I'd add to this that Apple's ability to support a third-party ecosystem with stable development interfaces to their hardware has been at best "mixed" over the years.
Especially in the modern era, the firmware/software side of macOS definitely doesn't seem like a priority.
jwr 2 days ago [-]
I've been running local models under ollama, then lm-studio, and now mtplx (command-line, from supervisord). I'd welcome a vendor-supported solution, if it doesn't turn into bloatware (like lm-studio did).
dawedev 1 days ago [-]
[flagged]
jedbrooke 2 days ago [-]
> Cluster for scale: “Connect two or more Thunderbolt 5-capable Mac computers and Harbor pools their unified memory into a single inference resource. Run models that exceed any single computer’s capacity, or serve more concurrent requests across your cluster.”
This seems like the main way it would differentiate itself over existing solutions like LMStudio etc.
_rwo 1 days ago [-]
I was excited about this until I saw "Thunderbolt 5-capable Mac" (sill rocking few M1Max devices with Thunderbolt 4)
waz0wski 1 days ago [-]
This functionality was already available from several other apps such as Exo
By "Apple" they mean "Claris", a wholly owned subsidiary which was formerly Filemaker, Inc.
So this is interesting, but it will likely be an independent product rather than part of the core operating system.
apparent 2 days ago [-]
This is what I've wanted for the last few years. I have played around with local models and had some success, but I don't want to deal with the hassle of setting up, updating, etc.
If all of this were easy, I would happily invest in new dedicated hardware to run it. This could be a full-blown Mac or it could be a souped up HomePod-type device, loaded with RAM. Better yet, make it a revitalized Matter-enabled Airport!
LeBit 2 days ago [-]
MacMini with M7 Pro and 96G of RAM.
They are going to sell sure 10,000$ and you won’t need anything else for the rest of your life (if you are over 90).
Btw, llama.cpp with llama-swap ain’t that hard to configure if you have access to a potential LLM and have 5h of your life available to that task.
apparent 2 days ago [-]
Yeah, I might dive in with llama.cpp at some point, but unless Apple censors the models I can choose I'd just as soon go with Apple's solution.
I also want something that integrates super easily with my iPhone and other devices, and hopefully Apple will make it possible to use my server as an intermediate fallback between my iPhone and their cloud models.
KolibriFly 1 days ago [-]
Calculate the total cost of two new Mac Studios with max memory and cables. For that budget you could burn tokens on cloud APIs for a long time or build a dedicated server on open hardware with clear server buses
justauserid 18 hours ago [-]
There are two use cases where this is useful:
1. privacy (w.r.t. personal data, human agency, IP, whatever) – this absolutely is the most crucial.
2. if the needs are absolutely sufficed with local model(s) runnable on a super-expensive mac with a whole lot of RAM (not less than triple digit GBs usually) and the equivalent cost on API/subscription would be at least few times (say >=2-3x?) factoring in mac repair/maintainence/etc (yep, that does happen)
There's a 3rd case thoguh – the hobbylist case, which, imho and in my anecdotal evidence, is the majority of local-model-chasing outside of enterprise (which is usually not hobbyist to begin with).
So there of couse are three legit use-cases.
PS. Having said that, at this point, any machine you can't control 100% or very close to 100% cannot be said to be 100% or close to 100% private. So without getting into debates of whether Apple is the bastion of privacy or not (esp. they way they have been going about and their software competence, or lack thereof, leave a lot to be desired), or whether we would rather slide down to whataboutism, you can think about that yourself. I had to add this because these days running local models has become synonymous with "if not mac then what" and it might as well have merit, or not.)
DerDerDaIst 1 days ago [-]
devise the cost by the burnrate with cloud ai and you know when you'll break even. Add a bonus for the privacy.
Another bonus: Here in Germany a huge chunk of the hardware cost can be deducted from the tax bill.
tencentshill 1 days ago [-]
Do you think the cost of cloud tokens will stay the same or go down over the next ~5 years? Not likely, especially as the big ones start IPOs.
CharlieDigital 1 days ago [-]
[dead]
_1 1 days ago [-]
Two new Mac Studios come with privacy.
hello5010 1 days ago [-]
> For that budget you could burn tokens on cloud APIs for a long time or build a dedicated server on open hardware with clear server buses
Let the market decide.
Seems like both enterprises and individual users are switching to local models.
To my surprise, people are willing to pay for privacy.
bel8 1 days ago [-]
> Seems like both enterprises and individual users are switching to local models.
I know a total of zero and individuals or companies using local inference for their workhorse inference.
Local models are just not up to most tasks for now at least.
CharlieDigital 1 days ago [-]
I take poster's usage of "local" to mean "self-hosted" which would include Revolut switching to self hosted GLM (which I think we'll see more of)
gizmodo59 2 days ago [-]
I really want capable models local but it’s impossible for me to afford the hardware. If there is a magical way to run glm 5.3 without quantization at 80-100tps with a total spend of less than 10K I’d be happy but that’s impossible now.
maipen 2 days ago [-]
$200 a month is only $2400 a year.
That’s 4.16 years until you spend 10k.
I don’t find it reasonable at all.
Subsidized Subscriptions or api for cheaper models, is the best value.
But the future of AI is so uncertain, regarding model sizes. I don’t think making huge hardware investments is reasonable for individuals.
EddieRingle 2 days ago [-]
> $200 a month is only $2400 a year. That’s 4.16 years until you spend 10k.
I don’t find it reasonable at all. Subsidized Subscriptions or api for cheaper models, is the best value.
If you buy your own hardware, then after those four years you still have that hardware, and it likely still holds significant value. Plus you know the local model you're running today won't change or suddenly degrade in four months, let alone four years. Whereas after four years of paying subscriptions and API costs, you have literally nothing.
cadamsdotcom 2 days ago [-]
Energy costs (including capex if you buy batteries or solar) complicate things.
SoftTalker 2 days ago [-]
Four year old hardware has almost zero value.
ahknight 1 days ago [-]
Still running models on an M1 Max, which is a bit older than that.
That statement made sense ten years ago, easily. Less now, though.
D13Fd 2 days ago [-]
Please send me all of your 4090's.
argee 2 days ago [-]
Oh? How come the four year old 4090 RTX cannot be purchased for less than (or even at) MSRP then? Can you buy me one? I'm willing to pay $500 even if it is worth zero in your eyes, that's a stellar deal.
Espressosaurus 2 days ago [-]
Tell that to the 3090s still selling at $1500 how many years after manufacture, used?
LeBit 2 days ago [-]
My 12 years old Xeon with 32G would like a word with you.
SoftTalker 1 days ago [-]
Sure, it has value to you, I'm the same. My main workstation is 10 years old. But try to sell it.
GPUs are holding value longer, for obvious reasons. But even a 5 year old PC or server will be out of warranty, full of NLA components, and will get pennies on the dollar of its original cost on the salvage market. Most businesses will have fully depreciated them and maybe expect to sell them for enough to cover the costs of disposal.
LeBit 12 hours ago [-]
I know VPS providers use these machines until they die and then simply swap them for something else until they die.
There are ways to salvage old machines even when there is 0 support left/available.
LeBit 2 days ago [-]
You don’t get privacy at that price.
There is no ZDR at that price.
I would not let a non-local AI have access to my financial or health data.
ahknight 1 days ago [-]
Conversely, can you trust a local AI's answers about such topics (being small models)?
gizmodo59 1 days ago [-]
[dead]
_pdp_ 2 days ago [-]
That will be really cool. It is already possible though through Apple Intelligence. There is an open source app that already leverages that.
I love that they are bringing Claris back for this. Moof!
platevoltage 2 days ago [-]
I'm just learning that the Claris brand still exists.
crossroadsguy 2 days ago [-]
I hope it will be optional. This is too much to ask for on Apple platform. I recently had to install a 3rd party script to get rid of Apple's laregely useless AI stuff from my 5 year old mac and save more than a few GBs which I badly needed.
Running local models is already extremely easy.
I have a suspicion this app will be a way to add a too many gigabytes to the mac and of course like the Chess.app there will be no way to get rid of it. There are excellent cli apps/GUI apps like this https://github.com/ddalcu/mlx-serve - they are both cli and gui – and even its gui surprisingly nimble (I use this, but I am not related to the project). I am yet to try this https://github.com/ggml-org/Llama-macOS but I've seen only good reviews of it.
I also do not think Apple is doing it for the users who won't explore around. I can't wait to get off this operating system. Next time a friend travels to the continent I will explore getting a Framework laptop via them.
Insanity 2 days ago [-]
“Extremely easy today” - to who?
Their customer base includes many non-tech people who don’t want open a terminal window or even know of what a “GitHub” is. And they probably would not trust it as much as an app build by Apple.
I agree it’s easy to run locally (although I do so on Linux), but what’s easy for the HN bubble and easy for the rest of population is not the same.
brainless 2 days ago [-]
I really do not understand the value of running large models locally. I am absolutely fond of local models but for specific tasks. The agents need to do a lot of work in this case: orchestration, big or small model split of planning and work, split into small tasks, merging, etc.
LLMs with <30B parameter models seem like the sweet spot. I would rather focus on multiple tiny LLMs that are tuned to specific tasks (SQL queries, finance/accounting, backend/frontend dev, etc.).
For larger models, a $10-40 ish Neuralwatt/Opencode Go or any similar subscription goes so far for the average user that it is ridiculous. We are still in the "youth" era of agents. There are many patterns that work well with smaller LLMs. Or with a big-small LLM combination.
My context:
I own the tiny 16GB M4 Mac Mini and I use LLMs (coding agents) to build software and a few of my products use LLMs directly. Full-time user of LLMs, do not read or write code manually. I run the tiny Qwen series (<10B params) sometimes but a couple $20 subscriptions (Claude, Neuralwatt) take care of my full-time agent usage.
olowe 2 days ago [-]
I can imagine a future where we look back at these times of relying on big opaque hosted services to run inference and find it quaint. Perhaps the same way nowadays we find it quaint that you couldn't always just compile software on a fanless portable computer.
How far away that is, or whether it will ever happen, I don't know. I agree though that the tooling is still so young it's hard to say what shape this type of computing will look like and therefore what kinds of resources will be in-demand.
Same context as yourself. I run 8 - 12Bish models locally on a 24GB M4 Macbook Air and also have a couple subscriptions (OpenCode Go, Mistral Pro) for access to DeepSeek etc. to power through yucky big bloated codebases at work.
phyzix5761 2 days ago [-]
Privacy is a big reason to want to run models locally.
brainless 2 days ago [-]
True that. But ZDR is also not that expensive. Although for many businesses, buying a Mac with tons of memory is not expensive. Running a dedicated agent on top of private data is certainly valuable.
bauruine 2 days ago [-]
ZDR is just a "bug" or "rogue AI agent" away from being all data retention. ZDR is not for privacy but for corporations that need to check a compliance box.
nolist_policy 2 days ago [-]
Openrouter now does CSAM scanning and retention on so called "Zero Data Retention" endpoints as well.
Yeah. I for example use local inference for tagging up my documents that I self-host in a local Paperless instance, and I don't really feel like sending my medical invoices to clammy Sammy.
WokeUp420 2 days ago [-]
It's called privacy
tokioyoyo 2 days ago [-]
Model/harness that runs locally, which you can connect from your phone to do non-dev queries (looking stuff up, recommendations, planning and etc.) can save ~$300/year on various subscriptions.
brainless 2 days ago [-]
Agreed but I feel we will see even cheaper annual or prepaid options. Say, a $20 upfront and get the cheapest inference, comparable to Sonnet with subscription. For a personal assistant that can run on laptop and phone, these will be mainstream. $20 may last a couple months for vast majority of users.
ThePinion 2 days ago [-]
I have the same Mac M4 16gb. Do you have the Qwen model assist the larger models for menial tasks/tool calls during coding it can handle? As in have them work in tandem to save on tokens/calls on the large models or are your local agents just meant for their own specific side tasks?
brainless 2 days ago [-]
A mix of both. I have been experimenting building agents that focus on small/tiny LLMs. For example, I built a web-app prototyping harness which used Qwen 4/9B models but separate agents (tool calls, prompts and actual code to parse) for CSS management, TSX management, Router, state, etc. It used SolidJS only.
