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Apple Foundation Models

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Re: Apple Foundation Models

#201

Post by Danox »

mcintyre1994 wrote: post #60

I think this is just Apple planning for their on-device models getting better, which makes sense given they have access to Gemini now. If developers use this for all their code calling an external LLM, then as Apple's model becomes more capable and covers more use cases it'll be easy to switch to it at individual call sites. That'll give apps better UX and save developers money on a bill that Apple doesn't get a cut…

UX is just another word for ecosystem building, which is what Apple does best in comparison to their competition and also doesn’t hurt to do hardware to go along with it. Microsoft and Nvidia aren’t teaming up for nothing.

Re: Apple Foundation Models

#202

Post by Danox »

criddell wrote: post #80
mcintyre1994 wrote: post #60

I think this is just Apple planning for their on-device models getting better, which makes sense given they have access to Gemini now. If developers use this for all their code calling an external LLM, then as Apple's model becomes more capable and covers more use cases it'll be easy to switch to it at individual call sites. That'll give apps better UX and save developers money on a bill that Apple doesn't get a cut…

How does using Gemini lead to better on-device models?

Gemini is just a stopgap like using Intel processors or Qualcomm modems.

Re: Apple Foundation Models

#203

Post by jmalicki »

sealeck wrote: post #185
CuriouslyC wrote: post #144

Earlier quoted context omitted.

If all you have is the starting point and the finishing point, the lack of the path taken from one point to another limits your ability to train models that can efficiently recreate the work, and increases its cost enough that it's possible the US labs can progress capabilities faster than Chinese labs can distill that behavior.

> lack of the path taken from one point to another limits your ability to train models that can efficiently recreate the work Isn’t this the problem inference (training) a model is designed to solve :)))

It is!

And it's a hard problem.

What's an easier form of training is being able to see the intermediate results and train to imitate them.

Re: Apple Foundation Models

#204

Post by mr_toad »

matwood wrote: post #61
klausa wrote: post #55

Earlier quoted context omitted.

How is this Apple keeping control of the UX?

The betas of the next OS's include a Siri AI chatbot, and the AI features are built into various parts of the OS. A user has no idea what model is powering any of it - Apple controls the UX.

I’ll be curious to see if they make the models accessible to Shortcuts, like they do with the current models.

Re: Apple Foundation Models

#205

Post by drivebyhooting »

HDThoreaun wrote: post #116
tarcon wrote: post #15

Earlier quoted context omitted.

Apple has some clever mechanics to protect user data. I had to work with App tracking stuff lately and their approach to keeping user details private with anonymized cohorts (SKAN, Differential Privacy) before reporting tracking events to third party platforms was surprisingly well thought out. There is value in having them in your loop if you care about privacy.

My read of the ATT stuff is basically that it forced all the apps to use meta ad tracking because they’re the only ones who figured out how to serve relevant ads despite it.

Figured out = do the forbidden PII join anyway with their partners in “clean rooms”.

Re: Apple Foundation Models

#206

Post by jdgoesmarching »

GeekyBear wrote: post #169

This isn't Claude specific. Developers can also write apps that call Google's server based Gemini models. > At WWDC, Apple announced that it's opening its Foundation Models framework to third-party cloud model providers. Starting with iOS 27, macOS 27, iPadOS 27, visionOS 27 and watchOS 27, model providers can implement the new public LanguageModel protocol to provide a common interface for model inference. We've mad…

The important part is Apple rebranding “OpenAI-compatible API” to “language model protocol” and I think we should all rally around this immediately before we’re cursed with that awful tongue twister.

Re: Apple Foundation Models

#207

Post by computerex »

embedding-shape wrote: post #82
alecco wrote: post #79

Earlier quoted context omitted.

In spite of their deeper pockets, massive datacenters, colosal amounts of user data, and hundreds of thousands of top developers, even Amazon, Meta, Microsoft, and Google are well behind. I think Evans is completely wrong. There are only 2 truly frontier models. (at least for now). And Anthropic seems to be leaving OpenAI behind so there might be only 1 in the near future. (which is scary/dangerous)

> I think Evans is completely wrong. There are only 2 truly frontier models. (at least for now). And Anthropic seems to be leaving OpenAI behind so there might be only 1 in the near future. (which is scary/dangerous) Truly fascinating ecosystem and community in general, as experiences differ so wildly. Anthropic's models seems far behind OpenAI to me, especially when you get into "Pro" territory, and there doesn't se…

For HPC/ai work opus blows gpt away, it’s no competition.

Re: Apple Foundation Models

#208

Post by HDThoreaun »

drivebyhooting wrote: post #205
HDThoreaun wrote: post #116

Earlier quoted context omitted.

My read of the ATT stuff is basically that it forced all the apps to use meta ad tracking because they’re the only ones who figured out how to serve relevant ads despite it.

Figured out = do the forbidden PII join anyway with their partners in “clean rooms”.

Right, the lesson here is that if you make rules with exploitable loopholes youre probably only going to end up strengthening malicious actors who are willing to exploit loopholes.

Re: Apple Foundation Models

#209

Post by bigyabai »

godzillabrennus wrote: post #132
FuriouslyAdrift wrote: post #125

Earlier quoted context omitted.

I've found most of the frontier coding models require somewhere between 300GB to 1TB to run with full capabilities.

If only we could buy 1TB of unified memory in a Mac for $1k-$2k in total hardware costs. Apple would basically be able to extinguish the entirety of the market cap for Nvidia, OpenAI, Anthropic, and others all at once. In 10 years, I hope my MacBook Pro can run today's frontier models and has 1TB of unified Memory.

> Apple would basically be able to extinguish the entirety of the market cap for Nvidia

I don't think you understand why people buy Nvidia hardware if you're beating the "just add more dual channel DDR, bro" drum. Apple wouldn't even be able to extinguish AMD with a product like that, it's all slow memory being fed into a raster-first GPU architecture.

Re: Apple Foundation Models

#210

Post by bigyabai »

coldtea wrote: post #70
saagarjha wrote: post #44

Earlier quoted context omitted.

Notably good models are not on that list.

Yeah, that totally makes them merely assemblers then /s

Apple Silicon is broadly unused for LLM training. Arguably, Apple isn't even helping to assemble real-world AI models, just the thin client hardware.
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