The Interview Question That Tells Me Everything (medium.com)
1 points by jensenbox 6m ago 0 comments
Running Linux on my Amiga 4000 (sandervanderburg.blogspot.com)
2 points by doener 47m ago 0 comments
Apple Intelligence Foundation Language Models Tech Report 2025
154 2bit 93 7/17/2025, 6:09:59 PM machinelearning.apple.com ↗
> We do not use our users’ private personal data or user interactions when training our foundation models. Additionally, we take steps to apply filters to remove certain categories of personally identifiable information and to exclude profanity and unsafe material.
> Further, we continue to follow best practices for ethical web crawling, including following widely-adopted robots.txt protocols to allow web publishers to opt out of their content being used to train Apple’s generative foundation models. Web publishers have fine-grained controls over which pages Applebot can see and how they are used while still appearing in search results within Siri and Spotlight.
Respect.
https://www.bloomberg.com/news/articles/2024-06-12/apple-to-...
Also the bigger problem is, you can't train a good model with smaller data. The model would be subpar.
- Famous Dead Person
Robots.txt is already the understood mechanism for getting robots to avoid scraping a website.
An issue for anti-AI people, as seen on Bluesky, is that they're often "insisting you write alt text for all images" people as well. But this is probably the main use for alt text at this point, so they're essentially doing annotation work for free.
> Apple has since confirmed in a statement provided to Ars that the US federal government "prohibited" the company "from sharing any information,"
Well partially generated content streaming thing is great and I haven't seen it anywhere else.
(I'm pretty sure this is actually what drove Microsoft Sydney insane.)
Reasoning models can do better at this, because they can write out a good freeform output and then do another pass to transform it.
So, it's nice to see Apple is doing research and talking about it, but we're out here waiting, still waiting, for anything useful to make of it all on our thousand-dollar devices that literally connect us to the world and contain our entire life data. It's what I would've expected from one of the most valuable companies in the world.
Err, what? As a native English speaker human that's a pretty confusing question to me, too!
"As of 2022, there were about 400 million native speakers of English. Including people who speak English as a second language, estimates of the total number of Anglophones vary from 1.5 billion to 2 billion."
Second, all popular models I tested did well with that query, including Gemini on Android (aka "ok Google"), except Apple's.
https://en.m.wikipedia.org/wiki/English-speaking_world
Probably wouldn't have made a difference but the second half of that statement isn't exactly clear. 85 degrees what?
I also think when you're chaining these two separate calculations together you get a problem when it comes to displaying the results.
So yeah, Apple is way behind on this stuff.
Why give this to developers if you haven’t been able to get Siri to use it yet? Does it not work or something? I guess we’ll find out when devs start trying to make stuff
What exactly are you referring to? Models do run on iPhone and there are features that take advantage of it, today.
The AI stuff with photography sure, but that’s more like machine learning.
The photo touch up thing is… useable? Sometimes?
What is it you’ve been so impressed with?
Probably Apple is trying to distill the models so they can run on your phone locally. Remember, most, if not all, of Siri is running on your device. There's no round trip whatsoever for voice processing.
Also, for larger models, there will be throwaway VMs per request, so building that infra takes time.
Running on device is also risky because cycle limitations will make it seem dumb in comparison.
My son (he's 11 years old now and fairly skilled with all the main AI tools, eg chatgpt, gemini, etc) and I retry her every month or so, and this past time we just laughed. Can't handle basic questions - hears the question wrong, starts, stops, takes us to some random ass webpage, etc, etc.
"She's so jacked up!" he said.
Apple needs to get this under control and figured out, stat!
And this is after they made very big claims with Apple Intelligence last year, when they had everyone fooled.
This is like watching a train-wreck in slow motion.
Yes, this is in fact what people want. Apple is the biggest company in the world (don’t quibble this y’all, you know what I mean) and should be able to deliver this experience. And sure, if they could do it on device that would be aces, but that’s not an item on the menu, and customers seem fine with web-based things like ChatGPT for now. To act like Apple is doing anything other than fumbling right now is cope.
I don’t really understand why Apple has to provide a ChatGPT product, baked directly into their software. Why on earth would Apple want to get involved in the race to the bottom for the cheapest LLMs? Apple doesn’t produce commodity products, they package commodities into something much more unique that gives them a real competitive advantage, so people are willing to pay a premium for the Apple’s product, rather than just buying the cheapest commodity equivalent.
There is no point Apple just delivering an LLM. OpenAI, Anthropic, Google etc already do that, and Apple is never going to get into the pay-per-call API service they all offer. Delivering AI experiences using on-device only compute, that’s something OpenAI, Anthropic and Google can’t build, which means Apple can easily charge an premium for it, assuming they build it.