There was a task manager which was given context of the tech stack so it could split the incoming requests. Then branch out the tasks to appropriate agents. Combine the generated code - this was a file/module/import manager.
The other way is let tiny models (again I would use agents for different use cases) do the busy work - tool calling, finding evidence, etc. I usually setup agents to re-write tool call history and create fresh API requests without using multi-turn chat with tool call history.
ThePinion 1 days ago [-]
I really appreciate the response, that gives me good ideas on where to start going about all this. It seems so silly to have API models doing so much file exploration and tool calling.
I saw this a while ago which shows small models and focuses on the ones that make the least (or no) wrong tool calls and it got me intrigued on the possibilities in this realm, especially for lower end devices. https://github.com/MikeVeerman/tool-calling-benchmark
rapsey 2 days ago [-]
The addressable market is enthusiasts. The cheapest and least loyal consumer that exists. But I guess it is just a small side project for apple which is fine.
conductr 2 days ago [-]
Idk. Once they say our AI app is facilitating AI needs of big number of DAUs, the stock price will likely go up even if there’s no revenue path. It’s a pretty tulip.
jmaker 2 days ago [-]
When I hear Apple and AI, I think of Siri. And then of my attempts to use it in my smart home where it would turn off all smart sockets instead of turning on the lights in one room. Or its response latency. Or how I was excited about Apple Intelligence and then removed it completely and am hesitant to upgrade to OS 27.
I understand that we’re talking about local inference with an Apple inference engine for Apple Silicon uniform memory. And I know it’s a stretch of an analogy. But somehow I’ve grown skeptical of Apple’s AI capabilities. Not to say Microsoft’s or Google’s weren’t disappointing.
conductr 1 days ago [-]
For me Siri hasn’t improved a bit since release and it’s just the fact that she can’t understand my voice/words. Constantly mishears or asks me to repeat things. I have a pretty “regular” or “generic” US English accent and other voice agents have no problem so it’s definitely Siri. So I have never really been able to ascertain if it’s any good without an acceptable interface. I bounce immediately when I encounter the friction of having to yell, try to enunciate differently, think how to word my statements, etc. It’s like ordering food at a drive thru that has a broken mic and speaker and the employee is distracted not even trying to pay attention to my order. All to say, the spirit of your analogy seems appropriate to me.
yieldcrv 2 days ago [-]
subagents use mostly the same allocation of memory, so you can do orchestration and planning easily with many subagents just like you do with Claude Code with anthropic's cloud models
Pi has a subagents package to enable in its harness
nghiemphucminh7 2 days ago [-]
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MBCook 2 days ago [-]
But you’re still in for a ton of pain if you want to run them headless right?
They desperately need to fix that.
ctkhn 2 days ago [-]
It was pretty fast to get it set up. It could be better for sure, as it's not a first class concept the same way that it is in linux, but an hour of google search ai mode will get you where you need to go.
MBCook 2 days ago [-]
I know you can set it up to make it seem to work, but from what I’ve seen people say over and over, it will eventually end up asking you some question through a dialog box. And you will have no idea that’s going on other than all work stops. And the machine seems locked up or something until you connect a display and find out it wants you to click OK.
It SHOULD be totally possible. But it fights you.
LeBit 2 days ago [-]
The MacMini stays on my desk for that reason.
It’s too bad I cannot trust it to put it in my rack.
ctkhn 11 hours ago [-]
Can't you enable local VNC and log in over the network to manage it?
mingus88 2 days ago [-]
How so?
MBCook 2 days ago [-]
MacOS is a desktop OS. You really REALLY need to treat it like one.
Lots of things pop up and can’t be dismissed any other way than though mouse/keyboard on the display.
OS updated and wants to tell you it worked? No command line way to get rid of that. Program wants to do something and one of those system security prompts pops up (“BBEdit wants to access your Documents folder”)? Same problem.
You can set it to auto login and auto update and grant permissions and everything.
And then, one day, it will stop responding and you’ll have to hook it up and log in to see some pointless dialog that just wanted someone to click “OK”. And until you do no work gets done.
avazhi 2 hours ago [-]
Can I natively remove AI bloatware and models from running on my Mac in Golden Gate yet?
mark_l_watson 1 days ago [-]
I am on the waiting list. I have a new 64G mac mini and an older 32G model. The directions for setting up a distributed inference system aren’t too gnarly but I haven’t bothered. I will when I get access to Harbor.
I think it is a great joy to run most things locally, and still occasionally use the best commercial models when local will not cut it.
ontouchstart 1 days ago [-]
I am already doing 100% offline inferences and AI assisted coding with bespoke software developed with local models.
In my case it reached the recursive self improvement stage a few weeks ago. It feels like the early days of personal computing in the era of DOS and Apple II.
The hardware is already there. The only limit is product imagination.
ConfusedDog 1 days ago [-]
Any blog post or information on how your setup looks like?
nkotov 1 days ago [-]
I built out Infinity (https://infinitychat.app) for myself which does something similar. One click to download and run, compare models etc.
joenot443 1 days ago [-]
This is an awesome looking landing page. Very aesthetic with lots of immediate examples of what it does.
quaddoggy 2 days ago [-]
After I think about it, this makes sense that Claris would tackle such a project under the auspices of Apple. They're a subsidiary so they can monkey around with this stuff without having to adhere to the draconian everyday operating restrictions of "Apple proper". Good on them if they can pivot into something that hews to AI.
nxobject 2 days ago [-]
It's fun to think about Claris as the hobby "well, we'll see if it works out I guess, but no worries if not" brand. Perhaps "Claris Vision Pro" would have been less embarrassing for Apple. Hell, if they want to bring their car project back, "Clarismobile" would be hilarious.
caycep 23 hours ago [-]
Also I keep forgetting about Claris; I'm kind of sentimental about it and I hope maybe this gives them a shot in the arm.
throwaway_new_1 2 days ago [-]
The Mac Pro was discontinued at the wrong time. Or maybe just introduced at the wrong time.
pavlov 2 days ago [-]
The Mac Studio is inheritor of the 2013 Mac Pro approach. Back then people still needed internal expansion slots, so it was just too early.
andy_ppp 2 days ago [-]
I would be quite happy with an external box with no processor, no ports etc. (potentially HDMI out), just the GPU cores and plenty of memory. Then I can upgrade AI without the rest of the machine.
Of course Apple will not offer this.
kenferry 2 days ago [-]
"Harbor is currently in a private preview under Apple’s Claris brand, but it seems likely that we’ll see it launch to the public in the weeks and months ahead."
Claris?? Ok, this sounds like it's just someone's personal project. Something like this that was actually going to ship would be in a different org.
JKCalhoun 2 days ago [-]
That's okay. Wasn't the Graphing Calculator essentially that as well?
If true, it is an astounding story. That said, I'm happy to see that Apple ships a graphing calculator with macOS 27 (albeit, a different one). I may not use it much these days, but I have fond memories of it when I was in university.
liuliu 2 days ago [-]
https://getlocalcode.app/ runs local AI models (larger ones of course, DeepSeek 4.1 Flash 1017) easy. You can download and try it now. The problem is elsewhere: you cannot find M5 Ultra that you can purchase and set it up today.
pentakkusu 2 days ago [-]
As a recent M6 Mac mini owner, HELL TO THE YEAHHH BABYYYYYYY
I use oMLX btw, on 32GB URAM, running Hermes with Qwen 3.6 @ 128k context window.
I realize I am a smalltimer but for general day to day sensitive agentic stuff, this is the entry point.
yieldcrv 2 days ago [-]
if you're running qwen, check out what happens when you swap oMLX for kapitsa
its built just for qwen, healthy competition on tokens/sec
Maxion 2 days ago [-]
What is the experience of these local LLM models on this type of hardware? what are they capable of ? what do you use them for?
pentakkusu 1 days ago [-]
A-OK, I would say. The pinnacle would be that I managed to develop a purpose made android app for my 2016 Honda dash unit with Hermes.
Hermes runs my personal to-do, manages 2 calendars, triages forwarded bills via it's own email address, orchestrates my docker container fleet. It also tends to a partly botched llm-wiki, that is built on Obsidian.
yieldcrv 1 days ago [-]
I do agentic coding and agentic search and document analysis just like what I do with Claude
they have 128k - 256k context windows now, subagents use the same weights loaded in memory so you have spawn many subagents at the same time just like Claude Code, and the tokens/sec has is like 150-200
I just do different projects based on its complexity or liability or its moat
pentakkusu 1 days ago [-]
never heard of it, will check!
zf00002 2 days ago [-]
You can chat with the local model that ships with macos on your M1+ mac right now. There's a few servers on github that make it easy.
(1) All the headaches of maintaining FileMaker Server on Apple hardware, (2) multiplied with the additional requirement to cluster devices, (3) but without users accustomed to the silliness of misusing consumer devices running a consumer operating system for a service that must be reliable, and (4) an Apple subsidiary unable to bring about meaningful change.
azuanrb 1 days ago [-]
All this talk about Apple being the long-term winner in AI is putting an awful lot of faith in Apple. Siri is still about 1/10th as useful as ChatGPT on a good day.
It’s the “year of the Linux desktop” meme all over again. Any day now.
What would make running local models easy is being able to buy a Mac Studio without a 6-month delay :-(
w10-1 2 days ago [-]
OMG after 25 years, Claris gets something beyond FileMaker (among the most legacy software still alive)? Claris would not have the engineering talent, so why would Apple use them as a vector?
detourdog 2 days ago [-]
Currently FileMaker is a really expensive but sophisticated developer deployment environment. They stayed pretty true to the original vision in the mid 80’s when they merged their DOS database and added a gui layer for the Macintosh. I started on version 2 and it was at its best at when it went relational in version 3. Since then they have been focusing on deployment of graphical data applications and being a better database.
It will be interesting to see how this compares to things like oMLX
chews 2 days ago [-]
Deepseek has found safe harbor!
ggcr 2 days ago [-]
So many projects, start-ups and frameworks called Harbor already
sgt 1 days ago [-]
Indeed, but practically you can just take any name unless any of the existing projects are seriously big.
DerDerDaIst 1 days ago [-]
they should add a sandbox for the agentic part as well.
so you can control and monitor what the whole setup is doing inside and outside the box.
nxobject 2 days ago [-]
Developers! Developers! Developers! Developers!
wewewedxfgdf 2 days ago [-]
AMD needs Apple to kick it in the pants and make it realise they need to ACTUALLY compete instead of trying to just copy Nvidia.
wingi 2 days ago [-]
what is the difference to ollama, lama.cpp ... ?
api 1 days ago [-]
What I’d like Apple Intelligence to be is this plus a good local app to chat with models plus an iCloud version of OpenRouter with privacy screening features.
Even better would be a peer to peer model hosting hardware pooling system but that’s probably too much to ask and would expose Apple to liability issues in some jurisdictions.
If Apple were willing to eat some margin on RAM they could use the present RAM bubble to gain ground in the hardware market too. Financially you could call it buying market share.
amelius 2 days ago [-]
Great, except with current DRAM prices nobody can afford it.
lenerdenator 1 days ago [-]
I'd absolutely use this; doubly so if there was a way to route traffic from your iPhone to it through iCloud. That might even get me to buy a second Mac just for server use.
sleight42 2 days ago [-]
An Apple M5 Ultra running an app like that? Because Apple hardware is a monolith, unlike the PC space, "Harbor" will be configured out of the box with the ideal settings for many well-known open-weight models.
... Looks like I picked the wrong week to buy parts for a linux-based inference box.
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rickdg 2 days ago [-]
MacOS is a bad server.
q4y2u35uk 2 days ago [-]
Hopefully it won't be another preinstalled bloatware app like Image Playground. macOS enshittification has been greatly accelerating, even giving Win 11 Home a run for its money.
tonymet 2 days ago [-]
Why so much investment in local models when the remote ones are so cheap ? Everyone was fine with remote compute & storage before AI, now they balk?
t-3 2 days ago [-]
Cheap remote is probably not going to last forever. Memory prices will eventually drop. Local models will be more than enough for many purposes when the hardware is available cheaply enough.
tonymet 2 days ago [-]
that's a lot of ifs / whens , and the remote models work right now, and are cheap. It's not a gym membership.
nier 2 days ago [-]
People and organizations have requirements that their data stays on their devices or at least in their networks.
tonymet 2 days ago [-]
i agree that's a benefit, but we've had that requirement for 40+ years and managed with cloud too.
nier 2 days ago [-]
While I might imagine that there are customers who would store their data in the cloud but not necessarily run inference on it, there are also those who have strict rules against any cloud-based service. Those are the ones I’m talking about.
mbgerring 2 days ago [-]
Some of us were never fine with remote compute or storage.
tonymet 1 days ago [-]
I understand the reluctance, but the cost equation is inverted.
