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Apple Intelligence Foundation Language Models Tech Report 2025

machinelearning.apple.com

121–130 of 210 posts

Re: Apple Intelligence Foundation Language Models Tech Report 2025

#121
post #89

Earlier quoted context omitted.

I think it is entirely morally consistent to provide alt text for accessibility even if you personally dislike it being used to train AI models.

It's fine if you want to, but I think they should consider that basically nobody is reading it. If it was important for society, photo apps would prompt you to embed it in the image like EXIF. Computer vision is getting good enough to generate it; it has to be, because real-world objects don't have alt text.

Why would photo apps do what's "important for society"?

Annotating photos takes time/effort, and I could totally imagine photo apps being resistant to prompting their users for that, some of which would undoubtedly find it annoying, and many more confusing.

Yet I don't think that one can conclude from that that annotations aren't helpful/important to vision impaired users (at least until very recently, i.e. before the widespread availability of high quality automatic image annotations).

In other words, the primary user base of photo editors isn't the set of people that would most benefit from it, which is probably why we started seeing "alt text nudging" first appear on social media, which has both producer and consumer in mind (at least more than photo editors).

Re: Apple Intelligence Foundation Language Models Tech Report 2025

#122
post #67
post #61

Earlier quoted context omitted.

Uncharitable. Robots.txt is already the understood mechanism for getting robots to avoid scraping a website.

People often use specific user agents in there, which is hard if you don't know what the user agents are in advance!

That seems like a potentially very useful addition to the robots.txt "standard": Crawler categories.

Wanting to disallow LLM training (or optionally only that of closed-weight models), but encouraging search indexing or even LLM retrieval in response to user queries, seems popular enough.

Re: Apple Intelligence Foundation Language Models Tech Report 2025

#123
post #67

Earlier quoted context omitted.

People often use specific user agents in there, which is hard if you don't know what the user agents are in advance!

If you're using a specific user agent, then you're saying "I want this specific user agent to follow this rule, and not any others." Don't be surprised when a new bot does what you say! If you don't want any bots reading something, use a wildcard.

Yes, but given the lack of generic "robot types" (e.g. "allow algorithmic search crawlers, allow archival, deny LLM training crawlers"), neither opt-in nor opt-out seems like a particularly great option in an age where new crawlers are appearing rapidly (and often, such as here, are announced only after the fact).

Re: Apple Intelligence Foundation Language Models Tech Report 2025

#124

Despite all the “Apple is evil” or “Apple is behind” (because they don’t do evil). Well, what they made with the Foundation Model is great. The fact that they build a system within the Swift language that allows you to specify structured data models (structs) to be used like any other model in a modern programming language, and you actually get back generated data in that format is great. Unlike a lot of other AIs wh…

How do you think their implementation works under the hood? I'm almost certain it's also just a variant of "structured outputs", which many inference providers or LLM libraries have long supported.

Re: Apple Intelligence Foundation Language Models Tech Report 2025

#125

> We believe in training our models using diverse and high-quality data. This includes data that we’ve licensed from publishers, curated from publicly available or open- sourced datasets, and publicly available information crawled by our web-crawler, Applebot. > 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 remo…

Respect actions, not words and PR.

Re: Apple Intelligence Foundation Language Models Tech Report 2025

#126

Earlier quoted context omitted.

"You haven't contorted your comically simple query enough to make the brittle tool work. Throw the chicken bones better next time."

It’s been this way for over a decade. If someone hasn’t figured it out by now, that’s kind of on them. I’m not even sure why those two things would be asked as a single question. It seems like a very unnatural way to pose those two questions. Most humans would trip on that, especially if it was asked verbally.

> It seems like a very unnatural way to pose those two questions. Most humans would trip on that

I'd assume GP only gave an example. As a pretty frequent user, I can unfortunately only confirm that Siri trips over almost every multi-part question.

This would be forgivable if there weren't multiple voice-based AI consumer products available that can handle these kinds of requests perfectly.

Re: Apple Intelligence Foundation Language Models Tech Report 2025

#127
post #75

All I can say is, I asked Siri today (verbatim): What is 75 degrees fahrenheit in celsius, and what is 85 degrees in fahrenheit — and it offered a web search about fahrenheit. The "and" completely disabled its most basic ability to do metric conversions. 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-d…

Your usage of Siri today (probably on an old version of iOS) frankly has nothing to do with the article we are discussing. Sorry to say this but it is going to take time. Comparing the performance of a chatgpt running in a big data center with a model running locally on a phone device... give it a few years.

> Your usage of Siri today (probably on an old version of iOS) frankly has nothing to do with the article we are discussing.

Yes, but isn't that infuriating? The technology exits! It even exists, as evidenced by this article, in the same company that provides Siri!

At least I feel that way every time I interact with it – or for that matter my Google Home speaker, ironically made and operated by the company that invented transformer networks.

Re: Apple Intelligence Foundation Language Models Tech Report 2025

#128
post #75

Earlier quoted context omitted.

Your usage of Siri today (probably on an old version of iOS) frankly has nothing to do with the article we are discussing. Sorry to say this but it is going to take time. Comparing the performance of a chatgpt running in a big data center with a model running locally on a phone device... give it a few years.

People have been giving Siri a few years for a decade now. Siri used to run in a data center (and still does for older hardware and things like HomePods) and it has never supported compound queries. Siri needs to be taken out back and shot. The problem with “upgrading” it is the pull to maintain backwards compatibility for every little thing Siri did, which leads them to try and incorporate existing Siri functionalit…

Those little things have been broken for a while now, it's best to bite the bullet and integrate LLM to Siri now.

Re: Apple Intelligence Foundation Language Models Tech Report 2025

#129
post #75

Earlier quoted context omitted.

Your usage of Siri today (probably on an old version of iOS) frankly has nothing to do with the article we are discussing. Sorry to say this but it is going to take time. Comparing the performance of a chatgpt running in a big data center with a model running locally on a phone device... give it a few years.

People have been giving Siri a few years for a decade now. Siri used to run in a data center (and still does for older hardware and things like HomePods) and it has never supported compound queries. Siri needs to be taken out back and shot. The problem with “upgrading” it is the pull to maintain backwards compatibility for every little thing Siri did, which leads them to try and incorporate existing Siri functionalit…

As a user, I'd gladly opt into a slightly less deeply integrated Siri that understands what I want from it.

Build a crude router in front of it, if you must, or give it access to "the old Siri" as a tool it can call, and let the LLM decide whether to return its own or a Siri-generated response!

I bet even smaller LLMs would be able to figure out, given a user input and Siri response pair, whether the request was resonably answered or whether the model itself could do better or at least explain that the request is out of capabilities for now.

Re: Apple Intelligence Foundation Language Models Tech Report 2025

#130

> We believe in training our models using diverse and high-quality data. This includes data that we’ve licensed from publishers, curated from publicly available or open- sourced datasets, and publicly available information crawled by our web-crawler, Applebot. > 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 remo…

> Using our web crawling strategy, we sourced pairs of images with corresponding alt-texts. 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.

> 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.

How did you come to the conclusion that those two groups overlap so significantly?

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