Apple keeps pushing AI industry forward with more open-source models

Google, Meta, Microsoft, Mistral and tons of other companies, both American and Chinese, are making open models and all of those are better than Apple's models, yet this site is saying that the famously proprietary supporting company is doing anything that would let them steer a field where they are the worst at. 

Meanwhile, Apple's LLM can't even say who Obama is. 
https://www.reddit.com/r/singularity/comments/1ck55ag/apples_open_elm_model_is_fast_but_it_isnt_very/?rdt=32852

Max_truth said:

Meanwhile, Apple's LLM can't even say who Obama is. 

Is Apple's model designed to be small enough to run natively on an iPhone? Are all the other models you mentioned small enough to run on an iPhone? (It's a sincere question; I don't know the answer. It sounds like you are comparing Apples to Oranges.)

22july2013 said:

Is Apple's model designed to be small enough to run natively on an iPhone? Are all the other models you mentioned small enough to run on an iPhone? (It's a sincere question; I don't know the answer. It sounds like you are comparing Apples to Oranges.)

Max_Troll isn't a good source of accurate information, so let me answer that one for you: Apple's models are designed to be as much on-device as possible, but of course the whole of human experience and knowledge isn't going to fit, so some tasks will be quickly handed to Apple's Private Cloud Compute online if needed.

For queries that involve specialized knowledge (like medical or legal advice, as examples, or other specialty areas), Apple will offer to send your query privately to OpenAI for an answer, but that requires your permission each time its needed. OpenAI doesn't get to collect your data, or train itself on your queries.

For more about how this all works, I'd suggest watching the "Apple Intelligence" video on Apple's YouTube channel rather than the entire keynote.

All that said, this article is about LLM and dataset models Apple is offering the wider AI community, not the specific models it will use on any of its own products. Apple has figured out how to create models that are modest in size AND use less computing power than the offerings from other companies, so it is offering those compression techniques and computing algorithms to the wider community.

chasm said:

22july2013 said:

Is Apple's model designed to be small enough to run natively on an iPhone? Are all the other models you mentioned small enough to run on an iPhone? (It's a sincere question; I don't know the answer. It sounds like you are comparing Apples to Oranges.)

Max_Troll isn't a good source of accurate information, so let me answer that one for you: Apple's models are designed to be as much on-device as possible, but of course the whole of human experience and knowledge isn't going to fit, so some tasks will be quickly handed to Apple's Private Cloud Compute online if needed.

For queries that involve specialized knowledge (like medical or legal advice, as examples, or other specialty areas), Apple will offer to send your query privately to OpenAI for an answer, but that requires your permission each time its needed. OpenAI doesn't get to collect your data, or train itself on your queries.

For more about how this all works, I'd suggest watching the "Apple Intelligence" video on Apple's YouTube channel rather than the entire keynote.

All that said, this article is about LLM and dataset models Apple is offering the wider AI community, not the specific models it will use on any of its own products. Apple has figured out how to create models that are modest in size AND use less computing power than the offerings from other companies, so it is offering those compression techniques and computing algorithms to the wider community.

That's a fair stab at an answer but, to be fair, claims in the article like this are off the mark:

"Apple's ability to create incredibly compact yet powerful AI models is unequaled in the industry."

There is a huge amount of research going into tiny LLM's and it seems new advances come out every week. Open source or not, and many are specifically tailored to specific areas or languages. Apple is unlikely to challenge native Chinese models for the Chinese language. And what about Arabic? 

When I say 'huge' I mean it's very difficult to know exactly what might appear and keep track of it all. 

Earbuds can make great use of NLP and everything related to voice biometrics, bone, conduction, audio processing etc. Little more is needed there. 

Then this:

"In debuting both Apple Intelligence and Private Cloud Compute at its WWDC conference in June, the company silenced critics who had claimed that Apple was behind the industry on artificial intelligence applications in its devices"

The critics were simply pointing out reality. No equivalent shipping product from Apple was available. That remains the case today and will remain the case until something actually ships. Sometime late this year on a small range of models and well into next year for the rest of what was announced.

To all intents and purposes 'Apple Intelligence' was more akin to a placeholder at WWDC to generate buzz and let people know what's coming.

That's fine but we still have to wait to see what eventually comes out of the pipe and how it performs. 

The more the better IMO but the 'industry' isn't slacking and is actually shipping. 

chasm said:

22july2013 said:

Is Apple's model designed to be small enough to run natively on an iPhone? Are all the other models you mentioned small enough to run on an iPhone? (It's a sincere question; I don't know the answer. It sounds like you are comparing Apples to Oranges.)

Max_Troll isn't a good source of accurate information, so let me answer that one for you: Thanks. To a degree I was disagreeing with Max_truth, but sometimes when I write posts I try to write them so politely that the person reading it doesn't even realize I'm disagreeing. I'm trying to make them defend the weaknesses in their arguments without them even knowing that's what I'm asking them to do. I noticed that he didn't answer.