Compute & storage were cheap, so renting them was expensive for many applications.
Inference is expensive. Just getting started is 4-5 figures. Why not rent it for pennies.
Distillation works: we can get models leaner, have better performance with lesser and lesser parameters, more efficient, running locally. Apple gets this and we'll see the result with M7 Max/ultra chips and I reckon this will be one of the titular apps when M7 line of chips are introduced.
I guess it explains the haste Anthropic and OpenAI are in to IPO, cash out and leave the the retail investor holding the bag.
I don't think it shows yet but I think the dominance of the App Store will end. I think a ton of iOS apps will be replaced by ChatGPT/Claude. I think there is a big opening for a company to redesign the phone from the ground up purely around an AI assistant instead of apps.
I think AI will severely weaken iOS, App Store, and the iPhone in the next few years. It was nearly impossible to start a 3rd competitor to iOS and Android until recently because no one is going to redesign their apps for your new phone. Today, that's different. Many productivity apps are just being replaced by GenAI/ChatGPT/etc and services are making it easy for AI agents to access directly without an app.
Not to mention higher chip prices will eat into hardware margins.
I do not think local LLM inference will make up for lesser iPhone dominance.
Commodities like todo apps and calculators rarely compete on features, they compete on product design. This includes look and feel, relation between elements, design choices on what exact common features are available.
All products are, at their essence, just a set of design decisions stitched and shipped together.
Now, making these design decisions is hard. It requires knowledge, consistency, and insights into how real people operate real products. Even as a sole user of the app you build you rarely know what you actually need.
LLMs are 'design-less' in their essence. Building your own todo app takes literal seconds and it all looks simple because LLMs will default most of these design decisions for you - until you try to use your new app daily and notice it somehow sucks. Building a good todo app or good calculator requires tweaking, publishing, polishing, and solving bugs, testing, rinse and repeat.
Another tricky side of this is that you might know logically what features you want, but you are not selecting one product over another logically. You need to try and see if that works for you, all the vibes and good parts and bad parts and design choices and colors, till you find something that "clicks" for you. Using pure Claude as a todo app only works as long as you want to have more Claude in your daily life.
In the meantime app store provides dozens of well-reviewed alternative solutions which look good and require zero maintenance.
And that's just a calculator or todo app. Non-commodity apps are even harder than that.
I don't see any future where programs follow the static nature of old paradigm programming. A nice intuitive UI? What about just telling the app what I need when I need it? The gold standard of consumer UI is...another person.
If I have a team of god tier light speed SWE's at my disposal, why the fuck am I fumbling around in an actions panel? The program can just be dynamically modified in near real time to be whatever I need it to be in that moment.
If you extrapolate LLMs out to their extreme, you get a shape-shifting liquid array of bits in memory that manifest anything at the behest of a completely natural language interface.
Absolutely not. Constraining the set of possible actions instead of having you verbalise what you want every time is often a feature, not just a technical limitation. A camera with a shutter button is better design than having to tell the camera “please take a photo”.
At the supermarket, I personally also prefer the self-checkout machines over going to a human cashier.
The UI is totally fluid at all times, because an "intelligence" is actively manifesting it at all times. Nothing needs to be hard coded.
Hell the computer might even see your face, see your age and style, and be like "Yup, this guy definitely wants to checkout with a dumb, midi keytone 8-bit styled program"
The only reason it works out in my favor is that I enjoyed doing it. Normal people don't want to fuck around with that kind of shit.
But already AI design is everywhere and regular people don't even notice (outside perhaps the intentional cues in mainstream image generators). It's only going to get better as people can interact with the design the same as the interact with another person.
You're also assuming that there are no negatives to saying what you want compared to just acting on things, but since the beginning of computing many people have proven this wrong time and again. I suggest you read about HCI as a research field and its history, it doesn't take much to realise how limited the average HNer's understanding of UI/UX design is, and how far current LLMs are from the skills required to be able to carefully design an app for productive human use.
I like to customize my Neovim setup or terminal and a bunch of scripts that I keep making them nice and maybe my blog and so on.
I don't want to become the PM of every app I need. But I do agree changes will happen to the current apps and how we buy and use them. Not sure exactly where it will settle. But still unknown unknowns and domain knowledge and vocabulary is not yet allowing anyone to build their own apps unless for simple cases.
Or maybe it is just me: I want someone else to think about my accounting app. I dont want to spend time to learn and understand and keep myself up to date or setup a series of LLM sessions that navigate and watch laws and propose changes.
Why do you need an accounting app when you have an accountant?
Programs of the future will in no way resemble what they are today. I don't even want to call it a "program" because in my head it's more like an intelligent digital liquid that can rapidly flow into any state. This flash-in-the-pan 50 year archaic era of software will look like what the oil lamp looks like today. A crude intermediate tech during a time of much larger transition.
it's nice to see my financial situation at a glance, without asking my accountant.
speech/text is one modality. we humans are also visual and tactile. and we need consistency and recurring patterns of interaction to function well.
Same thing for your accountant.
Imagine that both of them, while being good at their respective jobs, are also software engineers that can mint a custom throwaway app for you at a moment's notice.
I'm sure your secretary will make a note of your preference.
Good design rarely calls for a “you can do everything” approach. Good design is often context specific and subtly guides users to better outcomes.
Doctor appointments would absolutely suck if I had to navigate decision trees and click buttons to communicate my symptoms. Car blinkers would absolutely suck if I had to type “blink left” into a chat window before every turn.
Maybe it’s just the ‘tism, but I hard disagree that I would ever say another person is a superior interface into… anything? It’s slow, they may misinterpret you, they have their own ideas and motivations, they’re (mostly) expensive because the only reason I need them is because there’s information / skill asymmetry. I don’t know that many or even most of those problems are resolved with ai, in some ways the problems are amplified.
Sounds cumbersome, slow to use, and prone to failure.
I dont think llms are going to replace banking apps anytime soon. But I no longer look for an app to pull data from my Peloton app into another exercise app. LLMs can build an app or a script that will do that and I wont have to pay some annual or monthly fee. It feels like these types of apps are going to die off.
I think it's better when you are at the origin, and the software branches off of your taste. For so long, we had to adapt and accept the ways of established software because it would take so long to make something of your own. Now it's both cheap and fast to iterate.
At the end of the day, it seems we'll be left with a decision of using something made by a person with real opinions or using something generated by AI with opinions that are a distillation of past documentation fed into it.
We're in this weird spot now where we are transitioning toward all ui feeling the same, and only the people really tuned in even notice this. Once the general public starts noticing, I believe there's going to be a search for fresh, organic, opinionated software. Not that the software won't be AI-generated, but it will have a human truly sculpting it, like art.
So the question becomes, if people still appreciate human-made art in a world where a better image can be generated in a small fraction of time via a prompt, will they feel the same way about the software they use?
Whatever "good design" is (and it varies by user), it's very easy to copy. Commodity apps complete on marketing. Companies who charge $10/month for an app, are probably spending $8/month in marketing/advertising.
I recently used a coding agent to build a TV-like YouTube player for my mother, who is quite elderly. It's inspired by channelsurfer.tv, but runs on the Google TV Streamer in my living room. Unlike any set top box I've seen, it has on-screen diagrams that tell her which button to press on the remote to change the "channel." It doesn't have ads. The UI will never change unless I ask the AI to change it.
You can't say that about most apps in an app store. They will do a UI redesign and you're out of luck if you preferred the old version.
Do you really think Google or Apple or anyone else will build this app? Maybe some self-hosted media box out there would be similar, but I can't be bothered to search for one and I'm doubtful that any of them were designed for an elderly parent who isn't good with technology. It's still work in progress, but at least she can use a single remote to turn the TV on and watch TV without being bombarded with things she doesn't understand and doesn't care about.
There are downsides that make this app less compelling for other people, but I didn't build the app for them.
There's a recent benchmark indicating Hermes Agent and, I think, Qwen's harness are far and away the most effective.
Pi isn't bad but it doesn't seem as talented as Hermes. Nor does it currently array of self-learning/adaptive plugins seem as capable. That said, it's difficult to keep track of the SotA with pi; it grows like the node ecosystem in its first year.
But we are not there yet.
However, you could expect LLMs to train on existing successful apps and hardened design patterns that compose well into good UIs. In that case, you might expect the last mile polish to be the differentiating factor. However, the more marginal this last mile becomes, the more other social, political, business, etc. forces will determine which app rises and which falls. But this has always been the case, certainly in software.
If you meant training on UI and features of established apps then it gets even more complex, as success of B2C apps is obscured by their pricing strategies and marketing, and business models for successful B2B apps like Jira/Confluence/Office often revolve around sales, partnerships and other non-product things like that.
Any business is a set of design decision someone made, with their app just being a small subset of these.
I think folks who live in spec-driven worlds just don’t appreciate how poorly understood the capabilities and processes of computing and networks are, to the point where even if you gave people hallucination free LLMs you’d probably find people just frustrating themselves because they can’t figure out what they want, what it should do, and how it should be used.
Quite apart from the huge chunk of the app ecosystem that relies on common protocols, centralised services and so on.
I have seen this with yet "AI-unexperienced" users - for simple questions or textreformating, they are absolutely fine with the Chatbots. But thats all they can get out of it: Above that level their experience is very often frustrating due to too less understanding while having high expectancy towards the model in reverse (like "its AI so it should know...")
And this people end up then not using any of the AI tools beyond that because they do not "believe" / trust that this thingy can get work done.
* Based on our music discussions, make a playlist for me in Spotify. No songs older than 15 years.
* Look through my email, find all my receipts, show me a graph of my spend and categorize them.
* My business needs warehouse space. Find warehouse services within 15 miles of San Francisco. Ask them for their pricing and capacity. Here are pics of my items. Send these pics to them for quote.
* Find a hotel for me in Los Angeles on October 1st to Oct 5th. 4 starts. Max $200/night. Gym is a must. Don't care about pool. Close to airport. I have Platinum membership with Accor so try to find Accor hotels but not a must.
People do know what they want.
It is easy to express yes, but is this how people think about what they want to listen to?
Someone can already do this in a chat bot, see the list of things and then find it on Spotify or whatever their favorite music service is.
What the chat bot won't know is what they have listened to, which is probably a much higher predictor of what you'd like than the discussions you've had about music. You've probably had those discussions because you are already listening to that music!
I thought the parent's point is that the App Store will loose dominance (because you won't need apps).
That’s a surprising requirement. Is it a proxy for “less likely that I’ve already heard it”? For “the band probably still tours”? For “I can discuss it with friends without sounding like I’ve been living in a cave”?
Essentially every single non-builtin app on my phone fundamentally requires the internet to work, and is backed by some sort of SaaS with a proprietary API. And even if/when the APIs are open, I doubt any normal person is going to decide that from now on they want to somehow use YouTube or Tiktok or Feeld or Spotify by talking to ChatGPT.
Spotify is an interesting one. I could see myself wanting to control Spotify with my AI agent.
And that's the issue, each app maker will simply integrate AI themselves with their proprietary API rather than allowing ChatGPT to take their lunch.
IE. I want to stay inside ChatGPT/Claude.
I think Spotify will open up. Or some AI-native music service will be started to compete and fill the demand.
I also think you’re way overestimating (based on one datapoint?) the number of people who want to use their devices from within an LLM chat app, even if at some point they should become aware of the idea.
I think they would really like to have one unified, plain-language interface.
Nice username btw.
They learn these apps differently than "we" do.
They (again, particularly older users who didn't grow up with GUIs) don't understand GUI paradigms, so they compensate by memorizing... even a small change to their memorized flow is highly disruptive because they cannot reason about how to get back onto the happy path.
