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Apple caught off guard by AI demand for Mac Mini and Mac Studio

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201–210 of 630 posts

Re: Apple caught off guard by AI demand for Mac Mini and Mac Studio

#201

Earlier quoted context omitted.

> it seems really far off from the kind of experience even a basic $20/month subscription gets me. The $20/month subs are much stronger than the local models you can run, even with how far local models have advanced lately. The appeal of local models is that the data never leaves your network so you can feel safer putting sensitive content into it. It also feels “free” to use when you’ve already paid for the hardware…

I don't think it is really about "sensitive", but basically about any content you put in. Why would you give corporations your reasoning (data on how you interact with AI, how you "talk" etc.). All of this is private, but not necessarily sensitive. You never know what is happening with this data. They might say they don't log it or don't sell it, then few years later you'll find it all online or read a book that has…

Although in this use case, it's likely because GPT guided you to write the same story as somebody else. Talking with an LLM about an idea is a great way to make it more predictable and homogenized. If you're fixing a bike or writing software, this is usually a good thing.

Re: Apple caught off guard by AI demand for Mac Mini and Mac Studio

#203

Earlier quoted context omitted.

A new base model mac mini is $900. That is 45 month of Gemini. Gemini 4.7 Flash will give better OCR results that Qwen or GLM w/ 10GB.

That doesn't help with the not wanting to send confidential information to a cloud though. No amount of cost savings can negate that.

[deleted]

Re: Apple caught off guard by AI demand for Mac Mini and Mac Studio

#204

Earlier quoted context omitted.

It also takes some load off the AI data centers. IDK if that might be a concern for Apple or their AI partners.

It worsens the supply crunch, no? A unit you use sparingly vs that memory going into a GPU that serves many more people.

What supply crunch? Tons of RAM available for purchase. It's just expensive. That there is a "supply crunch" is made up to benefit from Trump administration not giving a shit how big corps operate

There's cloud hosts out there with unused compute. Wasted cycles are all over businesses running unused cloud apps and subscribed to services they don't use.

Still need a local computer to access the cloud; so a barely used gadget still exists. And this creates duplication of effort; we built RAM for servers AND the edge devices.

Seems redundant when tech nerds and corporations are really the only people that care.

And all that data in the web is meaningless yet we create a supply crunch storing it in servers.

This an out of touch nickel and dime perspective given the big picture to say nothing of the mess of strip mining and manufacturing pipelines that go into every screw, wire, and such

Re: Apple caught off guard by AI demand for Mac Mini and Mac Studio

#205
post #68

I’m curious to know if these local AI setups are legitimately useful compared to cloud. I’ve struggled a lot to get something useful out of the hardware I have. I realize I’m somewhat limited (16GB RX 9070), but still, it seems really far off from the kind of experience even a basic $20/month subscription gets me. Any tips anyone might have are appreciated! I’d love to be local first and would be willing to buy hardw…

>I realize I’m somewhat limited (16GB RTX 9070), but still, it seems really far off from the kind of experience even a basic $20/month subscription gets me. I just ordered a new Mac Studio M5 Max 128GB $5899 ($6400 with tax) to be able to run the bigger "consumer size" models in the 70B parameter range (~96 GB). That said, I have no illusions that this expensive setup with a Qwen Flash coding LLM will be comparable t…

It not only about it being an expensive setup (or not), and also other considerations:

- There's no guarantee of the $20/month service, and it likely has some limits compared to dedicated hardware token wise.

- Model are becoming more and more efficient, in many cases an M1 Max Mac Studio is still capable with 32 GB. 128 GB ram may not be the necessary baseline.

- Folks may think they want to only have a general model running locally (it's the comparable after all from the cloud providers), but we have to remember if the tasks we're trying to do ultimately are more specific than general and if there's space for the smaller models to do that.

Re: Apple caught off guard by AI demand for Mac Mini and Mac Studio

#206
I hope Apple does not gain some exclusive enterprise tier for hardware. Part of what I love about them is that everything is available to consumers. A lowly home user can buy the exact same 256 (or 512) gigabytes of memory in a Mac from Apple, as long as they have a couple dozen thousand dollars to spare. I'd be really sad to lose that.

Re: Apple caught off guard by AI demand for Mac Mini and Mac Studio

#207

Earlier quoted context omitted.

I was looking at $10k Mac Studio with M5 Ultra and 256 GB for local experiments, but then struggled to find what really good modern model I can fit into it. Yes, it can run a good dense 27B at Q8 with plenty of context, but what beyond that? IIUC, some Deepseek flash variants at Q4 are also feasible, but I am not sure if the quality will be good. They also don’t run that fast, like about 30 t/s So if I stay within 35…

I feel like for localAI t/s is less of an issue. Just make a PRD and run a ralph loop. For big slogging projects like reverse engineering, or converting a codebase to a new language it actually doesn't matter if it takes a day or seven days.

Yeah this is my experience. My 24GB 3090 + 64GB RAM takes a couple hours to crank out some code with largest Gemma 4 and Qwen3.8 models it can run

But in the meantime I get dishes done, vacuum, flip laundry... etc etc

Frontier models also seem in such a rush to emit anything they produce a mess that needs steering all day anyway

While I have not tested it, it feels like my local setup going slower is better at producing code that works the first time as its not trying to look fast for marketing sake

Re: Apple caught off guard by AI demand for Mac Mini and Mac Studio

#208
post #202

Classic monopoly move: Control the user base, then control hardware. Any decent always-on local LLM setup with Apple devices will have to compete with these behemoths now. Great.

> Classic monopoly move: Control the user base, then control hardware

Classic monopoly move by who?

Apple created MLX as an open source framework to allow users to run any open model locally.

Re: Apple caught off guard by AI demand for Mac Mini and Mac Studio

#209

Earlier quoted context omitted.

> it seems really far off from the kind of experience even a basic $20/month subscription gets me. The $20/month subs are much stronger than the local models you can run, even with how far local models have advanced lately. The appeal of local models is that the data never leaves your network so you can feel safer putting sensitive content into it. It also feels “free” to use when you’ve already paid for the hardware…

There are a few use cases that are (somewhat) surprisingly unsuited for cloud providers: - translations: cloud providers can bowdlerize (censor) bad words/content; also, if you want to do a translation for personal use of copyrighted materials, cloud providers may block it - image generation: generating drawings with a style that even just resembles a copyrighted one (ie. Disney) may be blocked by cloud providers - f…

What about a light but bulky AI job, like batch processing 50GB of files? I'm currently doing it on my used Macbook M1 Max 64gb, and it's chugging through it for the cost of electricity (free with my solar).

Re: Apple caught off guard by AI demand for Mac Mini and Mac Studio

#210
post #70
post #14

It's fun to see that even an extremely large company can find unexpected product market fit [0]. Per this article, "The company reportedly did not possess an engineering team dedicated to business customers or staff focused on developer relations, and lacked an enterprise AI strategy." That sounds insane in retrospect, but I think there's just inherent uncertainty in what people actually need and will use things for.…

You should listen to the podcast Acquired, specifically Nvidia and then Jensen Huang. They basically lucked into AI. Some researcher was using Nvidia gaming cards, and reached out to them about questions on CUDA. That email eventually turned them into a trillion dollar question.

In 2006. The next 20 years of cuda support weren't luck, as anyone trying to use AMD will know.
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