It's hard to be like "uhhh privacy" when you send all requests to a remote server where they're stored in clear text for god knows how long.
As of right now, there is no way to run big LLMs in a privacy preserving manner. It just doesn't exist. You can't E2EE encrypt these services, because the compute is done on the server, so it has to decrypt it.
There are some services which will randomize your instance and things like that, but that kind of defeats the a big part of what makes LLMs useful, context. Until we can run these models locally, there's no way to get around the privacy nightmare aspects of it.
The people running large models want to charge a monthly fee for that.
I'm fine with having a free model that runs on device without slurping up my data.
With my history encrypted in the cloud, and the trust that Apple has built around privacy ... I think they're going to come out alright.
This is the first time in 10+ years I've seen Apple so far on the back foot. They usually launch category defining products that are so far ahead of the competition, even by the time they work through the 'drawbacks' in the first versions of them they are still far ahead. OS X, the iPhone and the iPad were all like that. They are still way ahead of the competition on Apple Silicon as well.
I am not very confident on their on device strategy at least in the short to medium term. Nearly all their devices do not have enough RAM and even if they did SLMs are very far behind what users "know" as AI - even the free ChatGPT plan is leap years ahead of the best 3B param on device model. Maybe there will be huge efficiency gains.
Private cloud is used AFIAK for virtually 0 use cases so far. Perhaps it will be more interesting longer term but not very useful at the moment given the lack of a suitable (ie: non Chinese), large (>500b param) model. They would also struggle to scale it if they roll it out to billions of iOS devices especially if they put features that use a lot of tokens.
Then they've got OpenAI/Gemini/Anthropic via API. But this completely goes against all their private cloud messaging and gives those providers enormous potential control over Apple, which is not a position Apple usually finds itself in. It will also be extremely expensive to pay someone per token for OS level features for billions of iOS/Mac devices and unless they can recoup this via some sort of subscription will hit services margins badly.
To me its clear the future of "OS" is going to involve a lot of agentic tool calling. These require good models, with large context windows and a lot of tokens - this will definitely not work on device. Indeed this is exactly what the Siri vapourware demo was.
I'm sure they can potentially get to a great UX (though these missteps are making me question this). But having such a core feature outsourced does not leave them in a good position.
Applications using Apple's foundation models can seamlessly switch from on-device models to Private Compute Cloud.
Research is already showing the use of LLMs for people's most intimate relationship and medical issues. The usual suspects will try to monetize that, which why Private Cloud Compute is a thing from the jump.
> Then they've got OpenAI/Gemini/Anthropic via API. But this completely goes against all their private cloud messaging
Using ChatGPT via Siri today, no personally identifying information is shared with OpenAI and those prompts aren't used for training. I suspect Apple would want something similar for Google, Anthropic, etc.
At some point, there will be the inevitable enshitification of AI platforms to recoup the billions VCs have invested, which means ads, which won't happen to Apple users using foundation model-based apps.
> Nearly all their devices do not have enough RAM and
Every Apple Silicon Mac (going back to the M1 in 2020) can run Apple Intelligence. 8 GB RAM is all they need. Every iPhone 15 Pro, Pro Max and the entire 16 line can all run Apple Intelligence.
Flagship iPhone 17 models are expected to come with 12 GB of RAM and all current Mac models come with at least 16 GB.
Apple sells over 200 million iPhones in a given year.
There's no doubt Apple stumbled out of the gate regarding AI; these are early days. They can't be counted out.
It's already accessible using Shortcuts, even to non-developers "iOS 26 Shortcuts + Apple Intelligence is POWERFUL " (Youtube) [1].
[1]: https://youtu.be/Msde-lZwOxg?si=KJqTgtWjpdNDxneh
There's a WWDC video "Meet the Foundation Models Framework" [1].
[1]: https://developer.apple.com/videos/play/wwdc2025/286
https://share.icloud.com/photos/018AYAPEm06ALXciiJAsLGyuA
https://share.icloud.com/photos/0f9IzuYQwmhLIcUIhIuDiudFw
The above took like 3 seconds to generate. That little box that says On-device can be flipped between On-device, Private Cloud Compute, and ChatGPT.
Their LLM uses the ANE sipping battery and leaves the GPU available.
Most of his team are former Google brain so GDM knows who is good.
This is the first time that millions of people will actually download and run a model on their own devices.
The question is… will Apple be constantly tweaking these models, or only during OS upgrades?
I for one really like local software. Call me old-fashioned, but I enjoy when a company doesn’t switch up software anytime on the server, or phone the results home all the time in order to extract more profits from their collective users.
Certainly when new updates are released--going from macOS 26 to 26.1).
They can probably push model updates between releases if necessary.