(It's like the old, pre-GPS-navigation days when you went on a road trip with a stack of printed out directions from MapQuest. It was great, until you missed a turn and had no idea how to get back on track...)
Ideally, yeah, non-technical users could just invest a little time learning common UX paradigms. But a lot of people just won't. And really, GUIs were just a means to an end anyway. Maybe we just need to meet them where they're at with a more unified, naturalistic interface. The word "maybe" is of course doing a lot of work.
Only if structurally it makes sense. There's demand for many many things on this planet without a business model that would satisfy that demand.
I've played around a lot with using my own AI to generate music recommendations and build playlists.
> I don't want to use Spotify's AI. I want to use my own AI, who knows me more
It's pretty tough to beat what Spotify (or Apple, or whatever your platform is) knows about you w.r.t. listening habits and preferences. My successful experiments have involved exporting Spotify / Apple Music data into sqlite and a skill that tells my agent how to query this data.
It works pretty well! Still, I'd say it's only roughly on parity with the AI stuff Spotify is working on. The main benefit to rolling my own is being sure (at least, for now) that the recommendations aren't being corrupted by sponsored placement which I'm sure is Spotify's end goal.
I have no real point to this point, just blabbering. Have you cooked up any good solutions via rolling your own?
If Spotify won't do it, then maybe Apple Music might. Youtube Music might. Tidal might. Deezer might. Or a new service might.
It all depends on market share. If Amazon thinks they'll make more money letting ChatGPT/Grok/Gemini/Muse to shop, they will. I think they will personally.
I can imagine trying 'I want to hear a techno song that goes umm tss umm tss at 140bpm" and it finds a few million.
In what way? To find recommendations? Or search for a particular track?
It only needs to be created once. You don't want a different UI every time you listen to something.
For instance; I don't think LLMs will be replacing Spotify, Facebook, Insta, or Youtube for my parents. They absolutely do not want to purely interact with a blackbox. They want to scroll through songs/shows/etc. they want to tap on it, and have the app do the thing.
Even as a SWE, I have absolutely zero desire to interact with an LLM for everything, but I'm not the litmus. I have found use with these tools for taking on some nested set of tasks, but at no point do I want to give up the app entirely.
For people who like shopping (not me!), most of it is actually browsing and there is a joy in sifting through options. The OpenAI designers seem to understand this.
Apparently, GPT told him that there were 4 house listings in the area and so he asked my why the agency took down our house listing, even though he could have just went to <house_listing_website> and searched for it. Took me 3 minutes to open my phone and disprove him.
I think they are designing an addiction of knowledge. I think people want to feel like they possess all the information at a moment's notice (mixed with misinformation served as fact), without having to spend the effort to look for it
That's already happened. The curated feed you see is a machine-learning driven output of an AI model that Spotify calls a "Large Taste Model", supplimented by a host of models trained using Spotify's NEO framework. It might look pretty but it absolutely is the output of AI. I'd bet a fair sum that FB, Insta, and YouTube are also showing you the output of a model now rather than a traditional application.
(unrelated; but this sort of paradigm would be heinously more expensive)
Sure, but I don't think it's usually the apps that people pay much money for. And on top of that, app store revenue is (from a rough estimation) 6-7% of total revenue (although it's high-margin). Apple would be entirely fine.
And if you're right that the phone of the future will be reimagined as centred around being an AI assistant: innovative device design, user experience, hiding technology, integrating software/hardware/cloud are all things that Apple is historically pretty good at (with hiccups and bad periods for sure, but other companies certainly aren't better in general).
~15-20% of Apple's total profits at ~75% margin.
Investors are not going to like if that suddenly starts shrinking.
An LLM can probably whip up a music player app, but won't have the licenses to provide you the music.
An LLM can probably whip up someone akin to a free and single player Genshin Impact, but the whales want attention from other players.
An LLM can probably whip up some sort of SFTP from phone <-> Desktop for pseudo-cloud storage, but you still need to provide disk space
The other avenue that AI is hitting their services revenue is the Google Search deal, it's a revenue sharing agreement and AI is eroding that revenue on Google's side.
Why? Off the top of my mind (far from an expert and not thinking about it very hard), they can profit from AI in the following ways that have nothing at all to do with the app store:
For example if they capture 10% more of the global phone market because iPhones became that much better than alternatives thanks to AI integrations, that'd probably offset decline in app store revenue.Just throwing random ideas and numbers here, just making the point that shifting environment can weaken a revenue stream while strengthening (or enabling) others
To put it in perspective they reportedly collected about $675 million from OpenAI in fees last year, that's equivalent to about $1.5-$2 billion revenue in hardware sales and TBD for AI services but certainly over $1 billion.
https://www.macrumors.com/2026/03/20/apple-made-nearly-900m-...
Not to mention, Apple is going to want to not disrupt itself so they're going to deliberately slow down which opens up the opportunity for someone else.
OpenAI, Anthropic, and others can spend billions on the infrastructure to train the models at a time when the technology is still immature and largely inefficient and then Apple can simply license the models as needed, giving the user the choice while potentially protecting their privacy. Once there's relative maturity in the industry, they can either continue to license the models, distill their own from them, or even train their own using others' infrastructure. To me, it's a smarter long term strategy even if it temporarily gives up their control of key technology.
Personally, it seems to be the smarter play and aligned with how Apple usually does things. They're usually not first to market but they're first to introduce a refined product that make people forget about everything that came before it.
I get what Apple is trying to do. But it will still open them up to massive disruption and potential new entrants into mobile devices.
Therefore, I don't think they will be able to compete well in the new world.
Why this question? I don't think that the way that anyone expects Apple to profit off AI is from selling models
The Apple platform provides certain benefits to me. Take a look at Matthew Cassinelli' work (great speaker), if you have time (and a Mac I guess):
https://matthewcassinelli.com/sirishortcuts/library/#element...
His work is a library of Apple Shortcuts, AI, etc., that does stuff for consumers, I suppose pro-users. He was on a recent MacBreakWeekly podcast - https://twit.tv/shows/macbreak-weekly/episodes/1050?autostar...
The bits of AI mixed the platform affordance to simplify daily paper cuts by clicking on an icon is worlds apart from a Google SWE spawning 48 "agents" to parse lidar data to discover pyramids in Mexico. That's also cool.
Do I want to set up my scale to sync its data to my vibe coded app? Not really. Do I want to set up the dozens of visualizations and hundreds of different actions and thousands of different items for calorie tracking, where even a 5% error is extremely significant? No way. Am I going to convince any of my friends to download my vibe coded chat application? Absolutely not. Do I want to store my photos in my own vibe coded solution and trust it to run in 20 years? Not a chance.
While a segment of apps will surely become obsolete, I don’t think the majority of users time will be spent on their own vibe coded replacements. Even as a developer I have no interest in turning all my conveniences into maintenance burdens, with risk of catastrophic failure
The issue is there will be less demand for apps. I don’t need to pay for a dulingo subscription when Claude can write a 5 minute language quiz for me. I don’t need to pay for Turbo Tax when Claude can prepare my tax documents for me.
Sure, it won’t replace all apps, but people will spend less time in apps and more time interacting with llms which hurts App Store revenue (Apples golden goose)
And it’s not like Apple is fixed. If this really did become a threat, Apple could surely integrate into Siri some ability to generate apps from your iPhone and put it behind their iCloud subscription.
They’ve had XCode for years, managed their entire UI library basically since conception, and have their own language for their apps. Fine tune DeepSeek for a while on swift iOS apps and I’m sure you could generate apps rivaling frontier models.
I really don’t see any existential threats for Apple here.
We've already seen several attempts to make devices purely around assistants like Humane Pin or Rabbit. In 99% of cases users need a reliable screen with clear buttons not a conversational barrier between them and action
I personally didn't like the voice-approach of Humane Pin. Rabbit R1 was more interesting but execution was poor, screen was not big enough, models weren't smart enough, apps and services weren't as open via MCP as they are now and in the future.
I want to see a company like OpenAI or a very well funded veteran company give it a try.
I don't know, I think there's 1 or 2 apps I might like that for, but for many, I think I'd run into trade offs I didn't expec and at a certain point I feel like I'd end up feeling like 'I wish someone would just do this for me'.
If the models would tell me no sometimes, I could see this working, but opinionated models would need to 'mesh' with your opinions right? So then we'd end up where software is now, just choosing the model we prefer, instead of the specific app. And then there will be times my preferred model isn't the right model for 'this' application, so now I'm juggling multiple model apps, and what did we solve exactly?
That's why I've been trying to do everything in Claude Code.
To get something like this: https://www.youtube.com/watch?v=b9hxwgH2tN0
If Nvidia wanted they could end it overnight with a 60GB 6090.
Is this master stroke in the room with us now?
Now it can at maximum profit from it going public but not even that is sure now.
Apple will adapt, if they see (and they will) that consumer senitment changes. Right now, 90% of regular "consumers" seem to despise AI and anything made by it.
1. OpenAI/Anthropic must purposefully not sell their service to Apple and/or users using Apple hardware.
2. Local models must not get any better or slimmer than they are today, such that they can not be ran by Apple or locally on Apple hardware. This is arguably not even the case today, there are open-weight models that rival the frontier models.
None of these two things are going to happen. Apple does not need their own models.
From what I have seen you belong to the vast majority. Though not here on HN.
This is what we all want, this is what kicked off the open web back when the internet first started. This is what made everybody excited for user agents. Now we have user agents once more and we are getting excited about the new agentic web, but temper your expectations. This time, rent-seeking corporations are in it from the start, see the exact same promises that excited you about the open web, and plan to take full advantage right away. This is why everyone is trying to sell their own agent instead of giving access to your own.
Top paid apps outside of F2P gambling apps(all the "games" remaining on phones are gambling apps because they've repeatedly lured in and punished all traditional games, definitively burning bridges), making hundreds of dollars per paying users, had been like $3.50 ad blockers. iOS app development had been a lot less approachable than Android apps due to Mac host requirement, and with LLMs generating Android apps and HTMLs with ease, the fact that iOS can't execute .apk will make it successively less appealing.
Personally I don't think things like agent-first OS that don't rely on third party apps will come soon - that will have to be built from ground up as proper OS kernels, and I think it will run on desktops first.
The third OS always existed, the problem with those is that telcos won't carry it and people won't use such a phone with the nation's pick of social media - Fb Messenger for US, WhatsApp for EU, Telegram for Eastern Europe or whatever, MAX for Russia(presumably?), WeChat for China, LINE for Japan, KakaoTalk for Korea, ...
... thinking out loud, the third platform has to be the one endorsed by a social media. Like the old HTC ChaCha, or like, idk, "Startile" slab device running TeslaOS with Starlink DTC SIM built in. I wouldn't touch such a thing, but something spiritually like that. Or like a "Rakuten Star" with AST SpaceMobile eSIM baked in. Things like that.
What about doing something like REA on a whole app store collection, rewriting the app's reversed description set into code according the new devices' requirements? Perhaps we can't see the future as there are so many variations yet imagined.
This always puzzled me. Here's how that would go:
1. A new company, NeoPhone, launches that is redesigning a new "AI forward" phone.
2. The customers of that phone start noticing that they do many repetitive things with their phone, that they want the ability to design some repeat experiences with their chatbots. Call these repeat experiences "applets." Neophone ships some Applets on their phone that they created, a default set.
3. Customer A looks at customer B's phone, and notices their different applets that they designed. They work slightly better than customer A's applets, because customer B is slightly better at prompting.
4. NeoPhone notices this too. They create a new thing on their phone, the Applet store, where customers can share their applets and rate them and it surfaces the best ones to all customers.
5. Customers start complaining that they wish they had more creative control over Applets. Maybe the API is a bit more restrictive than they need, or the Applet needs to do special things with the phone's hardware, outside the context of the AI agent. Or they find that Claude Opus Fable 6.2 is better at making Applets even than NeoPhone's available chatbots.
6. NeoPhone allows 3rd party developers to develop on its phone, launching an "App Store" and a "Chat API" that is totally independent of the AI agent stuff.
???
Of course, Apple eats their lunch at step 2 or 3.
Sometimes even DoorDash gets it wrong, but at least I trust DoorDash to deterministically improve their systems so it doesn't happen frequently. With LLMs I would have to think that sometimes it just gets it wrong due to nondeterminism and insufficient reinforcement learning in the area of "reliable food ordering".
'Agent - file my tax return'.
In order to do that it's going to require you to have set up access to allow your bank accounts, shares holdings etc. etc.
Would you want to set that up to allow per task or simply always be in the background so if somebody hijacked your agent it could drain your funds?
[1] https://www.pewresearch.org/short-reads/2026/03/12/key-findi...
Example - search iPhone Settings.
They’ll be fine
Please, no. Just TELL me; that's why I'm using voice to talk to you in the first place. Summarize and tell me, don't show me a list of links from a web search.....
If a new mobile device form-factor proves to be usable, they'll come out with one eventually like they always do- like the iPhone duo being years and years behind?
When the bubble pops they could still snap up an AI lab on the cheap later.
They wanted to keep everyone on their proprietary platform instead of enabling their devices to be used on the wider internet / being a more open mobile platform.
As long as apple allows some AI integration, then I think they'll be fine- and in fact I trust their privacy and security model more than if I bought a Google device. (not to say I trust anyone's security model, but it's clear that Apple has a more vested interest in security and privacy than Google does)
It'll make the iPhone look like Blackberry.
And let's say that Apple wants to respond with their own AI-first phone. But wait, they don't have the model. They don't have the compute. Most of their employees only know the old way of doing things. It'll be like GM trying to compete against Tesla or BYD in EVs. Their whole workforce and skills are in ICE.
Just simply because interfaces need to be crafted, and they're a design language that you learn over time. And most likely everyone needs the same things 90% of the time anyways.
When I step into my car I don't need the heating button to move closer if it's cold. I just want to learn where it is once and use it when I need to for x number of months / time of day.
That also goes for things like films and music - most of the time we actually want to be seeing and hearing the same things as everyone else (for some different definitions of "everyone"), not something that's made for us.
It was fun as a toy (you could customize your UI theme to anything), but not useful as an actual user interface because it was inconsistent. Sometimes you'd get a progress bar, sometimes a percentage, sometimes a table of sub-tasks and their current status, etc.
Generating a UI to solve a specific problem of yours is just an example.
I can't be the only one who has ever used an app and thought, man I wish they added this or moved the button to this, or fixed this stupid UI bug.
You’re so DELUSIONAL. It’s hilarious.
Show us your portfolio of work as an innovator - just to ensure you have substance to support thes ridiculous claims.
Apple is absurdly late to the game. The MLX community looks anemic compared to Linux.
So far, I prefer tailnet to my home Hermes agent inference system and giving it ssh into my Mac.
It's easier having a single powerful inference system.
A Claude Pro account and Openeouter credits are my backups.
Would you trust access to your bank to a vibecoded phone of unknown origin? Backs will likely limit access as best they can for customer security. We already have banks who block GrapheneOS.
Look at the hardware wallet company that got sold and a spy chip to steal the contents was added.
I do believe AI is going to destroy companies like Adobe however.
This is the new reality that we must prepare to accept. You and I may not trust the companies, but the circle is closing in, and people around you are already on the "hype train".
However will they survive if they cede ground in commoditized consumer spaces to explore market fit in luxury goods?!
Literally nobody in the world wants more AI slop in their lives.
This is coming from my own experience as a software developer. I do not want to leave Claude Code. I'm hooking up everything into Claude Code and have it do what I want for me. I do not want to log into my cloud provider. I do not want to log into my Github. I don't want to log into any 3rd party services. I just want to stay in Claude Code.
I think developers tend to be ahead of the general public by 1-2 years in AI use. I imagine a future where most people simply want to stay within their ChatGPT/Claude/Muse/Grok/Gemini agent to do just about everything.
If my prediction is correct, I think Apple is going to be in trouble because it weakens the iPhone ecosystem severely and they are so far behind in AI everything that it's hard for me to see them ever catching up. Not to mention they do not have access to compute since they've not invested in compute.
Apple's use of Siri in Vision Pro is a good start, but there would need to be tighter integration w/ the UI. That's probably on the roadmap... assuming they continue to develop it.
It's competition.
I'm pushing the perennial 'developers (and engineers) think differently' trope here, but I think you're wildly optimistic.
The inability of the average person to write a detailed enough spec for implementation, compared to how trivial it is for an experienced developer, is mind boggling.
Imho, this is going to extend to agentic interactions with app-as-service-for-agent.
You don't magically increase customer experience by multiplying (garbage average user prompt) * (whatever agent they use) * (MCP, etc).
The first two variables are too unbounded.
I meant that non-developers will also find that staying within their AI agent to do what they want is better than downloading, logging in, learning different app UIs.
In our company, we recently gave Claude subscriptions to all office workers. They all hooked it up to their favorite tools already and they've been raving about it. It was a revelation for them.
In the past, you could look at a web page, see some structure, understand process, etc. and intuitively see and understand what you're suppose to do. When you remove all of that in favor of a text box, you spend a lot of time asking questions and prompting to get information or accomplish tasks that would otherwise have taken a minute or two and when you're done, you still don't understand how the underlying system, process, or policy is and how it works.
LLMs are getting exceptionally good at interpreting vague asks.
Do I trust a non-developer to build a production software system? No.
Do I think they can control Excel spreadsheets, PPTs, and other productivity tools through MCP? Absolutely.
One of the biggest issues I've seen in this kind of environment is that there are 50 dashboards, created by different people, and the data presented on them hasn't been validated to ensure that the data is correct and pulling from the same location. It's not clear that the data can be trusted and it's not clear what the authoritative source of truth is.
IE. They know what they're looking for. They know when the data is right or wrong because they've seen it from other places here and there over time.
When they're not sure and the risk of getting it wrong is costly, they'll find the data analyst to verify.
I've seen it firsthand, multiple time and while anecdotes aren't data, conversations I've had with peers at other companies suggest they have similar experiences.
Furthermore, that persona is also often incapable of self-checking and recognizing errors in their presented data, because they don't know how it was generated in the first place.
Instagram, Tiktok, Youtube, you're right. So hopefully OpenAI can convince those companies to convert their apps over. Wouldn't be too hard given how easy it is to duplicate an app nowadays.
How much longer do you give until Claude Code replaces you entirely? Product or CEO dictate their wishes and Claude returns a freshly compiled binary and offers to deploy it to production with a simple "yes". A SWE salary seems like an lot of money for middlemen to pull lever on Claude Code.
That's why my investment strategy is centered around AI replacing me and making me unemployable.
I'll definitely be buying Anthropic.
Funny enough, I do have substantial amount of Apple stocks I accumulated pre-ChatGPT but I've been selling here and there as it reaches all time highs due it being an "AI hedge".
I think Wallstreet is getting it wrong and I think the narrative around Apple will change fast in the next few months.
Failing to evaluate AI beyond "slop" is down to a lack of imagination.
Please.
I want to see the projected numbers.
Huh? I just took a look at my phone -- I have about 100 apps on there, though probably only use 20 of them with any regularity. I don't see more than a small handful that could be replace with Claude (if it had access to the APIs that the app does),
And even then, a chat interface isn't the optimal way to interact with many services. Random example: A simple metronome / tuner. Could I ask Claude to play a tick at a certain frequency for X amount of time, or a E-flat? Sure. Would it be easier than using the app? No. Could Claude design a metronome app for me? Yes, but I don't want to have to deal with that process -- I just want a metronome app that works and I don't have to spend time designing or fiddling with, and that works offline, and all of that is well worth the $5 I might spend to buy it.
Right now 128GB MacBook is the top of the line and you could do Qwen 3.8 Flash or similar.
There is a rumor that the M7 chip can use 1.5TB of memory which would imply Apple is aiming for more memory on devices.[1]
Would that imply the entry-level MacBook will have 128GB and top of the line models could run larger reasoning models? Then the question is price and if any of this will translate to iPhone for on-phone models.
With how expensive memory is, IDK if they can pull this off but I hope they do
[1] https://www.tomshardware.com/tech-industry/semiconductors/ap...
Most people neither need nor want to run large LLMs locally.
The entry level MacBook Neo costs $599. Even if RAM prices revert to the pre-AI mean, the entry level models are not going to be that stacked with RAM.
Eventually we'll get to a doubling where entry level means 16GB of RAM, but most people won't be running anything more than simple models for light local work.
Have you ever tried running large LLMs on a MacBook Pro? It's hot, loud, and makes your battery level disappear at rates you didn't know were possible if you're not plugged in. It's a very niche hobby.
You can get uncensored versions, but they are less usable (lobotomized).
Personally, I find the whole idea of AI porn pretty depressing. Porn is very bad acting, or no acting, but at least the people are real.
First someone would need to invest and train a model on pr0n, and then they'd likely first want to recoup that money - perhaps by selling a subscription to pr0n addicts.
Whatever local LLM device comes out of this, it certainly won't be a laptop.
(I envision a black box like a router you plug into a socket and let sit in a corner of some room.)
I'm old enough to remember the time when most people neither needed nor wanted a phone with a large screen and no buttons
If Apple, in 2030 has a compute product that a worker can BYO(X) to work that has 2TB RAM, with an encrypted personalized context that can float between agents, then they will be in a very interesting place.
holy shit
But the family shouldn’t be limited by that. We’re not going to see M6 Max hardware, because the M7 line is being fast-tracked and pulled forward. And I wouldn’t be at all surprised to see M7 capable of 1-2TB or more.
It is, at the very least, a practical limit. There are unlikely to be enough customers willing to pay $50k+ for a hypothetical 1TB RAM version to make it worth manufacturing.
Spoiler alert: they're supply-constrained too. Their customers will pay to outbid Apple, just like how Apple outbid the industry on TSMC's 5nm node.
If Apple can't place DDR5 orders that outbid the HBM demand, then yeah, Apple Silicon is going to get fucked over by every vendor. They'll be laughing their way to the bank while Apple begs Californian courts to give them free RAM.
i suspect that they will at least do offloading for casual usage as well. if they can ship 24GB in a homeview or appletv style product, it's game over.
why would a company who locks iPad Pro entry level literally out of ram that exists on its own chips.
I get their high end 10k-20k laptops will be able to reach these specs and gatekept behind also upgrading the cpu to the ultra but no way will it be an option in entry level.
Even so, DDR5 is so high-demand that it's likely that Apple can't outbid customers like Nvidia or OpenAI when they drive the margins they do.
Design, engineering capability and money are all a problem here, and the onus falls on you to prove otherwise.
SK hynix, Samsung and Micron are all eager to squeeze Apple for the market price of DDR5. They won't build extra fab capacity for them because Nvidia, AMD and OpenAI will outbid them for future capacity. Products like HBM are overbooked right now too, which means that building an extra DDR5 facility might just end up feeding the enterprise HBM market.
And CXMT has refused Apple's business entirely: https://appleinsider.com/articles/26/08/06/chinese-ram-suppl...
I don’t think Apple can be in a position where all of the Chinese device-making companies can get memory at a significantly cheaper price from CMXT, and Apple is stuck with buying memory from the three hyenas of memory at a significantly higher price.
That’s not going to help Apple sell their devices at a competitive price worldwide over time against the Chinese computer makers (Lenovo, Asus, and Motorola) and make no mistake about it: their share of the market worldwide will get bigger because of this change in the memory market; their focus will be on the long term, while the lawyers/MBA/finance types in the West will have their heads stuck in the short term.
It’s the (Chinese companies’) opportunity, and they’re not going to let it pass; I wouldn’t. In addition, Apple is in competition with Nvidia, Microsoft, Intel, AMD, Qualcomm, Google, Meta, and indirectly with Anthropic and OpenAI (whose CEO, Sam Altman, recently declared that computer ram is wasted on low-level regular computer users), along with a whole legion of other 3D model makers on the procurement of memory.
The combination of all these elements going into the future means that if Apple wants to stay ahead, I believe Apple has no choice but to take memory in house, they have the design and engineering capability in-house, and they have the money because they didn’t burn it on AI models and data centers.
This scenario is no different than replacing Intel or Qualcomm; you can see the writing/destination and the ultimate train wreck up ahead if Apple doesn’t roll up its sleeves and get busy, the market has changed and again Apple has to change and adapt to the new conditions.
I wouldn't be surprised if that was happening already -- they plan five years ahead, after all, and they've been slowly taking other systems in-house (e.g. baseband/modem) already.
Why are you talking about memory? Nobody cares about memory. You know what people care about? People care about ballrooms, and you know what, the US has the best!
People who know ballrooms say the US is hot right now, hotter than anywhere else in the world, because we're building the best ballroom in the world. Can you imagine that? China is nowhere on ballrooms.
Probably sitting under a router, so that it can hand off bigger jobs to an Apple DC somewhere, probably with a certain number of credits based on your iCloud sub.
And with a device like this, you pay one single time to buy the product and then never have to think about paying for tokens ever again. For ordinary users that's silly, but for users or businesses chewing through lots of tokens, this means they can create their own turnkey replacement for "the cloud" where the only cost after purchasing the machine is the electricity to run it (which with these machines is very little). Mix that with the privacy benefits and suddenly it makes a lot of sense.
Like I said, seems HPC is lost art. All four sub replies missed that in my original comment.
For individuals though, it’s the same reason plenty of people pay for the 2tb or 4tb SSD for their laptops or desktops even though NAS has been a thing for 40 years. Maintaining a “server” of any sort is a completely separate endeavor for most. Just like a NAS is a no-brainer for many and non-starter for many more.
The problem with LLMs outside of server is that people typically have many devices. So you can run LLM on your laptop. You want to make a query from your phone. Start your laptop? You want to do something from your smart home? Start your laptop? What about your partner? Will they need to buy another top of the line laptop for themselves? Your kids?
Alternative to server is of course that everything will have over 100 GB of memory, eat battery like crazy, be dumber and slower than single server in your household.
4 TB ssd was like $300 until recently. Even if RAM prices were to go to previous values, I don't think AI capability will be any comparable. Besides you also need proper compute, unless you want your prefill to be snail slow.
Every scenario you described applies the same to a NAS. What if you need a file from your phone? Open your laptop? What if your partner needs a file? Open your laptop? The answer to all of them is either yes, or they have it on their laptop/phone too.
Apple (and other laptop makers) weren’t charging $300 for 4tb even before the shortage. They realized that not everyone needed that and they way overcharged for that but still less than today’s prices. People who needed it bought it even though it would have been a lot cheaper for them to build a NAS. A current-gen M5 is perfectly capable of doing decent tk/s given enough RAM. In 2 or 3 years it would be even more capable, it just needs RAM.
Plenty of people will use clou hosted models like they do with storage today. Plenty of people will build home servers for AI. Just like plenty of people have home NASs. But the number of people who just want a large SSD on their laptop make the previous group a rounding error and those people would rather have a beefy laptop or desktop with enough RAM in it. If anyone can solve the Phone<->Desktop communication seamlessly it’s Apple after all.
Unlike storage however, a lot of people are now aware of how much data collection tech and AI companies are doing and the idea that AI models are training on their personal photos and prompts is deeply unappealing to many. With just storage, what could Google or Apple do? Certainly they wouldn’t just print your photos and put them in an ad or on their website. But with AI models, it’s a different equation
No. Files are your property. Inference is a service.
There's also the fact that working with files over network is often ill-advised and borderline impossible for some workloads. Even when that NAS is connected over wire and not wireless. Meanwhile even if you're on so-so connection, LLMs work great.
NAS is mostly good for backups, torrenting linux isos and serving them with Plex or Jellyfin. You are not installing software on your NAS instead of your machine. Or doing video editing. Or playing demanding games. I have file server at home and I still have ~8 TB of storage in my desktop, of which at leat 3 TB I can't move out.
B. If I have 1 TB of my work files, my wife has 1 TB of her work files, that's 2 TB of total storage. If both us need LLM, it doesn't mean we need twice the LLM as one of us.
Not saying they're right.
I agree with you, and i would like to set up a server at work for local inference but we simply do not have the knowledge, it's much easier to get a couple of AI Max machines that are good enough for me and the boss which i convinced on the good points on running clankers locally and be done with it (though my plan is to use the AI MAX machines to figure out what the infrastructure and workflow will look like, and at some point ask for the investment)
How is this literally even possible in 2026? In a thread about LLMs, no less?
Then there's testing the approaches and see whatever sticks best.
All while you're actually doing your actual job
But on the other side, equipping data centers was never Apples main business. Their approach to markets is to design products for the individuals. They also usually have very long time plans. Look at where the Apple Silicon today is and how long a path it took. What about the day, where at least a medium sized Mac becomes a great platform for running large models locally? Very easy to use, no setup, no privacy concerns. Also never worry about "tokens". You can then use AI as you use other local resources of the hardware you own today.
Could be the winner, in your opinion. They are extremely well positioned with hardware, devices, ecosystem, privacy, brand value & trust, and a significant active base. So far, they have not yet delivered on any useful AI application. There are so many opportunities in both MacOS and iOS, I guess they just need a new software VP.
So does Apple even need to create applications (that nowadays will get copied and opensourced in a day), or the hardware is the winning strategy in the end?
I think the more interesting question for Apple is the split between cloud and local. Economies of scale and aggregation vs privacy and ownership. I’d say so far it’s 2-1.
Who has? Google, Anthropic, OpenAI and Microsoft have spent hundreds of billions and produced nothing but chat apps that Apple could build in a few days, they’re all just interfaces to models that are available to Apple via an API. Hard to imagine Apple as anything but the winner of this era unless OpenAI or Anthropic pull something out of the bag.
None of that stuff has worked right for several years now apart from maybe Gmail.
> they are being inactive because they don't have the skillsets
Rare to see an argument that Apple can't hire talent.
They need a significant team creating their own model, (the talent of which has already gone elsewhere) and they also need to be working towards the future of photonic computing for running those models with success long term, again which will require a huge hiring effort. Considering it's clear they are not putting in that hiring effort it's obvious what work they have been doing.
This is extremely revisionist. For ex with WiFi, ThinkPad + a Lucent WiFi card was standard issue for years before any Apple product had WiFi. Apple shipped integrated WiFi, which is wholly consistent with the notion of improving what the industry is doing.
Connectors? Yes, Apple has a history of improving connectors. Other computers have had connectors since forever. In this case, Firewire was Apple's semi-proprietary alternative to USB. USB, which Apple put into their computers years after others had shipped it.
> They need a significant team creating their own model
Your judgement. It's entirely reasonable at this point to license other models and look for a better/cheaper entry point. Apple tends to enter markets when it is possible to make profit. It is not clear yet that the business of creating and running advanced models is a profitable venture. By which I mean no company has yet demonstrated the ability to earn a positive ROI by developing and running an advanced model.
> working towards the future of photonic computing
Again, nothing in Apple's history would suggest that they would even aim to do this.
This isn’t true they’ve literally launched Apple Intelligence with multiple apps and surfaces three times now and it’s flopped each time so badly they regroup and pretend it wasn’t the real launch then launch it again at the next WWDC.
You could spend it on free universal healthcare.
AI doesn’t have to be full-blown conversational AI.
In Photos, text recognition in Photos works well, object recognition and face recognition are somewhat decent.
In Mail, I find message summarization useful.
Small steps? Yes, but I think these are useful AI applications.
I do not use them, but in accessibility, they have AI applications to describe scenes which, I think, are useful to some.
Siri just got AI-fied and it's worse and slower than ChatGPT in 2022. Also it doesn't work offline anymore.
I used to "describe a shortcut" maybe 5 times this week and today I was hit with "you reached the limit". Mind you I have a 17 Pro and spend $120/year on iCloud.
These are useful applications of AI - or would be if they actually worked.
But this is all based on marketing not facts. Apple is as privacy invasive as the next guy. Obviously this shtick will work as long as marketing continues do to good job.
I don't think so. LLM inference enjoys huge economies of scale. At no point in the foreseeable future will a local model be able to compete with a cloud model in terms of price. Local models will have the privacy angle, but very few people will be willing to pay top dollar for that. There will be some people, for sure, but the vast majority will just use cloud models.
Does it actually? Sure, it is operating at huge scale and this design choice allows enormous models (presumably enormous MoE models). But is it achieving economies of scale?
Economies of scale are rooted more in the idea of a profitable thing becoming broadly sustainably cheaper as the market grows, allowing cheaper manufacturing and further growing the market.
The big two or three LLMs are cheap because they are substantially subsidised by investor cash, and they are not profitable at all in any sustainable sense: the current pricing can only be sustained for as long as they can raise money, and the market will (and does!) shrink when it is asked to pay a less-subsidised price.
There appears to me to be no route to true profitability for this design strategy at all. Even the open weights router companies are downstream of largesse from state-affiliated companies.
Maybe when chip would infer at 10-20x the speed of a 5090 RTX, otherwise it's really..bad.
Beside the 35b, the others are too slow to do anything vs cloud models, unless you have a local B200+. And the Qwen 35b has the reasoning capacity of a 2yo doing maths.
I wasn't "impressed" with any models for coding until 1year ago, only then they started to be "usuable" with the fault that we know and still exists.
What new bike should I get? How should I rephrase this email? What to do about my persistent headaches? Recipes based on these ingredients?
In the mainframe's heyday, it was difficult to grasp a world in which compute became so dense and so cheap that it made sense for each individual to have all processing and memory on their desk, talk less of on their lap and in their hand.
Of course this time could be different. But, when we look at previous relentless progress in compute and efficiency, then also couple that with the breakthroughs AI itself unlocks, it's hard for me to imagine that centralized AI will meet both the scale and flexibility desired for all use cases.
Just as centralized compute never fully disappeared -- it took the form of client-server computing and the cloud, there's no question that centralized inference will continue to exist.
But it wouldn't surprise me if, ten years from now, 90% of global inference happens at the client.
While simultaneously, the 10% of inference that takes place in the datacenter is wildly lucrative and orders of magnitude greater than today.
Put simply: the inference pie may become so large that both client and datacenter win.
Beyond inference, even local HPC or large in-memory workloads. Steve Jobs dreamed that the NeXT Computer could be used to cure cancer in a dorm room (whatever tha tmeans), and I guess a bunch of Mac Studios chained together wouldn't be bad for a lot of computationally tough biomedical "basic science" applications.
It'll become easier and more affordable to distill/train/optimize smaller local models to meet your specific work needs. Multi-agent efforts will orchestrate the balance between using on-prem hardware for most tasks, and then defer to cloud models for more demanding/edge-case tasks. Especially if an organization can manage what data is shared with which model, and most of their user base are everyday casual users.
I also expect cloud providers to eventually start charging different rates for on-peak and off-peak usage, which would incentivize running what you can with the local compute you have otherwise sitting idle across dozens to hundreds to thousands of machines in your fleet.
Anthropic just changed their policy to invalidate any unused credits without refund if you buy your API credits annually. I see that as a sign of unpredictable budgets for cloud models for customers.
I could be wrong and all your future hardware purchases for end-users will be thin clients, without the local processing capabilities of today's laptops and towers. I don't see the hardware manufacturers profiting much from that, but maybe we'll see more companies like AMD declaring they prioritize cloud compute customers over everything else.
With a hardware refresh for cloud computing every 3-5 years, we'll likely see today's compute hardware driving Opus and Sol available on the secondary market for companies willing to build more on-prem capabilities.
No, it's exactly the opposite.
The big money is in small(ish) but finely tuned for specific tasks models.
Whoever invents an app store for LoRA adapters will win this AI race.
Qwen flash-next is at least as good as Sonnet for my uses, and the speed is perfectly acceptable.
I really think the big labs are going to soon start feeling pricing pressure for everything smaller than Opus-tier models, and it will come for those next.
Only if you're comparing apples with oranges. There are no local LLMs at 128GB RAM which compete with Sonnet 5.5 intelligence. And the gap is a chasm when comparing against Opus 5.5, which is fast and cheap and plentiful on event he $20 subscription.
People saying this actually know how to run local models.
People claiming otherwise are Claude customers who know nothing beyond its point-and-click interface.
Consider that fact.
It's not comparable to huge models of course, but given the power/size ratio here it shows that serious gains are on the table for models that can run fast on a high-end laptop.
A few years back we never thought open source llm would get as good and even the small and cheap model
Its good to have a race and such competition
At some point, the real cost of inference/intelligence is going to come due, and the existing open source models will be good enough for 95% of tasks users want (or training their own model(s) will be inexpensive for Apple).
Apple will be there, as usual, to provide secure, on-device, faster inference that the vast majority of their customers will be fine with. Let everyone incur the R&D costs.
Look at what it costs to serve Kimi K3.1 Pro on a B300. It suggests margins of 98-99% at API prices for OpenAI and Anthropic.
Should the shortages for memory and GPUs ever improve, this will only become much cheaper, won't it?
That said, R&D is another story.
Where I am, it's cheaper to purchase multiple claude subscriptions than it is for the power bill from running a local model. Factor in the hardware costs, and you're looking at a break over a decade in the future, for comparable cloud models. Yes, there's privacy, etc, but now you're down into fractions of a percent of users who care about the government reading the memory of their computer.
Apple and Microsoft and other companies will own that front-end experience with the customer, and it’s not going to matter to most customers whose backend gets used for what.
It's not as if they are short of money.
Or are you saying that Apple should become a memory manufacturer, rather than working with TSMC?
Afterwards we’ll have 128gb apples for under 10k.
Also a lot of people work from laptops and running inference on data centres for 10th of the price is a no-brainer. Local models are more of a niche and always will be.
MacBook Air + Claude max sub for 20 years would still cost less before a maxed-out Mac Studio makes sense (not taking into account running costs), even then it’s not a Frontier or as fast.
Why, though? They had a sufficient mountain of cash to outbid everyone else for TSMC capacity, and no realistic hope of catching up to TSMC's process on their own fab
Also, I'm not exactly sure we should be claiming what is and what isn't realistic for a trillion-dollar company. People could (and probably did) argue that they had no hope of catching up to Intel/AMD, and yet here we are, with Apple arguably having surpassed both, at least from an energy efficiency point of view.
Realistically speaking, "catch up to TSMC" is something that every single EUVL fab has failed to do despite tens of billions of dollars in investment. Spending money is the easy part, developing high-yield processes over a timetable of decades is the hard part. I think Nvidia and Apple both agree that paying TSMC to build American fabs is a smarter use of their money if they just want excess fab capacity.
NVidia aggressively segments the market on VRAM. Apple’s shared memory model is a competitive advantage. Well, it will be when they hand the raw PFLOPS, which is coming.
Yes, I promise you, there are many, many people who are hesitant to build anything real on the assumption that either Anthropic or OpenAI will continue maintaining their services as they are today in perpetuity.
I agree that it pays to be wary of the additional abstraction layers they offer that purport to make your life easier, but for anything running standard completion calls or the like, I don’t see why this needs to be a concern.
Factoring in the increased cost of memory, Apple's threatened service revenue and the stagnation of ecosystem products like the Mac and iPad, I think they have a really challenging future to navigate. The whole "sell people a B2C ecosystem" business model is more threatened than ever.
I don’t think there will be a choice long-term for Apple the conditions of the market have changed, and you have to change with it or get left by the wayside. They have shown that they will adapt and they certainly haven’t wasted money like their tech competition over the years.
Apple would make more money investing in a CUDA-style architecture than they would by becoming a subsistance manufacturer for the pitiful margins of the iPhone, iPad and Mac.
You tell me.
Capability is one thing but a focus on the actual product, as an teleological destination that is built rather than something cobbled together as a solution to a problem about how to sell what you have generally has taken them the right way.
It's nice to have these types of niches when they make you money. But the Mac isn't profitable like the iPhone is, and probably makes less money than the iPad does if you count aftermarket service sales. The further Apple drifts from their roots as a computer manufacturer, the more the Mac starts to look like a liability to them.
Apple's Last Stand is their prosumer segment, and once that's gone I don't think their vertical integration playbook gets them anywhere further. Their bottom line is dependent on finding new ways to make B2C profitable, which has resulted in subscription services like AppleTV/Apple Music/iCloud so far.
That looks pretty healthy to me.
Note that because most enterprise software is now web based ( ie moved to the data centre as you have pointed out ) - a lot of the corporate Windows only lockin has gone - so I'm seeing a steady rise in Macs in business.
What's not healthy is the desktop market ( apple laptops outsell desktops like 10:1 ) - but that's whiles that's more marked in the Apple space, it's largely an overall market trend. ( Overall desktops are about 20% of total shipments ).
So Apple will only be in trouble in this space if the laptop ceases to become wanted - and that's all about the interface - some apps are better with keyboard and mouse/trackpad and a bigger screen. If all that goes away and we just talk to our computers then I'd argue that Apple are better placed than Lenovo to weather that one.
The proliferation of web-based enterprise software mostly stands to Windows and ChromeOS' advantage. macOS is the platform that has relied on "native" and "ecosystem" efforts that are becoming increasingly unpopular among consumers and industry pundits that don't like paying per-seat for software services. The Mac Pro used for render farms, on-prem hosting and cluster computing was depreciated completely, driving some of Apple's highest-margin customers over to Linux and Windows servers. Apple has absolutely began their Mac pivot to prosumer/B2C vending, and it's resulted in advertisements and SaaS slop invading macOS.
Lenovo will keep selling laptops because that's their product equivalent to the iPhone. Apple's equivalent to the iPhone is... well, the iPhone. If they see an opportunity to force Mac users into an iPad-esque experience, they'll take it in a heartbeat and play coy asking "what's a computer?" like the iPad advertisements. The Mac not an important product for Apple these days, the App Store is.
Totally agree that Mac servers ( they went years ago ) and Mac desktops ( and desktops in general ) are on the decline.
I just think you are basing your opinion on the past. Sure in the past, when Apple hardware was worse overall than the Wintel offering, Apple heavily relied on the Mac specific software, and your right that's less important now more than ever.
But the point here is right now, and for the last few years, Apple hardware is significantly better! And because of this in turns your argument on it's head.
I think we both agree that the landscape in terms of mix of devices may change in the future - I just think Apple is following that market, not 'forcing' Mac users into an iPad-esque experience.
And right now I think the laptop market is still pretty healthy - I can't see Apple moving away from it unless sales drop, and as I said sales are actually rising.
Soon enough: "Claude, please build me a MacOS clone. Hell, copy the entire Apple ecosystem the way I want it."
But the hardware. The hardware is fantastic for local LLM's, generative ai, etc. And they seem to maybe finally be waking up to that, in true slow sleepy Apple fashion.
If they'd been a bit quicker about it we could have a higher tier iCloud plan that included a chatgpt plus style setup with the "its private" marketing tag that cant be provided by anyone else. Instead we get Siri being slightly less useless than before.
Not if they can't sell anything because of ridiculous DRAM prices.
I'm not sure which chip it'll be, but I now for sure I'm not buying new devices until the AI boom has somewhat settled and we kinda understand what we'll be using it for. Until then, every manufacturer will just be guessing what device to build and will be outdated within a few months.
Local models literally cost more in electricity than using far more powerful cloud models cost in inference.
When your options are "dramatically drain your iPhone battery for substandard AI, or have instantaneous cloud AI with no battery drain" what do you think the average user will choose?
And that's before we discuss how ridiculous the pricing is for home hardware that has a chance of running a halfway decent model at a halfway decent speed. Residential electricity + overpriced underutilized hardware means you're going to pay 100X or more per token.
I think the future prospects for local AI are looking worse than ever. It will be far more expensive for a far worse experience for the foreseeable future. It will fill a privacy/control niche, but beyond that, it's not a serious option
Anthropic and OpenAI want to exit because they know they have no moat... and personally, I believe that the sociopaths running the US at the moment want to provoke a great economic crash. The Evangelical ones because they want the armageddon [1], the rich fucks because they took the "you shall own nothing" part for real and want to be the new neo-feudal overlords. And the best way to achieve that is by tying everyone's retirement savings up into their bubbly assets and then crashing down the economy, leading them to buy up everyone's asset at fire-sale prices with the liquid cash they made during the exit.
[1] https://www.theguardian.com/world/2023/oct/30/us-evangelical...
And Apple really wants to sell people who have no cred in the space their stuff because THEY have no cred in the space.
Its basically a club for stupid f**s
There's a name I haven't heard in a long time! Claris (always an Apple subsidiary, since being founded in 1987) renamed themselves to FileMaker in 1998, but apparently they rebranded back to Claris in 2019.
Looks like they've mostly just released annual upgrades to FileMaker for the past decade, but they did add MCP to it last year: https://www.claris.com/blog/2025/why-mcp-matters-for-claris-...
Some of that software has been in use since the 90s and still works. Adding AI to the equation will empower a lot of people.
However, FileMaker is not really targeted at software engineers. In fact using it as a developer will likely drive you up a wall. It's things that feel totally fine to non-devs but completely insane if you're used to something else. E.g. I remember having to click a thousand GUI buttons just to edit a few lines in a script once (regular users just "record" them through the UI). It did all work fine though, very reliable.
They added some more developer-specific features later, but it took a long time. E.g. editing scripts as text(-ish) only came in 2015 (FileMaker 14) and an actual programming language in 2020 (JS, FileMaker 19).
A few years ago Filemaker, Inc took on the Claris name.
If/when Anthropic changes to pure API pricing, or for API-heavy projects, that's when I'd switch to more local models. Of course there are tradeoffs for speed, quality, upgradeability, etc.
I currently run a Mac with 128GB and qwen3.8:27b-mlx. It hits the heat limit of the Mac when working on a 200k LOC codebase for security auditing and hardening for many hours at a time. This isn't as strong/fast as Sonnet, to be sure, yet the cost is only $6K one-time plus the usual electricity, maintenance time, etc.
$6k is not the only cost - electricity adds up over time. And hardware can fail, redundancy is priced into the token prices and subscription plans. Maintenance is mostly negligible, but some updates/upgrades might regress. There’s a lot to SRE to keep it running at that scale.
I run "npx ccusage@latest weekly" and also spot-check Claude Code sessions via "/usage".
> No consumer hardware will give you that level of latency at comparable cost.
You're right. My belief is the frontier AI companies are currently subsidizing real costs for the purpose of rapid growth customer sign ups, and that in a couple years or so local costs will become reasonable, at least for full-throttle work that's queueable.
Data sovereignty always makes sense in this case because it's explicitly not about cost, but I've not seen a convincing "it's actually cheaper to do it yourself" analysis that came to that conclusion by answering all of these things up front instead of just hoping it'll somehow get better by then.
For good latency, you would need a multi GPU server around $3-600K.
I agree the hardware will catch up and local is the future. For the average person who is sharing there privacy data out willy nilly all the time without much regard, i.e. most people, it makes no sense right now to go local vs. API / subscription given the price differential.
in 10 years your 10 year old Mac will almost certainly be a relic for running cutting edge local models
What am I missing
For example one of the projects is a web app that's processing user input, making AI suggestions, generating reports, doing ongoing observability, and running batch processing overnight.
Claude currently does these via API pricing, not Claude Ultra personal.
yes, but you pay the Ultra plan, that's the whole point, isn't it? Let's be honest also - qwen3.8:27b-mlx is nowhere near Sonnet, both in size and cap, and if you do $10k a week of usage, you should know that.
I've tried it out on a 512GB dram server with 2*3090s and it works really quite well. Draws enough power to cost something similar to Luna, though.
I don't think any of these self hosted setups are a good deal when you look at the NPV of the capex plus the power costs, but if you already own the hardware it can be okay or even a slight cost savings.
https://llama.app/
Note that it is under the ggml-org. So that's at least not a third-party taking advantage of llama.cpp
With the clean landing page URLs, you just don't know. So GitHub is probably the best source to link
https://github.com/ggml-org/llama.cpp/discussions/23875
I have the same reflex as you, especially something hosted on a .app TLD, I instinctively think it's a copy of something else.
You can always check here on HN as well to get a sense of its authenticity: https://news.ycombinator.com/item?id=49267928
That you can't configure the models independently is a glaring oversight. The alt-space to enter the chat window (at least on Windows) is awful and with no way to disable it I've resorted to just using the app as an easier interface to their downloader.
It does have a nice, clean UI and it doesn't hide the models behind some opaque identifier.
Jev allows for numerous small judgments: Is this email important? Which program should handle this request? Is this operation risky? There's no need for large LLMs to slowly generate long paragraphs of text; all you need is a fast, structured result that returns the message.
Having a local Jev-like model in the operating system for quick decision-making, and then calling the larger model when deeper thinking is needed, would be very useful.
https://sleepingrobots.com/dreams/stop-using-ollama/
Do you know how big jev is? Decision models are small but the "smart" (aka useable) ones aren't that small.
dabbling with it in browsers but i expect it would answer the mail for you, if you find it accurate enough
I am super interested to see what the Apple silicon team can deliver when their full attention is turned to local LLM acceleration.
But the problem is a $20 ChatGPT/Claude subscription utterly trounces it in usability, user experience, and performance. By the time we get Opus 5.5 at home, we'll be on like Opus 7 or 8, and I'd bet Sonnet 7 or 8 will dust whatever can be run on the base MacBook of that time. It's fine if people think local 5.5 will be good enough, but it just seems like as AI keeps getting better, you'd want to use the better tooling - nobody has decided a 2010 MacBook was good enough when the M1 came out.
- As AI continues to improve, the gains will become increasingly incremental. This means that your local model will be almost identical in performance as the latest cloud version, for all but edge case problems.
- If your local model is good enough for your current needs, the only "tokens" you are chewing through are utility costs and asset depreciation. Relatively cheap. It is easy to overrun even 200 /month cloud models for serious AI use.
How much is "good enough" depends what we want it for.
Right now, the vision which was presented as a joke in (AFAICT more than one project all called) vibeOS seems like it could be viable with better local inference… but that likely needs a few more 9s of reliability even relative to current SOTA models, and we might even never get there if smaller local models always produce code which big hosted models can find vulnerabilities in.
Same if you want home inference to replace hiring a professional lawyer, architect, tutor, etc.: even though the AI has been getting passing grades in the law and medical exams since the early days, whoever gives out public liability insurance probably want to see more 9s of reliability before giving the OK.
Not with the tok/s I get. I'm on a 128GB M4 Max laptop, and the latency + lack of parallelized sessions means you can't get anywhere near as much use vs. cloud models.
I ran OpenClaw in a VM on my mac a few months back, only using local models. It was painfully slow (no MLX) but what it created was on-par with Claude at that time too.
The models are certainly powerful enough, but the frontier models are more than just an LLM model in the back.
in 5yrs time running an M12 with a Bionic LLM Engine (or whatever they call it) may be good enough for a very very good AI experience. Enterprise / professionals will likely still pay for frontier models.
When comparing API prices and privacy concerns, local might win.
20tk/s is not unlimited when you have a lifespan that isn't infinite.
Not good for PII/PPI
For starters, they need to let me get rid of their AI stuff and free up the space. Apple aggressively pushing their AI down the throat of their users means that they suck at it but trying to make it happen using their muscles in other areas.
Just like people figured out how to make their Android TV not suck, it suggests that some time it the future people can make their OS not suck and this will make macOS irrelevant if Apple doesn't fix it first. Unfortunately for Apple, they operate in a system where they must keep growing their numbers.
Such a great company, its a shame that they couldn't figure out this AI stuff. Fingers crossed that this tool actually fixes that by just giving up and let people do whatever they want to do as efficiently as they can on the brilliant hardware Apple creates.
Especially in the modern era, the firmware/software side of macOS definitely doesn't seem like a priority.
This seems like the main way it would differentiate itself over existing solutions like LMStudio etc.
https://exolabs.net
Although this might be the shortest timeline as-yet that Apple has "Sherlock'd" 3rd party apps
https://en.wikipedia.org/wiki/Sherlock_(software)
So this is interesting, but it will likely be an independent product rather than part of the core operating system.
If all of this were easy, I would happily invest in new dedicated hardware to run it. This could be a full-blown Mac or it could be a souped up HomePod-type device, loaded with RAM. Better yet, make it a revitalized Matter-enabled Airport!
They are going to sell sure 10,000$ and you won’t need anything else for the rest of your life (if you are over 90).
Btw, llama.cpp with llama-swap ain’t that hard to configure if you have access to a potential LLM and have 5h of your life available to that task.
I also want something that integrates super easily with my iPhone and other devices, and hopefully Apple will make it possible to use my server as an intermediate fallback between my iPhone and their cloud models.
1. privacy (w.r.t. personal data, human agency, IP, whatever) – this absolutely is the most crucial.
2. if the needs are absolutely sufficed with local model(s) runnable on a super-expensive mac with a whole lot of RAM (not less than triple digit GBs usually) and the equivalent cost on API/subscription would be at least few times (say >=2-3x?) factoring in mac repair/maintainence/etc (yep, that does happen)
There's a 3rd case thoguh – the hobbylist case, which, imho and in my anecdotal evidence, is the majority of local-model-chasing outside of enterprise (which is usually not hobbyist to begin with).
So there of couse are three legit use-cases.
PS. Having said that, at this point, any machine you can't control 100% or very close to 100% cannot be said to be 100% or close to 100% private. So without getting into debates of whether Apple is the bastion of privacy or not (esp. they way they have been going about and their software competence, or lack thereof, leave a lot to be desired), or whether we would rather slide down to whataboutism, you can think about that yourself. I had to add this because these days running local models has become synonymous with "if not mac then what" and it might as well have merit, or not.)
Another bonus: Here in Germany a huge chunk of the hardware cost can be deducted from the tax bill.
Let the market decide.
Seems like both enterprises and individual users are switching to local models.
To my surprise, people are willing to pay for privacy.
I know a total of zero and individuals or companies using local inference for their workhorse inference.
Local models are just not up to most tasks for now at least.
I don’t find it reasonable at all. Subsidized Subscriptions or api for cheaper models, is the best value.
But the future of AI is so uncertain, regarding model sizes. I don’t think making huge hardware investments is reasonable for individuals.
If you buy your own hardware, then after those four years you still have that hardware, and it likely still holds significant value. Plus you know the local model you're running today won't change or suddenly degrade in four months, let alone four years. Whereas after four years of paying subscriptions and API costs, you have literally nothing.
That statement made sense ten years ago, easily. Less now, though.
GPUs are holding value longer, for obvious reasons. But even a 5 year old PC or server will be out of warranty, full of NLA components, and will get pennies on the dollar of its original cost on the salvage market. Most businesses will have fully depreciated them and maybe expect to sell them for enough to cover the costs of disposal.
There are ways to salvage old machines even when there is 0 support left/available.
There is no ZDR at that price.
I would not let a non-local AI have access to my financial or health data.
https://github.com/pdparchitect/noodle
Running local models is already extremely easy.
I have a suspicion this app will be a way to add a too many gigabytes to the mac and of course like the Chess.app there will be no way to get rid of it. There are excellent cli apps/GUI apps like this https://github.com/ddalcu/mlx-serve - they are both cli and gui – and even its gui surprisingly nimble (I use this, but I am not related to the project). I am yet to try this https://github.com/ggml-org/Llama-macOS but I've seen only good reviews of it.
I also do not think Apple is doing it for the users who won't explore around. I can't wait to get off this operating system. Next time a friend travels to the continent I will explore getting a Framework laptop via them.
Their customer base includes many non-tech people who don’t want open a terminal window or even know of what a “GitHub” is. And they probably would not trust it as much as an app build by Apple.
I agree it’s easy to run locally (although I do so on Linux), but what’s easy for the HN bubble and easy for the rest of population is not the same.
LLMs with <30B parameter models seem like the sweet spot. I would rather focus on multiple tiny LLMs that are tuned to specific tasks (SQL queries, finance/accounting, backend/frontend dev, etc.).
For larger models, a $10-40 ish Neuralwatt/Opencode Go or any similar subscription goes so far for the average user that it is ridiculous. We are still in the "youth" era of agents. There are many patterns that work well with smaller LLMs. Or with a big-small LLM combination.
My context:
I own the tiny 16GB M4 Mac Mini and I use LLMs (coding agents) to build software and a few of my products use LLMs directly. Full-time user of LLMs, do not read or write code manually. I run the tiny Qwen series (<10B params) sometimes but a couple $20 subscriptions (Claude, Neuralwatt) take care of my full-time agent usage.
How far away that is, or whether it will ever happen, I don't know. I agree though that the tooling is still so young it's hard to say what shape this type of computing will look like and therefore what kinds of resources will be in-demand.
Same context as yourself. I run 8 - 12Bish models locally on a 24GB M4 Macbook Air and also have a couple subscriptions (OpenCode Go, Mistral Pro) for access to DeepSeek etc. to power through yucky big bloated codebases at work.
https://openrouter.ai/blog/announcements/csam-screening/
There was a task manager which was given context of the tech stack so it could split the incoming requests. Then branch out the tasks to appropriate agents. Combine the generated code - this was a file/module/import manager.
The other way is let tiny models (again I would use agents for different use cases) do the busy work - tool calling, finding evidence, etc. I usually setup agents to re-write tool call history and create fresh API requests without using multi-turn chat with tool call history.
I saw this a while ago which shows small models and focuses on the ones that make the least (or no) wrong tool calls and it got me intrigued on the possibilities in this realm, especially for lower end devices. https://github.com/MikeVeerman/tool-calling-benchmark
I understand that we’re talking about local inference with an Apple inference engine for Apple Silicon uniform memory. And I know it’s a stretch of an analogy. But somehow I’ve grown skeptical of Apple’s AI capabilities. Not to say Microsoft’s or Google’s weren’t disappointing.
Pi has a subagents package to enable in its harness
They desperately need to fix that.
It SHOULD be totally possible. But it fights you.
It’s too bad I cannot trust it to put it in my rack.
Lots of things pop up and can’t be dismissed any other way than though mouse/keyboard on the display.
OS updated and wants to tell you it worked? No command line way to get rid of that. Program wants to do something and one of those system security prompts pops up (“BBEdit wants to access your Documents folder”)? Same problem.
You can set it to auto login and auto update and grant permissions and everything.
And then, one day, it will stop responding and you’ll have to hook it up and log in to see some pointless dialog that just wanted someone to click “OK”. And until you do no work gets done.
I think it is a great joy to run most things locally, and still occasionally use the best commercial models when local will not cut it.
In my case it reached the recursive self improvement stage a few weeks ago. It feels like the early days of personal computing in the era of DOS and Apple II.
The hardware is already there. The only limit is product imagination.
Of course Apple will not offer this.
Claris?? Ok, this sounds like it's just someone's personal project. Something like this that was actually going to ship would be in a different org.
https://www.pacifict.com/Story/
If true, it is an astounding story. That said, I'm happy to see that Apple ships a graphing calculator with macOS 27 (albeit, a different one). I may not use it much these days, but I have fond memories of it when I was in university.
I use oMLX btw, on 32GB URAM, running Hermes with Qwen 3.6 @ 128k context window.
I realize I am a smalltimer but for general day to day sensitive agentic stuff, this is the entry point.
its built just for qwen, healthy competition on tokens/sec
Hermes runs my personal to-do, manages 2 calendars, triages forwarded bills via it's own email address, orchestrates my docker container fleet. It also tends to a partly botched llm-wiki, that is built on Obsidian.
they have 128k - 256k context windows now, subagents use the same weights loaded in memory so you have spawn many subagents at the same time just like Claude Code, and the tokens/sec has is like 150-200
I just do different projects based on its complexity or liability or its moat
It’s the “year of the Linux desktop” meme all over again. Any day now.
- From a happy iPhone Duo user
https://en.wikipedia.org/wiki/FileMaker
so you can control and monitor what the whole setup is doing inside and outside the box.
Even better would be a peer to peer model hosting hardware pooling system but that’s probably too much to ask and would expose Apple to liability issues in some jurisdictions.
If Apple were willing to eat some margin on RAM they could use the present RAM bubble to gain ground in the hardware market too. Financially you could call it buying market share.
... Looks like I picked the wrong week to buy parts for a linux-based inference box.
Compute & storage were cheap, so renting them was expensive for many applications.
Inference is expensive. Just getting started is 4-5 figures. Why not rent it for pennies.